Search NASA⌕ Search

SEARCH · Search NASA

Results for “First Principles”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

Spacecraft surface charging as a function of material properties

Spacecraft material behavior plays a very important role in space missions. Spacecraft immersed in plasma get charged by absorbing plasma particles and by emitting electrons from spacecraft surfaces via photoelectron and secondary electron emission. Spacecraft charging depends heavily on material properties such as work function, secondary electron yield, dielectric constant, and electric conductivity among other. Material properties are typically assumed to be static in charging models. However, it is well known that this is not the case in space. This makes spacecraft charging predictions very challenging. Material properties are well characterized before the spacecraft is put in orbit through characterization in the lab under clean conditions. However, once in space, material properties change due to the harsh and very dynamic space environment. We present a new capability to predict material behavior in space from first-principles modeling. The ongoing effort seeks to couple material models, density functional theory (DFT) and molecular dynamic (MD) codes, with environment models, plasma kinetic codes. This preliminary study will show results of surface charging as a function of material work function, dielectric constant, and conductivity.

36 MATERIALS SCIENCE↗

Controlling 4 f antiferromagnetic dynamics via itinerant electronic susceptibility

Optical manipulation of magnetism holds promise for future ultrafast spintronics, especially with lanthanides and their huge, localized 4 f magnetic moments. These moments interact indirectly by spin polarizing the conduction electrons (the Ruderman-Kittel-Kasuya-Yosida exchange interaction), influenced by interatomic orbital overlap, and the conduction electron's susceptibility around the Fermi level. Here, we study this influence in a series of 4 f antiferromagnets, Gd T 2 Si 2 ( T = Co, Rh, Ir), using ultrafast resonant x-ray diffraction. We observe a twofold increase in the ultrafast intersublattice angular momentum transfer rate between the materials, originating from modifications in the conduction electron susceptibility, as confirmed by first-principles calculations. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Interplay of pressure and temperature in modulating the magnetic properties of Cr 2 O 3

The spin-lattice interaction is pivotal in tailoring materials properties and is crucial for developing novel spintronic devices. Here, in the current work, we aim to explore the effects of pressure and temperature on the magnetic properties of Cr 2 O 3 to gain insights into its spin-lattice interaction. Through high-pressure neutron diffraction experiments, we observed an enhancement of the magnetic Bragg intensity with increasing pressure and it becomes more pronounced as the temperature increases. Results from first-principles calculations reveal a strengthening of the easy-axis magnetic anisotropy, doubling from 0 to 20 GPa. The exchange parameters, calculated based on this spin orientation, show an enhancement of the dominant magnetic interactions and an increase of magnetic ordering temperature when pressure increases. These findings suggest that the contributions from these two mechanisms are responsible for the observed increase in magnetic Bragg intensity.

Cr2O3↗

Structural, magnetic and electrical transport properties of YMnAl

The intermetallic compound YMnAl, crystallizing in the cubic C-15 (MgCu 2 -type) structure, was prepared using arc-melting and annealing. Rietveld refinement of the XRD pattern yields a lattice parameter of a = 7.816(1) Å⁠. The system exhibits antiferromagnetic order with a transition temperature of approximately 38 K, along with indications of a spin-glass–like phase. The effective magnetic moment, estimated from Curie–Weiss fitting of the susceptibility versus temperature curve, is 6.06 μ B /f.u. and the Curie–Weiss temperature of −79 K confirming the antiferromagnetic nature. Isothermal magnetization measurements below and above the Néel temperature show no saturation, with a maximum magnetization of 0.09 μ B /f.u observed at an applied field of 9 T. The temperature dependence of resistivity exhibits a negative temperature coefficient, characteristic of dirty metals. Hall effect measurements indicate the absence of an anomalous Hall contribution. The Hall coefficient RH, carrier concentration n, and mobility μ estimated from R XY (H) are -1.05×10 -8 m 3 /C, 5.92×10 26 m -3 and 1.05×10 -3 m 2 /V.s, respectively. Our first-principles calculations indicate that YMnAl in the orthorhombic (Imma) structure has the lowest energy; however, the substitutional disorder occurring during experimental synthesis may favor the formation of the cubic Laves phase.

Crystallography↗

Artificial-Intelligence Aided Design and Synthesis of Novel Layered 2D Multi-Principal Element Materials for Energy Storage (Final Report)

This DOE-EPSCoR project aimed to predict, synthesize, and characterize novel layered two-dimensional (2D) high-entropy materials (HEMs). These 2D-HEMs, composed of multiple principal elements in nearly equal concentrations, are distinct from traditional 2D materials (typically containing two or three elements) and conventional alloys (dominated by a single primary element with minor secondary additions). Their unique structural and compositional features enable significant lattice strain accommodation, resulting in enhanced electrode performance and potential applications in catalysis, hydrogen storage, sensing, quantum information technologies, and flexible electronics. The research focused on addressing four fundamental questions: (i) What combinations of elements can form stable and synthesizable 2D-HEMs? (ii) What mechanisms drive the stability and synthesizability of crystalline single-phase 2D-HEMs? (iii) How do local chemical disorder and defects influence the macroscopic electronic and mechanical properties? and (iv) What charge storage mechanisms are active in selectively synthesized 2D-HEMs for battery and supercapacitor electrode applications? To achieve these goals, the project employed an integrated theory-experiment approach, incorporating high-throughput first-principles calculations, theoretical modeling, data mining, experimental synthesis, and advanced characterization techniques. The advanced computing resources and state-of-the-art experimental characterization facilities at Oak Ridge National Laboratory (ORNL) were leveraged through collaboration. Beyond scientific advancements, the project contributed to workforce development. Two postdoctoral researchers and three graduate students at the University of Maine were trained through co-advising by ORNL scientists and collaborative interactions, strengthening their expertise in cutting-edge materials science.

36 MATERIALS SCIENCE↗

Data Science-Driven Discovery of Multimetallic Oxygen-cycle Electrocatalysts for Enhanced Energy Conversion

The overarching objective of this effort has been to combine state-of-the-art data science techniques, first principles analyses, and molecular-level characterization of electrocatalyst structure and reactivity to identify both in-situ mechanisms for degradation and transformation of electrocatalysts with highly complex catalytic structures and the impact of these transformations on catalytic activity. The primary catalysts of interest have been multielemental alloys, including high entropy alloys (HEA’s), which are characterized by a high degree of disorder and up to 20 different elements within a single nanoparticle. We have applied these strategies primarily to energy-critical oxygen cycle electrocatalytic reactions, including oxygen reduction (ORR), but we have also considered extensions to non-electrochemical chemistries such as ammonia synthesis and decomposition. We have made strong progress in the development of computational methods on both the level of machine learning methods development as well as first principles-based treatments of HEA’s, and we have leveraged these insights to propose promising HEA catalysts for the ORR. On the experimental side, we developed new HEA synthesis and characterization protocols relevant to these reactions and developed a database combining our experimental results with corresponding computational tools.

36 MATERIALS SCIENCE↗

VZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys vanadium-zirconium (V-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements V and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions.

36 MATERIALS SCIENCE↗

An alternative ground state of MnBi 2 Te 4 obtained by magnetic annealing

Magnetic topological insulators are extremely interesting because they combine the unique properties of topological insulators with magnetism. While as-grown MnBi 2 Te 4 single crystals exhibit an A-type antiferromagnetic (AFM) ordering at T N ≈ 24 K, annealed MnBi 2 Te 4 under 10 T leads to the change of the magnetic properties from AFM to superparamagnetic behavior with the trend of the magnetization saturation at 2 K. Correspondingly, the magnetotransport properties change as well, revealing large positive magnetoresistance with the linear field dependence at low temperatures. Through the first-principles calculations, we provide insight into the experimental results. Our investigation demonstrates that magnetic annealing is a powerful approach for manipulating material properties due to the nearly degenerate ground states in MnBi 2 Te 4 .

Electronic transport↗

TaTi_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys tantalum-titanium (Ta-Ti). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Hf and Nb. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on Air Force HPC11 cluster using the VASP 6.5.1. Additional methodology and file structure information is available in the dataset README.txt file.

36 MATERIALS SCIENCE↗

Heterostructural Alloy Phase Diagram for (Cd 1-x Zn x ) 3 As 2

Alloying the topological semimetal Cd 3 As 2 with Zn 3 As 2 provides a potential route for controlling the electronic properties. We predict the alloy phase diagram from first-principles calculations, considering that both end members have a crystal structure derived from the antifluorite lattice, but with different arrangements of the unoccupied cation sites. To overcome the limitations of the regular solution approximation and to include short-range order effects, we perform Monte Carlo simulations, parameterize the temperature dependence of the mixing enthalpy ΔH m , and perform thermodynamic integration of the free energy. The resulting phase diagram exhibits features that are unique to heterostructural alloy systems and provides computational predictions of solubility limits and composition ranges that are stable against spinodal decomposition.

36 MATERIALS SCIENCE↗

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Abstract Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a cost similar to that of conventional interatomic potential approaches. While MLIPs have been extensively tested across various classes of materials and molecules, a clear characterization of the anharmonic terms encoded in the MLIPs is lacking. Here, we benchmark popular MLIPs using the anharmonic vibrational Hamiltonian of ThO 2 in the fluorite crystal structure, which was constructed from density functional theory (DFT) using our highly accurate and efficient irreducible derivative methods. The anharmonic Hamiltonian was used to generate molecular dynamics (MD) trajectories, which were used to train three classes of MLIPs: Gaussian approximation potentials, artificial neural networks (ANN), and graph neural networks (GNN). The results were assessed by directly comparing phonons and their interactions, as well as phonon linewidths, phonon lineshifts, and thermal conductivity. The models were also trained on a DFT MD dataset, demonstrating good agreement up to fifth-order for the ANN and GNN. Our analysis demonstrates that MLIPs have great potential for accurately characterizing anharmonicity in materials systems at a fraction of the cost of conventional first principles-based approaches.

interatomic potentials↗

Inert Gas Element as Active Infrared‐Absorption Source and Donor in Silicon for Forbidden‐Wavelength Sensing

Intrinsic silicon (Si) is forbidden for infrared (IR) sensing at the communication wavelength like 1.31 or 1.55 µm due to the well‐known bandgap limitation. In this work, an unexpected physical picture of using argon (Ar) is identified, which is usually inert to the surrounding chemical environment and used as a protective agent in semiconductor processing, to overcome the IR‐sensing‐forbidden problem in Si. Here, in this work, it is shown by an analysis of a dynamic secondary ion mass spectrometer that such a Si, when exposed to laser pulse in Ar gas, can contain a very high dose of Ar up to 10 20 cm −3 even after 1300 days. First‐principles calculations, molecular dynamics, and Hall effect measurements reveal that, due to both steric and dynamic repulsions by Ar orbitals to Si dangling bonds, the Ar‐filled‐vacancy produces a much wider defect band inside the gap, which is not only responsible for strong infrared absorption, but also causes a significant increase in n‐type conductivity, both in line with experiments. The study proves that originally inert elements in fact can act as active impurities in semiconductors for advanced applications, which updates the current knowledge of defect physics.

36 MATERIALS SCIENCE↗

Accurate point defect energy levels from non-empirical screened range-separated hybrid functionals: The case of native vacancies in ZnO

We use density functional theory (DFT) with non-empirically tuned screened range-separated hybrid (SRSH) functionals to calculate the electronic properties of native zinc and oxygen vacancy point defects in ZnO, and we predict their defect levels for thermal and optical transitions in excellent agreement with available experiments and prior calculations that use empirical hybrid functionals. Furthermore, the ability of this non-empirical first-principles framework to accurately predict quantities of relevance to both bulk- and defect-level spectroscopy enables high-accuracy DFT calculations with non-empirical hybrid functionals for defect physics, at a reduced computational cost.

Defects↗

Machine learning assisted search for Fe–Co–C ternary compounds with high magnetic anisotropy

We employ a machine learning (ML)-guided framework to explore rare earth free magnetic materials, specifically focusing on Fe–Co–C ternary compounds for potential use in permanent magnets. Utilizing a specifically trained crystal graph convolutional neural network model, we efficiently screen a vast space of nearly a million substitutional structures to select 620 promising structures for further investigation by first-principles calculation. We predict five low-energy metastable Fe–Co–C compounds with formation energy less than 150 meV/atom above the convex hull. These compounds exhibit high magnetization (Js > 1.0 T) and significant magnetic anisotropy (K1 > 1.0 MJ/m3), making them promising candidates for permanent magnet applications. The phonon calculations indicate these compounds are dynamically stable. Our ML-guided framework demonstrates the utility of rapidly identifying novel materials with tailored magnetic properties.

36 MATERIALS SCIENCE↗

Age hardening response of Cu-30Ni alloys: The role of Si microalloying additions

Cu-30Ni alloys offer high strength and excellent corrosion resistance for maritime applications. While primarily a solid solution system, industrial alloys typically include microalloying additions of Fe, Mn, Nb and/or Si to enable age hardening. However, an understanding of the microstructural evolution during age hardening remains incomplete. Here, we conduct systematic ageing treatments and report the resulting hardness and microstructures. The Cu-30Ni alloy with Si aged at 650 °C for 6 h demonstrates significantly enhanced Vickers hardness, reaching ∼201 HV 1 compared to 103 HV 1 for the as-homogenised sample. Si-rich clusters and γ′ precipitates are identified, with their composition, size, and volume fraction quantified to determine their strengthening contributions. First-principles atomistic simulations elucidate the underlying formation mechanisms of these clusters and precipitates, highlighting the critical role of Si in driving their nucleation and growth. This study advances the design of high-strength, Cu alloys with the potential for corrosion resistance in demanding maritime environments.

Age hardening↗

Carrier confinement and alloy disorder exacerbate Auger–Meitner recombination in AlGaN ultraviolet light-emitting diodes

The quantum efficiency of AlGaN ultraviolet light-emitting diodes declines (droops) at increasing operating powers due to Auger–Meitner recombination (AMR). Using first-principles density-functional theory, we show that indirect AMR mediated by electron–phonon coupling and alloy disorder can induce bulk C coefficients as large as ~10 –31 cm 6 /s. Furthermore, we find that the confinement of carriers by polarization fields within quantum wells severely relaxes crystal-momentum conservation, which exacerbates the rate of AMR over radiative recombination by an order of magnitude relative to the bulk. Furthermore, this results in a striking decrease in quantum efficiency at high power. Suppressing polarization fields and jointly increasing the well width would greatly mitigate AMR and efficiency droop.

36 MATERIALS SCIENCE↗

Fast lithium ion diffusion in brownmillerite Li x Sr 2 Co 2 O 5

Transition metal oxides not only exhibits novel magnetic properties but also provides outstanding ionic transports. Ionic conductors have great potential for interesting tunable physical properties via ionic liquid gating and novel energy storage applications such as all-solid-state lithium batteries. In particular, low migration barriers and high hopping attempt frequency are the keys to achieve fast ion diffusion in solids. Taking advantage of the oxygen-vacancy channel in Li x Sr 2 Co 2 O 5 , we show that migration barriers of lithium ion are as small as 0.28–0.17 eV depending on the lithium concentration rates. Our first-principles calculation also investigated hopping attempt frequency and concluded the room temperature ionic diffusivity and ion conductivity are high as 10 −7 –10 −6 cm 2 s −1 and 10 −3 –10 −2 Scm −1 , respectively, which outperform most of perovskite-type, garnet-type, and sulfide Li-ion solid-state electrolytes. This work proves Li x Sr 2 Co 2 O 5 as a promising super-ionic conductor.

Crystallographic defects↗