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Objective: To define incidence and predictors of nontraumatic lower-extremity amputation (LEA) in a diverse cohort of American Indians with diabetes.Research Design and Methods: The Strong Heart Study is a study of cardiovascular disease and its risk factors in 13 American-Indian communities. Data on the presence/absence of amputations were collected at each of three serial examinations (1989-1992, 1993-1995, and 1997-1999) by direct examination of the lower extremity. The logistic regression model was used to quantify the relationship between risk of LEA and potential risk factors, including diabetes duration, HbA(1c), peripheral arterial disease, and renal function.Results: Of the 1,974 individuals with diabetes and without prevalent LEA at baseline, 87 (4.4%) experienced an LEA during 8 years of follow-up, and a total of 157 anatomical sites were amputated among these individuals. Amputation of toes was most common, followed by below-the-knee and above-the-knee amputations. Age-adjusted odds of LEA were higher among individuals with unfavorable combinations of risk factors, such as albuminuria and elevated HbA(1c). Multivariable modeling indicated that male sex, renal dysfunction, high ankle-brachial index, longer duration of diabetes, less than a high school education, increasing systolic blood pressure, and HbA(1c) predicted LEA risk.Conclusions: The 8-year cumulative incidence of LEA in American Indians with diabetes is 4.4%, with marked differences in risk by sex, educational attainment, renal function, and glycemic control. [ABSTRACT FROM AUTHOR]

Objective: To compare risk of all-cause and cardiovascular disease (CVD) mortality in people with a lower-extremity amputation (LEA) attributable to diabetes and people without an LEA.Research Design and Methods: The Strong Heart Study is a study of CVD and its risk factors in 13 American-Indian communities. LEA was ascertained at baseline by direct examination of the legs and feet. Mortality surveillance is complete through 2000.Results: Of 2,108 participants with diabetes at baseline, 134 participants (6.4%) had an LEA. Abnormal ankle-brachial index (53%), albuminuria (87%), and long diabetes duration (mean 19.8 years) were common among diabetic subjects with LEA. Mean diabetes duration among diabetic participants without LEA and in those with toe and below-the-knee amputations was 11.9, 18.6, and 21.1 years, respectively. During 8.7 (+/-2.9) years of follow-up, 102 of the participants with LEA (76%) died from all causes and 35 (26%) died from CVD. Of the 1,974 diabetic participants without LEA at baseline, 604 (31%) died from all causes and 206 (10%) died from CVD. The unadjusted hazard ratios (HRs) for all-cause and CVD mortality in diabetic participants with LEA compared with those without were 4.0 and 4.1, respectively. Adjusting for known and suspected confounders, LEA persisted as a predictor of all-cause (HR 2.2, 95% CI 1.7-2.9) and CVD mortality (HR 1.9, 95% CI 1.3-2.9). We observed a significant interaction between baseline LEA and sex on CVD mortality, with female sex conferring added risk of CVD mortality.Conclusions: LEA is a potent predictor of all-cause and CVD mortality in diabetic American Indians. The combination of female sex and LEA is associated with greater risk of CVD mortality than either factor alone. [ABSTRACT FROM AUTHOR]

Objective: To review 16 years of National Collegiate Athletic Association injury surveillance data for women's lacrosse and identify potential areas for injury prevention initiatives. Background: Women's lacrosse is a fast-paced, primarily noncontact sport. Participation in collegiate women's lacrosse almost doubled between the 1988-1989 and 2003-2004 seasons. Lacrosse equipment consists of sticks made of wood or a synthetic material and a hard rubber ball. Until recently, mouth guards were the only required protective equipment. Main Results: Collegiate women's lacrosse game injury rates increased over the 16-year study period. More than 60% of all severe game injuries were lower extremity sprains and strains and knee internal derangements, most frequently the result of noncontact incidents. The most common injury scenarios by injury mechanism and player activity were no contact while ball handling (16.4%) and contact from a stick while ball handling (10.5%). Contact from a stick or a ball accounted for 5.6% and 5.2% of injuries sustained during shooting activities, respectively. Approximately 22% of all game and 12% of all practice injuries involved the head and neck. Contact from a stick accounted for the majority (56.0%) of above-the-neck injuries in games; contact from the ball accounted for 20.0% of these injuries. Participants had 5 times the risk of sustaining a concussion in a game as in a practice (0.70 versus 0.15 injuries per 1000 athletic-exposures, rate ratio = 4.7, 95% confidence interval = 3.8, 6.5). Recommendations: To reduce the lower extremity injuries that comprise the greatest injury burden in women's lacrosse, future researchers should evaluate proprioceptive, plyometric, and balance training interventions designed specifically for female players. Other research areas of great interest involve determining whether protective eyewear (mandated in 2004) reduces injuries to the eye, orbit, and nasal area and identifying any unintended consequences of the mandate, such as increased risk of injuries to other areas of the face or more aggressive play. [ABSTRACT FROM AUTHOR]

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 NH 3 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.

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.

Iron (Fe)-doped β-nickel oxyhydroxide (β-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 β-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 β-NiOOH is redox inactive towards both oxidation and reduction while five-fold-lattice-coordinated Fe in β-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 β-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 β-NiOOH demonstrates a roughly facet-independent oxygen evolution activity, the activity of Fe-doped β-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 β-NiOOH.

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.

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., (© 2023 Author(s). Published under an exclusive license by AIP Publishing.)

Ammonia (NH 3 ) is an attractive low-carbon fuel and hydrogen carrier. However, losses and inefficiencies across the value chain could result in reactive nitrogen emissions (NH 3 , NO x , and N 2 O), 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 (N 2 O), 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 gCO 2 e/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.

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 Ca 2+ and Mg 2+ 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 Ca 2+ and Mg 2+ cations for sequestration and storage. Nevertheless, atomic-scale understanding of the dehydration of aqueous Ca 2+ and Mg 2+ 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 Ca 2+ and Mg 2+ . 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.

The regular incremental secretion of enamel and dentine can be interrupted during periods of stress resulting in accentuated growth lines. These accentuated lines, visible under light microscopy, provide a chronology of an individual's stress exposure. Previously, we showed that small biochemical changes along accentuated growth lines detected by Raman spectroscopy, coincided with the timing of medical history events and disruptions of weight trajectory in teeth from captive macaques. Here, we translate those techniques to study biochemical changes related to illness and prolonged medical treatment during early infancy in humans. Chemometric analysis revealed biochemical changes related to known stress-induced changes in circulating phenylalanine as well as other biomolecules. Changes in phenylalanine are also known to affect biomineralization which is reflected in changes in the wavenumbers of hydroxyapatite phosphate bands associated with stress in the crystal lattice. Raman spectroscopy mapping of teeth is an objective, minimally-destructive technique that can aid in the reconstruction of an individual's stress response history and provide important information on the mixture of circulating biochemicals associated with medical conditions, as applied in epidemiological and clinical samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Simulations of carbon dioxide (CO 2 ) 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 CO 2 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.

The electrochemical carbon dioxide reduction reaction (CO 2 RR) is a promising route to close the carbon cycle by reducing CO 2 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 CH 4 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 CH 4 selectivity.

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., (© 2023. The Author(s).)

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.

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.

Copper (Cu) remains the most efficacious electrocatalyst for electrochemical CO 2 reduction (CO 2 R). 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 CO 2 R, 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 CO 2 R mechanisms and products on Cu electrodes and sheds light on how the selectivity of CO 2 R electrocatalysts can be controlled by the surface morphology.

The electrochemical CO 2 reduction reaction (CO 2 RR) powered by excess zero-carbon-emission electricity to produce especially multicarbon (C 2+ ) products could contribute to a carbon-neutral to carbon-negative economy. Foundational to the rational design of efficient, selective CO 2 RR 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 C 2+ product formation via CO 2 RR electrocatalysts.

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 H 2 + D 2 → 2HD and NH 3 + D 2 → NH 2 D + HD were both investigated on these nanostructured complexes. While the H 2 -D 2 exchange reaction showed an additive behavior for the linear (180°) nanodisk complex, the NH 3 + D 2 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.

Importance: In many hospitals, family members are separated from their children during the early phases of trauma care. Including family members during this phase of trauma care varies by institution and is limited by concerns for adverse effects on clinical care., Objective: The aim of this study is to evaluate the effect of family presence (FP) on advanced trauma life support primary and secondary survey task performance by pediatric trauma teams. We hypothesized that trauma care with FP would be noninferior to care when families were absent., Design: We performed a retrospective video review of consecutive pediatric trauma evaluations. Family presence status was determined by availability of the family., Setting: The study was conducted at an American College of Surgeons-designated level I pediatric trauma center that serves the Washington, DC, metropolitan area., Participants: Participants included patients younger than 16 years of age who met trauma activation criteria and were evaluated by the trauma team in our emergency department., Outcome Measures: We compared task performance between patients with and without FP., Results: Video recordings of 135 trauma evaluations were reviewed. Family was present for 88 (65%) evaluations. Patients with FP were younger (mean age, 6.4 years [SD = 4.1] vs 9.0 years [SD = 4.9]; P < 0.001) and more likely to have sustained blunt injuries (95% vs 85%, P = 0.03). Noninferiority of frequency and timeliness of completion of all primary survey tasks were confirmed for evaluations with FP. Noninferiority of frequencies of secondary survey task completion was confirmed for most tasks except for examination of the neck, pelvis, and upper extremities. Family members did not directly interfere with patient care in any case., Conclusions: Performance of most advanced trauma life support tasks during pediatric trauma evaluation was not worsened by FP. Our data provide additional evidence supporting FP during the acute management of injured children., Competing Interests: Disclosure: The authors declare no conflict of interest. I, Karen O'Connell, as the principal investigator of this study, had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. All authors of this article report no conflict of interest, including financial interest, activities, relationships, and affiliations., (Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.)

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 MO 2 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.

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., (© 2021. The Author(s).)

The control of oxygen vacancy (V O ) formation is critical to advancing multiple metal-oxide-perovskite-based technologies. We report the construction of a compact linear model for the neutral V O formation energy in ABO 3 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 ABO 3 perovskites. Our model considers perovskites containing alkaline-earth metals (Ca, Sr, and Ba) and lanthanides (La and Ce) on the A-site and 3 d 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)O 3 , 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 V O concentrations but also provides a clear picture of the dominant physics governing V O formation in metal-oxide perovskites.

Quantum-mechanics-(QM)-based simulations now routinely aid in understanding and even discovering new chemistries involving molecules and materials exhibiting desired functionalities. Ab initio correlated wavefunction (CW) theories systematically improve QM methods, with many exhibiting high accuracy. However, execution of CW methods requires expensive computations that typically scale poorly with system size. Divide-and-conquer approaches partition large systems into smaller fragments; a lower level of theory treats fragment interactions while a preferred higher level of theory describes the important fragment. These methods offer ways to incorporate CWs into chemical simulations of large systems, e.g., biomolecules, surfaces, large inorganic clusters, bulk crystals, etc. Here we propose a partitioning protocol that utilizes capping atoms to saturate severed covalent bonds at fragment interfaces and density functional embedding theory (DFET) to describe fragment interactions. The capping groups in each fragment provide an ad-hoc potential that approximates the effects of the environment. An embedding potential optimized via DFET then serves as an augmentation of the capping group to simulate the effects of the environment. We concurrently use an auxiliary fragment (a separate system comprised of only the combined capping groups) to account for, and thereby correct, the electron density contributions of all the capping groups added to all of the fragments. This method depends only on the capped-subsystem and auxiliary-fragment electron densities, forgoing, as with the original DFET developed for metallic systems, orbital-based projector approaches that determine a nonlocal action of the embedding potential onto the fragment electrons. By using an auxiliary fragment, the method maintains a purely electron-density-dependent embedding potential, substantially lessening the cost and leading to simpler implementation. Here, we demonstrate the utility of our capped-DFET and ensuing capped embedded CW method in two contrasting systems, namely, an organic molecule and an ionic metal oxide cluster.

Understanding optical properties of the dye molecule in dye-sensitized solar cells (DSSCs) from first-principles quantum mechanics can contribute to improving the efficiency of such devices. While density functional theory (DFT) and time-dependent DFT have been pivotal in simulating optoelectronic properties of photoanodes used in DSSCs at the atomic scale, questions remain regarding DFT's adequacy and accuracy to furnish critical information needed to understand the various excited-state processes involved. Here, we simulate the absorption spectra of a dye-sensitized solar cell analogue, comprised of a Ru-bipyridine (Ru-bpy) dye molecule and a small TiO 2 cluster via DFT and via an accurate embedded correlated wavefunction (CW) theory. We generated CW spectra for the adsorbed Ru-bpy dye via a recently introduced capped density functional embedding theory or capped-DFET (to generate the embedding potential that accounts for the interaction of the molecule and the TiO 2 cluster). We then combined capped-DFET with the accurate but expensive multiconfigurational complete active space second-order perturbation theory (CASPT2)-embedded CASPT2. Because the CW theory is conducted on only a portion of the total system in the presence of an embedding potential that describes that portion's interaction with its environment, we efficiently obtain CW-quality predictions that reflect local properties of the entire system. Specifically, for example, with capped-DFET and embedded CW theory, we can simulate accurately a plethora of metal-to-ligand charge-transfer excited properties at a manageable computational cost. Here, we predict detailed electronic spectra within the visible region, featuring the lowest three singlet and triplet excited states, along with predictions of the singlets' lifetimes. We illustrated these results using a Jablonski diagram that show the relative energy position of the singlet and longer-lived triplet excited states and analyzed and proposed relaxation paths for the excited state corresponding to the most intense but short-lived absorption (interconversion, intersystem crossing, fluorescence, and phosphorescence) that may lead to longer-lived excited states necessary for efficient charge separation required to generate current in solar cells.

Light-induced hot carriers derived from the surface plasmons of metal nanostructures have been shown to be highly promising agents for photocatalysis. While both nonthermal and thermalized hot carriers can potentially contribute to this process, their specific role in any given chemical reaction has generally not been identified. Here, we report the observation that the H 2 -D 2 exchange reaction photocatalyzed by Cu nanoparticles is driven primarily by thermalized hot carriers. The external quantum yield shows an intriguing S-shaped intensity dependence and exceeds 100% for high light intensities, suggesting that hot carrier multiplication plays a role. A simplified model for the quantum yield of thermalized hot carriers reproduces the observed kinetic features of the reaction, validating our hypothesis of a thermalized hot carrier mechanism. A quantum mechanical study reveals that vibrational excitations of the surface Cu-H bond is the likely activation mechanism, further supporting the effectiveness of low-energy thermalized hot carriers in photocatalyzing this reaction., Competing Interests: The authors declare no competing interest.

Copper (Cu) electrodes, as the most efficacious of CO 2 reduction reaction (CO 2 RR) electrocatalysts, serve as prototypes for determining and validating reaction mechanisms associated with electrochemical CO 2 reduction to hydrocarbons. As in situ electrochemical mechanism determination by experiments is still out of reach, such mechanistic analysis typically is conducted using density functional theory (DFT). The semilocal exchange-correlation (XC) approximations most often used to model such catalysis unfortunately engender a basic error: predicting the wrong adsorption site for CO (a key CO 2 RR intermediate) on the most ubiquitous facet of Cu, namely, Cu(111). This longstanding inconsistency casts lingering doubt on previous DFT predictions of the attendant CO 2 RR kinetics. Here, we apply embedded correlated wavefunction (ECW) theory, which corrects XC functional error, to study the CO 2 RR on Cu(111) via both surface hydride (*H) transfer and proton-coupled electron transfer (PCET). We predict that adsorbed CO (*CO) reduces almost equally to two intermediates, namely, hydroxymethylidyne (*COH) and formyl (*CHO) at -0.9 V vs the RHE. In contrast, semilocal DFT approximations predict a strong preference for *COH. With increasing applied potential, the dominance of *COH (formed via potential-independent surface *H transfer) diminishes, switching to the competitive formation of both *CHO and *COH (both formed via potential-dependent PCET). Our results also demonstrate the importance of including explicitly modeled solvent molecules in predicting electron-transfer barriers and reveal the pitfalls of overreliance on simple surface *H transfer models of reduction reactions.

The size- and shape-controlled enhanced optical response of metal nanoparticles (NPs) is referred to as a localized surface plasmon resonance (LSPR). LSPRs result in amplified surface and interparticle electric fields, which then enhance light absorption of the molecules or other materials coupled to the metallic NPs and/or generate hot carriers within the NPs themselves. When mediated by metallic NPs, photocatalysis can take advantage of this unique optical phenomenon. This review highlights the contributions of quantum mechanical modeling in understanding and guiding current attempts to incorporate plasmonic excitations to improve the kinetics of heterogeneously catalyzed reactions. A range of first-principles quantum mechanics techniques has offered insights, from ground-state density functional theory (DFT) to excited-state theories such as multireference correlated wavefunction methods. Here we discuss the advantages and limitations of these methods in the context of accurately capturing plasmonic effects, with accompanying examples.

Embedded (emb-) correlated wavefunction (CW) theory enables accurate assessments of both ground- and excited-state reaction mechanisms involved in heterogeneous catalysis. Embedded multireference second-order perturbation theory (emb-MRPT2) based on reference wavefunctions generated via embedded complete active space self-consistent field (emb-CASSCF) theory is currently state-of-the-art. However, the factorial scaling of CASSCF limits the size of active space and the complexity of systems that can be studied. Here, we assess the efficacy of an alternative CW method, adaptive sampling configuration interaction (ASCI)-which enables large active spaces to be used-for studying surface reactions. We couple ASCI with density functional embedding theory (DFET) and benchmark its performance for two reactions: H 2 desorption from and CH 4 dissociation on the Cu(111) surface. Unlike embedded complete active space second-order perturbation theory (emb-CASPT2) that accurately reproduces a measured H 2 desorption barrier, embedded ASCI, using a very large active space (though one that still comprises a small portion of the full set of orbitals) fails to do so. Adding an extra correlation term from embedded Møller-Plesset second-order perturbation theory (emb-MP2) improves the desorption barrier and endothermicity predictions. Thus, the inaccuracy of embedded ASCI comes from the missing dynamic correlation from the many other electrons and orbitals not included in the active space. For CH 4 dissociation, again embedded ASCI overestimates the dissociation barrier compared to emb-CASPT2 predictions. Adding dynamic correlation from emb-MP2 helps correct the barrier. However, this composite approach suffers from double counting of correlation within embedded ASCI followed by emb-MP2 calculations. We therefore conclude that the state-of-the-art emb-MRPT2 based on reference wavefunctions generated via emb-CASSCF remains the method of choice for studying surface reactions. emb-ASCI is useful when large active spaces beyond the limit of emb-CASSCF are essential, such as to study complex surface reactions with significant multiconfigurational character (static correlation) but weak dynamic correlation.

Electrical double layers (EDLs) play a significant role in a broad range of physical phenomena related to colloidal stability, diffuse-charge dynamics, electrokinetics, and energy storage applications. Recently, it has been suggested that for large ion sizes or multivalent electrolytes, ions can arrange in a layered structure inside the EDLs. However, the widely used Poisson-Boltzmann models for EDLs are unable to capture the details of ion concentration oscillations and the effect of electrolyte valence on such oscillations. Here, by treating a pair of ions as hard spheres below the distance of closest approach and as point charges otherwise, we are able to predict ionic layering without any additional parameters or boundary conditions while still being compatible with the Poisson-Boltzmann framework. Depending on the combination of ion valence, size, and concentration, our model reveals a structured EDL with spatially oscillating ion concentrations. We report the dependence of critical ion concentration, i.e., the ion concentration above which the oscillations are observed, on the counter-ion valence and the ion size. More importantly, our model displays quantitative agreement with the results of computationally intensive models of the EDL. Finally, we analyze the nonequilibrium problem of EDL charging and demonstrate that ionic layering increases the total charge storage capacity and the charging timescale.

We re-evaluate two key steps in the mechanism of CO 2 reduction on copper at a higher level of theory capable of correcting inherent errors in density functional theory (DFT) approximations, namely, embedded correlated wavefunction (ECW) theory. Here, we consider the CO reduction step on Cu(111), which is critical to understanding reaction selectivity. We optimize embedding potentials at the periodic plane-wave DFT level using density functional embedding theory (DFET). All possible adsorption sites (adsites) for each adsorbate then are screened with ECW theory at the catalytically active site to refine the local electronic structure. Unsurprisingly, DFT and ECW theory predict different adsite preferences, largely because of DFT's inability to properly situate the CO 2π* level. Differing preferred adsites suggest that different reaction pathways could emerge from DFT versus ECW theory. Starting from these preferred ECW theory adsites, we then obtain reaction pathways at the plane-wave DFT level using the climbing-image nudged elastic band method to determine minimum energy paths. Thereafter, we perform ECW calculations at the catalytically active site to correct the energetics at each interpolated structure (image) along the reaction pathways. Via this approach, we confirm that the first step in CO reduction via hydrogen transfer on Cu(111) is to form hydroxymethylidyne (*COH) instead of formyl (*CHO). Although the prediction to preferentially form *COH is consistent with that of DFT, the two theories predict quite different structural and mechanistic behaviors, suggesting that verification is needed for other parts of the mechanism of CO 2 reduction, which is the subject of ongoing work.

It is known that cells grown in 3D are more tolerant to drug treatment than those grown in dispersion, but the mechanism for this is still not clear; cells grown in 3D have opportunities to develop inter-cell communication, but are also closely packed which may impede diffusion. In this study we examine methods for dielectrophoresis-based cell aggregation of both suspension and adherent cell lines, and compare the effect of various drugs on cells grown in 3D and 2D. Comparing viability of pharmacological interventions on 3D cell clusters against both suspension cells and adherent cells grown in monolayer, as well as against a unicellular organism with no propensity for intracellular communication, we suggest that 3D aggregates of adherent cells, compared to suspension cells, show a substantially different drug response to cells grown in monolayer, which increases as the IC 50 is approached. Further, a mathematical model of the system for each agent demonstrates that changes to drug response are due to inherent changes in the system of adherent cells from the 2D to 3D state. Finally, differences in the electrophysiological membrane properties of the adherent cell type suggest this parameter plays an important role in the differences found in the 3D drug response.

The core part of the program system COLUMBUS allows highly efficient calculations using variational multireference (MR) methods in the framework of configuration interaction with single and double excitations (MR-CISD) and averaged quadratic coupled-cluster calculations (MR-AQCC), based on uncontracted sets of configurations and the graphical unitary group approach (GUGA). The availability of analytic MR-CISD and MR-AQCC energy gradients and analytic nonadiabatic couplings for MR-CISD enables exciting applications including, e.g., investigations of π-conjugated biradicaloid compounds, calculations of multitudes of excited states, development of diabatization procedures, and furnishing the electronic structure information for on-the-fly surface nonadiabatic dynamics. With fully variational uncontracted spin-orbit MRCI, COLUMBUS provides a unique possibility of performing high-level calculations on compounds containing heavy atoms up to lanthanides and actinides. Crucial for carrying out all of these calculations effectively is the availability of an efficient parallel code for the CI step. Configuration spaces of several billion in size now can be treated quite routinely on standard parallel computer clusters. Emerging developments in COLUMBUS, including the all configuration mean energy multiconfiguration self-consistent field method and the graphically contracted function method, promise to allow practically unlimited configuration space dimensions. Spin density based on the GUGA approach, analytic spin-orbit energy gradients, possibilities for local electron correlation MR calculations, development of general interfaces for nonadiabatic dynamics, and MRCI linear vibronic coupling models conclude this overview.