{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T06:52:50Z","timestamp":1775544770180,"version":"3.50.1"},"reference-count":50,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T00:00:00Z","timestamp":1680048000000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T00:00:00Z","timestamp":1680048000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["No.2019-0-00075"],"award-info":[{"award-number":["No.2019-0-00075"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["CAP-18-04-KRISS"],"award-info":[{"award-number":["CAP-18-04-KRISS"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","award":["FA2386-20-1-4085"],"award-info":[{"award-number":["FA2386-20-1-4085"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002701","name":"Ministry of Education","doi-asserted-by":"publisher","award":["NRF-2022R1A2C2091475"],"award-info":[{"award-number":["NRF-2022R1A2C2091475"]}],"id":[{"id":"10.13039\/501100002701","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["SSTF-BA2102-05"],"award-info":[{"award-number":["SSTF-BA2102-05"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["2022R1A2C2091945"],"award-info":[{"award-number":["2022R1A2C2091945"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["NRF-2022R1A2B5B02001913"],"award-info":[{"award-number":["NRF-2022R1A2B5B02001913"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Intelligent Systems"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:sec><jats:label\/><jats:p>The application of explainable artificial intelligence in nanomaterial research has emerged in the past few years, which has facilitated the discovery of novel physical findings. However, a fundamental question arises concerning the physical insights presented by deep neural networks; the model interpretation results have not been carefully evaluated. Herein, explainable artificial intelligence and quantum mechanical calculations is bridged to investigate the correlation between light scattering and emission in a WSe<jats:sub>2<\/jats:sub> monolayer. Convolutional neural networks using light scattering and emission data are first trained, while expecting the networks to determine the relationships between them. The trained models are interpreted and the specific phonon contribution during the exciton relaxation process is derived. Finally, the findings are independently evaluated through quantum mechanical calculations, such as the Born\u2013Oppenheimer molecular dynamics simulation and density functional perturbation theory. The study provides reliable fundamental physical insight by evaluating the results of neural networks and suggests a novel methodology that can be applied in materials science.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202200463","type":"journal-article","created":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T23:34:55Z","timestamp":1680132895000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Explainable Artificial Intelligence Approach to Identify the Origin of Phonon\u2010Assisted Emission in WSe<sub>2<\/sub> Monolayer"],"prefix":"10.1002","volume":"5","author":[{"given":"Jaekak","family":"Yoo","sequence":"first","affiliation":[{"name":"Department of Energy Science Sungkyunkwan University  Suwon 16419 Republic of Korea"},{"name":"Korea Research Institute of Standards and Science  Daejeon 34113 Republic of Korea"}]},{"given":"Youngwoo","family":"Cho","sequence":"additional","affiliation":[{"name":"Kim Jaechul Graduate School of Artificial Intelligence Korea Advanced Institute of Science and Technology  Daejeon 34141 Republic of Korea"}]},{"given":"Byeonggeun","family":"Jeong","sequence":"additional","affiliation":[{"name":"Department of Energy Science Sungkyunkwan University  Suwon 16419 Republic of Korea"}]},{"given":"Soo Ho","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Energy Science Sungkyunkwan University  Suwon 16419 Republic of Korea"}]},{"given":"Ki Kang","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Energy Science Sungkyunkwan University  Suwon 16419 Republic of Korea"}]},{"given":"Seong Chu","family":"Lim","sequence":"additional","affiliation":[{"name":"Department of Energy Science Sungkyunkwan University  Suwon 16419 Republic of Korea"},{"name":"Department of Smart Fabrication Technology Sungkyunkwan University  Suwon 16419 Republic of Korea"}]},{"given":"Seung Mi","family":"Lee","sequence":"additional","affiliation":[{"name":"Korea Research Institute of Standards and Science  Daejeon 34113 Republic of Korea"}]},{"given":"Jaegul","family":"Choo","sequence":"additional","affiliation":[{"name":"Kim Jaechul Graduate School of Artificial Intelligence Korea Advanced Institute of Science and Technology  Daejeon 34141 Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7019-8089","authenticated-orcid":false,"given":"Mun Seok","family":"Jeong","sequence":"additional","affiliation":[{"name":"Department of Physics Hanyang University  Seoul 04763 Republic of Korea"},{"name":"SMC Lab. Inc.  Seoul 04763 Republic of Korea"}]}],"member":"311","published-online":{"date-parts":[[2023,3,29]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/nnano.2014.25"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/natrevmats.2016.55"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/wcms.1313"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.88.085318"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/natrevmats.2017.33"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/adma.201503033"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1039\/C4CS00282B"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.89.075409"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.115.117401"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-20244-7"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41699-017-0035-1"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1021\/jacs.9b04663"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1021\/acsnano.6b02253"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cap.2016.03.023"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.97.205417"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.54.2151"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41377-018-0060-7"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1021\/accountsmr.1c00244"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/adma.202000953"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1021\/acsnano.7b07504"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.actamat.2021.117431"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1002\/adma.202202911"},{"key":"e_1_2_8_25_1","unstructured":"B.Zhou A.Khosla A.Lapedriza A.Oliva A.Torralba inProc. of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)2016 2921\u20132929."},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0130140"},{"key":"e_1_2_8_27_1","unstructured":"S. M.Lundberg S.-I.Lee inProc. the Advances in Neural Information Processing Systems (NeurIPS)(Eds.I.Guyon U. V.Luxburg S.Bengio H.Wallach R.Fergus S.Vishwanathan R.Garnett) Vol.30 Curran Associates Inc.2017 pp.4765\u20134774 https:\/\/proceedings.neurips.cc\/paper\/2017\/file\/8a20a8621978632d76c43dfd28b67767-Paper.pdf."},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41524-022-00884-7"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2014.907095"},{"key":"e_1_2_8_31_1","unstructured":"L.Liu H.Jiang P.He W.Chen X.Liu J.Gao J.Han inProc. the Int. Conf. on Learning Representations (ICLR)2020 https:\/\/openreview.net\/forum?id=rkgz2aEKDr"},{"key":"e_1_2_8_32_1","doi-asserted-by":"publisher","DOI":"10.1002\/smll.201202919"},{"key":"e_1_2_8_33_1","doi-asserted-by":"publisher","DOI":"10.1039\/c3nr03052k"},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.91.195411"},{"key":"e_1_2_8_35_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.4982817"},{"key":"e_1_2_8_36_1","doi-asserted-by":"publisher","DOI":"10.1021\/cr990029p"},{"key":"e_1_2_8_37_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.102.073005"},{"key":"e_1_2_8_38_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.nanolett.7b04374"},{"key":"e_1_2_8_39_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpcc.1c10258"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep04215"},{"key":"e_1_2_8_41_1","unstructured":"A.Paszke S.Gross F.Massa A.Lerer J.Bradbury G.Chanan T.Killeen Z.Lin N.Gimelshein L.Antiga A.Desmaison A.Kopf E.Yang Z.DeVito M.Raison A.Tejani S.Chilamkurthy B.Steiner L.Fang J.Bai S.Chintala inProc. the Advances in Neural Information Processing Systems (NeurIPS)(Eds.H.Wallach H.Larochelle A.Beygelzimer F.d'Alch\u00e9\u2010Buc E.Fox R.Garnett) Vol.32 Curran Associates Inc.2019 pp.8024\u20138035 https:\/\/proceedings.neurips.cc\/paper\/2019\/file\/bdbca288fee7f92f2bfa9f7012727740-Paper.pdf."},{"key":"e_1_2_8_42_1","unstructured":"X.Pan P.Luo J.Shi X.Tang inProc. of the European Conf. on Computer Vision (ECCV)(Eds.V.Ferrari M.Hebert C.Sminchisescu Y.Weiss) Springer International Publishing Cham2018 pp.484\u2013500 ISBN 978\u20103\u2010030\u201001225\u20100."},{"key":"e_1_2_8_43_1","doi-asserted-by":"crossref","unstructured":"K.He X.Zhang S.Ren J.Sun inProc. of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)2016 pp.770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_2_8_44_1","first-page":"1929","volume":"15","author":"Srivastava N.","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_2_8_45_1","unstructured":"D. P.Kingma J.Ba inProc. the Int. Conf. on Learning Representations (ICLR)(Eds.Y.Bengio Y.LeCun)2015 http:\/\/arxiv.org\/abs\/1412.6980."},{"key":"e_1_2_8_46_1","doi-asserted-by":"publisher","DOI":"10.1524\/zkri.220.5.567.65075"},{"key":"e_1_2_8_47_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.48.1425"},{"key":"e_1_2_8_48_1","doi-asserted-by":"publisher","DOI":"10.1088\/0022-3719\/10\/16\/019"},{"key":"e_1_2_8_49_1","doi-asserted-by":"publisher","DOI":"10.1039\/C4RA06378C"},{"key":"e_1_2_8_50_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.69.1077"},{"key":"e_1_2_8_51_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.84.094304"}],"container-title":["Advanced Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/aisy.202200463","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/aisy.202200463","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T23:46:14Z","timestamp":1759880774000},"score":1,"resource":{"primary":{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/10.1002\/aisy.202200463"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,29]]},"references-count":50,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["10.1002\/aisy.202200463"],"URL":"https:\/\/doi.org\/10.1002\/aisy.202200463","archive":["Portico"],"relation":{},"ISSN":["2640-4567","2640-4567"],"issn-type":[{"value":"2640-4567","type":"print"},{"value":"2640-4567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,29]]},"assertion":[{"value":"2022-12-29","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-03-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2200463"}}