{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T05:38:36Z","timestamp":1783402716964,"version":"3.54.6"},"reference-count":59,"publisher":"Elsevier BV","issue":"9","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100005825","name":"National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["CNS-2328395"],"award-info":[{"award-number":["CNS-2328395"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100003187","name":"NSF","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100003187","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000140","name":"U.S. Department of Transportation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000140","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000180","name":"U.S. Department of Homeland Security","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000180","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CMMI2038625"],"award-info":[{"award-number":["CMMI2038625"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["cell.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["iScience"],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1016\/j.isci.2024.110822","type":"journal-article","created":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T06:24:44Z","timestamp":1724653484000},"page":"110822","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"title":["Chemomechanical damage prediction from phase-field simulation video sequences using a deep-learning-based methodology"],"prefix":"10.1016","volume":"27","author":[{"given":"Quan","family":"Zeng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahed","family":"Rezaei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luis","family":"Carrillo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel","family":"Davidson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bai-Xiang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2028-4675","authenticated-orcid":false,"given":"Sarbajit","family":"Banerjee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.isci.2024.110822_bib1","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1039\/D2SC04157J","article-title":"Chemistry\u2013mechanics\u2013geometry coupling in positive electrode materials: a scale-bridging perspective for mitigating degradation in lithium-ion batteries through materials design","volume":"14","author":"Santos","year":"2023","journal-title":"Chem. Sci."},{"key":"10.1016\/j.isci.2024.110822_bib2","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.eml.2016.10.003","article-title":"Understanding the role of mechanics in energy materials: A perspective","volume":"9","author":"Zhao","year":"2016","journal-title":"Extreme Mechanics Letters"},{"key":"10.1016\/j.isci.2024.110822_bib3","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.joule.2020.11.003","article-title":"Peering into Batteries: Electrochemical Insight Through In Situ and Operando Methods over Multiple Length Scales","volume":"5","author":"Li","year":"2021","journal-title":"Joule"},{"key":"10.1016\/j.isci.2024.110822_bib4","doi-asserted-by":"crossref","first-page":"3548","DOI":"10.1021\/acsenergylett.0c01823","article-title":"Deformation during Electrosorption and Insertion-Type Charge Storage: Origins, Characterization, and Design of Materials for High Power","volume":"5","author":"Augustyn","year":"2020","journal-title":"ACS Energy Lett."},{"key":"10.1016\/j.isci.2024.110822_bib5","doi-asserted-by":"crossref","first-page":"1871","DOI":"10.1021\/acsenergylett.2c00870","article-title":"Asphericity Can Cause Nonuniform Lithium Intercalation in Battery Active Particles","volume":"7","author":"Mistry","year":"2022","journal-title":"ACS Energy Lett."},{"key":"10.1016\/j.isci.2024.110822_bib6","doi-asserted-by":"crossref","DOI":"10.1016\/j.actamat.2023.118879","article-title":"Designing shape-memory-like microstructures in intercalation materials","volume":"252","author":"Zhang","year":"2023","journal-title":"Acta Mater."},{"key":"10.1016\/j.isci.2024.110822_bib7","doi-asserted-by":"crossref","first-page":"1344","DOI":"10.1126\/science.aaa1313","article-title":"Topological defect dynamics in operando battery nanoparticles","volume":"348","author":"Ulvestad","year":"2015","journal-title":"Science"},{"key":"10.1016\/j.isci.2024.110822_bib8","doi-asserted-by":"crossref","first-page":"111099","DOI":"10.1016\/j.ijsolstr.2021.111099","article-title":"A chemomechanical damage model at large deformation: numerical and experimental studies on polycrystalline energy materials","volume":"228","author":"Bai","year":"2021","journal-title":"Int. J. Solid Struct."},{"key":"10.1016\/j.isci.2024.110822_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.jpowsour.2022.231805","article-title":"A coupled phase field formulation for modelling fatigue cracking in lithium-ion battery electrode particles","volume":"544","author":"Ai","year":"2022","journal-title":"J.\u00a0Power Sources"},{"key":"10.1016\/j.isci.2024.110822_bib10","doi-asserted-by":"crossref","first-page":"103758","DOI":"10.1016\/j.tafmec.2023.103758","article-title":"A cohesive phase-field fracture model for chemo-mechanical environments: Studies on degradation in battery materials","volume":"124","author":"Rezaei","year":"2023","journal-title":"Theor. Appl. Fract. Mech."},{"key":"10.1016\/j.isci.2024.110822_bib11","doi-asserted-by":"crossref","first-page":"1209","DOI":"10.1016\/j.jmps.2009.04.011","article-title":"Regularized formulation of the variational brittle fracture with unilateral contact: Numerical experiments","volume":"57","author":"Amor","year":"2009","journal-title":"J.\u00a0Mech. Phys. Solid."},{"key":"10.1016\/j.isci.2024.110822_bib12","doi-asserted-by":"crossref","first-page":"2765","DOI":"10.1016\/j.cma.2010.04.011","article-title":"A phase field model for rate-independent crack propagation: Robust algorithmic implementation based on operator splits","volume":"199","author":"Miehe","year":"2010","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"10.1016\/j.isci.2024.110822_bib13","doi-asserted-by":"crossref","first-page":"108177","DOI":"10.1016\/j.engfracmech.2021.108177","article-title":"An anisotropic cohesive fracture model: Advantages and limitations of length-scale insensitive phase-field damage models","volume":"261","author":"Rezaei","year":"2022","journal-title":"Eng. Fract. Mech."},{"key":"10.1016\/j.isci.2024.110822_bib14","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.jmps.2018.06.006","article-title":"A length scale insensitive phase-field damage model for brittle fracture","volume":"119","author":"Wu","year":"2018","journal-title":"J.\u00a0Mech. Phys. Solid."},{"key":"10.1016\/j.isci.2024.110822_bib15","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1002\/nme.5133","article-title":"A phase field model for chemo-mechanical induced fracture in lithium-ion battery electrode particles","volume":"106","author":"Miehe","year":"2016","journal-title":"Int. J. Numer. Methods Eng."},{"key":"10.1016\/j.isci.2024.110822_bib16","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.cma.2016.05.007","article-title":"A variational framework to model diffusion induced large plastic deformation and phase field fracture during initial two-phase lithiation of silicon electrodes","volume":"312","author":"Zhang","year":"2016","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"10.1016\/j.isci.2024.110822_bib17","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1039\/C4CP00563E","article-title":"A phase field model coupling lithium diffusion and stress evolution with crack propagation and application in lithium ion batteries","volume":"17","author":"Zuo","year":"2015","journal-title":"Phys. Chem. Chem. Phys."},{"key":"10.1016\/j.isci.2024.110822_bib18","doi-asserted-by":"crossref","first-page":"A102","DOI":"10.1149\/2.0281602jes","article-title":"Modeling Crack Growth during Li Extraction in Storage Particles Using a Fracture Phase Field Approach","volume":"163","author":"Klinsmann","year":"2015","journal-title":"J.\u00a0Electrochem. Soc."},{"key":"10.1016\/j.isci.2024.110822_bib19","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1002\/gamm.201610006","article-title":"Phase field modeling of electrochemically induced fracture in Li-ion battery with large deformation and phase segregation","volume":"39","author":"Xu","year":"2016","journal-title":"GAMM-Mitteilungen"},{"key":"10.1016\/j.isci.2024.110822_bib20","doi-asserted-by":"crossref","first-page":"104839","DOI":"10.1016\/j.jmps.2022.104839","article-title":"Chemo-mechanical modeling of inter- and intra-granular fracture in heterogeneous cathode with polycrystalline particles for lithium-ion battery","volume":"163","author":"Singh","year":"2022","journal-title":"J.\u00a0Mech. Phys. Solid."},{"key":"10.1016\/j.isci.2024.110822_bib21","doi-asserted-by":"crossref","DOI":"10.1002\/aenm.202200553","article-title":"Machine Learning Modeling for Accelerated Battery Materials Design in the Small Data Regime","volume":"12","author":"Sendek","year":"2022","journal-title":"Adv. Energy Mater."},{"key":"10.1016\/j.isci.2024.110822_bib22","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1038\/s41524-020-00471-8","article-title":"Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods","volume":"7","author":"Montes de Oca Zapiain","year":"2021","journal-title":"npj Comput. Mater."},{"key":"10.1016\/j.isci.2024.110822_bib23","doi-asserted-by":"crossref","first-page":"3894","DOI":"10.1021\/acsaelm.3c00601","article-title":"Machine Learning Surrogate Model for Acceleration of Ferroelectric Phase-Field Modeling","volume":"5","author":"Alhada-Lahbabi","year":"2023","journal-title":"ACS Appl. Electron. Mater."},{"key":"10.1016\/j.isci.2024.110822_bib24","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long Short-Term Memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"10.1016\/j.isci.2024.110822_bib25","first-page":"843","article-title":"Unsupervised Learning of Video Representations using LSTMs. Proceedings of the 32nd International Conference on Machine Learning, JMLR:","volume":"37","author":"Srivastava","year":"2015","journal-title":"W&CP"},{"key":"10.1016\/j.isci.2024.110822_bib26","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1038\/s41699-021-00228-x","article-title":"Deep learning model to predict fracture mechanisms of graphene","volume":"5","author":"Lew","year":"2021","journal-title":"npj 2D Mater. Appl."},{"key":"10.1016\/j.isci.2024.110822_bib27","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1038\/s41529-021-00151-y","article-title":"StressNet: Deep Learning to Predict Stress with Fracture Propagation in Brittle Materials","volume":"5","author":"Wang","year":"2021","journal-title":"npj Mater. Degrad."},{"key":"10.1016\/j.isci.2024.110822_bib28","doi-asserted-by":"crossref","first-page":"100712","DOI":"10.1016\/j.xcrp.2021.100712","article-title":"Topochemical stabilization and single-crystal transformations of a metastable 2D \u03b3\u2032 -V2O5 intercalation cathode","volume":"3","author":"Handy","year":"2022","journal-title":"Cell Reports Physical Science"},{"key":"10.1016\/j.isci.2024.110822_bib29","doi-asserted-by":"crossref","first-page":"100634","DOI":"10.1016\/j.patter.2022.100634","article-title":"Multivariate hyperspectral data analytics across length scales to probe compositional, phase, and strain heterogeneities in electrode materials","volume":"3","author":"Santos","year":"2022","journal-title":"Patterns"},{"key":"10.1016\/j.isci.2024.110822_bib30","doi-asserted-by":"crossref","DOI":"10.3390\/diagnostics11122183","article-title":"Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images","volume":"11","author":"Thambawita","year":"2021","journal-title":"Diagnostics"},{"key":"10.1016\/j.isci.2024.110822_bib31","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/72.298224","article-title":"Using mutual information for selecting features in supervised neural net learning","volume":"5","author":"Battiti","year":"1994","journal-title":"IEEE Trans. Neural Network."},{"key":"10.1016\/j.isci.2024.110822_bib32","series-title":"Data Science for Nano Image Analysis","first-page":"15","author":"Park","year":"2021"},{"key":"10.1016\/j.isci.2024.110822_bib33","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/S0031-3203(99)00055-2","article-title":"Adaptive document image binarization","volume":"33","author":"Sauvola","year":"2000","journal-title":"Pattern Recogn."},{"key":"10.1016\/j.isci.2024.110822_bib34","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1109\/CCECE.1998.682709","article-title":"An information theoretic image-quality measure","volume":"1","author":"Elbadawy","year":"1998","journal-title":"IEEE Canadian Conference on Electrical and Computer Engineering"},{"key":"10.1016\/j.isci.2024.110822_bib35","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.isci.2024.110822_bib36","doi-asserted-by":"crossref","first-page":"114587","DOI":"10.1016\/j.cma.2022.114587","article-title":"A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials","volume":"391","author":"Goswami","year":"2022","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"10.1016\/j.isci.2024.110822_bib37","doi-asserted-by":"crossref","first-page":"115616","DOI":"10.1016\/j.cma.2022.115616","article-title":"A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method","volume":"401","author":"Rezaei","year":"2022","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"10.1016\/j.isci.2024.110822_bib38","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1021\/acsnano.9b04365","article-title":"Electrode Degradation in Lithium-Ion Batteries","volume":"14","author":"Pender","year":"2020","journal-title":"ACS Nano"},{"key":"10.1016\/j.isci.2024.110822_bib39","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1016\/j.trechm.2019.06.013","article-title":"Chemo-Mechanical Challenges in Solid-State Batteries","volume":"1","author":"Lewis","year":"2019","journal-title":"Trends in Chemistry"},{"key":"10.1016\/j.isci.2024.110822_bib40","article-title":"Fracture behavior in battery materials","volume":"2","author":"Li","year":"2020","journal-title":"JPhys Energy"},{"key":"10.1016\/j.isci.2024.110822_bib41","doi-asserted-by":"crossref","first-page":"102914","DOI":"10.1016\/j.ijplas.2020.102914","article-title":"Phase transformations, fracture, and other structural changes in inelastic materials","volume":"140","author":"Levitas","year":"2021","journal-title":"Int. J. Plast."},{"key":"10.1016\/j.isci.2024.110822_bib42","doi-asserted-by":"crossref","first-page":"104612","DOI":"10.1016\/j.jmps.2021.104612","article-title":"A consistent framework for chemo-mechanical cohesive fracture and its application in solid-state batteries","volume":"157","author":"Rezaei","year":"2021","journal-title":"J.\u00a0Mech. Phys. Solid."},{"key":"10.1016\/j.isci.2024.110822_bib43","doi-asserted-by":"crossref","first-page":"1754","DOI":"10.1016\/j.matt.2020.08.030","article-title":"Curvature-Induced Modification of Mechano-Electrochemical Coupling and Nucleation Kinetics in a Cathode Material","volume":"3","author":"Andrews","year":"2020","journal-title":"Matter"},{"key":"10.1016\/j.isci.2024.110822_bib44","doi-asserted-by":"crossref","first-page":"3275","DOI":"10.1039\/D0MH01240H","article-title":"Bending good beats breaking bad: phase separation patterns in individual cathode particles upon lithiation and delithiation","volume":"7","author":"Santos","year":"2020","journal-title":"Mater. Horiz."},{"key":"10.1016\/j.isci.2024.110822_bib45","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1038\/s41699-021-00211-6","article-title":"Intercalation as a versatile tool for fabrication, property tuning, and phase transitions in 2D materials","volume":"5","author":"Rajapakse","year":"2021","journal-title":"npj 2D Mater. Appl."},{"key":"10.1016\/j.isci.2024.110822_bib46","doi-asserted-by":"crossref","DOI":"10.1063\/1.3492617","article-title":"Fracture of electrodes in lithium-ion batteries caused by fast charging","volume":"108","author":"Zhao","year":"2010","journal-title":"J.\u00a0Appl. Phys."},{"key":"10.1016\/j.isci.2024.110822_bib47","doi-asserted-by":"crossref","first-page":"11164","DOI":"10.1038\/s41598-017-11623-0","article-title":"Multi-characterization of LiCoO2 cathode films using advanced AFM-based techniques with high resolution","volume":"7","author":"Wu","year":"2017","journal-title":"Sci. Rep."},{"key":"10.1016\/j.isci.2024.110822_bib48","doi-asserted-by":"crossref","first-page":"5405","DOI":"10.1021\/acsaem.0c00380","article-title":"Tracking the Diffusion-Controlled Lithiation Reaction of LiMn2O4 by In Situ TEM","volume":"3","author":"Erichsen","year":"2020","journal-title":"ACS Appl. Energy Mater."},{"key":"10.1016\/j.isci.2024.110822_bib49","doi-asserted-by":"crossref","first-page":"49182","DOI":"10.1021\/acsami.0c13305","article-title":"Oriented LiMn2O4 Particle Fracture from Delithiation-Driven Surface Stress","volume":"12","author":"Warburton","year":"2020","journal-title":"ACS Appl. Mater. Interfaces"},{"key":"10.1016\/j.isci.2024.110822_bib50","doi-asserted-by":"crossref","first-page":"111688","DOI":"10.1016\/j.ijsolstr.2022.111688","article-title":"Phase-field simulation of misfit dislocations in two-phase electrode particles: Driving force calculation and stability analysis","volume":"249","author":"Zhou","year":"2022","journal-title":"Int. J. Solid Struct."},{"key":"10.1016\/j.isci.2024.110822_bib51","doi-asserted-by":"crossref","first-page":"4005","DOI":"10.1021\/nl501415b","article-title":"In situ Observation of Random Solid Solution Zone in LiFePO4 electrode","volume":"14","author":"Niu","year":"2014","journal-title":"Nano Lett."},{"key":"10.1016\/j.isci.2024.110822_bib52","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.jmps.2018.07.021","article-title":"Corrosive fracture of electrodes in Li-ion batteries","volume":"121","author":"Xu","year":"2018","journal-title":"J.\u00a0Mech. Phys. Solid."},{"key":"10.1016\/j.isci.2024.110822_bib53","doi-asserted-by":"crossref","first-page":"110015","DOI":"10.1016\/j.rser.2020.110015","article-title":"A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems","volume":"131","author":"Wang","year":"2020","journal-title":"Renew. Sustain. Energy Rev."},{"key":"10.1016\/j.isci.2024.110822_bib54","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1016\/j.joule.2020.02.010","article-title":"Mitigating Thermal Runaway of Lithium-Ion Batteries","volume":"4","author":"Feng","year":"2020","journal-title":"Joule"},{"key":"10.1016\/j.isci.2024.110822_bib55","doi-asserted-by":"crossref","first-page":"1240","DOI":"10.1016\/j.apenergy.2017.03.111","article-title":"Non-destructive fast charging algorithm of lithium-ion batteries based on the control-oriented electrochemical model","volume":"204","author":"Chu","year":"2017","journal-title":"Appl. Energy"},{"key":"10.1016\/j.isci.2024.110822_bib56","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jpowsour.2013.12.060","article-title":"Nondestructive detection, characterization, and quantification of lithium plating in commercial lithium-ion batteries","volume":"254","author":"Petzl","year":"2014","journal-title":"J.\u00a0Power Sources"},{"key":"10.1016\/j.isci.2024.110822_bib57","doi-asserted-by":"crossref","first-page":"232805","DOI":"10.1016\/j.jpowsour.2023.232805","article-title":"Lithium-ion battery lifetime extension: A review of derating methods","volume":"563","author":"Ruan","year":"2023","journal-title":"J.\u00a0Power Sources"},{"key":"10.1016\/j.isci.2024.110822_bib58","author":"Chollet"},{"key":"10.1016\/j.isci.2024.110822_bib59","author":"Abadi"}],"container-title":["iScience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2589004224020479?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2589004224020479?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,3]],"date-time":"2025-06-03T00:55:55Z","timestamp":1748912155000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2589004224020479"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9]]},"references-count":59,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2024,9]]}},"alternative-id":["S2589004224020479"],"URL":"https:\/\/doi.org\/10.1016\/j.isci.2024.110822","relation":{},"ISSN":["2589-0042"],"issn-type":[{"value":"2589-0042","type":"print"}],"subject":[],"published":{"date-parts":[[2024,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Chemomechanical damage prediction from phase-field simulation video sequences using a deep-learning-based methodology","name":"articletitle","label":"Article Title"},{"value":"iScience","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.isci.2024.110822","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"https:\/\/doi.org\/10.1016\/j.matt.2020.08.030","name":"associatedlink","label":"CrossRef DOI link to the associated document"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Author(s). Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"110822"}}