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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electrochemically-Formed Disordered Rock Salt ω-Li x V 9 Mo 6 O 40 as a Fast-Charging Li-Ion Electrode Material

Electrochemically-formed disordered rock salt compounds are an emerging class of Li-ion electrode materials for fast-charging energy storage. However, the specific factors that govern the formation process and the resulting charge storage performance are not well understood. Here, we characterize the transformation mechanism and charge storage properties of an electrochemically-formed disordered rock salt from V 9 Mo 6 O 40 (VMO). The crystal structure of VMO has similar motifs to that of α-V 2 O 5 , a well-studied analogue, but VMO has less mechanical flexibility due to additional corner-sharing octahedra in its structure. As a result, VMO undergoes a single-step transformation pathway, which we characterize through operando X-ray diffraction, and forms an unusual highly distorted lamellar microstructure, as we show with high-resolution transmission electron microscopy. The resulting Li x VMO material shows fast charging and other electrochemical characteristics and performance typical of many nanomaterials, even though the material is composed of relatively large particles.

25 ENERGY STORAGE↗
NASA NTRS2011

Statistical Models of Fracture Relevant to Nuclear-Grade Graphite: Review and Recommendations

The nuclear-grade (low-impurity) graphite needed for the fuel element and moderator material for next-generation (Gen IV) reactors displays large scatter in strength and a nonlinear stress-strain response from damage accumulation. This response can be characterized as quasi-brittle. In this expanded review, relevant statistical failure models for various brittle and quasi-brittle material systems are discussed with regard to strength distribution, size effect, multiaxial strength, and damage accumulation. This includes descriptions of the Weibull, Batdorf, and Burchell models as well as models that describe the strength response of composite materials, which involves distributed damage. Results from lattice simulations are included for a physics-based description of material breakdown. Consideration is given to the predicted transition between brittle and quasi-brittle damage behavior versus the density of damage (level of disorder) within the material system. The literature indicates that weakest-link-based failure modeling approaches appear to be reasonably robust in that they can be applied to materials that display distributed damage, provided that the level of disorder in the material is not too large. The Weibull distribution is argued to be the most appropriate statistical distribution to model the stochastic-strength response of graphite.

Nemeth, Noel N.↗
DOE OSTI2024

Orientational analysis of atomic pair correlations in nanocrystalline indium oxide thin films

The application of grazing-incidence total X-ray scattering (GITXS) for pair distribution function (PDF) analysis using >50 keV X-rays from synchrotron light sources has created new opportunities for structural characterization of supported thin films with high resolution. Compared with grazing-incidence wide-angle X-ray scattering, which is only useful for highly ordered materials, GITXS/PDFs expand such analysis to largely disordered or nanostructured materials by examining the atomic pair correlations dependent on the direction relative to the surface of the supporting substrate. A characterization of nanocrystalline In 2 O 3 -derived thin films is presented here with in-plane-isotropic and out-of-plane-anisotropic orientational ordering of the atomic structure, each synthesized using different techniques. The atomic orientations of such films are known to vary based on the synthetic conditions. Here, an azimuthal orientational analysis of these films using GITXS with a single incident angle is shown to resolve the markedly different orientations of the atomic structures with respect to the planar support and the different degrees of long-range order, and hence, the terminal surface chemistries. It is anticipated that orientational analysis of GITXS/PDF data will offer opportunities to extend structural analyses of thin films by providing a means to qualitatively determine the major atomic orientation within nanocrystalline and, eventually, non-crystalline films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Structural disorder-driven topological phase transition in noncentrosymmetric BiTeI

In this work, we investigate using local structural disorder to induce a topologically nontrivial phase in a solid state system. Using first-principles calculations, we introduce structural disorder in the trivial insulator BiTeI and observe the emergence of a topological insulating phase. By modifying the bonding environments, the crystal-field splitting is enhanced, with spin-orbit interactions producing a band inversion in the bulk electronic structure. Analysis of the Wannier charge centers and the surface electronic structure reveals a strong topological insulator with Dirac surface states. Finally, we propose a prescription for inducing topological states from disorder in crystalline materials. Understanding how local environments produce topological phases is a key step for predicting disordered and amorphous topological materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Correlated Anion Disorder in Heteroanionic Cubic TiOF 2

Resolving anion configurations in heteroanionic materials is crucial for understanding and controlling their properties. For anion-disordered oxyfluorides, conventional Bragg diffraction cannot fully resolve the anionic structure, necessitating alternative structure determination methods. We have investigated the anionic structure of anion-disordered cubic (ReO 3 -type) TiOF 2 using X-ray pair distribution function (PDF), 19 F MAS NMR analysis, density functional theory (DFT), cluster expansion modeling, and genetic-algorithm structure prediction. Our computational data predict short-range anion ordering in TiOF 2 , characterized by predominant cis-[O 2 F 4 ] titanium coordination, resulting in correlated anion disorder at longer ranges. To validate our predictions, we generated partially disordered supercells using genetic-algorithm structure prediction and computed simulated X-ray PDF data and 19 F MAS NMR spectra, which we compared directly to experimental data. To construct our simulated 19 F NMR spectra, we derived new transformation functions for mapping calculated magnetic shieldings to predicted magnetic chemical shifts in titanium (oxy)fluorides, obtained by fitting DFT-calculated magnetic shieldings to previously published experimental chemical shift data for TiF 4 . We find good agreement between our simulated and experimental data, which supports our computationally predicted structural model and demonstrates the effectiveness of complementary experimental and computational techniques in resolving anionic structure in anion-disordered oxyfluorides. From additional DFT calculations, we predict that increasing anion disorder makes lithium intercalation more favorable by, on average, up to 2 eV, highlighting the significant effect of variations in short-range order on the intercalation properties of anion-disordered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Method for fabricating superconducting devices using a focused ion beam

Nano-scale junctions, wires, and junction arrays are created by using a focused high-energy ion beam to direct-write insulating or poorly conducting barriers into thin films of materials that are sensitive to disorder, including superconductors, ferromagnetic materials and semiconductors.

Cybart, Shane A.↗
DOE OSTI2023

Design of functional materials based on new principles of disorder

The main goal of the project for many years was to study and understand the jamming transition and the properties of the marginally jammed state, and to apply that understanding to real systems, including atomic, molecular, metallic and polymeric glasses, colloidal suspensions, granular materials, foams and emulsions, as well as the dynamics of systems driven away from the static jammed state by applying temperature or strain. As we gained greater insight into the jamming problem, we applied it to other big problems that had not previously been recognized as being related to jamming, such as memory formation, metamaterials design and learning.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Integrating Machine Learning Potential and X-ray Absorption Spectroscopy for Predicting the Chemical Speciation of Disordered Carbon Nitrides

Precise determination of atomic structural information in functional materials holds transformative potential and broad implications for emerging technologies. Spectroscopic techniques, such as X-ray absorption near-edge structure (XANES), have been widely used for material characterization; however, extracting chemical information from experimental probes remains a significant challenge, particularly for disordered materials. We present an integrated approach that combines atomic simulations, data-driven techniques, and experimental measurements to investigate chemical speciation of amorphous carbon nitride systems as a case study. Here, we discuss the development of machine learning potentials that can efficiently explore the vast configuration space of amorphous carbon nitrides. By employing statistical methods, this structural database enables the elucidation of the most representative local structures and how they evolve with chemical compositions and density. Density functional theory simulations are used to establish a correlation between the local structure and spectroscopic signatures, which then serve as the basis for interpreting and extracting chemical content from experimental data. Although our framework is specifically demonstrated for XANES and carbon nitrides, the approach described herein is readily adaptable as applied to other experimental characterization probes and materials classes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Modeling Intercalation Chemistry with Multiredox Reactions by Sparse Lattice Models in Disordered Rocksalt Cathodes

Modern battery materials can contain many elements with substantial site disorder, and their configurational state has been shown to be critical for their performance. The intercalation voltage profile is a critical parameter to evaluate the performance of energy storage. The application of commonly used cluster expansion techniques to model the intercalation thermodynamics of such systems ab initio is challenged by the combinatorial increase in configurational degrees of freedom as the number of species grows. Such challenges necessitate the efficient generation of lattice models without overfitting and proper sampling of the configurational space under the requirement of charge balance in ionic systems. In this work, we introduce a combined approach that addresses these challenges by (1) constructing a robust cluster expansion Hamiltonian using the sparse regression technique, including -norm regularization and structural hierarchy; and (2) implementing semigrand-canonical Monte Carlo to sample charge-balanced ionic configurations using the table-exchange method and an ensemble average approach. These techniques are applied to a disordered rocksalt oxyfluoride (LMNOF) that is part of a family of promising earth-abundant cathode materials. The simulated voltage profile is found to be in good agreement with experimental data and particularly provides a clear demonstration of the and oxygen contributions to the redox potential as a function of content.

25 ENERGY STORAGE↗
DOE OSTI2021

Fluorination-Enhanced Surface Stability of Cation-Disordered Rocksalt Cathodes for Li-Ion Batteries

Cation-disordered rocksalt (DRX) materials have emerged as a class of novel high-capacity cathodes for Li-ion batteries. However, commercialization of DRX cathodes will require reducing their capacity decay, which has been associated with oxygen loss during cycling. Recent studies have shown that fluorination of DRX cathodes can effectively reduce the oxygen loss and improve the cycling stability; however, the underlying atomic-scale mechanisms remain elusive. Herein, using a combination of electrochemical measurements, scanning transmission electron microscopy, and electron energy loss spectroscopy, we examine the correlation between the electrochemical properties and structural evolution in Mn-redox-based DRX cathodes, Li1.2Ti0.4-xMn0.4+xO2.0-xFx (x = 0 and 0.2). We find that fluorination strongly suppresses structural amorphization and void formation initiated from the particle surface, therefore greatly enhancing the cyclability of the cathode. We further reveal a novel rocksalt-to-spinel-like structural transformation in the DRX bulk, which surprisingly contributes to a gradual capacity increase during cycling. Our results provide important insight for the design of novel DRX cathodes with high capacity and long cycle life.

Li, Linze↗
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multisublattice cluster expansion study of short-range ordering in iron-substituted strontium titanate

Owing to the challenges in obtaining realistic atomic configurations in large chemical phase spaces, it is not straightforward to describe structure–property relations in materials exhibiting configurational disorder. One example is iron-substituted strontium titanate (SrTi 1–x Fe x O 3–d , STF), a promising perovskite-derivative cathode material in solid oxide fuel cells that exhibits full solid solubility 0 ≤ x ≤ 1 and a tendency to exhibit short-range order. Here we demonstrate a multisublattice cluster expansion (CE) framework and apply it to STF across the full composition range. The CE approach is distinct from more traditional CE formulations in that clusters are defined explicitly by the chemical species distributed among multiple sublattices, rather than via cluster functions of occupation variables with decoration. The modified CE approach makes it easy to distinguish meaningful chemical interactions that are harder to extract from conventional CE, since for the latter chemical identity in a cluster is expressed as a product of site occupations. The least absolute shrinkage and selection operator (LASSO) is implemented as a regression analysis tool to select key clusters and avoid overfitting. We demonstrate this formulation on STF, and show that it can accurately predict configurational energies in comparison to conventional CE. From the key clusters, we identify that short-range ordering between substitutional Fe and oxygen vacancies (V O ) results in the formation of Fe–VO strings. In addition, we consider the stability of STF through CE-based Monte Carlo (MC) simulations and confirm the presence of superstructures that were previously observed in transmission electron microscopy. In this work, analysis of atomic configurations from MC samples reveals variations in the oxidation state of Fe atoms, which can be explained by the ordering tendency of Fe and V O . The cluster description and selection formalism described here may be applied to other disordered multisublattice systems for accurate and efficient material modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Structural origin of disorder-induced ion conduction in NaFePO 4 cathode materials

Diffusion in NaFePO 4 can be enhanced through amorphization. Based on computations using DFT and machine learning potentials, we ascribe this phenomenon to the formation of less constrained Na-ion environments upon disordering. Most modern battery technologies depend on solid-state crystalline cathode materials. However, some of these materials are constrained by the low ionic conductivity of their most stable phases. An example of this is maricite (NaFePO 4 ). Interestingly, experiments have shown that maricite can improve its rate capability through disordering (amorphization). However, experimental characterization of amorphous cathode materials remains a major challenge, hindering a clear understanding of the structural origin of the disorder-induced improvement in sodium-ion mobility. To address this, we here employ molecular dynamics simulations by first training a machine learning potential for NaFePO 4 based on the atomic cluster expansion approach and a batch active learning potential parameterization scheme. This potential is then applied to explore the structural and dynamical properties of NaFePO 4 glasses as cathode materials. Specifically, we investigate the effect of glass structure on sodium-ion diffusion, revealing the relative influences of short-range and medium-range order features. We find significant heterogeneity in sodium-ion diffusivity in the glass, with fast-conducting ions residing in less constrained atomic environments with fewer P and Fe neighbors. These more mobile ions are also surrounded by larger ring-type structures. Overall, the results and developed approach present promising avenues for developing high-performance glassy cathodes for next-generation batteries.

Christensen, Rasmus↗
DOE OSTI2021

Challenges and transformative opportunities in superconductor vortex physics

In superconductors, the motion of vortices introduces unwanted dissipation that is disruptive to applications. Fortunately, material defects can immobilize vortices, acting as vortex pinning centers, which engenders dramatic improvements in superconductor material properties and device operation. This has motivated decades of research into developing methods of tailoring the disorder landscape in superconductors to increase the strength of vortex pinning. Yet, efficacious materials engineering still eludes us. The electromagnetic properties of real (disordered) superconducting materials cannot yet be reliably predicted, such that designing superconductors for applications remains a largely inefficient process of trial and error. This is ultimately due to large gaps in our knowledge of vortex dynamics: the field is challenged by the extremely complex interplay between vortex elasticity, vortex-vortex interactions, and material disorder. Here, we review obstacles and recent successes in understanding and controlling vortex dynamics in superconducting materials and devices. We further identify major open questions and discuss opportunities for transformative research in the field. This includes improving our understanding of vortex creep, determining and reaching the ceiling for the critical current, advanced microscopy to garner accurate structure-property relationships, frontiers in predictive simulations and the benefits of artificial intelligence, as well as controlling and exploiting vortices in quantum information applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Modeling phase transformations in Mn-rich disordered rocksalt cathodes with machine-learning interatomic potentials

Mn-rich disordered rocksalt (DRX) cathode materials exhibit a phase transformation from a disordered to a partially disordered spinel-like structure (δ-phase) during electrochemical cycling. Here, in this computational study, we use charge-informed molecular dynamics with a fine-tuned CHGNet foundation potential to investigate the phase transformation in LixMn 0.8 Ti 0.1 O 1.9 F 0.1 . Our results indicate that transition metal migration occurs and reorders to form the spinel-like ordering in an FCC anion framework. The transformed structure contains a higher concentration of nontransition metal (0-TM) face-sharing channels, which are known to improve Li transport kinetics. Analysis of the Mn valence distribution suggests that the appearance of tetrahedral Mn 2+ is a consequence of spinel-like ordering, rather than the trigger for cation migration as previously suggested. Calculated equilibrium intercalation voltage profiles demonstrate that the δ-phase, unlike the ordered spinel, exhibits solid-solution signatures at low voltage. A higher Li capacity is obtained than in the DRX phase. This study provides atomic insights into solid-state phase transformation and its relation to experimental electrochemistry, highlighting the potential of machine-learning interatomic potentials for understanding complex oxide materials.

Zhong, Peichen [University of California, Berkeley↗
DOE OSTI2023

Quantitative Decoupling of Oxygen-Redox and Manganese-Redox Voltage Hysteresis in a Cation-Disordered Rock Salt Cathode

Pronounced voltage hysteresis in Li-excess cathode materials is commonly thought to be associated with oxygen redox. However, these materials often possess overlapping oxygen and transition-metal redox, whose contributions to hysteresis between charge and discharge are challenging to distinguish. In this work, a two-step aqueous redox titration is developed with the aid of mass spectrometry (MS) to quantify oxidized lattice oxygen and Mn 3+/4+ redox in a representative Li-excess cation-disordered rock salt—Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO). Two MS-countable gas molecules evolve from two separate titrant-analyte reactions, thereby allowing Mn and O redox capacities to be decoupled. The decoupled O and Mn redox coulombic efficiencies are close to 100% for the LMTO cathode, indicating high charge-compensation reversibility. As incremental Mn and O redox capacities are quantitatively decoupled, each redox voltage hysteresis is further evaluated. Overall, LMTO voltage hysteresis arises not only from an intrinsic charge-discharge voltage mismatch related to O redox, but also from asymmetric Mn-redox overvoltages. The results reveal that O and Mn redox both contribute substantially to voltage hysteresis. In conclusion, this work further shows the potential of designing new analytical workflows to experimentally quantify key properties, even in a disordered material having complex local coordination environments.

25 ENERGY STORAGE↗
DOE OSTI2020

Ab initio typical medium theory of substitutional disorder

Here, by merging single-site typical medium theory with density-functional theory, we introduce a self-consistent framework for electronic-structure calculations of materials with substitutional disorder which takes into account Anderson localization. The scheme and details of the implementation are presented and applied to the hypothetical alloy Li$_cBe_{1-c}$, and the results are compared with those obtained with the coherent potential approximation. Furthermore, we demonstrate that Anderson localization suppresses ferromagnetic order for a very low concentration of (i) carbon impurities substituting oxygen in $MgO_{1-c}C_c$ and (ii) manganese impurities substituting magnesium in $Mg_{1-c}Mn_cO$ for the low-spin magnetic configuration.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Materials design, synthesis, and transport properties of disordered rare-earth Zintl bismuthides with the anti -Th 3 P 4 structure type

The synthesis, structural elucidation, and transport properties of the extended series Ca 4–x RE x Bi 3 (RE = Y, La–Nd, Sm, Gd–Tm, and Lu; x ≈ 1) and Ca 4–x RE x Bi 3–δ Sb δ (RE = La, Ho, Er, and Lu; x ≈ 1, δ ≈ 1.5) are presented. Structural elucidation is based on single-crystal X-ray diffraction data and confirms the chemical drive of Ca4Bi3 with the cubic anti-Th 3 P 4 structure type (space group I4 ¯3d, no. 220, Z = 4) into a Zintl phase by the introduction of trivalent rare-earth atoms. The structure features complex bonding, heavy elements, and electron count akin to that of valence-precise semiconductors, making it an ideal target for thermoelectrics development. Introducing crystallographic site disorders at the cation site for the Ca 4–x RE x Bi 3 phase and both the cation and anion sites for the Ca 4–x RE x Bi 3–δ Sb δ phase brings about additional desirable characteristics for thermoelectric materials in the context of tuning knobs for lowering thermal conductivity. Electronic structure calculations of idealized Ca 3 YBi 3 and Ca 3 LaBi 3 compounds indicate the opening of indirect bandgaps at the Fermi level with magnitudes Eg = 0.38 eV and 0.57 eV, respectively. The electrical resistivity ρ(T) of some of the investigated phases measured on single crystals evolve in a metallic manner with magnitudes of order 1.4 mΩ cm near 500 K, thus supporting the notion of a degenerate semiconducting state, with the temperature dependence of the Seebeck coefficient α(T) suggesting the p-type behavior. Furthermore, the low electrical resistivity and the realization of a degenerate semiconducting state in the title phases present a window of opportunity for optimizing their carrier concentrations for enhanced thermoelectric performance.

36 MATERIALS SCIENCE↗