Addressing Rigor and Reproducibility in Heterogeneous, Thermal Catalysis

解决多相热催化的严谨性和重现性

• 批准号: 2152559
• 负责人: Neil Schweitzer
• 金额: $ 5.07万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2152559&HistoricalAwards=false
• 关键词: Addressing; Rigor; Reproducibility; Heterogeneous; Thermal

The project supports a workshop addressing the rigor and reproducibility of research conducted in heterogeneous thermal catalysis. The workshop is led by Dr. Neil Schweitzer of Northwestern University, with co-organizers Rajamani Gounder (Purdue University), and Robert Rioux (Penn State University). Experts from academe, industry, U.S. funding agencies and national laboratories, and the international catalysis research community will convene in both virtual and in-person sessions to assess the state of catalysis research methodology and identify actionable opportunities for coordinating rigorous and reproducible practices across the broader catalysis research community. Participants include an inclusive and diverse group of attendees including students, early-career researchers, and senior-level technical experts. Both short- and long-term objectives will be addressed covering 5 topic areas: 1) Standardized reporting in literature/proposals, 2) Developing benchmarking standards, 3) Producing training media and workshops, 4) Establishing a database of experimental data, and 5) Forming a network of testing labs. The workshop features a novel three-phase series of virtual sessions that will surround an in-person session of roughly 70 participants to be held at the Big Ten (B1G) Conference Center in Rosemont, Illinois (July 21 and July 22, 2022). Products and outcomes of the workshop will first consist of a workshop report followed by one or more journal articles summarizing best practices that researchers can use to benchmark, validate, and reproduce data in specific sub-fields of thermal catalysis.Heterogeneous thermal catalysis has long served as the bedrock of fuels and chemicals manufacturing. Complexity and variability spanning the entire breadth of catalyst materials properties, synthesis methods, characterization techniques, and evaluation procedures, has focused attention on the need to establish community-accepted practices for ensuring high-quality, benchmarked, and reproducible data. In addition, urgency around the transition to clean energy and greenhouse gas reduction has incentivized interdisciplinary, convergent, and translational approaches to catalysis research in recent years. Research engineers and scientists with expertise cutting broadly across materials, chemical synthesis, interfacial science, spectroscopic methods, and methods of data science and computational simulation, all bring welcome perspectives to catalysis research, but often with little awareness of the complexity of catalytic systems, especially in the working environment. Thus, mechanisms are needed to improve rigor and reproducibility (R&R) in experimental measurements to ensure alignment of the broader research community with a common core of practices specific to the realization of high-quality catalysis research. Similarly, the field is moving rapidly toward computational and data-science driven catalyst design, but successful implementation of such predictive tools hinges on model training and validation rooted in rigorously obtained and reproducible experimental data bases benchmarked to common specifications. Following the in-person session, specific sub-groups of workshop leaders and participants will be formed to pursue additional projects, including the development of online training material and content reflecting the best practices in catalysis research to improve rigor and reproducibility, the creation and maintenance of a public database of catalysis data, and the implementation of testing laboratory facilities that can be used by researchers to benchmark or validate their data. Emphasis will be placed on including early-career researchers in all phases of the workshop, to build appreciation of best practices, while also providing recommendations to those engaged in setting standards and practices for review of both grant proposals and journal article submissions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目支持一个讲习班，以解决在异质热催化中进行的研究的严格性和可重复性。 该研讨会由西北大学的尼尔·施韦特策博士（Neil Schweitzer）主持，共同组织者拉贾马尼·戈德（Rajamani Gounder）（普渡大学）和罗伯特·里奥克斯（Robert Rioux）（宾夕法尼亚州立大学）。 来自学术界，工业，美国资助机构和国家实验室以及国际催化研究界的专家将在虚拟和面对面的会议上召集，以评估催化研究方法的状况，并确定可行的机会，以协调整个更广泛的催化研究社区的严格和可重复实践。 参与者包括包括学生，早期研究人员和高级技术专家在内的包容性和多样化的与会者。 短期和长期目标都将解决5个主题领域：1）文献/建议中的标准化报告，2）制定基准标准标准，3）生产培训媒体和研讨会，4）建立实验数据数据库，以及5）形成一个测试实验室网络。 该研讨会以一系列新颖的三相虚拟会议为特色，该课程将围绕在伊利诺伊州罗斯蒙特市的十大（B1G）会议中心举行的大约70名参与者（2022年7月21日和7月22日）举行。研讨会的产品和结果将首先由研讨会报告组成，然后是一篇或多个期刊文章，总结了研究人员可以用来基准，验证和复制热催化的特定子场中的数据。热均匀催化的数据。 复杂性和可变性涵盖了催化剂材料特性，合成方法，表征技术和评估程序的整个广度，一直关注着建立社区认可的实践，以确保确保高质量，基准和可重复的数据。 此外，近年来，围绕清洁能源和温室气体减少过渡的紧迫性激励了跨学科，收敛和翻译方法催化研究。 具有专业知识的研究工程师和科学家跨越材料，化学合成，界面科学，光谱方法以及数据科学和计算模拟方法的削减，所有这些都为催化研究带来了欢迎的观点，但通常对催化系统的复杂性很少，尤其是在工作环境中。 因此，需要机制来改善实验测量中的严格性和可重复性（R＆R），以确保更广泛的研究界与更广泛的研究社区保持一致，以实现高质量催化研究的常见实践核心。 同样，该领域正在迅速朝着计算和数据科学驱动的催化剂设计方向发展，但是成功实施了此类预测工具在模型训练上的铰链和基于严格获得和可重现的实验数据基于基于常规规格的基于基础的验证。 在面对面的会议之后，将形成研讨会领导者和参与者的特定子组，以追求其他项目，包括开发在线培训材料和内容，以反映催化研究中的最佳实践，以改善严格性和可重复性，创建和维护催化数据的公共数据库，以及可以使用研究人员来实施的催化剂设施的公共数据库。将重点放在讲习班的各个阶段中包括早期职业研究人员，以建立对最佳实践的欣赏，同时还为参与审查赠款建议和期刊文章提交的标准和实践的人们提供建议。该奖项反映了NSF的法定任务，并通过评估智能委员会进行了评估，并通过基金会的范围进行了评估和广泛的影响。