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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Determining the Structure-Property Relationships of Quasi-Two-Dimensional Semiconductor Nanoplatelets.

We report a theoretical study of CdSe nanoplatelets aimed at identifying the main factors determining their photophysical properties. Using atomic configurations optimized with density functional theory calculations, we computed quasiparticle and exciton binding energies of nanoplatelets with two to seven monolayers. We employed many body perturbation theory at the GW level and solved the Bethe-Salpeter equation to obtain absorption spectra and excitonic properties. Our results, which agree well with recent experiments, were then used to design a model that allows us to disentangle the effects of quantum confinement, strain induced by passivating ligands, and dielectric environment on the electronic properties of nanoplatelets. We found that, for the model to accurately reproduce our first principle results, it is critical to account for surface stress and consider a finite potential barrier and energy-dependent effective masses when describing quantum confinement. Our findings call into question previous assumptions on the validity of an infinite barrier to describe carrier confinement in nanoplatelets, suggesting that it may be possible to optimize interfacial charge transfer and extraction by appropriately choosing passivating ligands. The model developed here is generalizable to core-shell platelets and enables the description of system sizes not yet directly treatable by first-principles calculations.

Greenwood, Arin R.↗
DOE OSTI2022

Transport and optical properties of the chiral semiconductor Ag 3 AuSe 2

Previous band structure calculations predicted Ag 3 AuSe 2 to be a semiconductor with a band gap of approximately 1 eV. Here, we report single crystal growth of Ag 3 AuSe 2 and its transport and optical properties. Single crystals of Ag 3 AuSe 2 were synthesized by slow-cooling from the melt, and grain sizes were confirmed to be greater than 2 mm using electron backscatter diffraction. Optical and transport measurements reveal that Ag 3 AuSe 2 is a highly resistive semiconductor with a band gap and activation energy around 0.3 eV. Our first-principles calculations show that the experimentally determined band gap lies between the predicted band gaps from GGA and hybrid functionals. We predict band inversion to be possible by applying tensile strain. The sensitivity of the gap to Ag/Au ordering, chemical substitution, and heat treatment merit further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗
DOE OSTI2020

First-principles study of the topological surface states of α-Sn(111)

α-Sn is on the boundary of a couple of distinct topological phases. It will transform into a topological insulator under a suitable strain. However, a clear picture of its topological surface states (TSSs) is still lacking. Furthermore we perform first-principles calculations on the electronic structure of α-Sn(111) surface to identify its TSSs and reveal their properties. The results show that the presence of valence band reorganizes the TSSs in the inverted sp gap into two Dirac cones. The lower one is in the valence band continuum; the upper one resides in the gap between the valence and conduction bands. We also demonstrate the transformation of the surface states by switching on or off of strain and/or spin-orbit coupling. Without spin-orbit coupling, only the TSSs associated with the lower Dirac cone survive, and they are spin unpolarized. The results are useful for understanding and engineering the topological properties of α-Sn.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Investigating the Electronic Structure of Prospective Water-Splitting Oxide BaCe 0.25 Mn 0.75 O 3-δ before and after Thermal Reduction

BaCe 0.25 Mn 0.75 O 3-δ (BCM), a non-stoichiometric oxide with a layered perovskite-like crystal structure, has recently emerged as a prospective contender for application in renewable energy harvesting by solar thermochemical hydrogen generation. Using solar-thermal energy and a reducing environment, oxygen vacancies can be created in high-temperature BCM, and the reduced crystal so obtained can, in turn, produce H 2 by stripping oxygen from H 2 O. Therefore, a first step toward understanding the working mechanism and optimizing the performance of BCM is a thorough and comparative analysis of the electronic structure of the pristine and the reduced material. In this paper, we probe the electronic structure of BCM using the combined effort of first-principles calculations and experimental O K-edge X-ray absorption spectroscopy (XAS). The computed projected density of states (PDOS) and orbital plots are used to propose a simplified model for orbital mixing between the oxygen and metal atoms. With the help of state-of-the-art simulations, we are able to find the origins of the XAS peaks and categorize them on the basis of contribution from Ce and Mn. For the reduced crystal, the calculations show that the change in electron density resulting from the reduction is strongly localized around the oxygen vacancy. Experimental measurements reveal a marked lowering of the first O K-edge peak in the reduced crystal. Using theoretical analysis, this is shown to result from lifting of spin degeneracy in the absorption peaks as well as from a diminished O 2p contribution to the frontier unoccupied orbitals, in accordance with the tight binding scheme. The simulated results serve as a reference for the extent of spectral change as a function of the percentage of oxygen vacancies in the reduced crystal. Here, our study paves the way for the investigation of the working mechanism of BCM and for computational and experimental efforts aimed at design and discovery of efficient water-splitting oxides.

08 HYDROGEN↗
DOE OSTI2020

Tuning magnetic order in the van der Waals metal $Fe_5GeTe_2$ by cobalt substitution

Fe 5 - x GeTe 2 is a van der Waals material with one of the highest reported bulk Curie temperatures, T C ≈ 310 K . Here, theoretical calculations and experiments are utilized to demonstrate that the magnetic ground state is highly sensitive to local atomic arrangements and the interlayer stacking. Cobalt substitution is found to be an effective way to manipulate the magnetic properties while also increasing the ordering temperature. In particular, cobalt substitution up to ≈ 30 % enhances T C and changes the magnetic anisotropy, while ≈ 50 % cobalt substitution yields an antiferromagnetic state. Single crystal x-ray diffraction evidences a structural change upon increasing the cobalt concentration, with a rhombohedral cell observed in the parent material and a primitive cell observed for ≈ 46 % cobalt content relative to iron. First-principles calculations demonstrate that it is a combination of high cobalt content and the concomitant change to primitive layer stacking that produces antiferromagnetic order. These results illustrate the sensitivity of magnetism in Fe 5 - x GeTe 2 to composition and structure, and emphasize the important role of local structural order-disorder and layer stacking in cleavable magnetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synergic Effects of Surface Chemistry and Applied Potentials on the Kinetics of the Electrocatalytic Oxygen Evolution Reaction in IrO 2

Improving the efficacy of the oxygen evolution reaction (OER) through water oxidation is critical for advancing photoelectrochemical water splitting. Among the catalysts, IrO 2 exhibits a high OER catalytic activity and stability under acidic conditions. The OER mechanism in this system has been a topic of intense research; however, many mechanistic understandings are lacking. In this work, we carried out first-principles calculations with an implicit solvation model at a constant potential to study the OER behavior on the IrO 2 (110) surface. We find that the surface hydrogen coverage has a significant effect on OER kinetics and transition states. We then develop a microkinetics model that accounts for the continuous evolution of both OER activation energy and hydrogen coverage as a function of an applied potential. We show that this inclusion leads to significant improvement in the simulated Tafel plot compared to available experiments. In conclusion, our results point to a complex interplay between surface chemistry and the applied potential on OER kinetics.

08 HYDROGEN↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Trajectory sampling and finite-size effects in first-principles stopping power calculations

Abstract Real-time time-dependent density functional theory (TDDFT) is presently the most accurate available method for computing electronic stopping powers from first principles. However, obtaining application-relevant results often involves either costly averages over multiple calculations or ad hoc selection of a representative ion trajectory. We consider a broadly applicable, quantitative metric for evaluating and optimizing trajectories in this context. This methodology enables rigorous analysis of the failure modes of various common trajectory choices in crystalline materials. Although randomly selecting trajectories is common practice in stopping power calculations in solids, we show that nearly 30% of random trajectories in an FCC aluminum crystal will not representatively sample the material over the time and length scales feasibly simulated with TDDFT, and unrepresentative choices incur errors of up to 60%. We also show that finite-size effects depend on ion trajectory via “ouroboros” effects beyond the prevailing plasmon-based interpretation, and we propose a cost-reducing scheme to obtain converged results even when expensive core-electron contributions preclude large supercells. This work helps to mitigate poorly controlled approximations in first-principles stopping power calculations, allowing 1–2 order of magnitude cost reductions for obtaining representatively averaged and converged results.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ab Initio Neutrinoless Double-Beta Decay Matrix Elements for Ca 48 , Ge 76 , and Se 82

We calculate basis-space converged neutrinoless ββ-decay nuclear matrix elements for the lightest candidates: 48 Ca, 76 Ge, and 82 Se. Starting from initial two- and three-nucleon forces, we apply the ab initio in-medium similarity renormalization group to construct valence-space Hamiltonians and consistently transformed ββ-decay operators. Here, we find that the tensor component is non-negligible in 76 Ge and 82 Se, and the resulting nuclear matrix elements are overall 25%–45% smaller than those obtained from the phenomenological shell model. While a final matrix element with uncertainties still requires substantial developments, this work nevertheless opens a path toward a true first-principles calculation of neutrinoless ββ decay in all nuclei relevant for ongoing large-scale searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Disorder-induced magnetoelastic behaviors of MnTexSbyBi1-x-y alloys

This dataset contains input and output files from density functional theory (DFT) simulations used to study the disorder-induced magnetoelastic behaviors of MnTexSbyBi1-x-y (0 ≤ x + y ≤ 1) alloys and their binary end members MnTe, MnSb, and MnBi. The alloys adopt the hexagonal NiAs-type (nickeline) structure and span ternary (MnTexSb1-x, MnTexBi1-x, MnBixSb1-x), and quaternary compositions across the full MnTe–MnSb–MnBi composition triangle. For each alloy composition, the dataset provides DFT calculations in three magnetic configurations: A-type antiferromagnetic (AFM), C-type AFM, and ferromagnetic (FM). Every magnetic configuration folder contains the fully relaxed crystal structure (CONTCAR), VASP input parameters (INCAR), and the main VASP output file (OUTCAR), from which total electronic energies, Mn magnetic moments, lattice parameters, and percent volume changes between magnetic states are extracted. These data are used to construct compositional phase diagrams, evaluate thermodynamic stability (formability), and map magnetoelastic responses across the alloy space. For A-type AFM and FM configurations, additional data are provided as follows: (i) FORCE_CONSTANTS and thermal_properties.yaml files at the top level of A-type_AFM/ and FM/ folders — present only for compositions marked with an asterisk (*) in Table I of the main text. These are derived from Phonopy finite-displacement calculations on full disordered 128-atom supercells and provide vibrational free energy, entropy (Svib)contribution from explicit disorder calculations. (Table I of the associated main manuscript) (ii) A VCA/ subfolder within A-type_AFM/ and FM/, containing FORCE_CONSTANTS and thermal_properties.yaml from Virtual Crystal Approximation phonon calculations (without spin-orbit coupling). VCA data are available for all compositions and are used to estimate vibrational contributions to the Gibbs free energy across the full composition space. (iii) A SOC/ subfolder containing CONTCAR, INCAR, and OUTCAR from spin-orbit coupling calculations, providing relativistic corrections to electronic energies and lattice parameters (Tables S2–S3 of the SM, and Table I of the main manuscript). (iv) A SOC/VCA/ subfolder containing FORCE_CONSTANTS and thermal_properties.yaml from VCA phonon calculations performed within the SOC framework, combining relativistic and vibrational thermodynamic corrections. The computed properties are used to map the AFM–FM magnetic crossover near MnTe0.75Sb0.25, demonstrate disorder- and spin-induced phonon broadening, identify a semiconductor-to-metal crossover, and quantify the pronounced magnetoelastic volume response near the magnetic phase boundary.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electron-phonon coupling strength from ab initio frozen-phonon approach

In this work, we propose a fast method for high-throughput screening of potential superconducting materials. The method is based on calculating metallic screening of zone-center phonon modes, which provides an accurate estimate for the electron-phonon coupling strength. This method is complementary to the recently proposed Rigid Muffin Tin (RMT) method, which amounts to integrating the electronphonon coupling over the entire Brillouin zone (as opposed to the zone center), but in a relatively inferior approximation. We illustrate the use of this method by applying it to MgB 2 , where the high-temperature superconductivity is known to be driven largely by the zone-center modes, and compare it to a sister compound AlB 2 . We further illustrate the usage of this descriptor by screening a large number of binary hydrides, for which accurate first-principle calculations of electron-phonon coupling have been recently published. Together with the RMT descriptor, this method opens a way to perform initial high-throughput screening in search of conventional superconductors via machine learning or data mining.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Diffusion energy barrier of Au on Bi 2 Se 3 : theory and experiment

The stability and diffusion of ultra-thin thermally deposited Au films on Bi 2 Se 3 was studied using scanning tunneling microscopy and density functional theory calculations. The Au/Bi 2 Se 3 interface is of interest as gold is predicted to provide excellent electrical contact while maintaining the spin-polarized characteristics of the electronic states in Bi 2 Se 3 that make the material attractive for spintronic applications. When deposited at room temperature, Au 10 covers the surface with tightly packed islands of nanometer scale dimension. The surface morphology is stable up to 400K. At this annealing temperature, Au atoms have sufficient energy to diffuse across the surface and aggregate into larger nanostructures. At 550K, the Bi 2 Se 3 surface is only sparsely covered, and the Au has formed clusters with length scales 5-10 times larger than the original islands formed at room temperature. Comparison of the experiment and first principle calculation lead to the conclusion that the diffusion energy barrier for Au on Bi 2 Se 3 is as high as 0.47 eV, 15 which is much larger than diffusion barriers on other van der Waals materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Modeling Short-Range Order in Disordered Rocksalt Cathodes by Pair Distribution Function Analysis

Pair distribution function (PDF) analysis is a powerful technique for the characterization of short-range order (SRO) in disordered materials. Accurate interpretation of experimental PDF data is critically reliant on the development of structural models that can account for local variations in site occupancies and bond lengths. To this end, we outline an approach to model SRO using first-principles calculations based on the cluster-expansion formalism. These methods are validated on neutron scattering data from two disordered rocksalt oxyfluorides, Li 1.3 Mn 0.4 Ti 0.3 O 1.7 F 0.3 and Li 1.3 Mn 0.4 Nb 0.2 Ti 0.1 O 1.7 F 0.3 . For each composition, we demonstrate that an average structure without any SRO fails to reproduce several key features in the experimental PDF. To pinpoint the origin of the suspected SRO in these materials, configurational and displacive effects were separately investigated using two disparate models. Special quasi-random structures were relaxed using density functional theory to account for local changes in bond lengths while maintaining a near-random ionic configuration. This leads to slightly improved accuracy but still misrepresents asymmetry in the first few peaks of the PDF. Monte Carlo simulations were performed to model configurational SRO on a fixed lattice, which by itself is shown to have a minimal influence on the PDF. Instead, we find that it is the bond length relaxations within environments created by SRO which controls the details of the PDF, thereby highlighting the subtle but important coupling between configurational and displacive SRO in disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Perpendicular magnetic anisotropy in half-metallic thin-film Co 2 CrAl

Magnetocrystalline anisotropy (MCA) is one of the key parameters investigated in spin-based electronics (spintronics), e.g. for memory applications. Here, we employ first-principles calculations to study MCA in thin film full Heusler alloy Co 2 CrAl. This material was studied in the past, and has been reported to exhibit half-metallic electronic structure in bulk geometry. In our recent work, we showed that it retains a 100% spin-polarization in thin-film geometry, at CrAl atomic surface termination. Here, we show that the same termination results in a perpendicular magnetic anisotropy, while Co surface termination not only destroys the half-metallicity, but also results in in-plane magnetization orientation. In addition, for films thicker than around 20 nm the contribution from magnetic shape anisotropy may become decisive, resulting in in-plane magnetization orientation. To the best of our knowledge, this is one of the first reports of half-metallic thin-film surfaces with perpendicular magnetic anisotropy. Furthermore, this result may be of interest for potential nano-device applications, and may stimulate a further experimental study of this and similar materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

NEXAFS Spectroscopy of P3HT and PBTTT at the Sulfur K-Edge

The sulfur K-edge near-edge X-ray absorption fine-structure (NEXAFS) spectra of the common conjugated polymers P3HT and PBTTT are studied from both experimental and theoretical perspectives. Experimental angle-resolved spectra are measured to characterize both the dominant peaks and the dichroism of the polymers. First-principles calculations using the density functional theory-based many-body X-ray absorption spectroscopy (MBXAS) method are performed for the two polymers as well as for the thiophene and thienothiophene units that make up the conjugated backbones of these polymers. Through this combined approach, we are able to confidently assign the observed peaks to specific molecular orbitals and identify the orientation of their transition dipole moments (TDMs) with respect to the coordinate frame of the polymer backbone. Here, in particular, we are able to establish the character and orthogonal nature of the three main low-energy peaks at: (i) 2473.5 eV, 1s → (S–C)­π* with TDM along the π-stacking direction; (ii) 2474.1 eV, 1s → (S–C)­σ* with TDM along the backbone; and (iii) 2475.4 eV, 1s → (S–C)­σ* with TDM perpendicular to the first two. By performing both gas-phase and solid-state simulations, and with reference to the NEXAFS spectra of thiophene and thienothiophene building blocks, the influences of polymerization and molecular packing are also explored.

Chantler, Paul Alexander [Monash University, Clayt↗
DOE OSTI2021

Low-frequency Raman signature of Ag-intercalated few-layer MoS 2

Density functional theory based calculations and experimental analysis on a limited number of real samples are performed to study how the presence of silver intercalated in the van der Waals gap of few-layer MoS 2 affects the low-frequency Raman active modes of this material. Silver is found to predominantly affect the breathing-like and shear-like vibrational modes of MoS 2 . These modes correspond to quasi-rigid movements of each individual layer with a restoring force (and, in turn, frequency) that is determined by modulations in the weak interlayer interactions. Noticeable red-shifts with increasing Ag concentration are found for all low-frequency modes. This finding indicates the potential for low-frequency vibrations as useful gauges for practical determination of silver concentration using low-frequency Raman spectroscopy. Finally, this work also describes a semi-classical linear chain model that allows to extrapolate results to a large number of layers. Further, first-principles calculations show how Raman spectroscopy can be used to characterize the quality of the two-dimensional interface between MoS 2 and a silver substrate.

36 MATERIALS SCIENCE↗