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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Electronic Structure and Safety Insights into Prussian Blue Analog Cathode Behavior at Elevated Temperatures in Sodium-Ion Batteries

Prussian blue analogs (PBAs) represent promising cathode materials for sodium-ion batteries (SIBs) due to their high theoretical capacity, open framework structure, and use of earth-abundant elements. However, the high-temperature structural evolution, water content effects, and thermal safety of PBAs, particularly in charged states, remain poorly understood, hindering their practical deployment. Here, we investigate Na 2 Fe[Fe(CN) 6 ]·2H 2 O using thermogravimetric analysis (TGA), ex situ and in situ temperature-dependent X-ray absorption spectroscopy (XAS), and accelerated rate calorimetry (ARC). TGA and ex situ XAS confirm water loss between 150 and 200 °C, resulting in Fe 2+ oxidation, enhanced local symmetry, and uniform redox behavior that improves electrochemical performance. In situ XAS reveals irreversible structural changes above 240 °C, including ligand loss, Fe site distortion, and increased disorder, while ARC on charged electrodes shows minimal self-heating rates (<0.1 °C/min) up to 300 °C, indicating exceptional thermal stability without lattice oxygen release. These insights elucidate PBA thermal dynamics, demonstrating improved electrochemical performance of water-deficient PBAs and informing future material design and safety assessment for SIB applications.

batteries↗
DOE OSTI2022

Direct Observation of the Pressure-Induced Structural Variation in Gold Nanoclusters and the Correlated Optical Response

The ability to gradually modify the atomic structures of nanomaterials and directly identify such structural variation is important in nanoscience research. Here, we present the first example of a high-pressure single-crystal X-ray diffraction analysis of atomically precise metal nanoclusters. The pressure-dependent, subangstrom structural evolution of an ultrasmall gold nanoparticle, Au 25 S 18 , has been directly identified. We found that a 0.1 Å decrease of the Au–Au bond length could induce a blue-shift of 30 nm in the photoluminescence spectra of gold nanoclusters. From theoretical calculations, the origins of the blue-shift and enhanced photoluminescence under pressure are investigated, which are ascribed to molecular orbital symmetry and conformational locking, respectively. Here, the combination of the high-pressure in situ X-ray results with both theoretical and experimental optical spectra provides a direct and generalizable avenue to unveil the underlying structure–property relations for nanoclusters and nanoparticles which cannot be obtained through traditional physical chemistry measurements.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Pipe Parity Analysis of Seawater Desalination in the United States: Exploring Costs, Energy, and Reliability via Case Studies and Scenarios of Emerging Technology

As climate change-induced variables exacerbate water scarcities, the use of seawater reverse osmosis (SWRO) membrane desalination technology for treating seawater could potentially provide a long-term drought-proof source of drinking water. This study carried out a technoeconomic assessment (TEA) for three SWRO desalination plants in the U.S. and one in Israel to set baselines for the cost and energy consumption for seawater desalination. In addition, a breakeven curve for implementing SWRO desalination was estimated in relation to the cost of water conservation measures to meet drought-induced reduction of the traditional water supply. The results show that the cost of SWRO water production scales with the plant capacity while energy intensity is not dramatically different across the plants. The higher cost in some U.S. plants is due to high capital investment, including land acquisition and permitting. Variations in plant capacity utilization have the greatest impact on the levelized cost of water (LCOW) over the plant service life, suggesting the importance of reducing fouling and maintenance-related downtime. Scenario analysis of fixed labor cost reduction through process automation indicates investments in automation and sensing technology could result in long-term savings. Breakeven analysis shows the decision to adopt SWRO is highly dependent on the local cost associated with water conservation to meet water supply reduction. Moreover, a small reduction in SWRO cost can influence a shift toward the adoption of SWRO over water conservation measures. Incorporation of future water demand, water conservation potential, and water stress data around the nation indicates SWRO desalination could be an important contributor to the future municipal drinking water portfolio in the U.S.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Modulating the Molecular Geometry and Solution Self-Assembly of Amphiphilic Polypeptoid Block Copolymers by Side Chain Branching Pattern

Solution self-assembly of coil-crystalline diblock copolypeptoids has attracted increasing attention due to its capability to form hierarchical nanostructures with tailorable morphologies and functionalities. While the N-substituent (or side chain) structures are known to affect the crystallization of polypeptoids, their roles in dictating the hierarchical solution self-assembly of diblock copolypeptoids are not fully understood. Herein, we designed and synthesized two types of diblock copolypeptoids, i.e., poly(N-methylglycine)-b-poly(N-octylglycine) (PNMG-b-PNOG) and poly(N-methylglycine)-b-poly(N-2-ethyl-1-hexylglycine) (PNMG-b-PNEHG), to investigate the influence of N-substituent structure on the crystalline packing and hierarchical self-assembly of diblock copolypeptoids in methanol. With a linear aliphatic N-substituent, the PNOG blocks pack into a highly ordered crystalline structure with a board-like molecular geometry, resulting in the self-assembly of PNMG-b-PNOG molecules into a hierarchical microflower morphology composed of radially arranged nanoribbon subunits. By contrast, the PNEHG blocks bearing bulky branched aliphatic N-substituents are rod-like and prefer to stack into a columnar hexagonal liquid crystalline mesophase, which drives PNMG-b-PNEHG molecules to self-assemble into symmetrical hexagonal nanosheets in solution. A combination of time-dependent small/wide-angle X-ray scattering and microscopic imaging analysis further revealed the self-assembly mechanisms for the formation of these microflowers and hexagonal nanosheets. These results highlight the significant impact of the N-substituent architecture (i.e., linear versus branched) on the supramolecular self-assembly of diblock copolypeptoids in solution, which can serve as an effective strategy to tune the geometry and hierarchical structure of polypeptoid-based nanomaterials.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Structural Evidence of Interanionic Hydrogen Bonding in Phosphoric Acid Solutions

Interanionic hydrogen bonding (IAHB) is a noncovalent interaction between like-charged ions that challenges conventional electrostatic understanding. This study provides direct structural evidence of IAHB in concentrated aqueous phosphoric acid (PA) solutions, which exhibit >60% dissociation under these conditions. Oxygen K-edge X-ray absorption fine structure spectroscopy, combined with electron affinity time-dependent density functional theory calculations, reveals the formation of stable, cyclic phosphate-phosphate IAHB dimers at PA concentrations ≥7 M. Extended X-ray absorption fine structure data show distinct long-range ordering consistent with these dimers, and near-edge X-ray absorption fine structure spectra confirm a concentration-dependent transition from monomeric to dimeric species. Energy decomposition analysis through density functional theory shows that the formation of solution-phase IAHB is energetically favored and is attributed to polarization of and the charge transfer between the two fragments driven by the surrounding solvent molecules, in addition to the permanent electrostatics. These findings offers crucial structural insights into the H-bonded networks in concentrated PA, highlighting the critical role of solvent in facilitating anion–anion association.

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

Interdependent iron and phosphorus availability controls photosynthesis through retrograde signaling

Abstract Iron deficiency hampers photosynthesis and is associated with chlorosis. We recently showed that iron deficiency-induced chlorosis depends on phosphorus availability. How plants integrate these cues to control chlorophyll accumulation is unknown. Here, we show that iron limitation downregulates photosynthesis genes in a phosphorus-dependent manner. Using transcriptomics and genome-wide association analysis, we identify two genes, PHT4;4 encoding a chloroplastic ascorbate transporter and bZIP58 , encoding a nuclear transcription factor, which prevent the downregulation of photosynthesis genes leading to the stay-green phenotype under iron-phosphorus deficiency. Joint limitation of these nutrients induces ascorbate accumulation by activating expression of an ascorbate biosynthesis gene, VTC4 , which requires bZIP58. Furthermore, we demonstrate that chloroplastic ascorbate transport prevents the downregulation of photosynthesis genes under iron-phosphorus combined deficiency through modulation of ROS homeostasis. Our study uncovers a ROS-mediated chloroplastic retrograde signaling pathway to adapt photosynthesis to nutrient availability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Reductive catalytic fractionation of agricultural residue and energy crop lignin and application of lignin oil as antimicrobials

Cheap and abundant waste from bioethanol and agricultural processing industries are an alluring alternative feedstock for biorefineries. In this work, we employ reductive catalytic fractionation (RCF) to depolymerize, over Ru/C powder and Ru/Al 2 O 3 pellets, five herbaceous biomass feedstocks, namely corn stover, miscanthus, switchgrass, sugarcane bagasse, and wheat straw into phenolic monomers with high yields (~40 wt.% based on total (Klason + acid soluble) lignin and > 50 wt.% when stabilized using aldehydes), leaving behind a carbohydrate pulp residue. Interestingly, a polar solvent is sufficient to solubilize and fragment the lignin polymer into monomers without any catalyst. Here, contrary to woody biomass, where the monomer yields are positively correlated with the S-content of lignin, principal component analysis indicates that the monomer yields from herbaceous biomass depend on the content of lignin crosslinker – ferulate. Using NMR, we further identify α – 6 C-C linked oligomers formed from condensation reactions, explaining the unexpected low monomer yields of high β-O-4 herbaceous biomass. Recyclability experiments indicate that catalyst deactivation occurs through sintering, leaching, and fouling. Lignin oil from herbaceous biomass exhibits bacteriostatic effects against Staphylococcus aureus, highlighting a potential application in functional food development and as food or feed preservative.

09 BIOMASS FUELS↗
DOE OSTI2023

Spin dynamics of [1,2- 13 C 2 ]pyruvate hyperpolarization by parahydrogen in reversible exchange at micro Tesla fields

Hyperpolarization of 13 C-pyruvate via Signal Amplification By Reversible Exchange (SABRE) is an important recent discovery because of both the relative simplicity of hyperpolarization and the central biological relevance of pyruvate as a biomolecular probe for in vitro or in vivo studies. Here, we analyze the [1,2- 13 C 2 ]pyruvate-SABRE spin system and its field dependence theoretically and experimentally. We provide first-principles analysis of the governing 4-spin dihydride- 13 C 2 Hamiltonian and numerical spin dynamics simulations of the 7-spin dihydride- 13 C 2 –CH 3 system. Furthermore, the analytical and the numerical results are compared to matching systematic experiments. With these methods we unravel the observed spin state mixing of singlet states and triplet states at microTesla fields and we also analyze the dynamics during transfer from micro-Tesla field to high field for detection to understand the resulting spectra from the [1,2- 13 C 2 ]pyruvate-SABRE system.

13C pyruvate↗
DOE OSTI2026

Evaluating Supply Prioritization Strategies for Risk-Informed Decision Making in an Arbitrary Gas Network

Supply disruptions and infrastructure failures in natural gas networks present critical challenges to energy reliability and risk-informed planning. This study evaluates two supply prioritization strategies, Maximum Delivery Prioritization (MDP) and Demand-Based Prioritization (DBP), within an arbitrary natural gas network under conditions of supply shortage. Model performance under both strategies is assessed in response to node and edge failure using demand satisfaction metrics, system-wide and localized dependency scores, and geographic information system (GIS)-based spatial analysis. Results show that DBP better preserves supply for high-demand nodes, while MDP offers broader coverage. The underlying network topology plays a critical role in shaping prioritization outcomes. Integrated GIS visualization enhances the interpretability of vulnerability assessments, revealing structurally critical components and localized vulnerabilities. The proposed framework supports scalable, data-driven decision-making for infrastructure planners and engineers, enabling improved disruption recovery and efficiency in constrained natural gas networks. These insights contribute to the development of more robust energy systems capable of withstanding stress and disruptions.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2020

Investigating shear flow through continuum gyrokinetic simulations of limiter biasing in the Texas Helimak

Previous limiter-biasing experiments on the Texas Helimak, a simple magnetized torus, have been inconclusive on the effect of flow shear on turbulence levels. To explore this, the first gyrokinetic simulations of limiter biasing in the Helimak using the plasma physics code Gkeyll have been carried out, and results are presented here. For the scenarios considered, turbulence is mostly driven by the interchange instability, which depends on gradients of steady state density profiles. An analysis of both experimental and simulation data demonstrates that shear rates are mostly less than than local linear growth rates, and not all requirements for shear stabilization are met. Yet, the mostly vertical shear flow has an important effect on bulk transport and experimental steady-state density profiles, and changes to the gradients correspond to changes in turbulence levels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

${\tt Warm}$SPy: a numerical study of cosmological perturbations in warm inflation

We present ${\tt Warm}$SPy, a numerical code in Python designed to solve for the perturbations' equations in warm inflation models and compute the corresponding scalar power spectrum at CMB horizon crossing. In models of warm inflation, a radiation bath of temperature T during inflation induces a dissipation (friction) rate of strength Q ∝ T c /Φ m in the equation of motion for the inflaton field Φ. While for a temperature-independent dissipation rate (c = 0) an analytic expression for the scalar power spectrum exists, in the case of a non-zero value for c the set of equations can only be solved numerically. For c > 0 (c < 0), the coupling between the perturbations in the inflaton field and radiation induces a growing (decaying) mode in the scalar perturbations, generally parameterized by a multiplicative function G(Q) which we refer to as the scalar dissipation function. Using ${\tt Warm}$SPy, we provide an analytic fit for G(Q) for the cases of c = {3,1,-1}, corresponding to three cases that have been realized in physical models. Compared to previous literature results, our fits are more robust and valid over a broader range of dissipation strengths Q ϵ [10 -7 ,10 4 ]. Additionally, for the first time, we numerically assess the stability of the scalar dissipation function against various model parameters, inflationary histories as well as the effects of metric perturbations. As a whole, the results do not depend appreciably on most of the parameters in the analysis, except for the dissipation index c, providing evidence for the universal behaviour of the scalar dissipation function G(Q).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Exclusive π 0 p electroproduction off protons in the resonance region at photon virtualities 0.4 GeV 2 ≤ Q 2 ≤ 1 GeV 2

The limited electroproduction process e p → e ' p ' π 0 was measured in the range of photon virtualities Q 2 = 0.4 – 1.0 GeV 2 and the invariant mass range of the p π 0 system of W = 1.1 – 1.8 GeV. These kinematics are covered in exclusive π 0 electroproduction off the proton with nearly complete angular coverage in the p π 0 center-of-mass system and with high statistical accuracy. Nearly 36 000 cross-section points were measured, and the structure functions σ T + ε σ L , σ L T , and σ T T , were extracted via fitting the φ π 0 dependence of the cross section. A Legendre polynomial expansion analysis demonstrates the sensitivity of our data to high-lying N * and Δ * resonances with M > 1.6 GeV. As part of a broad effort to determine the electrocouplings of the N * and Δ * resonances using both single- and double-pion electroproduction, this dataset is key for the reliable extraction of the high-lying resonance electrocouplings from the combined isospin analysis of the N π and π + π - p channels.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗
DOE OSTI2021

Systemic effects of rising atmospheric vapor pressure deficit on plant physiology and productivity

Abstract Earth is currently undergoing a global increase in atmospheric vapor pressure deficit (VPD), a trend which is expected to continue as climate warms. This phenomenon has been associated with productivity decreases in ecosystems and yield penalties in crops, with these losses attributed to photosynthetic limitations arising from decreased stomatal conductance. Such VPD increases, however, have occurred over decades, which raises the possibility that stomatal acclimation to VPD plays an important role in determining plant productivity under high VPD. Furthermore, evidence points to more far‐ranging and complex effects of elevated VPD on plant physiology, extending to the anatomical, biochemical, and developmental levels, which could vary substantially across species. Because these complex effects are typically not considered in modeling frameworks, we conducted a quantitative literature review documenting temperature‐independent VPD effects on 112 species and 59 traits and physiological variables, in order to develop an integrated and mechanistic physiological framework. We found that VPD increase reduced yield and primary productivity, an effect that was partially mediated by stomatal acclimation, and also linked with changes in leaf anatomy, nutrient, and hormonal status. The productivity decrease was also associated with negative effects on reproductive development, and changes in architecture and growth rates that could decrease the evaporative surface or minimize embolism risk. Cross‐species quantitative relationships were found between levels of VPD increase and trait responses, and we found differences across plant groups, indicating that future VPD impacts will depend on community assembly and crop functional diversity. Our analysis confirms predictions arising from the hydraulic corollary to Darcy's law, outlines a systemic physiological framework of plant responses to rising VPD, and provides recommendations for future research to better understand and mitigate VPD‐mediated climate change effects on ecosystems and agro‐systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Genomic and Transcriptomic Evidence Supports Methane Metabolism in Archaeoglobi

Euryarchaeal lineages have been believed to have a methanogenic last common ancestor. However, members of euryarchaeal Archaeoglobi have long been considered nonmethanogenic and their evolutionary history remains elusive. Here, three high-quality metagenomic-assembled genomes (MAGs) retrieved from high-temperature oil reservoir and hot springs, together with three newly assembled Archaeoglobi MAGs from previously reported hot spring metagenomes, are demonstrated to represent a novel genus of Archaeoglobaceae, “Candidatus Methanomixophus.” All “Ca. Methanomixophus” MAGs encode an M methyltransferase (MTR) complex and a traditional type of methyl-coenzyme M reductase (MCR) complex, which is different from the divergent MCR complexes found in “Ca. Polytropus marinifundus.” In addition, “Ca. Methanomixophus dualitatem” MAGs preserve the genomic capacity for dissimilatory sulfate reduction. Comparative phylogenetic analysis supports a laterally transferred origin for an MCR complex and vertical heritage of the MTR complex in this lineage. Metatranscriptomic analysis revealed concomitant in situ activity of hydrogen-dependent methylotrophic methanogenesis and heterotrophic fermentation within populations of “Ca. Methanomixophus hydrogenotrophicum” in a high-temperature oil reservoir.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

CMLM (Co-Optimized Machine-Learned Manifolds) [SWR-23-41]

Co-optimized Machine-Learned Manifolds (CMLM) is a data-driven approach for developing reduced-order manifold models for high-dimensional chemically reacting systems. It involves a specially designed neural network, the training of which simultaneously optimizes linear combinations of species that define the manifold, nonlinear mapping to outputs of interest such as reaction rates, and (optionally) subfilter closure for large eddy simulation. This software package provides an implementation of the CMLM approach in Python using the PyTorch machine learning library. A few example cases are included, showing how the tool can be applied to different types of data from 0D and 1D reacting simulations performed using Cantera. The neural networks can be saved in a format that is readable by the Pele suite of combustion solvers for use in reacting computational fluid dynamics simulations. This software repository contains several python scripts to perform various tasks associated with the Co-optimized Machine Learned Manifolds (CMLM) model, which is described in Perry, Henry de Frahan, and Yellapantula, CNF, 2022 (https://doi.org/10.1016/j.combustflame.2022.112286). This includes not only the code that defines the CMLM model, but also scripts to generate suitable training data, scripts to pre-process the data, scripts to train the CMLM model, and scripts to plot the output, as well as various other helper files. The scripts depend on several commonly used python libraries for data analysis and chemical reaction computations. The trained models that result from this tool are designed to work with the an interface being implemented in the Pele suite of reacting flow solvers (https://github.com/AMReX-Combustion).

Perry, Bruce↗
DOE OSTI2020

Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases

Coupled 1D2D models emerged as an efficient solution for a two-dimensional (2D) representation of the floodplain combined with a fast one-dimensional (1D) schematization of the main channel. At the same time, high-performance computing (HPC) has appeared as an efficient tool for model acceleration. In this work, a previously validated 1D2D Central Processing Unit (CPU) model is combined with an HPC technique for fast and accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a Graphics Processing Unit (GPU) is presented. Since the data transfer between sub-domains and devices (CPU/GPU) may be the main potential drawback of this architecture, the test cases are selected to carry out a careful time analysis. Here, the results reveal the speed-up dependency on the 2D mesh, the event to be solved and the 1D discretization of the main channel. Additionally, special attention must be paid to the time step size computation shared between sub-models. In spite of the use of a hybrid CPU/GPU implementation, high speed-ups are accomplished in some cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗