228 | OrgAIcat: Leveraging Literature Data for Enantioselectivity Prediction and Optimization in Organocatalysis
Qi Yang, Yidi Liu, Wenxuan Zhang, Long Zhang, Yufei Chen, Sanzhong Luo*
CCS Chem. 2026, 10.31635/ccschem.026.202607900.
227 | iBonD: bond energy database embracing the era of artificial intelligence
Shen Wang, Qi Yang, Sanzhong Luo*, Jin-Pei Cheng*
Digit. Discov., 2026, 10.1039/d6dd00231e.
226 | Electrochemical α-Acyloxylation by Cooperative Chiral Amine and Proton Shuttle Catalysis via an Asymmetric SN1 Mechanism
Na Zhang, Wenzhuo Xu, Jiawei Li, Pengxin Zhou*, Qifeng Lin*, Sanzhong Luo*
Chem. - Eur. J., 2026, 10.1002/chem.71522.
225 | Physical Organic Studies on the Stereoionic Interactions in Asymmetric Primary Aminocatalysis
Yuchen Zhang, Long Zhang, Qifeng Lin, Sanzhong Luo*
Acc. Chem. Res., 2026, 59, 13, 2139-2153.
224 | Chiral hafnium phosphate catalyzed asymmetric de Mayo reaction via visible-light-induced dearomatization
Chunming Yang, Yuzhi Wang, Yuchen Zhang, Xuegang Liu, Chaoqin Hu, Jie Yang, Xueling Mi*, Sanzhong Luo*
Nature Comm., 2026, 17, 6351.
223 | ScopeMap: An AI-Assisted, Human-in-the-Loop Workflow for Mapping Reaction Scope and Boundaries
Jiawei Li, Xiao Xiao, Qi Yang*, Baoguo Zhao*, Sanzhong Luo*
Angew. Chem. Int. Ed. 2026, 65, 26, e2455429.
222 | Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial
Zhongwei Yu, Rasul Tutunov, Alexandre Max Maraval, Zikai Xie, Zhenzhi Tan, Jiankang Wang, Bin Cao, Zijing Li, Liangliang Xu, Qi Yang*, Jun Jiang*, Sanzhong Luo*, Zhenxiao Guo*, Tongyi Zhang*, Haitham Bou-Ammar*, Jun Wang*
arXiv, 2026, 10.48550/arXiv.2604.01328
221 | ReactionSeek: LLM-Powered Literature Data Mining and Knowledge Discovery in Organic Synthesis
Jiawei Li, Minzhou Li, Qi Yang*, Sanzhong Luo*
Nature Comm., 2026, 17, 3356.
220 | Reductive iminium-ion catalysis: electrochemical β-arylation and alkenylation of enals by primary amine/nickel dual catalysis
Yingdong Duan, Fanzhu Zeng, Sanzhong Luo*
Chemrxiv 2026, 10.26434/chemrxiv-2026-4qftj.
219 | Synthetic Applicability Domain (SynAD): Navigating Chemical Space for Reliable AI-Driven Reaction Prediction
Zhenzhi Tan, Qi Yang*, Long Zhang, Sanzhong Luo*
Angew. Chem. Int. Ed. 2026, 65, 9, e23874.