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At least 199 records · Page 11

Integrated ab initio modelling of atomic ordering and magnetic anisotropy for design of FeNi-based magnets

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE↗

2D Mg-Cu Intermetallic Compounds with Nontrivial Band Topology and Dirac Nodal Lines

Synthesis of vertical heterostructures that include atomically thin layers of materials with topologically nontrivial energy bands is desirable for exploring exotic quantum states. In this study, the authors report on atomic-layer-by-layer deposition of magnesium on copper(111) surface by molecular beam epitaxy, monitored in situ by low-energy electron microscopy and diffraction, and modeled by ab initio theory. It is found that a 2D MgCu 2 intermetallic compound forms during initial Mg deposition and persists till a full monolayer of Mg is formed. Deposition of additional Mg triggers a phase transition from the commensurate MgCu 2 to an incommensurate Mg 2 Cu layer and enables growth of the second layer of Mg. Ab initio calculations indicate non-trivial topology of the electron bands in the interfacial Mg 2 Cu layer and the existence of Dirac nodal lines near the Fermi level. The new 2D Mg 2 Cu material emerges as a promising platform to study new topological states of matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Thermodynamics of Liquid Uranium from Atomistic and Ab Initio Modeling

We present thermodynamic properties for liquid uranium obtained from classical molecular dynamics (MD) simulations and the first-principles theory. The coexisting phases method incorporated within MD modeling defines the melting temperature of uranium in good agreement with the experiment. The calculated melting enthalpy is in agreement with the experimental range. Classical MD simulations show that ionic contribution to the total specific heat of uranium does not depend on temperature. The density of states at the Fermi level, which is a crucial parameter in the determination of the electronic contribution to the total specific heat of liquid uranium, is calculated by ab initio all electron density functional theory (DFT) formalism applied to the atomic configurations generated by classical MD. The calculated specific heat of liquid uranium is compared with the previously calculated specific heat of solid γ-uranium at high temperatures. The liquid uranium cannot be supercooled below T sc ≈ 800 K or approximately about 645 K below the calculated melting point, although, the self-diffusion coefficient approaches zero at T D ≈ 700 K. Uranium metal can be supercooled about 1.5 times more than it can be overheated. The features of the temperature hysteresis are discussed.

36 MATERIALS SCIENCE↗

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition

Abstract Vibrational spectroscopy allows us to understand complex physical and chemical interactions of molecular crystals and liquids such as ammonia, which has recently emerged as a strong hydrogen fuel candidate to support a sustainable society. We report inelastic neutron scattering measurement of vibrational properties of ammonia along the solid-to-liquid phase transition with high enough resolution for direct comparisons to ab-initio simulations. Theoretical analysis reveals the essential role of nuclear quantum effects (NQEs) for correctly describing the intermolecular spectrum as well as high energy intramolecular N-H stretching modes. This is achieved by training neural network models using ab-initio path-integral molecular dynamics (PIMD) simulations, thereby encompassing large spatiotemporal trajectories required to resolve low energy dynamics while retaining NQEs. Our results not only establish the role of NQEs in ammonia but also provide general computational frameworks to study complex molecular systems with NQEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-throughput phase-field simulations and machine learning of resistive switching in resistive random-access memory

Metal oxide-based Resistive Random-Access Memory (RRAM) exhibits multiple resistance states, arising from the activation/deactivation of a conductive filament (CF) inside a switching layer. Understanding CF formation kinetics is critical to achieving optimal functionality of RRAM. Here a phase-field model is developed, based on materials properties determined by ab initio calculations, to investigate the role of electrical bias, heat transport and defect-induced Vegard strain in the resistive switching behavior, using MO 2- x systems such as HfO 2- x as a prototypical model system. It successfully captures the CF formation and resultant bipolar resistive switching characteristics. High-throughput simulations are performed for RRAMs with different material parameters to establish a dataset, based on which a compressed-sensing machine learning is conducted to derive interpretable analytical models for device performance (current on/off ratio and switching time) metrics in terms of key material parameters (electrical and thermal conductivities, Vegard strain coefficients). These analytical models reveal that optimal performance (i.e., high current on/off ratio and low switching time) can be achieved in materials with a low Lorenz number, a fundamental material constant. This work provides a fundamental understanding to the resistive switching in RRAM and demonstrates a computational data-driven methodology of materials selection for improved RRAM performance, which can also be applied to other electro-thermo-mechanical systems.

36 MATERIALS SCIENCE↗

Anharmonic thermodynamic properties and phase boundary across the postperovskite transition in MgSi O 3

To address the effects of lattice anharmonicity across the perovskite to postperovskite transition in MgSiO 3 , we conduct calculations using the phonon quasiparticle (PHQ) approach. The PHQ is based on abinitio molecular dynamics and, in principle, captures full anharmonicity. Free energies in the thermodynamic limit (N → ∞) are computed using temperature-dependent quasiparticle dispersions within the phonon gas model. Systematic results on anharmonic thermodynamic properties and phase boundary are reported. Both the local density approximation and the generalized gradient approximation calculations are performed to provide confident constraints on these properties. Anharmonic effects are demonstrated by comparing results with those obtained using the quasiharmonic approximation (QHA). The inadequacy of the QHA is indicated by its overestimation of thermal expansivity and thermodynamic Grüneisen parameter and its converged isochoric heat capacity in the high-temperature limit. The PHQ phase boundary has a Clapeyron slope (dP/dT) that increases with temperature. This result contrasts with the nearly zero curvature of the QHA phase boundary. Anharmonicity bends the phase boundary to lower temperatures at high pressures. Implications for the double-crossing of the phase boundary by the mantle geotherm are discussed.

36 MATERIALS SCIENCE↗

Nuclear Theory from First Principles to Forefront Experiments (Final Report for DE-SC0018638)

The Lee research group is a part of the Nuclear Lattice Effective Field Theory Collaboration, which has developed and performed ab initio lattice simulations of nuclear structure, scattering, reactions, and many-body systems. The other senior members of the collaboration include Ulf-G. Meißner at Bonn/Julich, Evgeny Epelbaum and Hermann Krebs at Bochum, Timo Lahde and Thomas Luu at Julich, and Gautam Rupak at Mississippi State. Our letter “Ab initio alpha-alpha scattering” was featured in a Nature News and Views article. Another letter “Nuclear binding near a quantum phase transition” was highlighted in a Viewpoint article in the online APS journal Physics as well as a news article in the IOP publication Physics World (September 21, 2016). Our letter “Eigenvector continuation with subspace learning” was also highlighted a Synopsis article in Physics. There are many promising ab initio approaches being used to calculate the properties of few-and many-nucleon systems. This includes the no-core shell model, symmetry-adapted no-core shell model quantum Monte Carlo, auxiliary-field diffusion Monte Carlo, self-consistent Green’s functions, many-body perturbation theory, in-medium similarity renormalization group, and coupled cluster methods. Lattice effective field theory is another ab initio approach which combines the framework of effective field theory with lattice Monte Carlo methods to allow favorable scaling from few- to many-body systems. Perhaps the most important aspect of lattice effective field theory is that its strengths and weaknesses are orthogonal to that of other ab initio methods. For example, lattice effective field theory has little difficulty in probing cluster structures and collectivity, while such features are much more difficult using other methods. Furthermore it can be used to compute superfluid condensate fractions as well as the phase diagram of strongly matter and the density and temperature dependence of clustering. Lattice effective field theory was first used in simulations of infinite nuclear matter and infinite neutron matter with pions and without pions. In addition to the efforts by our collaboration, there have been recent efforts by other groups as well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC

Abstract Machine learning interatomic force fields are promising for combining high computational efficiency and accuracy in modeling quantum interactions and simulating atomistic dynamics. Active learning methods have been recently developed to train force fields efficiently and automatically. Among them, Bayesian active learning utilizes principled uncertainty quantification to make data acquisition decisions. In this work, we present a general Bayesian active learning workflow, where the force field is constructed from a sparse Gaussian process regression model based on atomic cluster expansion descriptors. To circumvent the high computational cost of the sparse Gaussian process uncertainty calculation, we formulate a high-performance approximate mapping of the uncertainty and demonstrate a speedup of several orders of magnitude. We demonstrate the autonomous active learning workflow by training a Bayesian force field model for silicon carbide (SiC) polymorphs in only a few days of computer time and show that pressure-induced phase transformations are accurately captured. The resulting model exhibits close agreement with both ab initio calculations and experimental measurements, and outperforms existing empirical models on vibrational and thermal properties. The active learning workflow readily generalizes to a wide range of material systems and accelerates their computational understanding.

36 MATERIALS SCIENCE↗

Strain-induced lead-free morphotropic phase boundary

Enhanced susceptibilities in ferroelectrics often arise near phase boundaries between competing ground states. While chemically-induced phase boundaries have enabled ultrahigh electrical and electromechanical responses in lead-based ferroelectrics, precise chemical tuning in lead-free alternatives, such as (K,Na)NbO 3 thin films, remains challenging due to the high volatility of alkali metals. Here, we demonstrate strain-induced morphotropic phase boundary-like polymorphic nanodomain structures in chemically simple, lead-free, epitaxial NaNbO 3 thin films. Combining ab initio simulations, thin-film epitaxy, scanning probe microscopy, synchrotron X-ray diffraction, and electron ptychography, we reveal a labyrinthine structure comprising coexisting monoclinic and bridging triclinic phases near a strain-induced phase boundary. The coexistence of energetically competing phases facilitates field-driven polarization rotation and phase transitions, giving rise to a multi-state polarization switching pathway and large enhancements in dielectric susceptibility and tunability across a broad frequency range. Our results open new possibilities for engineering lead-free thin films with enhanced functionalities for next-generation applications.

Electronic properties and materials↗

Theoretical Investigation of Delafossite-Cu 2 ZnSnO 4 as a Promising Photovoltaic Absorber

In the quest for efficient and cost-effective photovoltaic absorber materials beyond silicon, considerable attention has been directed toward exploring alternatives. One such material, zincblende-derived Cu2ZnSnS4 (CZTS), has shown promise due to its ideal band gap size and high absorption coefficient. However, challenges such as structural defects and secondary phase formation have hindered its development. In this study, we examine the potential of another compound, Cu2ZnSnO4 (CZTO), with a similar composition to CZTS as a promising alternative. Employing ab initio density function theory (DFT) calculations in combination with an evolutionary structure prediction algorithm, we identify that the crystalline phase of delafossite structure is the most stable among the 900 (meta)stable CZTO. Its thermodynamic stability at room temperature is also confirmed by the molecular dynamics study. Excitingly, this new phase of CZTO displays a direct band gap where the dipole-allowed transition occurs, making it a strong candidate for efficient light absorptions. Furthermore, the estimation of spectroscopic limited maximum efficiency (SLME) directly demonstrates the high potential of delafossite-CZTO as a photovoltaic absorber. Our numerical results suggest that delafossite-CZTO holds promise for future photovoltaic applications.

14 SOLAR ENERGY↗

Nucleation Rate Theory for Coordination Number: Elucidating Water-Mediated Formation of a Zigzag Na 2 SO 4 Morphology

Predicting and controlling nanostructure formation during nucleation can pave the way to synthesizing novel energy materials via crystallization. However, such control over nucleation and crystallization remains challenging due to an inadequate understanding of critical factors that govern evolving atomistic structures and dynamics. Here, in this paper, we utilize coordination number as a reaction coordinate and rate theory to investigate how sodium sulfate, commonly known as a phase-change energy material, nucleates in a supersaturated aqueous solution. In conjunction with ab initio and force field-based molecular dynamics simulation, the rate theoretical analysis reveals that sodium sulfate from an initially dissolved metastable state transits to a heterogeneous mixture of prenucleated clusters and finally to a large cylindrical zigzag morphology. Measurements of Raman spectra and their ab initio modeling confirm that this nucleated morphology contains a few waters for every sulfate. Rate processes such as solvent exchange and desolvation exhibit high sensitivity to the evolving prenucleation/nucleation structures, providing a means to distinguish between critical nucleation precursors. Desolvation and forming the first-shell interionic coordination structure via monomer-by-monomer addition around sulfates are found to explain the formation of large nuclei. Thus, a detailed understanding of the step-by-step structure formation across scales has been achieved. This can be leveraged to predict nucleation-related structures and dynamics and potentially control the synthesis of novel phase-change materials for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis and Characterization of Magnesium Vanadates as Potential Magnesium‐Ion Cathode Materials through an Ab Initio Guided Carbothermal Reduction Approach**

Abstract Many technologically relevant materials for advanced energy storage and catalysis feature reduced transition‐metal (TM) oxides that are often nontrivial to prepare because of the need to control the reducing nature of the atmosphere in which they are synthesized. Herein, we show that an ab initio predictive synthesis strategy can be used to produce multi‐gram‐scale products of various MgV x O y ‐type phases (δ‐MgV 2 O 5 , spinel MgV 2 O 4 , and MgVO 3 ) containing V 3+ or V 4+ relevant for Mg‐ion battery cathodes. Characterization of these phases using 25 Mg solid‐state NMR spectroscopy illustrates the potential of 25 Mg NMR for studying reversible magnesiation and local charge distributions. Rotor‐assisted population transfer (RAPT) is used as a much‐needed signal‐to‐noise enhancement technique. The ab initio guided synthesis method is seen as a step forward towards a predictive synthesis strategy for targeting specific complex TM oxides with variable oxidation states of technological importance.

Lee, Jeongjae↗

Palladium at high pressure and high temperature: A combined experimental and theoretical study

Palladium is one of the most important technological materials, yet its phase diagram remains poorly understood. At ambient conditions, its solid phase is face-centered cubic (fcc). However, another solid phase of Pd, body-centered cubic (bcc), was very recently predicted in two independent theoretical studies to occur at high pressures and temperatures. In this work, we report an experimental study on the room-temperature equation of state (EOS) of Pd to a pressure of 80 GPa, as well as a theoretical study on the phase diagram of Pd including both fcc-Pd and bcc-Pd. Our theoretical approach consists in ab initio quantum molecular dynamics (QMD) simulations based on the Z methodology which combines both direct Z method for the simulation of melting curves and inverse Z method for the calculation of solid–solid phase transition boundaries. We obtain the melting curves of both fcc-Pd and bcc-Pd and an equation for the fcc–bcc solid–solid phase transition boundary as well as the thermal EOS of Pd which is in agreement with experimental data and QMD simulations. We uncover the presence of another solid phase of Pd on its phase diagram, namely, random hexagonal close-packed (rhcp), and estimate the location of the rhcp-bcc solid–solid phase transition boundary and the rhcp–fcc–bcc triple point. We also discuss the topological similarity of the phase diagrams of palladium and silver, the neighbor of Pd in the periodic table. We argue that Pd is a reliable standard for shock-compression studies and present the analytic model of its principal Hugoniot in a wide pressure range.

36 MATERIALS SCIENCE↗

Palladium at high pressure and high temperature: A combined experimental and theoretical study

Palladium is one of the most important technological materials, yet its phase diagram remains poorly understood. At ambient conditions, its solid phase is face-centered cubic (fcc). However, another solid phase of Pd, body-centered cubic (bcc), was very recently predicted in two independent theoretical studies to occur at high pressures and temperatures. In this work, we report an experimental study on the room-temperature equation of state (EOS) of Pd to a pressure of 80 GPa, as well as a theoretical study on the phase diagram of Pd including both fcc-Pd and bcc-Pd. Our theoretical approach consists in ab initio quantum molecular dynamics (QMD) simulations based on the Z methodology which combines both direct Z method for the simulation of melting curves and inverse Z method for the calculation of solid–solid phase transition boundaries. We obtain the melting curves of both fcc-Pd and bcc-Pd and an equation for the fcc–bcc solid– solid phase transition boundary as well as the thermal EOS of Pd which is in agreement with experimental data and QMD simulations. We uncover the presence of another solid phase of Pd on its phase diagram, namely, random hexagonal close-packed (rhcp), and estimate the location of the rhcp-bcc solid–solid phase transition boundary and the rhcp–fcc–bcc triple point. We also discuss the topological similarity of the phase diagrams of palladium and silver, the neighbor of Pd in the periodic table. We argue that Pd is a reliable standard for shock-compression studies and present the analytic model of its principal Hugoniot in a wide pressure range.

36 MATERIALS SCIENCE↗

Characterizing the nonequilibrium response of FeRh thin films using time-domain thermoreflectance

Time-domain thermoreflectance (TDTR) characterization of FeRh throughout its first-order antiferromagnetic (AF) to ferromagnetic (FM) transition shows that the transient reflectance ΔR⁡(t)/R strongly depends on the magnetic order of the sample. Using TDTR, which uses optical pulses to induce small temperature excursions, we have found that Δ⁢R⁡(t)/R of the AF phase exhibits a large negative response, while the response of the FM phase is positive. This magnetic phase sensitivity has allowed us to study the transient response of both the AF and FM phases to the pump-pulse excitation and the mixed phase of the material. These results are significant since the ultrafast properties of antiferromagnetic materials and mixed antiferromagnetic and ferromagnetic materials are difficult to detect using other conventional techniques. We have found that the AF phase exhibits a strong subpicosecond decaying signal not observed in the FM phase. The magnetic phase dependence of the sign of Δ⁢R⁡(t)/R is qualitatively explained using the results of ab initio density functional theory calculations. Using the two-temperature model, we found that the change in the thermalization time across the transition is caused by differences in both the electronic heat capacity and the electron-phonon coupling factor of the AF and FM phases. The electron-phonon coupling constant in the AF phase is also determined using the two-temperature model conducted using the ntmpy code package. For the FM phase, we provide boundaries for the magnitude of the electron-phonon coupling factor for the FM phase. Finally, these results indicate that TDTR can be used to study the transient properties of magnetic materials that are otherwise challenging to probe.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Guided anisotropic oxygen transport in vacancy ordered oxides

Abstract Anisotropic and efficient transport of ions under external stimuli governs the operation and failure mechanisms of energy-conversion systems and microelectronics devices. However, fundamental understanding of ion hopping processes is impeded by the lack of atomically precise materials and probes that allow for the monitoring and control at the appropriate time- and length- scales. In this work, using in-situ transmission electron microscopy, we directly show that oxygen ion migration in vacancy ordered, semiconducting SrFeO 2.5 epitaxial thin films can be guided to proceed through two distinctly different diffusion pathways, each resulting in different polymorphs of SrFeO 2.75 with different ground electronic properties before reaching a fully oxidized, metallic SrFeO 3 phase. The diffusion steps and reaction intermediates are revealed by means of ab-initio calculations. The principles of controlling oxygen diffusion pathways and reaction intermediates demonstrated here may advance the rational design of structurally ordered oxides for tailored applications and provide insights for developing devices with multiple states of regulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Planar Systems for Quantum Information

This project aims to develop two‐dimensional (2D) moiré materials as a quantum simulator to implement model Hamiltonians and their phase diagrams. Progress in quantum information science (QIS) requires the development of advanced quantum materials systems. The rich family of layered van der Waals materials and their heterostructures present opportunities to create previously unrealized types of applications for QIS. Specifically, when two layers of van der Waals materials are overlaid with a small twist angle or/and lattice mismatch, a moiré superlattice with a period of about ten nanometers is formed. This provides a periodic trapping potential for electrons. Electrons can tunnel between the traps and repel each other by their mutual Coulomb interactions. The platform of 2D moiré materials provides many attractive features, including tunability of length and energy scales, charge density, and even lattice symmetry. It presents new possibilities for realizing quantum simulation of the many-body physics in a solid-state platform. This integrated team of six investigators seeks to develop relevant theoretical treatments to link ab-initio studies of 2D moiré materials to model Hamiltonians and to evaluate correlated phases predicted by these model Hamiltonians in the relevant regimes. On the experimental side, the team aims to develop methods to realize a homogeneous and highly controlled potential landscape for the electrons and to initiate, protect, and measure their quantum many-body states.

36 MATERIALS SCIENCE↗