Marija Alešković, Jasna Alić, Wolfgang E. Ernst* and Marina Šekutor*,
{"title":"","authors":"Marija Alešković, Jasna Alić, Wolfgang E. Ernst* and Marina Šekutor*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":57,"journal":{"name":"Journal of Organic Chemistry","volume":"90 26","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.3,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.joc.5c00590","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Davide Carboni, Giulio Casagranda, Simone Di Remigio, Alice Mirone, Arianna Quintavalla* and Marco Lombardo*,
{"title":"","authors":"Davide Carboni, Giulio Casagranda, Simone Di Remigio, Alice Mirone, Arianna Quintavalla* and Marco Lombardo*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":57,"journal":{"name":"Journal of Organic Chemistry","volume":"90 26","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.3,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.joc.5c01023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patrick W. Antoni, Annika Behnke, Christopher Golz and Max M. Hansmann*,
{"title":"","authors":"Patrick W. Antoni, Annika Behnke, Christopher Golz and Max M. Hansmann*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":57,"journal":{"name":"Journal of Organic Chemistry","volume":"90 26","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":3.3,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.joc.5c00880","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Machine learning for catalyst optimization: Outlier detection and material innovation","authors":"Alireza Mashayekhi, Sepehr Khazraei, Jack Bekou","doi":"10.1016/j.apcata.2025.120434","DOIUrl":"10.1016/j.apcata.2025.120434","url":null,"abstract":"<div><div>We present a machine learning-driven framework for the discovery and optimization of catalysts in gas adsorption mechanism, focusing on layered heterogeneous catalysts. This approach integrates electronic-structure descriptors with predictive and generative models to explore and evaluate catalyst compositions. By analyzing the adsorption energies of C, O, N, and H, we identify key electronic features that influence chemisorption and govern catalytic performance. Feature attribution methods and permutation importance analyses provide both local and global insights into feature significance, pinpointing critical descriptors that drive material behavior. The generative workflow uncovers novel catalyst candidates and outliers. These outliers — materials situated in low-density regions of the electronic feature space — were analyzed using statistical methods, principal component analysis (PCA), and feature importance techniques to uncover their unique electronic signatures and the potential influence of d-band width and d-band upper edge on catalytic behavior. This strategy accelerates the identification of high-performing catalytic materials, offering a scalable, data-driven pathway for innovation in catalysis and energy storage applications, while ensuring that the discovered materials meet specified adsorption energy ranges for targeted reactions.</div></div>","PeriodicalId":243,"journal":{"name":"Applied Catalysis A: General","volume":"705 ","pages":"Article 120434"},"PeriodicalIF":4.7,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}