Rapid Screening of Kinetic Models for Methane Total Oxidation using an Automated Gas Phase Catalytic Microreactor Platform

IF 6.1 Q1 CHEMISTRY, MULTIDISCIPLINARY
Solomon Gajere Bawa, Arun Pankajakshan, Dr. Conor Waldron, Dr. Enhong Cao, Dr. Federico Galvanin, Prof. Asterios Gavriilidis
{"title":"Rapid Screening of Kinetic Models for Methane Total Oxidation using an Automated Gas Phase Catalytic Microreactor Platform","authors":"Solomon Gajere Bawa,&nbsp;Arun Pankajakshan,&nbsp;Dr. Conor Waldron,&nbsp;Dr. Enhong Cao,&nbsp;Dr. Federico Galvanin,&nbsp;Prof. Asterios Gavriilidis","doi":"10.1002/cmtd.202200049","DOIUrl":null,"url":null,"abstract":"<p>An automated flow micropacked bed catalytic reactor platform was developed to conduct pre-planned experiments for rapid screening of kinetic models. The microreactor was fabricated using photolithography and deep reactive ion etching of a silicon wafer, with a reaction channel width and depth of 2 mm and 420 μm respectively. It was packed with ca. 10 mg of 5 wt. % Pd/Al<sub>2</sub>O<sub>3</sub> catalyst to perform methane combustion, which was the selected reaction to test the developed platform. The experimental system was monitored and controlled by LabVIEW to which Python scripts for online design of experiments and data analysis were integrated. Within each experimental campaign, the platform automatically adjusted the experimental conditions, and the analysis of the product stream was conducted by online gas chromatography. The experimental platform demonstrated the capability of identifying the most probable kinetic models amidst potential models within two days.</p>","PeriodicalId":72562,"journal":{"name":"Chemistry methods : new approaches to solving problems in chemistry","volume":"3 1","pages":""},"PeriodicalIF":6.1000,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cmtd.202200049","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemistry methods : new approaches to solving problems in chemistry","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cmtd.202200049","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: 1

Abstract

An automated flow micropacked bed catalytic reactor platform was developed to conduct pre-planned experiments for rapid screening of kinetic models. The microreactor was fabricated using photolithography and deep reactive ion etching of a silicon wafer, with a reaction channel width and depth of 2 mm and 420 μm respectively. It was packed with ca. 10 mg of 5 wt. % Pd/Al2O3 catalyst to perform methane combustion, which was the selected reaction to test the developed platform. The experimental system was monitored and controlled by LabVIEW to which Python scripts for online design of experiments and data analysis were integrated. Within each experimental campaign, the platform automatically adjusted the experimental conditions, and the analysis of the product stream was conducted by online gas chromatography. The experimental platform demonstrated the capability of identifying the most probable kinetic models amidst potential models within two days.

Abstract Image

利用自动化气相催化微反应器平台快速筛选甲烷全氧化动力学模型
开发了一种自动流动微填料床催化反应器平台,用于进行预先计划的实验,以快速筛选动力学模型。微反应器采用光刻法和深度反应离子刻蚀法制备,反应通道宽度为2 mm,深度为420 μm。它装了约10毫克的5吨。采用% Pd/Al2O3催化剂进行甲烷燃烧,该反应是测试开发平台的选择反应。实验系统采用LabVIEW进行监控,并集成Python脚本进行实验设计和数据分析。在每个实验周期内,平台自动调整实验条件,通过在线气相色谱对产品流进行分析。实验平台证明了在两天内从潜在模型中识别出最可能的动力学模型的能力。
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 求助全文
来源期刊
CiteScore
7.30
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信