Exploring Optimized Organic Fluorophore Search through Experimental Data-Driven Adaptive β‑VAE.

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Title: Exploring Optimized Organic Fluorophore Search through Experimental Data-Driven Adaptive β‑VAE.
Authors: Xu Y; Department of Chemistry, New York University, New York, New York 10003, United States.; Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning and NYU-ECNU Center for Computational Chemistry, NYU Shanghai, Shanghai 200062, P. R. China., Luo Y; Key Laboratory of Organofluorine Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, P. R. China., Li B; QuanMol Tech, Inc., San Carlos, California 94070, United States., Jiang W; Key Laboratory of Organofluorine Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, P. R. China., Zhang J; State Key Laboratory and Institute of Elemento-Organic Chemistry, College of Chemistry, Nankai University, Tianjin 300071, P. R. China., Wei J; Department of Chemistry and Department of Biological Sciences, National University of Singapore, Singapore 117544, Singapore., Bai H; Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, P. R. China., Wang Z; Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida 33431, United States., Ge J; Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States., Lin R; Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States., Mi Z; Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States., Zhang H; Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States., Tang Y; Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States., Jones MS; Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States., Li X; Faculty of Synthetic Biology, Shenzhen University of Advanced Technology, Shenzhen 518055, P. R. China., Zhang JZH; Department of Chemistry, New York University, New York, New York 10003, United States.; Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning and NYU-ECNU Center for Computational Chemistry, NYU Shanghai, Shanghai 200062, P. R. China.; Faculty of Synthetic Biology, Shenzhen University of Advanced Technology, Shenzhen 518055, P. R. China., Ju CW; Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States.
Source: JACS Au [JACS Au] 2025 Jun 30; Vol. 5 (7), pp. 3082-3091. Date of Electronic Publication: 2025 Jun 30 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101775714 Publication Model: eCollection Cited Medium: Internet ISSN: 2691-3704 (Electronic) Linking ISSN: 26913704 NLM ISO Abbreviation: JACS Au Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2691-3704
DOI:10.1021/jacsau.5c00052