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台灣理論計算分子科學學會自2021年起建置一個平台能讓會員們多了解年輕學者的研究方向，促進相互了解。「理論與計算分子科學論壇」將採線上演講方式(Webex)進行，時間訂於每月最後一週的週四晚上6點開始。
Speaker: Prof. Nongnuch Artrith (Debye Institute for Nanomaterials Science, Utrecht University)
Web: https://www.uu.nl/staff/NArtrith
Title: Development of efficient and accurate machine-learning potentials for the simulation of complex molecules and materials
Time: 6:00pm, Thursday, March 31, 2022 (GMT+8)
Online registration: https://forms.gle/Sou1YfpFVCv9oRYz8
Registration deadline: 12:00pm, March 31, 2022 (GMT+8)
Abstract
The properties of materials for energy applications, such as heterogeneous catalysts and battery materials, often depend on complicated chemical compositions and complex structural features including defects and disorder. This complexity makes the direct modelling with first principles methods challenging. Machine-learning (ML) potentials trained on first principles reference data enable linear-scaling atomistic simulations with an accuracy that is close to the reference method at a fraction of the computational cost. ML models can also be trained to predict the outcome of simulations or experiments, bypassing explicit atomistic modelling altogether.
Here, I will give an overview of our contributions to the development of ML potentials based on artificial neural networks (ANNs) and applications of the method to challenging materials classes including metal and oxide nanoparticles, amorphous phases, and interfaces. Further, I will show how large computational and small experimental data sets can be integrated for the ML-guided discovery of catalyst materials. These examples show that the combination of first-principles calculations and ML models is a useful tool for the modelling of nanomaterials and for materials discovery. All data and models are made publicly available. To promote Open Science, we also formulated guidelines for the publication of ML models for chemistry that aim at transparency and reproducibility.
If you have any questions, please do not hesitate to contact us.
Best regards,
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台灣理論計算分子科學學會
Taiwan Theoretical and Computational Molecular Sciences Association
Website: http://www.t2comsa.tw/
FB: https://www.facebook.com/t2comsa/
Email: t2comsa@gmail.com
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