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At least 1,387 records · Page 77

Revisiting Competing Paths in Electrochemical CO 2 Reduction on Copper via Embedded Correlated Wavefunction Theory

We re-evaluate two key steps in the mechanism of CO 2 reduction on copper at a higher level of theory capable of correcting inherent errors in density functional theory (DFT) approximations, namely, embedded correlated wavefunction (ECW) theory. Here, we consider the CO reduction step on Cu(111), which is critical to understanding reaction selectivity. Here, we optimize embedding potentials at the periodic plane-wave DFT level using density functional embedding theory (DFET). All possible adsorption sites (adsites) for each adsorbate then are screened with ECW theory at the catalytically active site to refine the local electronic structure. Unsurprisingly, DFT and ECW theory predict different adsite preferences, largely because of DFT’s inability to properly situate the CO 2π* level. Differing preferred adsites suggest that different reaction pathways could emerge from DFT versus ECW theory. Starting from these preferred ECW theory adsites, we then obtain reaction pathways at the plane-wave DFT level using the climbing-image nudged elastic band method to determine minimum energy paths. Thereafter, we perform ECW calculations at the catalytically active site to correct the energetics at each interpolated structure (image) along the reaction pathways. Via this approach, we confirm that the first step in CO reduction via hydrogen transfer on Cu(111) is to form hydroxymethylidyne (*COH) instead of formyl (*CHO). Although the prediction to preferentially form *COH is consistent with that of DFT, the two theories predict quite different structural and mechanistic behaviors, suggesting that verification is needed for other parts of the mechanism of CO 2 reduction, which is the subject of ongoing work.

30 DIRECT ENERGY CONVERSION↗

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry

Modeling complex materials using high-fidelity, ab initio methods at low cost is a fundamental goal for quantum chemical software packages. The GW approximation and random phase approximation (RPA) provide a unified description of both electronic structure and total energies using the same physics in a many-body perturbative approach that can be more accurate than generalized-gradient density functional theory (DFT) methods. However, GW/RPA implementations have historically been limited to either specific materials classes or application toward small chemical systems. Here, the static subspace approximation allows for reduced cost full-frequency GW/RPA calculations and has previously been benchmarked thoroughly for GW calculations. Here, we describe our approach to including partial occupations of electronic orbitals in full-frequency GW and RPA calculations for the study of electrocatalysts. We benchmarked RPA total energy calculations using the subspace approximation across a diverse test suite of materials for a variety of computational parameters. The benchmarking quantifies the impact of different extrapolation procedures for representing the static polarizability at infinite screened cutoff, and shows that using screened cutoffs above 20-25 Ryd result in diminishing accuracy returns for predicting RPA total energies. Additionally, for moderately sized electrocatalytic models, 2-3 times fewer computational resources are used to compute RPA total energies by representing the static polarizability with 20-30% of the static subspace basis, with an error of approximately 0.01 eV or better in RPA adsorption energy calculations. Finally, we show that for these electrochemical models RPA can shift DFT adsorption energy shifts by up to 0.5 eV and that GW can frequently shift DFT eigenvalues of surface and adsorbate states by approximately 0.5-1 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ruthenium Dye Excitations and Relaxations in Natural Sunlight

Solar harvesting devices using dyes convert the sun's energy to usable forms. The photophysics involved are generally investigated using time-resolved spectroscopic experiments with femtosecond to nanosecond resolution. We show that a kinetic framework constructed from transient and linear absorption measurements of metal-ligand charge transfer states for a set of ruthenium complexes in solution can be used to simulate the steady-state dynamics of dyes adsorbed on a substrate under diffuse solar radiation. Even though the intensity of sunlight is relatively low, double excitations to higher excited states can occur. The steady-state populations show that the dyes' triplet state is the main species present besides the ground state. While small, these persistent excited populations can influence reactivity over the extended periods of time that the systems operate. The results show that non-radiative and optical events (dye -1 s -1 ) within the singlet manifold and from the triplet state exhibit a dependence on ligand substituents.

14 SOLAR ENERGY↗

Metal-to-Ligand Charge-Transfer Spectrum of a Ru-Bipyridine-Sensitized TiO 2 Cluster from Embedded Multiconfigurational Excited-State Theory

Understanding optical properties of the dye molecule in dye-sensitized solar cells (DSSCs) from first-principles quantum mechanics can contribute to improving the efficiency of such devices. While density functional theory (DFT) and time-dependent DFT have been pivotal in simulating optoelectronic properties of photoanodes used in DSSCs at the atomic scale, questions remain regarding DFT’s adequacy and accuracy to furnish critical information needed to understand the various excited-state processes involved. In this work, we simulate the absorption spectra of a dye-sensitized solar cell analogue, comprised of a Ru-bipyridine (Ru-bpy) dye molecule and a small TiO2 cluster via DFT and via an accurate embedded correlated wavefunction (CW) theory. We generated CW spectra for the adsorbed Ru-bpy dye via a recently introduced capped density functional embedding theory or capped-DFET (to generate the embedding potential that accounts for the interaction of the molecule and the TiO 2 cluster). We then combined capped-DFET with the accurate but expensive multiconfigurational complete active space second-order perturbation theory (CASPT2)—embedded CASPT2. Because the CW theory is conducted on only a portion of the total system in the presence of an embedding potential that describes that portion’s interaction with its environment, we efficiently obtain CW-quality predictions that reflect local properties of the entire system. Specifically, for example, with capped-DFET and embedded CW theory, we can simulate accurately a plethora of metal-to-ligand charge-transfer excited properties at a manageable computational cost. Here, we predict detailed electronic spectra within the visible region, featuring the lowest three singlet and triplet excited states, along with predictions of the singlets’ lifetimes. We illustrated these results using a Jablonski diagram that show the relative energy position of the singlet and longer-lived triplet excited states and analyzed and proposed relaxation paths for the excited state corresponding to the most intense but short-lived absorption (interconversion, intersystem crossing, fluorescence, and phosphorescence) that may lead to longer-lived excited states necessary for efficient charge separation required to generate current in solar cells.

14 SOLAR ENERGY↗

Coupled Interfacial and Bulk Kinetics Govern the Timescales of Multiphase Ozonolysis Reactions

Chemical transformations in aerosols impact the lifetime of particle phase species, the fate of atmospheric pollutants, and both climate- and health-relevant aerosol properties. Timescales for multiphase reactions of ozone in atmospheric aqueous phases are governed by coupled kinetic processes between the gas phase, the particle interface, and its bulk, which respond dynamically to reactive consumption of O 3 . However, models of atmospheric aerosol reactivity often do not account for the coupled nature of multiphase processes. Herein, to examine these dynamics, we use new and prior experimental observations of aqueous droplet reaction kinetics, including three systems with a range of surface affinities and ozonolysis rate coefficients ( trans -aconitic acid (C 6 H 6 O 6 ), maleic acid (C 4 H 4 O 4 ), and sodium nitrite (NaNO 2 )). Using literature rate coefficients and thermodynamic properties, we constrain a simple two-compartment stochastic kinetic model which resolves the interface from the particle bulk and represents O 3 partitioning, diffusion, and reaction as a coupled kinetic system. Our kinetic model accurately predicts decay kinetics across all three systems, demonstrating that both the thermodynamic properties of O 3 and the coupled kinetic and diffusion processes are key to making accurate predictions. An enhanced concentration of adsorbed O 3 , compared to gas and bulk phases is rapidly maintained and remains constant even as O 3 is consumed by reaction. Multiphase systems dynamically seek to achieve equilibrium in response to reactive O 3 loss, but this is hampered at solute concentrations relevant to aqueous aerosol by the rate of O 3 arrival in the bulk by diffusion. As a result, bulk-phase O 3 becomes depleted from its Henry's law solubility. This bulk-phase O 3 depletion limits reaction timescales for relatively slow-reacting organic solutes with low interfacial affinity (i.e., trans-aconitic and maleic acids, with k rxn ≈ 10 3 -10 4 M -1 s -1 ), which is in contrast to fast-reacting solutes with higher surface affinity (i.e., nitrite, with k rxn ≈ 10 5 M -1 s -1 ) where surface reactions strongly impact the observed decay kinetics.

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Effects of Field Strength and Silver Nanowire Size on Plasmon-Enhanced N 2 Dissociation

Dissociation of the nitrogen molecule via plasmon-enhanced catalysis using noble metal nanoparticles has been investigated both experimentally and computationally in recent years. However, the mechanism of plasmon-enhanced nitrogen dissociation is still not very clear. In this work, we apply theoretical approaches to examine the dissociation of a nitrogen molecule on atomically-thin Ag n nanowires (n = 6, 8, 10, 12) and a Ag 19 + nanorod. Ehrenfest dynamics provides information about the motion of nuclei during the dynamics process and real-time TDDFT calculations show the electronic transitions and population of electrons over the first 10s of fs time scale. The activation and dissociation of nitrogen is typically enhanced when the electric field strength increases. However, the enhancement is not always monotonic with field strength. As the length of the Ag wire increases, nitrogen is typically easier to dissociate and thus requires lower field strengths, even though the plasmon frequency is lower. The Ag 19 + nanorod leads to faster dissociation of N 2 than the atomically-thin nanowires. Altogether, our detailed study yields insights into the mechanisms involved in plasmon-enhanced N 2 dissociation, as well as provides information about factors that can be used to improve adsorbate activation.

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Computing Thermodynamic Properties of Fluids Augmented by Nanoconfinement: Application to Pressurized Methane

Nanoconfined fluids exhibit remarkably different thermodynamic behavior compared to the bulk phase. These confinement effects render predictions of thermodynamic quantities of nanoconfined fluids challenging. In particular, confinement creates a spatially varying density profile near the wall that is primarily responsible for adsorption and capillary condensation behavior. Significant fluctuations in thermodynamic quantities, inherent in such nanoscale systems, coupled to strong fluid–wall interactions give rise to this near-wall density profile. Empirical models have been proposed to explain and model these effects, yet no first-principles based formulation has been developed. We present a statistical mechanics framework that embeds such a coupling to describe the effect of the fluid–wall interaction in amplifying the near-wall density behavior for compressible gases at elevated pressures such as pressurized methane in confinement. We show that the proposed theory predicts accurately the adsorbed layer thickness as obtained with small-angle neutron scattering measurements. Furthermore, the predictions of density under confinement from the proposed theory are shown to be in excellent agreement with available experimental and atomistic simulations data for a range of temperatures for nanoconfined methane. While the framework is presented for evaluating the near-wall density, owing to its rigorous foundation in statistical mechanics, the proposed theory can also be generalized for predicting phase-transition and nonequilibrium transport of nanoconfined fluids.

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Enhancing Nanoparticle Detection in Interferometric Scattering (iSCAT) Microscopy Using a Mask R-CNN

Interferometric scattering microscopy (iSCAT) is a label-free optical microscopy technique that enables imaging of individual nano-objects such as nanoparticles, viruses, and proteins. Essential to this technique is the suppression of background scattering and identification of signals from nano-objects. In the presence of substrates with high roughness, scattering heterogeneities in the background, when coupled with tiny stage movements, cause features in the background to be manifested in background-suppressed iSCAT images. Traditional computer vision algorithms detect these background features as particles, limiting the accuracy of object detection in iSCAT experiments. Here, in this paper, we present a pathway to improve particle detection in such situations using supervised machine learning via a mask region-based convolutional neural network (mask R-CNN). Using a model iSCAT experiment of 19.2 nm gold nanoparticles adsorbing to a rough layer-by-layer polyelectrolyte film, we develop a method to generate labeled datasets using experimental background images and simulated particle signals and train the mask R-CNN using limited computational resources via transfer learning. We then compare the performance of the mask R-CNN trained with and without inclusion of experimental backgrounds in the dataset against that of a traditional computer vision object detection algorithm, Haar-like feature detection, by analyzing data from the model experiment. Results demonstrate that including representative backgrounds in training datasets improved the mask R-CNN in differentiating between background and particle signals and elevated performance by markedly reducing false positives. The methodology for creating a labeled dataset with representative experimental backgrounds and simulated signals facilitates the application of machine learning in iSCAT experiments with strong background scattering and thus provides a useful workflow for future researchers to improve their image processing capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Structure and Thermodynamics of CO 2 and Water Adsorption on Mica

The adsorption of CO 2 and water on clay surfaces plays a key role in applications, such as gas storage in saline aquifers and depleted hydrocarbon reservoirs, but is not yet fully understood. Here, we study the adsorption of CO 2 and water vapor using Grand Canonical Monte Carlo and molecular dynamics simulations. At a bulk pressure of 100 bar, pure CO 2 adsorbs strongly on mica and forms extensive layers next to it. CO 2 adsorption is lowered substantially if introducing water vapor above mica and is largely eliminated when the relative humidity (RH) approaches about 60%. When pure water vapor is introduced above a mica surface, a subnanometer thick liquid water film develops on it to form apparent liquid–solid and liquid–vapor interfaces simultaneously. Using the identification of truly interfacial molecules (ITIM) analysis, we delineate how individual water layers develop in this film as RH increases. We highlight that the water film is spatially heterogeneous and the true liquid–vapor interface emerges only at an RH of 60–80%. Introducing 100 bar of CO 2 into the water vapor above the mica surface modulates water adsorption nonlinearly: at RH = 0.01%, the water adsorption is reduced by ∼30%; as RH increases, the reduction is weakened, and eventually, enhancement of water adsorption by about 7% occurs at RH = 90%. These variations are attributed to the interplay of film thinning by high-pressure CO 2 , competition of mica surface sites by CO 2 molecules, and energetic and entropic stabilization of interfacial water by CO 2 molecules.

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Intermediate Species in the Crystallization of Sodium Aluminate Hydroxy Hydrates

In highly alkaline “water-in-salt” Na 2 O/Al 2 O 3 /H 2 O solutions where the monomeric Al(OH) 4 - anion dominates, isolation of transitional species that seed crystallization of sodium aluminate salt hydrates has been challenging. For example, discrimination of dimeric [e.g., Al 2 O(OH) 6 2- ] from species via 27 Al nuclear magnetic resonance (NMR) spectroscopy is limited via fast interconversion through hydrolysis and condensation reactions. Despite this, using magic-angle spinning NMR ( 27 Al MAS NMR) at high magnetic field strengths (14.1 and 20.0 T) on crystals of nonasodium bis(hexahydroxyaluminate) trihydroxide hexahydrate [NSA, Na 9 [Al(OH) 6 ] 2 ·3(OH)·6(H 2 O)], we observed a 27 Al resonance consistent with Na 2 Al 2 O(OH) 6 . This tetrahedral dimeric species was also identified in the mother liquor by Raman spectroscopy while remaining expectedly unresolved by high-field liquid-state 27 Al NMR. Its substantial abundance in the mother liquor and as either an interstitial or an adsorbate on precipitated solids suggest that it plays a crucial role in NSA crystallization. Here, our detailed characterization, which includes single-pulse 27 Al MAS NMR, nutation 27 Al MAS NMR, and multiple quantum 27 Al MAS NMR, provides new molecular insights into how aluminate transitions from tetrahedral in solution to octahedral in solid. This understanding could ultimately lead to better predictions of aluminum phase change behavior in caustic sodium hydroxide with wide-ranging technological and environmental implications.

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Surface Hydration and Hydroxyl Configurations of Gibbsite and Boehmite Nanoplates

Discontinuation of the bulk structure at the interface between metal oxide particles and water leads to altered bonding characteristics and unique facet-dependent molecular environments. Surface hydration and consequent hydroxylation adds further complexity to the interface, details that for metal (oxy)hydroxides are especially difficult to isolate from the background signal of bulk structural hydroxyls. Here we probe for the first time the hydroxylation and hydration structures on basal surfaces of gibbsite (?-Al(OH)3) and boehmite (?-AlOOH) nanoplates at ambient conditions, using the interface-sensitive technique vibrational sum frequency generation spectroscopy (VSFG). Hydroxyl stretching modes at the interfaces with adsorbed water layers compared directly to Raman and infrared bulk modes show that while gibbsite surface frequencies were sharp and nearly identical to those in the bulk, boehmite surface hydroxyls displayed a very different broad spectrum of states. Ab initio molecular dynamics simulations of both basal surfaces with and without hydration waters reveal that gibbsite surface hydroxyls interact only weakly with overlying hydration waters remaining essentially unperturbed, whereasthose on boehmite can interact more strongly facilitated by higher configurational degrees of freedom at the interface. The findings clearly unveil substantial differences in the hydrated interfacial dynamics of these two otherwise similar materials, with implications for their interfacial chemistry and wettability.

Sassi, Michel JPC↗

Mechanistic understanding of catalytic conversion of ethanol to 1-butene over 2D-pillared MFI zeolite

Ethanol is an important C2 platform molecule for producing value-added chemicals and distillate hydrocarbon fuels (e.g., jet and diesel). Among these, catalytic upgrading of ethanol to butenes can generate valuable commodity chemicals (e.g., 1-butene) and provide C4 olefin intermediates that can be further upgraded to jet/diesel fuels. 2D zeolites offer hierarchical mesoporous structures, leading to improved mass transport and reduced diffusion length, which can help to address the coking challenges faced by ethanol conversion to hydrocarbons over 3D zeolites. In this study, we investigate the acid-catalyzed conversion of ethanol to 1-butene over the Brønsted acid sites (BAS) in 2D-pillared MFI zeolite (2D-PMFI) using ab initio molecular dynamics (AIMD) simulations, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and calorimetric measurements. A detailed thermodynamic analysis, using quasi-harmonic approximation (QHA), on the Gibbs free energy pathway of ethanol conversion shows that the consideration of entropy is critical to accurately capture the detailed thermodynamic profiles. The formation of bulky ethoxy-ethene complex is found to be a potential rate-determining step (RDS), proceeding via stepwise mechanism. The reactivity of 2D-PMFI can be further tuned by manipulating RDS through a careful control of number of BAS and operating temperatures. The accuracy of computational model is confirmed through the comparison of calculated vibrational density of states (VDOS) against the experimental DRIFTS measurements. Overall, our study provides mechanistic insights into ethanol upgrading over the 2D-PMFI and shows the importance of evaluating entropic effects in such confined system.

Ethanol conversion, 2D-pillared zeolite, MFI, Anha↗

Reactivity of a Zirconia–Copper Inverse Catalyst for CO 2 Hydrogenation

Copper–zirconia catalysts have been shown to be effective for methanol synthesis via CO 2 hydrogenation, yet the active phases and reaction mechanism remain uncertain. Here, an inverse model catalyst ZrO 2 /CuO 2 /Cu(111) was prepared by mass-selected ion deposition and tested for CO 2 hydrogenation under near-ambient pressure (AP) reaction conditions by using X-ray photoelectron spectroscopy (NAP-XPS) and infrared reflection–absorption spectroscopy (NAP-IRAS). The spatial resolution afforded by the small entrance cone of the AP-XPS spectrometer was used to resolve regions of the surface with and without Zr deposition. Carbon 1s core level spectra of the ZrO 2 /Cu 2 O/Cu(111) regions of the surface under 500 mTorr of CO 2 + H 2 (1:3 ratio) show evidence for reaction intermediates including carbonate (CO 3 *), formate (HCOO*), and H x CO* species, with methoxy having the highest surface concentration at 500–600 K. These intermediates are confirmed by IRAS vibrational spectra. In regions of the surface without Zr, the Cu 2 O/Cu(111) is reduced to metallic Cu, and the surface intermediates are different and are present at much lower concentrations. The observed surface intermediates and their temperature dependence suggest a mechanism in which CO 2 is adsorbed on zirconia as carbonate (CO 3 *) and then converted to HCOO* and H x CO* hydrogenated intermediates that ultimately lead to methoxy (CH 3 O*), the final surface-bound precursor for methanol. Overall, the results clearly demonstrate the promotional effects of small ZrO 2 particles for enhancing the reactivity of Cu surfaces for CO 2 hydrogenation.

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Radiation-Induced Interfacial Hydroxyl Transformation on Boehmite and Gibbsite Basal Surfaces

Understanding the radiolytic reactivity of aluminum oxyhydroxide phases widely present in stored nuclear wastes is essential to develop reliable processing approaches. Recent experiments using vibrational sum frequency generation (VSFG), a surface sensitive technique, have shown that rehydration of γ-irradiated boehmite (010) and gibbsite (001) surfaces does not recover the initial hydroxyl density prior to irradiation. In this study, using density functional theory and nudged elastic band calculations, we examine dehydration and rehydration of these surfaces and attendant proton transfer mechanisms. While dehydration of both surfaces is predicted to be energetically unfavorable, rehydration of boehmite (010) is favorable after overcoming an energy barrier of 0.52 eV that relates to the orientation of surface hydroxyls controlling the hydrogen bonding network of adsorbed water. In the case of gibbsite (001), for which the experimental results suggest that rehydration mainly involves the reformation of interlayer hydroxyls, we found that a two-proton transfer mechanism is more likely than a one-proton transfer mechanism, and that it prevents the reorientation of interlayer hydroxyls into intralayer hydroxyls consistent with experimental VSFG findings. A detailed analysis of the effect of surface hydrogen vacancy on the strength of hydrogen bond interactions was performed, which indicates that H 2 and H 2 O are the energetically most favorable product species to form from radiation-induced surface H and/or OH defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Role of the Solvent–Surfactant Duality of Ionic Liquids in Directing Two-Dimensional Particle Assembly

Nanoparticle self-assembly plays a key role in formation of superlattices, which exhibit remarkable physical and chemical properties. However, controlling assembly remains a challenge partly due to a lack of understanding of the assembly dynamics and the difficulty in linking interfacial solution properties to interparticle forces. In this study, using liquid-cell transmission electron microscopy, self-assembly of gold nanoparticles (NPs) into superlattices in mixtures of water and ionic liquid (IL) was visualized, revealing a dual role of the IL in the assembly process. At intermediate concentrations, the IL acts as a surfactant stabilizing the particles at a well-defined equilibrium separation corresponding to the length of hydrogen bonded IL cations adsorbed onto neighboring NPs. Analysis of the interparticle forces reveals attractive long-range interactions of a van der Waals nature. At separations of 1-3 nm, interactions are dominated by attractive ion correlation and repulsive hydration forces giving rise to an energy minimum at 1.5 nm separation. The superlattice is further stabilized by hydrogen bonding, which shifts the equilibrium interparticle distance to 1.1 nm. In contrast, at higher concentrations, IL accumulates and forms a structured network in the gap between nanoparticles, where it acts as a solvent that eliminates the repulsive barrier and thus promotes particle coalescence. This solvent-surfactant duality of IL opens new opportunities for their use in directing particle assembly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stability of Pt Skin Intermetallic Core Catalysts and Adsorption Properties for the Oxygen Reduction Reaction

Density functional theory calculations were used to determine the stability of metal slabs consisting of a Pt surface monolayer and intermetallic supporting layers made from combinations of six transition metal elements (Pt, Fe, Co, Ni, Cu, and Ag), as a model system for Pt skin intermetallic core nanoparticle catalysts. The stability of the slabs is largely determined by strain at the interface of the Pt skin and the subsurface intermetallic, which was described by a lattice matching parameter (r). The surface charge on the Pt skin was found to be correlated with the average electronegativity (EN) of the intermetallic core, so this average EN was used as a descriptor for how the electronic coupling (or ligand effect) affects adsorption energies. A total of 46 slabs were investigated in terms of their stability, from which 10 stable slabs were selected for further studies of adsorbate binding (OOH*, O*, and OH*) that are intermediates in the oxygen reduction reaction (ORR). The correlation between all three adsorption energies and descriptors r and EN was found. Using a linear fit between our descriptors and the calculated adsorption energies, the overpotential for the ORR was obtained as a function of r and EN, from which a volcano plot was produced. The volcano peak was found at r = 0.96 or at EN = 2.025. Interestingly, neither r nor EN was a sufficient single reactivity descriptor as the data points were well off the general trend in both linear fits; this implies that both the strain effect and the ligand effect influence the adsorption energies, although they are partly correlated. The (r, EN) target peak parameters were used to screen over 241 intermetallic combinations of transition metal elements as active ORR activity. In conclusion, this analysis identified 11 intermetallic compounds which can support a Pt skin to have a high predicted ORR activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasmon-Induced CO 2 Conversion on Al@Cu 2 O: A DFT Study

In plasmonic catalysis, localized surface plasmon was leveraged to drive chemical reactions. This approach is promising for catalyzing many challenging reactions at relatively low temperatures and pressures. We apply density functional calculations to provide the insight for the mechanism of plasmon-induced direct CO 2 dissociation on an Al@Cu 2 O core-shell structure, which was observed in a previous experimental study. We show that the interaction of Cu 2 O with CO 2 results in the accessible antibonding states of the adsorbed CO 2 in the range of visible light. Though the intrinsic activation barrier for direct CO 2 dissociation is as high as 3.6 eV, we find that an effective reaction barrier of CO 2 dissociation under photon excitation could be reduced by 2 eV. We also show that the charge transfer is more pronounced in the final state of the dissociation due to the strong hybridization of the dissociated species with Cu 2 O. These results thus provide an explanation for the visible-light-induced direct CO 2 dissociation at relatively low temperature and under ambient pressure. This finding also shows the promising impact of plasmonic catalysis in mitigating carbon emission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗