Strategies to Obtain Reliable Energy Landscapes from Embedded Multireference Correlated Wavefunction Methods for Surface Reactions.

Embedded correlated wavefunction (ECW) theory is a powerful tool for studying ground- and excited-state reaction mechanisms and associated energetics in heterogeneous catalysis. Several factors are important to obtaining reliable ECW energies, critically the construction of consistent active spaces (ASs) along reaction pathways when using a multireference correlated wavefunction (CW) method that relies on a subset of orbital spaces in the configuration interaction expansion to account for static electron correlation, e.g., complete AS self-consistent field theory, in addition to the adequate partitioning of the system into a cluster and environment, as well as the choice of a suitable basis set and number of states included in excited-state simulations. Here, we conducted a series of systematic studies to develop best-practice guidelines for ground- and excited-state ECW theory simulations, utilizing the decomposition of NH3 on Pd(111) as an example. We determine that ECW theory results are relatively insensitive to cluster size, the aug-cc-pVDZ basis set provides an adequate compromise between computational complexity and accuracy, and that a fixed-clean-surface approximation holds well for the derivation of the embedding potential. Additionally, we demonstrate that a merging approach, which involves generating ASs from the molecular fragments at each configuration, is preferable to a creeping approach, which utilizes ASs from adjacent structures as an initial guess, for the generation of consistent potential energy curves involving open-d-shell metal surfaces, and, finally, we show that it is essential to include bands of excited states in their entirety when simulating excited-state reaction pathways.

An Autonomous Implantable Device for the Prevention of Death from Opioid Overdose.

Opioid overdose accounts for nearly 75,000 deaths per year in the United States, representing a leading cause of mortality amongst the prime working age population (25-54 years). At overdose levels, opioid-induced respiratory depression becomes fatal without timely administration of the rescue drug naloxone. Currently, overdose survival relies entirely on bystander intervention, requiring a nearby person to discover and identify the overdosed individual, and have immediate access to naloxone to administer. Government efforts have focused on providing naloxone in abundance but do not address the equally critical component for overdose rescue: a willing and informed bystander. To address this unmet need, we developed the Naloximeter: a class of life-saving implantable devices that autonomously detect and treat overdose, with the ability to simultaneously contact first-responders. We present three Naloximeter platforms, for both fundamental research and clinical translation, all equipped with optical sensors, drug delivery mechanisms, and a supporting ecosystem of technology to counteract opioid-induced respiratory depression. In small and large animal studies, the Naloximeter rescues from otherwise fatal opioid overdose within minutes. This work introduces life-changing, clinically translatable technologies that broadly benefit a susceptible population recovering from opioid use disorder.

Strongly facet-dependent activity of iron-doped ß-nickel oxyhydroxide for the oxygen evolution reaction.

Iron (Fe)-doped ß-nickel oxyhydroxide (ß-NiOOH) is a highly active, noble-metal-free electrocatalyst for the oxygen evolution reaction (OER), with the latter being the bottleneck in electrochemical water splitting for sustainable hydrogen production. The mechanisms underlying how the Fe dopant modulates this host material's water electro-oxidation activity are still not entirely clear. Here, we combine hybrid density functional theory (DFT) and Hubbard-corrected DFT to investigate the OER activity of the most thermodynamically favorable (and therefore, expected to be the majority) crystallographic facets of ß-NiOOH, namely (0001) and (101̄0). By considering active sites involving both oxidation and reduction of the transition-metal active center during the redox cycle on these two different facets, we show that six-fold-lattice-coordinated Fe in ß-NiOOH is redox inactive towards both oxidation and reduction while five-fold-lattice-coordinated Fe in ß-NiOOH does exhibit redox activity. However, the determined redox activity of Fe (or lack of it) is not indicative of good (or bad) performance as a dopant on these two facets. Three of the four active sites investigated (oxo and hydroxo sites on (0001) and a hydrated site on (101̄0)) exhibit only a marginal (<0.1 V) decrease or increase in the thermodynamic overpotential upon doping with Fe. Only one of the redox-active sites investigated, the hydroxo site on (101̄0), exhibits a large attenuation in the thermodynamic overpotential upon doping (to ∼0.52 V from 0.86 V), although the doped overpotential is larger than that observed experimentally for Fe-doped NiOOH. Thus, although pure ß-NiOOH facets containing four-, five-, or six-fold lattice-coordinated Ni sites have roughly equal OER activities, yielding similar OER onset potentials (shown in A. Govind Rajan, J. M. P. Martirez and E. A. Carter, J. Am. Chem. Soc., 2020, 142, 3600-3612), only those facets containing four-fold lattice-coordinated Fe (e.g., as shown in J. M. P. Martirez and E. A. Carter, J. Am. Chem. Soc., 2019, 141, 693-705) would be active under analogous conditions for the Fe-doped material. It follows that, while undoped ß-NiOOH demonstrates a roughly facet-independent oxygen evolution activity, the activity of Fe-doped ß-NiOOH strongly depends on the crystallographic facet. Our study further motivates the investigation of strategies for the selective growth of facets with low iron coordination number to enhance the water splitting activity of Fe-doped ß-NiOOH.

Characterizing the Mechanisms of Ca and Mg Carbonate Ion-Pair Formation with Multi-Level Molecular Dynamics/Quantum Mechanics Simulations.

The carbonate minerals of Ca and Mg are abundant throughout the lithosphere and have recently garnered significant research interest as possible long-term carbon sinks in the sequestration of atmospheric carbon dioxide. Nonetheless, an understanding of the atomic-level processes comprising their mineralization remains limited. Here, we characterize and contrast the mechanisms of contact ion-pair formation in aqueous Ca and Mg carbonate systems, which represents the most fundamental step leading to the formation of their mineral solids. Utilizing multilevel embedded correlated wavefunction-based ab initio molecular dynamics/quantum mechanics simulations, we characterize not only the dynamics of these processes but also factors arising from the electronic structure of the involved species, revealing further details of the fundamentally different mechanisms for the interconversion between the contact ion-pairs and solvent-shared ion-pairs of Ca versus Mg carbonate.

Introducing the embedded random phase approximation: H2 dissociative adsorption on Cu(111) as an exemplar.

The random phase approximation (RPA) as a means of treating electron correlation recently has been shown to outperform standard density functional theory (DFT) approximations in a variety of cases. However, the computational cost of the RPA is substantially more than DFT, especially when aiming to study extended surfaces. Properly accounting for sufficient surface ensemble size, Brillouin zone sampling, and vacuum separation of periodic images in standard periodic-planewave-based DFT code raises the cost to achieve converged results. Here, we show that sub-system embedding schemes enable use of the RPA for modeling heterogeneous reactions at reduced computational cost. We explore two different embedded RPA (emb-RPA) approaches, periodic emb-RPA and cluster emb-RPA. We use the (experimentally and theoretically) well-studied H2 dissociative adsorption on Cu(111) as our exemplar, and first perform full periodic RPA calculations as a benchmark. The full RPA results match well the semi-empirical barrier fit to experimental observables and others derived from high-level computations, e.g., from recent embedded n-electron valence second order perturbation theory [Zhao et al., J. Chem. Theory Comput. 16(11), 7078-7088 (2020)] and quantum Monte Carlo [Doblhoff-Dier et al., J. Chem. Theory Comput. 13(7), 3208-3219 (2017)] simulations. Among the two emb-RPA approaches tested, the cluster emb-RPA accurately reproduces the energy profile (maximum error of 50 meV along the reaction pathway) while reducing the computational cost by approximately two orders of magnitude. We therefore expect that the embedded cluster approach will enable wider RPA implementation in heterogeneous catalysis.

Minimizing the impacts of the ammonia economy on the nitrogen cycle and climate.

Ammonia (NH3) is an attractive low-carbon fuel and hydrogen carrier. However, losses and inefficiencies across the value chain could result in reactive nitrogen emissions (NH3, NOx, and N2O), negatively impacting air quality, the environment, human health, and climate. A relatively robust ammonia economy (30 EJ/y) could perturb the global nitrogen cycle by up to 65 Mt/y with a 5% nitrogen loss rate, equivalent to 50% of the current global perturbation caused by fertilizers. Moreover, the emission rate of nitrous oxide (N2O), a potent greenhouse gas and ozone-depleting molecule, determines whether ammonia combustion has a greenhouse footprint comparable to renewable energy sources or higher than coal (100 to 1,400 gCO2e/kWh). The success of the ammonia economy hence hinges on adopting optimal practices and technologies that minimize reactive nitrogen emissions. We discuss how this constraint should be included in the ongoing broad engineering research to reduce environmental concerns and prevent the lock-in of high-leakage practices.

Probing pH-Dependent Dehydration Dynamics of Mg and Ca Cations in Aqueous Solutions with Multi-Level Quantum Mechanics/Molecular Dynamics Simulations.

The dehydration of aqueous calcium and magnesium cations is the most fundamental process controlling their reactivity in chemical and biological phenomena, such as the formation of ionic solids or passing through ion channels. It holds particular relevance in light of recent advancements in the development of carbon capture techniques that rely on mineralization for long-term carbon storage. Specifically, dehydration of Ca2+ and Mg2+ is a key step in proposed carbon capture processes aiming to exploit the relatively high concentration of dissolved carbon dioxide in seawater via the formation of carbonate minerals from solvated Ca2+ and Mg2+ cations for sequestration and storage. Nevertheless, atomic-scale understanding of the dehydration of aqueous Ca2+ and Mg2+ cations remains limited. Here, we utilize rare event sampling via density functional theory molecular dynamics and embedded wavefunction theory calculations to elucidate the dehydration dynamics of aqueous Ca2+ and Mg2+. Emphasis is placed on the investigation of the effect pH has on the stability of the different coordination environments. Our results reveal significant differences in the dehydration dynamics of the two cations and provide insight into how they may be modulated by pH changes.

Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water.

Simulations of carbon dioxide (CO2) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. We show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.

Highly Selective Electrochemical Reduction of CO2 into Methane on Nanotwinned Cu.

The electrochemical carbon dioxide reduction reaction (CO2RR) is a promising route to close the carbon cycle by reducing CO2 into valuable fuels and chemicals. Electrocatalysts with high selectivity toward a single product are economically desirable yet challenging to achieve. Herein, we demonstrated a highly (111)-oriented Cu foil electrocatalyst with dense twin boundaries (TB) (tw-Cu) that showed a high Faradaic efficiency of 86.1 ± 5.3% toward CH4 at -1.2 ± 0.02 V vs the reversible hydrogen electrode. Theoretical studies suggested that tw-Cu can significantly lower the reduction barrier for the rate-determining hydrogenation of CO compared to planar Cu(111) under working conditions, which suppressed the competing C-C coupling, leading to the experimentally observed high CH4 selectivity.

Observation of electron orbital signatures of single atoms within metal-phthalocyanines using atomic force microscopy.

Resolving the electronic structure of a single atom within a molecule is of fundamental importance for understanding and predicting chemical and physical properties of functional molecules such as molecular catalysts. However, the observation of the orbital signature of an individual atom is challenging. We report here the direct identification of two adjacent transition-metal atoms, Fe and Co, within phthalocyanine molecules using high-resolution noncontact atomic force microscopy (HR-AFM). HR-AFM imaging reveals that the Co atom is brighter and presents four distinct lobes on the horizontal plane whereas the Fe atom displays a "square" morphology. Pico-force spectroscopy measurements show a larger repulsion force of about 5 pN on the tip exerted by Co in comparison to Fe. Our combined experimental and theoretical results demonstrate that both the distinguishable features in AFM images and the variation in the measured forces arise from Co's higher electron orbital occupation above the molecular plane. The ability to directly observe orbital signatures using HR-AFM should provide a promising approach to characterizing the electronic structure of an individual atom in a molecular species and to understand mechanisms of certain chemical reactions.

Earth-abundant photocatalyst for H2 generation from NH3 with light-emitting diode illumination.

Catalysts based on platinum group metals have been a major focus of the chemical industry for decades. We show that plasmonic photocatalysis can transform a thermally unreactive, earth-abundant transition metal into a catalytically active site under illumination. Fe active sites in a Cu-Fe antenna-reactor complex achieve efficiencies very similar to Ru for the photocatalytic decomposition of ammonia under ultrafast pulsed illumination. When illuminated with light-emitting diodes rather than lasers, the photocatalytic efficiencies remain comparable, even when the scale of reaction increases by nearly three orders of magnitude. This result demonstrates the potential for highly efficient, electrically driven production of hydrogen from an ammonia carrier with earth-abundant transition metals.

Plasmonic Photocatalysis with Chemically and Spatially Specific Antenna-Dual Reactor Complexes.

Plasmonic antenna-reactor photocatalysts have been shown to convert light efficiently to chemical energy. Virtually all chemical reactions mediated by such complexes to date, however, have involved relatively simple reactions that require only a single type of reaction site. Here, we investigate a planar Al nanodisk antenna with two chemically distinct and spatially separated active sites in the form of Pd and Fe nanodisks, fabricated in 90° and 180° trimer configurations. The photocatalytic reactions H2 + D2 → 2HD and NH3 + D2 → NH2D + HD were both investigated on these nanostructured complexes. While the H2-D2 exchange reaction showed an additive behavior for the linear (180°) nanodisk complex, the NH3 + D2 reaction shows a clear synergistic effect of the position of the reactor nanodisks relative to the central Al nanodisk antenna. This study shows that light-driven chemical reactions can be performed with both chemical and spatial control of the specific reaction steps, demonstrating precisely designed antennas with multiple reactors for tailored control of chemical reactions of increasing complexity.

DFT exchange: sharing perspectives on the workhorse of quantum chemistry and materials science.

In this paper, the history, present status, and future of density-functional theory (DFT) is informally reviewed and discussed by 70 workers in the field, including molecular scientists, materials scientists, method developers and practitioners. The format of the paper is that of a roundtable discussion, in which the participants express and exchange views on DFT in the form of 302 individual contributions, formulated as responses to a preset list of 26 questions. Supported by a bibliography of 777 entries, the paper represents a broad snapshot of DFT, anno 2022.

Electrochemical Hydrogenation of CO on Cu(100): Insights from Accurate Multiconfigurational Wavefunction Methods.

Copper (Cu) remains the most efficacious electrocatalyst for electrochemical CO2 reduction (CO2R). Its activity and selectivity are highly facet-dependent. We recently examined the commonly proposed rate-limiting CO hydrogenation step on Cu(111) via embedded correlated wavefunction (ECW) theory and demonstrated that only this higher-level theory yields predictions consistent with potential-dependent experimental kinetics. Here, to understand the differing activities of Cu(111) and Cu(100) in catalyzing CO2R, we explore CO hydrogenation on Cu(100) using ECW theory. We predict that the preferred pathway involves the reduction of adsorbed CO (*CO) to *COH via proton-coupled electron transfer (PCET) at working potentials, although *CHO also may form with a kinetically accessible but higher barrier. In contrast, our earlier work on Cu(111) concluded that *COH and *CHO formation via PCET are equally feasible. This work illustrates one possible origin of the facet dependence of CO2R mechanisms and products on Cu electrodes and sheds light on how the selectivity of CO2R electrocatalysts can be controlled by the surface morphology.

Charting C-C coupling pathways in electrochemical CO2 reduction on Cu(111) using embedded correlated wavefunction theory.

The electrochemical CO2 reduction reaction (CO2RR) powered by excess zero-carbon-emission electricity to produce especially multicarbon (C2+) products could contribute to a carbon-neutral to carbon-negative economy. Foundational to the rational design of efficient, selective CO2RR electrocatalysts is mechanistic analysis of the best metal catalyst thus far identified, namely, copper (Cu), via quantum mechanical computations to complement experiments. Here, we apply embedded correlated wavefunction (ECW) theory, which regionally corrects the electron exchange-correlation error in density functional theory (DFT) approximations, to examine multiple C-C coupling steps involving adsorbed CO (*CO) and its hydrogenated derivatives on the most ubiquitous facet, Cu(111). We predict that two adsorbed hydrogenated CO species, either *COH or *CHO, are necessary precursors for C-C bond formation. The three kinetically feasible pathways involving these species yield all three possible products: *COH-CHO, *COH-*COH, and *OCH-*OCH. The most kinetically favorable path forms *COH-CHO. In contrast, standard DFT approximations arrive at qualitatively different conclusions, namely, that only *CO and *COH will prevail on the surface and their C-C coupling paths produce only *COH-*COH and *CO-*CO, with a preference for the first product. This work demonstrates the importance of applying qualitatively and quantitatively accurate quantum mechanical method to simulate electrochemistry in order ultimately to shed light on ways to enhance selectivity toward C2+ product formation via CO2RR electrocatalysts.

Assessing cathode property prediction via exchange-correlation functionals with and without long-range dispersion corrections.

We benchmark calculated interlayer spacings, average topotactic voltages, thermodynamic stabilities, and band gaps in layered lithium transition-metal oxides (TMOs) and their de-lithiated counterparts, which are used in lithium-ion batteries as positive electrode materials, against available experimental data. Specifically, we examine the accuracy of properties calculated within density functional theory (DFT) using eight different treatments of electron exchange-correlation: the strongly constrained and appropriately normed (SCAN) and Perdew-Burke-Ernzerhof (PBE) density functionals, Hubbard-U-corrected SCAN and PBE (i.e., SCAN+U and PBE+U), and SCAN(+U) and PBE(+U) with added long-range dispersion (D) interactions (i.e., DFT(+U)+D). van der Waals interactions are included respectively via the revised Vydrov-Van Voorhis (rVV10) for SCAN(+U) and the DFT-D3 for PBE(+U). We find that SCAN-based functionals predict larger voltages due to an underestimation of stability of the MO2 systems, while also predicting smaller interlayer spacings compared to their PBE-based counterparts. Furthermore, adding dispersion corrections to PBE has a greater effect on voltage predictions and interlayer spacings than with SCAN, indicating that DFT-SCAN - despite being a ground-state theory - fortuitously captures some short and medium-range dispersion interactions better than PBE. While SCAN-based and PBE-based functionals yield qualitatively similar band gap predictions, there is no significant quantitative improvement of SCAN-based functionals over the corresponding PBE-based versions. Finally, we expect SCAN-based functionals to yield more accurate property predictions than the respective PBE-based functionals for most TMOs, given SCAN's stronger theoretical underpinning and better predictions of systematic trends in interlayer spacings, intercalation voltages, and band gaps obtained in this work.

Breaking a dative bond with mechanical forces.

Bond breaking and forming are essential components of chemical reactions. Recently, the structure and formation of covalent bonds in single molecules have been studied by non-contact atomic force microscopy (AFM). Here, we report the details of a single dative bond breaking process using non-contact AFM. The dative bond between carbon monoxide and ferrous phthalocyanine was ruptured via mechanical forces applied by atomic force microscope tips; the process was quantitatively measured and characterized both experimentally and via quantum-based simulations. Our results show that the bond can be ruptured either by applying an attractive force of ~150 pN or by a repulsive force of ~220 pN with a significant contribution of shear forces, accompanied by changes of the spin state of the system. Our combined experimental and computational studies provide a deeper understanding of the chemical bond breaking process.

Factors Governing Oxygen Vacancy Formation in Oxide Perovskites.

The control of oxygen vacancy (VO) formation is critical to advancing multiple metal-oxide-perovskite-based technologies. We report the construction of a compact linear model for the neutral VO formation energy in ABO3 perovskites that reproduces, with reasonable fidelity, Hubbard-U-corrected density functional theory calculations based on the state-of-the-art, strongly constrained and appropriately normed exchange-correlation functional. We obtain a mean absolute error of 0.45 eV for perovskites stable at 298 K, an accuracy that holds across a large, electronically diverse set of ABO3 perovskites. Our model considers perovskites containing alkaline-earth metals (Ca, Sr, and Ba) and lanthanides (La and Ce) on the A-site and 3d transition metals (Ti, V, Cr, Mn, Fe, Co, and Ni) on the B-site in six different crystal systems (cubic, tetragonal, orthorhombic, hexagonal, rhombohedral, and monoclinic) common to perovskites. Physically intuitive metrics easily extracted from existing experimental thermochemical data or via inexpensive quantum mechanical calculations, including crystal bond dissociation energies and (solid phase) reduction potentials, are key components of the model. Beyond validation of the model against known experimental trends in materials used in solid oxide fuel cells, the model yields new candidate perovskites not contained in our training data set, such as (Bi,Y)(Fe,Co)O3, which we predict may have favorable thermochemical water-splitting properties. The confluence of sufficient accuracy, efficiency, and interpretability afforded by our model not only facilitates high-throughput computational screening for any application that requires the precise control of VO concentrations but also provides a clear picture of the dominant physics governing VO formation in metal-oxide perovskites.