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SUMMARY:COST NanoSpace - AI in Astrochemistry Training School 2025
DESCRIPTION:Training School Materials \nMotivation and overview\nArtificial intelligence (AI) and machine learning (ML) have suddenly emerged as game-changing tools across diverse scientific disciplines. This includes astronomy -including observational astronomy\, laboratory astrophysics and astrobiology- and chemistry -where machine learning interatomic potentials are already solidly established tools for atomistic modeling of materials and molecules. At the intersection between chemistry and astronomy\, astrochemistry is posed to similarly benefit from the opportunities for accelerated scientific discovery enabled by AI. The COST NanoSpace AI in Astrochemistry Training School 2025 aims to furnish our community with the necessary background to get started to utilize these tools\, by bringing together world-renowned experts to Aalto University in Southern Finland. The School will provide COST NanoSpace action participants and young researchers with specialized knowledge and address the urgent need for training on AI tools in astrochemistry. \nProgram\nThe School will provide a starting point for astrochemistry researchers interested in adopting AI tools for their research. We will cover the basics as well as showcase various examples of how AI has been successfully used to tackle research problems in chemistry and astrochemistry. \n\n\n\n\n\nTuesday 5 August\nWednesday 6 August\nThursday 7 August\nFriday 8 August\n\n\nTime\nTopic\nTrainer\nTopic\nTrainer\nTopic\nTrainer\nTopic\nTrainer\n\n\n9:00\nRegistration\nGaussian Processes and Regressors\nMads-Peter V. Christiansen\nML for Radio Interferometry\nRyan Loomis\n\n\n\n\n9:30\nInterpretable ML Techniques for Astrochemistry\nJohannes Heyl\n\n\n10:00\nNanoSpace and AI in Astrochemistry TS Overview\nAníbal García-Hernández &\nEdward Goldwyn\n\n\n10:30\nCoffee break\nCoffee break\nCoffee break\nCoffee break\n\n\n11:00\nFundamentals of ML\nMiguel Caro\nML for Interatomic Potentials\nRina Ibragimova\nML Binding Energies of Astrochemical Molecules\nJohannes Heyl\nExercise Session: ML for Interatomic Potentials\nRina Ibragimova\n\n\n11:30\n\n\n12:00\n\n\n12:30\nLunch\nLunch\nLunch\nLunch\n\n\n13:00\n\n\n13:30\n\n\n14:00\nBasics of Neural Networks\nXabier Pérez Couto\nExercise Session: Bayesian Optimization with\nGaussian Processes\nMads-Peter V.\nChristiansen\nNeural Networks for Astrochemistry\nLorenzo Branca\nIntelligent Crystal and Molecular Structure Search Algorithms\nIsabelle Braems\n\n\n14:30\n\n\n15:00\nExercise Session: Neural Networks I\nXabier Pérez Couto\nExercise Session: ML in Astrochemistry I\nLorenzo Branca\n\n\n15:30\nTea break\nTea break\nExercise Session: ML in Astrochemistry II\nLorenzo Branca\nTea break\n\n\n16:00\nExercise Session: Neural Networks II\nXabier Pérez Couto\nAtomistic Modelling for Radiation\nDamage in Space\nAndrea Sand\nTea break\nExercise Session (continuation)\nMads-Peter V.\nChristiansen\n\n\n16:30\nPoster pitches\nExcursion to Suomenlinna\nConclussions & goodbye\n\n\n17:00\nML for Chemical Intuition\nBrett McGuire\n\n\n\n17:30\n\n\n18:00\n\n\n18:30\n\n\n\n\n19:00\nDinner in Suomenlinna (paid by participants; participation optional)\n\n\n\n\nImportant dates\n\n8 April 2025 – First Announcement\n8 April 2025 – Registration starts\n30 May 2025 – Registration deadline\n15 June 2025 – Announcement of the final (and backup) lists of registered participants as well as those eligible for COST financial support\n5-8 August 2025 – NanoSpace AI in Astrochemistry Training School at Aalto University’s School of Chemical Engineering’s main building\n\nTrainers and Organizing Committee\nThe School is organized by COST NanoSpace in collaboration with Aalto University: \n\nD. Aníbal García Hernández\, COST NanoSpace Action Chair (IAC\, Spain)\nBrett A. McGuire\, COST NanoSpace member (MIT\, USA)\nMiguel A. Caro\, local organizer & COST NanoSpace member (Aalto\, Finland)\nRina Ibragimova\, local organizer & COST NanoSpace member (Aalto\, Finland)\nDora Javor\, local organizer (Aalto\, Finland)\n\nFor questions pertaining to the local matters of the School\, please get in touch with Miguel Caro (miguel.caro@aalto.fi). \nTrainers and topics\nThe program will include sessions on the following topics as well as series of practical exercises: \n\nFundamentals of ML – Miguel Caro\, Aalto Univ.\, Finland\nBasics of Neural Networks – Xabier Pérez Couto\, A Coruña Univ.\, Spain\nGaussian Processes and Regressors – Mads-Peter V. Christiansen\, Aarhus\nUniv.\, Denmark\nIntelligent Molecular Structure Search Algorithms – Isabelle Braems\,\nIMN-CNRS\, France\nML for Chemical Intuition – Brett McGuire\, MIT\, USA\nML for Radio Interferometry – Ryan Loomis\, NRAO\, USA\nML Binding Energies of Astrochemically Molecules and/or Interpretable ML Techniques for Astrochemistry – Johannes Heyl\, UCL\, UK\nNeural Networks for Astrochem – Lorenzo Branca\, Heidelberg Univ.\,\nGermany\nML for Protoplanetary Disk Chemistry and/or ML for Star Formation\nChemistry – (to be confirmed)\nML for Interatomic Potentials – Rina Ibragimova\, Aalto Univ.\, Finland\nML for Radiation Damage in Space – Andrea Sand\, Aalto Univ.\, Finland\n\nTrainees\nThis is a list of the participants (in addition to the organizers and trainers) who will take part in the School. \n\n\n\nName\nInstitution\n\n\nAlexia Anguera González\nInstitute of Spaces Sciences\, University of Barcelona\n\n\nRansel Barzaga Guzman\nIUDEA\, La Laguna University\n\n\nChiara Beldì\nUniversity of Edinburgh\n\n\nLise Boitard-Crépeau\nIPAG\, UGA\n\n\nMaren Brauner\nInstituto de Astrofísica de Canarias\, IAC\n\n\nJakub Bulička\nFaculty of Mathematics and Physics\, Charles University\n\n\nTadeus Carl\nChalmers University of Technology\n\n\nLorenzo Maria Casazza\nUniversity of Naples Federico II\n\n\nAyşe Ceylin Çelebi\nUniversity of Naples Federico II\n\n\nLouey Charradi\nHigher National Engineering School of Tunis\n\n\nGaëtan Clément\nInstitut des sciences moléculaires d’Orsay\, ISMO\n\n\nLorenzo Demaria\nOpen University\n\n\nPooja Devi\nCharles University\, FZU\n\n\nJosé Jairo Díaz Luis\nObservatorio Astronómico Nacional\, OAN-IGN\n\n\nElavenil Ganesan\nInstitute of physical chemistry polish academy of sciences\n\n\nGabriella Di Genova\nUniversity of Perugia\n\n\nRossella Di Giovanni\nScuola Superiore Meridionale\, Scuola Normale Superiore\n\n\nAmélie Godard Palluet\nCentro de Astrobiología\, CAB\n\n\nRoya Hamedani Golshan\nUniversity of Cologne\n\n\nYoussef Guermassi\nFaculty of sciences of Bizerte\n\n\nAlžběta Horynová\nInstitute of Physics of the Czech Academy of Sciences\n\n\nLukas Hrubcik\nUniversity of Chemistry and Technology Prague\n\n\nTeresa Huertas Roldán\nInstituto de Astrofísica de Canarias\, IAC\n\n\nMunavvar Husain\nUniversity of Warsaw\n\n\nGabriel Jaimes Illanes\nCentro de Astrobiología\, CAB\n\n\nStanka Jerosimic\nUniversity of Belgrade\, Faculty of Physical Chemistry\n\n\nDeniz Kacan\nPurdue University\n\n\nAlexandros Kyriazis\nUniversitat Autònoma de Barcelona\n\n\nRosell Martín\nUniversity of Extremadura\n\n\nSergio Mato Domínguez\nUniversity of Valladolid\n\n\nAndrés Megías\nCentro de Astrobiología\, CAB\n\n\nEnrico Di Micco\nUniversity of Naples Federico II\n\n\nMilan Milovanovic\nFaculty of Physical Chemistry\, University of Belgrade\n\n\nAlene Seyoum Mitiku\nEthiopian Space Science and Geospatial Institute\, SSGI\n\n\nVeronika Mitrokhina\nTartu Observatory\, University of Tartu\n\n\nDanial Mohammadi\nKU Leuven\, Stockholm University\n\n\nTanish Nandre\nUniversity of Bonn\n\n\nDevismita Panda\nLaboratoire d’Astrophysique de Bordeaux\, University of Bordeaux\n\n\nTheodore Pellegrin\nMax Planck Institute for Extraterrestrial Physics\n\n\nSergey Pyrlin\nCICECO – Aveiro Institute for Materials\, University of Aveiro\n\n\nW. M. C. Sameera\nChalmers University of Technology\n\n\nBethmini Senevirathne\nUniversity of Gothenburg\n\n\nMilan Sil\nInstitut de Planétologie et d’Astrophysique de Grenoble\n\n\nJelena Lubura Stošić\nFaculty of Technology\, University of Novi Sad\n\n\nMaxime Tanious\nIPAG\, IRAM\n\n\nDimitar Trifonov\nInstitute of Electronics\, Bulgarian Academy of Sciences\n\n\nMeenu Upadhyay\nUniversity of Basel\n\n\nLuis Velilla-Prieto\nCSIC – Institute of Fundamental Physics\n\n\nVojtech Vozda\nInstitute of Physics\, Czech Academy of Sciences\n\n\nOerd Xhemollari\nUniversity of Cologne\n\n\nJaime Yepes de Paz\nComplutense University of Madrid\n\n\n\nVenue\, transportation & accommodation\nVenue\n \nThe conference will take place in the main campus of Aalto University\, in the Helsinki metropolitan area. The venue is the Aalto University’s School of Chemical Engineering’s main building\, Kemistintie 1\, Espoo\, 02150 Finland. \nGetting there & around\nAalto University is very well connected within the Helsinki metro area. The Otaniemi campus can be reached via metro (“Aalto University” stop) and the light rail (“Maari”\, “Aalto-yliopisto” and “Otaranta” stops\, from west to east). Please visit the website of HSL\, the company operating the public transport system in the Helsinki metro area. This includes buses\, the metro\, trains\, downtown trams\, the light rail\, and some municipal ferry services (e.g.\, to the Suomenlinna fortress island). Public transport in the Helsinki metro area is safe\, clean and reliable. The easiest way to use the public transport system is to download the HSL app on your phone. \nThe Aalto University campus can be reached from Helsinki airport\, e.g.\, by combining the train with the metro (changing at Helsinki’s Central Railway Station). Non-collective public transport options like taxis are also available\, including popular apps like Uber; these are significantly pricier than collective transportations but might be more convenient depending on the situation (e.g.\, if you are in a hurry to reach the airport). \nAccommodation\nAalto University is located on the Otaniemi campus. Otaniemi is a district of the city of Espoo\, located within the Helsinki metropolitan area. There are various on-campus accommodation options in Otaniemi\, for instance the Radisson Blu Espoo hotel. Since the Otanimi campus is connected to Helsinki by metro\, and the commuting time is ~15 minutes from Helsinki city center\, it is entirely possible to stay in Helsinki and commute every day to the School. This opens the door to a wider variety of accommodation options in terms of quality and price. Two options for on-campus accommodation are: \n\nRadisson Blu Espoo (from ~100 EUR/night)\nHeymo 1 by Sokos (from ~85 EUR/night)\n\nFor accommodation options in Helsinki\, popular aggregators like Booking.com offer a “map-view” of the city and their user ratings are usually a good indicator of quality and value. If you opt for booking accommodation in Helsinki city center and commuting every day to the Aalto campus\, we recommend that you reserve a hotel within walking distance of a metro station for convenience\, e.g.\, stations “Ruoholahti”\, “Kamppi”\, “Central Railway Station”\, etc. \nRegistration\nThe School will be in person with attendance limited to 50-55 trainees and with priority given to PhD students and young researchers\, who are strongly encouraged to participate. There is no registration fee and the NanoSpace COST Action will provide financial support (i.e.\, reimbursement after the event\, covering full or partial travel\, accomodation\, and subsistence costs)* for a significant number of participants (at least ~20-25)\, with high priority to those with a primary affiliation in an institution located in an Inclusiveness Target Country (ITC)/Near Neighbour Country (NNC) participating in the Action**. \nThe information requested in the registration form below will be used to select the final list of registered participants as well as those eligible for financial support\, which will be notified in advance of the Training School (i.e.\, by mid-June 2025). The attendees are expected to arrange their own travel and accommodation ( see Venue and Accomodation above for more information ). \nTo apply to take part in the School\, please go to the registration website (deadline 30 May 2025): https://link.webropolsurveys.com/EP/88F312F3CB3ED0FF \n*The applicants eligible for financial support (i.e.\, reimbursement after the event) are requested to consult the COST Annotated Rules for information about COST rules and procedures for Training Schools. The financial support does not necessarily cover all expenses related to participating in the Training School and they are contributions to the overall travel\, accommodation and meal expenses of the trainee. \n**Please consult the specific ITC and NNC countries and any COST special measures taken regarding the participation of researchers/innovators from some countries in the Annex I of Level A Country and Organisations. \nAbout & contact\nThe AI in Astrochemistry Training School 2025 is part of the official activities of the COST Action NanoSpace\, chaired by D. Aníbal García Hernández (IAC\, Spain) and supported by COST (European Cooperation in Science and Technology). The main aim and objective of the COST Action NanoSpace (“Carbon molecular nanostructures in space”; CA21126) is to advance the fundamental understanding of the physics and chemistry of cosmic carbon nanomaterials (nanocarbons; nC) and their relevance in non-terrestrial environments by promoting the interdisciplinary combination of state-of-the-art astronomical\, laboratory\, and theoretical studies\, among others. The main Action scientific challenges are attacked via an interdisciplinary approach\, combining the expertise from a wide range of disciplines like observational astronomy\, laboratory astrophysics\, astrobiology\, theoretical chemistry\, synthetic chemistry\, molecular reaction dynamics\, material science\, spectroscopy\, graph theory\, and data science (AI\, big data). Researchers and innovators from all these fields are thus welcome to participate in the Action as Working Group members\, applying here. Read more about NanoSpace. \nAs part of the core mission of COST NanoSpace\, many events and activitites are organized every year in the framework of the Action\, including Training Schools that provide high-level education on research topics and methods relevant to the objectives of the project. Events are organized by COST NanoSpace in collaboration with a local organizer. The AI in Astrochemistry Training School 2025 is hosted by the Aalto University Department of Chemistry and Materials Science. For more information about COST NanoSpace and the School\, please contact the Action Chair (agarcia@iac.es); for practical matters about the school and Aalto University\, please contact Miguel Caro (miguel.caro@aalto.fi). \nSponsors\nThe AI in Astrochemistry Training School 2025 is made possible thanks to the support by COST (European Cooperation in Science & Technology). COST is a funding agency for research and innovation networks. COST Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research\, career and innovation. \nLocal support by the Department of Chemistry and Materials Science of Aalto University is also gratefully acknowledged. \n \n \n \n \nToday 08-08-2025 you use ruffle!
URL:https://ocamm.fi/event/cost-nanospace-ai-in-astrochemistry-training-school-2025/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:School
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2025/03/astrochemistry_ai_logo.png
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
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DTSTART;TZID=UTC:20250602T130000
DTEND;TZID=UTC:20250603T120000
DTSTAMP:20260417T134744
CREATED:20250324T094535Z
LAST-MODIFIED:20250609T114232Z
UID:313-1748869200-1748952000@ocamm.fi
SUMMARY:Computational Chemistry Days 2025
DESCRIPTION:The Computational Chemistry Days is the main annual event of the computational chemists and materials scientists of Finland. The event has a well-established tradition and serves the purpose of bringing the national community together. Its role to keep researchers of different chemistry (and related) departments in Finnish universities in contact with one another cannot be overstated. This event showcases current trends in computational chemistry research\, enables kickstarting of collaborative efforts and allows emerging researchers to advertise their work to the national community. Topics vary widely and cover the thematic areas of computational chemistry rather comprehensively\, except for perhaps continuum modeling: organic and inorganic materials chemistry\, molecular modeling\, electrochemistry and electrocatalysis\, soft- and bio-materials modeling\, polymers\, etc. Methodologically\, atomistic modeling is usually best represented\, density functional theory being the most popular technique\, followed by force field simulations and\, more recently\, machine learning potentials. Coarse-grained models are also usually represented. Sampling techniques include molecular dynamics\, Monte Carlo\, enhanced sampling\, structure search algorithms\, transition-state theory\, etc. \nIn 2025\, the Department of Chemistry and Materials Science at Aalto University takes the baton from University of Jyväskylä\, which organized the 2024 edition\, and organizes the event jointly by the four computational groups that operate at the department. We will continue the tradition of giving the stage to researchers at all career levels. The event is informal and short\, although relatively large in size\, since it caters to (and aspires to gather) the whole Finnish community. Since this year we are back to the metro area\, and having a large local community present\, we estimate a particularly high attendance from across Finland. The event has short sessions and many breaks\, to foster networking. \nGroup picture at the CCD 2025.\nInvited speakers\n\nProf Fernanda Duarte\, University of Oxford (UK) \n\n\nProf Karoliina Honkala\, University of Jyväskylä \n\n\nProf Matti Javanainen\, Tampere University \n\n\nDr Konstantinos Konstantinou\, University of Turku \n\n\nDr Petra Vasko\, University of Helsinki \n\n\nDr Rasmus Kronberg\, CSC – IT Center for Science \n\nProgram\nDownload a PDF copy of the program. \nThe program starts on Monday 2 June 2025 after lunch (13:00) and ends on Tuesday 3 June before lunch (12:20). The whole event takes place at the Aalto University School of Chemical Engineering main building\, Kemistintie 1\, Espoo. The lecture hall A305 (Ke1) will hold all the oral presentations while the poster session and coffee breaks will take place just outside the lecture hall. The idea is to allow for train travel in the morning from the main Finnish cities to minimize the financial cost to participants of attending the conference (only one overnight hotel stay). \n\n\n\nMonday 2 June\nTuesday 3 June\n\n\n13:00 – 13:10\nWelcome speech by organizers\n9:00 – 9:40\nInvited: Fernanda Duarte (U. Oxford) – “Beyond static DFT: Modelling Chemical Reactions in Solution with MLIPs”\n\n\n13:10 – 13:40\nInvited: Matti Javanainen (U. Tampere) – “Molecular insights into the Sec61/TRAP translocon functions”\n9:40 – 10:10\nInvited: Konstantinos Konstatinou (U. Turku) – “Athermal bond-breaking pathways in amorphous phase-change memory materials”\n\n\n13:40 – 14:00\nContributed: Samuli Ollila (VTT) – “Towards a Quality-Evaluated Simulation Databank for Intrinsically Disordered Proteins”\n10:10 – 10:30\nContributed: Minttu Maria Karppinen (U. Jyväskylä) – “Probing lignin adsorption sites on pristine\, defective\, and doped MoS2 surfaces” Tigany Zarrouk (Aalto U.) – “Molecular Augmented Dynamics: Experimentally consistent atomic structures by design”\n\n\n14:00 – 14:20\nContributed: Arun Kumar Kanakati (U. Jyväskylä) – “Simulating Nuclear Quantum Effects in Electronic Strong Coupling”\n10:30 – 11:00\nCoffee break\n\n\n14:20 – 14:50\nCoffee break\n11:00 – 11:30\nInvited: Karoliina Honkala (U. Jyväskylä) – “Advanced DFT calculations for modelling electrocatalytic systems at constant potential”\n\n\n14:50 – 15:20\nInvited: Petra Vasko (U. Helsinki) – “On the Mechanisms of Transition Metal-Free Transformations”\n11:30 – 11:50\nContributed: Timo Weckman (U. Jyväskylä) –\n“Comparative study of metal porphyrins for CO2 reduction and cation effect”\n\n\n15:20 – 15:40\nContributed: Akseli Mansikkamäki (U. Oulu) – “Magnetic Properties and Unconventional Bonding in Organometallic Complexes of Lanthanides and Actinides”\n11:50 – 12:10\nContributed: Saara Sippola (U. Turku) – “Active Learning Structure Search Study of 17-Beta-Estradiol Adsorption on Graphene”\n\n\n15:40 – 16:00\nContributed: Kim Eklund (Aalto U.) – “Pyroelectric properties of ordered Pb[Zr0.5Ti0.5]O3“\n12:10 – 12:20\nClosing remarks and farewell\n\n\n16:00 – 16:20\nBreak\n\n\n\n\n16:20 – 16:50\nInvited: Rasmus Kronberg (CSC) – “Roihu supercomputer and other updates from CSC”\n\n\n\n\n16:50 – 17:10\nContributed: Mandira Das (U. Turku) – “Decoding Aerosol Surface Chemistry: Insights from XPS Spectra via DFT and Machine Learning”\n\n\n\n\n17:10 – 17:30\nContributed: Lauri Franzon (U. Helsinki) – “Discovering the elusive mechanism of accretion product formation from RO2 + RO2“\n\n\n\n\n17:30 – 19:00\nPoster session (snacks and refreshments served)\n\n\n\n\n\nPosters\n\n\n\n#\nDetails\n\n\n1\nDániel Nagy (U. Oulu) – “Single Molecular Magnets as Quantum Processors”\n\n\n2\nQian Wang (U. Helsinki) – “Changing aromatic properties through stacking”\n\n\n3\nHugo Åström (U. Helsinki) – “Atomic Confinement Potentials”\n\n\n4\nAtte Sillanpää (CSC) – “BioExcel-3 CoE supports the biomolecular simulation community on using HPC”\n\n\n5\nEfstathia Mantzari (Aalto U.) – “Computational studies on the conformational landscape of mussel and barnacle adhesive proteins”\n\n\n6\nArtem Glova (Aalto U.) – “Representation learning for glass transition detection in polymers using simulations”\n\n\n7\nTiia Jacklin (U. Oulu) – “Quantum-mechanical treatment of thermal effects on NMR of buckminsterfullerene: negative thermal expansion\, chemical shift and isotope shifts”\n\n\n8\nVivek Sharma (U. Helsinki) – “A histidine molecular switch in the proton pump of respiratory complex I”\n\n\n9\nFabio Priante (Aalto U.) – “Metadynamics Exploration of Fibronectin 10FNIII Unfolding Pathways”\n\n\n10\nFelix Eurasto (U. Helsinki) – “Machine Learning analysis of GPCR structural data reveals activity classes”\n\n\n11\nOssi Laurila (U. Oulu) – “Path integral molecular dynamics with machine learning models for quantum effects of C60“\n\n\n12\nIzabella Leszczyńska (Jerzy Haber Institute) – “Phase separation process in ternary polyelectrolyte mixtures”\n\n\n13\nLuukas Nikkanen (U. Helsinki) – “NEO calculations need uncontracted electronic basis set for quantum protons”\n\n\n14\nAmiel Abettan (U. Helsinki) – “Structural dynamics of mitochondrial supercomplexes”\n\n\n15\nRichard Jana (Aalto U.) – “Carbon nano tube growth on Fe nano particles”\n\n\n16\nKaveh Farshadfar (Aalto U.) – “Mechanistic Evaluation of the Gold-Catalyzed Heck-Like Reaction: Allylic Deprotonation as a Key Step”\n\n\n17\nYanzhou Wang (Aalto U.) – “Density dependence of thermal conductivity in nanoporous and amorphous carbon with machine-learned molecular dynamics”\n\n\n18\nWilin Julian Sari (U. Helsinki) – “Hydration Mechanisms of Ternary Complex Formation of Dimethyl Sulfide by Hydroxyl Radical via Hydrogen”\n\n\n19\nGabriel Debais (Aalto U.) – “A model for predicting polyelectrolyte self-assembly in solution: effects of pH\, salt concentration\, and mixing ratio”\n\n\n20\nTirthonkor Saikia (U. Helsinki) – “Multiwavelet-based density functional calculations with MRChem and LibXC”\n\n\n21\nMilan Kunnatholy Babu (U. Helsinki) – “NEO-DFT Study of Proton Transfer in DNA Base Pairs”\n\n\n22\nGabriela Wojtan (Jerzy Haber Institute) – “De novo design and molecular dynamics investigation of peptides with inducible β-hairpin conformation inspired by natural structural proteins”\n\n\n23\nAino Nyman (U. Helsinki) – “Structural analysis of mGluR reveals underlying activation mechanism”\n\n\n24\nMax Philipp Holl (Aalto U.) – “Modeling active patterns in electroferrofluids”\n\n\n25\nRinat Nasibullin (U. Helsinki) – “Predicting Intersystem Crossing Rate Constants of Alkoxy-Radical Pairs with Structure-Based Descriptors and Machine Learning”\n\n\n26\nAmir Mahdian (Aalto U.) – “Machine Learning Insights into the Influence of Substituents on Diels-Alder Reaction Kinetics”\n\n\n27\nEmna Cherni (U. Oulu) – “Quantum chemical analysis of electronic properties and structural stability of ansa-aminoborane derivatives”\n\n\n28\nPiotr Sobiecki (U. Oulu) – “Theoretical Study of f-block Single-Molecule Magnets”\n\n\n29\nOuail Zakary (U. Oulu) – “Local E(3)-Equivariant Neural Network Force Field for Modeling Host-Guest Interactions in Xenon-Based Porous Organic Cages”\n\n\n30\nDmitry Tolmachev (Aalto U.) – “Molecular mechanism of solvent dependency of polyelectrolyte complexes glass transition”\n\n\n31\nOndrej Krejci (U. Turku) – “Innovative Approaches to Semiconductor Surface Oxidation Studies Using Active Learning and MLIP”\n\n\n32\nIda Karppinen (U. Helsinki) – “The impact of unimolecular reactions on acyl peroxy radical initiated isoprene oxidation”\n\n\n33\nBhumi Arunkumar Baraiya (U. Jyväskylä) – “Elucidating the Role of Lewis Acid-Base Sites in Aldol Condensation over m-ZrO2(-212) surface”\n\n\n34\nImon Mandal (H.U. Jerusalem) – “Mechanisms of Atmospheric Reactions at Water Surfaces: Determined by Ab Initio Molecular Dynamics”\n\n\n35\nMaria Dimitrova (U. Helsinki) – “Magnetically induced nuclear currents in the torsional conformers of toluene”\n\n\n36\nMario Mäkinen (Aalto U.) – “The Growth Reaction Pathways of Zincone ALD/MLD Hybrid Thin Films: a DFT Study”\n\n\n37\nKourosh Hasheminejad (Aalto U.) – “Exploring odd-even effects in self-assembled monolayers via molecular dynamics”\n\n\n38\nSakshi Jha (Tampere U.) – “NO and NO2 reactions with oxygenated peroxy radicals lead to indistinguishable product compositions: Computational insights from cyclohexene oxidation in presence of NOx“\n\n\n39\nLuka SImsive (U. Helsinki) – “Proton transfer through the E channel of respiratory complex I probed by hybrid QM/MM MD simulations”\n\n\n\nVenue\nThe Computational Chemistry Days 2025 will take place in the main campus of Aalto University\, in the Helsinki metropolitan area. The conference venue is lecture hall 305 (Ke1) in the main building of the School of Chemical Engineering\, Kemistintie 1\, Espoo\, 02150 Finland. \nAalto University is very well connected within the Helsinki metro area. The Otaniemi campus can be reached via metro (“Aalto University” stop) and the light rail (“Maari”\, “Aalto-yliopisto” and “Otaranta” stops\, from west to east). Please visit the website of HSL\, the company operating the public transport system in the Helsinki metro area. This includes buses\, the metro\, trains\, downtown trams\, the light rail\, and some municipal ferry services (e.g.\, to the Suomenlinna fortress island). Public transport in the Helsinki metro area is safe\, clean and reliable. The easiest way to use the public transport system is to download the HSL app on your phone. \nThe Aalto University campus can be reached from Helsinki airport\, e.g.\, by combining the train with the metro (changing at Helsinki’s Central Railway Station). Non-collective public transport options like taxis are also available\, including popular apps like Uber; these are significantly pricier than collective transportations but might be more convenient depending on the situation (e.g.\, if you are in a hurry to reach the airport or train station). \nRegistration\nThe Computational Chemistry Days 2025 is open to all participants within the Finnish computational chemistry community and related fields. The event is free of charge thanks to the support from Aalto University’s Department of Chemistry and Materials Science and the CECAM-FI node. You can register to attend the event until 16 May 2025. To submit an abstract for a poster or oral presentation\, the deadline is 30 April 2025. All the presentations are in English. To register for the event\, please follow this link. Please note that the event has no registration fees but you or your institution needs to cover your travel expenses. \nOrganizers\nThe Computational Chemistry Days 2025 is jointly organized by the four computational chemistry groups at the Department of Chemistry and Materials Science of Aalto University\, led by Dr Miguel Caro (Data-driven Atomistic Simulation\, chair)\, Prof Antti Karttunen (Inorganic Materials Modelling)\, Prof Kari Laasonen (Computational Chemistry) and Prof Maria Sammalkopi (Soft Materials Modelling). \nSponsors\nThe Computational Chemistry Days 2025 are possible\, free of charge\, thanks to the generous support from Aalto University’s Department of Chemistry and Materials Science and the CECAM-FI node.
URL:https://ocamm.fi/event/computational-chemistry-days-2025/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Conference
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2025/03/banner.png
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250527T100000
DTEND;TZID=UTC:20250527T133000
DTSTAMP:20260417T134744
CREATED:20250519T105039Z
LAST-MODIFIED:20250519T105039Z
UID:384-1748340000-1748352600@ocamm.fi
SUMMARY:AI for Science: from molecules to materials
DESCRIPTION:The Aalto University House of AI organizes the first AI for Science event in the Otaniemi campus\, with the collaboration of OCAMM. The events serves to highlight the research carried out at Aalto at the interface between AI and the chemical sciences. For more information\, visit the official website of the event: https://www.aalto.fi/en/events/ai-4-science-from-molecules-to-materials
URL:https://ocamm.fi/event/ai-for-science-from-molecules-to-materials/
LOCATION:Undergraduate Center\, Otakaari 1\, Espoo\, Uusimaa\, 02150\, Finland
CATEGORIES:Networking,Seminar
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250507T131500
DTEND;TZID=UTC:20250507T140000
DTSTAMP:20260417T134744
CREATED:20250220T073202Z
LAST-MODIFIED:20250430T115351Z
UID:298-1746623700-1746626400@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: Albert Bartók (Warwick)
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 7 May 2025 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Albert Bartók\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nMaterials modelling across the scales \nAlbert P. Bartók \nSchool of Engineering and Department of Physics\, University of Warwick\, UK \nThe past two decades have seen a transformative change in atomistic modelling with the development of machine-learned interatomic potentials\, which allow quantum-accurate simulations at an affordable computational cost. While the formalism of these models has converged\, there still remain open questions about the optimal way to generate training databases as well as about the reliability of potentials. In this talk\, I will present our efforts to automatically generate atomic databases using a combination of active learning and advanced sampling methods and how the resulting potential results in exceptionally accurate potential energy surface for Mg at a pressure range of 0-600 GPa. I will also show how fast and accurate potentials can help us discover novel phenomena\, illustrated by our observation on how helium affects dislocation mobility in tungsten. Finally\, I will report how transfer learning may be used to fine-tune foundation models using a little amount of data\, resulting in accurate\, but application-specific potentials. \nAbout the speaker\nAlbert Bartók-Pártay is an Associate Professor at the University of Warwick. He earned his Ph.D. degree in physics from the University of Cambridge in 2010\, his research having been on developing interatomic potentials based on ab initio data using machine learning. He was a Junior Research Fellow at Magdalene College\, Cambridge\, and later a Leverhulme Early Career Fellow. Before taking up his current position\, he was a Research Scientist at the Science and Technology Facilities Council. His research focuses on developing theoretical and computational tools to understand atomistic processes.
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-albert-bartok/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2025/02/ABartokPartay.png
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250416T131500
DTEND;TZID=UTC:20250416T140000
DTSTAMP:20260417T134744
CREATED:20250220T073014Z
LAST-MODIFIED:20250414T112150Z
UID:296-1744809300-1744812000@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: Leonardo Espinosa (VTT)
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 16 April 2025 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Leonardo Espinosa\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nMachine Learning Across Industries: From Academia to Real Applications \nLeonardo A. Espinosa-Leal \nPrincipal Scientist\, ProperTune AI Team\, VTT\, Espoo\, Finland \nIt is not a novelty to hear that machine learning is everywhere. Since you wake up until you go to sleep\, your life and decisions are driven (and in some cases controlled) through the interaction with machine learning algorithms. Despite their ubiquitousness and the constant buzz about AI and the need for digitalization across industries\, it is very interesting that most ML projects in the sector (60% to 80%\, depending on the area) never reach the deployment phase. In this talk\, we will discuss\, using real (successful and unsuccessful) examples from some Finnish industry players\, how “AI” is presented in academic environments and how to address the gap between the academy and the industry. In addition\, a general view of VTT’s strategy for materials discovery\, including those concepts\, will be presented and discussed. \nAbout the speaker\nLeonardo holds a BSc in physics from the National University of Colombia\, a Master in Nanoscience\, and a PhD in Computational Materials Science from the University of the Basque Country in Spain (2013). He moved to Finland in 2013 as a postdoc at Aalto University and\, in 2016\, decided to switch his research interests towards the world of machine learning and artificial intelligence. He got a Research fellowship (2017) at Arcada University of Applied Sciences (Finland)\, then was appointed Senior lecturer in Big Data Analytics (2020) and later\, Principal lecturer in Technology (2023). He was the head of the Applied Artificial Intelligence Laboratory and the Degree Programme Director of the Master in Big Data Analytics at the same institution from 2022 until 2025. \nIn 2025\, Leonardo was appointed as Principal Scientist at VTT in the ProperTune AI team. Currently\, His main interest is (but not limited to) the intersection of AI\, Materials Science\, and Quantum computing.
URL:https://ocamm.fi/event/ai-in-chem-leonardo-espinosa-vtt/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250326T131500
DTEND;TZID=UTC:20250326T140000
DTSTAMP:20260417T134744
CREATED:20250220T072711Z
LAST-MODIFIED:20250325T091539Z
UID:293-1742994900-1742997600@ocamm.fi
SUMMARY:CANCELED: AI in CHEM Seminar Series: Erik Berg (Uppsala)
DESCRIPTION:Unfortunately\, this seminar has been canceled due to unforeseeable circumstances. \nThis talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 26 March 2025 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Erik Berg\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nA Self-driving Battery Research Lab \nJackie Yik\, Viktor Vanoppen\, Leiting Zhang\, Erik J. Berg \nDepartment of Chemistry\, Ångström Laboratory\, Uppsala University\, Box 538\, SE-751 21\, Uppsala\, Sweden \nThe need for efficient and sustainable energy storage solutions has never been greater. In our battery research lab\, we address this urgency by developing a self-driving battery electrolyte formulation and analysis platform. In my talk\, I will present a robotic setup dedicated to battery electrolyte formulation\, coin-cell assembly and electrochemical testing. The development trajectory of the setup is presented along with a discussion of the pros/cons of various robot configurations. The integration of an active learning cycle in form of multi-objective optimization to identify the most highly performing electrolytes is showcased. Failing experiments as a result of automation will also be exemplified. Finally\, the need to educate next-generation chemists in the field of automation and to standardize chemical instrumentation and testing protocols is highlighted. \nAbout the speaker\nErik J. Berg is since 2021 Professor of Chemistry at Uppsala University-Sweden. He holds a MSc Physics degree from TU Darmstadt-Germany\, an Engineering Physics degree from the Royal Institute of Technology-Sweden in 2007 and earned in 2012 a Ph.D. at Uppsala University. He joined the Paul Scherrer Institute\, Switzerland as post-doctoral fellow in 2012 where he later was also promoted to Group Leader in 2016\, awarded tenure in 2017\, before returning to Uppsala University in 2018. He is currently a Knut and Alice Wallenberg Academy Fellow and SSF Future Research Leader. Erik’s research focuses since >10 years on fundamental mechanistic understanding of the chemistry governing the performance of rechargeable batteries. His research team primarily develops and applies operando characterization techniques to study battery dis-/charge processes in real-time\, often in close collaboration with industrial funding partners. Recently\, significant effort is invested in automating the battery research process with the aim to accelerate the discovery of high-performing electrolytes
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-erik-berg-uppsala/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2025/02/erik_berg.jpeg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250312T131500
DTEND;TZID=UTC:20250312T140000
DTSTAMP:20260417T134744
CREATED:20250220T072504Z
LAST-MODIFIED:20250307T104449Z
UID:290-1741785300-1741788000@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: Erin Makara (VTT)
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 12 March 2025 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Erin Makara\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nML-Assisted Material Simulation and Exploration: Moving Past Symmetry \nErin Makara\, VTT \nSimulating asymmetrical and amorphous materials with diverse elemental compositions presents significant challenges due to their large system sizes and the inability to leverage symmetry-based simplifications. Conventional computational methods struggle to efficiently model these high-entropy materials\, however advances in machine-learned force fields (MLFFs) have provided a promising avenue for accelerating simulations while maintaining accuracy. This talk will discuss how ML-accelerated electronic and dynamic calculations enable the exploration of amorphous materials. It will discuss considerations and workflows for generating training data for the ML models\, as well as discussion on validity of the approach through the lens of accuracy and time. \nAbout the speaker\nErin Makara has found themselves at the crossroads of physics\, chemistry\, mathematics\, and computer science\, working towards advancing computational methods beyond their current limitations. They are currently a Research Scientist at Technical Research Centre of Finland VTT and a PhD student at Aalto University under the guidance of Dr. Anssi Laukkanen and Prof. Antti Karttunen. Erin holds a Master’s degree in Chemistry and is working alongside the PhD on a second Master’s degree in Machine Learning\, Data Science and Artifical Intellignece. Alongside research and studies\, they work to simulate various molecules and materials and predict their properties to aid in their team’s multiscale simulation effort.
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-erin-makara-vtt/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250226T131500
DTEND;TZID=UTC:20250226T140000
DTSTAMP:20260417T134744
CREATED:20250220T072132Z
LAST-MODIFIED:20250220T072132Z
UID:288-1740575700-1740578400@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: Drug Discovery with Heikki Käsnänen (Orion Pharma)
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 26 February 2025 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Heikki Käsnänen\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nTransforming Drug Discovery: From Computational Tools to Model-Driven Innovation \nHeikki Käsnänen\, Orion Pharma \nThe pharmaceutical industry is undergoing a paradigm shift in how computational methods and models are integrated into the drug discovery process. Historically\, these tools played a supportive yet impactful role\, assisting chemists and biologists in decision-making and innovation. Today\, advancements in predictive and generative AI/ML\, the scaling of physics-based methods\, and the emergence of active learning are propelling us toward a future of truly model-driven drug discovery. This talk will explore how virtual DMTA (Design\, Make\, Test\, Analyze) cycles\, accelerated by AI/ML\, are transforming R&D workflows\, enabling faster and more efficient exploration of chemical space. It will also discuss the challenges and opportunities in scaling physics-based methods for broader applicability and how active learning can enhance the adoption of slower but more accurate computational approaches. While the vision of fully model-driven drug discovery is not yet realized\, this transition marks an exciting new era for innovation and impact in the pharmaceutical industry. \nAbout the speaker\nDr. Heikki Käsnänen describes himself as a digital drug hunter\, working at the intersection of computation\, chemistry\, and biology. He currently leads a research group at Orion Pharma\, focusing on hit discovery and the application of computational chemistry and AI/ML methods in small molecule drug discovery. Heikki holds a Master’s degree in Pharmacy from the University of Kuopio and completed his PhD in Computational Medicinal Chemistry under the guidance of Professor Antti Poso. In 2011\, while finalizing his doctoral studies\, he was invited to join Orion\, where he has since gained over a decade of experience in small molecule drug discovery\, with a particular focus on oncology and pain targets. Since 2020\, Heikki has led the Molecular Prospecting and Modeling unit\, driving innovation and advancing model-driven discovery alongside a talented team of colleagues.
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-drug-discovery-with-heikki-kasnanen-orion-pharma/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250205T131500
DTEND;TZID=UTC:20250205T140000
DTSTAMP:20260417T134744
CREATED:20250203T115441Z
LAST-MODIFIED:20250203T115625Z
UID:283-1738761300-1738764000@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: High Performance Computing for science with Rasmus Kronberg
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 5 February 2025 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Rasmus Kronberg\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nHigh Performance Computing for science \nRasmus Kronberg\, CSC – IT Center for Science \nCSC is not a research organization\, meaning that we do not conduct research on our own. However\, as a state-owned special purpose company\, CSC has been tasked to support scientific computing in Finland by providing high-quality computing\, data management and support services for research\, education and innovation. Thus\, CSC operates in close collaboration with universities\, state research institutes and companies\, with our primary aim being to help researchers focus on science while we take care of the required computing infrastructure. In this talk\, I will present CSC’s activities as a key service provider in the field of computational science in Finland and Europe. In line with the scope of this seminar series\, I will in particular highlight the ways in which we support chemistry and AI\, including examples of related projects in which we are involved. These activities extend beyond simply providing the required computing infrastructure\, as our role in collaboration projects is often related to ensuring efficient implementation and deployment of software and workflows on cutting-edge HPC platforms. Enabling researchers to use our resources as efficiently as possible is also the most important driver of our everyday support services. \nAbout the speaker\nRasmus Kronberg works as an application specialist at CSC – IT Center for Science\, the high-performance computing (HPC) center of Finland. At CSC\, Rasmus focuses on supporting researchers and company R&D professionals in using the Finnish supercomputing infrastructure\, as well as the pan-European supercomputer LUMI. Rasmus has a doctorate in computational chemistry from Aalto University and has authored multiple scientific articles within the areas of computational electrochemistry and -catalysis.
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-high-performance-computing-for-science-with-rasmus-kronberg/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2025/02/1692120741905.jpeg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250121T100000
DTEND;TZID=UTC:20250121T110000
DTSTAMP:20260417T134744
CREATED:20250110T105843Z
LAST-MODIFIED:20250110T105843Z
UID:276-1737453600-1737457200@ocamm.fi
SUMMARY:Special seminar by Prof. Alexandre Tkatchenko
DESCRIPTION:Save the date! OCAMM presents a special seminar by Prof. Alexandre Tkatchenko from the University of Luxembourg\, who will talk about the role of AI in accelerating molecular simulations. This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 21 January 2025 @ 10:00 in lecture hall A304 (Ke2) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi to find out how AI can be leveraged to speed up quantum mechanical simulations of atoms and molecules! \nTitle \nRealizing Schrödinger’s dream with AI-enabled molecular simulations \nAbout the speaker \nAlexandre Tkatchenko is a professor at the Department of Physics and Materials Science (and head of this department since January 2020) at the University of Luxembourg\, where he holds a chair in Theoretical Chemical Physics composed of ~35 multidisciplinary scientists. Tkatchenko also holds a distinguished visiting professor position at the Technical University of Berlin. His group develops accurate and efficient first-principles computational and artificial intelligence models to study a wide range of complex materials\, aiming at qualitative understanding and quantitative prediction of their structural\, cohesive\, electronic\, and optical properties at the atomic scale and beyond. He has delivered more than 450 invited talks\, seminars\, and colloquia worldwide\, published 240 articles in prestigious journals (h-index of 89 with more than 45\,000 citations; Top 1% ISI highly cited researcher since 2018 until now)\, and serves on the editorial boards of four society journals: Science Advances (AAAS)\, Physical Review Letters (APS)\, Journal of Physical Chemistry Letters (ACS)\, and Chemical Science (RSC). Tkatchenko has received a number of awards\, including APS Fellow from the American Physical Society\, Fellow of the Royal Society of Chemistry\, Gerhard Ertl Young Investigator Award of the German Physical Society\, Dirac Medal from the World Association of Theoretical and Computational Chemists (WATOC)\, van der Waals prize from ICNI\, Feynman Prize for Nanotechnology from the Foresight Institute\, and five flagship grants from the European Research Council (ERC): a Starting Grant in 2011\, a Consolidator Grant in 2017\, an Advanced Grant in 2022\, and Proof-of-Concept Grants in 2020 and 2023. He is also a co-founder of Quastify GmbH – a start-up that combines quantum and statistical mechanics with machine learning for efficiently exploring chemical spaces.
URL:https://ocamm.fi/event/special-seminar-by-prof-alexandre-tkatchenko/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2025/01/deeplearn-tkatchenko.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20250115T131500
DTEND;TZID=UTC:20250115T140000
DTSTAMP:20260417T134744
CREATED:20250110T104214Z
LAST-MODIFIED:20250110T105327Z
UID:273-1736946900-1736949600@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: Lab Automation for Scattering Analysis with Andy Anker
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 15 January 2025 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Andy Anker\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nMachine learning experimental scattering data analysis: concept\, practice\, and a future with automated laboratories \nAndy S. Anker1\,2 \n\nDepartment of Energy\, Danish Technical University\, Denmark\, ansoan@dtu.dk\nDepartment of Chemistry\, University of Oxford\, United Kingdom\, andy.anker@chem.ox.ac.uk\n\nThe rapid growth of materials chemistry data has outpaced conventional data analysis and modelling methods\, which can require enormous manual effort. To effectively analyse this wealth of information\, we are using machine learning (ML) models trained on extensive datasets of physics-based simulations for analysis of experimental scattering data [1\,2]. Yet\, relying solely on a single experimental technique often fails to provide sufficient information for resolving complex material structures. To overcome these limitations\, we are integrating diverse datasets into unified ML pipelines. Building on these methodological advances\, we look towards developing automated laboratories capable of accelerating materials synthesis. \nReferences \n\nAndy S. Anker\, Keith T. Butler\, Raghavendra Selvan\, Kirsten M. Ø. Jensen\, Chemical Science 2024\, 48\, 14003–14019.\nEmil T. S. Kjær\, Andy S. Anker\, Marcus N. Weng\, Simon J. L. Billinge\, Raghavendra Selvan\, Kirsten M. Ø. Jensen\, Digital Discovery 2023\, 1\, 69–80.\n\nAbout the speaker\nSee Andy’s Github page for more info \nI have recently been awarded a 4 000 000 DKK (~ £500 000) postdoctoral grant to pursue an academic career in the interface of materials chemistry\, machine learning and robotics. Here\, I am building a self-driving laboratory for controlled synthesis of inorganic nanomaterials in collaboration with Prof. Tejs Vegge and the CAPeX center at Technical University of Denmark\, Assoc. Prof. Volker Deringer’s group at Oxford University and Prof. Kasper Støy’s group at the IT University of Copenhagen. In 2024+2025\, I am physically working from Oxford. \nI obtained my PhD in materials chemistry from the Nanostructure Group UPCH\, University of Copenhagen\, supervised by Assoc. Prof. Kirsten Marie Ørnsbjerg Jensen\, where my main interest was to study nanoparticles and structures in solution with Total X-ray Scattering with Pair Distribution Function (PDF) and Small-Angle X-ray Scattering (SAXS). I applied advanced computer modelling\, in Python\, to combine information of both the local order from PDF and the particle order from SAXS\, which overcome problems that the methods cannot overcome individually. During my career\, the research focus has converged towards developing machine learning (ML) methods to analyse chemical data; especially PDF & SAXS\, after I met Assistant Professor Raghavendra Selvan who I had collaborated with since 2019. I have furthermore spent 6 months during my PhD working at Rutherford Appleton Laboratory with Senior Lecturer Keith Tobias Butler and the Scientific Machine Learning Group to develop an general approach to match simulated and experimental data in materials chemistry. During the last period of my PhD\, I have especially focused on using generative models to analyse scattering-\, and spectroscopy data.
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-lab-automation-for-scattering-analysis-with-andy-anker/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2025/01/AndySAnker_Portraet-web-e1736506396902.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241211T101500
DTEND;TZID=UTC:20241211T110000
DTSTAMP:20260417T134744
CREATED:20241127T081836Z
LAST-MODIFIED:20241127T081836Z
UID:267-1733912100-1733914800@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: AI for the Energy Transition with Árpád Toldy
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 11 December 2024 @ 10:15-11:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n10:00-10:15. Setup and brief info for the registered students.\n10:15-11:00. Seminar by Árpád Toldy\, lecture hall A304.\n11:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nUsing AI to boost the Energy transition \nAs renewable fuels enter the market\, their blending with existing components must be understood to facilitate their integration into existing infrastructure. Borne out of this necessity\, the Digifuels project (a collaboration between Neste and Aalto’s Research Group of Energy Conversion and Systems) took on the task to build a robust fuel blend property prediction pipeline that could work with real refinery data. This seminar will share the key findings of Digifuels work package 1 – both in terms of science and of managing a successful industrial collaboration. In addition\, the seminar will briefly cover other data-driven efforts in the group related to future fuels. More on Digifuels: https://www.aalto.fi/en/news/collaboration-with-aalto-brings-significant-financial-benefits-to-neste. \nAbout the speaker\nÁrpád is a Project Specialist at Aalto University’s Research Group of Energy Conversion and Systems (Prof. Annukka Santasalo-Aarnio’s team) where he conducts and supervises a broad range of research related to future energy carriers. His endeavors into data-driven approaches include predicting fuel blend properties\, optimizing the production of green hydrogen\, and predicting new catalysts for the production of green fuels and chemicals. In addition\, Árpád is involved in experimental\, techno-economic and social acceptance studies of renewable fuels. He earned his PhD in Chemical and Pharmaceutical Engineering from Singapore-MIT Alliance and worked for 6 years in the pharmaceutical industry before joining Aalto.
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-ai-for-the-energy-transition-with-arpad-toldy/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20241127T131500
DTEND;TZID=Europe/Helsinki:20241127T140000
DTSTAMP:20260417T134744
CREATED:20241125T075043Z
LAST-MODIFIED:20241127T081310Z
UID:262-1732713300-1732716000@ocamm.fi
SUMMARY:AI in CHEM Seminar Series: Intro session with Miguel Caro
DESCRIPTION:This talk is part of the “AI and Machine Learning in Chemical Research and Industry” Seminar Series organized by the Aalto University School of Chemical Engineering. It is open to all members of the public. Registered students in course CHEM-E4190 can also obtain 1cr by attending the seminars and completing the assignments. \nDate and location\n\nWednesday 27 November 2024 @ 13:15-14:00\nA304 Ke2 lecture hall in the main building of the School of Chemical Engineering\, Kemistintie 1\, 02150 Espoo.\n\nAgenda\n\n13:00-13:15. Setup and brief info for the registered students.\n13:15-14:00. Seminar by Miguel Caro\, lecture hall A304.\n14:00-onwards. Coffee\, netwoking and mingling in the lobby adjacent to the lecture hall.\n\nSeminar info\nAchieving a new degree of realism in materials modeling with machine learning \nWe are in the middle of an AI revolution in all aspects of society. However\, machine learning had already been trending in chemistry and materials science for a few years before ChatGPT popularized the use of AI among the general public. After a brief introduction to the field of AI in chemical research\, and links to the upcoming talks in the Seminar Series\, I will give some examples\, from our own group’s research activities\, showcasing the use of atomistic machine learning to achieve a degree of realism in materials modeling that was previously out of reach. \nAbout the speaker\nMiguel Caro is Senior Scientist at the Department of Chemistry and Materials Science\, Aalto University\, as well as main organizer of the AI in CHEM Seminar Series and teacher in charge of course CHEM-E4190. For more info\, visit miguelcaro.org.
URL:https://ocamm.fi/event/ai-in-chem-seminar-series-intro-session-with-miguel-caro/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20241101T131500
DTEND;TZID=UTC:20241101T140000
DTSTAMP:20260417T134744
CREATED:20241023T133256Z
LAST-MODIFIED:20241023T133256Z
UID:253-1730466900-1730469600@ocamm.fi
SUMMARY:Special seminar by Dr. Konstantinos Konstantinou
DESCRIPTION:Save the date! OCAMM presents a special seminar by Dr. Konstantinos Konstantinou from the University of Turku\, who will talk about atomistic simulations of phase-change materials for aerospace applications. This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 1 November 2024 @ 13:15 in lecture hall D311 (Ke5) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi to find out how order/disorder transitions in a material can be used to construct nanoscale computer memories! \nTitle \nNon-volatile phase-change memory for spaceship application \nAbstract \nRadiation-hard non-volatile memories are in high demand by the space community for implementation in microcontrollers and solid-state data recorders. In phase-change memories\, binary data are represented as changes in structural phase rather than by stored electrical charge; thus\, these devices are supposed to be tolerant to ionizing radiation effects. Ion irradiation corresponds to a process that involves the production of non-equilibrium cascades in the host material\, and the atomistic modelling of such events in glasses is challenging. Here\, radiation damage in amorphous Ge2Sb2Te5 phase-change memory material is modelled by carrying out thermal-spike simulations with ab initio molecular-dynamics calculations. A stochastic boundary-conditions approach is employed to treat the thermal nature of the cascades and drive the modelled system back to equilibrium in a natural way. The dynamics of the cascade evolution shows that the time-scale of the ballistic phase of the cascade inside the glass model is very short. Investigation of the atomic geometry highlights a structural recovery from the damage imposed during ion irradiation\, since the glass manages to maintain its amorphous network. Analysis of the bonding for all the species in the glass structure reveals particular structural modifications in the local atomic environments and the connectivity of the amorphous network. Overall\, the simulations manifest the remarkable ability of Ge2Sb2Te5 phase-change memory material to be radiation-tolerant\, hence indicating its potential applications in future space and other radiation-present environments. \nAbout the speaker \nAfter completing his MSc degree in Computational Physics at the Aristotle University of Thessaloniki in Greece\, Konstantinous moved to the UK to obtain a PhD in Physics from University College London. He then joined the University of Cambridge as a research associate in Chemistry. Konstantinos came to Finland in 2020 as postdoctoral researcher in Tampere University before joining the University of Turku\, where he currently holds the prestigious Academy Fellow position. His current research interests include defects in amorphous semiconductors\, resistive switching memories\, machine-learned molecular-dynamics simulations\, charge trapping processes\, and electronic excitations\, among others.
URL:https://ocamm.fi/event/special-seminar-by-dr-konstantinos-konstantinou/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2024/10/konstantinos.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240808T080000
DTEND;TZID=UTC:20240808T170000
DTSTAMP:20260417T134744
CREATED:20240808T061521Z
LAST-MODIFIED:20240808T062359Z
UID:236-1723104000-1723136400@ocamm.fi
SUMMARY:Special seminar by Dr. Michael Nolan
DESCRIPTION:Save the date! OCAMM presents a special seminar by Dr. Michael Nolan from the Tyndall National Institute\, Ireland on ab initio atomistic simulation of the chemical processes involved in atomic layer processing\, such as atomic layer deposition (ALD) and atomic layer etching (ALE). This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 9 August 2024 @ 9:30 in lecture hall A304 (Ke2) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi to learn more about how you can simulate the growth (and destruction!) of materials one atomic layer at a time! \nTitle\nFirst Principles Simulations of Atomic Level Processing \nAbstract\nAtomic level processing allowed for deposition and etch of materials on complex substrates giving a high level of control over conformality and uniformity. In this seminar I will discuss how first principles simulations provide insights into a range of process chemistries. This includes atomic layer etching of high-k oxides\, deposition of hybrid organic-inorganic materials and plasma deposition of metals. \nAbout the speaker\nDr. Michael Nolan is head of the Materials Modelling for Devices group at the Tyndall National Institute in Cork\, Ireland\, whose aim is “to understand and predict how devices work\, by research based on modelling materials at the atomic scale”. The applied focus areas are\, among others\, electronics\, solar energy conversion\, atomic-layer processing of materials\, and surface-based heterogeneous catalysis. Dr. Nolan carries out his modeling work in close collaboration with experimental groups and industry.
URL:https://ocamm.fi/event/special-seminar-by-dr-michael-nolan/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Moscow:20240617T140000
DTEND;TZID=Europe/Moscow:20240620T170000
DTSTAMP:20260417T134744
CREATED:20231218T122555Z
LAST-MODIFIED:20240805T085545Z
UID:135-1718632800-1718902800@ocamm.fi
SUMMARY:Recent Advances in Computer-aided X-ray Spectroscopy
DESCRIPTION:Recent Advances in Computer-aided X-ray Spectroscopy\n \nMotivation and overview\nX-ray spectroscopic techniques\, such as X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS)\, as well as different related techniques\, have been instrumental in improving our understanding of the structure of complex materials. However\, direct interpretation of experimental X-ray spectra is often hindered by overlapping signatures\, e.g.\, two different atomic environments can contribute in the same region of a material’s spectrum\, making it impossible to tell them apart. At the same time\, experimentalists often rely on simplified theoretical references to interpret their spectra. For these reasons\, simulations have always had an important role in interpretation of X-ray spectra since electronic-structure-based computations of core-level excitation energies became practical a couple of decades ago. Still\, many challenges remain regarding the accuracy and cost of these computations\, and how to reliably combine them with experiment. The field has seen rapid growth and development in recent years\, due to fundamental and methodological development (e.g.\, the development of low-scaling algorithms for core-level spectroscopy) as well as the introduction of machine-learning techniques which are opening up avenues that were not previously obvious\, both in terms of speeding up the computational predictions and integrating simulations and experiments. \nAbout this workshop\nThis workshop aims to get the community of computational X-ray spectroscopy together\, and discuss recent advances\, outstanding challenges\, and the directions in which the field will be developing in the near and medium future. In particular\, the workshop will cover advances in 1) highly accurate electronic structure techniques\, 2) methodologies for high-throughput spectra generation and materials screening\, 3) machine learning to speed up X-ray spectra predictions\, 4) machine learning to aid in the interpretation of experimental spectra\, 5) structure inference from spectra\, 6) novel techniques combining experimental and simulated spectra\, 7) applications to specific materials and molecules. \nWhile the event is focused on computational approaches\, one of the aspects we want to highlight are the developments combining experiment and simulation\, and we want to hear from experimentalists what are the outstanding challenges and how they understand the role of computations in aiding in the interpretation of experimental results. For this reason we have included experimental experts in the roster of proposed speakers below. \nInvited Speakers\n\nAnnika Bande (Hannover University & HZ Berlin\, Germany)\nMaria Chan (Argonne National Lab\, US)\nDorothea Golze (TU Dresden\, Germany)\nDeyu Lu (Brookhaven National Lab\, US)\nReinhard Maurer (University of Warwick\, UK)\nMounir Mensi (EPFL\, Switzerland)\nRobert Palgrave (UCL\, UK)\nPaavo Penttilä (Aalto University\, Finland)\nAnna Regoutz (UCL\, UK)\nSami Sainio (Aalto/SLAC)\n\nVenue\nThe conference will take place in the main campus of Aalto University\, in the Helsinki metropolitan area. The venue is the Aalto University’s School of Chemical Engineering’s main building\, Kemistintie 1\, Espoo\, 02150 Finland. \nAalto University is very well connected within the Helsinki metro area. The Otaniemi campus can be reached via metro (“Aalto University” stop) and the light rail (“Maari”\, “Aalto-yliopisto” and “Otaranta” stops\, from west to east). Please visit the website of HSL\, the company operating the public transport system in the Helsinki metro area. This includes buses\, the metro\, trains\, downtown trams\, the light rail\, and some municipal ferry services (e.g.\, to the Suomenlinna fortress island). Public transport in the Helsinki metro area is safe\, clean and reliable. The easiest way to use the public transport system is to download the HSL app on your phone. \nThe Aalto University campus can be reached from Helsinki airport\, e.g.\, by combining the train with the metro (changing at Helsinki’s Central Railway Station). Non-collective public transport options like taxis are also available\, including popular apps like Uber; these are significantly pricier than collective transportations but might be more convenient depending on the situation (e.g.\, if you are in a hurry to reach the airport). \nImportant information about disruptions to the Metro service during Summer 2024\nThere are ongoing renovation works during the Summer months of 2024 that will impact Metro services. The most important disruptions are: \n\nClosing of the Helsinki Central Railway Station Metro station during 3 June – 1 September 2024. While the Central Railway Station will keep operating regular train services (both short and long distance)\, travelers will not be able to transfer to the Metro line at this station. The westbound Metro services will operate from Kamppi station\, which will be the East terminus of the Metro line during this time. Travelers wishing to go to Aalto University with the Metro should thus board at Kamppi Metro station or any other station west of Kamppi (e.g.\, Ruoholahti). Do not board the Metro line at any station east of the Central Railway Station\, as those Metro trains are only eastbound and do not go to Aalto University. If you are arriving in the Central Railway Station by regular rail service\, e.g.\, with the train from the ariport\, you can either walk to Kamppi (5-10 minute walk) or use tram lines 9 or 9B – it is probably easiest to walk and enjoy Helsinki city center. More info here.\nTietotie exit of the Aalto University Metro station is closed starting 3 June for about 5 weeks. The Aalto University Metro station has two exits/entrances: Tietotie and Otaniementie. The exit closest to the conference venue\, Otaniementie\, will remain open during the conference. Thus\, this disruption should have very little impact on RACXS participants. Read more here.\nMellunmäki Metro station closed during 3 June – 8 September. This only affects public transit in the East Helsinki region and should not affect the vast majority of RACXS participants. If you want to read more about this\, click here.\n\nSchedule and program\nSome of the speakers agreed to share their talks publicly. \nWe will start in the afternoon (~2pm) of Monday 17 June (so that participants from Europe can travel in the morning) and end with a full day on Thursday 20 June. This is the detailed program of the workshop. \n\n\n\n\nMonday 17 June\n\nTuesday 18 June\nWednesday 19 June\nThursday 20 June\n\n\n\n9:30\nMounir Mensi (invited):\n“Dealing with the Surjective Nature of XPS”\nReinhard Maurer (invited):\n“X-ray spectroscopic signatures of chemical bonding and dynamics at metal-organic interfaces”\nMaria Chan (invited):\n“Data-driven capture and analysis of core-level spectra”\n\n\n10:10\nJavier Heras-Domingo (contributed):\n“Unlocking the Potential of EXAFS: Machine Learning Approaches for Spectroscopic Data”\nDylan Morgan (contributed):\n“Using Orbital-Constrained DFT to Simulate Surface Spectroscopy with Relativistic Corrections”\nAneta Gójska (contributed):\n“The K-X-ray intensity ratios as a tool of examination and thickness measurements of coating layers”\n\n\n10:30\nCoffee break\n\n\n11:00\nSami Sainio (invited):\n“Interpretation of experimental spectra and some related pitfalls”\nDeyu Lu (invited):\n“Data-driven X-ray absorption spectral analysis: theory\, workflow\, database and machine learning”\nAnna Regoutz (invited):\n“Recent developments in Hard X-ray Photoelectron Spectroscopy and Combination with Theoretical Approaches”\n\n\n11:40\nSam Hall (contributed):\n“X-ray Absorption Spectra Prediction of Extended Graphene Oxide Nanoflakes using Graph Neural Networks”\nBo Zhao (contributed):\n“Automated Mössbauer spectroscopy”\nMichael Walter (contributed):\n“Predicting x-ray absorption and photoemission spectra on the absolute energy scale”\n\n\n12:00\nLunch at Maukas\nLunch at Maukas\nLunch at conference venue\n\n\n13:30\nRobert Palgrave (invited):\n“Quantitative Simulation of XPS Valence Band Spectra from DFT”\nAnnika Bande (invited):\n“Prediction AND INTERPRETATION of XAS Spectra using Graph Neural Networks”\nConor Rankine (contributed):\n“Teaching Core-Hole Spectroscopy to a Deep Neural Network”\n\n\n14:00\nWelcome to participants at Kemistintie 1 (coffee served)\n13:50\nThomas Pope (contributed):\n“Refining the Syllabus: Can Physically Motivated Descriptors Improve Predictions”\n\n\n14:10\nLena Bäuml (contributed):\n“Following the Coupled Nuclear and Electron Dynamics of Chlorophyll with XMS-CASPT2 X-Ray Absorption Spectra”\nNavanthara Karippara Jayadev (contributed):\n“Insights to the Auger decay in benzene”\nBibek Samal (contributed):\n“A Parameter-Free Approach for Modeling X-ray Emission and Photoelectron Spectroscopy”\n\n\n14:30\nDorothea Golze (invited):\n“Accurate prediction of core-level spectra with GW for complex materials”\n14:30\nCoffee break\n\n\n15:10\nPaavo Penttilä (invited):\n“Upgrading X-ray scattering analysis of wood through modeling and machine learning”\n15:00\nXing Wang (tutorial):\n“Streamlining Core-Level Spectroscopy Calculations with AiiDAlab Quantum ESPRESSO App”\nTigany Zarrouk (tutorial):\n“TurboGAP : Machine-Learned Potential Atomistics with Experimental Observable Prediction/Optimization”\n\n\n\n15:50 – 17:00\nMingling (snacks & refreshments)\n16:00 – 17:30\nPoster session (snacks & refreshments)\n\n\n\n\n\n\n\n19:00 – 21:00\n\nDinner at Restaurant Fat Lizard Otaniemi\n\n\n\n\nParticipants\n\n\n\nAbdurrahman\nAdhyatma\nUniversity of Turku\nabadhy@utu.fi\n\n\nAnnika\nBande\nHannover Univeristy and Helmholtz-Zentrum Berlin\n\n\n\nLena\nBäuml\nLudwig Maximilian University of Munich\n\n\n\nPrajna\nBhatt\nUCL\n\n\n\nMiguel\nCaro\nAalto University\nmiguel.caro@aalto.fi\n\n\nMaria\nChan\nArgonne National Laboratory\nmchan@anl.gov\n\n\nPrathibha\nChandrashekhar\nUppsala University\nprathibha.chandrashekhar@physics.uu.se\n\n\nCarlos\nCorral-Casas\nImperial College London\nc.corral-casas@imperial.ac.uk\n\n\nMandira\nDas\nUniversity of Turku\nmandda@utu.fi\n\n\nDhilan\nDevadasan\nThermo Fisher Scientific\ndhilan.devadasan@thermofisher.com\n\n\nAndrea Filippo\nDi Feo\nLUT University\nandrea.di.feo@lut.fi\n\n\nAneta\nGójska\nNational Centre for Nuclear Studies\naneta.gojska@ncbj.gov.pl\n\n\nDorothea\nGolze\nTU Dresden\ndorothea.golze@tu-dresden.de\n\n\nSam\nHall\nHelmholtz-Zentrum Berlin\nsamuel.hall@helmholtz-berlin.de\n\n\nJavier\nHeras Domingo\nICIQ\njheras@iciq.es\n\n\nRina\nIbragimova\nAalto University\nrina.ibragimova@aalto.fi\n\n\nNayanthara\nK. Jayadev\nUniversity of Southern California\nkarippar@usc.edu\n\n\nJiahui\nKang\nAalto Universtiy\njiahui.kang@aalto.fi\n\n\nJannis\nKockläuner\nTU Dresden\njannis.kocklaeuner@mailbox.tu-dresden.de\n\n\nAlisher\nKumarov\nLUT\nalisher.kumarov@lut.fi\n\n\nDeyu\nLu\nBrookhaven National Laboratory\ndlu@bnl.gov\n\n\nReinhard\nMaurer\nUniversity of Warwick\n\n\n\nMounir\nMensi\nEPFL – Switzerland\nmounir.mensi@epfl.ch\n\n\nClelia\nMiddleton\nNewcastle University\n\n\n\nDylan\nMorgan\nUniversity of Warwick\ndylan.morgan@warwick.ac.uk\n\n\nHolger\nNeupert\nCERN\nHolger.Neupert@cern.ch\n\n\nRobert\nPalgrave\nUCL\nr.palgrave@ucl.ac.uk\n\n\nPaavo\nPenttilä\nAalto University\n\n\n\nThomas\nPope\nNewcastle University\nthomas.pope2@newcastle.ac.uk\n\n\nPaulina\nPrslja\nAalto university\npaulina.prslja@aalto.fi\n\n\nRamesh\nRaju\nAalto University\nramesh.raju@aalto.fi\n\n\nConor\nRankine\nUniversity of York\n\n\n\nAnna\nRegoutz\nUniversity College London\n\n\n\nSami\nSainio\nAalto/SLAC\n\n\n\nBibek\nSamal\nTata Institute of Fundamental Research\nbibeksamal8@gmail.com\n\n\nAri Paavo\nSeitsonen\nÉcole Normale Supérieure\nAri.P.Seitsonen@iki.fi\n\n\nTorsten\nStaab\nUniversity Würzburg – LCTM\ntorsten.staab@uni-wuerzburg.de\n\n\nMilica\nTodorovic\nUniversity of Turku\n\n\n\nKrystian\nTrela\nNational Centre for Nuclear Studies\nkrystian.trela@ncbj.gov.pl\n\n\nRyan\nTrevorah\nUniversity of Helsinki\nryan.trevorah@helsinki.fi\n\n\nXing\nWang\nPaul Scherrer Institute\nxing.wang@psi.ch\n\n\nYanzhou\nWang\nAaalto University\nyanzhou.wang@aalto.fi\n\n\nMichael\nWalter\nUniversity of Freiburg\nMichael.Walter@fmf.uni-freiburg.de\n\n\nYerkezhan\nYerkinbekova\nLUT University\nyerkezhan.yerkinbekova@lut.fi\n\n\nTigany\nZarrouk\nAalto University\ntigany.zarrouk@aalto.fi\n\n\nBo\nZhao\nTU Darmstadt\nbo.zhao@tmm.tu-darmstadt.de\n\n\n\nRegistration\nThe registration closed on 5 April 2024. If you applied\, you should have already been notified with a decision regarding your application. \nOrganizers\nScientific organizing committee\n\nMiguel Caro\, Aalto University (Finland)\nPatrick Rinke\, Aalto University (Finland)\nTigany Zarrouk\, Aalto University (Finland)\n\nPractical matters\n\nDora Javor\, Aalto University (Finland)\n\nAffiliations\nThis workshop is organized by OCAMM and affiliated to the Finnish Synchrotron Radiation User Organisation (FSRUO). \n \nSponsors\nIn addition to organization support by OCAMM\, the Recent Advances in Computer-aided X-ray Spectroscopy conference is financially supported by the Psi-K network\, the Finnish CECAM node\, the Aalto University Deparment of Chemistry and Materials Science\, and the Aalto Science Institute.
URL:https://ocamm.fi/event/recent-advances-in-computer-aided-x-ray-spectroscopy/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Conference
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2023/12/logo.png
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240318T141500
DTEND;TZID=UTC:20240318T151500
DTSTAMP:20260417T134744
CREATED:20230907T120034Z
LAST-MODIFIED:20240318T083359Z
UID:115-1710771300-1710774900@ocamm.fi
SUMMARY:Seminar by Prof. Volker Deringer on machine-learning-based simulation of amorphous materials
DESCRIPTION:OCAMM presents a special seminar by Prof. Volker Deringer from the University of Oxford\, UK on machine-learning-based simulation of amorphous materials. This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 18 March 2024 @ 14:15 in lecture hall A304 (Ke2) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi to delve into the intricate atomic structure and fascinating properties of amorphous materials! \nTitle \nMachine-learning-driven advances in modelling amorphous materials \nAbstract \nUnderstanding the connections between the atomic-scale structure of materials and their macroscopic properties is among the most important research challenges in solid-state and materials chemistry. Atomistic simulations based on quantum-mechanical methods have played a key role in this – but they are computationally demanding\, and therefore they will inevitably reach their limits when materials with highly complex structures are to be studied. Machine learning (ML) based interatomic potentials are a rapidly emerging approach that helps to overcome this limitation: being “trained” on a suitably chosen set of quantummechanical data\, ML potentials achieve comparable accuracy whilst giving access to much larger-scale simulations – with thousands or even millions of atoms.\nIn this presentation\, I will showcase some recent advances in the modelling and understanding of inorganic materials that have been enabled by ML-driven simulations. I will argue that ML potentials are particularly useful for modelling non-crystalline (amorphous) structures that are difficult to characterise experimentally. I will survey recent work ranging from structural transitions in amorphous silicon [1] to multicomponent systems – specifically\, chalcogenide phase-change materials used in digital data storage [2]. I will also discuss methodological aspects\, including a perspective for using large synthetic datasets to pre-train neural-network potentials which can subsequently be fine-tuned on quantum-mechanical data [3]. The development of new\, accurate and efficient atomistic ML models promises a way to more fully understand the structure and properties of amorphous materials on the atomic scale.\n[1] V. L. Deringer\, N. Bernstein\, G. Csányi\, C. Ben Mahmoud\, M. Ceriotti\, M. Wilson\, D. A. Drabold\, S. R. Elliott\, Nature 2021\, 589\, 59.\n[2] Y. Zhou\, W. Zhang\, E. Ma\, V. L. Deringer\, Nat. Electron. 2023\, 6\, 746.\n[3] J. L. A. Gardner\, K. T. Baker\, V. L. Deringer\, Mach. Learn.: Sci. Technol. 2024\, 5\, 015003.
URL:https://ocamm.fi/event/seminar-by-prof-volker-deringer-on-machine-learning-based-simulation-of-carbon-materials/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2023/09/volker-deringer.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240312
DTEND;VALUE=DATE:20240315
DTSTAMP:20260417T134744
CREATED:20230816T150048Z
LAST-MODIFIED:20240802T151728Z
UID:72-1710201600-1710460799@ocamm.fi
SUMMARY:LOBSTER School 2024
DESCRIPTION:LOBSTER School on Chemical Bonding Analysis\n \nMotivation and overview\nThe need to understand why a particular material is stable or not is of paramount importance for computational materials science. Today\, atomic-scale materials modelling is clearly dominated by high-performance density-functional theory (DFT) using plane waves and pseudopotentials\, but understanding the often incredibly complex results frequently benefits from a thorough chemical-bonding analysis using local orbitals. This 3-day school will teach ~25 participants how to carry out chemical-bonding analysis in general. In particular\, the computer program LOBSTER will be introduced\, which has been designed to suit the needs of high-performance materials simulations by being able to process output from VASP\, ABINIT and Quantum ESPRESSO. The school will be the fifth in a series of previous successful ones in Germany\, China\, Japan\, and an online school during the COVID-19 pandemic. It is targeted at researchers from various fields of computational science such as chemistry\, physics\, and materials science. \nMethods for chemical-bonding analysis\nAs the search for new materials based on increasingly CPU-affordable electronic structure calculations gathers pace\, and the amount of data generated by high-throughput calculations continues to accumulate\, it becomes important to develop effective quantitative techniques to make sense of this wealth of information. While electronic structure calculations\, predominantly based on DFT\, have proven increasingly reliable and useful in understanding and predicting the properties of solids\, the intricate contribution of local bonding networks in these materials escapes the most commonly used DFT analysis tools. A standard tool to probe the local character of the material’s band structure is the projected density of states (PDOS). Unfortunately\, the PDOS only provides information about where electrons reside in the material\, and not about how much local interactions contribute to the cohesive energy of the material. The crystal orbital Hamilton population (COHP) analysis\, developed by Dronskowski and Blöchl in 1993\, allows one to quantify the energy contribution of individual atomic bonds to the total energy of the system (the bond strength). This tool has established itself as a widely used method for understanding existing and new materials\, because it provides a detailed quantitative way to establish links between the (macroscopic) properties of a material and its microscopic structure. \nLecturers\n\nProf. Richard Dronskowski\, RWTH Aachen University (Germany)\nProf. Volker Deringer\, University of Oxford (UK)\nDr. Janine George\, Federal Institute for Materials Research and Testing\, Berlin (Germany) and FS University Jena (Germany)\nDr. David Schnieders\, RWTH Aachen University (Germany)\nPeter Müller\, RWTH Aachen University (Germany)\n\nVenue\nThe LOBSTER School 2024 will take place in the main campus of Aalto University\, in the Helsinki metropolitan area. The School’s venue is Aalto Design Factory‘s Studio\, Puumiehenkuja 5A\, Espoo\, 02150 Finland. \nAalto University is very well connected within the Helsinki metro area. The Otaniemi campus can be reached via metro (“Aalto University” stop) and the light rail (“Maari”\, “Aalto-yliopisto” and “Otaranta” stops\, from west to east). Please visit the website of HSL\, the company operating the public transport system in the Helsinki metro area. This includes buses\, the metro\, trains\, downtown trams\, the light rail\, and some municipal ferry services (e.g.\, to the Suomenlinna fortress island). Public transport in the Helsinki metro area is safe\, clean and reliable. The easiest way to use the public transport system is to download the HSL app on your phone. \nThe Aalto University campus can be reached from Helsinki airport\, e.g.\, by combining the train with the metro (changing at Helsinki’s Central Railway Station). Non-collective public transport options like taxis are also available\, including popular apps like Uber; these are significantly pricier than collective transportations but might be more convenient depending on the situation (e.g.\, if you are in a hurry to reach the airport). \nSchedule\nThis is the preliminary schedule. More detailed information will be provided later. \n\n\n\n\nTuesday 12 March\nWednesday 13 March\nThursday 14 March\n\n\n9:00 – 9:30\nRegistration and welcome addresses (9:20 Miguel Caro & 9:25 Richard Dronskowski)\n\n\n\n\n9:30 – 10:30\nChemical Bonding 101 (Richard Dronskowski)\nCharges\, Madelung\, Bond Indices\, Polarizations (Peter Mueller)\nDefects\, nanomaterials\, amorphous matter (Volker Deringer)\n\n\n10:30 – 11:00\nCoffee break\nCoffee break\nCoffee break\n\n\n11:00 – 12:30\nPractical session: LOBSTER installation\, first steps\nPractical session: advanced features and visualization\nPractical session: application of the previous session\n\n\n12:30 – 14:00\nLunch break (participants pay for their own lunch – Maukas space reservation at 12:45)\nLunch break (participants pay for their own lunch – Maukas space reservation at 12:45)\nLunch break (participants pay for their own lunch – Arvo space reservation at 12:45)\n\n\n14:00 – 15:00\nLOBSTER nuts-and-bolts\, plane waves & orbitals\, projection to atomic orbitals (Daniel Schnieders)\nLOBSTER advanced\, projection to molecular orbitals\, other basis sets\, magnetism\nLOBSTER automation (Janine George)\n\n\n15:00 – 15:30\nCoffee break\nCoffee break\nCoffee break\n\n\n15:30 – 17:00\nPractical session: basic features\nPractical session: more advanced features\nPractical session: application of the previous session\n\n\n17:30 – 19:00\nPoster session (takes place at the School of Chemical Engineering building’s upstairs lobby\, Kemistintie 1)\n\n\n\n\n18:30 – 20:30\n\nDinner @ Fat Lizard Restaurant Otaniemi\n\n\n\n\nParticipants\n\n\n\nName\nInstitution\nContact\n\n\nMiguel Caro\nAalto University\nmiguel.caro@aalto.fi\n\n\nPeter Müller\nRWTH Aachen University\npeter.mueller@ac.rwth-aachen.de\n\n\nHanwen Zhang\nUniversity of Oxford\n\n\n\nJavier Sanz Rodrigo\nDTU\nsanz@dtu.dk\n\n\nRajeev Dutt\nUniversity of Warwick\nrajeev.dutt@warwick.ac.uk\n\n\nLinh Tong\nAalto University\nlinh.tong@aalto.fi\n\n\nVolker Deringer\nUniversity of Oxford\nvolker.deringer@chem.ox.ac.uk\n\n\nWanja Schulze\nUniversity of Jena\nwanja.schulze@uni-jena.de\n\n\nNityasagar Jena\nLinköping University\nnityasagar.jena@liu.se\n\n\nRansel Barzaga\nInstituto de Astrofísica de Canarias\n\n\n\nScott Simpson\nSt. Bonaventure University\nssimpson@sbu.edu\n\n\nAlyssa Santos\nSt. Bonaventure University\n\n\n\nAnson Thomas\nIndian Institute of Technology Roorkee\nanson_t@cy.iitr.ac.in\n\n\nM.D. Hashan C. Peiris\nBinghamton University – State University of New York\nmpeiris1@binghamton.edu\n\n\nRichard Dronskowski\nRWTH Aachen University\n\n\n\nDivya Srivastava\nTurku University\ndivya.srivastava@utu.fi\n\n\nPablo Castro Latorre\nUniversity of Barcelona\np.castrola@ub.edu\n\n\nElisa Damiani\nUniversity of Bologna\nelisa.damiani4@unibo.it\n\n\nMadhavi Dalsaniya\nWarsaw University of Technology\nmadhavi.dalsaniya.dokt@pw.edu.pl\n\n\nYiXu Wang\nRWTH Aachen University\nyixu.wang@ac.rwth-aachen.de\n\n\nEdith Simmen\nETH Zurich\nedith.simmen@mat.ethz.ch\n\n\nRafael Nunez\nAalto University\nrafael.nunez@aalto.fi\n\n\nAleksandra Oranskaia\nKAUST\naleksandra.oranskaia@kaust.edu.sa\n\n\nDavid Schnieders\nRWTH Aachen University\ndavid.schnieders@ac.rwth-aachen.de\n\n\nNeeraj Mishra\nBen-Gurion University of the Negev\nneeraj@post.bgu.ac.il\n\n\nMadhavi Dalsaniya\nWarsaw University of Technology\nmadhavi.dalsaniya.dokt@pw.edu.pl\n\n\nRina Ibragimova\nAalto University\nrina.ibragimova@aalto.fi\n\n\nMunavvar Husain\nUniversity of Warsaw\n\n\n\nJanine George\nBAM Berlin\n\n\n\n\nOnline resources\n\nLOBSTER website (for code download\, etc.): http://cohp.de/\nGithub repository: https://github.com/davSchnieders/LOBSTERSchool\nwxDragon fro visualization: Linux version; Windows version\nStep-by-step procedure:\n\nDownload and unpack the LOBSTER code\nAdd the LOBSTER binary to your PATH: export PATH=/lobster_code_root_directory:$PATH\nClone the github repo: git clone https://github.com/davSchnieders/LOBSTERSchool.git\nDownload and unpack wxDragon\nMake the wxDragon binary executable (from within the wxDragon directory): chmod +x wxDragon\nAdd the wxDragon binary to your PATH: export PATH=/wxDragon_code_root_directory:$PATH\n\n\nTo install LobsterPy\, you can just do: pip install lobsterpy (under Ubuntu\, you may also need to upgrade your requests package\, e.g.: pip install requests==2.25.0)\n\nRegistration\nThe registration is now closed. \nLocal organizers\n\nDr. Miguel Caro\, Aalto University (Finland)\nDr. Rina Ibragimova\, Aalto University (Finland)\nDora Javor\, Aalto University (Finland)\n\nSponsors\nIn addition to organization support by OCAMM\, the LOBSTER School 2024 is financially supported by the Psi-K network\, the Aalto University Deparment of Chemistry and Materials Science\, and the Finnish CECAM node.
URL:https://ocamm.fi/event/lobster-school-2024/
LOCATION:Aalto Design Factory\, Puumiehenkuja 5A\, Espoo\, 02150\, Finland
CATEGORIES:School
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2023/08/lobster_logo.png
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240311T141500
DTEND;TZID=UTC:20240311T151500
DTSTAMP:20260417T134744
CREATED:20240123T150442Z
LAST-MODIFIED:20240125T082125Z
UID:157-1710166500-1710170100@ocamm.fi
SUMMARY:Seminar by Prof. Richard Dronskowski on the crystal structure of carbonic acid
DESCRIPTION:Save the date! OCAMM presents a special seminar by Prof. Richard Dronskowski from RWTH Aachen\, Germany on the always fascinating (and sometimes controversial!) topic of carbonic acid. This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 11 March 2024 @ 14:15 in lecture hall A304 (Ke2) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi to learn something new (or revisit your ideas) about carbonic acid! \nTitle\nThe Crystal Structure of Carbonic Acid – A Stroll between Molecular Chemistry\, Theory\, High Pressure\, Neutron Diffraction\, and Chemical Bonding \nAbstract\nUbiquitous carbonic acid\, H2CO3\, a key molecule in biochemistry\, geochemistry\, and also extraterrestrial chemistry\, is known\, at least in principle\, from various physicochemical studies but is often considered\, even up to the present day\, a somewhat mysterious “non-existing” molecule. In fact\, the molecule has never been directly seen\, the reason being that high pressure is needed to stabilize it\, as easily shown by electronic-structure theory. After an eight-years research study\, the crystal structure of carbonic acid was determined from neutron-diffraction data on a deuterated sample in a specially built hybrid clamped cell using “Russian alloy”. At 1.85 GPa\, D2CO3 crystallizes in the monoclinic space group P21/c with a = 5.392(2)\, b = 6.661(4)\, c = 5.690(1) Å\, β = 92.66(3)°\, Z = 4\, with one symmetry-inequivalent anti-anti shaped D2CO3 molecule forming dimers\, as previously predicted. Quantum chemistry evidences π bonding within the CO3 molecular core\, very strong hydrogen bonding between the molecules\, and a massive influence of the crystal field on all bonds; phonon calculations emphasize the locality of the vibrations\, being rather insensitive to the extended structure. Now that carbonic acid has been firmly established\, this may be important for other fields\, for example CO2 “sequestration” and its the chemical consequences. Likewise\, carbonic acid probably plays a role in our solar system\, say\, on outer gas planets such as Uranus or Neptune and\, also\, on the Jupiter moon Europa. Finally\, many chemistry textbooks must be rewritten because the simplest molecule consisting of water and carbon dioxide actually exists. \nSee also: “The Crystal Structure of Carbonic Acid”. S. Benz\, D. Chen\, A. Möller\, M. Hofmann\, D. Schnieders\, and R. Dronskowski. Inorganics 10\, 132 (2022). \nAbout the speaker\nRichard Dronskowski studied chemistry and physics at the University of Münster in the early 1980s. After having received his diplomas in 1987 and 1989\, he got his Ph.D. in 1990 from the Technical University of Stuttgart and the Max Planck Institute for Solid State Research with the thesis “Condensed Clusters in Oxides and Arsenides of Molybdenum”. Five years later\, he received both habilitation and venia legendi from the University of Dortmund. \nIn his professional career he worked as a visiting scientist at Cornell University and the Max Planck Institute at Stuttgart. Since 1997 he has been with RWTH Aachen University where he holds the Chair of Solid-State and Quantum Chemistry. He is also engaged at the Hoffmann Institute of Advanced Materials in Shenzhen\, China.
URL:https://ocamm.fi/event/seminar-by-prof-richard-dronskowski-on-the-crystal-structure-of-carbonic-acid/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2024/01/dronskowski.png
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240311T100000
DTEND;TZID=UTC:20240311T110000
DTSTAMP:20260417T134744
CREATED:20230907T121250Z
LAST-MODIFIED:20240124T131104Z
UID:118-1710151200-1710154800@ocamm.fi
SUMMARY:Seminar by Prof. Janine George on automation and workflows in atomistic simulation
DESCRIPTION:Save the date! OCAMM presents a special seminar by Prof. Janine George on automation and workflows in atomistic simulation. This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 11 March 2024 @ 10:00 in lecture hall A304 (Ke2) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi to learn more about how high-throughput calculations of molecules and materials can be made efficient and tractable! \nTitle\nData-Driven Chemical Understanding with Bonding Analysis \nAbstract\nBonds and local atomic environments are crucial descriptors of material properties. They have been used to create design rules and heuristics and as features in machine learning of materials properties [1]. Implementations and algorithms (e.g.\, ChemEnv and LobsterEnv) for identifying local atomic environments based on geometrical characteristics and quantum-chemical bonding analysis are nowadays available [2\,3]. Fully automatic workflows and analysis tools have been developed to use quantum-chemical bonding analysis on a large scale [3\,4]. The lecture will demonstrate how our tools\, that assess local atomic environments and perform automatic bonding analysis\, help to develop new machine learning models and a new intuitive understanding of materials [5\,6]. Furthermore\, the general trend toward automation in density functional-based materials science and some of our recent contributions will be discussed [7–10]. \nReferences \n\nJ. George\, G. Hautier\, Trends Chem. 2021\, 3\, 86–95.\nD. Waroquiers\, J. George\, M. Horton\, S. Schenk\, K. A. Persson\, G.-M. Rignanese\, X. Gonze\, G. Hautier\, Acta Cryst B 2020\, 76\, 683–695.\nJ. George\, G. Petretto\, A. Naik\, M. Esters\, A. J. Jackson\, R. Nelson\, R. Dronskowski\, G.-M. Rignanese\, G. Hautier\, ChemPlusChem 2022\, 87\, e202200123.\n“LobsterPy\,” can be found under https://github.com/JaGeo/LobsterPy\, 2022.\nA. A. Naik\, C. Ertural\, N. Dhamrait\, P. Benner\, J. George\, Sci Data 2023\, 10\, 610.\nK. Ueltzen\, A. Naik\, C. Ertural\, P. Benner\, J. George\, Article in Preparation 2024.\nJ. George\, Trends Chem. 2021\, 3\, 697–699.\nA. Ganose\, et al.\, “atomate2\,” can be found under https://github.com/materialsproject/atomate2\, 2023.\nA. S. Rosen\, M. Gallant\, J. George\, J. Riebesell\, H. Sahasrabuddhe\, J.-X. Shen\, M. Wen\, M. L. Evans\, G. Petretto\, D. Waroquiers\, G.-M. Rignanese\, K. A. Persson\, A. Jain\, A. M. Ganose\, Journal of Open Source Software 2024\, 9\, 5995.\nI. Batatia\, P. Benner\, Y. Chiang\, A. M. Elena\, D. P. Kovács\, J. Riebesell\, X. R. Advincula\, M. Asta\, W. J. Baldwin\, N. Bernstein\, A. Bhowmik\, S. M. Blau\, V. Cărare\, J. P. Darby\, S. De\, F. Della Pia\, V. L. Deringer\, R. Elijošius\, Z. El-Machachi\, E. Fako\, A. C. Ferrari\, A. Genreith-Schriever\, J. George\, R. E. A. Goodall\, C. P. Grey\, S. Han\, W. Handley\, H. H. Heenen\, K. Hermansson\, C. Holm\, J. Jaafar\, S. Hofmann\, K. S. Jakob\, H. Jung\, V. Kapil\, A. D. Kaplan\, N. Karimitari\, N. Kroupa\, J. Kullgren\, M. C. Kuner\, D. Kuryla\, G. Liepuoniute\, J. T. Margraf\, I.-B. Magdău\, A. Michaelides\, J. H. Moore\, A. A. Naik\, S. P. Niblett\, S. W. Norwood\, N. O’Neill\, C. Ortner\, K. A. Persson\, K. Reuter\, A. S. Rosen\, L. L. Schaaf\, C. Schran\, E. Sivonxay\, T. K. Stenczel\, V. Svahn\, C. Sutton\, C. van der Oord\, E. Varga-Umbrich\, T. Vegge\, M. Vondrák\, Y. Wang\, W. C. Witt\, F. Zills\, G. Csányi\, 2023\, DOI 10.48550/arXiv.2401.00096.\n\nAbout the speaker\nJanine George received her Bachelor of Science in Chemistry and Master of Science (summa cum laude) also in Chemistry\, both from RWTH Aachen University\, in 2011 and 2013\, respectively. She then obtained a Doctorate (Dr. rer. nat\, summa cum laude) in Computational Solid-State Chemistry under the supervision of Prof. Richard Dronskowski\, RWTH Aachen University in 2017. During 2018-2021 she held a Post-Doc position in the groups of Prof. Geoffroy Hautier at the Université catholique de Louvain (now at Darthmouth College) and Prof. Gian-Marco Rignanese also at the Université catholique de Louvain. Since 2021 she is Junior Group Leader of the Group “Computational Materials Design” at the Federal Institute for Materials Research and Testing (Department Materials Chemistry) in Berlin and\, since 2023\, she holds a joint appointment as Professor for Materials Informatics between the latter and the FSU Jena (Institute of Condensed Matter Theory and Optics).
URL:https://ocamm.fi/event/seminar-by-dr-janine-george-on-automation-and-workflows-in-atomistic-simulation/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2023/09/janine.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20240207T141500
DTEND;TZID=UTC:20240207T151500
DTSTAMP:20260417T134744
CREATED:20240131T134025Z
LAST-MODIFIED:20240131T153714Z
UID:169-1707315300-1707318900@ocamm.fi
SUMMARY:Seminar by Tamas Stenczel on machine-learning accelerated ab-initio molecular dynamics
DESCRIPTION:Save the date! OCAMM presents a special seminar by Tamas Stenczel on accelerating ab initio molecular dynamics with on-the-fly machine learning. This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 7 February 2024 @ 14:15 in lecture hall A304 (Ke2) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi to learn more about how you can make molecular dynamics orders of magnitude faster while retaining ab initio accuracy! \nTitle\nML Acceleration for Dynamics in Ab-Initio Modelling \nAbstract\nShowcase of existing methods and ongoing work on accelerating various dynamical simulations in ab-initio codes with modern ML. Replacing the ab-initio energy model where possible with an on-the-fly updated ML (GAP/ACE/MACE) one\, we will visit methods and frameworks making materials science & chemical ML models easy to access for all modelling needs. Next generation methods\, frameworks\, scientific challenges\, and opportunities for using and contributing to efforts in the field will be presented\, starting from recently published advances in the CASTEP code\, going to a general framework currently being implemented in a range of simulation tools. \nAbout the speaker\nTamás K. Stenczel is a researcher at the University of Cambridge\, with ties in academia and in various industrial realms. Amongst heading a research and software team at a family office\, conducting open academic research\, and everyday life\, he is a skiier and biker\, always striving to see and understand more of the world.
URL:https://ocamm.fi/event/seminar-by-tamas-stenczel-on-machine-learning-accelerated-ab-initio-molecular-dynamics/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2024/01/tamas.jpeg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20231113T140000
DTEND;TZID=Europe/Helsinki:20231113T150000
DTSTAMP:20260417T134744
CREATED:20230907T113618Z
LAST-MODIFIED:20230907T115837Z
UID:110-1699884000-1699887600@ocamm.fi
SUMMARY:Seminar by Prof. Rocío Mercado on artificial intelligence in biomolecular modeling
DESCRIPTION:OCAMM presents a special seminar by Prof. Rocío Mercado from Chalmers University of Technology\, Sweden on “Deep generative models for biomolecular engineering“. This invited seminar will take place at the Department of Chemistry and Materials Science\, Aalto University on 13 November 2023 @ 14:00 in lecture hall A304 (Ke2) at the main building of the School of Chemical Engineering in the Otaniemi campus\, Kemistintie 1\, 02150 Espoo. The seminar is open to all. Please join us in Otaniemi for a great talk on how artificial intelligence and molecular modeling are impacting the fields of biomolecular design and drug discovery. \nTitle\nDeep generative models for biomolecular engineering \nAbstract\nAI is transforming our approach to molecular engineering. Driven by the goal of accelerating drug development\, our aim is to develop AI-driven molecular engineering methods which will enhance our approach to biomolecular discovery\, such as drug discovery\, drug repurposing\, and chemical probe identification. This entails the development of generative and predictive tools that can learn from biochemical data\, such as molecular structures\, chemical reactions\, and biomedical data. While AI can be applied to a range of molecular engineering tasks\, one ideal area is de novo molecular design. De novo design is the concept of designing molecules with desired properties from scratch so as to minimize experimental screening\, and is poised to allow scientists to more efficiently traverse chemical space in search of optimal molecules\, and delegate error-prone decisions to computers via the use of predictive and generative models. In drug development\, de novo design methods can aid medicinal chemists in the design and selection of drug candidates\, with the added advantage that they can learn from datasets of billions of molecules in minutes and be constantly updated with new data. Deep molecular generative models are a particular approach to de novo design which uses deep neural networks to generate new molecules in silico\, and works by proposing atom-by-atom (or fragment-by-fragment) modifications to an initial graph structure to generate compounds predicted to achieve a certain property profile. Such models can be applied to a range of therapeutic modalities. \nIn this talk\, I will discuss the development of deep generative models for various molecular engineering tasks relevant to early-stage drug discovery. These include a model for synthesizability-constrained molecular generation\, a reinforcement learning framework for molecular graph optimization\, and recent applications from our group to the design of large modalities for targeted protein degradation. \nAbout the speaker\nRocío is a tenure-track assistant professor in the Data Science and AI division at Chalmers since January 2023. She heads the AI Laboratory for Biomolecular Engineering (AIBE) in the Department of Computer Science and Engineering. \nPreviously\, she was a postdoctoral associate in the Coley group at MIT\, as well as an industrial postdoc in the Molecular AI team at AstraZeneca. Throughout her postdoctoral career\, she worked on the development of deep generative models for small molecule drug discovery. Before AstraZeneca\, she was a PhD student in Professor Berend Smit’s molecular simulation group at UC Berkeley and EPFL. She received her PhD in Chemistry from UC Berkeley in August 2018\, and her BSc in Chemistry from Caltech in June 2013.
URL:https://ocamm.fi/event/seminar-by-prof-rocio-mercado-on-artificial-intelligence-in-biomolecular-modeling/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2023/09/rocio-scaled.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231106
DTEND;VALUE=DATE:20231111
DTSTAMP:20260417T134744
CREATED:20230817T151020Z
LAST-MODIFIED:20230818T091336Z
UID:92-1699228800-1699660799@ocamm.fi
SUMMARY:Machine Learning Interatomic Potential School for Young & Early Career Researchers
DESCRIPTION:For up-to-date and more complete information\, please visit the official website: https://www.mlip-workshop.xyz/home\n\n\nMLIP 2023 is a CECAM & Psi-k hybrid school aimed at young and early-career researchers who are interested in using machine learning interatomic potentials (MLIP) in their research. The two main goals of this school are:  \n\n\nto give researchers a solid introduction to the basic scientific techniques of designing\, fitting\, and validating MLIPs for chemical/material systems \n\n\nto provide a platform for those interested in using MLIPs to connect with those involved in MLIP development to accelerate the adoption of ML techniques in the wider atomistic simulation community \n\n\nMLIP 2023 is the second edition of the MLIP 2021 workshop\, and will physically take place at Aalto University in Espoo\, Finland\, between 06–10 November 2023. Remote\, online participation is also possible. \nThe school will consist of keynote lectures on different topics of MLIP as well as hands-on tutorials that will allow the participants to apply the explained concepts to relevant toy cases and also their own research. The invited speakers are leading scientists in the field of MLIP\, at various career stages\, who are well–equipped to share their experience with those getting started in the field. \nInvited speakers\n\n\n\n\n\n\n\n\n\n\n\nAlice Allen\, Los Alamos National Laboratory\, USA\nNongnuch Artrith\, Utrecht University\, the Netherlands\nJörg Behler\, Ruhr-Universität Bochum\, Germany\nMichele Ceriotti\, École polytechnique fédérale de Lausanne\, Switzerland\nRose Cersonsky\, University of Winsconsin-Madison\, USA\nCecilia Clementi\, Freie Universität Berlin\, Germany\nZheyong (Bruce) Fan\, Bohai University\, China and Aalto University\, Finland\nGuillaume Fraux\, École polytechnique fédérale de Lausanne\, Switzerland\nAndrea Grisafi\, École Normale Supérieure\, France\nDávid Kovács\, University of Cambridge\, UK\nChris Pickard\, University of Cambridge\, UK\nMartin Uhrin\, Université Grenoble Alpes\, France\nSander Vandenhaute\, Ghent University\, Belgium\nChuck Witt\, University of Cambridge\, UK\nLinfeng Zhang\, AI for Science Institute and DP Technology\, China\n\n\n\n\n\n\n\n\n\n\n\nSchedule\nPlease visit https://www.mlip-workshop.xyz/schedule for an up-to-date schedule. \nRegistration\nPlease see https://www.mlip-workshop.xyz/participate for detailed instructions. However\, applications should still be submitted via the CECAM website (using the “Participate” tab). The registration deadline is 22 September 2023. \nVenue\nAalto University\, Finland. Check https://www.mlip-workshop.xyz/practical-info for more details on practicalities. \nOrganizers\n\nChiheb Ben Mahmoud\, University of Oxford (UK)\nMiguel Caro\, Aalto University (Finland)\nSanggyu Chong\, EPFL (Switzerland)\nFederico Grasselli\, EPFL (Switzerland)\nKevin Kazuki Huguenin-Dumittan\, EPFL (Switzerland)\nVenkat Kapil\, University of Cambridge (UK)\nFelix-Cosmin Mocanu\, École Normale Supérieure (France)\nJigyasa Nigam\, EPFL (Switzerland)\nDavide Tisi\, EPFL (Switzerland)\nMax Veit\, Aalto University (Finland)\n\nSponsors
URL:https://ocamm.fi/event/machine-learning-interatomic-potentials-theory-and-practice/
CATEGORIES:Conference
ATTACH;FMTTYPE=image/png:https://ocamm.fi/wp-content/uploads/2023/08/mlip-workshop-logo-2023.png
ORGANIZER;CN="Max Veit":MAILTO:max.veit@aalto.fi
END:VEVENT
END:VCALENDAR