How Well Can Quantum Embedding Method Predict the Reaction Profiles for Hydrogenation of Small Li Clusters?

Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available number of physical qubits with high fidelity limit its application to small chemical systems. This work employed a quantum-classical framework which features a quantum active space-embedding approach to perform simulations of chemical reactions that require up to 14 qubits. This framework was applied to prototypical example metal hydrogenation reactions: the coupling between hydrogen and Li2, Li3, and Li4 clusters. Particular attention was paid to the computation of barriers and reaction energies. The predicted reaction profiles compare well with advanced classical quantum chemistry methods, demonstrating the potential of the quantum embedding algorithm to map out reaction profiles of realistic gas-phase chemical reactions to ascertain qualitative energetic trends. Additionally, the predicted potential energy curves provide a benchmark to compare against both current and future quantum embedding approaches.

Au36(SR)22 Nanocluster and a Periodic Pattern from Six to Fourteen Free Electrons in Core Size Evolution.

An Au36(S-tBu)22 nanocluster (NC) is synthesized using the bulky tert-butyl thiol as the ligand. Single-crystal X-ray crystallography reveals that it has an Au25 core which evolves from the Au22 core in the previously reported Au30(S-tBu)18, and the Au25 core is protected by longer staple-like surface motifs. The new Au36 NC extends the members of the face-centered cubic structural evolution by adding an Au3 triangle and an Au4 tetrahedron unit. Additionally, it is found that Au36 emits near-infrared photoluminescence at 863 nm with a quantum yield (QY) of 4.3%, which is five times larger than that of Au30(S-tBu)18-the closest neighbor in the structural evolution pattern. The higher QY of Au36 is attributed to a larger radiative relaxation (kr), resulting from the structural effect. Finally, we find that the longer staple motifs lead to enhanced stability of Au36(S-tBu)22 relative to Au30(S-tBu)18.

Boosting CO2 Electrochemical Reduction with Atomically Precise Surface Modification on Gold Nanoclusters.

Thiolate-protected gold nanoclusters (NCs) are promising catalytic materials for the electrochemical CO2 reduction reaction (CO2 RR). In this work an atomic level modification of a Au23 NC is made by substituting two surface Au atoms with two Cd atoms, and it enhances the CO2 RR selectivity to 90-95 % at the applied potential between -0.5 to -0.9 V, which is doubled compared to that of the undoped Au23 . Additionally, the Cd-doped Au19 Cd2 exhibits the highest CO2 RR activity (2200 mA mg-1 at -1.0 V vs. RHE) among the reported NCs. This synergetic effect between Au and Cd is remarkable. Density-functional theory calculations reveal that the exposure of a sulfur active site upon partial ligand removal provides an energetically feasible CO2 RR pathway. The thermodynamic energy barrier for CO formation is 0.74 eV lower on Au19 Cd2 than on Au23 . These results reveal that Cd doping can boost the CO2 RR performance of Au NCs by modifying the surface geometry and electronic structure, which further changes the intermediate binding energy. This work offers insights into the surface doping mechanism of the CO2 RR and bimetallic synergism.

Active sites of ligand-protected Au25 nanoparticle catalysts for CO2 electroreduction to CO.

Recent experimental studies have reported the electrochemical reduction of carbon dioxide (CO2) into CO at atomically precise negatively charged Au25 (-) nanoclusters. The studies showed CO2 conversion at remarkably low overpotentials, but the exact mechanisms and nature of the active sites remain unclear. We used first-principles density functional theory and continuum solvation models to examine the role of the cluster during electrochemical CO2 reduction and analyze the free energies of proposed intermediate species. Contrary to previous assumptions, our results show that the fully ligand protected cluster is not an active CO2 reduction catalyst because formation of the crucial carboxyl intermediate required very high electrochemical potentials. Instead, our calculations suggest that the reduction process likely occurs on a dethiolated gold site, and adsorbed carboxyl intermediate formation was significantly stabilized at dethiolated gold sites. These findings point to the crucial role of exposed metal sites during electrochemical CO2 reduction at gold nanocluster catalysts.

Kinetic Monte Carlo simulation of CO adsorption on sulfur-covered Pd(100).

The use of atomistic Kinetic Monte Carlo method was explored to examine the influence of sulfur poisoning on CO adsorption on Pd(100) surface. The model explicitly incorporates key elementary processes such as CO adsorption and CO desorption including diffusion of surface CO and S species. Relevant energetic and kinetic parameters were derived using information calculated from density functional theory as a starting point. Kinetic Monte Carlo simulation was performed to determine relevant observables such as CO saturation coverage as a function of amount of preadsorbed sulfur and to predict temperature programmed desorption spectra.

Photomediated Oxidation of Atomically Precise Au25(SC2H4Ph)18(-) Nanoclusters.

The anionic charge of atomically precise Au25(SC2H4Ph)18(-) nanoclusters (abbreviated as Au25(-)) is thought to facilitate the adsorption and activation of molecular species. We used optical spectroscopy, nonaqueous electrochemistry, and density functional theory to study the interaction between Au25(-) and O2. Surprisingly, the oxidation of Au25(-) by O2 was not a spontaneous process. Rather, Au25(-)-O2 charge transfer was found to be a photomediated process dependent on the relative energies of the Au25(-) LUMO and the O2 electron-accepting level. Photomediated charge transfer was not restricted to one particular electron accepting molecule or solvent system, and this phenomenon likely extends to other Au25(-)-adsorbate systems with appropriate electron donor-acceptor energy levels. These findings underscore the significant and sometimes overlooked way that photophysical processes can influence the chemistry of ligand-protected clusters. In a broader sense, the identification of photochemical pathways may help develop new cluster-adsorbate models and expand the range of catalytic reactions available to these materials.

Experimental and computational investigation of Au25 clusters and CO2: a unique interaction and enhanced electrocatalytic activity.

Atomically precise, inherently charged Au(25) clusters are an exciting prospect for promoting catalytically challenging reactions, and we have studied the interaction between CO(2) and Au(25). Experimental results indicate a reversible Au(25)-CO(2) interaction that produced spectroscopic and electrochemical changes similar to those seen with cluster oxidation. Density functional theory (DFT) modeling indicates these changes stem from a CO(2)-induced redistribution of charge within the cluster. Identification of this spontaneous coupling led to the application of Au(25) as a catalyst for the electrochemical reduction of CO(2) in aqueous media. Au(25) promoted the CO(2) → CO reaction within 90 mV of the formal potential (thermodynamic limit), representing an approximate 200-300 mV improvement over larger Au nanoparticles and bulk Au. Peak CO(2) conversion occurred at -1 V (vs RHE) with approximately 100% efficiency and a rate 7-700 times higher than that for larger Au catalysts and 10-100 times higher than those for current state-of-the-art processes.

A flexible nudged elastic band program for optimization of minimum energy pathways using ab initio electronic structure methods.

A driver program for carrying out nudged elastic band optimizations of minimum energy reaction pathways is described. This approach allows for the determination of minimum energy pathways using only energies and gradient information. The driver code has been interfaced with the GAUSSIAN 98 program. Applications to two isomerization reactions and to a cluster model for H(2) desorption from the Si(100)-2 x 1 surface are presented.