arXiv subjects

Robert B. Wexler

Publications and source records attributed to Robert B. Wexler.

8 recordsLinked to original sources

arXiv2026

Local B-site chemistry controls oxygen-vacancy energetics in Ca-Ce-Ti-Mn perovskites for thermochemical hydrogen production

Two-step thermochemical water splitting driven by concentrated solar heat is a scalable route to renewable hydrogen, but it requires oxides whose oxygen-vacancy formation energies balance facile reduction with favorable reoxidation. Perovskite solid solutions can tune this balance, but the relationship between bulk stoichiometry and local defect energetics remains poorly understood. Here we map oxygen-vacancy formation energetics across Ca-Ce-Ti-Mn (CCTM) perovskites by combining first-principles calculations with a coverage-constrained special quasirandom structure approach that realizes all fifteen symmetry-distinct oxygen nearest-neighbor environments, an interpretable crystal-feature model whose fitted coefficients directly encode the underlying Born-Haber thermochemistry, and a fine-tuned defect graph neural network. Local B-site chemistry dominates the oxygen-vacancy formation energy $E_\mathrm{v}$: varying the nearest-neighbor Mn fraction shifts $E_\mathrm{v}$ by 1.0-1.5 eV depending on local Ce content, whereas A-site Ce variation contributes a smaller, Mn-dependent shift of 0.2-0.6 eV. Short-range B-site cation order, if it can be established and kinetically retained through processing, is therefore a candidate means of tuning redox performance without changing bulk composition. Composition-space maps identify a Ce/Mn-balanced region ($X_\mathrm{Ce}$ = 0.29-0.33, $X_\mathrm{Mn}$ = 0.58-0.67) combining a high fraction of vacancy sites within the targeted $E_\mathrm{v}$ window with phase stability and solubility, whose predicted redox cycle capacity matches or exceeds the ceria benchmark at 1350 $^\circ$C rather than the roughly 1600 $^\circ$C ceria requires. Measurements on three CCTM compositions show cycle capacity increasing monotonically with Ce content under protocols close to the model conditions. The design rules are expected to transfer to related perovskite families.

cond-mat.mtrl-sci↗

arXiv2026

Equilibrium Thermochemistry and Crystallographic Morphology of Manganese Sulfide Nanocrystals

Manganese sulfide (MnS) is a p-type magnetic semiconductor whose physicochemical properties are sensitive to nanocrystal (NC) morphology, yet the thermodynamic driving forces governing morphology across MnS polymorphs remain poorly understood. Here, we use density functional theory (DFT) to predict the equilibrium morphologies of rock salt (RS), zinc blende (ZB), and wurtzite (WZ) MnS NCs as a function of the relative chemical potential of sulfur, $Δμ_{S}$. Benchmarking against Heyd$\unicode{x2013}$Scuseria$\unicode{x2013}$Ernzerhof (HSE06) hybrid functional calculations reveals that the r$^2$SCAN meta-generalized gradient approximation reproduces experimental lattice constants and thermochemical reaction energies but underestimates S-terminated polar surface energies by up to a factor of five; applying a Hubbard $U$ correction (r$^2$SCAN+$U$, $U = 2.7$ eV) to the Mn 3d states brings the results into close agreement with HSE06. Using the validated r$^2$SCAN+$U$ framework with the Gibbs$\unicode{x2013}$Wulff theorem, we predict that RS-MnS NCs favor nanocubes across nearly the entire stability window, ZB-MnS NCs transform from rhombic dodecahedra (Mn-rich) to polyhedra with 16 triangular faces (S-rich), and WZ-MnS NCs adopt rod-like morphologies with $Δμ_{S}$-sensitive base truncation. Synthesized RS-MnS NCs confirm the predicted cubic morphology, and high-temperature oxidative solution calorimetry yields an apparent surface energy of 1.15 $\pm$ 0.38 J$\cdot$m$^{-2}$, higher than the theoretical equilibrium value (0.42$\unicode{x2013}$0.43 J$\cdot$m$^{-2}$) due to high-index facet exposure, surface area uncertainty, and non-ideal surface configurations in real samples. This work establishes a framework for predicting the equilibrium morphologies of metal chalcogenide NCs.

cond-mat.mtrl-sci↗

arXiv2025

FreeBird.jl: An Extensible Toolbox for Simulating Interfacial Phase Equilibria

We present FreeBird, an extensible Julia-based platform for computational studies of phase equilibria at generic interfaces. The package supports a range of system configurations, from atomistic solid surfaces to coarse-grained lattice$-$gas models, with energies evaluated using classical interatomic potentials or lattice Hamiltonians. Both atomistic and lattice systems accommodate single- or multi-component mixtures with flexibly definable surface and lattice geometries. Implemented sampling algorithms include nested sampling, Wang$-$Landau sampling, Metropolis Monte Carlo, and, for tractable lattice systems, exact enumeration. Leveraging Julia's type hierarchies and multiple dispatch, FreeBird provides a modular interface that allows seamless integration of system definitions, energy evaluators, and sampling schemes. Designed for flexibility, extensibility, and performance, FreeBird offers a versatile framework for exploring the thermodynamics of interfacial phenomena.

cond-mat.stat-mech↗

arXiv2025

Adsorbate phase transitions on nanoclusters from nested sampling

Nested sampling was employed to investigate adsorption equilibria on the truncated-octahedral Lennard-Jones nanocluster LJ$_{38}$ while systematically varying adsorbate-surface well depth and Lennard-Jones size parameters. Evaluation of the canonical partition function over a wide temperature range identifies two successive phase transitions: (i) condensation of the gas phase onto the cluster surface at higher temperatures, and (ii) lateral rearrangement of the adsorbed layer at lower temperatures. For identical interactions, the condensate first populates both three- and four-fold hollow sites; when adsorbate-adsorbate interactions are weakened, preference shifts to the four-coordinated (100) sites. Size mismatch governs low-temperature behavior: smaller adsorbates aggregate to increase mutual contacts, whereas larger ones distribute more evenly to maximize coordination with the cluster. These findings highlight key trends in facet competition and lattice mismatch, and showcase nested sampling as an automated, unbiased tool for exploring surface configurational space and guiding investigations of more complex, realistic interfaces.

cond-mat.mtrl-sci↗

arXiv2024

Surface Phase Diagrams from Nested Sampling

Studies in atomic-scale modeling of surface phase equilibria often focus on temperatures near zero Kelvin due to the challenges in calculating the free energy of surfaces at finite temperatures. The Bayesian-inference-based nested sampling (NS) algorithm allows for modeling phase equilibria at arbitrary temperatures by directly and efficiently calculating the partition function, whose relationship with free energy is well known. This work extends NS to calculate adsorbate phase diagrams, incorporating all relevant configurational contributions to the free energy. We apply NS to the adsorption of Lennard-Jones (LJ) gas particles on low-index and vicinal LJ solid surfaces and construct the canonical partition function from these recorded energies to calculate ensemble averages of thermodynamic properties, such as the constant-volume heat capacity and order parameters that characterize the structure of adsorbate phases. Key results include determining the nature of phase transitions of adsorbed LJ particles on flat and stepped LJ surfaces, which typically feature an enthalpy-driven condensation at higher temperatures and an entropy-driven reordering process at lower temperatures, and the effect of surface geometry on the presence of triple points in the phase diagrams. Overall, we demonstrate the ability and potential of NS for surface modeling.

cond-mat.mtrl-sci↗

arXiv2024

JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods

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

cond-mat.mtrl-sci↗

arXiv2022

Ab initio study of proton-exchanged LiNbO3(I): Structural, thermodynamic, dielectric, and optical properties

Using first principles calculations, we study the ground-state structure of bulk proton-exchanged lithium niobate, which is also called hydrogen niobate and is widely used in waveguides. Thermodynamics helps to establish the most favorable nonpolar surface as well as the water-deficient and water-rich phases under different ambient conditions, which we refer to as "dehydrated" and "rehydrated" phases, respectively. We compute the low-frequency dielectric response and the optical refractive indices of hydrogen niobate in different phases. The dielectric constant is greatly enhanced compared to lithium niobate. At shorter wavelengths, the refractive indices vary between each phase and have a sharp contrast to lithium niobate. Our study characterizes the structures and thermal instabilities of this compound and reveals its excellent dielectric and optical properties, which can be important in the future application in waveguides.

cond-mat.mtrl-sci↗

arXiv2019

Sr-induced dipole scatter in BST: Insights from MD simulations using a transferable bond valence-based interatomic potential

In order to design next-generation ferroelectrics, a microscopic understanding of their macroscopic properties is critical. One means to achieving an atomistic description of ferroelectric and dielectric phenomena is classical molecular dynamics simulations. Previously, we have shown that interatomic potentials based on the bond valence molecular dynamics (BVMD) method can be used to study structural phase transitions, ferroelectric domain nucleation, and domain wall migration in several perovskite oxides and fixed-composition binary and ternary alloys. Most modern devices, however, use variable-composition perovskite oxide alloys such as Ba$_x$Sr$_{1-x}$TiO$_3$ (BST). In this paper, we extend our bond valence approach to BST solid solutions and, in so doing, show that the potential parameters for each element are transferable between materials with different $x$. Using this potential, we perform BVMD simulations investigating the temperature and composition dependence of the lattice constants, Ti displacements, and ferroelectric polarization of BST and find that our predictions match experiments and first-principles theory. Additionally, based on a detailed analysis of local dipole distributions, we demonstrate that substitution of Sr for Ba scrambles dipoles, reduces global polarization, and enhances the order-disorder character of the ferroelectric-paraelectric phase transition.

cond-mat.mtrl-sci↗