In this work, we implement a facile microwaveassisted synthesis method to yield three binary Chevrel-Phase chalcogenides (Mo 6 X 8 ; X = S, Se, Te) and investigate the effect of increasing chalcogen electronegativity on hydrogen evolution catalytic activity. Density functional theory predictions indicate that increasing chalcogen electronegativity in these materials will yield a favorable electronic structure for proton reduction. This is confirmed experimentally via X-ray absorption spectroscopy as well as traditional electrochemical analysis. We have identified that increasing the electronegativity of X in Mo 6 X 8 increases the hydrogen adsorption strength owing to a favorable shift in the pband position as well as an increase in the Lewis basicity of the chalcogen, thereby improving hydrogen evolution reaction energetics. We find that Mo 6 S 8 exhibits the highest hydrogen evolution activity of the Mo 6 X 8 series of catalysts, requiring an overpotential of 321 mV to achieve a current density of 10 mA cm −2 ECSA , a Tafel slope of 74 mV per decade, and an exchange current density of 6.01 × 10 −4 mA cm −2 ECSA . Agreement between theory and experiment in this work indicates that the compositionally tunable Chevrel-Phase chalcogenide family is a promising framework for which electronic structure can be predictably modified to improve catalytic small-molecule reduction reactivity.

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy-and CO 2 -intensive Haber− Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe−S−Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe−S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

Amine−peroxide redox polymerization (APRP) has been highly prevalent in industrial and medical applications since the 1950s, yet the initiation mechanism of this radical polymerization process is poorly understood so that innovations in the field are largely empirically driven and incremental. Through a combination of computational prediction and experimental analysis, we elucidate the mechanism of this important redox reaction between amines and benzoyl peroxide for the ambient production of initiating radicals. Our calculations show that APRP proceeds through S N 2 attack by the amine on the peroxide but that homolysis of the resulting intermediate is the rate-determining step. We demonstrate a correlation between the computationally predicted initiating rate and the experimentally measured polymerization rate with an R 2 = 0.80. The new mechanistic understanding was then applied to computationally predict amine reductant initiators with faster initiating kinetics. This led to our discovery of N-(4-methoxyphenyl)pyrrolidine (MPP) as amine reductant, which we confirmed significantly outperforms current state-of-the-art tertiary aromatic amines by ∼20-fold, making it the most efficient amine−peroxide redox initiator to date. The application of amines with superior kinetics such as MPP in APRP could greatly accelerate existing industrial processes, facilitate new industrial manufacturing methods, and improve biocompatibility in biomedical applications conducted with reduced initiator concentrations yet higher overall efficiency.

The Chevrel phase (CP) is a class of molybdenum chalcogenides that exhibit compelling properties for next-generation battery materials, electrocatalysts, and other energy applications. Despite their promise, CPs are underexplored, with only ∼100 compounds synthesized to date due to the challenge of identifying synthesizable phases. We present an interpretable machine-learned descriptor (H δ) that rapidly and accurately estimates decomposition enthalpy (ΔH d) to assess CP stability. To develop H δ, we first used density functional theory to compute ΔH d for 438 CP compositions. We then generated >560 000 descriptors with the new machine learning method SIFT, which provides an easy-to-use approach for developing accurate and interpretable chemical models. From a set of >200 000 compositions, we identified 48 501 CPs that H δ predicts are synthesizable based on the criterion that ΔH d < 65 meV/atom, which was obtained as a statistical boundary from 67 experimentally synthesized CPs. The set of candidate CPs includes 2307 CP tellurides, an underexplored CP subset with a predicted preference for channel site occupation by cation intercalants that is rare among CPs. We successfully synthesized five of five novel CP tellurides attempted from this set and confirmed their preference for channel site occupation. Our joint computational and experimental approach for developing and validating screening tools that enable the rapid identification of synthesizable materials within a sparse class is likely transferable to other materials families to accelerate their discovery.

State-of-the-art high temperature oxide melt solution calorimetry and density functional theory were employed to produce the first systematic study of thermodynamic stability in a series of binary and ternary Chevrel phases. Rapid microwave-assisted solid-state heating methods facilitated the nucleation of pure-phase polycrystalline M y Mo6S8 (M = Fe, Ni, Cu; y = 0, 1, 2) Chevrel phases, and a stability trend was observed wherein intercalation of M y species engenders stability that depends on both the electropositivity and ionic radii of the intercalant species. Ab initio calculations indicate that this stability trend results from competing ionic and covalent contributions, where transition metal intercalation stabilizes the Chevrel structure through increased ionicity but destabilizes the structure through reduced covalency of the Mo6S8 clusters. Our calculations predicted that over intercalation of high-valent M y species leads to slight destabilization of the Mo6 octahedral cores, which we confirm using calorimetry and X-ray absorption spectroscopy. Our combined computational and calorimetric analysis reveals the interplay of the foundational principles of ionic and covalent bonding characteristics that govern the thermodynamic stability of Chevrel and other inorganic phases.