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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hidden Local Symmetry Breaking in a Kagome-Lattice Magnetic Weyl Semimetal

Exploring the relationship between intriguing physical properties and structural complexity is a central topic in studying modern functional materials. Co 3 Sn 2 S 2 , a newly discovered kagome-lattice magnetic Weyl semimetal, has triggered intense interest owing to the intimate coupling between topological semimetallic states and peculiar magnetic properties. However, the origins of the magnetic phase separation and spin glass state below T C in this ordered compound are two unresolved yet important puzzles in understanding its magnetism. Here, we report the discovery of local symmetry breaking surprisingly co-emerges with the onset of ferromagnetic order in Co 3 Sn 2 S 2 , by a combined use of neutron total scattering and half-polarized neutron diffraction. An anisotropic distortion of the cobalt kagome lattice at the atomic/nano level is also found, with distinct distortion directions among the two Co1 and four Co2 atoms. The mismatch of local and average symmetries occurs below T C , indicating that Co 3 Sn 2 S 2 evolves to an intrinsically lattice disordered system when the ferromagnetic order is established. The local symmetry breaking with intrinsic lattice disorder provides new understanding of the puzzling magnetic properties. Our density functional theory (DFT) calculation indicates that the local symmetry breaking is expected to reorient local ferromagnetic moments, unveiling the existence of the ferromagnetic instability associated with the lattice instability. Furthermore, DFT calculation unveils that the local symmetry breaking could affect the Weyl property by breaking the mirror plane. In conclusion, our findings highlight the fundamentally important role that the local symmetry breaking plays in advancing our understanding on the magnetic and topological properties in Co 3 Sn 2 S 2 , which may draw attention to explore the overlooked local symmetry breaking in Co 3 Sn 2 S 2 , its derivatives and more broadly in other topological Dirac/Weyl semimetals and kagome-lattice magnets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗
DOE OSTI2024

Controlling the Manifold of Polariton States Through Molecular Disorder

Exciton polaritons, arising from the interaction of electronic transitions with confined electromagnetic fields, have emerged as a powerful tool to manipulate the properties of organic materials. However, standard experimental and theoretical approaches overlook the significant energetic disorder present in most materials now studied. Using the conjugated polymer P3HT as a model platform, the degree of energetic disorder is systematically tuned and a corresponding redistribution of photonic character within the polariton manifold is observed. Based on these subtle spectral features, a more generalized approach is developed to describe strong light–matter coupling in disordered systems that captures the key spectroscopic observables and provides a description of the rich manifold of states intermediate between bright and dark. Finally, applied to a wide range of organic systems, the method challenges prevailing notions about ultrastrong coupling and whether it can be achieved with broad, disordered absorbers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ice, glass, and solid phases in artificial spin systems with quenched disorder

We present a numerical study on a disordered artificial spin-ice system, which interpolates between the long-range ordered square ice and the fully degenerate shakti ice. Starting from the square-ice geometry, disorder is implemented by adding vertical/horizontal magnetic islands to the center of some randomly chosen square plaquettes of the array at different densities. When no island is added, we have ordered square ice. When all square plaquettes have been modified, we obtain shakti ice, which is disordered yet in a topological phase corresponding to the Rys F-model. In between, geometrical frustration due to these additional center spins disrupts the long-range Ising order of square ice, giving rise to a spin-glass regime at low temperatures. The artificial spin system proposed in our work provides an experimental platform to study the interplay between quenched disorder and geometrical frustration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Solid 3D Li–S Battery Design via Stacking 2D Conductive Microporous Coordination Polymers and Amorphous Li–S Layers

To make a lithium-sulfur (Li-S) battery practical, not only high gravimetric energy capacity is important, but also high volumetric energy capacity will be required. The currently explored Li-S cathode designs often deploy systems with liquid electrolyte infiltration, hence with relatively low volumetric capacity. In the current study, we theoretically test a compact solid three-dimensional (3D) design (more like a Li-ion battery cathode than a conventional Li-S cathode) consisted of a sandwich structure alternating between the two-dimensional (2D) Mn-hexaaminobenzene-based coordination polymer (2D Mn-HAB-CP) layer and the amorphous Li-S layer. We study the theoretical limits for both its gravimetric and volumetric energy capacity, as well as its structural stability and Li diffusion within the cathode system. To study the Li diffusion within an amorphous system, we also develop a pull-atom molecular dynamics (PA-MD) to calculate the barrier heights of such disordered systems. We reveal the mechanism that determines the Li diffusion in the amorphous layer of the system. Overall, we find such a 3D solid Li-S cathode can be practical, with sufficient large gravimetric and volumetric energy capacity, as well as the Li diffusion constant. It also solves many other common Li-S cathode problems, from Li polysulfide dissolution to electrical insulating, and structure instabilities.

25 ENERGY STORAGE↗
DOE OSTI2024

Characterizing structural features of two-dimensional particle systems through Voronoi topology

This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range of nominally disordered systems, and robustly describe complex structures such as grain boundaries. This paper also introduces two-dimensional functionality into the open-source software program VoroTop which automates this analysis. This software package is built on a recently-introduced multithreaded version of V ORO ++, enabling the analysis of systems with billions of particles on high-performance computer architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Light-matter interaction in complex photonics systems: introduction

This feature issue presents original work on light-matter interaction in complex photonics systems, which has been a continuously growing area of optics and photonics, in terms of both importance and breadth. From disordered systems to highly controlled micro- and nanostructures, recent decades have witnessed the onset of random media, photonic crystals, metamaterials, plasmonics, and, more recently, metasurfaces.

42 ENGINEERING↗
DOE OSTI2022

Bandgap analysis and carrier localization in cation-disordered ZnGeN 2

The bandgap of ZnGeN 2 changes with the degree of cation site disorder and is sought in light emitting diodes for emission at green to amber wavelengths. By combining the perspectives of carrier localization and defect states, we analyze the impact of different degrees of disorder on electronic properties in ZnGeN 2 , addressing a gap in current studies, which largely focus on dilute or fully disordered systems. The present study demonstrates changes in the density of states and localization of carriers in ZnGeN 2 calculated using bandgap-corrected density functional theory and hybrid calculations on partially disordered supercells generated using the Monte Carlo method. We use localization and density of states to discuss the ill-defined nature of a bandgap in a disordered material and identify site disorder and its impact on the structure as a mechanism controlling electronic properties and potential device performance. Decreasing the order parameter results in a large reduction of the bandgap. The reduction in bandgap is due, in part, to isolated, localized states that form above the valence band continuum associated with nitrogen coordinated by more zinc than germanium. The prevalence of defect states in all but the perfectly ordered structure creates challenges for incorporating disordered ZnGeN 2 into optical devices, but the localization associated with these defects provides insight into the mechanisms of electron/hole recombination in the material.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Superconducting phase transitions in disordered NbTiN films

Suppression of superconductivity in disordered systems is a fundamental problem of condensed matter physics. Here we investigate superconducting niobium-titanium-nitride (Nb 1-x Ti x N) thin films grown by the atomic layer deposition (ALD) with slightly different growth process parameters. We observe a smooth crossover from the disorder-driven superconductor-normal metal transition (SMT) to the superconductor-insulator transition (SIT) via the intermediate Bose metal state detected by the low-temperature saturation of the temperature dependence of the sheet resistance. We demonstrate that the SIT via the intervening Bose metal state occurs if the sheet resistance of the film in the maximum, R max prior to the superconducting drop of R(T), exceeds R q = h/4e 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Mitigating Band Tailing in Kesterite Solar Absorbers: Ab Initio Quantum Dynamics

Open-circuit voltage deficits are limiting factors in kesterite solar cells. Addressing this issue by suppressing band tailing and nonradiative charge recombination is essential for enhancing the performance. We employ ab initio nonadiabatic molecular dynamics to elucidate the origin of band tailing and charge losses and propose a mitigation strategy. The simulations show that Cu–Zn disorder, associated with antisite defect clusters [Cu Zn +Zn Cu ], is a significant source of band tailing in kesterites, as evidenced by the much larger Urbach energy in disordered than ordered kesterites. Cu–Zn disorder gives rise to new sulfur-centered coordination polyhedra, increases structural inhomogeneity, changes electrostatic potential at sulfur centers, and shifts the S(3p) orbital energy. Differences in the S(3p)/Cu(3d) and S(3p)/Sn(5s) hybridization strengths and the S(3p) orbital energy shift reduce the band gap by 0.37 eV. Furthermore, Cu–Zn disorder enhances vibrational motion of sulfur anions and surrounding cations, increasing band gap fluctuations by 15 meV. The stronger electron–phonon interactions reduce charge carrier lifetimes and limit the kesterite solar cell efficiency. Partial substitution of Zn with Cd facilitates structural ordering and significantly suppresses band tailing, particularly in disordered systems. The improvement can be attributed to the larger atomic radius and mass of Cd, which weakens bonding around the anion, suppresses S-related vibrations within the covalent tetrahedra, and reduces nonadiabatic coupling, thereby increasing charge carrier lifetimes. The reported results establish the key influence of cation disorder on band tailing and reduced charge carrier lifetimes in kesterites and highlight cation disorder engineering as a strategy to achieve high-efficiency kesterite solar cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Active Site Engineering via Optimizing the Heterogeneous Support Structure for Single-Atom Catalysis

Supported single-atom catalysts show a large range of activities and selectivities that depend on the local environment of the catalytic sites. Here a theory-based optimization strategy is presented that is based on a density functional theory determination of the transition states and intermediates for a low-dimensional coordinate representation of the heterogeneity of the active sites. The approach is applied to a vanadium catalyst on an amorphous SiO 2 support that involves a large kinetic network described using a full chemistry model. Without assuming a priori scaling relations or mechanism reduction, the optimal state of heterogeneity is found to lie at atomic configurations where the activation energies for two distinct key chemical processes are equal. It is found a posteriori that the behavior of the system is consistent with linear free energy scaling relations in the randomness parameters. The energetic span theory proves quite useful in reducing the full chemistry model to a small number of key reactions. The use of a nonlinear optimization algorithm in combination with energetic span theory provides significant simplification in treating disordered systems.

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

Effective Field Theory of Random Quantum Circuits

Quantum circuits have been widely used as a platform to simulate generic quantum many-body systems. In particular, random quantum circuits provide a means to probe universal features of many-body quantum chaos and ergodicity. Some such features have already been experimentally demonstrated in noisy intermediate-scale quantum (NISQ) devices. On the theory side, properties of random quantum circuits have been studied on a case-by-case basis and for certain specific systems, and a hallmark of quantum chaos—universal Wigner–Dyson level statistics—has been derived. This work develops an effective field theory for a large class of random quantum circuits. The theory has the form of a replica sigma model and is similar to the low-energy approach to diffusion in disordered systems. The method is used to explicitly derive the universal random matrix behavior of a large family of random circuits. In particular, we rederive the Wigner–Dyson spectral statistics of the brickwork circuit model by Chan, De Luca, and Chalker [Phys. Rev. X 8, 041019 (2018)] and show within the same calculation that its various permutations and higher-dimensional generalizations preserve the universal level statistics. Finally, we use the replica sigma model framework to rederive the Weingarten calculus, which is a method of evaluating integrals of polynomials of matrix elements with respect to the Haar measure over compact groups and has many applications in the study of quantum circuits. The effective field theory derived here provides both a method to quantitatively characterize the quantum dynamics of random Floquet systems (e.g., calculating operator and entanglement spreading) and a path to understanding the general fundamental mechanism behind quantum chaos and thermalization in these systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Efficient and interpretable graph network representation for angle-dependent properties applied to optical spectroscopy

Abstract Graph neural networks are attractive for learning properties of atomic structures thanks to their intuitive graph encoding of atoms and bonds. However, conventional encoding does not include angular information, which is critical for describing atomic arrangements in disordered systems. In this work, we extend the recently proposed ALIGNN (Atomistic Line Graph Neural Network) encoding, which incorporates bond angles, to also include dihedral angles (ALIGNN-d). This simple extension leads to a memory-efficient graph representation that captures the complete geometry of atomic structures. ALIGNN-d is applied to predict the infrared optical response of dynamically disordered Cu(II) aqua complexes, leveraging the intrinsic interpretability to elucidate the relative contributions of individual structural components. Bond and dihedral angles are found to be critical contributors to the fine structure of the absorption response, with distortions that represent transitions between more common geometries exhibiting the strongest absorption intensity. Future directions for further development of ALIGNN-d are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantum simulation: From spin models to gauge-gravity correspondence

Quantum many-body systems with coherent and controllable interactions enable the realization of novel quantum materials, the quantum simulation of problems that cannot be simulated on classical computers, computational systems that are exponentially faster than existing classical algorithms, and the direct investigation of the conjectured duality between gravitational theories and quantum field theories. This project focusses on quantum phase transitions in strongly interacting many-body spin systems, and in particular on the dynamical evolution near the critical point and across the phase transition. The dynamics of a large quantum system containing more than 50 qubits is investigated in various critical regimes. In particular, the Kibble-Zurek transition has been characterized and critical exponents have been measured. Furthermore, quantum many-body scars have been observed and characterized for the first time. We are investigating the Kibble-Zurek mechanism in the quantum phase transition in one dimension from a disordered system to a system with ordering induced by Rydberg interactions between neighboring atoms. The Kibble-Zurek mechanism describes the formation of topological defects as a system evolves across a phase transitions, and is expected to apply to a large number of problems, including cosmology, where it should describe the structure of domain formation in the early universe.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

SARS-CoV-2 Infection-Associated Aortic Thrombosis Treated with Oral Factor Xa Inhibition

Coronavirus disease 2019 (COVID-19) is an acute complex systemic disorder caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).While SARS-CoV-2 is known to cause significant pulmonary disease, various extrapulmonary manifestations of COVID-19 have also been reported. Growing evidence suggests that COVID-19 is associated with coagulopathy leading to micro and macrovascular complications. Although in patients with COVID-19, venous thromboembolic events are more frequent, arterial thrombosis also occurs at an increased rate. These often lead to acute life-threatening ischemia, which requires urgent diagnosis and treatment. We present case reports of two patients with an abnormal thrombus formation in the thoracic aorta who recently overcame COVID-19, which led to systemic embolism and splenic infarction. Ambulatory oral factor Xa inhibitor therapy led to aortic thrombosis resolution in both patients.

Strýčková, Alena↗
DOE OSTI2021

Immunophenotypic characterization and therapeutics effects of human bone marrow- and umbilical cord-derived mesenchymal stromal cells in an experimental model of sepsis

Highlights: • Mesenchymal stromal cells (MSCs) may be a therapeutic option for sepsis. • Bone marrow (BM) vs. umbilical cord (UC) -MSCs induce different M1/M2 gene profiles. • In a CLP model of sepsis, only BM-MSCs improved survival and bacterial clearance. Sepsis is a complicated multi-system disorder characterized by a dysregulated host response to infection. Despite substantial progress in the understanding of mechanisms of sepsis, translation of these advances into clinically effective therapies remains challenging. Mesenchymal Stromal Cells (MSCs) possess immunomodulatory properties that have shown therapeutic promise in preclinical models of sepsis. The therapeutic effects of MSCs may vary depending on the source and type of these cells. In this comparative study, the gene expression pattern and surface markers of bone marrow-derived MSCs (BM-MSCs) and umbilical cord-derived MSCs (UC-MSCs) as well as their therapeutic effects in a clinically relevant mouse model of polymicrobial sepsis, cecal ligation and puncture (CLP), were investigated. The results showed remarkable differences in gene expression profile, surface markers and therapeutic potency in terms of enhancing survival and pro/anti-inflammatory responses between the two MSC types. BM-MSCs improved survival concomitant with an enhanced systemic bacterial clearance and improved inflammatory profile post CLP surgery. Despite some improvement in the inflammatory profile of the septic animals, treatment with UC-MSCs did not enhance survival or bacterial clearance. Overall, the beneficial therapeutic effects of BM-MSCs over UC-MSCs may likely be attributed to their pro-inflammatory function, and to some extent anti-inflammatory features, reflected in their gene expression pattern enhancing macrophage polarization to M1/M2 phenotypes resulting in a balanced pro- and anti-inflammatory response against polymicrobial sepsis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The structural information filtered features (SIFF) potential: Maximizing information stored in machine-learning descriptors for materials prediction

Machine learning inspired potentials continue to improve the ability for predicting structures of materials. However, many challenges still exist, particularly when calculating structures of disordered systems. These challenges are primarily due to the rapidly increasing dimensionality of the feature-vector space which in most machine-learning algorithms is dependent on the size of the structure. In this article, we present a feature-engineered approach that establishes a set of principles for representing potentials of physical structures (crystals, molecules, and clusters) in a feature space rather than a physically motivated space. Our goal in this work is to define guiding principles that optimize information storage of the physical parameters within the feature representations. In this manner, we focus on keeping the dimensionality of the feature space independent of the number of atoms in the structure. Our Structural Information Filtered Features (SIFF) potential represents structures by utilizing a feature vector of low-correlated descriptors, which correspondingly maximizes information within the descriptor. We present results of our SIFF potential on datasets composed of disordered (carbon and carbon–oxygen) clusters, molecules with C 7 O 2 H 2 stoichiometry in the GDB9-14B dataset, and crystal structures of the form (Al x Ga y In z ) 2 O 3 as proposed in the NOMAD Kaggle competition. Our potential's performance is at least comparable, sometimes significantly more accurate, and often more efficient than other well-known machine-learning potentials for structure prediction. However, primarily, we offer a different perspective on how researchers should consider opportunities in maximizing information storage for features.

36 MATERIALS SCIENCE↗