Digichem: computational chemistry for everyone†

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY Digital discovery Pub Date : 2024-08-16 DOI:10.1039/D4DD00147H
Oliver S. Lee, Malte C. Gather and Eli Zysman-Colman
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Abstract

We describe a new tool for the efficient management of computational chemistry. Digichem is a program that automates and simplifies nearly the entire computational pipeline, including large-scale batch submission of calculations, analysis and results parsing, the generation of 3D density plots and 2D graphs of calculation data, storage and retrieval of calculation results to a database, and automated handling of multi-step jobs. The program is designed to reduce the tedium and likelihood of human error for researchers of all skill-levels but is particularly targeted towards novice users who otherwise may find the barrier to entry to computational chemistry unnecessarily high. To date, this program has been used to successfully run and analyse over 50 000 individual calculations, evidencing its usefulness and utility. The Digichem program is presently released under a free-to-use license, and components of the Digichem system are additionally available under an open-source license.

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Digichem:面向所有人的计算化学†。
我们介绍了一种高效管理计算化学的新工具。Digichem 是一个程序,它几乎自动简化了整个计算流程,包括大规模批量提交计算、分析和结果解析、生成计算数据的三维密度图和二维图形、将计算结果存储和检索到数据库,以及自动处理多步骤工作。该程序旨在为各种技能水平的研究人员减少乏味和人为错误的可能性,但特别针对新手用户,否则他们可能会发现进入计算化学的门槛过高。迄今为止,该程序已成功运行和分析了 50,000 多项计算,证明了它的实用性和有用性。Digichem 程序目前在免费使用许可证下发布,Digichem 系统的组件也在开源许可证下提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Back cover ArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials. Sorting polyolefins with near-infrared spectroscopy: identification of optimal data analysis pipelines and machine learning classifiers†‡ High accuracy uncertainty-aware interatomic force modeling with equivariant Bayesian neural networks† Correction: A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing
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