Conference Agenda

Session Overview
Session
MS-24: Data-driven discovery in crystallography
Time:
Monday, 16/Aug/2021:
10:20am - 12:45pm

Session Chair: Olivier C. Gagné
Session Chair: Anton Oliynyk
Location: Club H

100 1st floor

Invited: Wenhao Sun (USA), Aria Mansouri Tehrani (Switzerland)


Session Abstract

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

Olivier C. Gagné, Anton Oliynyk



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

Wenhao Sun

University of Michigan, Ann Arbor, United States of America



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

Aria Mansouri Tehrani, Bastien F. Grosso, Ramon Frey, Nicola A. Spaldin

ETH Zurich, Zurich, Switzerland



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

Julia Dshemuchadse1,2, Pablo F. Damasceno1,3, Carolyn L. Phillips4, Sharon C. Glotzer1, Michael Engel1,5

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



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

Shuyan Zhang, Jie Gong, B. Reeja Jayan, Alan J. H. McGaughey

Carnegie Mellon University, Pittsburgh, United States of America



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

Hande Öztürk1, I. Cevdet Noyan2

1Ozyegin University, Istanbul, TURKEY; 2Columbia University, New York, USA



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

Milan Milovanović1, Jelena Živković1, Dragan Ninković1, Jelena Blagojević Filipović1, Dubravka Vojislavljević–Vasilev1, Ivana Veljković2, Ivana Stanković2, Dušan Malenov3, Vesna Medaković3, Dušan Veljković3, Snežana Zarić3

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