Auto-VTNA: an automatic VTNA platform for determination of global rate laws†‡

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY Digital discovery Pub Date : 2024-09-13 DOI:10.1039/D4DD00111G
Daniel Dalland, Linden Schrecker and King Kuok (Mimi) Hii
{"title":"Auto-VTNA: an automatic VTNA platform for determination of global rate laws†‡","authors":"Daniel Dalland, Linden Schrecker and King Kuok (Mimi) Hii","doi":"10.1039/D4DD00111G","DOIUrl":null,"url":null,"abstract":"<p >The ability and desire to collect kinetic data has greatly increased in recent years, requiring more automated and quantitative methods for analysis. In this work, an automated program (Auto-VTNA) is developed, to simplify the kinetic analysis workflow. Auto-VTNA allows all the reaction orders to be determined concurrently, expediting the process of kinetic analysis. Auto-VTNA performs well on noisy or sparse data sets and can handle complex reactions involving multiple reaction orders. Quantitative error analysis and facile visualisation allows users to numerically justify and robustly present their findings. Auto-VTNA can be used through a free graphical user interface (GUI), requiring no coding or expert kinetic model input from the user, and can be customised and built on if required.</p>","PeriodicalId":72816,"journal":{"name":"Digital discovery","volume":" 10","pages":" 2118-2129"},"PeriodicalIF":6.2000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/dd/d4dd00111g?page=search","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital discovery","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/dd/d4dd00111g","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

The ability and desire to collect kinetic data has greatly increased in recent years, requiring more automated and quantitative methods for analysis. In this work, an automated program (Auto-VTNA) is developed, to simplify the kinetic analysis workflow. Auto-VTNA allows all the reaction orders to be determined concurrently, expediting the process of kinetic analysis. Auto-VTNA performs well on noisy or sparse data sets and can handle complex reactions involving multiple reaction orders. Quantitative error analysis and facile visualisation allows users to numerically justify and robustly present their findings. Auto-VTNA can be used through a free graphical user interface (GUI), requiring no coding or expert kinetic model input from the user, and can be customised and built on if required.

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
自动 VTNA:确定全球速率定律的自动 VTNA 平台
近年来,收集动力学数据的能力和愿望大大提高,需要更多的自动化定量分析方法。本研究开发了一个自动程序(Auto-VTNA),以简化动力学分析工作流程。自动 VTNA 允许同时确定所有反应顺序,加快了动力学分析过程。自动 VTNA 在噪声或稀疏数据集上表现良好,并能处理涉及多个反应阶的复杂反应。定量误差分析和简便的可视化功能使用户可以用数字证明并有力地展示他们的研究结果。Auto-VTNA 可通过免费的图形用户界面 (GUI) 使用,用户无需编码或输入专家级动力学模型,并可根据需要进行定制和构建。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
2.80
自引率
0.00%
发文量
0
期刊最新文献
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
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1