Application-oriented design of machine learning paradigms for battery science

In the development of battery science, machine learning (ML) has been widely employed to predict material properties, monitor morphological variations, learn the underlying physical rules and simplify the material-discovery processes. However, the widespread adoption of ML in battery research has en...

Full description

Saved in:
Bibliographic Details
Published innpj computational materials Vol. 11; no. 1; pp. 89 - 18
Main Author Wang, Ying
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 02.04.2025
Nature Publishing Group
Nature Portfolio
Subjects
639/166/987
639/301/1034/1037
639/301/299/891
Algorithms
Artificial intelligence
Automation
Characterization and Evaluation of Materials
Chemistry and Materials Science
Computational Intelligence
Datasets
Electrolytes
Energy consumption
Learning algorithms
Machine learning
Material properties
Materials Science
Mathematical and Computational Engineering
Mathematical and Computational Physics
Mathematical Modeling and Industrial Mathematics
Neural networks
Optimization
Perspective
Polymers
Science
Simulation
Software engineering
Theoretical
Online AccessGet full text

Cover

Abstract In the development of battery science, machine learning (ML) has been widely employed to predict material properties, monitor morphological variations, learn the underlying physical rules and simplify the material-discovery processes. However, the widespread adoption of ML in battery research has encountered limitations, such as the incomplete and unfocused databases, the low model accuracy and the difficulty in realizing experimental validation. It is significant to construct the dataset containing specific-domain knowledge with suitable ML models for battery research from the application-oriented perspective. We outline five key challenges in the field and highlight potential research directions that can unlock the full potential of ML in advancing battery technologies.
AbstractList In the development of battery science, machine learning (ML) has been widely employed to predict material properties, monitor morphological variations, learn the underlying physical rules and simplify the material-discovery processes. However, the widespread adoption of ML in battery research has encountered limitations, such as the incomplete and unfocused databases, the low model accuracy and the difficulty in realizing experimental validation. It is significant to construct the dataset containing specific-domain knowledge with suitable ML models for battery research from the application-oriented perspective. We outline five key challenges in the field and highlight potential research directions that can unlock the full potential of ML in advancing battery technologies.
Abstract In the development of battery science, machine learning (ML) has been widely employed to predict material properties, monitor morphological variations, learn the underlying physical rules and simplify the material-discovery processes. However, the widespread adoption of ML in battery research has encountered limitations, such as the incomplete and unfocused databases, the low model accuracy and the difficulty in realizing experimental validation. It is significant to construct the dataset containing specific-domain knowledge with suitable ML models for battery research from the application-oriented perspective. We outline five key challenges in the field and highlight potential research directions that can unlock the full potential of ML in advancing battery technologies.
ArticleNumber 89
Author Wang, Ying
Author_xml – sequence: 1
  givenname: Ying
  orcidid: 0000-0002-7459-1152
  surname: Wang
  fullname: Wang, Ying
  email: wying@fudan.edu.cn
  organization: State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Research center of AI for Polymer Science, Fudan University
BookMark eNp9kU1LxTAQRYMoqE__gKuC6-rks-lSxC9Q3Og6pMm05vFeUpO68N9bragrVxnCPWcG7iHZjSkiIScUzihwfV4ElUzUwGQNVDaybnfIAQPZ1LxVsPtn3ifHpawBgLZMMwEH5OFiHDfB2SmkWKccME7oK48lDLFKfbW17iVErDZocwxxqEabrQ_DtlR9ylVnpwnze1XcTDo8Inu93RQ8_n5X5Pn66unytr5_vLm7vLivHddsqoXmwNtOg_cd7xqwrlGopHCOI3O960Bo6DjjfeesQt9bYa3XwmvP0fUNX5G7xeuTXZsxh63N7ybZYL4-Uh6MzVNwGzS6o04Cp05RIUCh1kpiKxsmqFKUy9l1urjGnF7fsExmnd5ynM83nGopQbX0M8WWlMuplIz9z1YK5rMFs7Rg5hbMVwumnSG-QGUOxwHzr_of6gNJvouF
Cites_doi 10.1021/acs.chemrev.6b00504
10.1016/j.joule.2023.03.008
10.1016/j.jpowsour.2024.234272
10.1038/nmat3568
10.1038/s41586-023-06735-9
10.1002/aenm.202401644
10.1002/admi.202101734
10.1038/s41524-024-01470-9
10.1038/s41586-022-04503-9
10.1038/s41586-019-1682-5
10.1016/j.jclepro.2020.124152
10.1038/s41524-022-00951-z
10.1149/2.0521916jes
10.1002/adma.202101474
10.1002/adma.201505183
10.1016/j.rser.2023.114136
10.1038/s41524-022-00858-9
10.1038/s41524-020-0340-7
10.1103/PhysRevB.97.094106
10.1016/j.energy.2024.130764
10.1002/aenm.202400956
10.1109/TII.2023.3257299
10.1021/acsmaterialslett.3c00253
10.1038/s41586-018-0337-2
10.1109/ACCESS.2022.3151975
10.1038/s41586-022-05627-8
10.1038/s41467-023-43883-y
10.1038/srep29356
10.1021/acsenergylett.2c01898
10.1016/j.commatsci.2022.111984
10.1038/s41467-022-29837-w
10.1016/j.commatsci.2012.02.005
10.1038/s41467-019-13214-1
10.1126/sciadv.aba4098
10.1149/2.0142001JES
10.1038/s41560-020-0655-0
10.1021/acsami.4c00624
10.1038/s41467-022-29939-5
10.1021/acs.jpclett.4c00698
10.1038/nmat3602
10.1002/smm2.1183
10.1038/s41467-019-13362-4
10.1016/j.rser.2022.113053
10.1039/D1EE01136G
10.1038/natrevmats.2016.103
10.1038/s42256-020-0156-7
10.1039/D4TA00136B
10.1021/acsami.9b04933
10.1021/acs.accounts.6b00308
10.1002/aenm.202304480
10.1038/s41467-022-30994-1
10.1021/acsami.1c21683
10.1039/D4TA00361F
10.1002/aenm.202102917
10.1007/s11837-016-2001-3
10.1021/acsenergylett.1c02602
10.1038/s41524-023-01039-y
10.1063/5.0015872
10.1038/s41560-023-01194-y
10.1021/acsenergylett.1c00332
10.1126/sciadv.abn4372
10.1038/s41467-022-32422-w
10.1088/2399-6528/ab92d8
10.1016/j.nanoen.2022.107214
10.1016/j.ensm.2022.12.040
10.1016/j.commatsci.2016.02.021
10.1021/acs.chemmater.8b03272
10.1007/s10845-022-01936-x
10.1007/978-3-030-99666-6_123
10.1021/acs.jpclett.9b03664
10.1146/annurev-physchem-042018-052331
10.1016/j.resconrec.2022.106207
10.1038/s41563-021-00995-4
10.1016/j.nanoms.2023.08.002
10.1016/j.joule.2021.10.001
10.1021/acsami.3c18448
10.1038/s41560-019-0356-8
10.1038/s41586-022-04501-x
10.1038/s41467-021-26480-9
10.1038/s41578-021-00340-w
10.1016/j.ensm.2020.06.033
10.1038/npjcompumats.2015.10
10.1073/pnas.2214357120
10.1038/s41563-020-0777-6
10.1038/s42256-021-00312-3
10.1038/s41467-023-37034-6
10.1038/s43588-022-00349-3
10.1038/s43588-023-00563-7
10.1038/s41524-022-00713-x
10.1016/j.joule.2023.08.007
10.1021/acs.jpclett.1c01605
10.1021/jacs.3c08346
10.1038/s41586-020-1994-5
10.1016/j.polymertesting.2022.107796
10.1063/1.4812323
10.1016/j.jmat.2017.02.002
10.1016/j.ensm.2024.103710
10.1002/adts.202100196
10.1038/s41598-021-94275-5
10.1038/s41467-019-08756-3
10.1021/acs.jpcc.1c06821
10.1063/1.5016317
10.1021/jacs.9b11442
10.1038/s41467-022-33957-8
10.1016/j.energy.2024.132395
10.1021/ja045155b
10.1016/j.procs.2022.12.383
10.1002/batt.202300046
10.1038/s41467-020-15235-7
10.1038/nchem.121
10.1038/s41524-021-00554-0
10.1016/j.heliyon.2023.e17754
10.1038/s41560-023-01279-8
10.1016/j.ensm.2022.12.034
10.1038/s41586-021-03885-6
10.1038/s41467-023-38493-7
10.3390/ma15031157
10.1016/j.joule.2022.08.008
10.1016/j.jpowsour.2024.234156
10.1007/s10822-020-00346-6
10.1038/s41560-019-0405-3
ContentType Journal Article
Copyright The Author(s) 2025
Copyright Nature Publishing Group 2025
Copyright_xml – notice: The Author(s) 2025
– notice: Copyright Nature Publishing Group 2025
DBID C6C
AAYXX
CITATION
3V.
7X7
7XB
8FE
8FG
8FH
8FI
8FJ
8FK
ABJCF
ABUWG
AFKRA
AZQEC
BBNVY
BENPR
BGLVJ
BHPHI
CCPQU
D1I
DWQXO
FYUFA
GHDGH
GNUQQ
HCIFZ
K9.
KB.
LK8
M0S
M7P
PDBOC
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
DOA
DOI 10.1038/s41524-025-01575-9
DatabaseName Springer Nature OA Free Journals
CrossRef
ProQuest Central (Corporate)
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Natural Science Journals
Hospital Premium Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
Materials Science & Engineering Collection
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
Biological Science Collection
ProQuest Central
Technology Collection
Natural Science Collection
ProQuest One
ProQuest Materials Science Collection
ProQuest Central Korea
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
SciTech Premium Collection
ProQuest Health & Medical Complete (Alumni)
Materials Science Database
Biological Sciences
ProQuest Health & Medical Collection
Biological Science Database
Materials Science Collection
ProQuest Central Premium
ProQuest One Academic (New)
Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
ProQuest Central Student
Technology Collection
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
Materials Science Collection
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest Natural Science Collection
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
Health Research Premium Collection
Health and Medicine Complete (Alumni Edition)
Natural Science Collection
ProQuest Central Korea
Biological Science Collection
Materials Science Database
ProQuest Central (New)
ProQuest Materials Science Collection
ProQuest Biological Science Collection
ProQuest One Academic Eastern Edition
ProQuest Hospital Collection
ProQuest Technology Collection
Health Research Premium Collection (Alumni)
Biological Science Database
ProQuest SciTech Collection
ProQuest Hospital Collection (Alumni)
ProQuest Health & Medical Complete
ProQuest One Academic UKI Edition
Materials Science & Engineering Collection
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
DatabaseTitleList Publicly Available Content Database
CrossRef
Database_xml – sequence: 1
  dbid: C6C
  name: Springer Nature OA Free Journals (WRLC)
  url: http://www.springeropen.com/
  sourceTypes: Publisher
– sequence: 2
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 3
  dbid: 8FG
  name: ProQuest Technology Collection
  url: https://search.proquest.com/technologycollection1
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 2057-3960
EndPage 18
ExternalDocumentID oai_doaj_org_article_8b1c5031c614406e8865e95724166135
10_1038_s41524_025_01575_9
GrantInformation_xml – fundername: National Natural Science Foundation of China (National Science Foundation of China)
  grantid: 92372126; 52373203
  funderid: https://doi.org/10.13039/501100001809
GroupedDBID 0R~
5VS
7X7
8FE
8FG
8FH
8FI
8FJ
AAJSJ
AASML
ABJCF
ABUWG
ACGFS
ADBBV
ADMLS
AFKRA
AJTQC
ALIPV
ALMA_UNASSIGNED_HOLDINGS
ARCSS
BBNVY
BCNDV
BENPR
BGLVJ
BHPHI
BPHCQ
BVXVI
C6C
CCPQU
D1I
EBLON
EBS
FYUFA
GROUPED_DOAJ
HCIFZ
HMCUK
KB.
KQ8
LK8
M7P
M~E
NAO
NO~
OK1
PDBOC
PHGZT
PIMPY
PQQKQ
PROAC
RNT
SNYQT
UKHRP
AAYXX
CITATION
PHGZM
3V.
7XB
8FK
AARCD
AZQEC
DWQXO
GNUQQ
K9.
PKEHL
PQEST
PQGLB
PQUKI
PRINS
PUEGO
ID FETCH-LOGICAL-c382t-483039b80ddb3b70ac76e654cc3e2cfcb0480b323fbca6edfa4aad84d8d3ecf73
IEDL.DBID 7X7
ISSN 2057-3960
IngestDate Wed Aug 27 01:32:38 EDT 2025
Wed Aug 13 04:10:57 EDT 2025
Tue Jul 01 04:53:32 EDT 2025
Thu Apr 03 03:05:09 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c382t-483039b80ddb3b70ac76e654cc3e2cfcb0480b323fbca6edfa4aad84d8d3ecf73
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0002-7459-1152
OpenAccessLink https://www.proquest.com/docview/3185506915?pq-origsite=%requestingapplication%
PQID 3185506915
PQPubID 2041924
PageCount 18
ParticipantIDs doaj_primary_oai_doaj_org_article_8b1c5031c614406e8865e95724166135
proquest_journals_3185506915
crossref_primary_10_1038_s41524_025_01575_9
springer_journals_10_1038_s41524_025_01575_9
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2025-04-02
PublicationDateYYYYMMDD 2025-04-02
PublicationDate_xml – month: 04
  year: 2025
  text: 2025-04-02
  day: 02
PublicationDecade 2020
PublicationPlace London
PublicationPlace_xml – name: London
PublicationTitle npj computational materials
PublicationTitleAbbrev npj Comput Mater
PublicationYear 2025
Publisher Nature Publishing Group UK
Nature Publishing Group
Nature Portfolio
Publisher_xml – name: Nature Publishing Group UK
– name: Nature Publishing Group
– name: Nature Portfolio
References Z Yang (1575_CR15) 2024; 10
M Scheffler (1575_CR16) 2022; 604
MABH Susan (1575_CR92) 2005; 127
Y Zhang (1575_CR10) 2019; 10
M Attarian Shandiz (1575_CR34) 2016; 117
Y Hao (1575_CR99) 2024; 20
Z Wei (1575_CR98) 2023; 56
J Wu (1575_CR55) 2016; 6
T Morawietz (1575_CR69) 2021; 35
C Chen (1575_CR80) 2022; 2
A Manthiram (1575_CR67) 2017; 2
D Ge (1575_CR109) 2024; 305
C Duan (1575_CR14) 2023; 3
1575_CR12
1575_CR11
D Roman (1575_CR110) 2021; 3
1575_CR13
C Yang (1575_CR89) 2021; 598
A Jain (1575_CR19) 2013; 1
B Blaiszik (1575_CR22) 2016; 68
M Watanabe (1575_CR91) 2017; 117
Y Huang (1575_CR52) 2023; 9
J Jeong (1575_CR37) 2024; 16
A Hajibabaei (1575_CR79) 2021; 12
Y Li (1575_CR50) 2023; 5
J Neumann (1575_CR117) 2022; 12
S Curtarolo (1575_CR20) 2012; 58
1575_CR84
TP Lodge (1575_CR93) 2016; 49
S Kirklin (1575_CR21) 2015; 1
G Harper (1575_CR64) 2019; 575
S Park (1575_CR38) 2021; 14
RJ Zhu (1575_CR73) 2024; 15
Y Liu (1575_CR96) 2019; 4
X Zhang (1575_CR41) 2022; 8
1575_CR83
M-F Ng (1575_CR105) 2020; 2
JW Lee (1575_CR82) 2024; 12
C Lv (1575_CR2) 2022; 34
J Zhu (1575_CR107) 2022; 13
SC Kim (1575_CR29) 2023; 120
A Ran (1575_CR125) 2022; 7
PO Dral (1575_CR17) 2020; 11
KT Butler (1575_CR6) 2018; 559
JF Whitacre (1575_CR61) 2019; 166
ZM Konz (1575_CR101) 2023; 8
1575_CR9
Y Xu (1575_CR76) 2020; 4
M Duquesnoy (1575_CR65) 2023; 56
SJ Honrao (1575_CR47) 2021; 11
S Tao (1575_CR118) 2024; 597
Q Hu (1575_CR71) 2024; 5
J Li (1575_CR72) 2024; 14
Y Wang (1575_CR90) 2019; 10
Y Cai (1575_CR115) 2023; 9
DG Mackanic (1575_CR86) 2019; 10
T Xie (1575_CR87) 2022; 13
S Haghi (1575_CR66) 2023; 6
1575_CR62
K Li (1575_CR68) 2024; 14
AD Sendek (1575_CR70) 2019; 31
A Garg (1575_CR124) 2020; 275
W Yan (1575_CR57) 2023; 8
J Xu (1575_CR60) 2023; 614
M Cheng (1575_CR123) 2023; 173
C Ling (1575_CR1) 2022; 8
S Xu (1575_CR42) 2021; 125
CH Liow (1575_CR44) 2022; 98
SJ Harris (1575_CR103) 2023; 7
S Fujikake (1575_CR53) 2018; 148
1575_CR102
S Curtarolo (1575_CR24) 2013; 12
M Ahmadi (1575_CR27) 2021; 5
Y Liu (1575_CR3) 2020; 31
1575_CR54
1575_CR100
Y-T Chen (1575_CR85) 2021; 6
F Noé (1575_CR18) 2020; 71
B Onat (1575_CR56) 2018; 97
K Li (1575_CR7) 2023; 14
Y-T Liu (1575_CR8) 2022; 13
K Daems (1575_CR31) 2024; 191
L Ward (1575_CR4) 2022; 6
KA Severson (1575_CR108) 2019; 4
A Wołos (1575_CR77) 2022; 604
GLW Hart (1575_CR58) 2021; 6
W Song (1575_CR113) 2023; 217
P Seitz (1575_CR48) 2023; 218
ZJ Baum (1575_CR116) 2022; 7
S Batzner (1575_CR81) 2022; 13
R Bouchet (1575_CR88) 2013; 12
S Müller (1575_CR51) 2021; 12
1575_CR40
K Hatakeyama-Sato (1575_CR94) 2020; 142
PK Jones (1575_CR111) 2022; 13
CJ Hargreaves (1575_CR75) 2023; 9
Y Wang (1575_CR95) 2016; 28
V Fung (1575_CR25) 2021; 7
X Wang (1575_CR33) 2017; 3
Z Nozarijouybari (1575_CR104) 2024; 601
P Friederich (1575_CR78) 2021; 20
B Jagger (1575_CR30) 2023; 7
1575_CR121
Y Liang (1575_CR39) 2020; 5
X He (1575_CR36) 2024; 16
A Dave (1575_CR63) 2020; 167
G Houchins (1575_CR32) 2020; 153
C Qian (1575_CR106) 2024; 294
A Merchant (1575_CR46) 2023; 624
JK Nørskov (1575_CR23) 2009; 1
S Tao (1575_CR120) 2023; 14
A Gayon-Lombardo (1575_CR45) 2020; 6
Y Wang (1575_CR59) 2021; 20
1575_CR26
1575_CR28
Y Zhang (1575_CR112) 2020; 11
K Meng (1575_CR122) 2022; 182
J Du (1575_CR43) 2024; 12
G Xu (1575_CR5) 2024; 72
D Chen (1575_CR114) 2022; 10
PM Attia (1575_CR97) 2020; 578
RP Joshi (1575_CR35) 2019; 11
K Wang (1575_CR49) 2023; 14
F Yang (1575_CR74) 2024; 6
1575_CR119
References_xml – volume: 117
  start-page: 7190
  year: 2017
  ident: 1575_CR91
  publication-title: Chem. Rev.
  doi: 10.1021/acs.chemrev.6b00504
– volume: 7
  start-page: 920
  year: 2023
  ident: 1575_CR103
  publication-title: Joule
  doi: 10.1016/j.joule.2023.03.008
– volume: 601
  year: 2024
  ident: 1575_CR104
  publication-title: J. Power Sources
  doi: 10.1016/j.jpowsour.2024.234272
– volume: 12
  start-page: 191
  year: 2013
  ident: 1575_CR24
  publication-title: Nat. Mater.
  doi: 10.1038/nmat3568
– volume: 624
  start-page: 80
  year: 2023
  ident: 1575_CR46
  publication-title: Nature
  doi: 10.1038/s41586-023-06735-9
– ident: 1575_CR102
  doi: 10.1002/aenm.202401644
– ident: 1575_CR84
  doi: 10.1002/admi.202101734
– volume: 10
  year: 2024
  ident: 1575_CR15
  publication-title: npj Computational Mater.
  doi: 10.1038/s41524-024-01470-9
– volume: 604
  start-page: 668
  year: 2022
  ident: 1575_CR77
  publication-title: Nature
  doi: 10.1038/s41586-022-04503-9
– volume: 575
  start-page: 75
  year: 2019
  ident: 1575_CR64
  publication-title: Nature
  doi: 10.1038/s41586-019-1682-5
– volume: 275
  start-page: 124152
  year: 2020
  ident: 1575_CR124
  publication-title: J. Clean. Prod.
  doi: 10.1016/j.jclepro.2020.124152
– volume: 9
  year: 2023
  ident: 1575_CR75
  publication-title: npj Computational Mater.
  doi: 10.1038/s41524-022-00951-z
– volume: 166
  start-page: A4181
  year: 2019
  ident: 1575_CR61
  publication-title: J. Electrochem. Soc.
  doi: 10.1149/2.0521916jes
– volume: 5
  start-page: 100159
  year: 2024
  ident: 1575_CR71
  publication-title: Energy
– volume: 34
  year: 2022
  ident: 1575_CR2
  publication-title: Adv. Mater.
  doi: 10.1002/adma.202101474
– volume: 28
  start-page: 2571
  year: 2016
  ident: 1575_CR95
  publication-title: Adv. Mater.
  doi: 10.1002/adma.201505183
– volume: 191
  start-page: 114136
  year: 2024
  ident: 1575_CR31
  publication-title: Renew. Sustain. Energy Rev.
  doi: 10.1016/j.rser.2023.114136
– volume: 8
  year: 2022
  ident: 1575_CR41
  publication-title: npj Computational Mater.
  doi: 10.1038/s41524-022-00858-9
– volume: 6
  year: 2020
  ident: 1575_CR45
  publication-title: npj Computational Mater.
  doi: 10.1038/s41524-020-0340-7
– volume: 97
  start-page: 094106
  year: 2018
  ident: 1575_CR56
  publication-title: Phys. Rev. B
  doi: 10.1103/PhysRevB.97.094106
– volume: 294
  start-page: 130764
  year: 2024
  ident: 1575_CR106
  publication-title: Energy
  doi: 10.1016/j.energy.2024.130764
– volume: 14
  start-page: 2400956
  year: 2024
  ident: 1575_CR68
  publication-title: Adv. Energy Mater.
  doi: 10.1002/aenm.202400956
– volume: 20
  start-page: 127
  year: 2024
  ident: 1575_CR99
  publication-title: IEEE Trans. Ind. Inform.
  doi: 10.1109/TII.2023.3257299
– volume: 5
  start-page: 2948
  year: 2023
  ident: 1575_CR50
  publication-title: ACS Mater. Lett.
  doi: 10.1021/acsmaterialslett.3c00253
– volume: 559
  start-page: 547
  year: 2018
  ident: 1575_CR6
  publication-title: Nature
  doi: 10.1038/s41586-018-0337-2
– volume: 10
  start-page: 19621
  year: 2022
  ident: 1575_CR114
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2022.3151975
– ident: 1575_CR12
– volume: 614
  start-page: 694
  year: 2023
  ident: 1575_CR60
  publication-title: Nature
  doi: 10.1038/s41586-022-05627-8
– volume: 14
  year: 2023
  ident: 1575_CR120
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-023-43883-y
– volume: 6
  year: 2016
  ident: 1575_CR55
  publication-title: Sci. Rep.
  doi: 10.1038/srep29356
– volume: 7
  start-page: 3817
  year: 2022
  ident: 1575_CR125
  publication-title: ACS Energy Lett.
  doi: 10.1021/acsenergylett.2c01898
– volume: 218
  start-page: 111984
  year: 2023
  ident: 1575_CR48
  publication-title: Computational Mater. Sci.
  doi: 10.1016/j.commatsci.2022.111984
– volume: 13
  year: 2022
  ident: 1575_CR107
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-022-29837-w
– volume: 58
  start-page: 218
  year: 2012
  ident: 1575_CR20
  publication-title: Computational Mater. Sci.
  doi: 10.1016/j.commatsci.2012.02.005
– volume: 10
  year: 2019
  ident: 1575_CR10
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-019-13214-1
– ident: 1575_CR28
  doi: 10.1126/sciadv.aba4098
– volume: 167
  start-page: 013514
  year: 2020
  ident: 1575_CR63
  publication-title: J. Electrochem. Soc.
  doi: 10.1149/2.0142001JES
– volume: 5
  start-page: 646
  year: 2020
  ident: 1575_CR39
  publication-title: Nat. Energy
  doi: 10.1038/s41560-020-0655-0
– volume: 16
  start-page: 24494
  year: 2024
  ident: 1575_CR36
  publication-title: ACS Appl. Mater. Interfaces
  doi: 10.1021/acsami.4c00624
– volume: 13
  year: 2022
  ident: 1575_CR81
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-022-29939-5
– volume: 15
  start-page: 5191
  year: 2024
  ident: 1575_CR73
  publication-title: J. Phys. Chem. Lett.
  doi: 10.1021/acs.jpclett.4c00698
– volume: 12
  start-page: 452
  year: 2013
  ident: 1575_CR88
  publication-title: Nat. Mater.
  doi: 10.1038/nmat3602
– ident: 1575_CR83
  doi: 10.1002/smm2.1183
– volume: 10
  year: 2019
  ident: 1575_CR86
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-019-13362-4
– volume: 173
  start-page: 113053
  year: 2023
  ident: 1575_CR123
  publication-title: Renew. Sustain. Energy Rev.
  doi: 10.1016/j.rser.2022.113053
– volume: 14
  start-page: 5864
  year: 2021
  ident: 1575_CR38
  publication-title: Energy Environ. Sci.
  doi: 10.1039/D1EE01136G
– ident: 1575_CR11
– volume: 2
  start-page: 16103
  year: 2017
  ident: 1575_CR67
  publication-title: Nat. Rev. Mater.
  doi: 10.1038/natrevmats.2016.103
– volume: 2
  start-page: 161
  year: 2020
  ident: 1575_CR105
  publication-title: Nat. Mach. Intell.
  doi: 10.1038/s42256-020-0156-7
– volume: 12
  start-page: 12034
  year: 2024
  ident: 1575_CR43
  publication-title: J. Mater. Chem. A
  doi: 10.1039/D4TA00136B
– volume: 11
  start-page: 18494
  year: 2019
  ident: 1575_CR35
  publication-title: ACS Appl. Mater. Interfaces
  doi: 10.1021/acsami.9b04933
– volume: 49
  start-page: 2107
  year: 2016
  ident: 1575_CR93
  publication-title: Acc. Chem. Res
  doi: 10.1021/acs.accounts.6b00308
– volume: 14
  start-page: 2304480
  year: 2024
  ident: 1575_CR72
  publication-title: Adv. Energy Mater.
  doi: 10.1002/aenm.202304480
– volume: 13
  year: 2022
  ident: 1575_CR87
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-022-30994-1
– ident: 1575_CR100
  doi: 10.1021/acsami.1c21683
– volume: 12
  start-page: 7272
  year: 2024
  ident: 1575_CR82
  publication-title: J. Mater. Chem. A
  doi: 10.1039/D4TA00361F
– volume: 12
  start-page: 2102917
  year: 2022
  ident: 1575_CR117
  publication-title: Adv. Energy Mater.
  doi: 10.1002/aenm.202102917
– volume: 68
  start-page: 2045
  year: 2016
  ident: 1575_CR22
  publication-title: JOM
  doi: 10.1007/s11837-016-2001-3
– volume: 7
  start-page: 712
  year: 2022
  ident: 1575_CR116
  publication-title: ACS Energy Lett.
  doi: 10.1021/acsenergylett.1c02602
– volume: 9
  year: 2023
  ident: 1575_CR52
  publication-title: npj Computational Mater.
  doi: 10.1038/s41524-023-01039-y
– volume: 153
  start-page: 054124
  year: 2020
  ident: 1575_CR32
  publication-title: J. Chem. Phys.
  doi: 10.1063/5.0015872
– volume: 8
  start-page: 450
  year: 2023
  ident: 1575_CR101
  publication-title: Nat. Energy
  doi: 10.1038/s41560-023-01194-y
– volume: 6
  start-page: 1639
  year: 2021
  ident: 1575_CR85
  publication-title: ACS Energy Lett.
  doi: 10.1021/acsenergylett.1c00332
– ident: 1575_CR54
  doi: 10.1126/sciadv.abn4372
– volume: 13
  year: 2022
  ident: 1575_CR111
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-022-32422-w
– volume: 4
  start-page: 055015
  year: 2020
  ident: 1575_CR76
  publication-title: J. Phys. Commun.
  doi: 10.1088/2399-6528/ab92d8
– volume: 98
  start-page: 107214
  year: 2022
  ident: 1575_CR44
  publication-title: Nano Energy
  doi: 10.1016/j.nanoen.2022.107214
– volume: 56
  start-page: 50
  year: 2023
  ident: 1575_CR65
  publication-title: Energy Storage Mater.
  doi: 10.1016/j.ensm.2022.12.040
– volume: 117
  start-page: 270
  year: 2016
  ident: 1575_CR34
  publication-title: Computational Mater. Sci.
  doi: 10.1016/j.commatsci.2016.02.021
– volume: 31
  start-page: 342
  year: 2019
  ident: 1575_CR70
  publication-title: Chem. Mater.
  doi: 10.1021/acs.chemmater.8b03272
– ident: 1575_CR121
  doi: 10.1007/s10845-022-01936-x
– ident: 1575_CR119
  doi: 10.1007/978-3-030-99666-6_123
– volume: 11
  start-page: 2336
  year: 2020
  ident: 1575_CR17
  publication-title: J. Phys. Chem. Lett.
  doi: 10.1021/acs.jpclett.9b03664
– volume: 71
  start-page: 361
  year: 2020
  ident: 1575_CR18
  publication-title: Annu. Rev. Phys. Chem.
  doi: 10.1146/annurev-physchem-042018-052331
– volume: 182
  start-page: 106207
  year: 2022
  ident: 1575_CR122
  publication-title: Resour. Conserv. Recycling
  doi: 10.1016/j.resconrec.2022.106207
– volume: 20
  start-page: 1255
  year: 2021
  ident: 1575_CR59
  publication-title: Nat. Mater.
  doi: 10.1038/s41563-021-00995-4
– volume: 6
  start-page: 256
  year: 2024
  ident: 1575_CR74
  publication-title: Nano Mater. Sci.
  doi: 10.1016/j.nanoms.2023.08.002
– volume: 5
  start-page: 2797
  year: 2021
  ident: 1575_CR27
  publication-title: Joule
  doi: 10.1016/j.joule.2021.10.001
– volume: 16
  start-page: 24431
  year: 2024
  ident: 1575_CR37
  publication-title: ACS Appl. Mater. Interfaces
  doi: 10.1021/acsami.3c18448
– volume: 4
  start-page: 383
  year: 2019
  ident: 1575_CR108
  publication-title: Nat. Energy
  doi: 10.1038/s41560-019-0356-8
– volume: 604
  start-page: 635
  year: 2022
  ident: 1575_CR16
  publication-title: Nature
  doi: 10.1038/s41586-022-04501-x
– volume: 12
  year: 2021
  ident: 1575_CR51
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-021-26480-9
– volume: 6
  start-page: 730
  year: 2021
  ident: 1575_CR58
  publication-title: Nat. Rev. Mater.
  doi: 10.1038/s41578-021-00340-w
– volume: 31
  start-page: 434
  year: 2020
  ident: 1575_CR3
  publication-title: Energy Storage Mater.
  doi: 10.1016/j.ensm.2020.06.033
– volume: 1
  year: 2015
  ident: 1575_CR21
  publication-title: npj Computational Mater.
  doi: 10.1038/npjcompumats.2015.10
– ident: 1575_CR13
– volume: 120
  start-page: e2214357120
  year: 2023
  ident: 1575_CR29
  publication-title: Proc. Natl Acad. Sci. USA
  doi: 10.1073/pnas.2214357120
– volume: 20
  start-page: 750
  year: 2021
  ident: 1575_CR78
  publication-title: Nat. Mater.
  doi: 10.1038/s41563-020-0777-6
– volume: 3
  start-page: 447
  year: 2021
  ident: 1575_CR110
  publication-title: Nat. Mach. Intell.
  doi: 10.1038/s42256-021-00312-3
– volume: 14
  year: 2023
  ident: 1575_CR49
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-023-37034-6
– volume: 2
  start-page: 718
  year: 2022
  ident: 1575_CR80
  publication-title: Nat. Computational Sci.
  doi: 10.1038/s43588-022-00349-3
– volume: 3
  start-page: 1045
  year: 2023
  ident: 1575_CR14
  publication-title: Nat. Computational Sci.
  doi: 10.1038/s43588-023-00563-7
– volume: 8
  year: 2022
  ident: 1575_CR1
  publication-title: npj Computational Mater.
  doi: 10.1038/s41524-022-00713-x
– volume: 7
  start-page: 2228
  year: 2023
  ident: 1575_CR30
  publication-title: Joule
  doi: 10.1016/j.joule.2023.08.007
– volume: 12
  start-page: 8115
  year: 2021
  ident: 1575_CR79
  publication-title: J. Phys. Chem. Lett.
  doi: 10.1021/acs.jpclett.1c01605
– ident: 1575_CR62
  doi: 10.1021/jacs.3c08346
– volume: 578
  start-page: 397
  year: 2020
  ident: 1575_CR97
  publication-title: Nature
  doi: 10.1038/s41586-020-1994-5
– ident: 1575_CR9
  doi: 10.1016/j.polymertesting.2022.107796
– volume: 1
  start-page: 011002
  year: 2013
  ident: 1575_CR19
  publication-title: APL Mater.
  doi: 10.1063/1.4812323
– volume: 3
  start-page: 178
  year: 2017
  ident: 1575_CR33
  publication-title: J. Materiomics
  doi: 10.1016/j.jmat.2017.02.002
– volume: 72
  year: 2024
  ident: 1575_CR5
  publication-title: Energy Storage Mater.
  doi: 10.1016/j.ensm.2024.103710
– ident: 1575_CR40
  doi: 10.1002/adts.202100196
– volume: 11
  year: 2021
  ident: 1575_CR47
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-021-94275-5
– volume: 10
  year: 2019
  ident: 1575_CR90
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-019-08756-3
– volume: 125
  start-page: 21352
  year: 2021
  ident: 1575_CR42
  publication-title: J. Phys. Chem. C.
  doi: 10.1021/acs.jpcc.1c06821
– volume: 148
  start-page: 241714
  year: 2018
  ident: 1575_CR53
  publication-title: J. Chem. Phys.
  doi: 10.1063/1.5016317
– volume: 142
  start-page: 3301
  year: 2020
  ident: 1575_CR94
  publication-title: J. Am. Chem. Soc.
  doi: 10.1021/jacs.9b11442
– volume: 13
  year: 2022
  ident: 1575_CR8
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-022-33957-8
– volume: 305
  start-page: 132395
  year: 2024
  ident: 1575_CR109
  publication-title: Energy
  doi: 10.1016/j.energy.2024.132395
– volume: 127
  start-page: 4976
  year: 2005
  ident: 1575_CR92
  publication-title: J. Am. Chem. Soc.
  doi: 10.1021/ja045155b
– volume: 217
  start-page: 1830
  year: 2023
  ident: 1575_CR113
  publication-title: Proc. Comput. Sci.
  doi: 10.1016/j.procs.2022.12.383
– volume: 6
  start-page: e202300046
  year: 2023
  ident: 1575_CR66
  publication-title: Batteries Supercaps
  doi: 10.1002/batt.202300046
– volume: 11
  year: 2020
  ident: 1575_CR112
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-020-15235-7
– volume: 1
  start-page: 37
  year: 2009
  ident: 1575_CR23
  publication-title: Nat. Chem.
  doi: 10.1038/nchem.121
– volume: 7
  year: 2021
  ident: 1575_CR25
  publication-title: npj Computational Mater.
  doi: 10.1038/s41524-021-00554-0
– volume: 9
  start-page: e17754
  year: 2023
  ident: 1575_CR115
  publication-title: Heliyon
  doi: 10.1016/j.heliyon.2023.e17754
– volume: 8
  start-page: 800
  year: 2023
  ident: 1575_CR57
  publication-title: Nat. Energy
  doi: 10.1038/s41560-023-01279-8
– volume: 56
  start-page: 62
  year: 2023
  ident: 1575_CR98
  publication-title: Energy Storage Mater.
  doi: 10.1016/j.ensm.2022.12.034
– volume: 598
  start-page: 590
  year: 2021
  ident: 1575_CR89
  publication-title: Nature
  doi: 10.1038/s41586-021-03885-6
– volume: 14
  year: 2023
  ident: 1575_CR7
  publication-title: Nat. Commun.
  doi: 10.1038/s41467-023-38493-7
– ident: 1575_CR26
  doi: 10.3390/ma15031157
– volume: 6
  start-page: 2253
  year: 2022
  ident: 1575_CR4
  publication-title: Joule
  doi: 10.1016/j.joule.2022.08.008
– volume: 597
  start-page: 234156
  year: 2024
  ident: 1575_CR118
  publication-title: J. Power Sources
  doi: 10.1016/j.jpowsour.2024.234156
– volume: 35
  start-page: 557
  year: 2021
  ident: 1575_CR69
  publication-title: J. Comput. Aided Mol. Des.
  doi: 10.1007/s10822-020-00346-6
– volume: 4
  start-page: 540
  year: 2019
  ident: 1575_CR96
  publication-title: Nat. Energy
  doi: 10.1038/s41560-019-0405-3
SSID ssj0001928240
Score 2.3321207
SecondaryResourceType review_article
Snippet In the development of battery science, machine learning (ML) has been widely employed to predict material properties, monitor morphological variations, learn...
Abstract In the development of battery science, machine learning (ML) has been widely employed to predict material properties, monitor morphological...
SourceID doaj
proquest
crossref
springer
SourceType Open Website
Aggregation Database
Index Database
Publisher
StartPage 89
SubjectTerms 639/166/987
639/301/1034/1037
639/301/299/891
Algorithms
Artificial intelligence
Automation
Characterization and Evaluation of Materials
Chemistry and Materials Science
Computational Intelligence
Datasets
Electrolytes
Energy consumption
Learning algorithms
Machine learning
Material properties
Materials Science
Mathematical and Computational Engineering
Mathematical and Computational Physics
Mathematical Modeling and Industrial Mathematics
Neural networks
Optimization
Perspective
Polymers
Science
Simulation
Software engineering
Theoretical
SummonAdditionalLinks – databaseName: DOAJ Directory of Open Access Journals
  dbid: DOA
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwELYQEwyIpygU5IENrKZx7NhjQaAKqUxU6mb5lQqktoiWgX_PnZPSFgmxsCW2B-vunO-cu_uOkCvAGB-0sgzMyTH44Ck4c3nFJDbrtlrDCF4UB0-yPyweR2K01uoLc8JqeuBacB3lul6A5Xm8uWQyKiVF1KIE5AFo4Ym9FDBv7TL1WvstCrCqqZLJuOrMEakKht1bAQFLwfQGEiXC_g0v80dgNOHNwz7ZaxxF2qs3eEC24vSQ7K7RBx6RQW8VfWYzJCwG95GGlJNBZxWdpETJSJvOEGOKPN_hZTyZU3BVqUvUmp-0AcFjMny4f77rs6Y9AvNc5Qv8DZhx7VQWguOuzKwvZZSi8J7H3FfeYbm44zmvnLcyhsoW1gZVBBV49FXJT8j2dDaNp1i47QorfSWskoWorMtgLT5x3y3htUWul6IybzULhknRa65MLVgDgjVJsEa3yC1K83slMlinAdCrafRq_tJri7SXujDNsZobLPUWmdRdmL5Z6mc1_fuWzv5jS-dkJ0_2g2bUJtuL9494AS7Jwl0m6_sCuD3Ylg
  priority: 102
  providerName: Directory of Open Access Journals
– databaseName: Springer Nature OA Free Journals
  dbid: C6C
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4QL3owPiOKpgdvunHZbrvtEYmEmOBJEm5NX0s8AAbw4L93puyKGD142z42aabTztd25htCbsDGOK-kSUCdbAIbnoQ1l5WJwGTdRimowYPi8FkMRvnTmI8bJKtjYaLTfqS0jNt07R12v0RDkyeYfBUMWMETtUN2kbodtbonept7FQWHiDyt4mNSJn_5dcsGRar-LXz540k0Wpr-ITmoICLtrgd1RBphdkz2vxEHnpBhd_PunMyRqhiAI_XRG4POSzqNLpKBVjkhJhQZvv3rZLqkAFKpjaSaH7Qyf6dk1H986Q2SKjFC4pjMVngBmDJlZeq9ZbZIjStEEDx3joXMlc5ioLhlGSutMyL40uTGeJl76VlwZcHOSHM2n4VzDNm2uRGu5EaKnJfGptAXv5jrFFBskdtaVPptzX-h47s1k3otWA2C1VGwWrXIA0rzqydyV8eK-WKiq7nU0nYch73E4Vk0FUFKwYPiBWAJAAuMt0i7ngtdLailxiBvngrVgea7en42zX8P6eJ_3S_JXhY1BRWmTZqrxXu4AtixstdRzz4BtwTQXw
  priority: 102
  providerName: Springer Nature
Title Application-oriented design of machine learning paradigms for battery science
URI https://link.springer.com/article/10.1038/s41524-025-01575-9
https://www.proquest.com/docview/3185506915
https://doaj.org/article/8b1c5031c614406e8865e95724166135
Volume 11
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfR3JSgMxNLhc9CCuWJeSgzcdnE4mmeQktViloIgL9BayTfFgq7Ye_HvfS1Orgl5myYQhvLy8fSHkCHiM80qaDNDJZkDwJJy5os4ENus2SsEIKorXN-Lqsez1eT8Z3MYprHJGEyOh9iOHNvJTzPLluVAtfvbymmHXKPSuphYai2QZS5dhSFfVr-Y2FgUKRZmnXJmcydMx8qsywx6uwAcrnqkf_CiW7f8ha_5yj0au010na0lcpO3p_m6QhTDcJKvfighukev23AeNK8Yim576GJlBRzV9juGSgab-EAOK1b790-B5TEFgpTYW2PygiRVuk8fuxUPnKktNEjLHZDFBY2DOlJW595bZKjeuEkHw0jkWClc7i0njlhWsts6I4GtTGuNl6aVnwdUV2yFLw9Ew7GL6ti2NcDU3UpS8NjaHufjEXKuC1wY5noFKv0xrYejow2ZSTwGrAbA6AlarBjlHaH7NxDrWcWD0NtDpWGhpW44DXXGol-YiSCl4ULwCuQIEB8Yb5GC2FzodrrGeo0KDnMz2Z_757yXt_f-3fbJSRMxABDkgS5O393AIIsfENiNewVV2L5tkud3u3ffgfn5xc3sHox3RaUZl_hP1Wdh7
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1LTxRBEK4gHtSD8RkXQfqgJ5wwO_2Y7oMhKKyLsJwg4db2azYe2EV2ieFP-Rut6p1xwURu3GZ6Op1J9Vevrq4qgPeoY0I02hUIJ1-gwNPIc1VTKGrW7YzBEXIUR8dqeCq-ncmzFfjd5cLQtcpOJmZBHaeBzsi3KctXlsr05c7Fz4K6RlF0tWuhsYDFYbr-hS7b7NPBHu7vh6oa7J98GRZtV4EicF3N6fSs5MbrMkbPfV26UKukpAiBpyo0wVOWtecVb3xwKsXGCeeiFlFHnkJTc1z3ATwUnBviKD34ujzTMejAiLLNzSm53p6RfhQF9YxFvVvLwtzSf7lNwC3b9p9wbNZyg2fwtDVP2e4CT89hJU1ewJMbRQtfwmh3GfMmClFRz8hivgnCpg07z9czE2v7UYwZVRePP8bnM4YGMvO5oOc1a1XvKzi9F_K9htXJdJLeULq4F06FRjqthGycL3EuPfHQr_G1B1sdqezFovaGzTFzru2CsBYJazNhrenBZ6Lm35lUNzsPTC_HtmVDq30_SJRjgfzgUiWtlUxG1mjHoKHCZQ_Wu72wLTPP7BJ6PfjY7c_y8_9_ae3u1Tbh0fBkdGSPDo4P38LjKqOEwLIOq_PLq7SB5s7cv8sYY_D9vkH9B0iREjQ
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1LbxMxEB6VIiE4IJ5qoIAPcIJVNuv164BQoUQtpRUHKuVm_Iw4NClNqqp_jV_HjLNLKBLcetv1WtZq_M3DnhfAS9QxIRrtKoSTr1DgaeS5JleSmnU7Y3CEDoqHR3LvuP00EZMN-NnnwlBYZS8Ti6CO80B35EPK8hW1NCMxzF1YxJfd8bvTHxV1kCJPa99OYwWRg3R5gce3xdv9XdzrV00z_vj1w17VdRioAtfNkm7Sam68rmP03KvaBSWTFG0IPDUhB08Z1543PPvgZIrZtc5F3UYdeQpZcVz3BtxUXIyIx9REre93DB5m2rrL06m5Hi5IV7YV9Y9FHaxEZa7owtIy4Iqd-5drtmi88T2425mqbGeFrfuwkWYP4M4fBQwfwuHO2v9NFKICn5HFEhXC5pmdlFDNxLreFFNGlcbj9-nJgqGxzHwp7nnJOjX8CI6vhXyPYXM2n6UtSh33rZMhC6dlK7LzNc6lJx5GCl8H8LonlT1d1eGwxX_OtV0R1iJhbSGsNQN4T9T8PZNqaJeB-dnUdixptR8FgTIt0Jm4lklrKZIRCm0aNFq4GMB2vxe2Y-yFXcNwAG_6_Vl__vcvPfn_ai_gFsLZft4_OngKt5sCEsLKNmwuz87TM7R8lv55gRiDb9eN6V-vtRZh
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Application-oriented+design+of+machine+learning+paradigms+for+battery+science&rft.jtitle=npj+computational+materials&rft.date=2025-04-02&rft.pub=Nature+Publishing+Group&rft.eissn=2057-3960&rft.volume=11&rft.issue=1&rft.spage=89&rft_id=info:doi/10.1038%2Fs41524-025-01575-9&rft.externalDBID=HAS_PDF_LINK
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2057-3960&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2057-3960&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2057-3960&client=summon