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At least 487 records · Page 27

Further steps toward the next generation of covariant energy density functionals

The present study aims at further development of covariant energy density functionals (CEDFs) towards more accurate description of binding energies across the nuclear chart. Infinite basis corrections to binding energies in the fermionic and bosonic sectors of the covariant density functional theory are taken into account in the fitting protocol within the covariant density functional theory. In addition, total electron binding energies are used in the conversion of atomic binding energies into nuclear ones. Their dependence on neutron excess is investigated across the nuclear chart within the atomic approach. Furthermore, these factors were disregarded in the previous generation of covariant energy density functionals, but their omission leads to substantial global calculation errors for physical quantities of interest. For example, these errors for binding energies are of the order of 0.8 MeV or higher for the three major classes of covariant energy density functionals.

Binding energy & masses↗

Molecular Based Temperature and Strain Rate Dependent Yield Criterion for Anisotropic Elastomeric Thin Films

A molecular formulation of the onset of plasticity is proposed to assess temperature and strain rate effects in anisotropic semi-crystalline rubbery films. The presented plane stress criterion is based on the strain rate-temperature superposition principle and the cooperative theory of yielding, where some parameters are assumed to be material constants, while others are considered to depend on specific modes of deformation. An orthotropic yield function is developed for a linear low density polyethylene thin film. Uniaxial and biaxial inflation experiments were carried out to determine the yield stress of the membrane via a strain recovery method. It is shown that the 3% offset method predicts the uniaxial elastoplastic transition with good accuracy. Both the tensile yield points along the two principal directions of the film and the biaxial yield stresses are found to obey the superposition principle. The proposed yield criterion is compared against experimental measurements, showing excellent agreement over a wide range of deformation rates and temperatures.

Bosi, F.↗

Energy Frontier Research Centers: Center for the Computational Design of Functional Layered Materials (CCDM) August 1, 2014 - July 31, 2018; Center for Complex Materials from First Principles (CCM) August 1, 2018 - July 31, 2021 (Final Report)

The mission of the DOE Energy Frontier Research Centers CCDM (2014-2018) and CCM (2018-2021) was to theoretically develop, computationally apply, and experimentally validate electronic structure methods for all materials, with a focus on the complex materials, especially layered and two-dimensional materials, strongly-correlated materials, and liquid water. This was achieved by over 200 published journal articles authored by about 17 senior investigators from physics and chemistry and from theory, computation, and experiment, plus their collaborators. In particular, the Centers confirmed the predictive power of the SCAN (strongly constrained and appropriately normed) density functional, which was constructed to satisfy 17 known exact constraints and several appropriate norms. Without being fitted to real bonded systems, and at a modest computational cost, SCAN correctly predicted covalent, ionic, metallic, hydrogen, and van der Waals bonds in many challenging materials. SCAN gave an improved description of defects in semiconductors, surface properties of metals, seven phases of ice, liquid water, liquid and supercooled silicon, subtle structural distortions in ferroelectrics, formation energies and structural predictions for solids, and critical pressures for structural phase transitions. Perhaps most remarkably, SCAN correctly described some strongly-correlated materials that were previously believed to be beyond the reach of density-functional approximations. SCAN is the only density functional that correctly predicts the band gap closing under chemical doping of the cuprate high-temperature superconducting materials. SCAN also predicts a landscape of competing stripe and magnetic phases in the cuprates. For some materials with some codes, SCAN has convergence problems that are greatly reduced by the CCM-developed r 2 SCAN, without loss of accuracy or rigor. SCAN and r 2 SCAN still make some self-interaction error, which is greatly reduced by the CCDM/ CCM-developed local orbital scaling correction (LOSC). These Centers further proved that the fundamental energy gaps of a solid from an orbital energy difference and from total energy differences are the same for a large class of generalized Kohn-Sham (GKS) functionals, including SCAN and standard hybrid functionals, and that symmetry breaking arises when a dynamic density fluctuation drops to zero frequency. The Centers identified new mechanisms for catalysis in layered materials with ions intercalated between the layers, investigated charge density waves both in model systems and in real layered materials, studied changes of band gap with the number of layers, and explored topological ultrathin films, bent nanoribbons, and defects.

08 HYDROGEN↗

Ethylene oxidation on unpromoted silver catalysts: Reaction pathway and selectivity analysis using DFT calculations

Chemical conversions in catalytic partial oxidation processes of light hydrocarbons are responsible for the production of numerous industrial chemicals, plastics, and intermediates. These processes are relatively expensive to perform, and are typically operated at high thermodynamic inefficiency, so the development of novel, highly efficient catalysts would prove to be very cost effective. Herein, our study focused on surface catalytic mechanisms of the ethylene oxide (EO) formation process. Periodic plane-wave Density Functional Theory (DFT) methods were used to analyze related reaction mechanisms on the Ag(111) surface facet with low coverage. Energetic changes of related species and pathways were calculated. Key surface species are identified to suggest the factors for the observed selectivity during EO formation. Our results are consistent with previous kinetic modeling efforts in the literature which did not employ DFT analysis. Lastly, our study demonstrates how fundamental theoretical investigations and multi-scale modeling techniques are currently impacting the advancement of rational catalyst design and microkinetic modeling techniques in the light hydrocarbon processing industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Random Phase Approximation Correlation Energy Using Real-Space Density Functional Perturbation Theory

We present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn–Sham density functional theory, leveraging the low-rank nature of the frequency-dependent density response operator. In particular, we employ a cubic-scaling formalism based on density functional perturbation theory that circumvents the calculation of the response function matrix, instead relying on the ability to compute its product with a vector through the solution of the associated Sternheimer linear systems. We develop a large-scale parallel implementation of this formalism using the subspace iteration method in conjunction with the spectral quadrature method while employing the Kronecker product-based method for the application of the Coulomb operator and the conjugate orthogonal conjugate gradient method for the solution of the linear systems. We demonstrate convergence with respect to key parameters and verify the method’s accuracy by comparing with plane-wave results. We show that the framework achieves good strong scaling to many thousands of processors, reducing the time to solution for a lithium hydride system with 128 electrons to around 150 s on 4608 processors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cu–Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and in Situ TEM Study

Here, the development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge in materials science. Using machine learning-accelerated density functional theory and rare-event methods, in conjunction with in situ environmental transmission electron microscopy (ETEM), we examine the interplay between surface reconstructions and preferential segregation tendencies of CuNi(100) surfaces under oxidation conditions. Our modeling approach predicts that oxygen-induced Ni segregation in CuNi alloys favors Cu(100)-O c(2 × 2) reconstruction and destabilizes the Cu(100)-O (2√2 × √2)R45° missing row reconstruction (MRR). In situ ETEM experiments validate these predictions and show Ni segregation followed by NiO nucleation and growth in regions without MRR, with secondary nucleation and growth of Cu 2 O in MRR regions. Our approach based on combining disparate computational components and in situ ETEM provides a holistic description of the oxidation mechanism in CuNi, which applies to other alloy systems.

36 MATERIALS SCIENCE↗

Li 5 VF 4 (SO 4 ) 2 : A Prototype High-Voltage Li-Ion Cathode.

A Li-rich polyanionic compound based on V 3+ with a previously unknown structure, Li 5 VF 4 (SO 4 ) 2 , has been developed as a high-voltage cathode material for Li-ion batteries. The solvothermal preparation of this material, crystal structure solution, and initial electrochemical characterization are presented. An analysis based on density functional theory electronic structure calculations suggests that a high voltage close to 5 V is required to extract two Li ions and to reach the oxidation state of V 5+ . However, the use of conventional carbonate-based electrolytes, which exhibit increasing degradation above a potential of 4.3 V, does not permit the full capacity of this compound to be achieved at this time.

25 ENERGY STORAGE↗

A first-principles machine-learning force field for heterogeneous ice nucleation on microcline feldspar

The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid water at deeply supercooled conditions, the presence of foreign particles can aid ice formation at much warmer temperatures. Over the past decade, experiments have highlighted the remarkable efficiency of feldspar minerals as ice nuclei compared to other particles present in the atmosphere. However, the exact mechanism of ice formation on feldspar surfaces has yet to be fully understood. Here, we develop a first-principles machine-learning model for the potential energy surface aimed at studying ice nucleation at microcline feldspar surfaces. The model is able to reproduce with high-fidelity the energies and forces derived from density-functional theory (DFT) based on the SCAN exchange and correlation functional. Our training set includes configurations of bulk supercooled water, hexagonal and cubic ice, microcline, and fully-hydroxylated feldspar surfaces exposed to vacuum, liquid water, and ice. In this work, we apply the machine-learning force field to study different fully-hydroxylated terminations of the (100), (010), and (001) surfaces of microcline exposed to vacuum. Our calculations suggest that terminations that do not minimize the number of broken bonds are preferred in vacuum. We also study the structure of supercooled liquid water in contact with microcline surfaces, and find that water density correlations extend up to around 10 Å from the surfaces. Finally, we show that the force field maintains a high accuracy during the simulation of ice formation at microcline surfaces, even for large systems of around 30,000 atoms. Future work will be directed towards the calculation of nucleation free energy barriers and rates using the force field developed herein, and understanding the role of different microcline surfaces on ice nucleation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unveiling the role of structural vacancies in Mn-based Prussian blue analogues for energy storage applications

Prussian blue analogues (PBAs) are promising cathode materials for monovalent- and multivalent-ion batteries due to their large framework structures. Nevertheless, the influence of lattice vacancies on their electrochemical performance has not been thoroughly clarified, hindering the further development of PBAs. Here we identify two types of functional vacancies, i.e., structural vacancies (SVs) and incidental vacancies (IVs), in manganese hexacyanoferrate (MnHCF) through synchrotron-based X-ray absorption spectroscopy and density functional theory calculations. Unlike structurally disordered IVs, the introduction of structurally ordered SVs promotes ion transport and reduces the interaction between host ions and the framework, enabling improved cycling and rate performance. The controllable adjustment of SVs in K-rich MnHCF is achieved through a co-reactant method. Furthermore, the partial introduction of SVs in K-rich MnHCF is demonstrated to favor both a milder structural evolution by alleviating the Jahn–Teller distortion of Mn 3+ and a stable dynamic process of interface reaction. As a result, this study unveils the potential importance of incorporating structural vacancies into MnHCF for advanced energy storage applications.

Gao, Chongwei↗

The role of surfaces in flexoelectricity

We develop the relationship between the strain derivative of the mean-inner potential and surface contributions to flexoelectricity, identifying the true surface-specific component of the flexoelectric response of finite samples. Density functional theory calculations on a range of experimentally observed, low energy SrTiO 3 , MgO, and Si surfaces demonstrate that the mean-inner potential and its contributions to flexoelectricity are sensitive to small differences in surface structure, chemistry, and adsorbates. We also introduce a method to estimate mean-inner potential contributions to flexoelectricity using electron scattering factors and use this approximation to predict total flexoelectric responses for a variety of insulators. Strategies to experimentally disentangle bulk and surface flexoelectric terms are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Suppression of antiferromagnetic order and strong ferromagnetic spin fluctuations in Ca(Co 1-x Ni x ) 2-y As 2 single crystals

CaCo 2–y As 2 is a unique itinerant system having strong magnetic frustration. Here, we report the effect of electron doping on the physical properties resulting from Ni substitutions for Co. The single crystals of Ca(Co 1–x Ni x ) 2–y As 2 were characterized by single-crystal x-ray diffraction, energy-dispersive x-ray spectroscopy, magnetization M versus temperature T, magnetic field H, time t, and heat capacity C p (H, T) measurements. The A-type antiferromagnetic (AFM) transition temperature T N = 52 K for x = 0 decreases to 22 K with only 3% Ni substitution and is completely suppressed for x > 0.16. For 0.11 ≤ x ≤ 0.52 strong ferromagnetic (FM) fluctuations develop as revealed by magnetic susceptibility χ(T) = M(T) / H measurements. For x = 0.11 and 0.16 competing AFM and FM interactions result in a reentrant spin-glass behavior below T N , as evidenced by the observations of thermomagnetic hysteresis and magnetic relaxation. Enhanced FM fluctuations are also found for the x = 0.21 and 0.31 crystals, where χ c increases significantly at low T. A large χ anisotropy in these compositions where χ c is up to a factor of two larger than χ ab suggests that the FM spin fluctuations are quasi-1D in nature. Weak ferromagnetic contributions to the magnetization are found at T = 2 K for x = 0.11 –0.31. Heat-capacity Cp(T) measurements reveal the presence of FM quantum spin fluctuations for 0.11 ≤ x ≤ 0.52, where a logarithmic T dependence of Cp(T) / T is observed at low T. Here, the suppression of AFM order by the development of strong FM fluctuations in Ca(Co 1–x Ni x ) 2–y As 2 crystals suggests the presence of a FM quantum-critical point at x ≈ 0.20. Our density-functional theory (DFT) calculations confirm that FM fluctuations are enhanced by Ni substitutions for Co in CaCo 2–y As 2 . The Sommerfeld electronic heat-capacity coefficient is enhanced for x = 0, 0.21, and 0.42 by about a factor of two compared to DFT calculations of the density of states (DOS) at the Fermi energy, suggesting an enhancement of the DOS from electron-phonon and/or electron-electron interactions. The crystals with x > 0.52 do not exhibit FM spin fluctuations or magnetic order at T ≥ 1.8 K, which was found from the DFT calculations to arise from a Stoner transition. Superconductivity is not observed above 1.8 K for any of the compositions. Neutron-diffraction studies of crystals with x = 0.11 and 0.16 in the crossover regime (0.1 ≲ x ≲ 0.2) show no evidence of A-type ordering as observed in the parent compound with x = 0. Furthermore, no other common magnetic structures, such as ferromagnetic (FM), helical stacking of in-plane FM layers, or in-plane AFM structure, are found with an ordered moment greater than the uncertainty of 0.05 μ B per transition-metal atom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

VOTCA: multiscale frameworks for quantum and classical simulations in soft matter

Many physical phenomena in liquids and soft matter are multiscale by nature and can involve processes with quantum and classical degrees of freedom occurring over a vast range of length- and timescales. Examples range from structure formation processes of complex polymers or even polymer blends (Svaneborg & Everaers, 2023) on the classical side to charge and energy transport and conversion processes (Lee et al., 2019) involving explicit electronic and, therefore, quantum information. The Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) provides multiscale frameworks built on a comprehensive set of methods for the development of classical coarse-grained potentials (VOTCA-CSG) as well as state-of-the art excited state electronic structure methods based on density-functional and many-body Green’s function theories, coupled in mixed quantum-classical models and used in kinetic network models (VOTCA-XTP).

97 MATHEMATICS AND COMPUTING↗

Elementary solutions of coupled model equations in the kinetic theory of gases

The method of elementary solutions is employed to solve two coupled integrodifferential equations sufficient for determining temperature-density effects in a linearized BGK model in the kinetic theory of gases. Full-range completeness and orthogonality theorems are proved for the developed normal modes and the infinite-medium Green's function is constructed as an illustration of the full-range formalism. The appropriate homogeneous matrix Riemann problem is discussed, and half-range completeness and orthogonality theorems are proved for a certain subset of the normal modes. The required existence and uniqueness theorems relevant to the H matrix, basic to the half-range analysis, are proved, and an accurate and efficient computational method is discussed. The half-space temperature-slip problem is solved analytically, and a highly accurate value of the temperature-slip coefficient is reported.

Kriese, J. T.↗

Novel Ultrabright and Air-Stable Photocathodes Discovered from Machine Learning and Density Functional Theory Driven Screening

The high brightness, low emittance electron beams achieved in modern X-ray free-electron lasers (XFELs) have enabled powerful X-ray imaging tools, allowing molecular systems to be imaged at picosecond time scales and sub-nanometer length scales. One of the most promising directions for increasing the brightness of XFELs is through the development of novel photocathode materials. Whereas past efforts aimed at discovering photocathode materials have typically employed trial-and-error-based iterative approaches, this work represents the first data-driven screening for high brightness photocathode materials. Through screening over 74 000 semiconducting materials, a vast photocathode dataset is generated, resulting in statistically meaningful insights into the nature of high brightness photocathode materials. This screening results in a diverse list of photocathode materials that exhibit intrinsic emittances that are up to 4x lower than currently used photocathodes. In a second effort, multiobjective screening is employed to identify the family of M 2 O (M = Na, K, Rb) that exhibits photoemission properties that are comparable to the current state-of-the-art photocathode materials, but with superior air stability. This family represents perhaps the first intrinsically bright, visible light photocathode materials that are resistant to reactions with oxygen, allowing for their transport and storage in dry air environments.

36 MATERIALS SCIENCE↗

Influence of External Conditions on the Black-to-Yellow Phase Transition of CsPbI 3 Based on First-Principles Calculations: Pressure and Moisture

All-inorganic CsPbI 3 perovskite has emerged as a promising candidate for next-generation solar cells. However, owing to the poor structural stability of black phase CsPbI 3 perovskite at room temperature, it spontaneously transforms to the yellow, photoinactive, nonperovskite phase at room temperature, limiting further development of CsPbI 3 perovskite solar cells. Here, to better understand the mechanism driving such undesirable phase transformation, we examine the thermodynamics and kinetics associated with γ-to-δ phase transformation using density functional theory calculation. A solid-state nudged elastic band method was employed to find minimum energy pathways assuming a concerted solid-state phase transformation between these two phases. The gas molecules representing atmospheric (H 2 O, O 2 , and N 2 ) and inert (Ar) ambient environments, as well as applied external pressure, were considered to examine the influence of external conditions on the black-to-yellow phase transition. Our calculation reveals that, with increasing pressure, the thermodynamic driving force for converting the γ-phase to the δ-phase increases, whereas a larger activation energy must be overcome for the phase transition to occur. We also investigate the moisture-induced phase transformation with an H 2 O molecule and its dissociated species (H + /OH – ) and demonstrate that the reaction energy barriers can be significantly lowered in the presence of H 2 O or OH – . On the other hand, other nonpolar species (O 2 , N 2 , and Ar) have a negligible effect on the phase transformation kinetics, while they might reduce the thermodynamic driving force for the phase transformation and suppress the undesirable phase transformation. Our theoretical prediction could support recent observations that the γ-to-δ phase transformation occurs rapidly and catalytically in the presence of moisture, whereas in dry argon and dry oxygen atmospheres, the γ-CsPbI 3 remains stable.

14 SOLAR ENERGY↗

Electronic Structure of Above-Room-Temperature van der Waals Ferromagnet Fe 3 GaTe 2

Fe 3 GaTe 2 , a recently discovered van der Waals ferromagnet, demonstrates intrinsic ferromagnetism above room temperature, necessitating a comprehensive investigation of the microscopic origins of its high Curie temperature ($T$ C ). In this study, we reveal the electronic structure of Fe 3 GaTe 2 in its ferromagnetic ground state using angle-resolved photoemission spectroscopy and density functional theory calculations. Our results establish a consistent correspondence between the measured band structure and theoretical calculations, underscoring the significant contributions of the Heisenberg exchange interaction ($J$ ex ) and magnetic anisotropy energy to the development of the high-$T$ C ferromagnetic ordering in Fe 3 GaTe 2 . Intriguingly, we observe substantial modifications to these crucial driving factors through doping, which we attribute to alterations in multiple spin-splitting bands near the Fermi level. In conclusion, these findings provide valuable insights into the underlying electronic structure and its correlation with the emergence of high-$T$ C ferromagnetic ordering in Fe 3 GaTe 2 .

36 MATERIALS SCIENCE↗

On the liquid–liquid phase transition of dense hydrogen

Until recently the consensus theory/computation interpretation of the challenging liquid liquid phase transition (LLPT) of high-pressure hydrogen was first order. Cheng et al. developed a machine-learnt potential (MLP) that, in larger molecular dynamics (MD) simulations, gives a continuous transition instead. Here, we show that the MLP does not reproduce our still larger MD density-functional theory (MD-DFT) calculations as it should. Since the MLP is not a faithful surrogate for the MD-DFT, the Ref. 6 prediction of a supercritical atomic liquid is unfounded.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗