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Results for “first principles calculation”
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Data-driven modeling of Landau damping by physics-informed neural networks
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Phononic drumhead surface state in the distorted kagome compound RhPb
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Kitaev physics in the two-dimensional magnet NiPSe 3
The Kitaev interaction, found in candidate materials such as α − RuCl 3 , occurs through the metal ( M )-ligand ( X )-metal ( M ) paths of the edge-sharing octahedra because the large spin-orbit coupling (SOC) on the metal atoms activates directional spin interactions. Here, we show that even in 3 d transition-metal compounds, where the SOC of the metal atom is negligible, heavy ligands can induce bond-dependent Kitaev interactions. In this work, we take as an example the 3 d transition-metal chalcogenophosphate NiPSe 3 and show that the key is found in the presence of a sizable SOC on the Se p orbital, one which mediates the super-exchange between the nearest-neighbor Ni sites. Our study provides a pathway for engineering enhanced Kitaev interactions through the interplay of SOC strength, lattice distortions, and chemical substitutions. Published by the American Physical Society 2024
Three-dimensional higher-order saddle-point-induced flatbands in Co-based kagome metals
The saddle point (Van Hove singularity) exhibits a divergent density of states in two-dimensional systems, leading to fascinating phenomena such as strong correlations and unconventional superconductivity, yet it is seldom observed in three-dimensional (3D) systems. In this work we find two types of 3D higher-order saddle points (HOSPs) in emerging 3D kagome metals YbCo 6 Ge 6 and MgCo 6 Ge 6 . Both HOSPs exhibit a singularity in their density of states, which is significantly enhanced compared to the ordinary saddle point. The HOSP near the Fermi energy generates a flatband extending a large area in the Brillouin zone, potentially amplifying the correlation effect and fostering electronic instabilities. Two types of HOSPs exhibit distinct robustness upon element substitution and lattice distortions in these kagome compounds. Our work paves the way for engineering exotic band structures, such as saddle points and flatbands, and exploring interesting phenomena in Co-based kagome materials.
Effective many-body interactions in reduced-dimensionality spaces through neural network models
Accurately describing properties of challenging problems in physical sciences often requires complex mathematical models that are unmanageable to tackle head on. Therefore, developing reduced-dimensionality representations that encapsulate complex correlation effects in many-body systems is crucial to advance the understanding of these complicated problems. However, a numerical evaluation of these predictive models can still be associated with a significant computational overhead. To address this challenge, in this paper we discuss a combined framework that integrates recent advances in the development of active-space representations of coupled cluster (CC) downfolded Hamiltonians with neural network approaches. The primary objective of this effort is to train neural networks to eliminate the computationally expensive steps required for evaluating hundreds or thousands of Hugenholtz diagrams, which correspond to multidimensional tensor contractions necessary for evaluating a many-body form of downfolded effective Hamiltonians. Using small molecular systems (the H 2 O and HF molecules) as examples, we demonstrate that training neural networks employing effective Hamiltonians for a few nuclear geometries of molecules can accurately interpolate or extrapolate their forms to other geometrical configurations characterized by different intensities of correlation effects. We also discuss differences between effective interactions that define CC downfolded Hamiltonians with those of bare Hamiltonians defined by Coulomb interactions in the active spaces. Published by the American Physical Society 2024
Effect of interparticle fields and radiation reaction on beam dynamics
The dynamics of relativistic particles in an intense electromagnetic field can be described by the Landau-Lifshitz (LL) equation, where the radiation reaction (RR) is accounted for via a self-force, and interparticle fields are often neglected as an approximation. However, the inclusion of interparticle fields is necessary to ensure energy-momentum conservation, particularly during coherent emission. Here we present (i) an analytical proof showing that the energy-momentum conservation law of the Hamilton-Rohrlich-Dirac action, which is divergence free and describes a generic system of interacting charges, respects causality and provides physically sensible results; (ii) a simple generalization of the LL equation for many particles evaluated as a function of the total field, i.e., the sum of the external and interparticle fields. By performing first-principles numerical simulations of a neutral, relativistic bunch of electrons and positrons (e − /e + ) colliding with a laser pulse, this theory is shown to satisfy energy-momentum conservation when interparticle fields and RR are simultaneously taken into account; and (iii) the combined effect of interparticle fields and RR primarily affects the tail of the particle energy distribution. Additionally, our first-principles simulations show that the effect of interparticle fields on beam energy loss becomes smaller when most of the radiated energy is incoherent.
Robust Ferromagnetism in Highly Strained SrCoO 3 Thin Films
Epitaxial strain provides important pathways to control the magnetic and electronic states in transition-metal oxides. However, the large strain is usually accompanied by a strong reduction of the oxygen-vacancy formation energy, which hinders the direct manipulation of their intrinsic properties. Here, using a postdeposition ozone annealing method, we obtain a series of oxygen stoichiometric SrCoO 3 thin films with the tensile strain up to 3.0%. We observe a robust ferromagnetic ground state in all strained thin films, while interestingly the tensile strain triggers a distinct metal-to-insulator transition along with the increase of the tensile strain. The persistent ferromagnetic state across the electrical transition therefore suggests that the magnetic state is directly correlated with the localized electrons, rather than the itinerant ones, which then calls for further investigation of the intrinsic mechanism of this magnetic compound beyond the double-exchange mechanism.
Direct Detection of V-V Atom Dimerization and Rotation Dynamic Pathways upon Ultrafast Photoexcitation in VO 2
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Accurate Nonempirical Range-Separated Hybrid van der Waals Density Functional for Complex Molecular Problems, Solids, and Surfaces
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First-principles thermodynamics of Al 10 V: An analytical treatment of localized anharmonic modes
Many complex intermetallic structures possess cagelike environments that can host additional guest atoms. In Al 10 V, these atoms give rise to low-frequency, localized vibrations (Einstein modes) that dominate the thermodynamic response at low temperature. They become imaginary under volume expansion as temperature rises, invalidating the harmonic approximation. Here, we develop a framework to incorporate these strongly anharmonic vibrational modes into first-principles thermodynamic calculations. By explicitly modeling the cage potential and solving the associated Schrödinger equation numerically, we compute the full anharmonic free energy contribution and demonstrate its impact on the thermodynamic behavior of Al 10 V. This allows us to examine structures with different cage fillings and construct the Al-V phase diagram in the relevant composition range. Our results reproduce key experimental signatures, including the anomalous rise in the thermal expansion coefficient and heat capacity at low temperatures, and reveal that the presence and the extent of cage filling by guest atoms is essential to stabilizing the Al 10 V phase at elevated temperatures.
Kinetic Effects of Anion Clusters on the Interfacial Stability between Solid-State Electrolyte and Metal Anode
The success of all-solid-state batteries (ASSBs) depends on the solid-state electrolyte (SSE) exhibiting high interfacial stability and room-temperature ionic conductivity. However, the current SSEs, especially those with practical ionic conductivities (≥10 –3 S/cm) at room temperature, often develop unstable interfaces at the metal anode, in some cases with even greater severity than with liquid organic electrolytes. Despite persistent efforts, achieving interfacial stability and sufficient ionic conductivity simultaneously represents one of the greatest challenges in ASSBs. The current approaches focus on stabilizing the interface by incorporating secondary interlayers or introducing coatings by surface engineering. The method is often material-specific, and the added interlayers often deteriorate during cycling. In this work, using phase analysis and explicit interface modeling, we demonstrate a strategy to kinetically stabilize the interface between the SSE and metal anode by incorporating selected monoanion clusters in the SSE; they can effectively lower or even halt the reduction kinetics at the interface by promoting on-site formation of interphases that are highly electron insulating. The study provides insight into the kinetic effects to achieve SSEs with superior properties in bulk and at the interface.
Multiple Lattice Instabilities and Complex Ground State in Cs 2 Ag Bi Br 6
Metal-halide perovskites (MHPs) are attracting considerable interest for optoelectronic applications, with Cs 2 Ag Bi Br 6 one of the main contenders among lead-free systems. Cs 2 Ag Bi Br 6 crystallizes in a nominally double-perovskite structure, but exhibits a soft lattice with large atomic fluctuations characteristic of MHPs. While crucial to understand electron-phonon and phonon-phonon couplings, the spatiotemporal correlations of these fluctuations remain largely unknown. Here, we reveal these correlations using comprehensive neutron and x-ray scattering measurements on Cs 2 Ag Bi Br 6 single crystals, complemented with first-principles simulations augmented with machine-learned neural-network potentials. We report the discovery of an unexpected complex modulated ground-state structure containing several hundred atoms, arising from a soft-phonon instability of the low-temperature tetragonal phase. Further, our experiments and simulations both reveal extensive correlated two-dimensional fluctuations of Br octahedra at finite temperature, arising from soft optic phonons that are strongly broadened by anhamonicity, reflecting very shallow potential wells. These results provide new insights into the atomic structure and fluctuations in MHPs, critical to understand and control their thermal and optoelectronic properties. Published by the American Physical Society 2024
Say NO to Optimization: A Nonorthogonal Quantum Eigensolver
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Measuring the Debye energy in superconductors via two-electron photoemission spectroscopy
In this work, we demonstrate theoretically that double angle resolved photoemission spectroscopy (2eARPES) can directly probe the existence of Cooper pairs away from the Fermi surface, and can thus provide insight into the characteristic energy scale around the Fermi surface, the Debye energy, in which electrons are bound into Cooper pairs. To this end, we compute the photoelectron counting rate 𝑃 (2) in two different types of unconventional superconductors, a 𝑑 𝑥 2 −𝑦 2 -wave superconductor, and a topological superconductor with a broken time-reversal symmetry. We show that 𝑃 (2) provides insight into the relative strength of intra- and interband pairing in multiband systems, as well as into the spin polarization of the bands.
First-principles effective Hamiltonian for finite-temperature modeling of nonperovskite ferroelectrics
First-principles-based effective Hamiltonian techniques have been widely employed for over three decades to investigate ferroelectricity and related phenomena in perovskite materials. These techniques offer high accuracy, transferability, compatibility with various finite-temperature algorithms, computational efficiency, and ease in incorporating interactions with external fields. They have been adapted to study diverse phenomena, ranging from topological dipole patterns in ferroelectric nanostructures to multicaloric effects. In this work, we develop an effective Hamiltonian for the nonperovskite ferroelectric HfO 2 (hafnia). Applying this methodology to explore the finite-temperature and finite-electric-field properties of ferroelectric hafnia revealed (1) exceptionally large intrinsic coercive fields, an order of magnitude higher than those observed in perovskite ferroelectrics; (2) their atomistic origin; and (3) the existence of a regime where the relationship between the coercive field and the energy barrier for polarization reversal is counterintuitive. Here, these developments could accelerate progress both in methodological advancements for simulating ferroics and in the atomistic understanding of a broad range of ferroelectrics.
Ferroelectric phase transition in group-IV monochalcogenides from an equivariant machine learned force field
Group-IV monochalcogenides are a class of layered ferroelectric semiconductors that have demonstrated spontaneous intrinsic polarization above room temperature. Here, in this study, we use the multi-atomic cluster expansion (MACE) machine learning architecture to train and test a force field capable of modeling the structural properties and second-order ferroelectric-to-paraelectric phase transition in a Group-IV monochalcogenide, GeSe. The model captures the double-well potential energy surface associated with the onset of macroscopic polarization in bulk GeSe within 12.5 meV/atom, as well as near-equilibrium properties like the phonon dispersion. The development of this quantitatively accurate force field enables long-time molecular dynamics simulations, which predict the critical temperature of the ferroelectric-to-paraelectric phase transition in bulk GeSe to be T c = 600 K. This study demonstrates the capabilities of equivariant force-fields to accurately describe phenomena associated with structural symmetry breaking.
CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning
In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.