机器学习已成为化学家和工程师预测或加深理解化学过程的基本工具，不仅有助于更为快速的研究发现，还为以往靠想象才获得的各种可能性提供了可靠工具。本期虚拟专刊精选了在 JACS Au上发表的15篇机器学习主题的论文，收录了在分析化学、催化、诊断、药物发现、蛋白质、反应预测及谱学等相关领域的突出成果，为当前化学科学的研究方向及其未来发展提供了深刻的见解。欢迎阅读。
Emerging Chemistry & Machine Learning
Christopher W. Jones, Wasiu Lawal, and Xin Xu*
JACS Au 2022, ASAP
DOI: 10.1021/jacsau.2c00142
Deep Learning Optical Spectroscopy Based on Experimental Database: Potential Applications to Molecular Design
Joonyoung F. Joung, Minhi Han, Jinhyo Hwang, Minseok Jeong, Dong Hoon Choi, and Sungnam Park*
JACS Au 2021, 1, 4, 427-438
DOI: 10.1021/jacsau.1c00106
Deep Retrosynthetic Reaction Prediction using Local Reactivity and Global Attention
Shuan Chen and Yousung Jung*
JACS Au 2021, 1, 10, 1612-1620
DOI: 10.1021/jacsau.1c00246
Markov State Models to Study the Functional Dynamics of Proteins in the Wake of Machine Learning
Kirill A. Konovalov, Ilona Christy Unarta, Siqin Cao, Eshani C. Goonetilleke, and Xuhui Huang*
JACS Au 2021, 1, 9, 1330-1341
DOI: 10.1021/jacsau.1c00254
AutoDetect-mNP: An Unsupervised Machine Learning Algorithm for Automated Analysis of Transmission Electron Microscope Images of Metal Nanoparticles
Xingzhi Wang, Jie Li, Hyun Dong Ha, Jakob C. Dahl, Justin C. Ondry, Ivan Moreno-Hernandez, Teresa Head-Gordon*, and A. Paul Alivisatos*
JACS Au 2021, 1, 3, 316-327
DOI: 10.1021/jacsau.0c00030
Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning
Yingdi Zhu, Andreas Lesch, Xiaoyun Li, Tzu-En Lin, Natalia Gasilova, Milica Jović, Horst Matthias Pick, Ping-Chih Ho, and Hubert H. Girault*
JACS Au 2021, 1, 5, 598-611
DOI: 10.1021/jacsau.0c00074
Determining the Effect of Hot Electron Dissipation on Molecular Scattering Experiments at Metal Surfaces
Connor L. Box, Yaolong Zhang, Rongrong Yin, Bin Jiang*, and Reinhard J. Maurer*
JACS Au 2021, 1, 2, 164-173
DOI: 10.1021/jacsau.0c00066
The Quest to Simulate Excited-State Dynamics of Transition Metal Complexes
J. Patrick Zobel* and Leticia González*
JACS Au 2021, 1, 8, 1116-1140
DOI: 10.1021/jacsau.1c00252
Screening and Understanding Li Adsorption on Two-Dimensional Metallic Materials by Learning Physics and Physics-Simplified Learning
Sheng Gong, Shuo Wang, Taishan Zhu, Xi Chen, Zhenze Yang, Markus J. Buehler, Yang Shao-Horn, and Jeffrey C. Grossman*
JACS Au 2021, 1, 11, 1904-1914
DOI: 10.1021/jacsau.1c00260
Deep Learning Enables Discovery of a Short Nuclear Targeting Peptide for Efficient Delivery of Antisense Oligomers
Eva M. López-Vidal, Carly K. Schissel, Somesh Mohapatra, Kamela Bellovoda, Chia-Ling Wu, Jenna A. Wood, Annika B. Malmberg, Andrei Loas, Rafael Gómez-Bombarelli*, and Bradley L. Pentelute*
JACS Au 2021, 1, 11, 2009-2020
DOI: 10.1021/jacsau.1c00327
Dynamics of Heterogeneous Catalytic Processes at Operando Conditions
Xiangcheng Shi, Xiaoyun Lin, Ran Luo, Shican Wu, Lulu Li, Zhi-Jian Zhao*, and Jinlong Gong*
JACS Au 2021, 1, 12, 2100-2120
DOI: 10.1021/jacsau.1c00355
Power in Numbers: Harnessing Combinatorial and Integrated Screens to Advance Nanomedicine
Natalie Boehnke and Paula T. Hammond*
JACS Au 2022, 2, 1, 12-21
DOI: 10.1021/jacsau.1c00313
Chemputation and the Standardization of Chemical Informatics
Alexander J. S. Hammer, Artem I. Leonov, Nicola L. Bell, and Leroy Cronin*
JACS Au 2021, 1, 10, 1572-1587
DOI: 10.1021/jacsau.1c00303
Accurate Machine Learning Prediction of Protein Circular Dichroism Spectra with Embedded Density Descriptors
Luyuan Zhao, Jinxiao Zhang, Yaolong Zhang, Sheng Ye, Guozhen Zhang, Xin Chen, Bin Jiang*, and Jun Jiang*
JACS Au 2021, 1, 12, 2377-2384
DOI: 10.1021/jacsau.1c00449
Understanding High-Temperature Chemical Reactions on Metal Surfaces: A Case Study on Equilibrium Concentration and Diffusivity of CxHy on a Cu(111) Surface
Pai Li, Xiongzhi Zeng, and Zhenyu Li*
JACS Au 2022, 2, 2, 443-452
DOI: 10.1021/jacsau.1c00483
Combinatorial Polycation Synthesis and Causal Machine Learning Reveal Divergent Polymer Design Rules for Effective pDNA and Ribonucleoprotein Delivery
Ramya Kumar, Ngoc Le, Felipe Oviedo, Mary E. Brown, and Theresa M. Reineke*
JACS Au 2022, 2, 2, 428-442
DOI:10.1021/jacsau.1c00467
Copyright © 2022 American Chemical Society
主编：Christopher W. Jones（Georgia Institute of Technology）
JACS Au 是美国化学会于 2020 年推出的一本完全开放获取期刊，是 JACS 的姊妹刊，于 2021 年 1 月出版第一期，以实现在整个化学及所有与化学交叉的相关领域快速传播具有高度影响力的前沿研究成果为宗旨。JACS Au 沿用与JACS 相同的卓越标准进行编辑和出版。JACS Au 拥有一支完全独立的编辑团队，他们将从需要或希望在开放获取期刊上发表研究成果的作者中挑选出最激动人心、最具影响力和新颖性的研究工作。
