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Session Overview |
| Session | ||
MS-24: Data-driven discovery in crystallography
Invited: Wenhao Sun (USA), Aria Mansouri Tehrani (Switzerland) | ||
| Session Abstract | ||
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The mining of large datasets and databases is now commonplace pursuit in science, and data-driven discovery has become an essential component of various fields of research (e.g., recommendation engines in materials sciences, data-driven optimization in engineering) and a significant contributing factor to their prolific output. We propose to organize a session that will focus on the promotion and integration of data-driven discovery in crystallography, with primary focus on minerals, inorganic materials, and extended inorganic solids. This session will showcase recent works that have employed large data resources, computational-driven approach, machine-learning guidance, and advanced analytical methods to realize large-scale patterns in the solid state leading to discovery. For all abstracts of the session as prepared for Acta Crystallographica see PDF in Introduction, or individual abstracts below. | ||
| Introduction | ||
| Presentations | ||
10:20am - 10:25am
ID: 1753 / MS-24: 1 Introduction Oral/poster Introduction to session 10:25am - 10:55am
ID: 603 / MS-24: 2 Theory, computation, modelling, data, standards Invited lecture to session MS: Data-driven discovery in crystallography Keywords: Computational materials discovery, Exploratory synthesis, Unsupervised Machine Learning, Stability Maps Unsupervised Knowledge Discovery in ‘Big’ Materials Data University of Michigan, Ann Arbor, United States of America External Resource: https://www.xray.cz/iucrv/vidp.asp?id=196
10:55am - 11:25am
ID: 1351 / MS-24: 3 Theory, computation, modelling, data, standards Invited lecture to session MS: Data-driven discovery in crystallography Keywords: Machine Learning; Bismuth Ferrite; Distortion Modes; DFT Predicting ground state and metastable crystal structures using elemental and phonon mode ETH Zurich, Zurich, Switzerland External Resource: https://www.xray.cz/iucrv/vidp.asp?id=197
11:25am - 11:45am
ID: 857 / MS-24: 4 Theory, computation, modelling, data, standards Oral/poster MS: Data-driven discovery in crystallography Keywords: self-assembly. crystal structures, isotropic pair potentials Beyond the constraints of chemistry: Crystal structure discovery in particle simulations 1University of Michigan, Ann Arbor, MI, USA; 2Cornell University, Ithaca, NY, USA; 3University of California, San Francisco, CA, USA; 4Argonne National Laboratory, Argonne, IL, USA; 5Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany External Resource: https://www.xray.cz/iucrv/vidp.asp?id=198
11:45am - 12:05pm
ID: 894 / MS-24: 5 Theory, computation, modelling, data, standards Oral/poster MS: Crystal structure prediction, Advanced methods for analysis of XAFS and crystallographic data, Data-driven discovery in crystallography Keywords: Defect, Pair distribution function, Data-driven, Matrix factorization Data-driven approaches on pair distribution function data: matrix factorization and clustering Carnegie Mellon University, Pittsburgh, United States of America External Resource: https://www.xray.cz/iucrv/vidp.asp?id=199
12:05pm - 12:25pm
ID: 128 / MS-24: 6 Theory, computation, modelling, data, standards Oral/poster MS: High troughput vs. careful planning: How to get the best data?, Data-driven discovery in crystallography Keywords: Nanodiffraction, x-rays, powder diffraction, computer simulations First-principle diffraction simulations as a tool to solve the nanodiffraction problem 1Ozyegin University, Istanbul, TURKEY; 2Columbia University, New York, USA External Resource: https://www.xray.cz/iucrv/vidp.asp?id=200
12:25pm - 12:45pm
ID: 1139 / MS-24: 7 Theory, computation, modelling, data, standards Oral/poster MS: Quantum crystallographic studies on intra/inter-molecular interactions, Data-driven discovery in crystallography Keywords: Cambridge Structural Database; noncovalent interactions; ab initio calculations; aromatic molecules; metal complexes Study of noncovalent interactions using crystal structure data in the Cambridge Structural Database 1Innovation center of the Faculty of Chemistry, Belgrade, Serbia; 2Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Serbia; 3Faculty of Chemistry, Belgrade University, Belgrade, Serbia | ||