Ab Initio-Based Kinetic Modeling for the Design of Molecular Catalysts: The Case of H₂ Production Electrocatalysts

Journal Article · Fri Aug 07 00:00:00 EDT 2015 · ACS Catalysis

DOI:https://doi.org/10.1021/acscatal.5b01152· OSTI ID:1490329

Ho, Ming-Hsun ^[1]; Rousseau, Roger ^[1]; Roberts, John A. S. ^[1]; Wiedner, Eric S. ^[1]; Dupuis, Michel ^[1]; DuBois, Daniel L. ^[1]; Bullock, R. Morris ^[1]; Raugei, Simone ^[1]

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1. Center for Molecular Electrocatalysis, Pacific Northwest National Laboratory, P.O. Box 999, K1-83, Richland, Washington 99352, United States

Design of fast, efficient electrocatalysts for energy storage and energy production requires a systematic approach to predict and tune the energetics of reaction intermediates and the kinetic barriers between them, as well as to tune reaction conditions (e.g., concentration of reactants, acidity of the reaction medium, and applied electric potential). Thermodynamics schemes based on the knowledge of pKa values, hydride donor ability, redox potentials and other relevant thermodynamic properties have been demonstrated to be very effective for exploring possible reaction pathways. We seek to identify high-energy intermediates, which may represent a catalytic bottleneck, and low-energy intermediates, which may represent a thermodynamic sink. In this study, working on a well-established Ni-based bio-inspired electrocatalyst for H₂ production, we performed a detailed kinetic analysis of the catalytic pathways to assess the limitations of our current (standard state) thermodynamic analysis with respect to prediction of optimal catalyst performance. To this end, we developed a microkinetic model based on extensive ab initio simulations. The model was validated against available experimental data, and it reproduces remarkably well the observed turnover rate as a function of the acid concentration and catalytic conditions, providing valuable information on the main factors limiting catalysis. Using this kinetic analysis as a reference, we show that indeed a purely thermodynamic analysis of the possible reaction pathways provides us with valuable information, such as a qualitative picture of the species involved during catalysis, identification of the possible branching points, and the origin of the observed overpotential, which are critical insights for electrocatalyst design. However, a significant limitation of this approach is understanding how these insights relate to rate, which is an equally critical piece of information. Taking our analysis a step further, we show that the kinetic model can easily be extended to different catalytic conditions by using linear free energy relationships for activation barriers based on simple thermodynamics quantities, such as pKa values. We also outline a possible procedure to extend it to other catalytic platforms, making it a general and effective way to design catalysts with improved performance. We thank Dr. W. J. Shaw, Dr. Aaron M. Appel and Dr. M. L. Helm for useful discussions. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy. Computer Resources were provided by the W. R. Wiley Environmental Molecular Sciences Laboratory (EMSL), a DOE Office of Science National User Facility located at Pacific Northwest National Laboratory. Computer resources were also provided by the National Energy Research Computing Center (NERSC) at Lawrence Berkeley National Laboratory.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Basic Energy Sciences (BES)
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1490329
• Report Number(s): PNNL-SA-110596
• Journal Information: ACS Catalysis, Vol. 5, Issue 9; ISSN 2155-5435
• Publisher: American Chemical Society (ACS)
• Country of Publication: United States
• Language: English