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The field of two-dimensional (2D) materials has grown dramatically in the last two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computation applications. These 2D structures, which are often exfoliated from layered van der Waals (vdW) materials, possess highly inhomogeneous electron densities and can possess short- and long-range electron correlations. The complexities of 2D materials make them challenging to study with standard mean-field electronic structure methods such as density functional theory (DFT), which relies on approximations for the unknown exchange-correlation functional. In order to overcome the limitations of DFT, highly accurate many-body electronic structure approaches such as Diffusion Monte Carlo (DMC) can be utilized. In the past decade, DMC has been used to calculate accurate magnetic, electronic, excitonic, and topological properties in addition to accurately capturing interlayer interactions and cohesion and adsorption energetics of 2D materials. This approach has been applied to 2D systems of wide interest including graphene, phosphorene, MoS$_2$, CrI$_3$, VSe$_2$, GaSe, GeSe, borophene, and several others. In this review article, we highlight some successful recent applications of DMC to 2D systems for improved property predictions beyond standard DFT.

Stochastic electronic structure theories, e.g., Quantum Monte Carlo methods, enable highly accurate total energy calculations which in principle can be used to construct highly accurate potential energy surfaces. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged-elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method - previously developed for QMC structural optimization - to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and on saddle points, we show that it is possible to identify MEPs and TSs using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia molecule and an SN2 reaction. We validate our results using Density Functional Theory- and coupled cluster-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities - free energy differences, rate constants, and equilibrium constants - that incorporates stochastically-optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations, at significantly reduced computational expense.

We provide an overview of the software engineering efforts and their impact in QMCPACK, a production-level ab-initio Quantum Monte Carlo open-source code targeting high-performance computing (HPC) systems. Aspects included are: (i) strategic expansion of continuous integration (CI) targeting CPUs, using GitHub Actions runners, and NVIDIA and AMD GPUs in pre-exascale systems, using self-hosted hardware; (ii) incremental reduction of memory leaks using sanitizers, (iii) incorporation of Docker containers for CI and reproducibility, and (iv) refactoring efforts to improve maintainability, testing coverage, and memory lifetime management. We quantify the value of these improvements by providing metrics to illustrate the shift towards a predictive, rather than reactive, sustainable maintenance approach. Our goal, in documenting the impact of these efforts on QMCPACK, is to contribute to the body of knowledge on the importance of research software engineering (RSE) for the sustainability of community HPC codes and scientific discovery at scale., Comment: Accepted at the first US-RSE Conference, USRSE2023, https://us-rse.org/usrse23/, 8 pages, 3 figures, 4 tables

Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard

As the only semimetallic $d^{10}$-based delafossite, AgNiO$_2$ has received a great deal of attention due to both its unique semimetallicity and its antiferromagnetism in the NiO$_2$ layer that is coupled with a lattice distortion. In contrast, other delafossites such as AgCoO$_2$ are insulating. Here we study how the electronic structure of AgNi$_{1-x}$Co$_{x}$O$_2$ alloys vary with Ni/Co concentration, in order to investigate the electronic properties and phase stability of the intermetallics. While the electronic and magnetic structure of delafossites have been studied using Density Functional Theory (DFT), earlier studies have not included corrections for strong on-site Coulomb interactions. In order to treat these interactions accurately, in this study we use Quantum Monte Carlo (QMC) simulations to obtain accurate estimates for the electronic and magnetic properties of AgNiO$_2$. By comparison to DFT results we show that these electron correlations are critical to account for. We show that Co doping on the magnetic Ni sites results in a metal-insulator transition near $x\sim 0.33$, and reentrant behavior near $x\sim 0.66$, Comment: 25 Pages, 12 figures

Hybrid materials of MXenes (2D carbides and nitrides) and transition-metal oxides (TMOs) have shown great promise in electrical energy storage and 2D heterostructures have been proposed as the next-generation electrode materials to expand the limits of current technology. Here we use first principles density functional theory to investigate the interfacial structure, energetics, and electronic properties of the heterostructures of MXenes (Tin+1CnT2; T=terminal groups) and anatase TiO2. We find that the greatest work-function differences are between OH-terminated-MXene (1.6 eV) and anatase TiO2(101) (6.4 eV), resulting in the largest interfacial electron transfer (~0.9 e/nm2 across the interface) from MXene to the TiO2 layer. This interface also has the strongest adhesion and further strengthened by hydrogen bond formation. For O-, F-, or mixed O-/F- terminated Tin+1Cn MXenes, electron transfer is minimal and interfacial adhesion is weak for their heterostructures with TiO2. The strong dependence of the interfacial properties of the MXene/TiO2 heterostructures on the surface chemistry of the MXenes will be useful to tune the heterostructures for electric-energy-storage applications., Comment: 13 pages, 5 figures

The mechanisms that drive metal-to-insulator transitions (MIT) in correlated solids are not fully understood. For example, the perovskite (PV) SrCoO3 is a FM metal while the oxygen-deficient (n-doped) brownmillerite (BM) SrCoO2.5 is an anti-ferromagnetic (AFM) insulator. Given the magnetic and structural transitions that accompany the MIT, the driver for such a MIT transition is unclear. We also observe that the perovskite metals LaNiO3, SrFeO3, and SrCoO3 also undergo MIT when n-doped via high-to-low valence compositional changes. Also, pressurizing the insulating BM SrCoO2.5 phase, drives a gap closing. Using DFT and correlated diffusion Monte Carlo approaches we demonstrate that the ABO3 perovskites most prone to MIT are self hole-doped materials, reminiscent of a negative charge-transfer system. Upon n-doping away from the negative-charge transfer metallic phase, an underlying charge-lattice (or e-phonon) coupling drives the system to a bond-disproportionated gapped state, thereby achieving ligand hole passivation at certain sites only, leading to charge-disproportionated states. The size of the gap opened is correlated with the size of the hole-filling at these ligand sites. This suggests that the interactions driving the gap opening to realize a MIT even in correlated metals is the charge-transfer energy, but it couples with the underlying phonons to enable the transition to the insulating phase. Other orderings (magnetic, charge, etc.) driven by weaker interactions are secondary and may assist gap openings at small dopings, but its the charge-transfer energy that predominantly determines the bandgap, with a negative energy preferring the metallic phase. This n-doping can be achieved by modulations in stoichiometry or composition or pressure. Hence, controlling the amount of the ligand-hole is key in controlling MIT. We compare our predictions to experiments where possible.

While Diffusion Monte Carlo (DMC) is in principle an exact stochastic method for \textit{ab initio} electronic structure calculations, in practice the fermionic sign problem necessitates the use of the fixed-node approximation and trial wavefunctions with approximate nodes (or zeros) must be used. This approximation introduces a variational error in the energy that potentially can be tested and systematically improved. Here, we present a computational method that produces trial wavefunctions with systematically improvable nodes for DMC calculations of periodic solids. These trial wavefunctions are efficiently generated with the configuration interaction using a perturbative selection made iteratively (CIPSI) method. A simple protocol in which both exact and approximate results for finite supercells are used to extrapolate to the thermodynamic limit is introduced.

The evolution of the electronic structures of strongly correlated insulators with doping has long been a central fundamental question in condensed matter physics; it is also of great practical relevance for applications. We have studied the evolution of NiO under hole {\em and} electron doping using high-quality thin film and a wide range of experimental and theoretical methods. The evolution is in both cases very smooth with dopant concentration. The band gap is asymmetric under electron and hole doping, consistent with a charge-transfer insulator picture, and is reduced faster under hole than electron doping. For both electron and hole doping, occupied states are introduced at the top of the valence band. The formation of deep donor levels under electron doping and the inability to pin otherwise empty states near the conduction band edge is indicative that local electron addition and removal energies are dominated by a Mott-like Hubbard $U$-interaction even though the global bandgap is predominantly a charge-transfer type gap., Comment: Revised version

MXene-based heterostructures have received considerable interest owing to their unique properties. Herein, we examine various heterostructures of a prototypical MXene and graphene using density functional theory. We find that the adhesion energy, charge transfer, and band structure of these heterostructures are sensitive not only to the surface functional group, but also to the stacking order. Difference in work function dictates the direction and amount of electron transfer across the interface, which causes a shift in the Dirac point of the graphene bands in the heterostructures of monolayer graphene and monolayer MXene. In the heterostructures of bilayer graphene and monolayer MXene, the interface breaks the symmetry of the bilayer graphene; in the case of the AB-stacking bilayer, the electron transfer leads to an interfacial electric field that opens up a gap in the graphene bands at the K point. This internal polarization strengthens both the interfacial adhesions and the cohesion between the two graphene layers. The MXene-graphene-MXene and graphene-MXene-graphene sandwich structures behave as two mirror-symmetric MXene-graphene interfaces. Our first principles studies provide a comprehensive understanding for the interaction between a typical MXene and graphene., Comment: 17 pages, 7 figures

Rutile ($R$) phase VO$_2$ is a quintessential example of a strongly correlated bad-metal, which undergoes a metal-insulator transition (MIT) concomitant with a structural transition to a V-V dimerized monoclinic phase below T$_{MIT} \sim 340K$. It has been experimentally shown that one can control this transition by doping VO$_2$. In particular, doping with oxygen vacancies ($V_O$) has been shown to completely suppress this MIT {\em without} any structural transition. We explain this suppression by elucidating the influence of oxygen-vacancies on the electronic-structure of the metallic $R$ phase VO$_2$, explicitly treating strong electron-electron correlations using dynamical mean-field theory (DMFT) as well as diffusion Monte Carlo (DMC) flavor of quantum Monte Carlo (QMC) techniques. We show that $V_O$'s tend to change the V-3$d$ filling away from its nominal half-filled value, with the $e_{g}^{\pi}$ orbitals competing with the otherwise dominant $a_{1g}$ orbital. Loss of this near orbital polarization of the $a_{1g}$ orbital is associated with a weakening of electron correlations, especially along the V-V dimerization direction. This removes a charge-density wave (CDW) instability along this direction above a critical doping concentration, which further suppresses the metal-insulator transition. Our study also suggests that the MIT is predominantly driven by a correlation-induced CDW instability along the V-V dimerization direction.

Two-dimensional charge carrier accumulation at oxide heterointerfaces presents a paradigm shift for oxide electronics. Like a capacitor, interfacial charge buildup couples to an electric field across the dielectric medium. To prevent the so-called polar catastrophe, several charge screening mechanisms emerge, including polar distortions and interfacial intermixing which reduce the sharpness of the interface. Here, we examine how atomic intermixing at oxide interfaces affect the balance between polar distortions and electric potential across the dielectric medium. We find that intermixing moves the peak charge distribution away from the oxide/oxide interface; thereby changing the direction of polar distortions away from this boundary with minimal effect on the electric field. This opposing electric field and polar distortions is equivalent to the transient phase transition tipping point observed in double well ferroelectrics; resulting in an anomalous dielectric response -- a possible signature of local negative differential capacitance, with implications for designing dissipationless oxide electronics.

The defect stability in a prototypical perovskite oxide superlattice consisting of SrTiO$_3$ and PbTiO$_3$ (STO/PTO) is determined using first principles density functional theory calculations. Specifically, the oxygen vacancy formation energies E$_v$ in the paraelectric and ferroelectric phases of a superlattice with four atomic layers of STO and four layers of PTO (4STO/4PTO) are determined and compared. The effects of charge state, octahedral rotation, polarization, and interfaces on the E$_v$ are examined. The formation energies vary layer-by-layer in the superlattices, with E$_v$ being higher in the ferroelectric phase than that in the paraelectric phase. The two interfaces constructed in these oxide superlattices, which are symmetrically equivalent in the paraelectric systems, exhibit very different formation energies in the ferroelectric superlattices and this can be seen to be driven by the coupling of ferroelectric and rotational modes. At equivalent lattice sites, E$_v$ of charged vacancies is generally lower than that of neutral vacancies. Octahedral rotations (a$^0$a$^0$c$^-$) in the FE superlattice have a significant effect on the E$_v$, increasing the formation energy of vacancies located near the interface but decreasing the formation energy of the oxygen vacancies located in the bulk-like regions of the STO and PTO constituent parts. The formation energy variations among different layers are found to be primarily caused by the difference in the local relaxation at each layer. These fundamental insights into the defect stability in perovskite superlattices can be used to tune defect properties via controlling the constituent materials of superlattices and interface engineering., Comment: 20 pages, 5 figures, accepted at Physical Review Materials

The scale and complexity of quantum system to which real-space quantum Monte Carlo (QMC) can be applied in part depends on the representation and memory usage of the trial wavefunction. B-splines, the computationally most efficient basis set, can have memory requirements exceeding the capacity of a single computational node. This situation has traditionally forced a difficult choice of either using slow internode communication or a potentially less accurate but smaller basis set such as Gaussians. Here, we introduce a hybrid representation of the single particle orbitals that combine a localized atomic basis set around atomic cores and B-splines in the interstitial regions to reduce the memory usage while retaining high speed of evaluation and either retaining or increasing overall accuracy. We present a benchmark calculation for NiO demonstrating a superior accuracy while using only one eighth the memory required for conventional B-splines. The hybrid orbital representation therefore expands the overall range of systems that can be practically studied with QMC.

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program's capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org .

The equations of state, formation energy and migration energy barrier of the oxygen vacancy in SrFeO${_3}$ and LaFeO${_3}$ were calculated with the diffusion quantum Monte Carlo (DMC) method. Calculations were also performed with various Density Functional Theory (DFT) approximations for comparison. DMC reproduces the measured cohesive energies of these materials with errors below 0.23(5) eV and the structural properties within 1% of the experimental values. The DMC formation energies of the oxygen vacancy in SrFeO${_3}$ and LaFeO${_3}$ under oxygen-rich conditions are 1.3(1) and 6.24(7) eV, respectively. Similar calculations with semi-local DFT approximations for LaFeO$_3$ yielded vacancy formation energies 1.5 eV lower. Comparison of charge density evaluated with DMC and DFT approximations shows that DFT tends to overdelocalize the electrons in defected SrFeO${_3}$ and LaFeO${_3}$. Calculations with DMC and LDA yield similar vacancy migration energy barriers, indicating that steric/electrostatic effects mainly determine migration barriers in these materials., Comment: 25 pages, 4 figures

Growth in computational resources has lead to the application of real space diffusion quantum Monte Carlo (DMC) to increasingly heavy elements. Although generally assumed to be small, we find that when using standard techniques the pseudopotential localization error can be large, on the order of an electron volt for an isolated cerium atom. We formally show that localization error can be reduced to zero with improvements to the Jastrow factor alone and we define a metric of Jastrow sensitivity that may be useful in the design of pseudopotentials. We employ an extrapolation scheme to extract the bare fixed node energy and estimate the localization error in both the locality approximation and the T-moves schemes for the Ce atom in charge states 3+ and 4+. The locality approximation exhibits the lowest Jastrow sensitivity and generally smaller localization errors than T-moves, although the locality approximation energy approaches the localization free limit from above/below for the 3+/4+ charge state. We find that energy minimized Jastrow factors including three-body electron-electron-ion terms are the most effective at reducing localization error for both the locality approximation and T-moves. Less complex or variance minimized Jastrows are generally less effective. Our results suggest that further improvements to Jastrow factors and trial wavefunction forms will be necessary to reduce localization errors to chemical accuracy in calculations of heavy elements., Comment: 8 pages, 2 figures

We have applied the diffusion quantum Monte Carlo (DMC) method to calculate the cohesive energy and the structural parameters of the binary oxides CaO, SrO, BaO, Sc2O3, Y2O3 and La2O3. The aim of our calculations is to systematically quantify the accuracy of the DMC method to study this type of metal oxides. The DMC results were compared with local, semi-local and hybrid Density Functional Theory (DFT) approximations as well as with experimental measurements. The DMC method yields cohesive energies for these oxides with a mean absolute deviation from experimental measurements of 0.18(2) eV, while with local, semi-local and hybrid DFT approximations the deviation is 3.06, 0.94 and 1.23 eV, respectively. For lattice constants, the mean absolute deviation in DMC, local, semi-local and hybrid DFT approximations, are 0.017(1), 0.07, 0.05 and 0.04 {\AA}, respectively. DMC is highly accurate method, outperforming the DFT approximations in describing the cohesive energies and structural parameters of these binary oxides., Comment: 22 pages, 3 figures

Titanium dioxide, TiO$_2$, has multiple applications in catalysis, energy conversion and memristive devices because of its electronic structure. Most of these applications utilize the naturally existing phases: rutile, anatase and brookite. Despite the simple form of TiO$_2$ and its wide uses, there is long-standing disagreement between theory and experiment on the energetic ordering of these phases that has never been resolved. We present the first analysis of phase stability at zero temperature using the highly accurate many-body fixed node diffusion Quantum Monte Carlo (QMC) method. We also include the effects of temperature by calculating the Helmholtz free energy including both internal energy and vibrational contributions from density functional perturbation theory based quasi harmonic phonon calculations. Our QMC calculations find that anatase is the most stable phase at zero temperature, consistent with many previous mean-field calculations. However, at elevated temperatures, rutile becomes the most stable phase. For all finite temperatures, brookite is always the least stable phase.

Correlating 3D arrangements of atoms and defects with material properties and functionality forms the core of several scientific disciplines. Here, we determined the 3D coordinates of 6,569 iron and 16,627 platinum atoms in a model iron-platinum nanoparticle system to correlate 3D atomic arrangements and chemical order/disorder with material properties at the single-atom level. We identified rich structural variety and chemical order/disorder including 3D atomic composition, grain boundaries, anti-phase boundaries, anti-site point defects and swap defects. We show for the first time that experimentally measured 3D atomic coordinates and chemical species with 22 pm precision can be used as direct input for first-principles calculations of material properties such as atomic magnetic moments and local magnetocrystalline anisotropy. This work not only opens the door to determining 3D atomic arrangements and chemical order/disorder of a wide range of nanostructured materials with high precision, but also will transform our understanding of structure-property relationships at the most fundamental level., Comment: 21 pages, 4 figures

The Magn\'eli phase Ti$_4$O$_7$ is an important transition metal oxide with a wide range of applications because of its interplay between charge, spin, and lattice degrees of freedom. At low temperatures, it has non-trivial magnetic states very close in energy, driven by electronic exchange and correlation interactions. We have examined three low-lying states, one ferromagnetic and two antiferromagnetic, and calculated their energies as well as Ti spin moment distributions using highly accurate Quantum Monte Carlo methods. We compare our results to those obtained from density functional theory-based methods that include approximate corrections for exchange and correlation. Our results confirm the nature of the states and their ordering in energy, as compared with density-functional theory methods. However, the energy differences and spin distributions differ. A detailed analysis suggests that non-local exchange-correlation functionals, in addition to other approximations such as LDA+U to account for correlations, are needed to simultaneously obtain better estimates for spin moments, distributions, energy differences and energy gaps., Comment: Accepter for publication, Physical Chemistry Chemical Physics 2016

We have applied the many-body ab-initio diffusion quantum Monte Carlo (DMC) method to study Zn and ZnO crystals under pressure, and the energetics of the oxygen vacancy, zinc interstitial and hydrogen impurities in ZnO. We show that DMC is an accurate and practical method that can be used to characterize multiple properties of materials that are challenging for density functional theory approximations. DMC agrees with experimental measurements to within 0.3 eV, including the band-gap of ZnO, the ionization potential of O and Zn, and the atomization energy of O$_2$, ZnO dimer, and wurtzite ZnO. DMC predicts the oxygen vacancy as a deep donor with a formation energy of 5.0(2) eV under O-rich conditions and thermodynamic transition levels located between 1.8 and 2.5 eV from the valence band maximum. Our DMC results indicate that the concentration of zinc interstitial and hydrogen impurities in ZnO should be low under n-type, and Zn- and H-rich conditions because these defects have formation energies above 1.4 eV under these conditions. Comparison of DMC and hybrid functionals shows that these DFT approximations can be parameterized to yield a general correct qualitative description of ZnO. However, the formation energy of defects in ZnO evaluated with DMC and hybrid functionals can differ by more than 0.5 eV., Comment: 43 pages, 10 figures

We present a first-principles theoretical study of electric field-and strain-controlled intrinsic half-metallic properties of zigzagged aluminium nitride (AlN) nanoribbons. We show that the half-metallic property of AlN ribbons can undergo a transition into fully-metallic or semiconducting behavior with application of an electric field or uniaxial strain. An external transverse electric field induces a full charge screening that renders the material semiconducting. In contrast, as uniaxial strain varies from compressive to tensile, a spin-resolved selective self-doping increases the half-metallic character of the ribbons. The relevant strain-induced changes in electronic properties arise from band structure modifications at the Fermi level as a consequence of a spin-polarized charge transfer between pi-orbitals of the N and Al edge atoms in a spin-resolved self-doping process. This band structure tunability indicates the possibility ofdesigning magnetic nanoribbons with tunable electronic structure by deriving edge states from elements with sufficiently different localization properties. Finite temperature molecular dynamics reveal a thermally stable half-metallic nanoribbon up to room temperature., Comment: 7 pages, 5 figures

The interaction of interfacial water with graphitic carbon at the atomic scale is studied as a function of the hydrophobicity of epitaxial graphene. High resolution X-ray reflectivity shows that the graphene-water contact angle is controlled by the average graphene thickness, due to the fraction of the film surface expressed as the epitaxial buffer layer whose contact angle (contact angle \theta_c = 73{\deg}) is substantially smaller than that of multilayer graphene (\theta_c = 93{\deg}). Classical and ab initio molecular dynamics simulations show that the reduced contact angle of the buffer layer is due to both its epitaxy with the SiC substrate and the presence of interfacial defects. This insight clarifies the relationship between interfacial water structure and hydrophobicity, in general, and suggests new routes to control interface properties of epitaxial graphene., Comment: 40 Pages, 3 Tables, 8 Figures; Some minor corrections and changes have been made through the publication production process. The manuscript has been published on-line by Physical Review B

We report comprehensive high-accuracy molecular dynamics simulations using the ReaxFF forcefield to explore the structural changes that occur as Au nanowires are elongated, establishing trends as a function of both temperature and nanowire diameter. Our simulations and subsequent quantitative structural analysis reveal that polytetrahedral structures (e.g., icosahedra) form within the "amorphous" neck regions, most prominently for systems with small diameter at high temperature. We demonstrate that the formation of polytetrahedra diminishes the conductance quantization as compared to systems without this structural motif. We demonstrate that use of the ReaxFF forcefield, fitted to high-accuracy first principles calculations of Au, combines the accuracy of quantum calculations with the speed of semi-empirical methods., Comment: 26 pages (double spaced), 5 figures

We study the electronic structure of a spherical jellium in the presence of a central Gaussian impurity. We test how well the resulting inhomogeneity effects beyond spherical jellium are reproduced by several approximations of density functional theory (DFT). Four rungs of Perdew's ladder of DFT functionals, namely local density approximation (LDA), generalized gradient approximation (GGA), meta-GGA and orbital-dependent hybrid functionals are compared against our quantum Monte Carlo (QMC) benchmarks. We identify several distinct transitions in the ground state of the system as the electronic occupation changes between delocalized and localized states. We examine the parameter space of realistic densities ($1 \le r_s\le 5$) and moderate depths of the Gaussian impurity ($Z<7$). The selected 18 electron system (with closed-shell ground state) presents $1d \to 2s$ transitions while the 30 electron system (with open-shell ground state) exhibits $1f \to 2p$ transitions. For the former system, the accuracy for the transitions is clearly improving with increasing sophistication of functionals with meta-GGA and hybrid functionals having only small deviations from QMC. However, for the latter system, we find much larger differences for the underlying transitions between our pool of DFT functionals and QMC. We attribute this failure to treatment of the exact exchange within these functionals. Additionally, we amplify the inhomogeneity effects by creating the system with spherical shell which leads to even larger errors in DFT approximations., Comment: 8 pages, 4 figures, submitted to PRB as a regular article revisited version after review

The self-healing diffusion Monte Carlo algorithm (SHDMC) [Phys. Rev. B {\bf 79}, 195117 (2009), {\it ibid.} {\bf 80}, 125110 (2009)] is shown to be an accurate and robust method for calculating the ground state of atoms and molecules. By direct comparison with accurate configuration interaction results for the oxygen atom we show that SHDMC converges systematically towards the ground-state wave function. We present results for the challenging N$_2$ molecule, where the binding energies obtained via both energy minimization and SHDMC are near chemical accuracy (1 kcal/mol). Moreover, we demonstrate that SHDMC is robust enough to find the nodal surface for systems at least as large as C$_{20}$ starting from random coefficients. SHDMC is a linear-scaling method, in the degrees of freedom of the nodes, that systematically reduces the fermion sign problem., Comment: Final version accepted in Physical Review Letters. The review history (referees' comments and our replies) is included in the source.

We develop a formalism and present an algorithm for optimization of the trial wave-function used in fixed-node diffusion quantum Monte Carlo (DMC) methods. We take advantage of a basic property of the walker configuration distribution generated in a DMC calculation, to (i) project-out a multi-determinant expansion of the fixed-node ground-state wave function and (ii) to define a cost function that relates the fixed-node ground-state and the non-interacting trial wave functions. We show that (a) locally smoothing out the kink of the fixed-node ground-state wave function at the node generates a new trial wave-function with better nodal structure and (b) we argue that the noise in the fixed-node wave-function resulting from finite sampling plays a beneficial role, allowing the nodes to adjust towards the ones of the exact many-body ground state in a simulated annealing-like process. We propose a method to improve both single determinant and multi-determinant expansions of the trial wave-function. We test the method in a model system where benchmark configuration interaction calculations can be performed. Comparing the DMC calculations with the exact solutions, we find that the trial wave-function is systematically improved. The overlap of the optimized trial wave function and the exact ground state converges to 100% even starting from wave-functions orthogonal to the exact ground state. In the optimization process we find an optimal non-interacting nodal potential of density-functional-like form whose existence was predicted earlier[Phys.Rev. B {\bf 77}, 245110 (2008)]. We obtain the exact Kohn-Sham effective potential from the DMC data., Comment: Final version of the paper accepted in Physical Review B. The review reports and replies are included in the source