Updates to the DScribe library : New descriptors and derivatives

Jarno Laakso; Lauri Himanen; Henrietta Homm; Eiaki V. Morooka; Marc O.J. Jäger; Milica Todorović; Patrick Rinke

doi:10.1063/5.0151031

Updates to the DScribe library : New descriptors and derivatives

Jarno Laakso^*, Lauri Himanen, Henrietta Homm, Eiaki V. Morooka, Marc O.J. Jäger, Milica Todorović, Patrick Rinke

^*Tämän työn vastaava kirjoittaja

University of Turku

Tutkimustuotos: Lehtiartikkeli › Article › Scientific › vertaisarvioitu

40 Sitaatiot (Scopus)

17 Lataukset (Pure)

Abstrakti

We present an update of the DScribe package, a Python library for atomistic descriptors. The update extends DScribe’s descriptor selection with the Valle-Oganov materials fingerprint and provides descriptor derivatives to enable more advanced machine learning tasks, such as force prediction and structure optimization. For all descriptors, numeric derivatives are now available in DScribe. For the many-body tensor representation (MBTR) and the Smooth Overlap of Atomic Positions (SOAP), we have also implemented analytic derivatives. We demonstrate the effectiveness of the descriptor derivatives for machine learning models of Cu clusters and perovskite alloys.

Alkuperäiskieli	Englanti
Artikkeli	234802
Sivut	1-8
Sivumäärä	8
Julkaisu	Journal of Chemical Physics
Vuosikerta	158
Numero	23
DOI - pysyväislinkit	https://doi.org/10.1063/5.0151031
Tila	Julkaistu - 21 kesäk. 2023
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Pääsy asiakirjaan

10.1063/5.0151031

Updates to the DScribe library - New descriptors and derivativesFinal published version, 5,5 MB

https://arxiv.org/abs/2303.14046

Muut tiedostot ja linkit

Linkki julkaisuun Scopuksessa

VILMA: Virtual laboratory for molecular level atmospheric transformations
Rinke, P. (Vastuullinen tutkija)
01/01/2022 → 31/12/2024
Projekti: RCF Centre of Excellence
NOMAD CoE: Novel Materials Discovery
Rinke, P. (Vastuullinen tutkija)
01/10/2020 → 30/09/2023
Projekti: EU H2020 Framework program
LEARNSOLAR: Rinke-LearnSolar
Rinke, P. (Vastuullinen tutkija)
01/09/2020 → 31/08/2024
Projekti: RCF Academy Project

Science-IT
Hakala, M. (Manager)
Perustieteiden korkeakoulu
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Siteeraa tätä

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title = "Updates to the DScribe library : New descriptors and derivatives",

abstract = "We present an update of the DScribe package, a Python library for atomistic descriptors. The update extends DScribe{\textquoteright}s descriptor selection with the Valle-Oganov materials fingerprint and provides descriptor derivatives to enable more advanced machine learning tasks, such as force prediction and structure optimization. For all descriptors, numeric derivatives are now available in DScribe. For the many-body tensor representation (MBTR) and the Smooth Overlap of Atomic Positions (SOAP), we have also implemented analytic derivatives. We demonstrate the effectiveness of the descriptor derivatives for machine learning models of Cu clusters and perovskite alloys.",

author = "Jarno Laakso and Lauri Himanen and Henrietta Homm and Morooka, {Eiaki V.} and J{\"a}ger, {Marc O.J.} and Milica Todorovi{\'c} and Patrick Rinke",

note = "Funding Information: We acknowledge the funding from the European Union{\textquoteright}s Horizon program under Grant Agreement No. 951786, the Academy of Finland through Project No. 334532, and the Center of Excellence Virtual Laboratory for Molecular Level Atmospheric Transformations (VILMA; Project No. 346377). We further acknowledge the CSC-IT Center for Science, Finland, and the Aalto Science-IT project. | openaire: EC/H2020/951786/EU//NOMAD CoE ",

year = "2023",

month = jun,

day = "21",

doi = "10.1063/5.0151031",

language = "English",

volume = "158",

pages = "1--8",

journal = "Journal of Chemical Physics",

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TY - JOUR

T1 - Updates to the DScribe library : New descriptors and derivatives

AU - Laakso, Jarno

AU - Himanen, Lauri

AU - Homm, Henrietta

AU - Morooka, Eiaki V.

AU - Jäger, Marc O.J.

AU - Todorović, Milica

AU - Rinke, Patrick

N1 - Funding Information: We acknowledge the funding from the European Union’s Horizon program under Grant Agreement No. 951786, the Academy of Finland through Project No. 334532, and the Center of Excellence Virtual Laboratory for Molecular Level Atmospheric Transformations (VILMA; Project No. 346377). We further acknowledge the CSC-IT Center for Science, Finland, and the Aalto Science-IT project. | openaire: EC/H2020/951786/EU//NOMAD CoE

PY - 2023/6/21

Y1 - 2023/6/21

N2 - We present an update of the DScribe package, a Python library for atomistic descriptors. The update extends DScribe’s descriptor selection with the Valle-Oganov materials fingerprint and provides descriptor derivatives to enable more advanced machine learning tasks, such as force prediction and structure optimization. For all descriptors, numeric derivatives are now available in DScribe. For the many-body tensor representation (MBTR) and the Smooth Overlap of Atomic Positions (SOAP), we have also implemented analytic derivatives. We demonstrate the effectiveness of the descriptor derivatives for machine learning models of Cu clusters and perovskite alloys.

AB - We present an update of the DScribe package, a Python library for atomistic descriptors. The update extends DScribe’s descriptor selection with the Valle-Oganov materials fingerprint and provides descriptor derivatives to enable more advanced machine learning tasks, such as force prediction and structure optimization. For all descriptors, numeric derivatives are now available in DScribe. For the many-body tensor representation (MBTR) and the Smooth Overlap of Atomic Positions (SOAP), we have also implemented analytic derivatives. We demonstrate the effectiveness of the descriptor derivatives for machine learning models of Cu clusters and perovskite alloys.

UR - http://www.scopus.com/inward/record.url?scp=85162717051&partnerID=8YFLogxK

U2 - 10.1063/5.0151031

DO - 10.1063/5.0151031

M3 - Article

C2 - 37338028

AN - SCOPUS:85162717051

SN - 0021-9606

VL - 158

SP - 1

EP - 8

JO - Journal of Chemical Physics

JF - Journal of Chemical Physics

IS - 23

M1 - 234802

ER -

Updates to the DScribe library : New descriptors and derivatives

Abstrakti

Pääsy asiakirjaan

Muut tiedostot ja linkit

Sormenjälki

Projektit

VILMA: Virtual laboratory for molecular level atmospheric transformations

NOMAD CoE: Novel Materials Discovery

LEARNSOLAR: Rinke-LearnSolar

Laitteet

Science-IT

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