About: Addressing Rigor and Reproducibility in Heterogeneous, Thermal Catalysis

Abstract

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.  The primary outcome of this workshop will be a report summarizing best practices for reporting data that researchers can use to benchmark, validate, and reproduce data in specific sub-fields of thermal catalysis.