DOI: 10.1039/c7sc04665k. Machine learning for the structure–energy–property landscapes of molecular crystals

Machine learning for the structure–energy–property landscapes of molecular crystals

10.1039/c7sc04665k

Crossref journal-article

Royal Society of Chemistry (RSC)

Chemical Science (292)

Abstract

Polymorphism is common in molecular crystals, whose energy landscapes usually contain many structures with similar stability, but very different physical–chemical properties. Machine-learning techniques can accelerate the evaluation of energy and properties by side-stepping accurate but demanding electronic-structure calculations, and provide a data-driven classification of the most important molecular packing motifs.

Bibliography

Musil, F., De, S., Yang, J., Campbell, J. E., Day, G. M., & Ceriotti, M. (2018). Machine learning for the structureâenergyâproperty landscapes of molecular crystals. Chemical Science, 9(5), 1289â1300.

Authors 6

Félix Musil (first)
Sandip De (additional)
Jack Yang (additional)
Joshua E. Campbell (additional)
Graeme M. Day (additional)
Michele Ceriotti (additional)

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Dates

Type	When
Created	7 years, 8 months ago (Dec. 12, 2017, 2:13 p.m.)
Deposited	1 year, 4 months ago (April 17, 2024, 7:38 p.m.)
Indexed	19 minutes ago (Aug. 26, 2025, 11:48 p.m.)
Issued	7 years, 7 months ago (Jan. 1, 2018)
Published	7 years, 7 months ago (Jan. 1, 2018)
Published Online	7 years, 7 months ago (Jan. 1, 2018)

Funders 3

H2020 European Research Council 10.13039/100010663
Region: Europe
gov (National government)
Labels17
1. H2020 Excellent Science - European Research Council
2. European Research Council
3. H2020 Wissenschaftsexzellenz - Für das Einzelziel 'Europäischer Forschungsrat (ERC)'
4. H2020 Ciencia Excelente - Consejo Europeo de Investigación (CEI)
5. H2020 Excellence Scientifique - Conseil européen de la recherche (CER)
6. H2020 Eccellenza Scientifica - Consiglio europeo della ricerca (CER)
7. H2020 Doskonała Baza Naukowa - Europejska Rada ds. Badań Naukowych (ERBN)
8. EXCELLENT SCIENCE - European Research Council
9. WISSENSCHAFTSEXZELLENZ - Für das Einzelziel 'Europäischer Forschungsrat
10. CIENCIA EXCELENTE - Consejo Europeo de Investigación
11. EXCELLENCE SCIENTIFIQUE - Conseil européen de la recherche
12. ECCELLENZA SCIENTIFICA - Consiglio europeo della ricerca
13. DOSKONAŁA BAZA NAUKOWA - Europejska Rada ds. Badań Naukowych
14. ERC
15. CEI
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17. ERBN
Awards1
1. 677013-HBMAP
Seventh Framework Programme 10.13039/100011102
Region: Europe
gov (National government)
Labels13
1. EC Seventh Framework Programm
2. European Commission Seventh Framework Programme
3. EU Seventh Framework Programme
4. European Union Seventh Framework Programme
5. EU 7th Framework Programme
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7. Siebten Rahmenprogramm
8. Séptimo Programa Marco
9. Septième programme-cadre
10. Settimo programma quadro
11. 7th Framework Programme
12. Seventh EU Framework Programme
13. FP7
Awards1
1. 307358, ERC-stG-2012-ANGLE
Swiss National Science Foundation 10.13039/501100001711 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Region: Europe
pri (Trusts, charities, foundations (both public and private))
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BibTeX

@article{Musil_2018, title={Machine learning for the structure–energy–property landscapes of molecular crystals}, volume={9}, ISSN={2041-6539}, url={http://dx.doi.org/10.1039/c7sc04665k}, DOI={10.1039/c7sc04665k}, number={5}, journal={Chemical Science}, publisher={Royal Society of Chemistry (RSC)}, author={Musil, Félix and De, Sandip and Yang, Jack and Campbell, Joshua E. and Day, Graeme M. and Ceriotti, Michele}, year={2018}, pages={1289–1300} }

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