BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//OCAMM - ECPv6.2.9//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://ocamm.fi
X-WR-CALDESC:Events for OCAMM
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20250101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=UTC:20250312T131500
DTEND;TZID=UTC:20250312T140000
DTSTAMP:20260420T061924
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:20250326T131500
DTEND;TZID=UTC:20250326T140000
DTSTAMP:20260420T061924
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
END:VCALENDAR