{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T13:46:26Z","timestamp":1790084786255,"version":"4.0.1"},"reference-count":75,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T00:00:00Z","timestamp":1750636800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["202208260014"],"award-info":[{"award-number":["202208260014"]}],"id":[{"id":"10.13039\/501100004543","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":[[2025,11]]},"abstract":"<jats:p>\n                    Electrochemical CO\n                    <jats:sub>2<\/jats:sub>\n                    reduction (CO\n                    <jats:sub>2<\/jats:sub>\n                    RR) presents a sustainable approach to converting greenhouse gases into valuable chemicals. However, achieving precise product selectivity remains challenging. This study investigates the influence of applied potential and catalyst morphology on CO\n                    <jats:sub>2<\/jats:sub>\n                    RR selectivity using a machine learning (ML) framework. Unlike most existing ML applications which primarily rely on open databases, we collect 378 experimental data points from literature focusing on Cu and Cu\u2010derived catalysts in H\u2010type cells. Various ML models are trained using both numerical and categorical parameters, with the artificial neural network model demonstrating the highest accuracy in predicting Faradaic efficiencies of key CO\n                    <jats:sub>2<\/jats:sub>\n                    RR products. The SHapley Additive exPlanations (SHAP) analysis identifies applied potential as the primary determinant of product distribution. Additionally, it reveals synergistic effects between catalyst morphology and size, influencing pathways toward CO, C\n                    <jats:sub>1<\/jats:sub>\n                    , and C\n                    <jats:sub>2+<\/jats:sub>\n                    products. These insights offer guidance for the rational design of Cu\u2010based CO\n                    <jats:sub>2<\/jats:sub>\n                    RR systems by optimizing operational parameters to enhance multi\u2010carbon product selectivity. The study introduces a novel dataset and a data\u2010driven methodology that integrates experimental findings with ML techniques, advancing the mechanistic understanding of CO\n                    <jats:sub>2<\/jats:sub>\n                    RR and providing a scalable approach for catalyst discovery and optimization.\n                  <\/jats:p>","DOI":"10.1002\/aisy.202500311","type":"journal-article","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T22:44:03Z","timestamp":1750718643000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Exploring the Influence of Applied Potential and Catalyst Morphology on the Selectivities of Copper Toward Carbon Dioxide Electroreduction Using Machine Learning"],"prefix":"10.1002","volume":"7","author":[{"given":"Chengxi","family":"Yao","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering Sungkyunkwan University  2066, Seobu\u2010Ro, Jangan\u2010Gu Suwon Gyeong Gi\u2010Do 16419 South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4465-7342","authenticated-orcid":false,"given":"Mo","family":"Yan","sequence":"additional","affiliation":[{"name":"International Institute for Carbon\u2010Neutral Energy Research (I2CNER) Kyushu University  744 Motooka, Nishi\u2010ku Fukuoka\u2010shi Fukuoka 819\u20100395 Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Asif","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences COMSATS University Islamabad Abbottabad Campus  Abbottabad 22060 Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering Sungkyunkwan University  2066, Seobu\u2010Ro, Jangan\u2010Gu Suwon Gyeong Gi\u2010Do 16419 South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seungjae","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering Sungkyunkwan University  2066, Seobu\u2010Ro, Jangan\u2010Gu Suwon Gyeong Gi\u2010Do 16419 South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joohwan","family":"Ha","sequence":"additional","affiliation":[{"name":"Department of Semiconductor Convergence Engineering Sungkyunkwan University  2066, Seobu\u2010Ro, Jangan\u2010Gu Suwon Gyeong Gi\u2010Do 16419 South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6280-7668","authenticated-orcid":false,"given":"Taesung","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering Sungkyunkwan University  2066, Seobu\u2010Ro, Jangan\u2010Gu Suwon Gyeong Gi\u2010Do 16419 South Korea"},{"name":"Department of Semiconductor Convergence Engineering Sungkyunkwan University  2066, Seobu\u2010Ro, Jangan\u2010Gu Suwon Gyeong Gi\u2010Do 16419 South Korea"},{"name":"SKKU Advance Institute in Nanotechnology Sungkyunkwan University  2066, Seobu\u2010Ro, Jangan\u2010Gu Suwon Gyeong Gi\u2010Do 16419 South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,6,23]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41557-021-00880-2"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aay3111"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.adq8594"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.chemrev.8b00705"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-20314-w"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/anie.202401821"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1021\/ja5065284"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41929-023-01010-6"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1711493114"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41929-023-01009-z"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1021\/acscatal.2c03650"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1021\/jacs.9b11790"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-04540-4"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-07882-8"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-52692-w"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpclett.1c01526"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpcc.0c05964"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1021\/jacs.1c00339"},{"key":"e_1_2_8_20_1","first-page":"18","volume":"3","author":"Hu Y.","year":"2023","journal-title":"J. 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