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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Inducing Order from Disordered Copolymers: On Demand Generation of Triblock Morphologies Including Networks

Disordered block copolymers are generally impractical in nanopatterning applications due to their inability to self-assemble into well-defined nanostructures. However, inducing order in low molecular weight disordered systems permits the design of periodic structures with smaller characteristic sizes. Here, we have induced nanoscale phase separation from disordered triblock copolymer melts to form well-ordered lamellae, hexagonally packed cylinders, and a triply periodic gyroid network structure, using a copolymer/homopolymer blending approach, which incorporates constituent homopolymers into selective block domains. This versatile blending approach allows one to precisely target multiple nanostructures from a single disordered material and can be applied to a wide variety of triblock copolymer systems for nanotemplating and nanoscale separation applications requiring nanoscale feature sizes and/or high areal feature densities.

Tureau, Maëva S.↗
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 OSTI2014

Modeling Electronic Quantum Transport with Machine Learning

We present a machine learning approach to solve electronic quantum transport equations of one-dimensional nanostructures. The transmission coefficients of disordered systems were computed to provide training and test data sets to the machine. The system’s representation encodes energetic as well as geometrical information to characterize similarities between disordered configurations, while the Euclidean norm is used as a measure of similarity. Errors for out-of-sample predictions systematically decrease with training set size, enabling the accurate and fast prediction of new transmission coefficients. The remarkable performance of our model to capture the complexity of interference phenomena lends further support to its viability in dealing with transport problems of undulatory nature.

97 MATHEMATICS AND COMPUTING↗
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↗
NASA NTRS1992

Fractal landscapes in biological systems: long-range correlations in DNA and interbeat heart intervals

Here we discuss recent advances in applying ideas of fractals and disordered systems to two topics of biological interest, both topics having common the appearance of scale-free phenomena, i.e., correlations that have no characteristic length scale, typically exhibited by physical systems near a critical point and dynamical systems far from equilibrium. (i) DNA nucleotide sequences have traditionally been analyzed using models which incorporate the possibility of short-range nucleotide correlations. We found, instead, a remarkably long-range power law correlation. We found such long-range correlations in intron-containing genes and in non-transcribed regulatory DNA sequences as well as intragenomic DNA, but not in cDNA sequences or intron-less genes. We also found that the myosin heavy chain family gene evolution increases the fractal complexity of the DNA landscapes, consistent with the intron-late hypothesis of gene evolution. (ii) The healthy heartbeat is traditionally thought to be regulated according to the classical principle of homeostasis, whereby physiologic systems operate to reduce variability and achieve an equilibrium-like state. We found, however, that under normal conditions, beat-to-beat fluctuations in heart rate display long-range power law correlations.

Non-NASA Center↗
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 OSTI2016

Emergent geometric frustration of artificial magnetic skyrmion crystals

Magnetic skyrmions have been receiving growing attention as potential information storage and magnetic logic devices since an increasing number of materials have been identified that support skyrmion phases. Explorations of artificial frustrated systems have led to new insights into controlling and engineering new emergent frustration phenomena in frustrated and disordered systems. Here, we propose a skyrmion spin ice, giving a unifying framework for the study of geometric frustration of skyrmion crystals (SCs) in a nonfrustrated artificial geometrical lattice as a consequence of the structural confinement of skyrmions in magnetic potential wells. The emergent ice rules from the geometrically frustrated SCs highlight a novel phenomenon in this skyrmion system: emergent geometrical frustration. We demonstrate how SC topology transitions between a nonfrustrated periodic configuration and a frustrated icelike ordering can also be realized reversibly. The proposed artificial frustrated skyrmion systems can be annealed into different ice phases with an applied current-induced spin-transfer torque, including a long-range ordered ice rule obeying ground state, as-relaxed random state, biased state, and monopole state. In conclusion, the spin-torque reconfigurability of the artificial skyrmion ice states, difficult to achieve in other artificial spin ice systems, is compatible with standard spintronic device fabrication technology, which makes the semiconductor industrial integration straightforward.

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 OSTI2014

Following atomistic kinetics on experimental timescales with the kinetic Activation–Relaxation Technique

The properties of materials, even at the atomic level, evolve on macroscopic time scales. Following this evolution through simulation has been a challenge for many years. For lattice-based activated diffusion, kinetic Monte Carlo has turned out to be an almost perfect solution. Various accelerated molecular dynamical schemes, for their part, have allowed the study on long time scale of relatively simple systems. There is still a desire and need, however, for methods able to handle complex materials such as alloys and disordered systems. In this paper, we review the kinetic Activation–Relaxation Technique (k-ART), one of a handful of off-lattice kinetic Monte Carlo methods, with on-the-fly cataloging, that have been proposed in the last few years.

36 MATERIALS SCIENCE↗
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 OSTI2014

Clustering versus non-clustering phase synchronizations

Clustering phase synchronization (CPS) is a common scenario to the global phase synchronization of coupled dynamical systems. In this work, a novel scenario, the non-clustering phase synchronization (NPS), is reported. It is found that coupled systems do not transit to the global synchronization until a certain sufficiently large coupling is attained, and there is no clustering prior to the global synchronization. To reveal the relationship between CPS and NPS, we further analyze the noise effect on coupled phase oscillators and find that the coupled oscillator system can change from CPS to NPS with the increase of noise intensity or system disorder. These findings are expected to shed light on the mechanism of various intriguing self-organized behaviors in coupled systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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 OSTI2017

First-principles Green-Kubo method for thermal conductivity calculations

We present a first-principles approach to calculate the phonon thermal conductivity based on the Green-Kubo formalism. In this approach, the density functional theory energy is distributed to each atom, and a two-step method in the molecular dynamics is introduced to avoid the atomic position R wrapping problem in a periodic system when the heat current is calculated. We show that this first-principles Green-Kubo approach is particularly suitable for disordered systems like amorphous and liquid, where the thermal conductivities are small due to strong phonon scattering but difficult to be calculated using anharmonic interaction energy. We have applied our method to liquid Ar, liquid Si, and amorphous Si. In this work, the calculated thermal conductivities agree well with previous theoretical and experimental results. We have also compared our method to previous works combining first-principles simulations with the Green-Kubo formalism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA

Background Adverse Drug Reactions (ADRs) are of great public health concern. FDA-approved drug labeling summarizes ADRs of a drug product mainly in three sections, i.e., Boxed Warning (BW), Warnings and Precautions (WP), and Adverse Reactions (AR), where the severity of ADRs are intended to decrease in the order of BW > WP > AR. Several reported studies have extracted ADRs from labeling documents, but most, if not all, did not discriminate the severity of the ADRs by the different labeling sections. Such a practice could overstate or underestimate the impact of certain ADRs to the public health. In this study, we applied the Medical Dictionary for Regulatory Activities (MedDRA) to drug labeling and systematically analyzed and compared the ADRs from the three labeling sections with a specific emphasis on analyzing serious ADRs presented in BW, which is of most drug safety concern. Results This study investigated New Drug Application (NDA) labeling documents for 1164 single-ingredient drugs using Oracle Text search to extract MedDRA terms. We found that only a small portion of MedDRA Preferred Terms (PTs), 3819 out of 21,920 or 17.42%, were observed in a whole set of documents. In detail, 466/3819 (12.0%) PTs were in BW, 2023/3819 (53.0%) were in WP, and 2961/3819 (77.5%) were in AR sections. We also found a higher overlap of top 20 occurring BW PTs with WP sections compared to AR sections. Within the MedDRA System Organ Class levels, serious ADRs (sADRs) from BW were prevalent in Nervous System disorders and Vascular disorders. A Hierarchical Cluster Analysis (HCA) revealed that drugs within the same therapeutic category shared the same ADR patterns in BW (e.g., nervous system drug class is highly associated with drug abuse terms such as dependence, substance abuse, and respiratory depression). Conclusions This study demonstrated that combining MedDRA standard terminologies with data mining techniques facilitated computer-aided ADR analysis of drug labeling. We also highlighted the importance of labeling sections that differ in seriousness and application in drug safety. Using sADRs primarily related to BW sections, we illustrated a prototype approach for computer-aided ADR monitoring and studies which can be applied to other public health documents.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

BES-HEP Connections: Common Problems in Condensed Matter and High Energy Physics, Round Table Discussion

On February 2, 2015 the Offices of High Energy Physics (HEP) and Basic Energy Sciences (BES) convened a Round Table discussion among a group of physicists on ‘Common Problems in Condensed Matter and High Energy Physics’. This was motivated by the realization that both fields deal with quantum many body problems, share many of the same challenges, use quantum field theoretical approaches and have productively interacted in the past. The meeting brought together physicists with intersecting interests to explore recent developments and identify possible areas of collaboration.... Several topics were identified as offering great opportunity for discovery and advancement in both condensed matter physics and particle physics research. These included topological phases of matter, the use of entanglement as a tool to study nontrivial quantum systems in condensed matter and gravity, the gauge-gravity duality, non-Fermi liquids, the interplay of transport and anomalies, and strongly interacting disordered systems. Many of the condensed matter problems are realizable in laboratory experiments, where new methods beyond the usual quasi-particle approximation are needed to explain the observed exotic and anomalous results. Tools and techniques such as lattice gauge theories, numerical simulations of many-body systems, and tensor networks are seen as valuable to both communities and will likely benefit from collaborative development.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1994

Effect of the degree of disorder on electronic and optical properties in random superlattices

A three-dimensional tight-binding calculation is developed and used to study disorder effects in a realistic random superlattice. With increasing disorder, a tendency of possible indirect-direct band-gap transition is suggested. Direct evidence of mobility edges between localized and extended states in three-dimensional random systems is given. As system disorder increases, the optical absorption intensities increase dramatically from five to forty-five times stronger than the ordered (GaAs)(sub 1)/(AlAs)(sub 1) superlattice. It is believed that the degree of disorder significantly affects electronic and optical properties of GaAs/AlAs random superlattices.

Wang, E. G.↗