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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Concurrency Supply Chain Optimization (Final Report)

Brunswick is experiencing unprecedented volume for engines and fully produced boats. Supply Chain (parts) has difficulty accurately forecasting demand needs which presents problems in the manufacturing process. Streamline ordering process enabling the Brunswick Boat Group (BBG) to more efficiently forecast part demand for the Mercury Engine Group by setting up an AI/ML model. Initial focus will be 15 SKUs with inaccurate demand forecasting based on current manual processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Fission Product Chain Yield Measurements [Slides]

Fission product chain yields were historically determined by chemical separation and beta counting of fissile samples irradiated in carefully controlled fission chamber experiments. These measurements provided the means to extract absolute fission product yields (yield per fission, or Y $\mathcal{i}$ /$\mathcal{f}$ for the $\mathcal{i}$ $\mathcal{th}$ fission product) that are included in the international nuclear data libraries, and ultimately used to model and characterize multiplying systems. However, reevaluations conducted at Los Alamos National Lab and Lawrence Livermore National Lab in 2005-2009 for neutron-induced fission of 235 U and 239 Pu highlighted disagreement among many of the measurements. This led to several new, targeted experimental programs to resolve these disagreements. In this presentation we will highlight recent efforts to address these discrepancies using energy-integral measurements at the National Criticality Experiments Research Center (NCERC) and outline our plans to complete the work over the next several years.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Deep Neural Network Informed Markov Chain Monte Carlo Methods

In subsurface flow modeling, quantifying the uncertainty of model parameters and the corresponding uncertainly on output quantities is a crucial task for groundwater management. Markov chain Monte Carlo (MCMC) methods can take advantage of observed data to estimate parameters in a Bayesian setting. However, MCMC can be slow to converge and produce highly correlated samples when the dimensions of the parameters is high. Using gradients for the posterior distribution can help samplers explore the parameter space more efficiently, but obtaining gradients can be computationally challenging.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

SBND Analysis using ML Reconstruction Chain

As part of the Short Baseline Neutrino (SBN) Program at Fermilab, the Short Baseline Near Detector (SBND) is positioned in the Booster Neutrino Beam (BNB) and explores neutrino-argon interactions with unprecedented statistics. SBND is a Liquid Argon Time Projection Chamber (LArTPC). Electrons produced through ionization drift toward three wire planes, providing signals that form 2D images of particle trajectories. I introduce the Scalable Particle Imaging using Neural Embeddings (SPINE) framework, which employs a Machine Learning (ML)-based 3D reconstruction using a series of neural networks. Here, we present SPINE’s reconstruction chain, analysis approaches, and results from our latest simulation samples.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Development Results on Replacement Materials for Current Scarce or High Supply Chain Risk Materials

In September 2020, the U.S. government issued an executive order to address the threat to the domestic supply chain from its reliance on critical minerals (CMs) from foreign competitors and to support the domestic mining and processing industry. The Advanced Materials and Manufacturing Technology (AMMT) program is addressing this executive order by evaluating advanced manufacturing (AM) and its impact on the demands of CMs for energy production in general and how the deployment of AM in nuclear energy will support the projected goals of the Paris Accord and further a net-zero carbon economy (NZE) by 2050. Three strategic reports were previously prepared by the AMMT program to date and identified two areas for more detailed exploration: (1) the replacement of high-risk CMs such as cobalt and niobium by more abundant minerals and (2) the minimization and utilization of CM waste streams. The design of nuclear materials without critical elements as alloying elements, is a part of the nuclear materials strategy to overcome the critical minerals scarcity. In this report, two approaches are evaluated namely (1) replacement of critical elements as alloying elements in nuclear materials, and (2) the design of a new alloys that does not contain critical minerals as an alloying element.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nano- and Earth-Science-inspired Electric Vehicle Battery Recycling to Secure Battery Supply Chain

With the expected growth of electric vehicles (EV) in the transportation sector, recycling or upcycling spent battery materials will be required to reduce EV costs, lessen waste, and ease critical material supply chain pressure for EV battery applications. “Direct” recycling or upcycling is an alternative to current industrial approaches. Many challenges remain for viable direct battery upcycling, including upgrading the transition metal ratio in the costliest component (cathode oxide); separation of transition metal ions in the exit stream; battery disassembly; improving cathode exfoliation which can lead to a new way of direct recycling; and lithium metal anode recycling -- including safety concerns. We devise and deploy a suite of methods to deal with these challenges. The results pave the way to future work on battery recycling, in areas of technological/commercial readiness level ranging from basic research to large-scale commercialization.

25 ENERGY STORAGE↗
DOE OSTI2026

Retrofit & Expansion Project at Ultra-High Molecular Weight Polyethylene Plant: Completing a Full Domestic Supply Chain for Lithium-Ion Batteries (Final Scientific and Technical Report)

The UTEC-1 LIBS Retrofit and Expansion Project aimed to retrofit and expand Braskem’s UHMWPE unit in La Porte, TX to produce lithium-ion battery separator (LIBS) grade material and increase capacity. The project sought to strengthen the domestic supply chain for advanced battery manufacturing and reduce reliance on imports. While significant progress was achieved in conceptual design and FEL-2 engineering, strategic realignment and external factors led to project termination prior to FEL-3 and FEED execution.

25 ENERGY STORAGE↗
DOE OSTI2022

Eigenstate entanglement scaling for critical interacting spin chains

With increasing subsystem size and energy, bipartite entanglement entropies of energy eigenstates cross over from the groundstate scaling to a volume law. In previous work, we pointed out that, when strong or weak eigenstate thermalization (ETH) applies, the entanglement entropies of all or, respectively, almost all eigenstates follow a single crossover function. The crossover functions are determined by the subsystem entropy of thermal states and assume universal scaling forms in quantum-critical regimes. This was demonstrated by field-theoretical arguments and the analysis of large systems of non-interacting fermions and bosons. Here, we substantiate such scaling properties for integrable and non-integrable interacting spin-1/2 chains at criticality using exact diagonalization. In particular, we analyze XXZ and transverse-field Ising models with and without next-nearest-neighbor interactions. Indeed, the crossover of thermal subsystem entropies can be described by a universal scaling function following from conformal field theory. Furthermore, we analyze the validity of ETH for entanglement in these models. Even for the relatively small system sizes that can be simulated, the distributions of eigenstate entanglement entropies are sharply peaked around the subsystem entropies of the corresponding thermal ensembles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Confinement and Kink Entanglement Asymmetry on a Quantum Ising Chain

In this work, we explore the interplay of confinement, string breaking and entanglement asymmetry on a 1D quantum Ising chain. We consider the evolution of an initial domain wall and show that, surprisingly, while the introduction of confinement through a longitudinal field typically suppresses entanglement, it can also serve to increase it beyond a bound set for free particles. Our model can be tuned to conserve the number of domain walls, which gives an opportunity to explore entanglement asymmetry associated with link variables. We study two approaches to deal with the non-locality of the link variables, either directly or following a Kramers-Wannier transformation that maps bond variables (kinks) to site variables (spins). We develop a numerical procedure for computing the asymmetry using tensor network methods and use it to demonstrate the different types of entanglement and entanglement asymmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Many Routes to an Antibody Heavy-Chain CDR3: Necessary, Yet Insufficient, for Specific Binding

Because of its great potential for diversity, the immunoglobulin heavy-chain complementarity-determining region 3 (HCDR3) is taken as an antibody molecule’s most important component in conferring binding activity and specificity. For this reason, HCDR3s have been used as unique identifiers to investigate adaptive immune responses in vivo and to characterize in vitro selection outputs where display systems were employed. Here, we show that many different HCDR3s can be identified within a target-specific antibody population after in vitro selection. For each identified HCDR3, a number of different antibodies bearing differences elsewhere can be found. In such selected populations, all antibodies with the same HCDR3 recognize the target, albeit at different affinities. In contrast, within unselected populations, the majority of antibodies with the same HCDR3 sequence do not bind the target. In one HCDR3 examined in depth, all target-specific antibodies were derived from the same VDJ rearrangement, while non-binding antibodies with the same HCDR3 were derived from many different V and D gene rearrangements. Careful examination of previously published in vivo datasets reveals that HCDR3s shared between, and within, different individuals can also originate from rearrangements of different V and D genes, with up to 26 different rearrangements yielding the same identical HCDR3 sequence. On the basis of these observations, we conclude that the same HCDR3 can be generated by many different rearrangements, but that specific target binding is an outcome of unique rearrangements and VL pairing: the HCDR3 is necessary, albeit insufficient, for specific antibody binding.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Mechanism of dielectric barrier discharge plasma technology to improve the quantity of short-chain fatty acids in anaerobic fermentation of waste active sludge

The mechanism of improving the anaerobic fermentation performance of waste active sludge by using dielectric barrier discharge (DBD) plasma pretreatment technology was investigated. The maximum accumulation of short-chain fatty acids (SCFAs) was observed on the 7th day of anaerobic fermentation when the DBD power was 76.50 W, which was 1726.70 mg COD/L, 1.50 times of the control group. The ratio of acetic acid in DBD group was 9.30% higher than that in the control. Further mechanism research indicated that DBD pretreatment can destroy the structure of extracellular polymer substances and release organic substances such as protein and polysaccharide. The dissolved organic matter analysis indicated that the DBD technique could increase the release of biodegradable organics (eg., tyrosine proteins, soluble microbial by-products), thus accelerate the biotransformation of organic substance. Bacterial community structure analysis showed that the increase in the abundance of Firmicutes and Bacteroidetes and the decrease in the abundance of Proteobacteria in DBD group were beneficial to the accumulation of SCFAs. Besides, further archaeal analysis indicated that the decrease of Methanosaeta sp. and Methanosarcina sp . abundance in the DBD group facilitate acetic acid accumulation. This study demonstrated that the DBD technique can be used as an effective and potential pretreatment method to improve sludge anaerobic fermentation performance.

Wang, Jie↗
DOE OSTI2023

Determinants of photochemical characteristics of the photosynthetic electron transport chain of maize

The photosynthetic electron transport chain (ETC) is the bridge that links energy harvesting during the photophysical reactions at one end and energy consumption during the biochemical reactions at the other. Its functioning is thus fundamental for the proper balance between energy supply and demand in photosynthesis. Currently, there is a lack of understanding regarding how the structural properties of the ETC are affected by nutrient availability and plant developmental stages, which is a major roadblock to comprehensive modeling of photosynthesis. Redox parameters reflect the structural controls of ETC on the photochemical reactions and electron transport. We conducted joint measurements of chlorophyll fluorescence (ChlF) and gas exchange under systematically varying environmental conditions and growth stages of maize and sampled foliar nutrient contents. We utilized the recently developed steady-state photochemical model to infer redox parameters of electron transport from these measurements. We found that the inferred values of these photochemical redox parameters varied with leaf macronutrient content. These variations may be caused either directly by these nutrients being components of protein complexes on the ETC or indirectly by their impacts on the structural integrity of the thylakoid and feedback from the biochemical reactions. Also, the redox parameters varied with plant morphology and developmental stage, reflecting seasonal changes in the structural properties of the ETC. Our findings will facilitate the parameterization and simulation of complete models of photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Markov Chain Monte Carlo Used in Parameter Inference of Magnetic Resonance Spectra

In this paper, we use Boltzmann statistics and the maximum likelihood distribution derived from Bayes’ Theorem to infer parameter values for a Pake Doublet Spectrum, a lineshape of historical significance and contemporary relevance for determining distances between interacting magnetic dipoles. A Metropolis Hastings Markov Chain Monte Carlo algorithm is implemented and designed to find the optimum parameter set and to estimate parameter uncertainties. In conclusion, the posterior distribution allows us to define a metric on parameter space that induces a geometry with negative curvature that affects the parameter uncertainty estimates, particularly for spectra with low signal to noise.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization

Global food security is under significant threat from climate change, population growth, and resource scarcity. This review examines how advanced AI-driven forecasting models, including machine learning (ML), deep learning (DL), and time-series forecasting models like SARIMA/ARIMA, are transforming regional agricultural practices and food supply chains. Through the integration of Internet of Things (IoT), remote sensing, and blockchain technologies, these models facilitate the real-time monitoring of crop growth, resource allocation, and market dynamics, enhancing decision making and sustainability. The study adopts a mixed-methods approach, including systematic literature analysis and regional case studies. Highlights include AI-driven yield forecasting in European hydroponic systems and resource optimization in southeast Asian aquaponics, showcasing localized efficiency gains. Furthermore, AI applications in food processing, such as plasma, ozone and Pulsed Electric Field (PEF) treatments, are shown to improve food preservation and reduce spoilage. Key challenges—such as data quality, model scalability, and prediction accuracy—are discussed, particularly in the context of data-poor environments, limiting broader model applicability. The paper concludes by outlining future directions, emphasizing context-specific AI implementations, the need for public–private collaboration, and policy interventions to enhance scalability and adoption in food security contexts.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Integrating Biomass Conversion Technologies with Recovery Operations In-Woods: Modeling Supply Chain

Economic potential of feedstock generated low-valued forest residue can be enhanced by emerging biomass conversion technologies (BCT), such as torrefaction, briquetting, and gasification. However, for implementing these emerging processes within the woods, several hurdles are to be overcome, among which a balanced supply chain is pivotal. Centralized biomass recovery operation (CBRO) could be an economically viable solution in accessing harvesting sites and allows integration of BCT into forest management. The goal of this study was to examine the logistic effects of integrating a BCT into a CBRO, under different in-wood scenarios based on variations in travel time between the facility locations, amount of raw materials handled, intermediate storage capacity, and duration (number of days) of annual operations. Specific objectives included analyzing the effects of forest residue recoverability (BDMT, bone dry metric ton/ha), total transportation time from the harvest unit to the market, and the annual number of in-woods production sites on the overall efficiency of the BCT operations. Concurrently, this study examined the forest managerial impacts due to such an integration. Location-allocation tool (maximize market share problem type) within the ArcGIS Network Analyst platform was utilized to model the scenarios and generate one-way travel times from the harvest site to final markets. Results from geospatial analysis showed that there were 89–159 and 64–136 suitable locations for the BCT for logistics model (LM) I and II, respectively. Total one-way travel time for all the models ranged between 1.0–1.7 h. Additionally, the annual numbers of BCT sites was inversely proportional to the total one-way travel time (i.e., harvest unit to market). Arranging CBRO and BCT operations to occur at the same in-woods site returned shorter total and average travel times than arranging the two activities at separate in-woods sites. The model developed for this study can be used by forest managers and entrepreneurs to identify sites for placing BCTs in the forest that minimizes transportation times.

Paulson, Jeffrey↗
DOE OSTI2022

Calcium Sulfate and Calcium Carbonate Scaling of Thin-Film Composite Polyamide Reverse Osmosis Membranes with Surface-Tethered Polyacrylic Acid Chains

The gypsum and calcite scaling propensities of the thin-film composite polyamide (PA-TFC) reverse osmosis (RO) membrane, modified with a tethered surface layer of polyacrylic acid (PAA) chains, was evaluated and compared to the scaling of selected commercial RO membranes. The tethered PAA layer was synthesized onto a commercial polyamide membrane (i.e., base-PA) via atmospheric pressure plasma-induced graft polymerization (APPIGP). The PAA nano-structured (SNS) base-PA membrane (SNS-PAA-PA) was scaled to a lesser degree, as quantified by a lower permeate flux decline and surface imaging, relative to the tested commercial membranes (Dow SW30, Toray SWRO, and BWRO). The cleaning of gypsum-scaled membranes with D.I. water flushing achieved 100% water permeability recovery for both the SNS-PAA-PA and Dow SW30 membranes, relative to 92–98% permeability restoration for the Toray membranes. The calcium carbonate scaling of SNS-PAA-PA membranes was also lower relative to the commercial membranes, but permeability recovery after D.I. water cleaning was somewhat lower (94%) but consistent with the level of surface scale coverage. In contrast, the calcite and gypsum-scaled membrane areas of the commercial membranes post-cleaning were significantly higher than for the SNS-PAA-PA membrane but with 100% permeability recovery, suggesting the potential for membrane damage when mineral scaling is severe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗