The reactive force-field (ReaxFF) interatomic potential is a powerful computational tool for exploring, developing and optimizing material properties. Methods based on the principles of quantum mechanics (QM), while offering valuable theoretical guidance at the electronic level, are often too computationally intense for simulations that consider the full dynamic evolution of a system. Alternatively, empirical interatomic potentials that are based on classical principles require significantly fewer computational resources, which enables simulations to better describe dynamic processes over longer timeframes and on larger scales. Such methods, however, typically require a predefined connectivity between atoms, precluding simulations that involve reactive events. The ReaxFF method was developed to help bridge this gap. Approaching the gap from the classical side, ReaxFF casts the empirical interatomic potential within a bond-order formalism, thus implicitly describing chemical bonding without expensive QM calculations. This article provides an overview of the development, application, and future directions of the ReaxFF method. INTRODUCTIONAtomistic-scale computational techniques provide a powerful means for exploring, developing and optimizing promising properties of novel materials. Simulation methods based on quantum mechanics (QM) have grown in popularity over recent decades due to the development of user-friendly software packages making QM level calculations widely accessible. Such availability has proved particularly relevant to material design, where QM frequently serves as a theoretical guide and screening tool. Unfortunately, the computational cost inherent to QM level calculations severely limits simulation scales. This limitation often excludes QM methods from considering the dynamic evolution of a system, thus hampering our theoretical understanding of key factors affecting the overall behaviour of a material. To alleviate this issue, QM structure and energy data are used to train empirical force fields that require significantly fewer computational resources, thereby enabling simulations to better describe dynamic processes. Such empirical methods, including reactive force-field (ReaxFF), 1 trade accuracy for lower computational expense, making it possible to reach simulation scales that are orders of magnitude beyond what is tractable for QM.Atomistic force-field methods utilise empirically determined interatomic potentials to calculate system energy as a function of atomic positions. Classical approximations are well suited for nonreactive interactions, such as angle-strain represented by harmonic potentials, dispersion represented by van der Waals potentials and Coulombic interactions represented by various polarisation schemes. However, such descriptions are inadequate for modelling changes in atom connectivity (i.e., for modelling chemical reactions as bonds break and form). This motivates the

The discovery of materials that combine selectively, controllably, and reversibly with CO2 is a key challenge for realizing practical carbon capture from flue gas and other point sources. We report the design of ionic liquids (ILs) with properties tailored to this CO2 separation problem. Atomistic simulations predict that suitably substituted aprotic heterocyclic anions, or “AHAs,” bind CO2 with energies that can be controlled over a wide range suitable to gas separations. Further, unlike all previously known CO2-binding ILs, the AHA IL viscosity is predicted to be insensitive to CO2. Spectroscopic, temperature-dependent absorption, rheological, and calorimetric measurements on trihexyl(tetradecyl)-phosphonium 2-cyanopyrrolide ([P66614][2-CNpyr]) show CO2 uptakes close to prediction as well as insignificant changes in viscosity in the presence of CO2. A pyrazolide-based AHA IL behaves qualitatively similarly but with weaker binding energy. The results demonstrate the intrinsic design advantages of ILs as a platform for CO2 separations.

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The design of electrocatalysts capable of selectively reducing nitrate to ammonia is gaining interest as a means of transforming waste into fertilizers. However, most prior investigations of prototypical electrocatalysts, such as polycrystalline Pd and Pt, have focused on unraveling the mechanisms responsible for the selective reduction of nitrate to nitrogen gas. Such polycrystalline noble metals demonstrate notoriously low activity for nitrate reduction (nitrate to nitrite) and high activity for nitrite reduction (nitrite to nitrogen). Here, we aim to elucidate the effect Pd surface structure has on nitrate and nitrite reduction and to determine what role catalyst structural design can play in enabling selective reduction of nitrate to ammonia. Through synthesizing nanocatalysts with controlled facets (e.g., nanocubes, cuboctahedrons, octahedrons, and concave nanocubes), we demonstrate that Pd(111) > Pd(100) > Pd­(hk0) for nitrate reduction activity and Pd(100) > Pd­(hk0) > Pd(111) for nitrite reduction activity in an alkaline electrolyte. Octahedrons without Pd (100) facets exhibited nearly selective production of NO2 – with little to no measurable NH3 or N2. However, nanocubes that expose only the Pd(100) facet exhibited high activity for NO2 – reduction to NH3. Cuboctahedrons that expose both Pd(111) and Pd(100) facets demonstrated the highest production of ammonia (306.8 μg h–1 mgPd –1) with a faradaic efficiency of 35%. Density functional theory (DFT) simulations reveal that *NO3 dissociation to *NO2 + O* is more favorable on Pd(111) than Pd(100), explaining the faster nitrate reduction kinetics on the Pd(111) facet observed in the experiments. The simulations also show that *NO2 binds less strongly to Pd(111) compared to Pd(100). Thus, nitrite formed via nitrate dissociation readily desorbs from the Pd(111) surface, which explains why Pd(111) selectively reduces nitrate to nitrite. The results show that cuboctahedron is bifunctional in nature, with the (111) facet catalyzing the conversion of NO3 – to NO2 – and the (100) facet catalyzing the conversion of NO2 – to NH3.