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Interconversion of the oxidation states of uranium enables separations and reactivity schemes involving this element and contributes to technologies for recycling of spent nuclear fuels. The redox behaviors of uranium species impact these processes, but use of electrochemical methods to drive reactions of molecular uranium complexes and to obtain molecular insights into the outcomes of electrode-driven reactions has received far less attention than it deserves. Here, we show that electro-reduction of the uranyl ion (UO22+) can be used to promote stepwise functionalization of the typically unreactive oxo groups with exogenous triphenylborane (BPh3) serving as a moderate electrophile, avoiding the conventional requirement for a chemical reductant. Parallel electroanalytical, spectrochemical, and chemical reactivity studies, supported by spectroscopic findings and structural data from X-ray diffraction analysis on key reduced and borylated products, demonstrate that our electrochemical approach largely avoids undesired cross reactions and disproportionation pathways; these usually impact the multicomponent systems needed for uranyl functionalization chemistry. Joint computational studies have been used to map the changes associated with U–O activation and to quantify the free energy differences related to key reactions. Taken together, the results suggest that electrochemical methods can be used for selective interconversion of molecular actinide species, reminiscent of methods commonly employed in transition metal redox catalysis.

Nitrogen oxides, present in flue gas, can cause negative impacts on amine carbon capture solvents by the formation of heat-stable salts and suspected carcinogens. Thus, to maximize the performance of water-lean solvents, a better understanding of this process in these systems is necessary. Here, a computational study for the fixation of the CO2capture solvent N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (EEMPA) to nitramine/nitrosamine was conducted. The first step involves the dissociation of the NH bond of EEMPA, in which the homolytic mechanism is energetically more favorable than the heterolytic mechanism. The second step involves radical recombination to form N–N bonds. While NO2directly reacts with EEMPA, NO has almost no effect. However, in the presence of O2, fixation of EEMPA by NO is enhanced via the formation of N2O4species. Low reaction energies indicate that the formation of nitramine/nitrosamine may be a reversible process, suggesting that EEMPA could be recovered under thermal stripping conditions.

Proton transfer is critically important to many electrocatalytic reactions, and directed proton delivery could open new avenues for the design of electrocatalysts. However, although this approach has been successful in molecular electrocatalysis, proton transfer has not received the same attention in heterogeneous electrocatalyst design. Here, we report that a metal oxide proton relay can be built within heterogeneous electrocatalyst architectures and improves the kinetics of electrochemical hydrogen evolution and oxidation reactions. The volcano-type relationship between activity enhancement and pKaof amine additives confirms this improvement; we observe maximum rate enhancement when the pKaof a proton relay matches the pH of the electrolyte solution. Density-functional-theory-based reactivity studies reveal a decreased proton transfer energy barrier with a metal oxide proton relay. These findings demonstrate the possibility of controlling the proton delivery and enhancing the reaction kinetics by tuning the chemical properties and structures at heterogeneous interfaces.

In situ Al K-edge X-ray absorption near edge structure (XANES) and Extended X-ray absorption fine structure (EXAFS) spectroscopy in conjunction with ab initio molecular dynamics (AIMD) simulations show that adsorption of 1-propanol alters the structure of the Brønsted acid site through changes in the associated aluminum–oxygen tetrahedron in zeolite H-MFI. The decreasing intensity of the pre-edge signal of the in situ Al K-edge XANES spectra with increasing 1-propanol coverage shows that Al T-sites become more symmetric as the sorbed alcohol molecules form monomers, dimers, and trimers. The adsorption of monomeric 1-propanol on Brønsted acid sites reduces the distortion of the associated Al T-site, shortens the Al–O distance, and causes the formation of a Zundel-like structure. With dimeric and trimeric alcohol clusters, the zeolite proton is fully transferred to the alcohols and the aluminum–oxygen tetrahedron becomes fully symmetric. The subtle changes in Al–K-edge XANES in the presence of sorbate structures, with the use of theory, are used to probe the local zeolite structures and provide a basis to predict the population and chemical state of the sorbed species.

Research interest in single-atom catalysts (SACs) has been continuously increasing. However, the lack of understanding of the dynamic behaviors of SACs during applications hinders catalyst development and mechanistic understanding. Herein, we report on the evolution of active sites over Pd/TiO2-anatase SAC (Pd1/TiO2) in the reverse water–gas shift (rWGS) reaction. Combining kinetics, in situ characterization, and theory, we show that at T≥ 350 °C, the reduction of TiO2by H2alters the coordination environment of Pd, creating Pd sites with partially cleaved Pd–O interfacial bonds and a unique electronic structure that exhibit high intrinsic rWGS activity through the carboxyl pathway. The activation by H2is accompanied by the partial sintering of single Pd atoms (Pd1) into disordered, flat, ∼1 nm diameter clusters (Pdn). The highly active Pd sites in the new coordination environment under H2are eliminated by oxidation, which, when performed at a high temperature, also redisperses Pdnand facilitates the reduction of TiO2. In contrast, Pd1sinters into crystalline, ∼5 nm particles (PdNP) during CO treatment, deactivating Pd1/TiO2. During the rWGS reaction, the two Pd evolution pathways coexist. The activation by H2dominates, leading to the increasing rate with time-on-stream, and steady-state Pd active sites similar to the ones formed under H2. This work demonstrates how the coordination environment and nuclearity of metal sites on a SAC evolve during catalysis and pretreatments and how their activity is modulated by these behaviors. These insights on SAC dynamics and the structure–function relationship are valuable to mechanistic understanding and catalyst design.

A mechanistic understanding of metal–organic framework (MOF) synthesis and scale-up remains underexplored due to the complex nature of the interactions of their building blocks. In this work, we investigate the collective assembly of building units at the early stages of MOF nucleation, using MIL-101(Cr) as a prototypical example. Using large-scale molecular dynamics simulations, we observe that the choice of solvent (water and N,N-dimethylformamide), the introduction of ions (Na+and F–) and the relative populations of MIL-101(Cr) half-secondary building unit (half-SBU) isomers have a strong influence on the cluster formation process. Additionally, the shape, size, nucleation and growth rates, crystallinity, and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting the self-assembly of MOF nuclei as the time evolution of an undirected graph. Solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly. While pure solvents lead to the rapid formation of a small number of large clusters, the presence of ions in aqueous solutions results in smaller clusters and slower nucleation. This diversity is captured by the key features of the graph representation. Principle component analysis on graph properties reveals that only a small number of molecular descriptors is needed to deconvolute MOF self-assembly. Descriptors such as the average coordination number between half-SBUs and fractal dimension are of particulalr interest as they can be can be followed experimentally by techniques like by time-resolved spectroscopy. Ultimately, graph theory emerges as an approach that can be used to understand complex processes revealing molecular descriptors accessible by both simulation and experiment.

Functionalization of graphene oxide (GO) membranes is generally achieved using carboxyl groups as binding sites for ligands. Herein, by taking advantage of the ability of imidazolium-based ionic liquids (ILs) to undergo an epoxide ring-opening reaction, a new approach of GO modification was established, in which ILs were bonded to the abundant epoxides on GO without sacrificing the carboxyl groups. Computational methods confirmed this unique configuration of ILs on GO, which enabled the dispersion of IL/GO flakes in water for facile casting into laminate membranes. Compared with neat GO, the ILs in IL/GO membranes served as spacers that substantially reduced the multi-valent cation mobility, simultaneously facilitated ion desolvation, and increased the water flux across the membrane. Our studies found that the higher separation efficiency of IL/GO membranes may be attributed to the synergistic modification of the hydrophobicity and surface charge. Specifically, the protonated nitrogen of the imidazolium cations altered the surface charge of GO, thereby generating electrostatic repulsion that enhanced the selectivity of cation rejection. On the other hand, the increased length of the alkyl chains bound to the imidazolium rings was found to increase the hydrophobicity of GO, which, in turn, aided the fine-tuning of the water desolvation/transport dynamics at the GO/IL interface to achieve a high water flux. Additionally, the water retention was reduced on the hydrophobic planes, which inhibited GO swelling during aqueous separations. Molecular dynamics simulations revealed increased water diffusivity when ILs were intercalated within GO layers. We establish that without requiring a high energy input, functionalization of GO membranes with ILs may be a promising approach to achieve efficient ion separation and critical material recovery.

Adsorption of organics in the aqueous phase is an area which is experimentally difficult to measure, while computational techniques require extensive configurational sampling of the solvent and adsorbate. This is exceedingly computationally demanding, which excludes its routine use. If implicit solvent could be applied instead, this would dramatically reduce the computational cost as configurational sampling of solvent is not needed. Here, using statistical thermodynamic arguments and DFT calculations with implicit solvent models, we show that semiquantitative values for the free energy and entropy change of adsorption in the aqueous phase (ΔGadssolvand ΔSadssolv) for small organics can be calculated, for a range of coverages. We parametrize the soft sphere based solute dielectric cavity to an approximated free energy of solvation for a single Pt atom at the (111) facet, forming upper and lower bounds based on the entropy of water at the aqueous metal interface (ΔGsolv(Pt) = −4.35 to −7.18 kJ mol–1). This captures the decrease in ΔGadssolvcompared to the free energy of adsorption in the vacuum phase (ΔGadsvac), while solvent models with electron density based cavities fail to do so. For a range of oxygenated aromatics, the adsorption energetics using horizontal gas phase geometries significantly overestimate ΔGadssolvcompared to experiment by ∼100 kJ mol–1, but they agree with ab initioMD simulations using similar geometries. This suggests oxygenated aromatic compounds adsorb perpendicular to the metallic surface, while the ΔGadssolvfor vertical geometries of furfural and cyclohexanol agree to within 20 kJ mol–1of experimental studies. The proposed techniques provide an inexpensive toolset for validation and prediction of adsorption energetics on solvated metallic surfaces, which could be further validated by the future availability of more experimental measurements for the aqueous entropy/free energy of adsorption.

Ab initiomolecular dynamics simulations combined with enhanced sampling techniques are becoming widespread methods to investigate chemical phenomena in catalytic systems. These techniques automatically include finite temperature effects, anharmonicity, and collective dynamics in their robust description of enthalpic and entropic contributions, which can have significant impact on reaction free energy landscapes. This contrasts with standard ab initiostatic approaches that are based on assessing reaction free energies from various coarse-grained descriptions of the reaction potential energy surface. Enhanced sampling ab initiomolecular dynamics opens the way to first principles simulations of systems of increasing complexity like solid/liquid catalytic interfaces. In this work, we aim at guiding the reader through the basis of these techniques, summarizing their fundamental theoretical and practical aspects, and reviewing the relevant literature in the field. After a brief introduction to the problem, we will illustrate the advantage of using molecular simulations to include finite temperature effects, examine the most common ab initiotechniques currently in use, describe their application to solid state heterogeneous catalysts, and finally critically review the most popular enhanced sampling techniques used in computational catalysis.

Cu-zeolites are able to directly convert methane to methanol via a three-step process using O2as oxidant. Among the different zeolite topologies, Cu-exchanged mordenite (MOR) shows the highest methanol yields, attributed to a preferential formation of active Cu–oxo species in its 8-MR pores. The presence of extra-framework or partially detached Al species entrained in the micropores of MOR leads to the formation of nearly homotopic redox active Cu–Al–oxo nanoclusters with the ability to activate CH4. Studies of the activity of these sites together with characterization by 27Al NMR and IR spectroscopy leads to the conclusion that the active species are located in the 8-MR side pockets of MOR, and it consists of two Cu ions and one Al linked by O. This Cu–Al–oxo cluster shows an activity per Cu in methane oxidation significantly higher than of any previously reported active Cu–oxo species. In order to determine unambiguously the structure of the active Cu–Al–oxo cluster, we combine experimental XANES of Cu K- and L-edges, Cu K-edge HERFD-XANES, and Cu K-edge EXAFS with TDDFT and AIMD-assisted simulations. Our results provide evidence of a [Cu2AlO3]2+cluster exchanged on MOR Al pairs that is able to oxidize up to two methane molecules per cluster at ambient pressure.

We have developed a new set of norm-conserving pseudopotentials and companion Gaussian basis sets for the actinide (An) series (Ac–Lr) using the Goedecker, Teter, and Hutter (GTH) formalism with the Perdew, Burke, and Ernzerhof (PBE) exchange–correlation functional of generalized gradient approximation. To test the accuracy and reliability of the newly parameterized An-GTH pseudopotentials and basis sets, a variety of benchmarks on actinide-containing molecules were carried out and compared to all-electron and available experimental results. The new pseudopotentials include both medium- ([Xe]4f14) and large-core ([Xe]4f145d10) options that successfully reproduce the structures and energetics, particularly redox processes. The medium-core size set, in particular, reproduces all-electron calculations over multiple oxidation states from 0 to VII, whereas the large-core set is suitable only for the early series elements and low oxidation states. The underlying reason for these transferability issues is discussed in detail. This work fills a critical void in the literature for studying the chemistry of 5f-block elements in the condensed phase.

Planewave density functional theory (DFT-PW91) calculations are employed to study the methanol synthesis through CO2and CO hydrogenation, as well as the two side reactions: the water gas shift (WGS) reaction and formic acid formation, on Ni(110). For the WGS reaction on Ni(110), we find that the redox mechanism is favored over the carboxyl-mediated mechanism. We show that the formate pathway is the dominant one for formic acid formation. For methanol synthesis through CO2and CO hydrogenation on Ni(110), our results reveal that the formic-acid- and dioxymethylene-mediated pathways coexist, in contrast to methanol synthesis on Cu(111) where the formic-acid-mediated pathway dominates. We also find that on Ni(110), hydrogenation of CH2O* to CH3O* and that to CH2OH* both contribute to MeOH synthesis. Based on the derived energetics, we ascertain that CH3O* hydrogenation to CH3OH* is likely the rate-determining step along the CH3O* pathway on Ni(110). Remarkably, CH3O* hydrogenation can be facilitated by the presence of HCO*, demonstrating the promotional effect of CO. We further show that CO also participates in methanol synthesis directly viaits hydrogenation to HCO* and further to CH2O*. Additional microkinetic modeling by considering feed composition and reaction conditions would provide further mechanistic insights into methanol synthesis on Ni(110).

Ethanol is an important C2platform 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 C4olefin intermediates that can be further upgraded to jet/diesel fuels. Two-dimensional (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 three-dimensional (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 situdiffuse 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. Employing the Blue Moon ensemble method, the formation of framework-bound butoxide from ethoxy and ethene is found to be the likely rate-determining step (RDS), proceeding via a stepwise mechanism. The reactivity of 2D-PMFI can be further tuned by manipulating RDS through careful control of the number of BAS and operating temperatures. The calculated vibrational density of states (VDOS) validate the structural models of adsorbed ethanol by comparing with 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 a confined system.

An accurate prediction of NMR chemical shifts at affordable computational cost is very important for different types of structural assignments in experimental studies. Density functional theory (DFT) and gauge-including atomic orbital (GIAO) are two of the most popular computational methods for NMR calculation, yet they often fail to resolve ambiguities in structural assignments. Here, we present a new method that uses machine learning (ML) techniques (DFT + ML) that significantly increases the accuracy of 13C/1H NMR chemical shift prediction for a variety of organic molecules. The input of the generalizable DFT + ML model contains two critical parts: one is a vector providing insights into chemical environments, which can be evaluated without knowing the exact geometry of the molecule; the other one is the DFT-calculated isotropic shielding constant. The DFT + ML model was trained with a data set containing 476 13C and 270 1H experimental chemical shifts. For the DFT methods used here, the root mean square deviations (RMSDs) for the errors between predicted and experimental 13C/1H chemical shifts can be as small as 2.10/0.18 ppm, which is much lower than those from simple DFT (5.54/0.25 ppm), or DFT + linear regression (LR) (4.77/0.23 ppm) approaches. It also has a smaller maximum absolute error than two previously proposed NMR-predicting ML models. The robustness of the DFT + ML model is tested on two classes of organic molecules (TIC10 and hyacinthacines), where the correct isomers were unambiguously assigned to the experimental ones. Overall, the DFT + ML model shows promise for structural assignments in a variety of systems, including stereoisomers, that are often challenging to determine experimentally.

Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials, or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in the gas phase and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au55, ligated Au82+, Au8supported on graphene oxide and defected rutile, and a large cluster assembly [Co6Te8(PEt3)6][C60]n, with sizes ranging between 1 and 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available, and it provides a powerful and efficient approach for global optimization of nanosized cluster systems.

CO2has attracted considerable attention in recent years due to its role in the greenhouse effect and environmental management. While its reaction with water has been studied extensively, the same cannot be said for reactivity in the supercritical CO2phase, where the conjugate acid/base equilibria proceed through different mechanisms and activation barriers. In spite of the apparent simplicity of the CO2+ H2O reaction, the collective effect of different environments has a drastic influence on the free energy profile. Enhanced sampling techniques and well-tailored collective variables provide a detailed picture of the enthalpic and entropic drivers underscoring the differences in the formation mechanism of carbonic acid in the gas, aqueous, and supercritical CO2phases.

Implicit solvent models are a computationally efficient method of representing solid/liquid interfaces prevalent in electrocatalysis, energy storage, and materials science. However, electronic structure changes induced at the metallic surface by the dielectric continuum are not fully understood. To address this, we perform DFT calculations for the Pt(111)/water interface, in order to compare Poisson–Boltzmann continuum solvation methods with ab initiomolecular dynamics (AIMD) simulations of explicit solvent. We show that the implicit solvent cavity can be parametrized in terms of the electric dipole moment change at the equilibrated explicit Pt/water interface to obtain the potential of zero charge (PZC). We also compare the accuracy of aqueous enthalpies of adsorption of phenol on Pt(111) using geometry and charge density based dielectric cavitation methods. The ability to parametrize the cavity according to individual atoms, as afforded in the geometry based approach, is key to obtaining accurate enthalpy changes of adsorption under aqueous conditions. We also show that the electronic structure changes induced by explicit solvent and our proposed implicit solvent parametrization scheme yield comparable density difference profiles and d-band projected density of states. We therefore demonstrate the capability of implicit solvent approaches to capture both the energetics of adsorption processes and the main electronic effects of aqueous solvent on the metallic surface. This work therefore provides a scheme for computationally efficient simulations of interfacial processes for applications in areas such as heterogeneous catalysis and electrochemistry.