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At least 235 records · Page 13

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗

The total neutron cross section of liquid and solid ammonia

Ammonia is a material of interest for future neutron moderators at high-power sources due to its high hydrogen density, low melting point, and resistance to polymerization in an intense radiation field. Its performance in such applications cannot currently be calculated due to the absence of suitable computer models for the interaction of neutrons with ammonia under relevant conditions. In an effort to develop suitable scattering kernels for computer simulations of moderator performance, we have conducted a series of Density Functional Theory and Molecular Dynamics calculations of the molecular-level thermal properties of ammonia at various temperatures within both the solid and liquid phases. In this paper, we compare computer calculations for the energy-dependent total neutron cross section of ammonia, based on these models, to experimental measurements of those cross sections at temperatures of 221 K, 180 K, and 35 K. The experimental data were collected over an energy range from 0.1 meV to 10 eV using time-of-flight techniques at the Low Energy Neutron Source (LENS) facility at Indiana University. This comparison provides a first validation in the development of thermal scattering libraries for Monte Carlo source design simulations based on liquid and solid ammonia. In conclusion, we also provide some insights into where additional development of tools for creating such models may be needed.

Ammonia↗

Insights into the Hydrogen Evolution Reaction on 2D Transition-Metal Dichalcogenides

Understanding hydrogen evolution reaction (HER) behaviors over two-dimensional transition-metal dichalcogenides (2D-TMDs) is critical for the development of nonprecious HER electrocatalysts with better activity. Here, in this work, by combining density functional theory calculations with microkinetic modeling, we thoroughly investigated the HER mechanism on 2D-TMDs. We find an important dependence of simulated cell size on the calculated hydrogen adsorption energy and the activation barrier for MoS 2 . Distinct from previous “H migration” mechanisms proposed for the Heyrovsky reaction, the rate-determining step for MoS 2 , we propose that the Mo site only serves as the stabilized transition state rather than H adsorption. In comparison to transition-metal electrocatalysts, we find that the activation barrier of the Heyrovsky reaction on 2D-TMDs scales with the hydrogen adsorption energy exactly as for transition metals except that all activation energies are displaced upward by ca. 0.4 eV. This higher Heyrovsky activation barrier is responsible for the substantially lower activity of 2D-TMDs. We further show that this higher activation barrier stems from the more positively charged adsorbed hydrogen on the chalcogenides interacting repulsively with the incoming proton. Based on these insights, we discuss potential strategies for the design of nonprecious HER catalysts with activity comparable to Pt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Performance Iridium–Molybdenum Oxide Electrocatalysts for Water Oxidation in Acid: Bayesian Optimization Discovery and Experimental Testing

Ir oxides are costly and scarce catalysts for oxygen evolution reaction (OER) in acid. There has been extensive interest in developing alternatives that are either Ir-free or require smaller amounts of Ir to drive the reactions at acceptable rates. One design strategy is to identify Ir-based mixed oxides that achieve similar performance while requiring smaller amounts of Ir. The obstacle to this strategy has been a very large phase space of the Ir-based mixed metal oxides, in terms of the metals combined with Ir and the different crystallographic structures of the mixed oxides, which prevents a thorough exploration of possible materials. In this work, we developed a workflow that uses machine-learning-aided Bayesian optimization in combination with density functional theory to make the exploration of this phase space plausible. This screening identified Mo as a promising dopant for forming acid-tolerant Ir-based oxides for the OER. We synthesized and characterized the Ir–Mo mixed oxides in the form of thin-film electrocatalysts with a known surface area. We show that these mixed oxides exhibited overpotentials ~30 mV lower than a pure Ir control while maintaining 24% lower Ir dissolution rates than the Ir control. Furthermore, these findings suggest that Mo is a promising dopant and highlight the promise of machine learning to guide the experimental exploration and optimization of catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncovering the True Active Sites in Ni–N–C Catalysts for CO 2 Electroreduction

Understanding and designing active sites in single-atom catalysts (SACs) requires going beyond static models to capture their dynamic evolution under realistic electrochemical conditions. Here, in this work, we develop an integrated theoretical framework that accounts for operational conditions, by combining grand canonical density functional theory (GC-DFT) with machine-learning-accelerated sampling, to uncover structure–activity–stability relationships in Ni–N–C SACs for the CO 2 reduction reaction (CO 2 RR). A library of NiN x C 4–x (x = 0–4) motifs─representing coordination defects likely formed during high-temperature synthesis─was systematically evaluated. Under working conditions, these sites were found to undergo hydrogenation, and NiN 3 C 1_ H 1 was identified as the most probable active site. At reducing potentials, hydrogen adsorbs spontaneously at C–Ni bridge sites rather than Ni top sites, while subsurface hydrogen facilitates bent CO 2 adsorption crucial for activation. High CO 2 RR selectivity toward CO arises from site separation: Ni centers drive CO2RR, while the hydrogen evolution reaction (HER) occurs at the C–Ni bridge or N sites and from thermodynamic suppression of HER at moderate hydrogen coverage. At more negative potentials, a shift in the CO 2 RR rate-determining process (RDP) and Ni out-of-surface displacement induced by coadsorption of H and H 2 O jointly reduce activity and selectivity. Thus, both the high CO2RR selectivity of Ni–N–C catalysts and its reversal with more negative potentials can be rationalized by accounting for hydrogenated surfaces. This highlights the necessity of modeling realistic; in situ conditions. This framework provides generalizable insights into the dynamic behavior of active sites in SACs, offering guidance for the rational design of active and robust catalysts for a wide range of electrochemical reactions.

25 ENERGY STORAGE↗

Kramers nodal lines and Weyl fermions in SmAlSi

Kramers nodal lines (KNLs) have recently been proposed theoretically as a special type of Weyl line degeneracy connecting time-reversal invariant momenta. KNLs are robust to spin orbit coupling and are inherent to all non-centrosymmetric achiral crystal structures, leading to unusual spin, magneto-electric, and optical properties. However, their existence in in real quantum materials has not been experimentally established. Here we gather the experimental evidence pointing at the presence of KNLs in SmAlSi, a non-centrosymmetric metal that develops incommensurate spin density wave order at low temperature. Using angle-resolved photoemission spectroscopy, density functional theory calculations, and magneto-transport methods, we provide evidence suggesting the presence of KNLs, together with observing Weyl fermions under the broken inversion symmetry in the paramagnetic phase of SmAlSi. We discuss the nesting possibilities regarding the emergent magnetic orders in SmAlSi. Our results provide a solid basis of experimental observations for exploring correlated topology in SmAlSi.

36 MATERIALS SCIENCE↗

Molecular dynamics study on the interfacial properties of mixtures of monomers of polyvinylpyrrolidone (PVP)-based battery binders on graphene and graphite surfaces

This study investigates the behavior of two different mixtures of monomers of polyvinylpyrrolidone (PVP)-based battery binders, polyvinylpyrrolidone:polyvinylidene difluoride (PVP:PVDF) and polyvinylpyrrolidone:polyacrylic acid (PVP:PAA), at graphene and graphite interfaces using classical molecular dynamics simulations. The aim is to identify the best performing monomer binder blend and carbon-based material for the design of battery-optimized energy devices. The PVP:PAA monomer binder blend and graphite are found to have the best interaction energies, densification upon adsorption, and more ordered structure. The adsorption of both monomer binder blends is strongly guided by the higher affinity of PVP and PAA monomeric molecules for the surfaces compared to PVDF. The structure of adsorbed layers of PVP:PVDF monomer binder blend on graphene and graphite develops more quickly than PVP:PAA, indicating faster kinetics. This study complements a previous density functional theory study recently reported by our group and contributes to a better understanding of the nanoscopic features of relevant interfacial regions involving mixtures of monomers of PVP-based battery binders and different carbon-based materials. In conclusion, the effect of a blend of commonly used monomer binders on carbon-based materials is essential for obtaining tightly bound anode and cathode active materials in lithium-ion batteries, which is crucial for designing battery-optimized energy devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Helimagnetism in the candidate ferroelectric CrI 2

CrI 2 is a van der Waals (vdW) layered material that exhibits helimagnetism that propagates along ribbon chains. This is determined from neutron time-of-flight diffraction measurements. Be low T N = 17 K in the orthorhombic structure, a screw-like helimagnetic order develops with an incommensurate wavevector of q ≈ (0.2492, 0, 0) at 8 K. Using density functional theory (DFT)+U calculations, the J 1 -J 2 model is leveraged to describe the helimagnetism, where J 1 (> 0) and J 2 (< 0) correspond, respectively, to a ferromagnetic nearest neighbor (NN) and antiferromagnetic next nearest neighbor (NNN) intrachain interaction. In conclusion, the DFT+U calculations suggest that orthorhombic CrI 2 satisfies conditions that favor formation of helimagnetic order.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dense plasma opacity via the multiple-scattering method

The calculation of the optical properties of hot dense plasmas with a model that has self-consistent plasma physics is a grand challenge for high energy density science. Here we exploit a recently developed electronic structure model that uses multiple scattering theory to solve the Kohn-Sham density functional theory equations for dense plasmas. Here we calculate opacities in this regime, validate the method, and apply it to recent experimental measurements of opacity for Cr, Ni, and Fe. Good agreement is found in the quasicontinuum region for Cr and Ni, while the self-consistent plasma physics of the approach cannot explain the observed difference between models and the experiment for Fe.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiscale Modeling of Vinyl-Addition Polynorbornenes: The Effect of Stereochemistry

Vinyl-addition polynorbornenes are candidates for designing high-performance polymers due to unique characteristics, which include a high glass transition temperature associated with a rigid backbone. Recent studies have established that the processability and properties of these polymers can be fine-tuned by using targeted substitutions. However, synthesis with different catalysts results in materials with distinct properties, potentially due to the presence of various stereoisomers that are difficult to quantify experimentally. Herein, we develop all-atom models of polynorbornene oligomers based on classical force fields and density functional theory. To establish the relationship between chemical architecture, chain conformations, and melt structure, we perform detailed molecular dynamics simulations with the fine-tuned atomistic force field and propose simpler coarse-grained descriptions to address the high molecular weight limit. All-atom simulations of oligomers suggest high glass transition temperatures in the range of 550–600 K. In the melt state (800 K), meso chains form highly rigid extended coils (C∞≈11) with amorphous structural characteristics similar to the X-ray diffraction data observed in the literature. In contrast, simulations with racemo chains predict highly helical tubular chain conformations that could promote assembly into crystalline structures.

Polymer Science↗

Machine learning interatomic potential for predicting the thermal properties of uranium nitride

We present a combined computational and experimental investigation of the thermal properties of uranium nitride (UN), focusing on the development of a machine learning interatomic potential (MLIP) using the moment tensor potential framework. The MLIP was trained on density functional theory (DFT) data and validated against various quantities including energies, forces, elastic constants, phonon dispersion, and defect formation energies, achieving excellent agreement with DFT calculations, prior experimental results, and our thermal conductivity measurement. The potential was then employed in molecular dynamics simulations to predict key thermal properties such as melting point, thermal expansion, specific heat, and lattice thermal conductivity. To further assess model accuracy, we fabricated a UN sample and performed new thermal conductivity measurements representative of single-crystal properties, which showed strong agreement with the MLIP predictions. This work confirms the reliability and predictive capability of the developed potential for determining the thermal properties of UN.

36 - MATERIALS SCIENCE↗

Erratum: “DFTB+, a software package for efficient approximate density functional theory based atomistic simulations” [J. Chem. Phys. 152, 124101 (2020)]

The implementation of the GPU support in DFTB+, as described in Sec. III C of the original publication,1 was developed based on a previous unpublished implementation by Jacek Jakowski. In order to acknowledge his work on this first implementation, the authors of the original publication wish to include J. Jakowski as co-author. The scientific content of the original publication is not affected.

42 ENGINEERING↗

Mixed stochastic-deterministic density functional theoretic decomposition of Kubo–Greenwood conductivities in the projector augmented wave formalism

Pairing the accuracy of the Kohn–Sham density-functional framework with the efficiency of a stochastic algorithmic approach, mixed stochastic-deterministic density functional theory (mDFT) achieves a favorable computational scaling with system sizes and electronic temperatures. We employ the recently developed mDFT formalism to investigate the dynamic charge-transport properties of systems in the warm dense matter regime. The optical conductivity spectra are computed for single- and multi- component mixtures of carbon, hydrogen, and beryllium using two complementary approaches: Kubo–Greenwood in the mDFT picture and real-time time-dependent mDFT. We further devise a decomposition of the Onsager coefficients leading up to the Kubo–Greenwood spectra to exhibit contributions from the deterministic, stochastic, and mixed electronic state transitions at different incident photon energies.

36 MATERIALS SCIENCE↗

DFTTK: Density Functional Theory ToolKit for high-throughput lattice dynamics calculations

In this work, we present a software package in Python for high-throughput first-principles calculations of thermodynamic properties at finite temperatures, which we refer to as DFTTK (Density Functional Theory ToolKit). DFTTK is based on the atomate package and integrates our experiences in the last decades on the development of theoretical methods and computational softwares. It includes task submissions on all major operating systems and task executions on high-performance computing environments. Furthermore, the distribution of the DFTTK package comes with examples of calculations of phonon density of states, heat capacity, entropy, enthalpy, and free energy under the quasi-harmonic phonon scheme for the stoichiometric phases of Al, Ni, Al 3 Ni, AlNi, AlNi 3 , Al 3 Ni 4 , and Al 3 Ni 5 , and the fcc solution phases treated using the special quasirandom structures at the compositions of Al 3 Ni, AlNi, and AlNi 3 .

97 MATHEMATICS AND COMPUTING↗

Two-way coherent tracking systems.

Review of some results pertinent to the development of nonlinear theory on two-way coherent tracking systems. In particular, the model of cascaded systems is presented, and approximations to steady state probability density functions of the two-way system phase and Doppler error are developed. From these, certain numerical results required in the design and planning of these systems are derived.

Lindsey, W. C.↗

Exploring the role of electronic structure on photo-catalytic behavior of carbon-nitride polymorphs

A fully self-consistent density-functional theory (DFT) with improved functionals is used herein to provide a comprehensive account of structural, electronic, and optical properties of C 3 N 4 polymorphs. Using our recently developed van Leeuwen-Baerends (vLB) corrected local-density approximation (LDA), we implemented LDA + vLB within full-potential N th -order muffin-tin orbital (FP-NMTO) method and show that it improves structural properties and band gaps compared to semi-local functionals (LDA/GGA). We demonstrate that the LDA + vLB predicts band-structure and work-function for well-studied 2D-graphene and bulk-Si in very good agreement with experiments, and more exact hybrid functional (HSE) calculations as implemented in the Quantum-Espresso (QE) package. The structural and electronic-structure (band gap) properties of C 3 N 4 polymorphs calculated using FP-NMTO-LDA + vLB is compared with more sophisticated hybrid-functional calculations. We also perform detailed investigation of photocatalytic behavior using QE-HSE method of C 3 N 4 polymorphs through work-function, band (valence and conduction) position with respect to water reduction and oxidation potential. Our results show $γ$-C 3 N 4 as the best candidate for photocatalysis among all the C 3 N 4 polymorphs but it is dynamically unstable at ‘zero’ pressure. We show that $γ$-C 3 N 4 can be stabilized under hydrostatic-pressure, which improves its photocatalytic behavior relative to water reduction and oxidation potentials.

36 MATERIALS SCIENCE↗

Surface structure of Sn doped β-Ga 2 O 3 (010) p(1×1) studied by quantitative low energy electron diffraction

Here, we have studied the surface structure of a single crystal β-Ga 2 O 3 (010) using quantitative Low Energy Electron Diffraction (LEED) and X-ray photoelectron spectroscopy (XPS). The XPS measurements show spectra typical of stoichiometric Ga 2 O 3 with a clean surface. LEED consistently shows a p(1x1) pattern, free of surface reconstruction. Quantitative LEED I(V) curves are acquired for 41 distinct diffraction spots. The experimental I(V) curves are compared to simulations over the first five layers. The best fits to the experimental LEED I(V) curves acquired at all diffraction spots are then used to calculate the interplanar relaxation and atomic rumpling. Significant atomic rumpling and interplanar relaxation are found over the first 5 atomic layers. As a result of rumpling a polarization of ~ 2 μC/cm 2 develops in the topmost surface layer. The structural results are in good agreement with previous density functional theory calculations and experimental X-ray photoelectron diffraction.

36 MATERIALS SCIENCE↗