publications (catalysis)

2022

1. Catalysis

   Heterogeneous Catalysis in Grammar School

   Johannes T. Margraf , Zachary W. Ulissi, Yousung Jung , and 1 more author

   The Journal of Physical Chemistry C, 2022
2. Catalysis

   Site Geometry as a Descriptor for Catalyst Selectivity in Intermetallics

   Unnatti Sharma , Angela Nguyen , Michael John Janik , and 1 more author

   Preprint available at SSRN 4145497, 2022
3. Catalysis

   Detailed Microkinetics for the Oxidation of Exhaust Gas Emissions through Automated Mechanism Generation

   Bjarne Kreitz , Patrick Lott , Jongyoon Bae , and 6 more authors

   ACS Catalysis, 2022

2021

1. Catalysis

   Efficient Discovery of Active, Selective, and Stable Catalysts for Electrochemical H_2O_2 Synthesis through Active Motif Screening

   Seoin Back , Jonggeol Na , and Zachary W. Ulissi

   ACS Catalysis, Feb 2021

2020

1. Catalysis

   Parallelized Screening of Characterized and DFT-Modeled Bimetallic Colloidal Cocatalysts for Photocatalytic Hydrogen Evolution

   Eric M Lopato , Emily A Eikey , Zoe C Simon , and 8 more authors

   ACS Catalysis, Mar 2020
2. Catalysis

   In silico discovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation

   Seoin Back , Jonggeol Na , Kevin Tran , and 1 more author

   Phys. Chem. Chem. Phys., Aug 2020

   Abs

   Various databases of density functional theory (DFT) calculations for materials and adsorption properties are currently available. Using the Materials Project and GASpy databases of material stability and binding energies (H* and CO*), respectively, we evaluate multiple aspects of catalysts to discover active, stable, CO-tolerant, and cost-effective hydrogen evolution and oxidation catalysts. Finally, we suggest a few candidate materials for future experimental validations. We highlight that the stability analysis is easily obtainable but provides invaluable information to assess thermodynamic and electrochemical stability, bridging the gap between simulations and experiments. Furthermore, it reduces the number of expensive DFT calculations required to predict catalytic activities of surfaces by filtering out unstable materials.

3. Catalysis

   Discovery of Acid-Stable Oxygen Evolution Catalysts: High-throughput Computational Screening of Equimolar Bimetallic Oxides

   Seoin Back , Kevin Tran , and Zachary W Ulissi

   ACS Applied Materials & Interfaces, Aug 2020

2018

1. Catalysis

   Copper Silver Thin Films with Metastable Miscibility for Oxygen Reduction Electrocatalysis in Alkaline Electrolytes

   Drew Higgins , Melissa Wette , Brenna M. Gibbons , and 10 more authors

   ACS Applied Energy Materials, May 2018
2. Catalysis

   Theoretical Investigations of Transition Metal Surface Energies under Lattice Strain and CO Environment

   Michael T. Tang , Zachary W. Ulissi, and Karen Chan

   The Journal of Physical Chemistry C, May 2018
3. Catalysis

   Dynamic workflows for routine materials discovery in surface science

   Kevin Tran , Aini Palizhati , Seoin Back , and 1 more author

   Journal of Chemical Information and Modeling, May 2018

2012

1. Catalysis

   Modelling and development of photoelectrochemical reactor for H-2 production

   C. Carver , Zachary W. Ulissi, C. K. Ong , and 3 more authors

   International Journal of Hydrogen Energy, Feb 2012

   Abs

   Photoelectrolysis of aqueous solutions, using one or more semiconducting electrodes in a photoelectrochemical reactor, is a potentially attractive process for hydrogen production because of its prospectively high energy efficiency, simplicity and potentially low cost. The design requirements and preliminary results of modelling a photoelectrochemical (PEC) reactor are described. Potential and current density distributions, due to ohmic potential losses in thin (non-photo) anodes on poorly conducting fluoride-doped tin oxide coated glass substrates, were modelled. The predicted current densities decayed rapidly from the terminals at the edges, towards the centre of a 0.1 x 0.1 m(2) anode, so limiting scale-up with such substrates. Spatial distributions of dissolved oxygen concentrations were also modelled, aiming to define operating conditions that would avoid forming bubbles, which reflect light specularly decreasing photon absorption efficiencies of photoelectrodes. The implications for the future optimization of the reactor are discussed. Copyright (C) 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

2011

1. Catalysis

   Effect of multiscale model uncertainty on identification of optimal catalyst properties

   Zachary W. Ulissi, Vinay Prasad , and Dionisios Vlachos

   Journal of Catalysis, Jul 2011

   Abs

   Computer-based catalyst design has been a long standing dream of the chemistry community for replacing tedious and expensive experimental trial-and-error. While first-principle kinetic modeling emerges as a powerful tool for catalyst selection, it has mainly been limited to using a single catalyst descriptor, simplified chemical kinetic models, and assumptions that question the predictive capability of computational results in the absence of addressing the effect of error in kinetic parameters. Here, we introduce a new framework to address the effect of model uncertainty on optimal catalyst property identification. The framework is applied to the ammonia decomposition reaction for CO-free H(2) production for fuel cells. It is shown that a range of materials, rather than a single material, should be experimentally screened. Among kinetic model parameters, the often neglected adsorbate-adsorbate interactions can have a profound effect on catalyst selection. The importance of lateral interactions is confirmed with recent experimental data. (C) 2011 Elsevier Inc. All rights reserved.

2010

1. Catalysis

   High throughput multiscale modeling for design of experiments, catalysts, and reactors: Application to hydrogen production from ammonia

   Vinay Prasad , Ayman Karim , Zachary W. Ulissi, and 2 more authors

   Chemical Engineering Science, Jan 2010

   Abs

   A novel approach for design of experiments (DOE) is outlined that combines high throughput multiscale modeling, sensitivity analysis, and information extraction from massive computational data using informatics tools. This approach is implemented by conducting experiments of ammonia decomposition on a Ru/gamma-Al(2)O(3) catalyst in a fixed bed reactor. It is shown that a relatively small number of experiments chosen from this new DOE approach can enable refinement of microkinetic models and render them predictive over the (large) experimentally important parameter space. Microkinetic models are subsequently used for process and product design. Specifically, a membrane fixed bed reactor is simulated and is shown to outperform the conventional fixed bed reactor at intermediate temperatures for hydrogen production. Also, the attributes of the best catalyst for ammonia decomposition are identified as a function of processing conditions. It is shown that for NH(3) decomposition, processing conditions do not significantly affect the best catalyst choice. In contrast, fundamental physicochemical phenomena, such as adsorbate adsorbate interactions, can have a profound effect on catalyst discovery. (C) 2009 Elsevier Ltd. All rights reserved.