Foundational Machine Learning Potentials - Challenges and Opportunities
Graph neural network interatomic potentials have emerged as powerful tools for accelerating materials simulation and property prediction.
The latest generation of models approach about ab initio accuracy while maintaining linear scaling of compute cost with system size, promising high quality molecular dynamics at unprecedented time and length scales.
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In this workshop, we would like to give you an introduction to FAIR data management and point out the problems present in laboratories that use optical spectroscopy methods such as ellipsometry, Raman spectroscopy, photoluminescence, reflection & transmission spectroscopy. We want to present our approach to map FAIR data as well with examples. We invite you to contribute so that you as well can use these structures as various optical spectroscopy methods have different requirements. We want to use the feedback from discussions to finalize the minimal needs and maximal capabilities, to define a standard, which is used as the base class for all the different spectroscopy methods.
The 18th International Congress on Catalysis will be held in Lyon, France, from July 14-19, 2024. As digitization has far-reaching implications for methodologies and workflows, also in catalysis research, a symposium will be dedicated to this topic and the need for FAIR data.
It will provide an opportunity to discuss the potential of digitalization in catalysis in all its aspects, including standardization of catalysis data, data sharing and curation, catalysis informatics, community-driven infrastructure, and digital research. The aim is to show a viable path for a digital transition for the community, both from an experimental and a theoretical perspective.
Welcome to the FAIR-DI European Conference on Data Intelligence! The conference will take place in Karlsruhe, Germany, on October 27 - 30, 2024.