Engineering topics
Deo, Shyam
Publications and source records attributed to Deo, Shyam.
Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance
Computationally predicting the performance of catalysts under reaction conditions is a challenging task due to the complexity of catalytic surfaces and their evolution in situ, different reaction paths, and the presence of solid-liquid interfaces in the case of electrochemistry. We demonstrate here how relatively simple machine learning models can be found that enable prediction of experimentally observed onset potentials. Inputs to our model are comprised of data from the oxygen reduction reaction on non-precious transition-metal antimony oxide nanoparticulate catalysts with a combination of experimental conditions and computationally affordable bulk atomic and electronic structural descriptors from density functional theory simulations. From human-interpretable genetic programming models, we identify key experimental descriptors and key supplemental bulk electronic and atomic structural descriptors that govern trends in onset potentials for these oxides and deduce how these descriptors should be tuned to increase onset potentials. Here, we finally validate these machine learning predictions by experimentally confirming that scandium as a dopant in nickel antimony oxide leads to a desired onset potential increase. Macroscopic experimental factors are found to be crucially important descriptors to be considered for models of catalytic performance, highlighting the important role machine learning can play here even in the presence of small datasets.
A First-Principles Approach to Modeling Surface Site Stabilities on Multimetallic Catalysts
The study of multimetallic alloys and the multitude of possible surface compositions have sparked a tremendous interest in engineering low-cost materials with high activity and selectivity in heterogeneous catalysis. Multimetallic systems provide complementary functionalities and an unprecedented tunability when designing catalyst formulations. However, due to their immense structural and compositional complexity, the investigation and identification of an optimal catalyst is a tedious and time-consuming process, both experimentally and theoretically. Therefore, theoretical design principles are highly desirable to accelerate the screening of catalyst structures across the vast compositional space. In this paper, we introduce a simple and general model for predicting the site stability of multimetallic surfaces and nanoparticles, which is based on physical principles. The model requires only a small set of density functional theory (DFT) calculations of metal atom binding energies on monometallic and dilute alloy surface slabs to optimize the parameters in the simple model. The resulting model allows for the quantification of the stability of any particular atom site in any conceivable chemical environment across a wide range of morphologies, sizes, and arrangements by interpolating the derived parameters from a monometallic system to a completely diluted alloyed system. Herein, we demonstrate the robustness of the model across an extensive data set of transition metal alloy surfaces and 147-atoms cuboctahedral nanoparticles (NPs) composed of IrRhRu and PtPdRu. In conclusion, our approach yields mean absolute errors of ≈0.15 (IrRhRu), 0.20 (PtPdRu), 0.19 (IrRhRu NP), and 0.26 (PtPdRu NP) eV relative to site binding energies calculated using DFT.
Control of Molecular Bonding Strength on Metal Catalysts with Organic Monolayers for CO 2 Reduction
The development of separate levers for controlling the bonding strength of different reactive species on catalyst surfaces is challenging but essential for the design of highly active and selective catalysts. For example, during CO 2 reduction, production of CO often requires balancing a trade-off between the adsorption strength of the reactant and product states: weak binding of CO is desirable from a selectivity perspective, but weak binding of CO 2 leads to low activity. Here in this paper, we demonstrate a new method of controlling both CO 2 adsorption and CO desorption over supported metal catalysts by employing a single self-assembly step where organic monolayer films were deposited on the catalyst support. Binding of phosphonic acid monolayers on supported Pt and Pd catalysts weakened CO binding via a through-support effect. The weakened CO adsorption was generally accompanied by decreased adsorption and reactivity of CO 2 . However, by the incorporation of basic amine functions at controlled positions in the modifying film, strong CO 2 adsorption and hydrogenation reactivity could be restored. Thus, both through-surface and through-space interactions could be manipulated by design of the organic modifiers. After surface modification, the catalysts exhibited significantly improved selectivity (up to ~99% at conversions near 50%) and activity toward CO production. Moreover, the rate of deactivation was notably reduced due to prevention of CO poisoning.
Activity and Selectivity Control in CO 2 Electroreduction to Multicarbon Products over CuO x Catalysts via Electrolyte Design
The CO 2 electroreduction reaction (CO 2 RR) to chemicals and fuels is of both fundamental and practical significance, since it would lead to a more efficient storage of renewable energy while closing the carbon cycle. Here we report enhanced activity and selectivity for the CO 2 RR to multicarbon hydrocarbons and alcohols (~69% Faradaic efficiency and -45.5 mA cm –2 partial current density for C 2+ at -1.0 V vs RHE) over O 2 -plasma-activated Cu catalysts via electrolyte design. Increasing the size of the alkali-metal cations in the electrolyte, in combination with the presence of subsurface oxygen species which favor their adsorption, significantly improved C–C coupling on CuO x electrodes. The coexistence of Cs + and I – induced drastic restructuring of the CuO x surface, the formation of shaped particles containing stable CuI species, and a more favorable stabilization of the reaction intermediates and concomitant high C 2+ selectivity. This work, combining both experiment and density functional theory, provides insights into the active sites and reaction mechanism of oxide-derived Cu catalysts for the CO 2 RR.