报告题目(Title)：Mechanistic Insights into Asymmetric Catalysis Accelerated by Automated Computational Workflows（自动化计算工作流程加速对不对称催化的机理理解）
报告人(Speaker)：Xinglong Zhang（Department of Chemistry, The Chinese University of Hong Kong，章兴龙，香港中文大学化学系）
报告时间(Time)：2026年8月21日（星期五）15:00
报告地点(Place): E106
邀请人(Inviter)：李永乐教授
主办部门：理学院物理系
摘要(Abstract)：
Homogeneous catalysis forms a cornerstone of modern organic synthesis, yet factors governing chemical reactivity and selectivity are often challenging to discern from experiments alone. In this seminar, I will show how state-of-the-art computational chemistry can yield detailed mechanistic insights into various catalytic systems. Through case studies on transition-metal and organic asymmetric catalysis, I will discuss how density functional theory and related methods reveal the operative pathways, the origin of chemo-, regio- and enantioselectivity, and the roles of ligand environment, non-covalent interactions and reaction microenvironment. These examples highlight how mechanistic understanding may suggest new substrate classes, leaving groups and ligands, and rationalize unexpected experimental trends. I will then introduce CHEMSMART, an open-source Python toolkit we develop to automate quantum chemical workflows from input generation to job submission and results analysis. By integrating mechanistic insight with reproducible, scalable workflows, we aim to equip researchers with an extensible framework for data-rich, mechanistically guided catalyst and reaction design.
均相催化是现代有机合成的基石，然而，仅凭实验往往难以辨别影响化学反应活性和选择性的因素。本次报告中，报告人将展示如何利用最先进的计算化学方法，深入理解各种催化体系的机理。通过过渡金属催化和有机不对称催化的案例研究，报告人将探讨密度泛函理论及相关方法如何揭示反应路径、化学选择性、区域选择性和对映选择性的起源，以及配体环境、非共价相互作用和反应微环境的作用。这些案例突显了机理理解如何提示新的底物类型、离去基团和配体，并解释一些意料之外的实验趋势。随后，我将介绍CHEMSMART，这是一个我们开发的开源Python工具包，用于自动化量子化学工作流程，涵盖从输入生成到任务提交和结果分析的各个环节。通过将机制见解与可重复、可扩展的工作流程相结合，我们旨在为研究人员提供一个可扩展的框架，用于数据丰富、机制指导的催化剂和反应设计。
