Direct Coupling of Methane and Carbon Dioxide on Tantalum Cluster Cations

Understanding molecular-scale reaction mechanisms is crucial for the design of modern catalysts with industrial prospect. Through joint experimental and computational studies, we investigate the direct coupling reaction of CH₄ and CO₂ , two abundant greenhouse gases, mediated by Ta_1,4 ⁺ ions to form larger oxygenated hydrocarbons. Coherent with proposed elementary steps, we expose products of CH₄ dehydrogenation [Ta_1,4 CH₂ ]⁺ to CO₂ in a ring electrode ion trap. Product analysis and reaction kinetics indicate a predisposition of the tetramers for C-O coupling with a conversion to products of CH₂ O, whereas atomic cations enable C-C coupling yielding CH₂ CO. Selected experimental findings are supported by thermodynamic computations, connecting structure, electronic properties, and catalyst function. Moreover, the study of bare Ta_1,4 ⁺ compounds indicates that methane dehydrogenation is a significant initial step in the direct coupling reaction, enabling new, yet unknown reaction pathways.

Boosting propane dehydroaromatization by confining PtZn alloy nanoparticles within H-ZSM-5 crystals

A Pt–Zn@H-ZSM-5 catalyst with Pt–Zn alloy nanoparticles confined in H-ZSM-5 crystals exhibits a significantly improved performance in the propane dehydroaromatization reaction.

Spectroscopic Probe Molecule Selection Using Quantum Theory, First-Principles Calculations, and Machine Learning

Probe molecule vibrational spectra have a long history of being used to characterize materials including metals, oxides, metal-organic frameworks, and even human proteins. Furthermore, recent advances in machine learning have enabled computationally generated spectra to aid in detailed characterization of complex surfaces with probe molecules. Despite widespread use of probe molecules, the science of probe molecule selection is underdeveloped. Here, we develop physical concepts, including orbital interaction energy and the energy overlap integral, to explain and predict the ability of probe molecules to discriminate structural descriptors. We resolve the crystal orbital overlap population (COOP) to specific molecular orbitals and quantify their bonding character, which directly influences vibrational frequencies. Using only a single adsorbate calculation from density function theory (DFT), we compute the interaction energy of individual adsorbate molecular orbitals with adsorption site atomic orbitals across many different sites. Combining the molecular orbital resolved COOP and changes in orbital interaction energy enables probe molecule selection for improved discrimination of various sites. We demonstrate these concepts by comparing the predicted effectiveness of carbon monoxide (CO), nitric oxide (NO), and ethylene (C₂H₄) to probe Pt adsorption sites. Finally, using a previously developed machine learning framework, we show that models trained on hundreds of thousands of C₂H₄ spectra, computed from DFT, which regress surface binding-type and generalized coordination number, outperform those trained using CO and NO spectra. A python package, pDOS_overlap, for implementing the electron density-based analysis on any combination of adsorbates and materials, is also made available.