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At least 631 records · Page 35

Nonlocal correlations in iron pnictides and chalcogenides

Deviations of low-energy electronic structurse of iron-based superconductors from density-functional-theory predictions have been parametrized in terms of band- and orbital-dependent mass renormalizations and energy shifts. The former have typically been described in terms of a local self-energy within the framework of dynamical mean field theory, while the latter appears to require nonlocal effects due to interband scattering. By calculating the renormalized band structure in both random phase approximation (RPA) and the two-particle self-consistent approximation (TPSC), we show that correlations in pnictide systems like LaFeAsO and LiFeAs can be described rather well by a nonlocal self-energy. In particular, Fermi pocket shrinkage as seen in experiments occurs due to repulsive interband finite-energy scattering. For the canonical iron chalcogenide system FeSe in its bulk tetragonal phase, the situation is, however, more complex since even including momentum-dependent band renormalizations cannot explain experimental findings. We propose that the nearest-neighbor Coulomb interaction may play an important role in band-structure renormalization in FeSe. Finally, we further compare our evaluations of nonlocal quasiparticle scattering lifetime within RPA and TPSC with experimental data for LiFeAs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning

Knowing the rate at which particle radiation releases energy in a material, the “stopping power,” is key to designing nuclear reactors, medical treatments, semiconductor and quantum materials, and many other technologies. While the nuclear contribution to stopping power, i.e., elastic scattering between atoms, is well understood in the literature, the route for gathering data on the electronic contribution has for decades remained costly and reliant on many simplifying assumptions, including that materials are isotropic. We establish a method that combines time-dependent density functional theory (TDDFT) and machine learning to reduce the time to assess new materials to hours on a supercomputer and provide valuable data on how atomic details influence electronic stopping. Our approach uses TDDFT to compute the electronic stopping from first principles in several directions and then machine learning to interpolate to other directions at a cost of 10 million times fewer core-hours. We demonstrate the combined approach in a study of proton irradiation in aluminum and employ it to predict how the depth of maximum energy deposition, the “Bragg Peak,” varies depending on the incident angle—a quantity otherwise inaccessible to modelers and far outside the scales of quantum mechanical simulations. The lack of any experimental information requirement makes our method applicable to most materials, and its speed makes it a prime candidate for enabling quantum-to-continuum models of radiation damage. The prospect of reusing valuable TDDFT data for training the model makes our approach appealing for applications in the age of materials data science.

36 MATERIALS SCIENCE↗

Computational descriptor for electrochemical currents of carbon dioxide reduction on Cu facets

Computation screening is crucial for designing efficient electrochemical catalysts for carbon dioxide (CO 2 R) reduction that produce valuable hydrocarbons and oxygenates. In this work, leveraging density functional theory calculations for the CO adsorption energy ΔE CO on seventeen Cu terminations, we discover a strong linear correlation between ΔE CO and the experimentally measured CO 2 R electrochemical currents (ACS Catal. 2022, 12, 11, 6578–6588). Examining ab initio thermodynamics of early critical intermediates CO*, COH*, and CHO*, we find that CO* → CHO* is the thermodynamically controlling step. Beyond the general CO adsorption energy that only shows a linear trend with CO 2 R activity, we show that the reaction free energy of CO* → CHO* is the descriptor for the overall CO 2 R activity for Cu facets, as it displays a volcano relationship with the experimental current. Importantly, we show that high step and kink density of the Cu terminations not only enhances CO adsorption strength but also modulates the CO* → CHO* pathway, as respectively exemplified in the (941) and (741) facets. In addition, we explain that the high activity of (741) is due to its relatively low hydrogen evolution reaction activity compared with the other Cu surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Factors influencing quantum evaporation of helium from polar semiconductors from first principles

While there is much indirect evidence for the existence of dark matter (DM), to date it has evaded detection. Current efforts focus on DM masses over ~GeV—to push the sensitivity of DM searches to lower masses, new DM targets and detection schemes are needed. In this work, we focus on the latter—a novel detection scheme recently proposed to detect 10–100 meV phonons in polar target materials. Previous work showed that well-motivated models of DM can interact with polar semiconductors to produce an athermal population of phonons. This new sensing scheme proposes that these phonons then facilitate quantum evaporation of 3 He from a van der Waals film deposited on the target material. However, a fundamental understanding of the underlying process is still unclear, with several uncertainties related to the precise rate of evaporation and how it can be controlled. In this work, we use ab initio density functional theory calculations to compare the adsorption energies of helium atoms on a polar target material, sodium iodide, to understand the underlying evaporation physics. We explore the role of surface termination, monolayer coverage, and elemental species on the rate of He evaporation from the target material. Using this, we discuss the optimal target features for He-evaporation experiments and their range of tunability through chemical and physical modifications such as applied field and surface termination.

36 MATERIALS SCIENCE↗

Benchmarking Density Functional Theory Methods for Efficient Calculations of a Strongly Correlated Li 1– x Ni 1– y O 2−δ System

Transition metal oxides (TMOs), such as LiNiO 2 , are promising candidates for energy storage and electronic devices due to their unique electronic properties, exceptional physical and chemical characteristics, and ability to adopt multiple oxidation states. However, accurately predicting their properties using mean-field density functional theory (DFT) is challenging due to the presence of strongly correlated d-electrons and the complex interplay between their structural, electronic, and magnetic responses. These challenges are further exacerbated by the need to model defects, surfaces, and interfaces, which require computationally efficient, large-scale simulations. To address these issues, we carry out a benchmark study on the Li 1–x NiO 2 system, evaluating the performance of several popular functionals. Our findings demonstrate that combining SCAN functional relaxation with single-step HSE calculations provides a practical and scalable computational strategy. This approach balances accuracy and efficiency, enabling high-throughput simulations of strongly correlated TMOs and improved predictive modeling capability of TMOs for practical applications.

25 ENERGY STORAGE↗

Feasibility of Prelithiation in LiFePO 4

Lithium iron phosphate (LiFePO 4 ) is widely applied as the cathode material for the energy storage Li-ion batteries due to its low cost and high cycling stability. However, the low theoretical specific capacity of LiFePO 4 makes its initial capacity loss more concerning. Therefore, lithium compensation by way of prelithiation and applications of sacrificial Li-rich additives in LiFePO 4 is imminent in elevating the energy density and/or prolonging the lifetime of the LiFePO 4 -based Li-ion batteries (LIBs). Prelithiation in LiFePO 4 is herein carried out by electrochemical and chemical methods and its feasibility is proved on the basis of the electrochemical evaluations such as the initial charge capacity and the cycling stability. In addition, the site of the pre-intercalated Li-ions is found via comprehensive physical characterizations and the density functional theory (DFT) calculations. Furthermore, these findings open a new avenue for elevating the energy density and/or prolonging the lifetime of the high-energy-density batteries.

36 MATERIALS SCIENCE↗

Critical Assessment of the Thermodynamics of Vacancy Formation in Fe 2 O 3 Using Hybrid Density Functional Theory

Fe 2 O 3 hematite is a technologically important material with applications in energy storage as well as being the key phase formed in the rust of iron-based materials. Despite this central importance, there is much that is still unknown regarding the properties of defects in Fe 2 O 3 and consequently oxide growth. In this work, using screened hybrid density functional theory (HSE06), we consider the thermodynamics of vacancies in Fe 2 O 3 , considering the effects of ionic and electronic chemical potentials on both iron and oxygen vacancy formation. We find that, in the oxygen-rich limit, iron vacancies are easier to form, though the difference in formation energy between the two vacancies is only about 1 eV. In contrast, in the Fe-rich limit, oxygen vacancies have an extremely low formation energy, only 0.07 eV at mid-gap, and would spontaneously form as the Fermi level is reduced, while Fe vacancies require over 5 eV to form. Consistent with experiment, this indicates that Fe 2 O 3 is relatively easily reduced but not oxidized. However, the theoretical picture is very different when considering other exchange–correlation functionals (GGA + U or SCAN), emphasizing the critical role of the exchange–correlation functional in describing this system accurately.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Use of FLOSIC for understanding anion-solvent interactions

An Achille’s heel of lower-rung density-functional approximations is that the highest-occupied-molecular-orbital energy levels of anions, known to be stable or metastable in nature, are often found to be positive in the worst case or above the lowest-unoccupied-molecular-orbital levels on neighboring complexes that are not expected to accept charge. A trianionic example, [Cr(C2O4)3]3−, is of interest for constraining models linking Cr isotope ratios in rock samples to oxygen levels in Earth’s atmosphere over geological timescales. Here we describe how crowd sourcing can be used to carry out self-consistent Fermi–Löwdin–Orbital-Self-Interaction corrected calculations (FLOSIC) on this trianion in solution. The calculations give a physically correct description of the electronic structure of the trianion and water. In contrast, uncorrected local density approximation (LDA) calculations result in approximately half of the anion charge being transferred to the water bath due to the effects of self-interaction error. Use of group-theory and the intrinsic sparsity of the theory enables calculations roughly 125 times faster than our initial implementation in the large N limit reached here. By integrating charge density densities and Coulomb potentials over regions of space and analyzing core-level shifts of the Cr and O atoms as a function of position and functional, we unambiguously show that FLOSIC, relative to LDA, reverses incorrect solute-solvent charge transfer in the trianion-water complex. In comparison to other functionals investigated herein, including Hartree–Fock and the local density approximation, the FLOSIC Cr 1s eigenvalues provide the best agreement with experimental core ionization energies.

Chemistry↗

Screened Range-Separated Hybrid Functional with Polarizable Continuum Model Overcomes Challenges in Describing Triplet Excitations in the Condensed Phase Using TDDFT

Long range-corrected (LRC) or range-separated hybrid (RSH) functionals where the long-range (LR) limit of electronic interactions is set to the exact exchange have been shown to correct the tendency of traditional density functional theory (DFT) to underestimate the frontier orbital gap. Consequently, the use of such functionals in calculating electronic excited states using linear response based time-dependent DFT (TDDFT) has been successful in correcting the tendency for underestimating the energies of charge transfer states by DFT-based calculations. More recently formulations of functionals that attenuate the LR limit to address condensed-phase effects to polarize the electronic density have been reported. In particular screened RSH (SRSH) combined with polarizable continuum model (PCM) was benchmarked successfully in reproducing the fundamental gap and charge transfer state energies of molecular systems in the condensed phase. Here we use SRSH-PCM to address triplet excited states, and show its success in obtaining correspondence of the low-lying triplet states to the singlet–triplet gap in a similar way that the fundamental orbital gap corresponds to electron removal and addition energies. Importantly, the accuracy of the SRSH-PCM in calculating triplet excitations stands on the polarization consistent framework in addressing the scalar dielectric constant and without affecting the optimal tuning by triplet energies. Finally, the prospect of even further improving the SRSH-PCM accuracy in calculating triplet states can be achieved by optimal tuning on the basis of the spin multiplicity gap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Third-Order Møller–Plesset Theory Made More Useful? The Role of Density Functional Theory Orbitals

The practical utility of Møller–Plesset (MP) perturbation theory is severely constrained by the use of Hartree–Fock (HF) orbitals. It has recently been shown that the use of regularized orbital-optimized MP2 orbitals and scaling of MP3 energy could lead to a significant reduction in MP3 error. In this work, we examine whether density functional theory (DFT)-optimized orbitals can be similarly employed to improve the performance of MP theory at both the MP2 and MP3 levels. We find that the use of DFT orbitals leads to significantly improved performance for prediction of thermochemistry, barrier heights, noncovalent interactions, and dipole moments relative to the standard HF-based MP theory. Indeed, MP3 (with or without scaling) with DFT orbitals is found to surpass the accuracy of coupled-cluster singles and doubles (CCSD) for several data sets. We also found that the results are not particularly functional sensitive in most cases (although range-separated hybrid functionals with low delocalization error perform the best). As such, MP3 based on DFT orbitals thus appears to be an efficient, noniterative O(N 6 ) scaling wave-function approach for single-reference electronic structure computations. Scaled MP2 with DFT orbitals is also found to be quite accurate in many cases, although modern double hybrid functionals are likely to be considerably more accurate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A critical examination of compound stability predictions from machine-learned formation energies

Machine learning has emerged as a novel tool for the efficient prediction of material properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional Theory (DFT). The models tested in this work include five recently published compositional models, a baseline model using stoichiometry alone, and a structural model. By testing seven machine learning models for formation energy on stability predictions using the Materials Project database of DFT calculations for 85,014 unique chemical compositions, we show that while formation energies can indeed be predicted well, all compositional models perform poorly on predicting the stability of compounds, making them considerably less useful than DFT for the discovery and design of new solids. Most critically, in sparse chemical spaces where few stoichiometries have stable compounds, only the structural model is capable of efficiently detecting which materials are stable. The nonincremental improvement of structural models compared with compositional models is noteworthy and encourages the use of structural models for materials discovery, with the constraint that for any new composition, the ground-state structure is not known a priori. This work demonstrates that accurate predictions of formation energy do not imply accurate predictions of stability, emphasizing the importance of assessing model performance on stability predictions, for which we provide a set of publicly available tests.

36 MATERIALS SCIENCE↗

Vibrational study of CO, O 2 , and H 2 Adsorbed on the CoCrFeNi (110) High Entropy Alloy Surface

The vibrational properties of CO, O 2 , and H 2 molecularly or dissociatively adsorbed on a CoCrFeNi(110) surface have been probed using highresolution energy loss spectroscopy (HREELS) and modeled using density functional theory (DFT) calculations. Large (~20 mm3) single-crystal, quaternary face-centered cubic CoCrFeNi was synthesized via a modified Czochralski technique. We show strong evidence that CO adsorbs primarily on bridge and on-top sites in compositionally varied local environments, which reflect the random, multielemental surface composition inherent in a high entropy alloy. A variation of adsorption sites is also found with oxygen, which exhibits two broad groups of modes. Comparison to previous photoemission and theoretical studies suggests that the higher energy modes consist primarily of local CrO x species, while the lower energy modes are due to oxygen atoms adsorbed on other metal sites. Unlike CO and O 2 , HREELS upon H 2 adsorption shows only two much narrower modes and is consistent with atomic adsorption on 3-fold hollow sites. The hypothesized adsorption sites for all three species are directly corroborated by our DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of heteroatom doping on hydrogen uptake in tungsten oxide

Redox-active transition metal oxides (TMOs) that can undergo proton-insertion coupled electron transfer (PICET) are promising candidates for catalyzing molecular conversion reactions which require the transfer of hydrogen atoms (or the thermochemical equivalent, H + , e − ). Herein, we studied the effects of isovalent (Mo 6+ ) and aliovalent (V 5+ and Nb 5+ ) heteroatom doping on the electrochemical PICET behavior of monoclinic tungsten oxide (WO 3 ). Cyclic voltammetry in aqueous acidic electrolytes shows that the addition of redox-active heteroatoms (Mo 6+ and V 5+ ) leads to systematic shifts in redox couple half-wave potentials (E 1/2 ), broadening, and an overall decrease in the current response. Conversely, the non-redox active heteroatom (Nb 5+ ) only reduces the current response with no observable peak-current broadening. This broadening is attributed to changes in the proton binding affinities of oxygen in different chemical environments, i.e., bridging different pairs of redox-active transition metal cations. We determined the hydrogen bond dissociation free energy (H BDFE) values to elucidate the thermodynamic effect of heteroatom substitution. Density functional theory calculations reveal a differentiation in the hydrogen binding and oxygen vacancy formation energies between heteroatom doped structures. The PICET-induced structural phase transitions of the pristine and doped samples were further probed with operando electrochemical X-ray diffraction (EC-XRD) and with ex situ chemical reduction. The broadening of the potential-dependent current response with increased heteroatom doping manifests in the operando EC-XRD results as prolonged structural regions where multiple hydrogen bronze phases exist and the appearance of cubic bronze phases at lower degrees of reduction compared to pristine WO 3 .

Holzapfel, Noah P. [North Carolina State Universit↗

Quantum Non-Equilibrium Dynamics Prediction of Electronic Transport Coefficients in Non-Linear Regimes

The goal of this work was to develop unique LLNL capabilities for the computational prediction of electrical, optical and thermal transport properties from quantum simulations. Using a recently developed theory of microscopic quantum transport, we were able to model compressed metallic hydrogen and it’s non-linear and out-of-equilibrium contributions in electrical and thermal transport. This theory was implemented in the open-source, real-space time-dependent density functional theory code Octopus. This model is general and widely applicable to high energy density systems that are important to LLNL and NNSA mission areas.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Descriptors for Cu facets for CO2 reduction reaction activity

Computation screening is crucial for designing efficient electrochemical catalysts for carbon dioxide (CO2R) reduction to valuable hydrocarbons and oxygenates. Herein, leveraging density functional theory calculations of the CO adsorption energy ΔE_CO on seventeen Cu terminations, we discover a strong linear correlation between ΔE_CO and the recently experimentally measured CO2R electrochemical currents (ACS Catal. 2022, 12, 11, 6578–6588). Examining the ab initio thermodynamics of the early critical intermediates CO*, COH*, and CHO*, we find that CO* → CHO* is the thermodynamically preferred step, and notably shows a volcano trend with the experimental currents where the maximum CO2R current corresponds to the moderate CHO* formation energy. Importantly, we show that increasing the step and kink density of the Cu termination not only enhances CO adsorption strength but also modulates the CO* → CHO* pathway, as respectively exemplified in the (941) and (741) facets. We also explain why (741) is exceptional with high CO2R activity as measured experimentally due to its relatively low activity toward the hydrogen evolution reaction compared with the other Cu surfaces. Beyond the general CO adsorption energy that only shows a linear trend with CO2R activity, we show that the reaction CO* → CHO* free energy is a descriptor that displays a volcano relationship with the overall CO2R activity on Cu facets.

machine learning↗

SCF Framework, HF Stability, and RPA Correlation for Jordan–Wigner-Transformed Spin Hamiltonians on Arbitrary Coupling Topologies

Mapping spins to fermions via the Jordan–Wigner (JW) transformation can render mean-field (Hartree–Fock, HF) descriptions effective for strongly correlated spin systems. As established in recent work, the application of such approaches is not limited by the nonlocal structure of JW strings or by site ordering because string operators can be absorbed into Thouless rotations of a Slater determinant, and the variational optimization of a unitary Lie-algebraic similarity transformation removes any ordering dependence. Leveraging these ideas, we develop a self-consistent field (SCF) scheme that expresses the mean-field energy as a functional of the single-particle density matrix, providing an alternative to gradient-based optimization of Thouless parameters. We derive the analytical orbital Hessian to diagnose HF stability and compute the ground-state correlation energy through the random-phase approximation (RPA). Benchmark results for the XXZ and J 1 –J 2 model on one- and two-dimensional lattices demonstrate that RPA significantly improves mean-field accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phenyl‐Free Polynorbornenes for Potential Anion Exchange Ionomers for Fuel Cells and Electrolyzers

Abstract Ionomers in the catalyst layer play a critical role in the performance of fuel cells and electrolyzers. Phenyl adsorption on hydrogen oxidation catalysts and electrochemical oxidation of phenyl moieties on oxygen evolution catalysts are detrimental to the alkaline devices’ performance. Here the adsorption energy of phenyl‐containing ionomers is compared to provide the rationale for implementing phenyl‐free ionomers. Density functional theory calculations indicated that the norbornane fragment has minimal adsorption energy on Pt(111) due to the absence of aromatic π electrons. A soluble quaternized polynorbornene ionomer is prepared by vinyl addition polymerization, and it exhibits high performance in both fuel cells and electrolyzers, proving the advantage of the phenyl‐free structure. This study establishes the phenyl adsorption energy‐electrode performance relationship, highlighting the importance of material interactions between the catalysts and ionomers.

25 ENERGY STORAGE↗

Plasmon assisted synthesis of TiN-supported single-atom nickel catalysts

We report the deposition of single atom nickel catalyst on refractory plasmonic titanium nitride (TiN) nanomaterials supports using the wet synthesis method under visible light irradiation. TiN nanoparticles efficiently absorb visible light to generate photoexcited electrons and holes. Photoexcited electrons reduce nickel precursor to deposit Ni atoms on TiN nanoparticles’ surface. The generated hot holes are scavenged by the methanol. We studied the Ni deposition on TiN nanoparticles by varying light intensity, light exposure time, and metal precursor concentration. These studies confirmed the photodeposition method is driven by hot electrons and helped us to find optimum synthesis conditions for single atoms deposition. We characterized the nanocatalysts using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), energy dispersive X-ray spectroscopy (EDX), and X-ray photoelectron spectroscopy (XPS). We used density functional theory (DFT) calculations to predict favorable deposition sites and aggregation energy of Ni atoms on TiN. Surface defect sites of TiN are most favorable for single nickel atoms depositions. Interestingly, the oxygen sites on native surface oxide layer of TiN also exhibit strong binding with the single Ni atoms. Plasmon enhanced synthesis method can facilitate photodeposition of single atom catalysts on a wide class of metallic supports with plasmonic properties.

36 MATERIALS SCIENCE↗