Benchmarking physics-inspired machine learning models for transition metal complexes with diverse charge and spin states [0.03%]
基准测试物理启发的机器学习模型以求解不同电荷和自旋态的过渡金属配合物问题
Yuri Cho,Ksenia R Briling,Yannick Calvino Alonso et al.
Yuri Cho et al.
Physics-inspired machine learning (ML) models can be categorized into two classes: those relying solely on three-dimensional structure and those incorporating electronic information. In this work, we benchmark both classes for predicting qu...
Autonomous sampling and SHAP interpretation of deposition-rates in bipolar HiPIMS [0.03%]
自采样和SHAP解释在双极HiPIMS中沉积率的自主采样和SHAP解释
Alexander Wieczorek,Nathan Rodkey,Jan Sommerhäuser et al.
Alexander Wieczorek et al.
High-power impulse magnetron sputtering (HiPIMS) offers considerable control over ion energy and flux, making it invaluable for tailoring the microstructure and properties of advanced functional coatings. However, compared to conventional s...
Ian Dunn,David R Koes
Ian Dunn
A generative model capable of sampling realistic molecules with desired properties could accelerate chemical discovery across a wide range of applications. Toward this goal, significant effort has focused on developing models that jointly s...
Chemist Eye: a visual language model-powered system for safety monitoring and robot decision-making in self-driving laboratories [0.03%]
基于视觉语言模型的自动驾驶实验室安全监控和机器人决策系统化学眼
Francisco Munguia-Galeano,Zhengxue Zhou,Satheeshkumar Veeramani et al.
Francisco Munguia-Galeano et al.
The use of robotics and automation in self-driving laboratories (SDLs) can introduce additional safety complexities, beyond those already present in conventional research laboratories. Personal protective equipment (PPE) is an essential req...
Generalization of long-range machine learning potentials in complex chemical spaces [0.03%]
复杂化学空间中长程机器学习势能的拓展
Michał Sanocki,Julija Zavadlav
Michał Sanocki
The vastness of chemical space makes generalization a central challenge in the development of machine learning interatomic potentials (MLIPs). While MLIPs could enable large-scale atomistic simulations with near-quantum accuracy, their usef...
Apostolos P Maroulis,Dylan M Waynor,Quinn M Gallagher et al.
Apostolos P Maroulis et al.
Experimentation is inherently difficult because most methods require substantial refinement, calibration, and validation before high-quality, reliable data can be collected. In most cases, experimental outcomes are impacted by multiple vari...
Learning potential energy surfaces of hydrogen atom transfer reactions in peptides [0.03%]
学习肽中氢原子转移反应的势能表面
Marlen Neubert,Patrick Reiser,Frauke Gräter et al.
Marlen Neubert et al.
Hydrogen atom transfer (HAT) reactions are essential in many biological processes, such as radical migration in damaged proteins, but their mechanistic pathways remain incompletely understood. Simulating HAT processes is challenging due to ...
NaviDiv: a web app for monitoring chemical diversity in generative molecular design [0.03%]
NaviDiv：一种用于生成分子设计中化学多样性的监测的网络应用程序
Mohammed Azzouzi,Thanapat Worakul,Clémence Corminboeuf
Mohammed Azzouzi
The rapid progress in generative models for molecular design has led to extensive libraries of candidate molecules for biological and chemical applications. However, ensuring these molecules are diverse and representative of broader chemica...
Database utility for cyclovoltammetry knowledge (DUCK): unified platform for electrochemical data [0.03%]
用于循环伏安法知识的数据库工具（鸭子）：电化学数据统一平台
Diego Garay-Ruiz,Sergio Pablo-García,Han Hao et al.
Diego Garay-Ruiz et al.
Cyclic voltammetry (CV) is a valuable tool for electrochemistry, providing qualitative and quantitative information about redox processes occurring in solution. Despite its ubiquity, the lack of standardized reporting and sharing protocols,...
Looking back and to the future after four-plus years of language in chemistry [0.03%]
化学中的语言四年多的回顾与展望
Glen M Hocky,Andrew D White
Glen M Hocky
Four years ago we wrote an article predicting the disruptive effect of large language models in the fields of chemical education and research. Here we review and grade our past predictions, give our perspective on some of the progress that ...