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SUMMARY:Seminar by Volker Deringer
DESCRIPTION:Prof. Volker Deringer from the University of Oxford will deliver an invited seminar on Wednesday 25 March 2025 at 10:15-11:00 in hall A304 (Ke2) of the Aalto University School of Chemical Engineering main building\, Kemistintie 1\, Espoo. \nMachine-learned interatomic potentials for materials chemistry \nVolker Deringer \nDepartment of Chemistry\, University of Oxford \nMachine-learned interatomic potentials (MLIPs) are now widely used in atomistic simulations\, giving access to length and time scales that are otherwise inaccessible to first-principles methods. Their reliability in practice\, however\, depends crucially on the quality and coverage of the training data. In this talk\, I will discuss data-efficient approaches to constructing MLIPs\, including ML-accelerated first-principles molecular dynamics for generating reference configurations\, and automated de novo exploration of relevant configurational spaces using the autoplex software. I will also highlight model-distillation strategies (specifically\, a teacher–student approach) using accurate but computationally costly models to train fast\, task-specific MLIPs for downstream applications. I will illustrate these ideas using examples of structurally complex materials: amorphous silicon\, graphene oxide\, and phase-change materials that are used in data storage and neuromorphic computing.
URL:https://ocamm.fi/event/seminar-by-volker-deringer/
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
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DTSTART;TZID=UTC:20260416T100000
DTEND;TZID=UTC:20260416T153500
DTSTAMP:20261107T131639
CREATED:20260213T124618Z
LAST-MODIFIED:20260213T124623Z
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SUMMARY:ChemBio Finland: Session Machine Learning in Chemistry
DESCRIPTION:As part of the ChemBio Finland 2026 Exhibition\, held at Messukeskus in Helsinki\, OCAMM and Aalto University professors Kari Laasonen and Miguel Caro are chairing a session on Machine Learning in Chemistry. The sympossium will take place on the second day of the ChemBio Finland event\, 16 April 2026 between 10:00 and 15:35 in room 5 (“Sali 5”). The official website of the event is this\, where you can find more information about the venue and the other parallel sessions. \nRegistration\nThe registration is free of charge. To register as a visitor\, go to the official website or go directly to the registration page. \nProgram\nThe official web site for the program is here. There\, you can also check the other sessions taking place in parallel at the same venue during ChemBio 2026. \nChairs: Kari Laasonen and Miguel Caro \nChairperson 10-12 Kari Laasonen \n\n10:00–10:05 Opening. Kari Laasonen\, Aalto University\n10:05–10:30 Autonomous analysis\, manipulation and reactions in Scanning Probe Microscopy. Nian Wu\, Aalto University\n10:30–10:55 Decoding Surface Adsorption Chemistry with Active Learning. Milica Todorovic\, University of Turku\n10:55–11:20 LUMI-AI: A novel platform for AI4Science. Pekka Manninen\, CSC Tieteen tietotekniikan keskus\n11:20–11:55 ML-trained interaction potential for simulations of graphite nucleation from paramagnetic Fe-C melt. Jaakko Akola\, NTNU\, Trondheim\n12:00–13:00 Lunch break\n\nChairperson 13-14:15 Miguel Caro \n\n13:00–13:25 Advancing Biomolecular Simulations with ML: GROMACS Integration and QM/ML/MM Synergies. Dmitry Morozov\, University of Jyväskylä\n13:25–13:50 Machine Learning in soft matter systems. Mikko Karttunen\, University of Eastern Finland\n13:50–14:15 Machine Learning in drug discovery. Serhii Vakal\, Orion Pharma\n14:15–14:35 small break/coffee break\n\nChairperson 14:35–15:25 N.N. \n\n14:35–15:00 Inferring the atomic-scale structure of complex materials from experimental observables with MAD. Tigany Zarrouk\, Aalto University\n15:00–15:25 ML search for new catalyst structures. Timo Weckman\, University of Jyväskylä\n15:25–15:35 Closing. Miguel Caro\, Aalto University
URL:https://ocamm.fi/event/chembio-finland-session-machine-learning-in-chemistry/
LOCATION:Messukeskus\, Messuaukio 1\, Helsinki\, 00520\, Finland
CATEGORIES:Conference
ORGANIZER;CN="Kari Laasonen":MAILTO:kari.laasonen@aalto.fi
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20261116T140000
DTEND;TZID=Europe/Helsinki:20261116T150000
DTSTAMP:20261107T131639
CREATED:20261107T090531Z
LAST-MODIFIED:20261107T090657Z
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SUMMARY:Special seminar: Autonomous Materials Synthesis on Demand (Andy Anker\, DTU)
DESCRIPTION:OCAMM organizes an exciting Special Seminar on autonomous laboratories by Prof. Andy Anker! \n\nTitle: Autonomous Materials Synthesis on Demand\nPresenter: Prof. Andy Anker\, Department of Energy Conversion and Storage\, Technical University of Denmark (DTU)\nPlace and time: School of Chemical Engineering main building (Kemistintie 1)\, Aalto University\, lecture hall Ke2\, Monday 16 November 2026. Coffee served at 14:00\, seminar starts at 14:15.\n\nAbstract \nAfter two teaching lectures on self-driving laboratories\, the trilogy reaches the research part: how can we actually use these systems to synthesise materials autonomously? \nThe discovery and synthesis of functional materials underpin advances in technologies ranging from energy storage to catalysis. Yet identifying suitable synthesis protocols is still largely based on trial-and-error experimentation. In this talk\, I will present our work towards self-driving laboratories for inorganic materials synthesis\, combining modular robotic experimentation\, advanced X-ray characterisation\, and machine learning in closed-loop platforms. \nI will show experiments carried out at synchrotron facilities\, where robotic synthesis is coupled directly to total X-ray scattering and pair distribution function analysis\, providing atomic-scale structural information on the synthesised materials. These data are fed into Bayesian optimisation algorithms running on GPU-based computing infrastructure\, which select the next synthesis experiment. Using this approach\, we have autonomously developed synthesis protocols for targeted gold nanomaterials during synchrotron beamtime. \nBuilding on these experiments\, we are now developing similar autonomous platforms at DTU\, integrating robotic synthesis\, advanced characterisation\, and machine learning within the laboratory. Our longer-term aim is to move from trial-and-error experimentation towards autonomous\, data-driven materials synthesis on demand. \nAbout the presenter \nAndy Anker is Assistant Professor at the Department of Energy Conversion and Storage of the Technical University of Denmark (DTU Energy). His interests include nanomaterials\, X-ray scattering\, self-driving laboratories\, total scattering with pair distribution function analysis\, machine learning/AI\, robotics and automation. Visit the DTU website for more information.
URL:https://ocamm.fi/event/special-seminar-autonomous-materials-synthesis-on-demand-andy-anker-dtu/
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/AndySAnker_Portraet-web-e1736506396902.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
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