In this lecture, Efim Zelmanov will discuss the unique features of Mathematics using examples from history and from our time.

在石油、化工、制药等工业应用中，45-55%的能耗等用于分离过程中。相较于传统分离过程如蒸发、精馏等，膜分离过程更加地节能、环保、高效。但长久以来，对膜分离层厚度以及其孔径的精准调控一直都是个难题。本报告中，通过控制界面聚合过程，膜分离层的厚度被降到10纳米以下，实现了溶剂的通量成数量级地增长。并且，通过对单体进行改性，加入疏水嵌段，让膜由亲水变为疏水，使其在原油分馏中同时达到了高通量和高选择性。另外，通过利用多孔材料（如有机分子笼、大环分子等）构建膜结构，并使之在膜内有序排列，实现了对膜孔径在埃米尺度的精准调控，拓展了膜在精细分离过程（如药物提纯）中的应用。 The chemical separations often account for 45-55% of the total industrial energy consumption in petroleum, chemical engineering, pharmaceuticals and other industrial applications. Compared to conventional separation process (i.e., distillation and rectification), membrane separation process will be more energy-saving, environmental-friendly, and high-efficiency. However, to precisely regulate the thickness and pore size of membranes has long been a great challenge in this field. In this report, the manipulation of the film thickness down to ~10 nanometers achieved permeance one order of magnitude higher than that of current state-of-the-art polyamide membranes while retaining comparable size- and class-based separation. Meanwhile, with the introduction of hydrophobic block, the hydrophilic membrane surface turned into hydrophobic surface, achieving much higher permeance and selectivity in the fractionation of light crude oil. Additionally, the porous material-based building blocks have been applied for the creation of well-defined membrane with aligned pore structure, further realizing the precision separation at the sub-nanometre scale, which expands their potential for application in crude oil fractionation, purification of drugs, etc.

徐一鸿教授将列举并讨论理论物理学的十大基础思想。本讲座基于普林斯顿大学出版社即将出版的同名科普读物。该书旨在对理论物理进行全面概述，而不是提供大量细节，因此本讲座可能适合那些对理论物理感兴趣但又不甚了解的人。 Prof. Anthony Zee will list and discuss the ten foundational ideas of theoretical physics. The lecture is based on a forthcoming popular book with the same title now in production at Princeton University Press. The book is meant to provide a sweeping overview of theoretical physics rather than a morass of details, and thus this talk may be suitable for those who are interested in theoretical physics but do not know much about it.

The data science ecosystem encompasses data fairness, statistical, ML methods and tools, interpretable data analysis, and trustworthy decision-making. Rapid advancements in ML have revolutionized data utilization and enabled machines to learn from data more effectively. Statistics, as the science of learning from data while accounting for uncertainty, plays a pivotal role in addressing complex real-world problems and facilitating trustworthy decision-making. In this talk, I will discuss the challenges and opportunities involved in building an end-to-end scalable and interpretable data science ecosystem that integrates statistics, ML, and domain science. I will illustrate key points using the analysis of whole genome sequencing data and electronic health records by discussing a few scalable and interpretable statistical and ML methods, tools and data science resources, using large annotation databases, summary statistics, sparsity, and ensemble methods. This talk aims to ignite proactive and thought-provoking discussions, foster collaboration, and cultivate open-minded approaches to advance scientific discovery.

催化反应在绿色可持续化学的发展过程中发挥着至关重要的作用。近年来，协同催化（即多位点协同进行化学催化）的概念引起了研究领域的广泛关注。协同催化突破了传统催化单一位点的局限性，为催化剂设计带来全新的思路。在本报告中，我将从分子催化、生物催化和异相催化三个维度分别介绍我们近期在协同催化方面所取得的重要进展，借此向大家展示协同催化概念针对诸多类型催化剂设计的通用性和适用性。 Catalysis has an important role in green and sustainable chemistry. The notion of cooperative catalysis, whereby more than one chemical entities work together to catalyze a chemical process, has gained momentums in recent years. Such cooperative catalysis may bring in new tools in catalyst design, and may overcome limitations of single-site catalysis. In this presentation I will describe several recent examples of our work covering cooperative catalysis in the three separate domains of catalysis: molecular, bio, and hetereogeneoues (electro) catalysis. I hope to demonstrate cooperative catalysis as a universal design principle for all types of catalysts.

动力系统描述了几何空间中的点在固定规则下随时间的演化情况。作为现代数学的新兴研究领域，动力系统的起源蕴含深厚的统计力学、信息论、微分方程与概率论背景，串联了分析、几何、代数、组合图论等数学主要领域，从独特的角度剖析背景各异的数学现象之间的关联。同时，动力系统被广泛应用于机械工程、航空航天、交通运输、气象分析等各个行业里模型的构建与解析中，与我们的日常生活息息相关。在本报告中，我们将回顾现代动力系统发展的历史，并通过剖析数个形式简单的经典案例中丰富而复杂的动力学行为，来介绍现代动力系统理论的思想和方法。