应张国旭副教授邀请，卢森堡大学Tkatchenko教授到我校进行学术访问，并于太阳成城集团tyc234cc做“明德讲堂”学术报告，欢迎广大师生参加。
报告题目：Unlocking Schrödinger's dream with Al-driven molecular simulations
报告时间：2026年4月9日 14:00-15:00
报告地点：明理学术报告厅（明德楼 D702）
报告摘要：
The convergence between accurate quantum-mechanical (**) models (and codes) with efficient machine learning (ML) methods seem to promise a paradigm shift in all-atom simulations. Many challenging applications are now being tackled by increasingly powerful **/ML methodologies [1-2]. These include modeling covalent materials, molecules, molecular crystals, surfaces, and even whole proteins under physiological conditions [3-4]. In this talk, I attempt to provide a reality check on these recent advances and on the developments required to enable fully predictive dynamics of complex functional (bio)molecular and material systems Multiple challenges are highlighted - in particular transferability in chemical space and interatomic interactions - that should enable this field to grow for the foreseeable future.
[1] Chem. Rev. 121, 10142 (2021)
[2] Chem. Rev. 121, 9816 (2021)
[3] Sci. Adv. 10, eadn4397 (2024)
[4] J. Am. Chem. Soc. 147, 33723 (2025)
报告人简介：
Tkatchenko教授自2020年起担任卢森堡大学物理与材料科学系主任及理论化学物理教授。团队开发了精确和高效的第一性原理计算模型来广泛研究复杂材料，旨在定性理解和定量预测其在原子尺度及更大尺度上的结构、内聚力、电子和光学性质；在著名期刊上发表了200多篇文章（h指数80，引用超过35000次），担任Sci Adv.，Phys. Rev. Lett.和J. Phys. Chem. Lett.编委会成员；美国物理学会APS Fellow；获得德国物理学会Gerhard ErtI青年研究员奖，世界理论与计算化学家协会(WATOO) Dirac奖章，国际非共价相互作用会议(ICNI) van der Waals奖等。
