Smart Sampling for Chemical Property Landscapes with BOSS
A Seminar of the NOMAD Laboratory
- Online Seminar of the NOMAD Laboratory
- Date: Jan 14, 2021
- Time: 01:15 PM (Local Time Germany)
- Speaker: Milica Todorović
- Aalto University, Finland
- Location: https://us02web.zoom.us/j/83575269594?pwd=WFpLUjR2bDFESzdlZmlDVlN4eEwzQT09
- Room: Webinar ID: 835 7526 9594 | Password: NOMAD
- Host: NOMAD Laboratory
We applied this active learning scheme to study 1) molecular adsorption at the organic/inorganic interfaces and 2) molecular conformers. For 1), we studied camphor deposited on Cu(111) and identified 8 unique stable adsorbates . By comparing them to atomic force microscopy (AFM) images, we were able to recognize 3 different structures of chemisorbed camphor in experiments . For 2), we applied BOSS to conformer search of several amino acid molecules. We successfully recovered more than 10 experimentally and theoretically determined conformer structures in less than 10% computational cost of the current fastest method . With a recent batch implementation for active learning, BOSS can make use of exascale computing resources to solve large-scale structural problems without sacrificing quantum-mechanical accuracy.
 M. Todorović, M. U. Gutmann, J. Corander and P. Rinke, ‘Efficient Bayesian Inference of Atomistic Structure in Complex Functional Materials’, npj Comput. Mater., 5, 35 (2019)
 J. Järvi, P. Rinke and M. Todorović, ‘Detecting stable adsorbates of (1S)-camphor on Cu(111) with Bayesian optimization’ Beilstein J. Nanotechnol. 11, 1577-1589 (2020)
 J. Järvi, B. Aldritt, O. Krejčí, M. Todorović, P. Liljeroth and P. Rinke, ‘Integrating Bayesian Inference with Scanning Probe Experiments for Robust Identification of Surface Adsorbate Configurations’, under consideration at Adv. Funct. Mater., doi:10.21203/rs.3.rs-50783/v1, (2020)
 L. Fang, E. Makkonen, M. M. Todorović, P. Rinke, X. Chen, ’Efficient Cysteine Conformer Search with Bayesian Optimization’, accepted at JCTC, arXiv:2006.15006 (2020).