Thomas P. Senftle

Development of a ReaxFF potential for Pd/O and application to palladium oxide formation

Oxide formation on palladium surfaces impacts the activity and selectivity of Pd-based catalysts, which are widely employed under oxygen rich operating conditions. To investigate oxidation processes over Pd catalysts at time and length scales inaccessible to quantum based computational methods, we have developed a Pd∕O interaction potential for the ReaxFF reactive force field. The parameters of the ReaxFF potential were fit against an extensive set of quantum data for both bulk and surface properties. Using the resulting potential, we conducted molecular dynamics simulations of oxide formation on Pd(111), Pd(110), and Pd(100) surfaces. The results demonstrate good agreement with previous experimental observations; oxygen diffusion from the surface to the subsurface occurs faster on the Pd(110) surface than on the Pd(111) and Pd(100) surfaces under comparable conditions at high temperatures and pressures. Additionally, we developed a ReaxFF-based hybrid grand canonical Monte Carlo∕molecular dynamics (GC-MC∕MD) approach to assess the thermodynamic stability of oxide formations. This method is used to derive a theoretical phase diagram for the oxidation of Pd935 clusters in temperatures ranging from 300 K to 1300 K and oxygen pressures ranging from 10(-14) atm to 1 atm. We observe good agreement between experiment and ReaxFF, which validates the Pd∕O interaction potential and demonstrates the feasibility of the hybrid GC-MC∕MD method for deriving theoretical phase diagrams. This GC-MC∕MD method is novel to ReaxFF, and is well suited to studies of supported-metal-oxide catalysts, where the extent of oxidation in metal clusters can significantly influence catalytic activity, selectivity, and stability.

Influence of Hydroxyls on Pd Atom Mobility and Clustering on Rutile TiO2(011)-2 × 1

Understanding agglomeration of late transition metal atoms, such as Pd, on metal oxide supports, such as TiO2, is critical for designing heterogeneous catalysts as well as for controlling metal/oxide interfaces in general. One approach for reducing particle sintering is to modify the metal oxide surface with hydroxyls that decrease adatom mobility. We study by scanning tunneling microscopy experiments, density functional theory (DFT) calculations, and Monte Carlo (MC) computer simulations the atomistic processes of Pd sintering on a hydroxyl-modified TiO2(011)-2 × 1 surface. The formation of small 1-3 atom clusters that are stable at room temperature is achieved on the hydroxylated surface, while much larger clusters are formed under the same conditions on a hydroxyl-free surface. DFT shows that this is a consequence of stronger binding of Pd atoms adjacent to hydroxyls and increased surface diffusion barriers for Pd atoms on the hydroxylated surface. DFT, kinetic MC, and ReaxFF-based NVT-MC simulations show that Pd clusters larger than single Pd monomers can adsorb the hydrogen from the oxide surface and form Pd hydrides. This depletes the surface hydroxyl coverage, thus allowing Pd to more freely diffuse and agglomerate at room temperature. Experimentally, this causes a bimodal cluster size distribution with 1-3 atom clusters prevalent at low Pd coverage, while significantly larger clusters become dominant at higher Pd concentrations. This study demonstrates that hydroxylated oxide surfaces can significantly reduce Pd cluster sizes, thus enabling the preparation of surfaces populated with metal clusters composed of single to few atoms.

The Holy Grail: Chemistry Enabling an Economically Viable CO2 Capture, Utilization, and Storage Strategy

Technologies for reducing the concentration of CO2 in our atmosphere are essential for mitigating the risks of climate change, and novel chemistry is required for such technologies to work at scale. Here, we highlight challenges that chemists must overcome to realize the Holy Grail of an economically viable strategy for CO2 capture, utilization, and storage.

Growth of Stable Surface Oxides on Pt(111) at Near‐Ambient Pressures

Detailed knowledge of the structure and degree of oxidation of platinum surfaces under operando conditions is essential for understanding catalytic performance. However, experimental investigations of platinum surface oxides have been hampered by technical limitations, preventing in situ investigations at relevant pressures. As a result, the time-dependent evolution of oxide formation has only received superficial treatment. In addition, the amorphous structures of many surface oxides have hindered realistic theoretical studies. Using near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) we show that a time scale of hours (t≥4 h) is required for the formation of platinum surface oxides. These experimental observations are consistent with ReaxFF grand canonical Monte Carlo (ReaxFF-GCMC) calculations, predicting the structures and coverages of stable, amorphous surface oxides at temperatures between 430-680 K and an O2 partial pressure of 1 mbar.

The Role of Surface-Bound Dihydropyridine Analogues in Pyridine-Catalyzed CO2 Reduction over Semiconductor Photoelectrodes

We propose a general reaction mechanism for the pyridine (Py)-catalyzed reduction of CO2 over GaP(111), CdTe(111), and CuInS2(112) photoelectrode surfaces. This mechanism proceeds via formation of a surface-bound dihydropyridine (DHP) analogue, which is a newly postulated intermediate in the Py-catalyzed mechanism. Using density functional theory, we calculate the standard reduction potential related to the formation of the DHP analogue, which demonstrates that it is thermodynamically feasible to form this intermediate on all three investigated electrode surfaces under photoelectrochemical conditions. Hydride transfer barriers from the intermediate to CO2 demonstrate that the surface-bound DHP analogue is as effective at reducing CO2 to HCOO– as the DHP(aq) molecule in solution. This intermediate is predicted to be both stable and active on many varying electrodes, therefore pointing to a mechanism that can be generalized across a variety of semiconductor surfaces, and explains the observed electrode dependence of the photocatalysis. Design principles that emerge are also outlined.

Interaction trends between single metal atoms and oxide supports identified with density functional theory and statistical learning

Single-atom catalysts offer high reactivity and selectivity while maximizing utilization of the expensive active metal component. However, they are susceptible to sintering, where single metal atoms agglomerate into thermodynamically stable clusters. Tuning the binding strength between single metal atoms and oxide supports is essential to prevent sintering. We apply density functional theory, together with a statistical learning approach based on least absolute shrinkage and selection operator regression, to identify property descriptors that predict interaction strengths between single metal atoms and oxide supports. Here, we show that interfacial binding is correlated with readily available physical properties of both the supported metal, such as oxophilicity measured by oxide formation energy, and the support, such as reducibility measured by oxygen vacancy formation energy. These properties can be used to empirically screen interaction strengths between metal–support pairs, thus aiding the design of single-atom catalysts that are robust against sintering.Predicting metal–support combinations that can afford stable single-atom catalysts remains a complex problem. Now, a computational method is reported that can be used to screen interaction strengths between metals and supports and identify those pairs that generate strongly adsorbed single-atom catalysts.

Theoretical Determination of Band Edge Alignments at the Water–CuInS2(112) Semiconductor Interface

Knowledge of a semiconductor electrodes band edge alignment is essential for optimizing processes that occur at the semiconductor/electrolyte interface. Photocatalytic processes are particularly sensitive to such alignments, as they govern the transfer of photoexcited electrons or holes from the surface to reactants in the electrolyte solution. Reconstructions of a semiconductor surface during operation, as well as its interaction with the electrolyte solution, must be considered when determining band edge alignment. Here, we employ density functional theory + U theory to assess the stability of reconstructed CuInS2 surfaces, a system which has shown promise for the active and selective photoelectrocatalytic reduction of CO2 to CH3OH. Using many-body Greens function theory combined with calculations of surface work functions, we determine band edge positions of explicitly solvated, reconstructed CuInS2 surfaces. We find that there is a linear relationship between band edge position and net surface dipole, with the most stable solvent/surface structures tending to minimize this dipole because of generally weak interactions between the surface and solvating water molecules. We predict a conduction band minimum (CBM) of the solvated, reconstructed CuInS2 surface of -2.44 eV vs vacuum at the zero-dipole intercept of the dipole/CBM trendline, in reasonable agreement with the experimentally reported CBM position at -2.64 eV vs vacuum. This methodology offers a simplified approach for approximating the band edge positions at complex semiconductor/electrolyte interfaces.

Hydride Shuttle Formation and Reaction with CO2 on GaP(110)

Adsorbed hydrogenated N-heterocycles have been proposed as co-catalysts in the mechanism of pyridine (Py)-catalyzed CO2 reduction over semiconductor photoelectrodes. Initially, adsorbed dihydropyridine (DHP*) was hypothesized to catalyze CO2 reduction through hydride and proton transfer. Formation of DHP* itself, by surface hydride transfer, indeed any hydride transfer away from the surface, was found to be kinetically hindered. Consequently, adsorbed deprotonated dihydropyridine (2-PyH- *) was then proposed as a more likely catalytic intermediate because its formation, by transfer of a solvated proton and two electrons from the surface to adsorbed Py, is predicted to be thermodynamically favored on various semiconductor electrode surfaces active for CO2 reduction, namely GaP(111), CdTe(111), and CuInS2 (112). Furthermore, this species was found to be a better hydride donor for CO2 reduction than is DHP*. Density functional theory was used to investigate various aspects of 2-PyH- * formation and its reaction with CO2 on GaP(110), a surface found experimentally to be more active than GaP(111). 2-PyH- * formation was established to also be thermodynamically viable on this surface under illumination. The full energetics of CO2 reduction through hydride transfer from 2-PyH- * were then investigated and compared to the analogous hydride transfer from DHP*. 2-PyH- * was again found to be a better hydride donor for CO2 reduction. Because of these positive results, full energetics of 2-PyH- * formation were investigated and this process was found to be kinetically feasible on the illuminated GaP(110) surface. Overall, the results presented in this contribution support the hypothesis of 2-PyH- *-catalyzed CO2 reduction on p-GaP electrodes.

CHAPTER 4:Application of Computational Methods to Supported Metal–Oxide Catalysis

Enhancing the design of supported metal–oxide catalysts, featuring metal particles dispersed on an oxide support, is essential for optimizing the performance of numerous industrial chemical processes. Advances in computational chemistry over the last few decades have had a great impact on design strategies for obtaining active, selective, and stable catalysts. This chapter outlines computational approaches for modeling metal–oxide catalytic systems at the atomic level, and reviews pertinent studies that exemplify these methods. Examples are chosen to emphasize both quantum-based methods [utilizing density functional theory (DFT) and ab initio thermodynamics] and classical force-field methods (utilizing the ReaxFF empirical potential). We discuss studies that use DFT to evaluate the relative energies of metal–oxide surface structures, studies that extend the formalism of DFT to non-zero temperature and pressure via ab initio thermodynamics, and finally studies that use the COMB and ReaxFF empirical force-fields in MD and MC simulations to investigate system dynamics and structure at large scales. Reviewing the application of these methods will provide the reader with a general understanding of how computational methods can be applied to atomistic studies of supported metal–oxide catalysts.