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The correlation consistent basis sets (cc-pVnZ with n = D, T, Q, 5) for the Ga–Br elements have been redesigned, tuning the sets for use for density functional approximations. Steps to redesign these basis sets for an improved correlation energy recovery and efficiency include truncation of higher angular momentum functions, recontraction of basis set coefficients, and reoptimization of basis set exponents. These redesigned basis sets are compared with conventional cc-pVnZ basis sets and other basis sets, which are, in principle, designed to achieve systematic improvement with respect to increasing basis set size. The convergence of atomic energies, bond lengths, bond dissociation energies, and enthalpies of formation to the Kohn–Sham limit is improved relative to other basis sets where convergence to the Kohn–Sham limit is typically not observed. [ABSTRACT FROM AUTHOR]

Understanding the behavior of intrinsic defects and helium (He) in tungsten oxides is useful for the application of tungsten (W) in a fusion environment because of the oxidation of W surfaces. The formation and diffusion energies of intrinsic defects and He in monoclinic γ-WO3 have been investigated using first-principles density functional theory calculations. The formation energy and diffusion activation energy of O defects are lower than W defects. O vacancy prefers to diffuse along the ⟨ 001 ⟩ direction, then followed by ⟨ 010 ⟩ and ⟨ 100 ⟩ directions; however, the W vacancy is immobile at temperatures lower than 2000 K. The stability of Schottky defects (SDs) is sensitive to their geometry and orientation. W interstitials prefer to move along the [100] direction, while O interstitials jump around W atoms rather than through the W quasi-cubic centers. He interstitial atoms are predicted to have a high solubility and an anisotropic diffusion mechanism in γ-WO3. In addition, the effect of biaxial strain on the solubility and diffusivity of He interstitials was investigated. He interstitials prefer to reside at individual sites rather than clusters. He atoms are weakly trapped by single vacancies or SDs. Vacancies assist the local migration of nearby He. Correspondingly, He self-clustering and bubble formation are less likely to form in γ-WO3 relative to bcc W. The energetics obtained in this work can be used to predict the microstructure evolution of the WO3 layer on a W substrate exposed to He plasmas at different temperatures. [ABSTRACT FROM AUTHOR]

Photoredox properties of several earth-abundant light-harvesting transition metal complexes in combination with cobalt-based proton reduction catalysts have been investigated computationally to assess the fundamental viability of different photocatalytic systems of current experimental interest. Density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations using several GGA (BP86, BLYP), hybrid-GGA (B3LYP, B3LYP*), hybrid meta-GGA (M06, TPSSh), and range-separated hybrid (ωB97X, CAM-B3LYP) functionals were used to calculate relevant ground and excited state reduction potentials for photosensitizers, catalysts, and sacrificial electron donors. Linear energy correction factors for the DFT/TD-DFT results that provide the best agreement with available experimental reference results were determined in order to provide more accurate predictions. Among the selection of functionals, the B3LYP* and TPSSh sets of correction parameters were determined to give the best redox potentials and excited states energies, ΔEexc, with errors of ∼0.2 eV. Linear corrections for both reduction and oxidation processes significantly improve the predictions for all the redox pairs. In particular, for TPSSh and B3LYP*, the calculated errors decrease by more than 0.5 V against experimental values for catalyst reduction potentials, photosensitizer oxidation potentials, and electron donor oxidation potentials. Energy-corrected TPSSh results were finally used to predict the energetics of complete photocatalytic cycles for the light-driven activation of selected proton reduction cobalt catalysts. These predictions demonstrate the broader usefulness of the adopted approach to systematically predict full photocycle behavior for first-row transition metal photosensitizer–catalyst combinations more broadly. [ABSTRACT FROM AUTHOR]

We present a systematic study of the electronic properties of dangling bonds (DBs) in a variety of semiconductors and examine the relationship between DBs and the charge neutrality level (CNL) in the context of band alignments of semiconductors. We use first-principles calculations based on density functional theory to assess the energetics of DBs in a set of diamond-structure group-IV and III–V or II–VI zinc-blende-structure semiconductors, considering both cation and anion-derived states. We examine the charge-state transition levels of DBs to assess whether they can serve as a CNL to align band structures, by comparing with offsets calculated from interface calculations. Our results show that this approach for evaluating the CNL yields quantitative results for band offsets and provides useful insights. We discuss the relation with alternative approaches for determination of CNLs based on branch-point energies or transition levels of interstitial hydrogen. [ABSTRACT FROM AUTHOR]

A layered sodium-ion battery cathode, O3/P3/P2-type NaNi1/3Mn1/3Fe1/3O2, has been systematically investigated by first-principles density functional theory to explore the detailed structural and Na-ion diffusion behavior during desodiation. Our results suggest that the (NaO6) spacing is greatest in the P3 phase and lowest in the O3 phase, with the P2 phase exhibiting intermediate spacing. During desodiation, the intermediate stages have a greater (NaO6) spacing than the initial and final stages. The great (NaO6) spacing facilitates the formation of the P3 phase, resulting in the structural evolution of NaxNi1/3Mn1/3Fe1/3O2 from the O3 to the P3 phase at x ≈ 0.59, finally reaching the O3 structure again at x ≈ 0.12. The electronic structure clearly proves that both Ni and Fe are active in O3/P3/P2-type NaxNi1/3Mn1/3Fe1/3O2. Ni2+ is oxidized to Ni3+ as Na content decreases from x = 1 to x = 0.66, then further oxidized to Ni4+ at x = 0.33, and finally, Fe3+ → Fe4+ oxidation occurs at x = 0. In the Na ion diffusion behavior, the order of the barrier is O3 (0.82 eV) > P2 (0.53 eV) > P3 (0.35 eV) at the initial stage, whereas it is O3 (0.53 eV) > P3 (0.21 eV) > P2 (0.16 eV) at a highly desodiated stage. The former can be traced back to the (NaO6) spacing, but the latter is related to the different Na sites. Our results thus provide a factor of the structural evolution and Na ion diffusion barrier by considering (NaO6) width and Na site changes during desodiation. [ABSTRACT FROM AUTHOR]

Electrostatic correlations between ions dissolved in water are known to impact their transport properties in numerous ways, from conductivity to ion selectivity. The effects of these correlations on the solvent itself remain, however, much less clear. In particular, the addition of salt has been consistently reported to affect the solution's viscosity, but most modeling attempts fail to reproduce experimental data even at moderate salt concentrations. Here, we use an approach based on stochastic density functional theory, which accurately captures charge fluctuations and correlations. We derive a simple analytical expression for the viscosity correction in concentrated electrolytes, by directly linking it to the liquid's structure factor. Our prediction compares quantitatively to experimental data at all temperatures and all salt concentrations up to the saturation limit. This universal link between the microscopic structure and viscosity allows us to shed light on the nanoscale dynamics of water and ions under highly concentrated and correlated conditions. [ABSTRACT FROM AUTHOR]

Simulations of condensed matter systems at the hybrid density functional theory level pose significant computational challenges. The elevated costs arise from the non-local nature of the Hartree–Fock exchange (HFX) in conjunction with the necessity to approach the thermodynamic limit. In this work, we address these issues with the development of a new efficient method for the calculation of HFX in periodic systems, employing k-point sampling. We rely on a local atom-specific resolution-of-the-identity scheme, the use of atom-centered Gaussian type orbitals, and the truncation of the Coulomb interaction to limit computational complexity. Our real-space approach exhibits a scaling that is, at worst, linear with the number of k-points. Issues related to basis set diffuseness are effectively addressed through the auxiliary density matrix method. We report the implementation in the CP2K software package, as well as accuracy and performance benchmarks. This method demonstrates excellent agreement with equivalent Γ-point supercell calculations in terms of relative energies and nuclear gradients. Good strong and weak scaling performances, as well as graphics processing unit (GPU) acceleration, make this implementation a promising candidate for high-performance computing. [ABSTRACT FROM AUTHOR]

Computational study of electronic resonances is still a very challenging topic, with the phenomenon of dissociative electron attachment (DEA) being one of the multiple features worth investigating. Recently, we extended the charge stabilization method from energies to properties of conceptual density functional theory and applied this to metastable anionic states of ethene and chlorinated ethene derivatives to study the DEA mechanism present in these compounds. We now present an extension to spatial functions, namely, the electronic Fukui function and the electron localization function. The results of our analysis show that extrapolated spatial functions are relevant and useful for more precise localization of the unbound electron. Furthermore, we report for the first time the combination of the electron localization function with Berlin's binding function for these challenging electronic states. This promising methodology allows for accurate predictions of when and where DEA will happen in the molecules studied and provides more insight into the process. [ABSTRACT FROM AUTHOR]

We present an algorithm to find first order saddle points on the potential energy surface (PES). The algorithm is formulated as a constrained optimization problem that involves two sets of atomic coordinates (images), a time-varying distance constraint and a constraint on the energy difference. Both images start in different valleys of the PES and are pulled toward each other by gradually reducing the distance. The search space is restricted to the pairs of configurations that share the same potential energy. By minimizing the energy while the distance shrinks, a minimum of the constrained search space is tracked. In simple cases, the two images are confined to their respective sides of the barrier until they finally converge near the saddle point. If one image accidentally crosses the barrier, the path is split at suitable locations and the algorithm is repeated recursively. The optimization is implemented as a combination of a quasi-Newton optimization and a linear constraint. The method was tested on a set of Lennard-Jones-38 cluster transitions and a set of 121 molecular reactions using density functional theory calculations. The efficiency in terms of energy and force evaluation is better than with competing methods as long as they do not switch to single-ended methods. The construction of a continuous search path with small steps and the ability to focus on arbitrary subsegments of the path provide an additional value in terms of robustness and flexibility. [ABSTRACT FROM AUTHOR]

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy. [ABSTRACT FROM AUTHOR]

Expanding the pool of stable halide perovskites with attractive optoelectronic properties is crucial to addressing current limitations in their performance as photovoltaic (PV) absorbers. In this article, we demonstrate how a high-throughput density functional theory (DFT) dataset of halide perovskite alloys can be used to train accurate surrogate models for property prediction and subsequently perform inverse design using genetic algorithm (GA). Our dataset consists of decomposition energies, bandgaps, and photovoltaic efficiencies of nearly 800 pure and mixed composition ABX3 compounds from both the GGA-PBE and HSE06 functionals, and are combined with ∼100 experimental data points collected from the literature. Multi-fidelity random forest regression models are trained on the DFT + experimental dataset for each property using descriptors that one-hot encode composition, phase, and fidelity, and additionally include well-known elemental or molecular properties of species at the A, B, and X sites. Rigorously optimized models are deployed for experiment-level prediction over >150 000 hypothetical compounds, leading to thousands of promising materials with low decomposition energy, band gap between 1 and 2 eV, and efficiency of >15%. Surrogate models are further combined with GA using an objective function to maintain chemical feasibility, minimize decomposition energy, maximize PV efficiency, and keep bandgap between 1 and 2 eV; thus, hundreds more optimal compositions and phases are discovered. We present an analysis of the screened and inverse-designed materials, visualize ternary phase diagrams generated for many systems of interest using machine learning predictions, and suggest strategies for further improvement and expansion in the future. [ABSTRACT FROM AUTHOR]

Many important chemical processes involve reactivity and dynamics in complex solutions. Gaining a fundamental understanding of these reaction mechanisms is a challenging goal that requires advanced computational and experimental approaches. However, important techniques such as molecular simulation have limitations in terms of scales of time, length, and system complexity. Furthermore, among the currently available solvation models, there are very few designed to describe the interaction between the molecular scale and the mesoscale. To help address this challenge, here, we establish a novel hybrid approach that couples first-principles plane-wave density functional theory with classical density functional theory (cDFT). In this approach, a region of interest described by ab initio molecular dynamics (AIMD) interacts with the surrounding medium described using cDFT to arrive at a self-consistent ground state. cDFT is a robust but efficient mesoscopic approach to accurate thermodynamics of bulk electrolyte solutions over a wide concentration range (up to 2M concentrations). Benchmarking against commonly used continuum models of solvation, such as SMD, as well as experiments, demonstrates that our hybrid AIMD–cDFT method is able to produce reasonable solvation energies for a variety of molecules and ions. With this model, we also examined the solvent effects on a prototype SN2 reaction of the nucleophilic attack of a chloride ion on methyl chloride in the solution. The resulting reaction pathway profile and the solution phase barrier agree well with experiment, showing that our AIMD/cDFT hybrid approach can provide insight into the specific role of the solvent on the reaction coordinate. [ABSTRACT FROM AUTHOR]

Negative differential resistance (NDR) is observed in various emerging electronic devices. As compared to the conventional silicon-based field effect transistor (FET), the NDR is widely investigated in two-dimensional (2D) transition metal dichalcogenide (TMD) FETs. In this work, we study the NDR effect for the TMD-based metal-edge-contact MoS 2 double-gate FET with 10 nm channel length. The multiscale atomistic simulation is demonstrated for the lateral heterostructure of a metal–semiconductor–metal FET by density functional theory, maximally localized Wannier function tight-binding Hamiltonian, and non-equilibrium Green's function methods. The quantum transport model in the given lateral heterostructure resulted in NDR in a double-gate FET. Here, we focus on the NDR by the systematic study of the transmission spectrum of the metal-edge-contact MoS 2 channel FET and finally compare it with zero NDR ideal highly doped FET. The peak-to-valley ratio in the NDR response can be modulated with the change in the gate-to-source voltage and can be used to explore various future electronic applications. [ABSTRACT FROM AUTHOR]

We designed a trigonal symmetric imine-linked covalent organic framework (COF), TFPC-DAB, with control over the angularity of the building units, where a bent C2-symmetric diamine, such as 1,3-diaminobenzene (1,3-DAB or DAB), with an exo-angle of 120° was used instead of those with an exo-angle of 180°, in combination with a C3-symmetric trialdehyde, such as tri(4-formylphenoxy)cyanurate (TFPC). Its synthesis was accomplished by reacting the building units in a mixture of mesitylene/dioxane/6 M acetic acid under solvothermal conditions. The phase purity, thermal stability, and porosity of TFPC-DAB were established by various analytical techniques. Utilizing the Density Functional Tight Binding (DFTB+) simulation and Pawley refinement, the best fit of the small angle x-ray pattern was found to have an AA stacking of TFPC-DAB in the trigonal space group P3 with low refinement parameters. Such smart materials are in huge demand to detect hazardous corrosive chemicals, such as HCl and NH3. The dual features of electron deficient π-acidic triazine moiety and heteroatoms (N/O) from TFPC and electron rich phenyl units from DAB embodied in the framework enhance its luminescent property and thereby make it suitable for solvent-based HCl and NH3 sensing. The detection limits for HCl and NH3 in methanol were found to be 14 and 82 ppb, respectively. The effect of solvent polarity on the sensing studies was observed with much lower detection limits in dioxane: 2.5 and 11 ppb for HCl and NH3, respectively. A detailed theoretical calculation using density functional theory and configurational bias Monte Carlo modules was conducted for understanding interactions between the COF and HCl or NH3 analytes. [ABSTRACT FROM AUTHOR]

For the most precise incorporation of single impurities in silicon, which is utilized to create quantum devices, a monolayer of adatoms on the Si(100) surface and a dopant-containing molecule are used. Here, we studied the interaction of phosphorus tribromide with a chlorine monolayer with mono- and bivacancies using a scanning tunneling microscope (STM) at 77 K. The combination of different halogens in the molecule and the adsorbate layer enabled unambiguous identification of the structures after PBr3 dissociation on Si(100)-Cl. A Cl monolayer was exposed to PBr3 in the STM chamber, which allows us to compare the same surface areas before and after PBr3 adsorption. As a result of this comparison, we detected small changes in the chlorine layer and unraveled the molecular fragments filling mono- and bivacancies. Using density functional theory, we found that the phosphorus atom occupies a bridge position after dissociation of the PBr3 molecule, which primarily bonds with silicon in Cl bivacancies. These findings provide insight into the interaction of a dopant-containing molecule with an adsorbate monolayer on Si(100) and can be applied to improve the process of single impurity incorporation into silicon. [ABSTRACT FROM AUTHOR]

A new free-energy functional is proposed for inhomogeneous associating fluids. The general formulation of Wertheim's thermodynamic perturbation theory is considered as the starting point of the derivation. We apply the hypotheses of the statistical associating fluid theory in the classical density functional theory (DFT) framework to obtain a tractable expression of the free-energy functional for inhomogeneous associating fluids. Specific weighted functions are introduced in our framework to describe association interactions for a fluid under confinement. These weighted functions have a mathematical structure similar to the weighted densities of the fundamental-measure theory (i.e., they can be expressed as convolution products) such that they can be efficiently evaluated with Fourier transforms in a 3D space. The resulting free-energy functional can be employed to determine the microscopic structure of inhomogeneous associating fluids of arbitrary 3D geometry. The new model is first compared with Monte Carlo simulations and previous versions of DFT for a planar hard wall system in order to check its consistency in a 1D case. As an example of application in a 3D configuration, we then investigate the extreme confinement of an associating hard-sphere fluid inside an anisotropic open cavity with a shape that mimics a simplified model of zeolite. Both the density distribution and the corresponding molecular bonding profile are given, revealing complementary information to understand the structure of the associating fluid inside the cavity network. The impact of the degree of association on the preferential positions of the molecules inside the cavity is investigated as well as the competition between association and steric effect on adsorption. [ABSTRACT FROM AUTHOR]

We describe Reflection Absorption Infrared Spectroscopy (RAIRS) and first-principles Density Functional Theory (DFT) studies of ammonia adsorption on the Cu{311} surface. Our experimental results indicate an upright chemisorbed species at low coverages, with at least one additional species accompanying this at higher coverages. Our high-coverage RAIRS data cannot be fully explained by DFT models containing only ammonia or its dissociation products, even allowing for molecular tilt and/or the formation of a bilayer. We therefore also consider urea and formamide as possible products of surface reaction with residual carbon monoxide, but these species are again not fully compatible with our observed spectra. The overlayer composition at high coverages remains mysterious. [ABSTRACT FROM AUTHOR]

Ever since ferroelectricity was discovered in HfO 2 , the question of its origin remains controversial. Here, we probe this question using a combination of Landau theory of phase transitions and first-principles computations. In such an approach, the energy landscape associated with the phase transition between cubic and different experimentally demonstrated phases of HfO 2 (tetragonal, monoclinic, orthorhombic Pbca, orthorhombic Pnma, and orthorhombic Pca 2 1) is explored using density functional theory calculations. Computations revealed that stabilization of all but orthorhombic Pbca phase is driven by a single unstable zone-boundary antipolar mode X 2 −. When coupled with zone-center modes (Γ 1 + and Γ 3 +), it stabilizes the tetragonal phase. Coupling with four additional modes (Γ 5 + , X 3 − , X 5 − , X 5 +) results in the monoclinic phase, which is the ground state of the material. If, however, Γ 5 + mode is replaced with Γ 4 − mode, orthorhombic polar phase Pca 2 1 is stabilized. The application of this framework to examine the effect of electric field on the ferroelectric phase of hafnia reveals that the field of 5 MV/cm is capable of stabilizing ferroelectric phase over the monoclinic one at 0 K. [ABSTRACT FROM AUTHOR]

With the development of electronic structure theory, a new class of materials—quantum ones—has been recognized by the community. Traditionally, it has been believed that the properties of such compounds cannot be described within the framework of modern density functional theory, and indeed, more advanced post-mean-field theory methods are needed. Motivated by this, herein, we develop a fundamental understanding of such complex materials using the example of paramagnetic YNiO3, which is experimentally known to exhibit metal-to-insulator phase transition. We show that this material has a temperature-dependent distribution of local motifs. Thus, while at low temperatures, YNiO3 has distinct structural disproportionation with the formation of large and small octahedra, as the temperature increases, this disproportionation is suppressed. We also explain the paramagnetic monoclinic to paramagnetic orthorhombic phase transition within the double-well to single-well energy profile, predicting the variation in the corresponding energy profile as a function of octahedral size distribution. In this way, we demonstrate a fundamental understanding of structural phase transitions in quantum materials, giving insights into how they can be used for different applications and what minimum level of theory is needed to describe such types of complex materials at finite temperatures. [ABSTRACT FROM AUTHOR]

We explore theoretically the effects of external potentials on the spatial distribution of particle properties in a liquid of explicitly responsive macromolecules. In particular, we focus on the bistable particle size as a coarse-grained internal degree of freedom (DoF, or "property"), σ, that moves in a bimodal energy landscape, in order to model the response of a state-switching (big-to-small) macromolecular liquid to external stimuli. We employ a mean-field density functional theory (DFT) that provides the full inhomogeneous equilibrium distributions of a one-component model system of responsive colloids (RCs) interacting with a Gaussian pair potential. For systems confined between two parallel hard walls, we observe and rationalize a significant localization of the big particle state close to the walls, with pressures described by an exact RC wall theorem. Application of more complex external potentials, such as linear (gravitational), osmotic, and Hamaker potentials, promotes even stronger particle size segregation, in which macromolecules of different size are localized in different spatial regions. Importantly, we demonstrate how the degree of responsiveness of the particle size and its coupling to the external potential tune the position-dependent size distribution. The DFT predictions are corroborated by Brownian dynamics simulations. Our study highlights the fact that particle responsiveness can be used to localize liquid properties and therefore helps to control the property- and position-dependent function of macromolecules, e.g., in biomedical applications. [ABSTRACT FROM AUTHOR]

The Random-Phase approximation (RPA) provides an appealing framework for semi-local density functional theory. In its Resolution-of-the-Identity (RI) approach, it is a very accurate and more cost-effective method than most other wavefunction-based correlation methods. For widespread applications, efficient implementations of nuclear gradients for structure optimizations and data sampling of machine learning approaches are required. We report a well scaling implementation of RI-RPA nuclear gradients on massively parallel computers. The approach is applied to two polymorphs of the benzene crystal obtaining very good cohesive and relative energies. Different correction and extrapolation schemes are investigated for further improvement of the results and estimations of error bars. [ABSTRACT FROM AUTHOR]

Hydrogen is a promising energy carrier, but its onboard application is limited by the need for compact, low-pressure storage solutions. Solid-state complex metal hydride systems, such as MgB 2 /Mg(BH 4) 2 , offer high storage capacities but suffer from sluggish kinetics and poor reversibility. One avenue for improving reactivity is to introduce metal dopants to alter electronic and atomic properties, but the role of these chemical additives remains poorly understood, particularly for the hydrogenation reaction. In this work, we used density functional theory calculations on model MgB 2 systems to rationalize the potential role of metal dopants in destabilizing B–B bonding within the MgB 2 lattice. We carried out detailed electronic structure analyses for 28 different metal dopant adatoms to identify properties that contribute to a dopant's efficacy. Based on the simulation results, we propose that an intermediate ionic and covalent character of the bonds between adatoms and B atoms is desirable for facilitating charge redistribution, disrupting the B–B bond network, and promoting H 2 dissociation and H atom chemisorption on MgB 2. [ABSTRACT FROM AUTHOR]

A thermally driven needle-like (NL) to distorted perovskite (DP) phase transition in SrZrS3 was investigated by means of ab initio free energy calculations accelerated by machine learning. As a first step, a systematic screening of the methods to include long-range interactions in semilocal density functional theory Perdew–Burke–Ernzerhof calculations was performed. Out of the ten correction schemes tested, the Tkatchenko–Scheffler method with iterative Hirshfeld partitioning method was found to yield the best match between calculated and experimental lattice geometries, while predicting the correct order of stability of NL and DP phases at zero temperature. This method was then used in free energy calculations, performed using several approaches, so as to determine the effect of various anharmonicity contributions, such as the anisotropic thermal lattice expansion or the thermally induced internal structure changes, on the phase transition temperature (TNP→DP). Accounting for the full anharmonicity by combining the NPT molecular dynamics data with thermodynamic integration with harmonic reference provided our best estimate of TNL→DP = 867 K. Although this result is ∼150 K lower than the experimental value, it still provides an improvement by nearly 300 K compared to the previous theoretical report by Koocher et al. [Inorg. Chem. 62, 11134–11141 (2023)]. [ABSTRACT FROM AUTHOR]

The 6D time-dependent wave packet calculations were performed to explore H2 dissociation on Ag, Au, and two AgAu alloy surfaces, using four newly fitted potential energy surfaces based on the neural network fitting to density functional theory energy points. The ligand effect resulting from the Ag–Au interaction causes a reduction in the barrier height for H2+Ag/Au(111) compared to H2+Ag(111). However, the scenario is reversed for H2+Au/Ag(111) and H2+Au(111). The 6D dissociation probabilities of H2 on Ag/Au(111) surfaces are significantly higher than those on the pure Ag(111) surface, but the corresponding results for H2 on Au/Ag(111) surfaces are substantially lower than those on the pure Au(111) surface. The reactivity of H2 on Au(111) is larger than that on Ag(111), despite Ag(111) having a slightly lower static barrier height. This can be attributed to the exceptionally small dissociation probabilities at the hcp and fcc regions, which are at least 100 times smaller compared to those at the bridge or top site for H2+Ag(111). Due to the late barrier being more pronounced, the vibrational excitation of H2 on Ag(111) is more effective in promoting the reaction than on Au(111). Moreover, a high degree of alignment dependence is detected for the four reactions, where the H2 dissociation has the highest probability at the helicopter alignment, as opposed to the cartwheel alignment. [ABSTRACT FROM AUTHOR]

EA-EOM-CCSD electron affinities and LUMO energies of various Kohn–Sham density functional theory (DFT) methods are calculated for an a priori IP benchmark set of 64 small, closed-shell molecules. The purpose of these calculations was to investigate whether the QTP KS-DFT functionals can emulate EA-EOM-CC with only a mean-field approximation. We show that the accuracy of DFT—relative to CCSD—improves significantly when elements of correlated orbital theory are introduced into the parameterization to define the QTP family of functionals. In particular, QTP(02), which has only a single range separation parameter, provides results accurate to a MAD of < 0.15 eV for the whole set of 64 molecules compared to EA-EOM-CCSD, far exceeding the results from the non-QTP family of density functionals. [ABSTRACT FROM AUTHOR]

Kohn–Sham density functional theory has been the most popular method in electronic structure calculations. To fulfill the increasing accuracy requirements, new approximate functionals are needed to address key issues in existing approximations. It is well known that nonlocal components are crucial. Current nonlocal functionals mostly require orbital dependence such as in Hartree–Fock exchange and many-body perturbation correlation energy, which, however, leads to higher computational costs. Deviating from this pathway, we describe functional nonlocality in a new approach. By partitioning the total density to atom-centered local densities, a many-body expansion is proposed. This many-body expansion can be truncated at one-body contributions, if a base functional is used and an energy correction is approximated. The contribution from each atom-centered local density is a single finite-range nonlocal functional that is universal for all atoms. We then use machine learning to develop this universal atom-centered functional. Parameters in this functional are determined by fitting to data that are produced by high-level theories. Extensive tests on several different test sets, which include reaction energies, reaction barrier heights, and non-covalent interaction energies, show that the new functional, with only the density as the basic variable, can produce results comparable to the best-performing double-hybrid functionals, (for example, for the thermochemistry test set selected from the GMTKN55 database, BLYP based machine learning functional gives a weighted total mean absolute deviations of 3.33 kcal/mol, while DSD-BLYP-D3(BJ) gives 3.28 kcal/mol) with a lower computational cost. This opens a new pathway to nonlocal functional development and applications. [ABSTRACT FROM AUTHOR]

π-conjugated polymers have been used in a wide range of practical applications, partly due to their unique properties that originate in the delocalization of electrons through the polymer backbone. The level of delocalization can be characterized by the induced bond length alternation (BLA), with shorter BLA connected with strong delocalization and vice versa. The accurate description of this structural parameter can be considered a benchmark for testing the capability of different electronic structure methods for self-interaction error (SIE) removal and electron correlation inclusion. Density functional theory (DFT), in its local or semi-local flavors, suffers from SIE and, thus, underestimates the BLA compared to self-interaction-free methods. In this work, we utilize the Fermi–Löwdin orbital self-interaction correction (FLOSIC) method for one-electron self-interaction removal to characterize the BLA of five oligomers with increasing length extrapolated to the polymeric limit. We compare the self-interaction-free BLA to several DFT approximations, Møller–Plesset second-order perturbation theory (MP2), and the BLA obtained with the domain based local pair natural orbital CCSD(T) [DLPNO-CCSD(T)] approximation. Our findings show that FLOSIC corrects for the small BLA given by (semi-)local DFT approximations, but it tends to overcorrect with respect to CAM-B3LYP, MP2, and DLPNO-CCSD(T). [ABSTRACT FROM AUTHOR]

Because of an acquired obsession to understand as much as possible in a limited but important area of science and because of optimism, luck, and help from others, my life in science turned out to be much better than I or others could have expected or planned. This is the story of how that happened, and also the story of the groundstate density functional theory of electronic structure, told from a personal perspective. [ABSTRACT FROM AUTHOR]

An extension of a first-principle combined Monte Carlo method is proposed in this work to obtain the secondary electron emission characteristics of anisotropic crystal Al2O3. Unlike isotropic crystal Cu, density functional theory calculations reveal that the q-dependent energy loss function of Al2O3 in all directions is different. Therefore, an interpolation algorithm is introduced in the Monte Carlo method to determine the loss of energy and inelastic mean free path of electrons. The simulation results are in good agreement with experimental data. This method can be further used to simulate the secondary emission yield of other anisotropic crystal materials. [ABSTRACT FROM AUTHOR]

An extension of a first-principle combined Monte Carlo method is proposed in this work to obtain the secondary electron emission characteristics of anisotropic crystal Al2O3. Unlike isotropic crystal Cu, density functional theory calculations reveal that the q-dependent energy loss function of Al2O3 in all directions is different. Therefore, an interpolation algorithm is introduced in the Monte Carlo method to determine the loss of energy and inelastic mean free path of electrons. The simulation results are in good agreement with experimental data. This method can be further used to simulate the secondary emission yield of other anisotropic crystal materials. [ABSTRACT FROM AUTHOR]

In the context of condensed matter physics, the Sommerfeld parameter describes the enhancement or suppression of free-carrier charge density in the vicinity of a charged center. The Sommerfeld parameter is known for three-dimensional systems and is integral to the description of trap-assisted recombination in solids. Here we derive the Sommerfeld parameter in one and two dimensions and compare with the results in three dimensions. We provide an approximate analytical expression for the Sommerfeld parameter in two dimensions. Our results indicate that the effect of the Sommerfeld parameter is to suppress trap-assisted recombination in decreased dimensionality.

Nuclear magnetic resonance (NMR) spectroscopy is an important analytical technique in synthetic organic chemistry, but its integration into high-throughput experimentation workflows has been limited by the necessity of manually analyzing the NMR spectra of new chemical entities. Current efforts to automate the analysis of NMR spectra rely on comparisons to databases of reported spectra for known compounds and, therefore, are incompatible with the exploration of new chemical space. By reframing the NMR spectrum of a reaction mixture as a joint probability distribution, we have used Hamiltonian Monte Carlo Markov Chain and density functional theory to fit the predicted NMR spectra to those of crude reaction mixtures. This approach enables the deconvolution and analysis of the spectra of mixtures of compounds without relying on reported spectra. The utility of our approach to analyze crude reaction mixtures is demonstrated with the experimental spectra of reactions that generate a mixture of isomers, such as Wittig olefination and C-H functionalization reactions. The correct identification of compounds in a reaction mixture and their relative concentrations is achieved with a mean absolute error as low as 1%.

Gold nanoclusters have attracted significant attention due to their unique physical-chemical properties, which can be tuned by alloying with elements such as Cu, Pd, Ag, and Pt to design materials for various applications. Although Au-nanoalloys have promising applications, our atomistic understanding of the descriptors that drive their stability is far from satisfactory. To address this problem, we considered 55-atom model nanoalloys that have been synthesized by experimental techniques. Here, we combined data mining techniques for creating a large sample of representative configurations, density functional theory for performing total energy optimizations, and Spearman correlation analyses to identify the most important descriptors. Among our results, we have identified trends in core–shell formation in the AuCu and AuPd systems and an onion-like design in the AuAg system, characterized by the aggregation of gold atoms on nanocluster surfaces. These features are explained by Au's surface energy, packing efficiency, and charge transfer mechanisms, which are enhanced by the alloys' preference for adopting the structure of the alloying metal rather than the low-symmetry one presented by Au55. These generalizations provide insights into the interplay between electronic and structural properties in gold nanoalloys, contributing to the understanding of their stabilization mechanisms and potential applications in various fields. [ABSTRACT FROM AUTHOR]

Kohn–Sham density functional theory (DFT) typically works well for describing dynamic correlation. Two other types of correlation, arising in the cases of degenerate (static) or quasidegenerate (nondynamic) zero-order states, represent a difficult problem for DFT. When symmetry is present, multiplet sum method (MSM) DFT [Ziegler et al., Theor. Chim. Acta 4, 877 (1977)] provides one of the earliest and simplest ways to include static correlation in DFT. MSM-DFT assumes that DFT provides a good description of single-determinant energies and uses symmetry and simple ansätze to include the effects of static correlation. This is equivalent to determining the off-diagonal matrix elements in a small configuration interaction (CI) eigenvalue problem. Our ultimate goal, however, is nondynamic correlation in cases where symmetry is inadequate for fixing the dynamic-correlation limitation of DFT. To this end, we have developed a diagrammatic approach to MSM-DFT, which does not, by itself, solve the nondynamic correlation problem in DFT but which facilitates comparison with wave function CI and so allows educated guesses of off-diagonal CI matrix elements even in the absence of symmetry. In every case, an additional exchange-only ansatz (EXAN) allows the MSM-DFT formulas to be transformed into wave function formulas. This EXAN also works for transforming time-dependent DFT into time-dependent Hartree–Fock. Although not enough to uniquely guess DFT formulas from wave function formulas, the diagrammatic approach and the EXAN provide important constraints on any guesses that might be used. We illustrate how diagrammatic MSM-DFT may be used to guess a nondynamic correlation correction for the dissociation of H2 and how diagrammatic MSM-DFT may be used to guess a nonsymmetry-based coupling element in the O2 multiplet problem, which is reasonably close to a previous symmetry-derived result. [ABSTRACT FROM AUTHOR]

One of the well-known limitations of Kohn–Sham density functional theory is the tendency to strongly underestimate bandgaps. Meta-generalized gradient approximations (mGGAs), which include the kinetic energy density in the functional form, have been shown to significantly alleviate this deficiency. In this study, we explore the mechanisms responsible for this improvement from the angle of the underlying local densities. We find that the highest occupied and lowest unoccupied states are distinct in the space of the underlying descriptors. The gap opening is compared to a simple scaling of the local density approximation, and two mechanisms responsible for opening the mGGA gaps are identified. First of all, the relatively large negative derivative of the functional form with respect to reduced kinetic energy tends to elevate the lowest unoccupied state. Second, the curvature of functional, which ensures that it is bounded, tends to lower the highest occupied state. Remarkably, these two mechanisms are found to be transferable over a large and diverse database of compounds. [ABSTRACT FROM AUTHOR]

A new non-empirical ab initio intermolecular force field (NICE-FF in buffered 14-7 potential form) has been developed for nucleic acids and beyond based on the dimer interaction energies (IEs) calculated at the spin component scaled-MI-second order Møller–Plesset perturbation theory. A fully automatic framework has been implemented for this purpose, capable of generating well-polished computational grids, performing the necessary ab initio calculations, conducting machine learning (ML) assisted force field (FF) parametrization, and extending existing FF parameters by incorporating new atom types. For the ML-assisted parametrization of NICE-FF, interaction energies of ∼18 000 dimer geometries (with IE < 0) were used, and the best fit gave a mean square deviation of about 0.46 kcal/mol. During this parametrization, atom types apparent in four deoxyribonucleic acid (DNA) bases have been first trained using the generated DNA base datasets. Both uracil and hypoxanthine, which contain the same atom types found in DNA bases, have been considered as test molecules. Three new atom types have been added to the DNA atom types by using IE datasets of both pyrazinamide and 9-methylhypoxanthine. Finally, the last test molecule, theophylline, has been selected, which contains already-fitted atom-type parameters. The performance of NICE-FF has been investigated on the S22 dataset, and it has been found that NICE-FF outperforms the well-known FFs by generating the most consistent IEs with the high-level ab initio ones. Moreover, NICE-FF has been integrated into our in-house developed crystal structure prediction (CSP) tool [called FFCASP (Fast and Flexible CrystAl Structure Predictor)], aiming to find the experimental crystal structures of all considered molecules. CSPs, which were performed up to 4 formula units (Z), resulted in NICE-FF being able to locate almost all the known experimental crystal structures with sufficiently low RMSD20 values to provide good starting points for density functional theory optimizations. [ABSTRACT FROM AUTHOR]

Pseudopotentials (PP) are extensively used in electronic structure calculations, particularly for molecules containing heavy elements. Parameters in PPs are mainly determined from ab initio results, and errors of such PPs in density functional theory (DFT) calculations have been studied previously. However, PP errors on results with spin–orbit coupling and those in time-dependent DFT (TDDFT) calculations have not been reported previously. In this work, we investigate the error of the small-core energy-consistent Stuttgart/Koln pseudopotentials in DFT and TDDFT calculations with and without spin–orbit coupling. Ground state bond lengths, harmonic frequencies, dissociation energies, and vertical excitation energies for a series of closed-shell diatomic heavy and superheavy p-block molecules are calculated using several popular exchange-correlation functionals. PP errors are estimated by comparing with results using the all-electron Dirac–Coulomb (-Gaunt) Hamiltonian. Our results show that the difference between ground state properties and most excitation energies in scalar-relativistic calculations with the PP and those of all-electron calculations is quite small. This difference becomes somewhat larger when spin–orbit coupling (SOC) is present, especially for properties that are affected by SOC to some extent. In addition, the errors of the PPs are insensitive to the employed exchange-correlation functionals in most cases. Our results indicate that reasonable DFT and TDDFT results can be obtained using the small-core energy-consistent Stuttgart/Koln pseudopotentials for heavy and super-heavy p-block molecules. [ABSTRACT FROM AUTHOR]

We present a Δ-machine learning model for obtaining Kohn–Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine-learned force field (MLFF) scheme based on the kernel method to capture the difference between Kohn–Sham and orbital-free DFT energies/forces. We implement this model in the context of on-the-fly molecular dynamics simulations and study its accuracy, performance, and sensitivity to parameters for representative systems. We find that the formalism not only improves the accuracy of Thomas–Fermi–von Weizsäcker orbital-free energies and forces by more than two orders of magnitude but is also more accurate than MLFFs based solely on Kohn–Sham DFT while being more efficient and less sensitive to model parameters. We apply the framework to study the structure of molten Al0.88Si0.12, the results suggesting no aggregation of Si atoms, in agreement with a previous Kohn–Sham study performed at an order of magnitude smaller length and time scales. [ABSTRACT FROM AUTHOR]

We have developed and implemented an implicit electrolyte model in the Vienna Ab initio Simulation Package (VASP) that includes nonlinear dielectric and ionic responses as well as a nonlocal definition of the cavities defining the spatial regions where these responses can occur. The implementation into the existing VASPsol code is numerically efficient and exhibits robust convergence, requiring computational effort only slightly higher than the original linear polarizable continuum model. The nonlinear + nonlocal model is able to reproduce the characteristic "double hump" shape observed experimentally for the differential capacitance of an electrified metal interface while preventing "leakage" of the electrolyte into regions of space too small to contain a single water molecule or solvated ion. The model also gives a reasonable prediction of molecular solvation free energies as well as the self-ionization free energy of water and the absolute electron chemical potential of the standard hydrogen electrode. All of this, combined with the additional ability to run constant potential density functional theory calculations, should enable the routine computation of activation barriers for electrocatalytic processes. [ABSTRACT FROM AUTHOR]

Spontaneous emission and internal conversion rates are calculated within harmonic approximations and compared to the results obtained within the semi-classical extended thawed Gaussian approximation (ETGA). This is the first application of the ETGA in the calculation of internal conversion and emission rates for real molecular systems, namely, formaldehyde, fluorobenzene, azulene, and a dicyano-squaraine dye. The viability of the models as black-box tools for prediction of spontaneous emission and internal conversion rates is assessed. All calculations were done using a consistent protocol in order to investigate how different methods perform without previous experimental knowledge using density functional theory (DFT) and time-dependent DFT (TD-DFT) with B3LYP, PBE0, ωB97XD, and CAM-B3LYP functionals. Contrasting the results with experimental data shows that there are further improvements required before theoretical predictions of emission and internal conversion rates can be used as reliable indicators for the photo-luminescence properties of molecules. We find that the ETGA performs rather similar to the vertical harmonical model. Including anharmonicities in the calculation of internal conversion rates has a moderate effect on the quantitative results in the studied systems. The emission rates are fairly stable with respect to computational parameters, but the internal conversion rate reveals itself to be highly dependent on the choice of the spectral line shape function, particularly the width of the Lorentzian function, associated with homogeneous broadening. [ABSTRACT FROM AUTHOR]

Machine learning (ML) of kinetic energy functionals (KEFs), in particular kinetic energy density (KED) functionals, is a promising way to construct KEFs for orbital-free density functional theory (DFT). Neural networks and kernel methods including Gaussian process regression (GPR) have been used to learn Kohn–Sham (KS) KED from density-based descriptors derived from KS DFT calculations. The descriptors are typically expressed as functions of different powers and derivatives of the electron density. This can generate large and extremely unevenly distributed datasets, which complicates effective application of ML techniques. Very uneven data distributions require many training datapoints, can cause overfitting, and can ultimately lower the quality of an ML KED model. We show that one can produce more accurate ML models from fewer data by working with smoothed density-dependent variables and KED. Smoothing palliates the issue of very uneven data distributions and associated difficulties of sampling while retaining enough spatial structure necessary for working within the paradigm of KEDF. We use GPR as a function of smoothed terms of the fourth order gradient expansion and KS effective potential and obtain accurate and stable (with respect to different random choices of training points) kinetic energy models for Al, Mg, and Si simultaneously from as few as 2000 samples (about 0.3% of the total KS DFT data). In particular, accuracies on the order of 1% in a measure of the quality of energy–volume dependence B ′ = E V 0 − Δ V − 2 E V 0 + E ( V 0 + Δ V) Δ V / V 0 2 (where V0 is the equilibrium volume and ΔV is a deviation from it) are obtained simultaneously for all three materials. [ABSTRACT FROM AUTHOR]

We review the concept of ultranonlocality in density functional theory and the relation between ultranonlocality, the derivative discontinuity of the exchange energy, and the static electric response in extended molecular systems. We present the construction of a new meta-generalized gradient approximation for exchange that captures the ultranonlocal response to a static electric field in very close correspondence to exact exchange, yet at a fraction of its computational cost. This functional, in particular, also captures the dependence of the response on the system size. The static electric polarizabilities of hydrogen chains and oligo-acetylene molecules calculated with this meta-GGA are quantitatively close to the ones obtained with exact exchange. The chances and challenges associated with the construction of meta-GGAs that are intended to combine a substantial derivative discontinuity and ultranonlocality with an accurate description of electronic binding are discussed. [ABSTRACT FROM AUTHOR]

TurboGenius is an open-source Python package designed to fully control ab initio quantum Monte Carlo (QMC) jobs using a Python script, which allows one to perform high-throughput calculations combined with TurboRVB [Nakano et al. J. Phys. Chem. 152, 204121 (2020)]. This paper provides an overview of the TurboGenius package and showcases several results obtained in a high-throughput mode. For the purpose of performing high-throughput calculations with TurboGenius, we implemented another open-source Python package, TurboWorkflows, that enables one to construct simple workflows using TurboGenius. We demonstrate its effectiveness by performing (1) validations of density functional theory (DFT) and QMC drivers as implemented in the TurboRVB package and (2) benchmarks of Diffusion Monte Carlo (DMC) calculations for several datasets. For (1), we checked inter-package consistencies between TurboRVB and other established quantum chemistry packages. By doing so, we confirmed that DFT energies obtained by PySCF are consistent with those obtained by TurboRVB within the local density approximation (LDA) and that Hartree–Fock (HF) energies obtained by PySCF and Quantum Package are consistent with variational Monte Carlo energies obtained by TurboRVB with the HF wavefunctions. These validation tests constitute a further reliability check of the TurboRVB package. For (2), we benchmarked the atomization energies of the Gaussian-2 set, the binding energies of the S22, A24, and SCAI sets, and the equilibrium lattice parameters of 12 cubic crystals using DMC calculations. We found that, for all compounds analyzed here, the DMC calculations with the LDA nodal surface give satisfactory results, i.e., consistent either with high-level computational or with experimental reference values. [ABSTRACT FROM AUTHOR]

In this work, we revisit the dynamics of carbon monoxide molecular chemisorption on Cu(110) by using quasi-classical trajectory calculations. The molecule–surface interaction is described through an atomistic neural network approach based on Density Functional Theory calculations using a nonlocal exchange–correlation (XC) functional that includes the effect of long-range dispersion forces: vdW-DF2 [Lee et al. Phys. Rev. B, 82, 081101 (2010)]. With this approach, we significantly improve the agreement with experiments with respect to a similar previous study based on a semi-local XC functional. In particular, we obtain excellent agreement with molecular beam experimental data concerning the dependence of the initial sticking probability on surface temperature and impact energy at normal incidence. For off-normal incidence, our results also reproduce two trends observed experimentally: (i) the preferential sticking for molecules impinging parallel to the [ 1 ̄ 10] direction compared to [001] and (ii) the change from positive to negative scaling as the impact energy increases. Nevertheless, understanding the origin of some remaining quantitative discrepancies with experiments requires further investigations. [ABSTRACT FROM AUTHOR]

Theoretical prediction of interfacial capacitance in graphene-based supercapacitors is crucial to accelerating materials' design and development cycles. However, there is currently a significant gap between ab initio predictions and experimental reports, particularly in the case of nitrogen-doped graphene. Analyses based on changes to the density of states of freestanding graphene upon doping do not account for the electronic interactions between the electrode, dopants, and substrates. The result is an overestimation of the doping-induced capacitance increase by up to two orders of magnitude. Moreover, it is unclear whether electrolyte and solvent interactions can further complicate matters by inducing changes to the band structure and, therefore, the capacitive properties of the electrode. A third complication lies in the fixed-band approximation, where materials are simulated without accounting for the influence of an external electrical field. In this work, we present an interfacial modeling and characterization procedure that leverages the combined strengths of ab-initio molecular dynamics, density functional theory, and microscopic polarization theory to produce reliable predictions of interfacial capacitance. The procedure is applied to two case studies of interest in supercapacitor design: (1) nitrogen-doped graphene on a Cu(111) substrate and (2) an interface between bulk water and Cu(111)-supported graphene at room temperature. Results show that water alters graphene's band structure from a semi-metallic to an n-doped-semiconducting character and that metallic substrates dominate the band structure of the electrode interface even in the presence of dopants. The water interface also shows an asymmetric capacitive response relative to the polarity of the applied field. [ABSTRACT FROM AUTHOR]

The present study explores the hydrogen-bond network in an equimolar mixture of acetic acid and water (AA–W). The investigation was conducted using a combination of neutron scattering and Density Functional Theory (DFT). New neutron scattering data at large scattering wave vectors were analyzed to determine the total structure factor SM(q) and the molecular form factor F1(q) of the system. DFT calculations using the 6-311++G(d, p) basis set were performed to optimize the monomers and various AA–W H-bonded clusters, including one acetic acid (AA) molecule connected to one, two, and three water molecules. Consequently, three dimers, three trimers, and one tetramer have been considered in order to describe the local order in the mixture. In addition, this study focused on the H-bond interactions in the most probable clusters in the solution, using the natural bond orbital and the atoms in molecules analyses. Our analysis particularly shows that stronger H-bond interactions occur in the ring structures. [ABSTRACT FROM AUTHOR]

Nanoscale magnesium clusters are important potential hydrogen storage materials, and density functional theory (DFT) is mainly used for their theoretical investigation. The results of the coupled-cluster theory at the singles and doubles level with a perturbative treatment of triples [CCSD(T)] were employed previously to choose proper exchange–correlation (XC) functionals in DFT calculations for magnesium clusters, but it is too expensive to be applied to Mgn with n > 7. The diffusion Monte Carlo (DMC) method is employed in this work to study magnesium clusters up to nanosize. The error of atomization energies with DMC using single-determinant-Jastrow (SDJ) trial wavefunctions has been shown to be somewhat larger than that of CCSD(T) for many molecules. However, cohesive energies with DMC using SDJ for Mgn with n ≤ 7 are in excellent agreement with those of CCSD(T) using the aug-cc-pVQZ basis set, with a difference of less than 1 kcal/mol. DMC results are employed to investigate the performance of different XC functionals on magnesium clusters. Our results indicate that the PBE0 functional is the best XC functional for determining the lowest-energy isomer when compared with DMC results, while the RPBE functional is the best XC functional for calculating cohesive energies per atom of these magnesium clusters with a mean absolute error of 0.5 kcal/mol. These XC functionals are expected to provide reasonable results for even larger magnesium clusters. [ABSTRACT FROM AUTHOR]

Standard approximations for the exchange–correlation functional in Kohn–Sham density functional theory (KS-DFT) typically lead to unacceptably large errors when applied to strongly correlated electronic systems. Partition-DFT (PDFT) is a formally exact reformulation of KS-DFT in which the ground-state density and energy of a system are obtained through self-consistent calculations on isolated fragments, with a partition energy representing inter-fragment interactions. Here, we show how typical errors of the local density approximation (LDA) in KS-DFT can be largely suppressed through a simple approximation, the multi-fragment overlap approximation (MFOA), for the partition energy in PDFT. Our method is illustrated on simple models of one-dimensional strongly correlated linear hydrogen chains. The MFOA, when used in combination with the LDA for the fragments, improves LDA dissociation curves of hydrogen chains and produces results that are comparable to those of spin-unrestricted LDA, but without breaking the spin symmetry. MFOA also induces a correction to the LDA electron density that partially captures the correct density dimerization in strongly correlated hydrogen chains. Moreover, with an additional correction to the partition energy that is specific to the one-dimensional LDA, the approximation is shown to produce dissociation energies in quantitative agreement with calculations based on the density matrix renormalization group method. [ABSTRACT FROM AUTHOR]

Conventional theories of weak polyelectrolytes are either computationally prohibitive to account for the multidimensional inhomogeneity of polymer ionization in a liquid environment or oversimplistic in describing the coupling effects of ion-explicit electrostatic interactions and long-range intrachain correlations. To bridge this gap, we implement the Ising density functional theory (iDFT) for ionizable polymer systems using the single-chain-in-mean-field algorithm. The single-chain-in-iDFT (sc-iDFT) shows significant improvements over conventional mean-field methods in describing segment-level dissociation equilibrium, specific ion effects, and long-range intrachain correlations. With an explicit consideration of the fluctuations of polymer configurations and the position-dependent ionization of individual polymer segments, sc-iDFT provides a faithful description of the structure and thermodynamic properties of inhomogeneous weak polyelectrolyte systems across multiple length scales. [ABSTRACT FROM AUTHOR]

Recent experiments related to a study concerning the adsorption of water on graphene have demonstrated the p-doping of graphene, although most of the ab initio calculations predict nearly zero doping. To shed more light on this problem, we have carried out van der Waals density functional theory calculations of water on graphene for both individual water molecules and continuous water layers with coverage ranging from one to eight monolayers. Furthermore, we have paid attention to the influence of the water molecule orientation toward graphene on its doping properties. In this article, we present the results of the band structure and the Bader charge analysis, showing the p-doping of graphene can be synergistically enhanced by putting 4–8 layers of an ice–like water structure on graphene having the water molecules oriented with oxygen atoms toward graphene. [ABSTRACT FROM AUTHOR]