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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Carbohydrate Deacetylase Unique to Gut Microbe Bacteroides Reveals Atypical Structure

Bacteroides are often the most abundant, commensal species in the gut microbiome of industrialized human populations. One of the most commonly detected species is Bacteroides ovatus. It has been linked to benefits like the suppression of intestinal inflammation but is also correlated with some autoimmune disorders, for example irritable bowel disorder (IBD). Bacterial cell surface carbohydrates, like capsular polysaccharides (CPS), may play a role in modulating these varied host interactions. Recent studies have begun to explore the diversity of CPS loci in Bacteroides; however, there is still much unknown. Here, we present structural and functional characterization of a putative polysaccharide deacetylase from Bacteroides ovatus (BoPDA) encoded in a CPS biosynthetic locus. We solved four high resolution crystal structures (1.36-1.56 Å) of the enzyme bound to divalent cations Co 2+ , Ni 2+ , Cu 2+ , or Zn 2+ and performed carbohydrate binding and deacetylase activity assays. Structural analysis of BoPDA revealed an atypical domain architecture that is unique to this enzyme, with a carbohydrate esterase 4 (CE4) superfamily catalytic domain inserted into a carbohydrate binding module (CBM). Additionally, BoPDA lacks the canonical CE4 His-His-Asp metal binding motif and our structures show it utilizes a noncanonical His-Asp dyad to bind metal ions. BoPDA is the first protein involved in CPS biosynthesis from B. ovatus to be characterized, furthering our understanding of significant biosynthetic processes in this medically relevant gut microbe.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Nine Canyon Long-Duration Energy Storage: A Feasibility Study

The Nine Canyon Long Duration Energy Storage (LDES) Feasibility Study explores the technical and economic viability of deploying advanced energy storage technologies at Energy Northwest's (EN) Nine Canyon (9C) Wind Project site in Benton County, Washington. Supported by the Washington State Department of Commerce and the U.S. Department of Energy’s Office of Electricity under its LDES Voucher Program, the study represents a collaborative effort between EN, Pacific Northwest National Laboratory (PNNL), and ARES North America. At the core of this effort is the development of a generalized techno-economic modeling framework and evaluation tool designed to assess the value proposition of LDES projects across a variety of contexts. The modeling tool is technology-agnostic and accommodates user-defined parameters such as rated power, energy duration, round-trip efficiency, capital and operational costs, and dispatch constraints. It also integrates economic inputs, including market prices, energy revenue structures, and financing parameters to evaluate performance through key metrics. The tool provides utilities with a transparent, adaptable platform to support decision-making, investment prioritization, and portfolio planning for various storage technologies. To guide scenario design and interpretation, the study first surveyed the LDES technology landscape, including lithium-ion batteries, flow batteries, non-hydro gravity storage, and thermo-mechanical systems, comparing cost trajectories, technical performance, safety and hazards, materials sourcing and recyclability, and spatial/siting considerations. This literature-grounded review highlights technology trade-offs and reinforces the need to align technology choice with site characteristics, use cases, and project objectives. A companion chapter examines ownership structures (EN ownership, third-party ownership, shared models) and offtake options (energy marketing, capacity/energy PPAs, time-of-use PPAs, block-delivery PPAs, and tolling), where PPAs (power purchase agreements) represent contractual arrangements for buying and selling electricity. The chapter also highlights implications for risk allocation, capital access, operational control, and revenue certainty. The study also evaluates supervisory control and data acquisition (SCADA) and transmission interconnection pathways, options include upgrading the existing SCADA or deploying a dedicated LDES controller, with attention to protection schemes, data telemetry, cybersecurity, and regulatory coordination with BPA. In addition, an ARES-specific geotechnical and hydrology assessment presented in the appendix screens multiple corridors for slope stability, bearing capacity, cut-and-fill magnitude, and stormwater behavior.

25 ENERGY STORAGE↗
DOE OSTI2023

Graphitized Mesoporous Engineered Carbon Support for Fuel Cell Applications

As proton exchange membrane fuel cells mature into commercial devices capable of powering a wide range of stationary and automotive applications, they need materials with tunable properties to improve their performance and durability. Carbon supports used for platinum (Pt) nanoparticle dispersion is typically based on a furnace black-type material with a random structure, thereby hindering progress in catalyst development. To address this challenge, engineered carbons with a tunable mesoporous structure offer an opportunity to maximize catalyst performance and durability. In this article, we report on the development of a graphitized, mesoporous carbon support with a high degree of ordering, labeled here as ECS4005, for the dispersion of Pt nanoparticles. Pt/ECS4005 shows significantly improved kinetic activity due to its mesoporous structure that mitigates Pt poisoning by sulfonate functional groups in the ionomer while simultaneously enabling favorable accessibility to reactants.

25 ENERGY STORAGE↗
DOE OSTI2020

Thermal conductivity and its relation to atomic structure for symmetrical tilt grain boundaries in silicon

We perform a systematic study of thermal resistance and conductance of tilt grain boundaries (GBs) in Si using classical molecular dynamics. The GBs studied are naturally divided into three groups according to the structural units forming the GB core. In this work we find that, within each group, the GB thermal conductivity strongly correlates with the excess GB energy. All three groups predict nearly the same GB conductivity extrapolated to the high-energy limit. This limiting value is close to the thermal conductivity of amorphous Si, suggesting similar heat transport mechanisms. While the lattice thermal conductivity decreases with temperature, the GB conductivity slightly increases. However, at high temperatures it turns over and starts decreasing if the GB structure undergoes a premelting transformation. Analysis of vibrational spectra of GBs resolved along different directions sheds light on the mechanisms of their thermal resistance. The existence of alternating tensile and compressive atomic environments in the GB core gives rise to localized vibrational modes, frequency gaps creating acoustic mismatch with lattice phonons, and anharmonic vibrations of loosely bound atoms residing in open atomic environments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accelerating Random Forest Classification on GPU and FPGA

Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification. In this work, we accelerate RF classification on GPU and FPGA. In order to provide efficient support for large datasets, we propose a hierarchical memory layout suitable to the GPU/FPGA memory hierarchy. We design three RF classification code variants based on that layout, and we investigate GPU- and FPGA-specific considerations for these kernels. Our experimental evaluation, performed on an Nvidia Xp GPU and on a Xilinx Alveo U250 FPGA accelerator card using publicly available datasets on the scale of millions of samples and tens of features, covers various aspects. First, we evaluate the performance benefits of our hierarchical data structure over the standard compressed sparse row (CSR) format. Second, we compare our GPU implementation with cuML, a machine learning library targeting Nvidia GPUs. Third, we explore the performance/accuracy tradeoff resulting from the use of different tree depths in the RF. Finally, we perform a comparative performance analysis of our GPU and FPGA implementations. Our evaluation shows that for high accuracy targets, our GPU implementation yields 5-9x speedup over CSR, and up to a 2x speedup over cuML.

FPGA, Xilinx FPGA, GPU, Random Forest classificati↗
DOE OSTI2023

Adaptive optics for optical microscopy [Invited]

Optical microscopy is widely used to visualize fine structures. When applied to bioimaging, its performance is often degraded by sample-induced aberrations. In recent years, adaptive optics (AO), originally developed to correct for atmosphere-associated aberrations, has been applied to a wide range of microscopy modalities, enabling high- or super-resolution imaging of biological structure and function in complex tissues. Here, we review classic and recently developed AO techniques and their applications in optical microscopy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Impact of LWR Assembly Structural Features on Cladding Burst Behavior under LOCA Conditions

This report builds on the previous work by assessing the impact of assembly structural features on cladding balloon and burst behavior. The BISON fuel performance code was used to generate two dimensional RZ meshes containing structural features commonly used in nuclear fuel assemblies. The results were then compared to the cladding burst temperature and balloon strain results from the previous work. A mesh sensitivity study was performed to ensure spacer grid effects were appropriately considered, resulting in a more refined mesh than the previous study. The balloon deformation and burst times of the cladding were compared. Consideration was also given to the effect of rod initial pressure. Overall, the BISON simulations indicated the spacer grids can locally influence cladding performance, however, the impact on the cladding performance was minor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Growth and Performance of High-Quality SWCNT Forests on Inconel Foils as Lithium-Ion Battery Anodes

Large-scale production of vertically aligned single-walled carbon nanotubes (VA-SWCNTs) on metal foils promises to enable technological advancements in many fields, from functional composites to energy storage to thermal interfaces. In this work, we demonstrate growth of high-quality (G/D > 6, average diameters ~ 2–3 nm, densities > 10 12 cm –2 ) VA-SWCNTs on Inconel metal for use as a lithium-ion battery (LIB) anode. Scale-up of SWCNT growth on Inconel 625 to 100 cm 2 exhibits nearly invariant CNT structural properties, even when synthesis is performed near atmospheric pressure, and this robustness is attributed to a growth kinetic regime dominated by the carbon precursor diffusion in the bulk gas mixture. SWCNT forests produced on large-area metal substrates at close to atmospheric pressure possess a combination of structural features that are among the best demonstrated so far in the literature for growth on metal foils. Leveraging these achievements for energy applications, we demonstrate a VA-SWCNT LIB anode with capacity >1200 mAh/g at 1.0C and stable cycling beyond 300 cycles. Furthermore, this robust synthesis of high-quality VA-SWCNTs on metal foils presents a promising route toward mass production of high-performance CNT devices for a broad range of applications.

Energy↗
DOE OSTI2021

Adhesive Bonding of Copper Prepared by Laser-Interference near the Interference Structuring Limits

Adhesive bonding requires adequate surface preparation for ensuring an appropriate joint quality. The interest in adhesive joining has recently expanded to thermal systems having a large number of joints employed for manufacturing and assembly. This study presents surface topology of copper 110 produced by a laser-interference setup that would theoretically yield a periodicity of 1.7 μm, which is near the 1.6–2 μm structuring limit that was estimated based on thermal diffusion length scale for an 8 ns laser pulse. The results show that although the expected periodic interference structuring was not attained, the melt-induced texturing was affected by the laser-interference profile. Single-lap shear tests were performed with specimen surfaces prepared by traditional abrasion and laser-interference structuring methods. Several laser processing parameters, such as the laser spot size, density, number of pulses, and raster speed, were studied. Scanning electron microscope and profilometry measurements were used to characterize the processed surface microstructures. Web-like structures, which indicate widespread melting, were shown to be formed at different processing conditions. Based on the surface topologies investigated, two laser raster speeds were selected to make single-lap-joint specimens. Baseline joints were prepared by abrading joining specimens. The shear-lap strength and displacement at maximum load were shown to be higher by 16.8% and 43.8% for the laser-structured specimens than those of the baseline specimens, respectively. Moreover, the load-displacement curves indicated that the laser-structured joints were more ductile than those without laser-structuring. The increased ductility for the laser-structured joints was found to yield an increase in the energy absorbed during shear-lap testing of approximately of 80–90% over those measured for baseline joints. It is another indicator that laser-interference structuring enhanced the bonding performance of single-lap shear joints.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dirac's equation and its implications for density functional theory based calculations of materials containing heavy elements

Electronic structure calculations based on density functional theory (DFT) give quantitatively accurate predictions of properties of most materials containing light elements. For heavy materials, and in particular for f -electron systems, DFT based methods can fail both qualitatively and quantitatively for two distinct reasons: their failure to describe confinement effects arising from localized f -electron behavior and their incomplete or approximate treatment of relativity. In addition, different methods for incorporating relativistic effects, which give identical results in most light materials, can give different predictions in heavy elements. In order to develop a quantitative capability for calculating the properties of these materials, it is essential to separate the predictions of the underlying equations from the uncertainty introduced in approximations used in computation. Working toward that goal, here we have developed a code, called dirac-fp , which is based directly on solving the Dirac-Kohn-Sham equations and uses the full-potential linear muffin-tin orbital (FP-LMTO) approach to electronic structure. In order to assess the performance of dirac-fp , we perform calculations on three different face-centered cubic materials using different approximate treatments of relativity: the scalar relativistic (SR) approach commonly used in most solid-state DFT codes, the scalar relativistic plus spin-orbit coupling corrections (SR+SO) approach which includes spin-orbit coupling self-consistently using the SR states inside the muffin tins, and the Dirac-Kohn-Sham (Dirac) approach implemented in dirac-fp . Performing calculations on thorium, in which relativistic effects should be strong, aluminum, in which relativistic effects should be negligible, and gold, in which relativistic effects play an intermediate role, we find that the Dirac approach is able to provide theoretically consistent results in the electronic structure and ground-state properties across all three materials.

3-dimensional systems↗
DOE OSTI2020

Performance Characterization of a Natural Gas–Air Rotating Detonation Engine

An experimental study of a rotating detonation engine (RDE) operating with natural gas and air at elevated chamber pressures and air preheat temperatures was conducted to quantify its performance at conditions representative of land-based power generation gas turbine engines. Here, the thrust produced by the combustor was measured to characterize its work output potential. High-frequency pressure transducers and broadband chemiluminescence measurements of the flame provided information about the wave structure and dynamics. Analysis of common performance metrics demonstrated the necessity of normalizing any RDE performance parameter by the driving system potential, typically the reactant manifold pressure. Application of a thermodynamic performance model to a generic RDE identified the area ratio between the RDE exhaust and injection throats as the primary parameter affecting delivered pressure gain. The model was further applied to draw comparison with experimental measurements of net pressure gain for identical flow conditions. Only one of the two tested injector configurations followed the predicted trends, suggesting that performance of the second was governed by physical processes other than the reactant thermodynamics. Although an absolute pressure gain was not demonstrated, it is promising that the natural gas–air RDE delivered up to 90% of the theoretical performance.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Pt Atomic Single-Layer Catalyst Embedded in Defect-Enriched Ceria for Efficient CO Oxidation

The local coordination structure of metal sites essentially determines the performance of supported metal catalysts. Here, using a surface defect enrichment strategy, we successfully fabricated Pt atomic single-layer (Pt ASL ) structures with 100% metal dispersion and precisely controlled local coordination environment (embedded vs adsorbed) derived from Pt single-atoms (Pt 1 ) on ceria-alumina supports. The local coordination environment of Pt 1 not only governs its catalytic activity but also determines the Pt 1 structure evolution upon reduction activation. For CO oxidation, the highest turnover frequency can be achieved on the embedded Pt ASL in the CeO 2 lattice, which is 3.5 times of that on the adsorbed Pt ASL on the CeO 2 surface and 10–70 times of that on Pt1. The favorable CO adsorption on embedded Pt ASL and improved activation/reactivity of lattice oxygen within CeO 2 effectively facilitate the CO oxidation. This work provides new insights for the precise control of the local coordination structure of active metal sites for achieving 100% atomic utilization efficiency and optimal intrinsic catalytic activity for targeted reactions simultaneously.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Selecting the Optimal Fluorinated Ether Co-Solvent for Lithium Metal Batteries

To guide the selection of a suitable fluorinated ether (FE) co -solvent for lithium metal batteries, it is crucial to understand the relationship between the organic structures of the FEs and the electrochemical performance of an FE-containing electrolyte. In this work, 1,1,2,2-tetrafluoro-1-(2,2,2-trifluoroethoxy)ethane (FEE), 1,1,2,2-tetrafluoro-3-(1,1,2,2-tetrafluoroethoxy)-propane (TTE), and 1,2-bis(1,1,2,2-tetrafluoroethoxy)ethane (OFDEE) were chosen as representative FE co-solvents because of their distinct structural properties. The structure-activity relationship between the FEs and the electrochemical performance of Li||LiNi 0.6 Mn 0.2 Co 0.2 O 2 (Li||NMC622) cells was correlated and quantified by Fourier-transform infrared and multi-dimensional nuclear magnetic resonance techniques. Sand's model was also employed to assess the extent of lithium dendrite formation in the cells using various FE electrolytes. The cycling performance of Li||NMC622 cells using different FE co-solvents follows the order FEE > TTE > OFDEE. Further, since the direct measurement of Sand's time is difficult, we introduced relative Sand's time to probe the diffusion behavior of each electrolyte, and the results showed that the best performance was obtained in the electrolyte with the longest relative Sand's time. Moreover, the lithium metal cell using the electrolyte with FEE co-solvent showed similar capacity retention compared with the baseline electrolyte at room temperature, but it demonstrated significantly improved low-temperature performance. The results indicate that FEE is a promising co-solvent candidate for improving the low-temperature performance of lithium metal batteries because it possesses not only non-solvating behavior but also very low viscosity and non-flammability. The advanced electrolyte LiPF 6 -FEC-DMC-FEE enables very stable cycling of lithium metal batteries at various temperatures.

25 ENERGY STORAGE↗
DOE OSTI2023

Predictive understanding of the surface tension and velocity of sound in ionic liquids using machine learning

Knowledge of the physical properties of ionic liquids (ILs), such as the surface tension and speed of sound, is important for both industrial and research applications. Unfortunately, technical challenges and costs limit exhaustive experimental screening efforts of ILs for these critical properties. Previous work has demonstrated that the use of quantum-mechanics-based thermochemical property prediction tools, such as the conductor-like screening model for real solvents, when combined with machine learning (ML) approaches, may provide an alternative pathway to guide the rapid screening and design of ILs for desired physiochemical properties. However, the question of which machine-learning approaches are most appropriate remains. In the present study, we examine how different ML architectures, ranging from tree-based approaches to feed-forward artificial neural networks, perform in generating nonlinear multivariate quantitative structure–property relationship models for the prediction of the temperature- and pressure-dependent surface tension of and speed of sound in ILs over a wide range of surface tensions (16.9–76.2 mN/m) and speeds of sound (1009.7–1992 m/s). The ML models are further interrogated using the powerful interpretation method, shapley additive explanations. We find that several different ML models provide high accuracy, according to traditional statistical metrics. The decision tree-based approaches appear to be the most accurate and precise, with extreme gradient-boosting trees and gradient-boosting trees being the best performers. However, our results also indicate that the promise of using machine-learning to gain deep insights into the underlying physics driving structure–property relationships in ILs may still be somewhat premature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Simplifying the Chemical Design of Nonfused-Ring Electron Acceptors─Lessons Learned from Thienothiophene and Benzodithiophene Cores

Nonfused-ring electron acceptors (NFREA)s have been proposed as alternatives to fused-ring acceptors in organic photovoltaics (OPV)s. The simpler molecular design of NFREAs results in a reduced synthetic complexity, potentially lowering manufacturing costs, and easier access to desired optoelectronic properties by structural modifications. However, they have not seen the same rise in popularity as fused nonfullerene acceptors (NFA)s due to their lower performances in devices. In this work, we explore structure–property relationships of three NFREA molecules based on thieno[3,2-b]thiophene (TT) and benzo[1,2-b:4,5-b′]dithiophene (BDT) cores and malononitrile functionalized-isatin end group acceptors. We describe their synthetic routes, computational analysis, and photophysical and electronic properties. Here, we investigated the effect of changing the core from TT to BDT on electronic properties of the molecules─a result of raising/lowering of the frontier molecular orbital (FMO) levels. We also explored the effect of branched vs nonbranched alkyl groups on the morphological and blend-capabilities in bulk heterojunction (BHJ) OPV devices. These effects were then reflected in the overall device performances, primarily due to favorable FMO energy alignment between the NFREA and polymer. To investigate the behavior of the excited states of the NFREAs within the active layer of the devices, we performed time-resolved microwave conductivity and transient absorption experiments, which confirmed that the TT molecules exhibited very low conductance while the BDT molecule showed moderate photoconductance. Our combined theoretical, synthetic, device, and charge carrier dynamics studies of these materials reveal the central role that structure–property relationships play in future molecular designs of NFREAs that can perform as well as their fused counterparts.

14 SOLAR ENERGY↗
DOE OSTI2022

Oxygen Loss in Layered Oxide Cathodes for Li-Ion Batteries: Mechanisms, Effects, and Mitigation

Layered lithium transition metal oxides derived from LiMO 2 (M = Co, Ni, Mn, etc.) have been widely adopted as the cathodes of Li-ion batteries for portable electronics, electric vehicles, and energy storage. Oxygen loss in the layered oxides is one of the major factors leading to cycling-induced structural degradation and its associated fade in electrochemical performance. Herein, we review recent progress in understanding the phenomena of oxygen loss and the resulting structural degradation in layered oxide cathodes. We first present the major driving forces leading to the oxygen loss and then describe the associated structural degradation resulting from the oxygen loss. Here, we follow this analysis with a discussion of the kinetic pathways that enable oxygen loss, and then we address the resulting electrochemical fade. Finally, we review the possible approaches toward mitigating oxygen loss and the associated electrochemical fade as well as detail novel analytical methods for probing the oxygen loss.

36 MATERIALS SCIENCE↗
DOE OSTI2023

On-Chip Batteries as Distributed Energy Sources in Heterogeneous 2.5D/3D Integrated Circuits

Energy efficiency in digital systems faces challenges due to the constraints imposed by small-scale transistors. Moreover, the growing demand for portable consumer electronics necessitates the use of compact energy sources. To address these challenges, heterogeneous 3D IC technology has emerged as a promising solution for the former. Regarding the latter, we propose the concept of distributed batteries within a heterogeneous 3D IC. This approach involves utilizing multiple smaller batteries with different specifications among different modules of 3D ICs. This approach optimizes performance and overcomes limitations associated with both 3D ICs and conventional power delivery methods. Distributed batteries play a vital role in effectively managing the heat generated by energy sources and modules within a 3D IC. Furthermore, they contribute to achieving a uniform distribution of heat throughout the entire structure, which ultimately ensures the optimal performance of the batteries and modules. The simulation results indicate a 40 percent enhancement in achieving a more even distribution of generated heat. Additionally, the proposed distributed battery techniques improve power delivery, enhance reliability, and enable optimized voltage regulation while improving efficiency. In addition to the primary benefits, alternative configurations of the proposed approach can offer extra energy storage capacity and act as efficient electromagnetic shields, resulting in an impressive reduction of external electromagnetic noises by 60 dB.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Bottom‐Up Synthesized Nanoporous Graphene Transistors

Abstract Nanoporous graphene (NPG) can exhibit a uniform electronic band gap and rationally‐engineered emergent electronic properties, promising for electronic devices such as field‐effect transistors (FETs), when synthesized with atomic precision. Bottom‐up, on‐surface synthetic approaches developed for graphene nanoribbons (GNRs) now provide the necessary atomic precision in NPG formation to access these desirable properties. However, the potential of bottom‐up synthesized NPG for electronic devices has remained largely unexplored to date. Here, FETs based on bottom‐up synthesized chevron‐type NPG (C‐NPG), consisting of ordered arrays of nanopores defined by laterally connected chevron GNRs, are demonstrated. C‐NPG FETs show excellent switching performance with on–off ratios exceeding 10 4 , which are tightly linked to the structural quality of C‐NPG. The devices operate as p‐type transistors in the air, while n‐type transport is observed when measured under vacuum, which is associated with reversible adsorption of gases or moisture. Theoretical analysis of charge transport in C‐NPG is also performed through electronic structure and transport calculations, which reveal strong conductance anisotropy effects in C‐NPG. The present study provides important insights into the design of high‐performance graphene‐based electronic devices where ballistic conductance and conduction anisotropy are achieved, which could be used in logic applications, and ultra‐sensitive sensors for chemical or biological detection.

Mutlu, Zafer↗