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At least 73 records · Page 4

Nuclear energy density functionals grounded in ab initio calculations

Here, we discuss the construction of a nuclear energy density functional (EDF) from ab initio computations and advocate the need for a methodical approach that is free from ad hoc assumptions. The equations of state (EoSs) of symmetric nuclear and pure neutron matter are computed using the chiral NNLO sat and the phenomenological AV4' + UIX c Hamiltonians as inputs to self-consistent Green's function (SCGF) and auxiliary field diffusion Monte Carlo (AFDMC) methods. We propose a convenient parametrization of the EoS as a function of the Fermi momentum and fit it on the SCGF and AFDMC calculations. We apply the ab initio based EDF to carry out an analysis of the binding energies and charge radii of different nuclei in the local density approximation. The NNLO sat -based EDF produces encouraging results, whereas the AV4' + UIX c -based one is farther from experiment. Possible explanations of these different behaviors are suggested, and the importance of gradient and spin-orbit terms is analyzed. Our paper paves the way for a practical and systematic way to merge ab initio nuclear theory and density functional theory, while shedding light on some critical aspects of this procedure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

CrI 3 revisited with a many-body ab initio theoretical approach

CrI 3 has recently been shown to exhibit low-dimensional, long-range magnetic ordering from few layers to single layers of CrI 3 . The properties of CrI 3 bulk and few layered systems are uniquely defined by a combination of short-range intralayer and long-range interlayer interactions; including strong correlations, exchange and spin orbit coupling. Unfortunately, both the long-range van der Waals interactions, which are driven by dynamic, many-body electronic correlations and the competing strong intralayer correlations, present a formidable challenging for the local or semi local mean-field approximations employed in workhorse electronic structure approaches like density functional theory. In this work, we employ a sophisticated many-body approach that can simultaneously describe long- and short-range correlations. Herein, we establish that the fixed-node diffusion Monte Carlo (FNDMC) method reproduces the experimental interlayer separation distance of bulk CrI 3 for the high-temperature, monoclinic phase, with a reliable prediction of the interlayer binding energy. We subsequently employed, the FNDMC results to benchmark the accuracy of several density functional theory exchange-correlation approximations.

36 MATERIALS SCIENCE↗

Isotope Effects in the Zundel–Eigen Isomerization of H + (H 2 O) 6

The isomerization pathway between the energetically low-lying Zundel and Eigen isomers of the protonated water hexamer was investigated using high-level ab initio calculations including a treatment of zero-point corrections. On the basis of these calculations, the Zundel–Eigen isomerization was found to proceed through a stable intermediate isomer, which consists of a four-membered ring with two single acceptor water molecules. Further, the inclusion of vibrational zero-point energy is shown to be important for accurately establishing the relative energies of the three relevant isomers involved in the Zundel–Eigen isomerization. Diffusion Monte Carlo calculations including anharmonic vibrational effects show that all three isomers of H + (H 2 O) 6 and D + (D 2 O) 6 have well-defined structures. The energetic ordering of the three isomers changes upon deuteration. The implications of these results for the vibrational spectra of H + (H 2 O) 6 and D + (D 2 O) 6 are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗

Candidate structure for the H 2 -PRE phase of solid hydrogen

Experimental progress finally reached the metallic solid hydrogen phase, which was predicted by Wigner and Huntington over 80 years ago. However, the different structures in the phase diagram are still being debated due to the difficulty of diffraction experiments for high-pressured hydrogen. The determination of crystal structures under extreme condition is both of the basic condensed matter physics, and in planetary science: the behavior of giant gaseous planets (e.g., Jupiter and Saturn) strongly depends on the properties of inner high-pressured hydrogen. This work describes possible structures appearing under high pressures of 400~600 GPa. We applied a structural search using particle swarm optimization with density functional theory (DFT) to propose several candidate structures. For these structures, we performed fixed-node diffusion Monte Carlo simulations combined with DFT zero-point energy corrections to confirm their relative stability. We found P2 1 /c-8 as a promising candidate structure for the H 2 -PRE phase. P2 1 /c-8 is predicted the most stable at 400 and 500 GPa. P2 1 /c-8 reproduces qualitatively the IR spectrum peaks observed in the H 2 -PRE phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exploring interlayer coupling in the twisted bilayer PtTe 2

We have investigated interlayer interactions in the bilayer PtTe 2 system, which influence the electronic energy bands near the Fermi level. Our diffusion Monte Carlo (DMC) calculations for the high-symmetry bilayer stackings (AA, AB, AC) manifest distinct interlayer binding characteristics among the stacking modes by revealing significantly different interlayer separations depending on the stacking, which is critical to understanding the interlayer coupling of the twisted bilayers consisting of various local stacking arrangements. Furthermore, a comparison between the interlayer separations obtained from DMC and density functional theory (DFT) shows that meta-generalized gradient approximation (GGA)-based van der Waals–DFT results agree with DMC for different layer stackings, including twisted bilayers, but only the ground-state AA stacking matches well with GGA-based DFT predictions. This underscores the importance of accurate exchange-correlation potentials even for capturing the stacking-dependent interlayer binding properties. We further show that the variability in DFT-predicted interlayer separations is responsible for the large discrepancy of band structures in the 21 . 79 ∘ twisted bilayer PtTe 2 , affecting its classification as metallic or insulating. These results demonstrate the importance of obtaining a correct description of stacking-dependent interlayer coupling in modeling delicate bilayer systems at finite twists. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Importance of Van der Waals Interactions in Hydrogen Adsorption on a Silicon-carbide Nanotube Revisited with vdW-DFT and Quantum Monte Carlo

Density functional theory (DFT) is a valuable tool for calculating adsorption energies toward designing materials for hydrogen storage. However, dispersion forces being absent from the local/semi-local theory, it remains unclear as to how the consideration of van der Waals (vdW) interactions affects such calculations. For the first time, we applied diffusion Monte Carlo (DMC) to evaluate the adsorption characteristics of a hydrogen molecule on a (5,5) armchair silicon-carbide nanotube (H 2 -SiCNT). Within the DFT framework, we benchmarked various exchange-correlation functionals, including those recently developed for treating dispersion or vdW interactions. We found that the vdW-corrected DFT methods agree well with DMC, whereas the local (semilocal) functional significantly over (under)-binds. Furthermore, we fully optimized the H 2 -SiCNT geometry within the DFT framework and investigated the correlation between the structure and charge density. The vdW contribution to the adsorption was found to be non-negligible at similar to 1 kcal/mol per hydrogen molecule, which amounts to 9-29% of the ideal adsorption energy required for hydrogen storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum Monte Carlo Benchmarking of Molecular Adsorption on Graphene-Supported Single Pt Atom

The precise understanding of adsorption energetics and molecular geometry at catalytic sites is fundamental for advancing catalysis, particularly under the constraints of resource efficiency and environmental sustainability. Here, this study benchmarks the performance of density functional theory (DFT) calculations against diffusion Monte Carlo (DMC) calculations for adsorption properties of small gas molecules relevant to CO oxidation—namely O 2 , CO, CO 2 , and atomic oxygen—on a single Pt atom supported by pristine graphene. Our findings reveal that DMC calculations provide a significantly different landscape of adsorption energetics compared to DFT results. Notably, DFT predicts different lowest-energy configurations and spin states, particularly for O 2 , which suggests potential discrepancies in predicting the catalytic behavior. Furthermore, this study identifies the critical issue of CO poisoning, highlighted by the large disparity between the DMC adsorption energies of O 2 (−1.23(2) eV) and CO (−3.37(1) eV), which can inhibit the catalytic process. These results emphasize the necessity for more sophisticated computational approaches in catalysis research, aiming to refine the prediction accuracy of reaction mechanisms and to enhance the design of more effective catalysts.

Ahn, Jeonghwan [University of Illinois at Urbana-C↗

Enhanced stability and ordering of 2D MnBi2Se2Te2

This dataset includes density functional theory and quantum Monte Carlo calculations on MnBi(Se(1-x)Te(x))4 system for its phase stability and defect formation energies. The data supports publication "Increased Defect Resistance and Ordering in MnBi2(Se(1–x)Te(x))4 via Accurate Diffusion Monte Carlo" (https://doi.org/10.1021/acs.jpcc.5c04299).

36 MATERIALS SCIENCE↗

Quantum Monte Carlo and Density Functional Theory Study of Strain and Magnetism in 2D 1T-VSe 2 with Charge Density Wave States

Two-dimensional (2D) 1T-VSe 2 has prompted significant interest due to the discrepancies regarding alleged ferromagnetism (FM) at room temperature, charge density wave (CDW) states, and the interplay between the two. We employed a combined Diffusion Monte Carlo (DMC) and density functional theory (DFT) approach to accurately investigate the magnetic properties, CDW states, and their responses to strain in monolayer 1T-VSe 2 . Our calculations show the delicate competition between various phases, revealing critical insights into the relationship between their energetic and structural properties. Here, we performed classical Monte Carlo simulations informed by our DMC and DFT results and found the magnetic transition temperature (T c ) of the undistorted (non-CDW) FM phase to be 228 K and the distorted (CDW) phase to be 68 K. Additionally, we studied the response of biaxial strain on the energetic stability and magnetic properties of various phases of 2D 1T-VSe 2 and found that small amounts of strain can increase the T c , suggesting a promising route for engineering and enhancing magnetic behavior. Finally, we synthesized 1T-VSe 2 and performed Raman spectroscopy measurements, which were in close agreement with our calculated results, validating our computational approach. Our work emphasizes the role of highly accurate DMC methods in advancing the understanding of monolayer 1T-VSe 2 and provides a robust framework for future studies of 2D magnetic materials.

2D magnets↗

Resolution of Selectivity Steps of CO Reduction Reaction on Copper by Quantum Monte Carlo

Electrochemical reduction of carbon monoxide to valuable fuels and chemicals on copper surfaces remains a challenging area in catalysis due to a limited understanding of adsorption mechanisms and reaction pathways. Although density functional theory (DFT)-based studies have investigated these processes, their accuracy varies across different functionals. Here, in this study, we present the application of fixed-node diffusion Monte Carlo (FNDMC) to benchmark the adsorption energies of CO*, H*, and key CO reduction reaction (CORR) intermediates, COH* and CHO* on the Cu(111) surface. Our results for CO* and H* adsorption energies closely align with experimentally measured chemisorption reactions, highlighting the limitations of DFT and providing site-specific energy comparisons that are often not available experimentally. Additionally, we explore the effect of explicit solvation, demonstrating how water stabilizes the COH* over CHO*, thus suggesting a critical role of COH* in CORR. Finally, we release our high-accuracy FNDMC benchmarks for testing and developing new DFT functionals for electrocatalysis. Overall, this study underscores the potential of FNDMC for detailed surface chemistry studies and offers new insights into catalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic Improvement of Quantum Monte Carlo Calculations in Transition Metal Oxides: sCI-Driven Wavefunction Optimization for Reliable Band Gap Prediction

Accurate determination of the electronic properties of correlated oxides remains a significant challenge for computational theory. Traditional Hubbard-corrected density functional theory (DFT+U) frequently encounters limitations in precisely capturing electron correlation, particularly in predicting band gaps. We introduce a systematic methodology to enhance the accuracy of diffusion Monte Carlo (DMC) simulations for both ground and excited states, focusing on LiCoO 2 as a case study. By employing a selected configuration interaction (sCI) approach, we demonstrate the capability to optimize wavefunctions beyond the constraints of single-reference DFT+U trial wavefunctions. Here, we show that the sCI framework enables accurate prediction of band gaps in LiCoO 2 , closely aligning with experimental values and substantially improving traditional computational methods. The study uncovers a nuanced mixed state of t 2g and e g orbitals at the band edges that is not captured by conventional single-reference methods, further elucidating the limitations of PBE+U in describing d-d excitations. Our findings advocate for the adoption of beyond-DFT methodologies, such as sCI, to capture the essential physics of excited-state wavefunctions in strongly correlated materials. The improved accuracy in band gap predictions and the ability to generate more reliable trial wavefunctions for DMC calculations underscore the potential of this approach for broader applications in the study of correlated oxides. This work not only provides a pathway for more accurate simulations of electronic structures in complex materials but also suggests a framework for future investigations of the excited states of other challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

rmc-discord : reverse Monte Carlo refinement of diffuse scattering and correlated disorder from single crystals

A user-friendly program has been developed to analyze diffuse scattering from single crystals with the reverse Monte Carlo method. The approach allows for refinement of correlated disorder from atomistic supercells with magnetic or structural (occupational and/or displacive) disorder. The program is written in Python and optimized for performance and efficiency. Refinements of two user cases obtained with legacy neutron-scattering data demonstrate the effectiveness of the approach and the developed program. It is shown with bixbyite, a naturally occurring magnetic mineral, that the calculated three-dimensional spin-pair correlations are resolved with finer real-space resolution compared with the pair distribution function calculated directly from the reciprocal-space pattern. With the triangular lattice Ba 3 Co 2 O 6 (CO 3 ) 0.7 , refinements of occupational and displacive disorder are combined to extract the one-dimensional intra-chain correlations of carbonate molecules that move toward neighboring vacant sites to accommodate strain induced by electrostatic interactions. The program is packaged with a graphical user interface and extensible to serve the needs of single-crystal diffractometer instruments that collect diffuse-scattering data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spinbox: tools for many-body quantum systems in a Monte Carlo context

Spinbox is a piece of software that facilitates quantum mechanical calculations relevant to Monte Carlo simulation of atomic nuclei. At the front lines of research on the nuclear many-body problem are a large number of supercomputer-scale simulation codes. These codes produce valuable results but can be hard to understand, especially for those without intimate knowledge of the relevant theoretical methods. Thus, tools that fill pedagogical roles are extremely valuable. Spinbox makes it easy for one to replicate and analyze the computational processes relevant to a Quantum Monte Carlo (QMC) simulation that may be difficult to understand/debug/analyze due to the scale of the corresponding simulation software. Spinbox is written in Python using other state-of-the-art Python modules for numerical calculations. While a number of Python libraries exist that are suited to general quantum many-body calculations, the motivation of Spinbox is quite particular. In Diffusion Monte Carlo methods (DMC, GFMC, AFDMC), the central calculation is the imaginary-time propagation of individual samples of the many-body wavefunction. Although quantum wavefunctions generally must be described by a probability distribution over a basis, DMC imbues particles (within one sample) with classical spatial coordinates. This method is unusual, so other Python packages are typically not set up to do this easily. Furthermore, the software has built-in options for nuclear systems assuming isospin symmetry, which can be set up with other libraries but is a nontrivial process to do so. Features: - numerical representation of samples of the many-body wavefunctions, including tensor-product states (used in AFDMC) - numerical representation of many-body operators, including tensor-product operators: general, spin, imaginary-time propagation, etc. - the correct associated arithmetic and algebra, implemented as class methods - classes for representing realistic nuclear two- and three-body Hamiltonians (e.g. Argonne V18, Illinois NNN) - large-scale parallel integration over random variables, crucial for the AFDMC method My goal is to make this package open source so that anyone may use it and contribute to it, particularly other researchers doing AFDMC calculations

Fox, Jordan↗

A Quantum Monte Carlo Study of the Structural, Energetic, and Magnetic Properties of Two-Dimensional H and T Phase VSe 2

Previous works have controversially claimed near-room-temperature ferromagnetism in two-dimensional (2D) VSe 2 , with conflicting results throughout the literature. These discrepancies in magnetic properties between both phases (T and H) of 2D VSe 2 are most likely due to the structural parameters being coupled to the magnetic properties. Specifically, both phases have a close lattice match and similar total energies, which makes it difficult to determine which phase is being observed experimentally. Here, in this study, we used a combination of density functional theory, highly accurate diffusion Monte Carlo (DMC), and a surrogate Hessian line-search optimization technique to resolve the previously reported discrepancy in structural parameters and relative phase stability. With DMC accuracy, we determined the free-standing geometry of both phases and constructed a phase diagram. Our findings demonstrate the successes of the DMC method coupled with the surrogate Hessian structural optimization technique when applied to a 2D magnetic system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods

The field of 2D materials has grown dramatically in the past two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computing applications. These 2D structures, which are often exfoliated from layered van der Waals 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. 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. Here, 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.

2D materials↗

Monte Carlo simulations of particle acceleration at oblique shocks: Including cross-field diffusion

The Monte Carlo technique of simulating diffusive particle acceleration at shocks has made spectral predictions that compare extremely well with particle distributions observed at the quasi-parallel region of the earth's bow shock. The current extension of this work to compare simulation predictions with particle spectra at oblique interplanetary shocks has required the inclusion of significant cross-field diffusion (strong scattering) in the simulation technique, since oblique shocks are intrinsically inefficient in the limit of weak scattering. In this paper, we present results from the method we have developed for the inclusion of cross-field diffusion in our simulations, namely model predictions of particle spectra downstream of oblique subluminal shocks. While the high-energy spectral index is independent of the shock obliquity and the strength of the scattering, the latter is observed to profoundly influence the efficiency of injection of cosmic rays into the acceleration process.

Baring, M. G.↗

Unraveling H2 chemisorption and physisorption on metal decorated graphene using quantum Monte Carlo

Molecular hydrogen has the potential to significantly reduce the use of carbon dioxide emitting energy processes. However, hydrogen gas storage is a major bottleneck for its large-scale use as current storage methods are energy intensive. Among different storage methods, physisorbing molecular hydrogen at ambient pressure and temperatures is a promising alternative—particularly in light of the advancements in tunable lightweight nanomaterials and high throughput screening methods. Nonetheless, understanding hydrogen adsorption in well-defined nanomaterials remains experimentally challenging and reference information is scarce despite the proliferation of works predicting hydrogen adsorption. We focus on Li, Na, Ca, and K, decorated graphene sheets as substrates for molecular hydrogen adsorption, and compute the most accurate adsorption energies available to date using quantum diffusion Monte Carlo (DMC). Building on our previous insights at the density functional theory (DFT) level, we find that a weak covalent chemisorption of molecular hydrogen, known as Kubas interaction, is feasible on Ca decorated graphene according to DMC, in agreement with DFT. This finding is in contrast to previous DMC predictions of the 4H2/Ca+ gas cluster (without graphene) where chemisorption is not favored. However, we find that the adsorption energy of hydrogen on metal decorated graphene according to a widely used DFT method is not fully consistent with DMC. The reference adsorption energies reported herein can be used to find better work-horse methods for application in large-scale modeling of hydrogen adsorption. Furthermore, the implications of this work affect strategies for finding suitable hydrogen storage materials and high-throughput methods.

Chemistry↗