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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Layered-rocksalt intergrown cathode for high-capacity zero-strain battery operation

Abstract The dependence on lithium-ion batteries leads to a pressing demand for advanced cathode materials. We demonstrate a new concept of layered-rocksalt intergrown structure that harnesses the combined figures of merit from each phase, including high capacity of layered and rocksalt phases, good kinetics of layered oxide and structural advantage of rocksalt. Based on this concept, lithium nickel ruthenium oxide of a main layered structure ( R $$\bar{3}$$ 3 ¯ m ) with intergrown rocksalt ( Fm $$\bar{3}$$ 3 ¯ m ) is developed, which delivers a high capacity with good rate performance. The interwoven rocksalt structure successfully prevents the anisotropic structural change that is typical for layered oxide, enabling a nearly zero-strain operation upon high-capacity cycling. Furthermore, a design principle is successfully extrapolated and experimentally verified in a series of compositions. Here, we show the success of such layered-rocksalt intergrown structure exemplifies a new battery electrode design concept and opens up a vast space of compositions to develop high-performance intergrown cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2025

Comparative Analysis of TCR and TCR-pMHC Complex Structure Prediction Tools

The rapid development of computational approaches for predicting the structures of T cell receptors (TCRs) and TCR-peptide-major histocompatibility (TCR-pMHC) complexes, accelerated by AI breakthroughs such as AlphaFold, has made it feasible to calculate these structures with increasing accuracy. Although these tools show great potential, their relative accuracy and limitations remain unclear due to the lack of standardized benchmarks. Here, we systematically evaluate seven tools for predicting isolated TCR structures together with six tools for predicting TCR-pMHC complex structures. The methods include homology-based approaches, general prediction tools using AlphaFold, TCR-specific tools derived from AlphaFold2, and the newly developed tFold-TCR model. The evaluation uses a post-training data set comprising 40 αβ TCRs and 27 TCR-pMHC complexes (21 Class I and 6 Class II). Model accuracy is assessed at global, local, and interface levels using a variety of metrics. We find that each tool offers distinct advantages in various aspects of its predictions. AlphaFold2, AlphaFold3, and tFold-TCR excel in overall accuracy of TCR structure prediction, and TCRmodel2 and AlphaFold2 perform well in overall accuracy of TCR-pMHC structure prediction. However, TCR-specific tools derived from AlphaFold2 show lower accuracy in the framework region than both homology-based methods and general-purpose tools such as AlphaFold, and challenges remain for all in modeling CDR3 loops, docking orientations, TCR-peptide interfaces, and Class II MHC-peptide interfaces. Furthermore, these findings will guide researchers in selecting appropriate tools, emphasize the importance of using multiple evaluation metrics to assess model performance, and offer suggestions for improving TCR and TCR-pMHC structure prediction tools.

Chemical structure↗
DOE OSTI2023

A New Semistructured Algebraic Multigrid Method

Multigrid methods are well suited to large massively parallel computer architectures because they are mathematically optimal and display good parallelization properties. Since current architecture trends are favoring regular compute patterns to achieve high performance, the ability to express structure has become much more important. The hypre software library provides high-performance multigrid preconditioners and solvers through conceptual interfaces, including a semistructured interface that describes matrices primarily in terms of stencils and logically structured grids. This paper presents a new semistructured algebraic multigrid (SSAMG) method built on this interface. The numerical convergence and performance of a CPU implementation of this method are evaluated for a set of semistructured problems. In conclusion, SSAMG achieves significantly better setup times than hypre’s unstructured AMG solvers and comparable convergence. In addition, the new method is capable of solving more complex problems than hypre’s structured solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

The prediction of protein 3D structure from amino acid sequence is a computational grand challenge in biophysics and plays a key role in robust protein structure prediction algorithms, from drug discovery to genome interpretation. The advent of AI models, such as AlphaFold, is revolutionizing applications that depend on robust protein structure prediction algorithms. To maximize the impact, and ease the usability, of these AI tools we introduce APACE, AlphaFold2 and advanced computing as a service, a computational framework that effectively handles this AI model and its TB-size database to conduct accelerated protein structure prediction analyses in modern supercomputing environments. We deployed APACE in the Delta and Polaris supercomputers and quantified its performance for accurate protein structure predictions using four exemplar proteins: 6AWO, 6OAN, 7MEZ, and 6D6U. Using up to 300 ensembles, distributed across 200 NVIDIA A100 GPUs, we found that APACE is up to two orders of magnitude faster than off-the-self AlphaFold2 implementations, reducing time-to-solution from weeks to minutes. This computational approach may be readily linked with robotics laboratories to automate and accelerate scientific discovery.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Pareto Optimal and Dual-Objective Geometric and Structural Design of an Underwater Kite for Closed-Loop Flight Performance

This paper presents the formulation and results for a control-aware optimization of the combined geometric and structural design of an energy-harvesting underwater kite. Because kite-based energy-harvesting systems, both airborne and underwater, possess strong coupling between closed-loop flight control, geometric design, and structural design, consideration of all three facets of the design within a single codesign framework is highly desirable. However, while prior literature has addressed one or two attributes of the design at a time, this work constitutes the first comprehensive effort aimed at addressing all three. In particular, focusing on the goals of power maximization and mass minimization, we present a codesign formulation that fuses a geometric optimization tool, structural optimization tool, and closed-loop flight efficiency map. The resulting integrated codesign tool is used to address two mathematical optimization formulations that exhibit subtle differences: a Pareto optimal formulation and a dual-objective formulation that focuses on a weighted power-to-mass ratio as the techno-economic metric of merit. Further, based on the resulting geometric and structural designs, using a mediumfidelity closed-loop simulation tool, the proposed formulation is shown to achieve more than three times the powerto-mass ratio of a previously published, unoptimized benchmark design.

42 ENGINEERING↗
DOE OSTI2020

Performance and usability enhancements for continuous subgraph matching queries on graph-structured data

A query graph, which includes vertices and edges, represents a query on graph-structured data. The query graph is decomposed into query subgraphs. A network analysis tool performs continuous subgraph matching queries to facilitate analysis of computer network traffic, social media events, or other streams of data represented as a dynamic data graph (graph-structured data). This can help identify emerging trends in the data. Some features of the network analysis tool enhance performance by effectively utilizing distributed computing resources (including processing cores and memory at different nodes of a cluster) to speed up the process of updating the dynamic data graph and detecting matches of query subgraphs. Features of a query graph building tool enhance usability by providing intuitive ways to specify query graphs and their subgraphs. Features of a results visualization tool enhance usability by providing an intuitive way to present the results of continuous subgraph matching queries.

Choudhury, Sutanay↗
DOE OSTI2025

The Alamo multiphysics solver for phase field simulations with strong-form mechanics and block structured adaptive mesh refinement

Alamo is a high-performance scientific code that uses block-structured adaptive mesh refinement to solve such problems as: the ignition and burn of solid rocket propellant, plasticity, damage and fracture in materials undergoing loading, and the interaction of compressible flow with eroding solid materials. Alamo is powered by AMReX, and provides a set of unique methods, models, and algorithms that enable it to solve solid-mechanics problems (coupled to other physical behavior such as fluid flow or thermal diffusion) using the power of block-structured adaptive mesh refinement.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ba₁₋ₓSrₓFeO₃₋ᵧ as an Improved Oxygen Carrier for Chemical Looping Air Separation: A Computational and Experimental Study

Chemical looping air separation (CLAS) is a promising method to generate pure carbon-dioxide from fuel combustion with a pure oxygen stream, which is produced through the capture, and targeted release, of oxygen from the atmosphere using a solid oxide carrier. The performance of this process depends on the redox characteristics of the oxide carrier. Using experimental oxygen-temperature-programmed desorption (TPD) and thermogravimetric analysis (TGA), the study shows that Ba₀․₇₅Sr₀․₂₅FeO₃ has improved oxygen storage capacity (OSC), oxidation, and reduction kinetics over pristine SrFeO₃ at temperatures ranging from 300-500 °C. The redox energetics computed by using first-principles density functional theory (DFT) calculations also depict the measured trend establishing it as an important descriptor of the measured performance. The Ba₁₋ₓSrₓFeO₃₋ᵧ depicts a Sr-substitution and oxygen stoichiometry induced structural phase transition from hexagonal at low temperatures to pseudo-cubic phase with higher OSC up to T=400 °C. Also, the mechanism leading to this structural phase transition is identified by performing electronic and vibrational structural calculations. This presentation was given on March 8, 2024 at the APS March Meeting in Minneapolis, MN.

Acharya, Shree Ram↗
DOE OSTI2022

High-performance organic photodetectors enabled by a refined fibrillar multiphase morphology

Film morphology of donor:acceptor blend layers plays a critical role in photon-to-current efficiency and dark/noise current of organic photodetectors (OPDs). One effective approach to manipulate crystallization and mesoscale phase separation of such blend layers is sequential casting (SC). However, the guiding strategies to control the morphology and the impacts on OPD performance of the SC films remain elusive, as the film structural evolution during SC is different from conventional blend casting (BC). In this report a refined fibrillar multiphase morphology is demonstrated by SC in an NT812:IEICO-4F blend film, where the high-quality IEICO-4F crystallites infiltrate the robust NT812 fibril network from the surface to the bulk. Such a morphology leads to improved charge generation and collection, reduced trap states, and enhanced charge block capability of resultant device, enabling simultaneous achievement of high external quantum efficiency and low dark/noise current. A maximum special detectivity of 5 × 10 13 Jones is achieved at 860 nm under –0.1 V, which is among the highest detectivities for vis-to-NIR OPDs. The linear dynamic range and response speed are also improved. Such enhancements are parallelly observed from OPD devices based on other blend systems with similar fibrillar refinement, which provides guidelines for film structure manipulation towards high OPD performance.

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

Evaluation of electrochemical performance and redox activity of Fe in Ti doped layered P2-Na0.67Mn0.5Fe0.5O2 cathode for sodium ion batteries

Here, we report a wet synthesis-based titanium doping strategy to improve the structural stability and electrochemical performances, such as cycling stability and rate capability, of P2-type Na 0.67 Fe 0.5 Mn 0.5 O 2 layered oxide cathodes. Through Ti 4+ doping aimed at replacing some of the Mn and Fe atoms in the crystal structure, effective mitigation of the Jahn Teller distortion caused by active Mn 3+ before charging and Fe 4+ after charging was achieved. X-ray diffraction (XRD), Raman spectroscopy, Electrochemical Impedance Spectroscopy (EIS) and Mössbauer spectroscopy were used to investigate the effects of the Ti 4+ dopant before and after cycling. It was observed that Ti 4+ doping increased the Na layer thickness, minimized the lattice volume strain, showed better structural stability, minimally decreased Fe migration to the Na layer, and lowered charge transfer resistance in these P2-type cathodes. Overall, our reported synthesis methodology and electrochemical characterizations highlight the feasibility of Ti doping in sodium layered oxide P2-type cathodes.

25 ENERGY STORAGE↗
DOE OSTI2020

EPRI Demonstration of an Autonomous Site Characterization Vehicle - 20523

A substantial effort is applied in performing radiological characterization of structures and land areas during decommissioning of a nuclear facility. This includes multiple surveys of land areas and large structures to support eventual site release under the Multi Agency Survey and Site Investigation Manual (MARSSIM, Reference 1). These surveys are typically performed using manually delivered systems, which is time consuming and labor intensive. Radiological surveys intentionally follow a prescribed protocol with respect to areas covered, scan speeds, responses to elevated readings, required detector offsets, the need for repeat measurements, etc. Based on these attributes, combined with the repetitive effort of performing surveys over large areas, automation of radiological characterization techniques has a high potential to be successful and promises substantial benefit. EPRI has performed a project that resulted in the development and demonstration of an autonomous site characterization system. This EPRI project focused on building surfaces and the surfaces of large land areas as these configurations lend themselves more readily to automated survey. The project included: - Identification of the requirements for an autonomous site characterization system; - A survey of existing control systems that use automation to conduct characterization of structures and land areas. - As no fully adequate systems were identified, a complete system was developed that utilized commercially available detection and analysis systems and a self driving vehicle owned by EPRI. The system was demonstrated at the Kewaunee nuclear power plant site in the fall of 2019. The demonstration included: - Autonomous surveys of floor areas inside the Auxiliary Building at Kewaunee after manually controlled mapping of the survey areas. - For land areas, the vehicle autonomously surveyed areas using travel paths had been preprogrammed onto an internet available map of area. In this case, GPS coordinates from the preprogramming were used for navigation by the vehicles guidance system. This paper summarizes the characterization system development and system demonstration which will also be published in an EPRI report in the first half of 2020. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function

Computational biology is one of many scientific disciplines ripe for innovation and acceleration with the advent of high-performance computing (HPC). In recent years, the field of machine learning has also seen significant benefits from adopting HPC practices. In this work, we present a novel HPC pipeline that incorporates various machine-learning approaches for structure-based functional annotation of proteins on the scale of whole genomes. Our pipeline makes extensive use of deep learning and provides computational insights into best practices for training advanced deep-learning models for high-throughput data such as proteomics data. We showcase methodologies our pipeline currently supports and detail future tasks for our pipeline to envelop, including large-scale sequence comparison using SAdLSA and prediction of protein tertiary structures using AlphaFold2.

Gao, Mu↗
DOE OSTI2024

Exciton engineering of 2D Ruddlesden–Popper perovskites by synergistically tuning the intra and interlayer structures

Designing two-dimensional halide perovskites for high-performance optoelectronic applications requires deep understanding of the structure-property relationship that governs their excitonic behaviors. However, a design framework that considers both intra and interlayer structures modified by the A-site and spacer cations, respectively, has not been developed. Here, we use pressure to synergistically tune the intra and interlayer structures and uncover the structural modulations that result in improved optoelectronic performance. Under applied pressure, (BA) 2 (GA)Pb 2 I 7 exhibits a 72-fold boost of photoluminescence and 10-fold increase of photoconductivity. Based on the observed structural change, we introduce a structural descriptor χ that describes both the intra and interlayer characteristics and establish a general quantitative relationship between χ and photoluminescence quantum yield: smaller χ correlates with minimized trapped excitons and more efficient emission from free excitons. Building on this principle, we design a perovskite (CMA) 2 (FA)Pb 2 I 7 that exhibits a small χ and an impressive photoluminescence quantum yield of 59.3%.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Altermagnetic behavior in OsO2: Parallels with RuO2

This dataset contains input and output files from DFT simulations used to reproduce the electronic and phonon band structures of bulk OsO₂ and RuO₂. The files include data from initial electronic structure and phonon calculations performed with Hubbard-U correction (i.e., Antiferromagnetic, AFM) and without Hubbard-U correction (i.e., Non-magnetic, NM). The electronic structure calculations are provided both with and without spin-orbit coupling (SOC). The computed electronic properties are compared with existing literature, while the calculated phonon density of states (PhDOS) is compared with experimental PhDOS.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ground-State In-Plane Light-Holes in GaAs/AlGaAs Structures [Book Chapter]

We have performed low-temperature magnetoluminescence, far-infrared cyclotron resonance, and magneto-transport measurements on narrow (4.5 nm) GaAs/Al 0.25 Ga 0.75 As single quantum-wells. The ground state in-plane valence band was found to be light and very nonparabolic, i.e., at zone center, the valence band mass is m v ≈ 0. 1 and for E f ≈ 10 meV, m v ≈ 0.25.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhanced Electrocatalytic and Selective CO 2 -to-CO Reduction by a Rhenium(I) Complex Bearing 6,6′-Substituted 2,2′-Bipyridines

The electrochemical reduction of CO 2 (CO 2 RR) into value-added chemicals offers a promising route toward a circular carbon economy and reduced reliance on fossil fuels. A detailed understanding of the structural and electronic factors governing the performance of molecular CO 2 RR electrocatalysts is essential for the design of efficient, tunable systems. Here, in this study, we report a series of rhenium(I) complexes, fac-[Re I (6,6′-(R) 2 -bpy)(CO) 3 Cl] (bpy = 2,2′-bipyridine; R = mesityl (mes), 2,4,6-triisopropylphenyl (trip), or isophthalic acid (phth)) and evaluate their electrocatalytic activity. Among these, fac-[Re I (6,6′-(mes) 2 -bpy)(CO) 3 Cl] exhibited the highest performance, enabling selective CO 2 -to-CO conversion for 1 hour with Faradaic efficiency (FE) > 97%, representing an unprecedented activity level for a Re-bpy catalysts. Single-crystal X-ray diffraction and density functional theory (DFT) calculations indicated that favorable CO 2 binding could be promoted by the tilting of the 6,6′-(mes)2-bpy ligand (from the Re-CO coordination plane), providing mechanistic insight into the observed enhancement. The study consequently demonstrates a rational correlation between the CO 2 electrocatalytic performance of Re-bpy catalysts and their structural variations, as derived from X-ray data and corroborated by computational modeling.

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

Low Temperature Cyclic Deformation Behavior of Ultrafine-grained Pure Magnesium (Final Technical Report)

The primary goal of the project is to explore the fundamental deformation and fatigue failure mechanisms for magnesium with a hexagonal close packed (HCP) crystal structure. It is important to perform the project for several reasons. Firstly, magnesium is the lightest structural metal and its application in various structural components can reduce the final component weight.

36 MATERIALS SCIENCE↗