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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Panel Session 68: Key EFCOG Actions: Risk Communication, Supply Chain Management, Human Capital and More

Overview on the Energy Facility Contractor Group's (EFCOG) most recent work in partnership with DOE to improve performance and EFCOG's mission is to ensure safety, security, and quality across the US DOE complex. Best practices were highlighted in discussions with US DOE/ NNSA leaders and key project executives. EFCOG's key priorities for 2020 were featured in the panel discussions to include: addressing human capital issues to ensure future mission needs can be met; addressing supply chain issues for nuclear projects; improving the data quality and performance assurance; and improving risk communication and stakeholder relations. EFCOG accomplishes its mission through working groups that provide forums to address common challenges and exchange proven techniques and other management and technical information among member contractors. Panelists with presentations: WM EFCOG Panel Slides (Morgan Smith); EFCOG DOE Supply Chain Initiative (SCI) - Enabling The DOE Mission - (Darrell Graddy); Data Quality and Performance Assurance (JD Dowell); Risk Communication - Different Events - Very Different Responses from the Community (Rick McLeod); Current State of Cybersecurity (Liz Porter)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Efficient Subset Simulation using Hamiltonian Neural Network enhanced Markov Chain Monte Carlo Methods

The Monte Carlo method delivers an unbiased estimate of the probability of failure. However, the variance of the estimate depends on the number of evaluated samples. This number must be very large for estimations of a low probability of failure. If the evaluation of each sample is computationally expensive, the crude Monte Carlo simulation strategy is impracticable. Therefore, subset simulations are used to reduce the required number of evaluations. Subset simulations require a Markov Chain Monte Carlo sampler, such as the random walk Metropolis-Hastings algorithm. The algorithm, however, struggles with sampling in low-probability regions, especially if they are narrow. As a consequence, advanced Markov Chain Monte Carlo simulations have been developed. In particular, the Hamiltonian Monte Carlo method explores the target distribution rapidly. Driven by the idea of Hamiltonian dynamics, this sampler provides a non-random walk through the target distribution. The incorporation of subset simulation and Hamiltonian Monte Carlo methods has shown promising results for reliability analysis. One downside of the Hamiltonian Monte Carlo method is that gradient evaluations are computationally expensive, especially when dealing with high-dimensional problems and evaluating long trajectories. We show that integrating Hamiltonian neural networks in Hamiltonian Monte Carlo simulations significantly speeds up the sampling task. Furthermore, the enhancement of adaptive trajectory length within the Hamiltonian Monte Carlo results in the efficient proposal of the following states. Based on this recent enhancement, we provide a fast sampling strategy for subset simulations using Hamiltonian neural networks to replace the evaluation of the gradient and significantly speed up the Hamiltonian Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The 2022 Russian Invasion of Ukraine: Nuclear Supply Chains vs. Sanctions

The United States and European countries are unlikely to collectively approve of sanctions against Russian exports of nuclear fuel assemblies and uranium in the near term despite the 2022 invasion of Ukraine. Rather than bearing the costs that cutting off Russian imports would have on domestic nuclear energy production, the United States and European countries are more likely to prefer developing alternative supply chains of nuclear fuel and enriched uranium to reduce dependence on Russian resources. This outlook is primarily based on two areas of evaluation: (1) comparison of the Russian-made reactor fuel supply chain within the European Union (EU) in 2014 following the annexation of Crimea and in 2022 following the invasion of Ukraine, and (2) the dependence of France and the United States on Russia’s exports of enriched uranium. Additionally, the potential impacts to Kazakh uranium exports if trade routes for nuclear resources through Russia became unavailable were considered as an additional factor in the push for disentanglement from Russian nuclear resources. This work utilized BACI, a database of harmonized international trade data at the product level drawn from the United Nations Comtrade Database and created by the French international economics research institute CEPII.1 Comparisons of imports and exports were based on the trade value in U.S. dollars as reported in BACI instead of the quantity of the traded product. This evaluation only considers import and export data up until 2021, since the trade data for 2022 is incomplete within the Comtrade Database for several of the key countries presented in this work, including Australia, Canada, Namibia, Niger, and Russia.

Political science↗
DOE OSTI2025

Clean Energy for the Battery-to-EV Supply Chain: A Roadmap for Indonesia - Summary Brief

Indonesia has a unique opportunity to support the clean energy transition, enhance energy security, and spur economic growth with local battery manufacturing, bridging from the material supply all the way to pack designs and, ultimately, the manufacturing of electric cars. Following the elevation of United States and Indonesia relations to a Comprehensive Strategic Partnership, leaders of both countries highlighted the importance of Net Zero World support for Indonesia's energy transition, including collaboration on low-carbon battery supply chains. In support of this agreement, Net Zero World has partnered with Indonesia's Ministry of Energy and Mineral Resources and other Indonesian partners to chart actionable steps for establishing a clean, resilient battery supply chain and circular economy. This partnership aims to position Indonesia as a regional leader in clean energy and can help attract investment in the domestic battery and electric vehicle (EV) sectors.

batteries↗
DOE OSTI2023

1D Magnetic MX 3 Single-Chains (M = Cr, V and X = Cl, Br, I)

Magnetic materials in reduced dimensions are not only excellent platforms for fundamental studies of magnetism, but they play crucial roles in technological advances. The discovery of intrinsic magnetism in monolayer 2D van der Waals systems has sparked enormous interest, but the single-chain limit of 1D magnetic van der Waals materials has been largely unexplored. This paper reports on a family of 1D magnetic van der Waals materials with composition MX 3 (M = Cr, V, and X = Cl, Br, I), prepared in fully-isolated fashion within the protective cores of carbon nanotubes. Atomic-resolution scanning transmission electron microscopy identifies unique structures that differ from the well-known 2D honeycomb lattice MX 3 structure. Density functional theory calculations reveal charge-driven reversible magnetic phase transitions.

1D materials↗
DOE OSTI2021

Multilevel Hierarchical Decomposition of Finite Element White Noise with Application to Multilevel Markov Chain Monte Carlo

In this work we develop a new hierarchical multilevel approach to generate Gaussian random field realizations in an algorithmically scalable manner that is well suited to incorporating into multilevel Markov chain Monte Carlo (MCMC) algorithms. This approach builds off of other partial differential equation (PDE) approaches for generating Gaussian random field realizations; in particular, a single field realization may be formed by solving a reaction-diffusion PDE with a spatial white noise source function as the right-hand side. While these approaches have been explored to accelerate forward uncertainty quantification tasks, e.g., multilevel Monte Carlo, the previous constructions are not directly applicable to multilevel MCMC frameworks which build fine-scale random fields in a hierarchical fashion from coarse-scale random fields. Our new hierarchical multilevel method relies on a hierarchical decomposition of the white noise source function in $L^2$ which allows us to form Gaussian random field realizations across multiple levels of discretization in a way that fits into multilevel MCMC algorithmic frameworks. After presenting our main theoretical results and numerical scaling results to showcase the utility of this new hierarchical PDE method for generating Gaussian random field realizations, this method is tested on a four-level MCMC algorithm to explore its feasibility.

algebraic multigrid↗
DOE OSTI2022

Donor End-Capped Alkyl Chain Length Dependent Non-Radiative Energy Loss in All-Small-Molecule Organic Solar Cells

A critical bottleneck for further efficiency breakthroughs in organic solar cells (OSCs) is to minimize the non-radiative energy loss (eΔV nr ) while maximizing the charge generation. With the development of highly emissive low-bandgap non-fullerene acceptors, the design of high-performance donors becomes critical to enable the blend with the electroluminescence quantum efficiency to approach or surpass the pristine acceptor. Herein, by shortening the end-capped alkyl chains of the small-molecular donors from hexyl (MPhS-C6) to ethyl (MPhS-C2), the material obtained aggregation that was insensitive to thermal annealing (TA) along with condensed packing simultaneously. The former leads to small phase separation and suppressed upshifts of the highest occupied molecular orbital energy level during TA, and the latter facilitates its efficient charge-transport at aggregation-less packing. Hence, the ΔV nr decreases from 0.242 to 0.182 V, from MPhS-C6 to MPhS-C2 based OSCs. An excellent PCE of 17.11% is obtained by 1,8-diiodoctane addition due to almost unchanged high J sc (26.6 mA cm –2 ) and V oc (0.888 V) with improved fill factor, which is the record efficiency with the smallest energy loss (0.497 eV) and ΔV nr (0.192 V) in all-small-molecule OSCs. Finally, these results emphasize the potential material design direction of obtaining concurrent TA-insensitive aggregation and condensed packing to maximize the device performances with a super low ΔV nr .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Techno‐economic, environmental, and social measurement of clean energy technology supply chains

Abstract In addition to the criteria of reliability and cost, clean energy technologies, such as wind, solar, and batteries, need to strive to a higher standard of environmental and societal benefit along their entire supply chain. This means additional performance metrics for these technologies should be considered, such as embodied energy, embodied carbon, recycled content and recyclability, environmental impact of material sourcing, impact on land and ecosystems, materials recovery at end of life, and production through quality nonexploitive jobs with community benefit. Many commercial and emerging energy technologies have not yet been explicitly evaluated based on these environmental and social performance metrics, which presents multiple opportunities for researchers and analysts. In this paper, we review the importance and current limitations of techno‐economic and life‐cycle assessment models for research design and manufacturing decisions. We explore emerging manufacturing modeling options that could improve environmental and social performance and how they could be used to help guide research. Even with the deployment of low‐carbon energy‐generation technologies, the future of a successful clean energy transition requires collaboration between researchers, advanced manufacturers, independent standards and tracking organizations, local communities, and national governments, to ensure the financial, environmental, and social sustainability of the entire supply and manufacturing process of energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Screening of alkali-assisted storage conditions to define the operational window of deacetylation within storage systems in the bioenergy supply chain

Overcoming biomass heterogeneity and associated recalcitrance to thermal, chemical, and enzymatic depolymerization is a necessary but challenging aspect of valorizing lignocellulosic biomass to fuels and chemicals. Here, this study explores how this recalcitrance can be reduced during the supply chain unit operation of storage, which is required for seasonally harvested agricultural residues to maintain constant throughput at a biorefinery. In this work, partial alkali pretreatment was performed just prior to corn stover entering storage, which had the benefit of providing a high pH environment entering storage such that soluble sugars were preserved and saponified acetyl groups in hemicellulose. This work investigated a range of viable conditions where saponification and preservation occur simultaneously by varying the moisture content (40% and 60%) and concentrations of sodium hydroxide (low and high) during aerobic and anaerobic storage. Anaerobic conditions preserved overall dry matter below 5% in the three scenarios evaluated, and the highest alkali loading solubilized up to 15% lignin, 18% xylan, and 50% of acetate, meanwhile doubling the extractable components. Scanning electron microscopy images highlighted potential physical impacts including cell-wall disruption near vascular bundles, pitting within parenchyma cells, and cell-wall distortion. Techno-economic assessment indicated that this storage approach and associated logistics system is economically competitive with a conventional approach using low-moisture bales.

09 BIOMASS FUELS↗
DOE OSTI2021

Qualitative and quantitative profiles of jejunal oligosaccharides and cecal short–chain fatty acids in broiler chickens receiving different dietary levels of fiber, protein and exogenous enzymes

Dietary supplemental carbohydrases are able to degrade non-starch polysaccharides and generate oligosaccharides in the gastrointestinal tract. This study was conducted to investigate the influence of dietary fiber and protein levels on growth performance, nutrient utilization, digesta oligosaccharides profile and cecal short-chain fatty acid (SCFA) profile in broilers receiving diets supplemented with xylanase or protease individually or in combination. Enzyme supplementation had no effect on growth performance. There was significant (P < 0.05) fiber × protein × xylanase interaction for ileal nitrogen digestibility and significant (P < 0.01) protein × xylanase × protease interaction for nitrogen-corrected apparent metabolizable energy. Birds fed high-fiber diets had higher (P < 0.05) jejunal oligosaccharides and cecal SCFA concentrations. Xylanase and protease combination produced the greatest pentose (Pent) levels in low fiber–adequate protein diets but lowest levels in highfiber–low protein diets. There was significant (P < 0.05) fiber × xylanase × protease interaction explained by the digesta concentrations of (Pent) 3 , (Pent) 4 and (Pent) 5 being greatest (P < 0.5) in protease-only supplemented high-fiber diets but lowest in protease-only supplemented low-fiber diets. Furthermore, these results suggest that, of all the factors investigated, dietary fiber level had the greatest effect on modulating digesta concentration of oligosaccharides and cecal SCFA. Evidence points to the fact that there is considerable capacity for generating pentose oligosaccharides in the digestive tract of broilers receiving diets rich in fibrous feedstuffs, and that this may have a beneficial effect on microbial profile in the digestive tract.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rewiring metabolism of Clostridium thermocellum for consolidated bioprocessing of lignocellulosic biomass poplar to produce short-chain esters

Consolidated bioprocessing (CBP) of lignocellulosic biomass uses cellulolytic microorganisms to enable enzyme production, saccharification, and fermentation to produce biofuels, biochemicals, and biomaterials in a single step. However, understanding and redirecting metabolisms of these microorganisms compatible with CBP are limited. Here, a cellulolytic thermophile Clostridium thermocellum was engineered and demonstrated to be compatible with CBP integrated with a Co-solvent Enhanced Lignocellulosic Fractionation (CELF) pretreatment for conversion of hardwood poplar into short-chain esters with industrial use as solvents, flavors, fragrances, and biofuels. The recombinant C. thermocellum engineered with deletion of carbohydrate esterases and stable overexpression of alcohol acetyltransferases improved ester production without compromised deacetylation activities. These esterases were discovered to exhibit promiscuous thioesterase activities and their deletion enhanced ester production by rerouting the electron and carbon metabolism. Ester production was further improved up to 80-fold and ester composition could be modulated by deleting lactate biosynthesis and using poplar with different pretreatment severity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Accelerating Markov Chain Monte Carlo sampling with diffusion models

Global fits of physics models require efficient methods for exploring high-dimensional and/or multimodal posterior functions. We introduce a novel method for accelerating Markov Chain Monte Carlo (MCMC) sampling by pairing a Metropolis-Hastings algorithm with a diffusion model that can draw global samples with the aim of approximating the posterior. We briefly review diffusion models in the context of image synthesis before providing a streamlined diffusion model tailored towards low-dimensional data arrays. We then present our adapted Metropolis-Hastings algorithm which combines local proposals with global proposals taken from a diffusion model that is regularly trained on the samples produced during the MCMC run. Our approach leads to a significant reduction in the number of likelihood evaluations required to obtain an accurate representation of the Bayesian posterior across several analytic functions, as well as for a physical example based on a global fit of parton distribution functions. Our method is extensible to other MCMC techniques, and we briefly compare our method to similar approaches based on normalising flows. A code implementation can be found at https://github.com/NickHunt-Smith/MCMC-diffusion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Mitochondrial respiratory chain protein co-regulation in the human brain

Mitochondrial respiratory chain (RC) function requires the stoichiometric interaction among dozens of proteins but their co-regulation has not been defined in the human brain. Here, using quantitative proteomics across three independent cohorts we systematically characterized the co-regulation patterns of mitochondrial RC proteins in the human dorsolateral prefrontal cortex (DLPFC). Whereas the abundance of RC protein subunits that physically assemble into stable complexes were correlated, indicating their co-regulation, RC assembly factors exhibited modest co-regulation. Within complex I, nuclear DNA-encoded subunits exhibited >2.5-times higher co-regulation than mitochondrial (mt)DNA-encoded subunits. Moreover, mtDNA copy number was unrelated to mtDNA-encoded subunits abundance, suggesting that mtDNA content is not limiting. Alzheimer's disease (AD) brains exhibited reduced abundance of complex I RC subunits, an effect largely driven by a 2–4% overall lower mitochondrial protein content. These findings provide foundational knowledge to identify molecular mechanisms contributing to age- and disease-related erosion of mitochondrial function in the human brain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Chain rigidity controlled aggregation ability and solid-state microstructures for efficient stretchable conjugated polymer films

Stretchable conjugated polymer films with good electrical performance under mechanical deformation are highly desirable for soft electronics. However, the mechanical and electrical properties of these films, particularly in conjugated polymer:elastomer blends, are not fully understood at molecular level. Here, this study explores the relationships among molecular structure, aggregation ability, film microstructure, and the electrical/mechanical properties of three diketopyrrolopyrrole-based conjugated polymers (P1, P2, P3) with decreasing backbone rigidity and their corresponding polymer:elastomer blends. The most flexible polymer P3 shows strong aggregation, which forms highly crystalline fibers to produce fragile neat film and produces large isolated crystallites restricting charge transport in blend film. As chain rigidity increases, the P1 and P2 polymers show weaker aggregation, and produce smaller crystallites in neat films with enhanced ductility. P1 and P2 based blend films display nanocrystallites polymer networks with dispersed elastomer domains. As a result, we achieved near-constant charge mobility before and after stretching under 50 % strain for P2-based blend films with well-controlled pathways for both charge transport and energy dissipation. This study demonstrates the critical role of backbone rigidity in regulating the properties of stretchable conjugated polymer films, paving the way for more reliable and deformable materials in soft electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Biomass to bio-energy supply chain: Economic viability, case studies, challenges and policy implications in India

Biomass supply chain (BSC) management is an integral part of renewable energy projects, which include biomass-harvesting, collection, storage, processing and transportation to the bio-energy plants. The sustainability concept identifies economy, environment, and society as the three principal pillars of bioenergy. With an effective BSC implemented, all three dimensions of sustainability can be attained. Although, there’s been extensive research on the environmental sustainability of BSC, the economic aspects are under-represented in existing literature. So, an elaborate analysis on the economic viability of BSCs developed worldwide and those in India is critical, and needs to be studied. This review conducts a detailed accounting of the economic aspects of a BSC which includes the existing challenges in designing an environmental-cum-economically efficient BSC and strategies to address the issues. The Indian context has been studied on the BSC models, highlighting their shortcomings, while encapsulating the essential insights from global BSC models for a cost-effective BSC-to-bioenergy in India. Here, this review also emphasizes the policies supporting the BSC in India and forecasts the future biomass demand and supply. This review will provide stakeholders with critical insights on BSC and related challenges and assist them to investigate and devise strategies for successful implementation of BSCs in India.

Biomass↗
DOE OSTI2020

Effect of Nanoconfinement on Polymer Chain Dynamics

Here, we report on a study of the effects of nanoconfinement on polymer chain dynamics within the framework developed by Muthukumar [Muthukumar, M. (1991). Journal of Non-Crystalline Solids, 131, 654-666.], who suggests that there is an entropically controlled dynamical regime between the Rouse and the reptation regimes that affects the power law dependence on molecular weight of the transport properties.

36 MATERIALS SCIENCE↗