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The seventh blind test of crystal structure prediction: structure ranking methods.

Authors :
Hunnisett LM
Francia N
Nyman J
Abraham NS
Aitipamula S
Alkhidir T
Almehairbi M
Anelli A
Anstine DM
Anthony JE
Arnold JE
Bahrami F
Bellucci MA
Beran GJO
Bhardwaj RM
Bianco R
Bis JA
Boese AD
Bramley J
Braun DE
Butler PWV
Cadden J
Carino S
Červinka C
Chan EJ
Chang C
Clarke SM
Coles SJ
Cook CJ
Cooper RI
Darden T
Day GM
Deng W
Dietrich H
DiPasquale A
Dhokale B
van Eijck BP
Elsegood MRJ
Firaha D
Fu W
Fukuzawa K
Galanakis N
Goto H
Greenwell C
Guo R
Harter J
Helfferich J
Hoja J
Hone J
Hong R
Hušák M
Ikabata Y
Isayev O
Ishaque O
Jain V
Jin Y
Jing A
Johnson ER
Jones I
Jose KVJ
Kabova EA
Keates A
Kelly PF
Klimeš J
Kostková V
Li H
Lin X
List A
Liu C
Liu YM
Liu Z
Lončarić I
Lubach JW
Ludík J
Maryewski AA
Marom N
Matsui H
Mattei A
Mayo RA
Melkumov JW
Mladineo B
Mohamed S
Momenzadeh Abardeh Z
Muddana HS
Nakayama N
Nayal KS
Neumann MA
Nikhar R
Obata S
O'Connor D
Oganov AR
Okuwaki K
Otero-de-la-Roza A
Parkin S
Parunov A
Podeszwa R
Price AJA
Price LS
Price SL
Probert MR
Pulido A
Ramteke GR
Rehman AU
Reutzel-Edens SM
Rogal J
Ross MJ
Rumson AF
Sadiq G
Saeed ZM
Salimi A
Sasikumar K
Sekharan S
Shankland K
Shi B
Shi X
Shinohara K
Skillman AG
Song H
Strasser N
van de Streek J
Sugden IJ
Sun G
Szalewicz K
Tan L
Tang K
Tarczynski F
Taylor CR
Tkatchenko A
Touš P
Tuckerman ME
Unzueta PA
Utsumi Y
Vogt-Maranto L
Weatherston J
Wilkinson LJ
Willacy RD
Wojtas L
Woollam GR
Yang Y
Yang Z
Yonemochi E
Yue X
Zeng Q
Zhou T
Zhou Y
Zubatyuk R
Cole JC
Source :
Acta crystallographica Section B, Structural science, crystal engineering and materials [Acta Crystallogr B Struct Sci Cryst Eng Mater] 2024 Dec 01. Date of Electronic Publication: 2024 Dec 01.
Publication Year :
2024
Publisher :
Ahead of Print

Abstract

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol <superscript>-1</superscript> at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases.<br /> (open access.)

Details

Language :
English
ISSN :
2052-5206
Database :
MEDLINE
Journal :
Acta crystallographica Section B, Structural science, crystal engineering and materials
Publication Type :
Academic Journal
Accession number :
39418598
Full Text :
https://doi.org/10.1107/S2052520624008679