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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Advanced biorefinery feedstock from non-recyclable municipal solid waste by mechanical preprocessing

Because of accelerated urbanization and the development of a global economy, a large quantity of municipal solid waste (MSW) has been collected and disposed of by the municipalities. Due to this drastic increase in the disposal of MSW, the need for its management is a must to preserve the environment. Currently, approximately 50% of the total MSW generated in the United States has been utilized through various recycling, combustion, and composting technologies, which means the remaining 50% is sent to landfill; this is often known as non-recyclable MSW (nMSW). As this nMSW is physically and chemically heterogenous and contains very high amounts of inorganic material, processing is required prior to using it as a biorefinery feedstock. Thus, this study focused on how mechanical preprocessing advanced the physical and chemical properties of nMSW. The physical and chemical properties were investigated in terms of particle size distribution, bulk density, ultimate and proximate analysis, and the higher heating value (HHV). The combustion properties were examined in terms of ignition temperature, peak heat release rate, and combustion efficiency. Results showed that the variability of physical and chemical properties of nMSW can be reduced by mechanical preprocessing. For example, the variability of the bulk density of the as-received nMSW was approximately 17.3% while it reduced to 5.8% when the sample size was reduced to 2 mm. Similarly, the variability of ash and HHV reduced from 49.2% to 11.0% and 13.4%–4.2%, respectively. Combustion thermograms showed that the size reduction positively improved the combustion properties. For example, 2 mm of spec sample started to ignite approximately 4 times earlier and took 6.5 folds less time to reach the peak heating rate compared to as-received nMSW. Overall, the mechanical preprocessing reduced the variability of physical and chemical properties in addition to the improvement of combustion behavior of the nMSW which is one step forward toward the biorefinery feedstock.

09 BIOMASS FUELS↗
DOE OSTI2026

Learning turbulent flows with generative models for super resolution and sparse flow reconstruction

Neural operators are promising surrogates for dynamical systems but when trained with standard L 2 losses they tend to oversmooth fine-scale turbulent structures. Here, we show that combining operator learning with generative modeling overcomes this limitation. We consider three practical turbulent-flow challenges where conventional neural operators fail: spatio-temporal super-resolution, forecasting, and sparse flow reconstruction. For Schlieren jet super-resolution, an adversarially trained neural operator (adv-NO) reduces the energy-spectrum error by 15 × while preserving sharp gradients at neural operator-like inference cost. For 3D homogeneous isotropic turbulence, adv-NO trained on only 160 timesteps from a single trajectory forecasts accurately for five eddy-turnover times and offers 114 × wall-clock speed-up at inference than the baseline diffusion-based forecasters, enabling near-real-time rollouts. For reconstructing cylinder wake flows from highly sparse Particle Tracking Velocimetry-like inputs, a conditional generative model infers full 3D velocity and pressure fields with correct phase alignment and statistics. These advances enable accurate reconstruction and forecasting at low compute cost, bringing near-real-time analysis and control within reach in experimental and computational fluid mechanics.

Fluid dynamics↗
DOE OSTI2024

Visualizing a Vulnerability: Its Connections to Hardware and Software

All Hazards Analysis (AHA) is a framework developed by Idaho National Laboratory that provides capabilities to collect, store, analyze, and visualize critical infrastructure information. A core function of AHA is its ability to simulate faults or outages in networks of infrastructure originating from a plethora of causes, ranging from natural disasters to cyberattacks. AHA utilizes Hardware and Software Bills of Material (HBOM and SBOM, respectively) along with Known Exploited Vulnerabilities (KEVs) to document the potential attack vectors for each piece of infrastructure. The objective of this contribution to AHA was to create a visualization tool that could capture the small details held in each individual artifact as well as preserve the large-scale connections that link them together to aid threat modeling.

58 GEOSCIENCES↗
DOE OSTI2024

Biochar-compost-based controlled-release nitrogen fertilizer intended for an active microbial community

Nitrogen (N) fertilizers in agriculture suffer losses by volatilization of N to the air, surface runoff and leaching into the soil, resulting in low N use efficiency (NUE) (< 50%) and raising severe environmental pollutions. Controlled- release nitrogen fertilizers (CRNFs) can control the release of N nutrients to NUE in crop production. Different methods were used to develop new CRNFs. However, different CRNF technologies are still underdeveloped due to inadequate controlling on N releasing time and/or unsustainable diffusion. The study on the influences of CRNF processing parameters on microbial conditions are lacking when the CRNFs composed of various bio-ingredients such as biochar, composts, and biowaste. The complexity of processing methods, material biodegradability, and other physical properties make current CRNFs of questionable value in agricultural production. This research aims to develop a novel biochar-compost-based controlled-release urea fertilizer (BCRUF) to preserve microbial properties carried by the compost. The BCRUF was synthesized by pelletizing the 50:50 (dry, wt/wt) mixture of biochar and compost. BCRUF was loaded with urea and then spray-coated with polylactic acid (PLA). The releasing time of two types of BCRUFs, coated and uncoated with PLA, for 80% of N release in water was up to 6 h at three different temperatures (4, 23, and 40 °C), compared to conventional urea fertilizer and commercial environmentally smart N (ESN) fertilizer. The releasing time of coated BCRUF for 80% N release in soil was up to 192 h (8 days). Fourier-transform infrared spectroscopy (FTIR) analysis revealed that no new functional groups were found in the release solution, indicating no new chemical hazards generated. The differential scanning calorimetry (DSC) tests also verified that its thermal stability could be up to 160 °C. The microbe populations in the BCRUF pellets were reduced after the pelleting and drying processes in BCRUF fabrication, but a few bacteria can endure in the air-drying process. BCRUF pellets soaked in water for 4 days retained some bacteria. The BCRUF showed very promising characteristics to improve NUE and sustainability in agricultural production.

58 GEOSCIENCES↗
DOE OSTI2023

PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" program project was a highly integrated and comprehensive systems biology research core, funded by the National Institute of Health (U19AI106772) from 2013-06-01 to 2018-05-31, investigating the complex host response to category A, B, and C priority pathogen infections. Resulting project deliverables include an extensive comprehensive collections of linked primary and secondary transformation viral experimental infection data. Here we provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open access to viral Omics lifecycle datasets and project metadata. Using a highly integrated and multidisciplinary approach, linked primary data and metadata supporting secondary normalization datasets, provide critical information necessary for research reproducibility and long-term preservation. Enabling on-demand data access for research community consumption and developer reuse, serves to support new mechanistic insights and discoveries into host-pathogen interactions for aiding future biohazard data preparedness efforts in emergency response to global health crises involving viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Small-Angle X-ray Scattering Analysis of Colloidal Crystals and Replica Materials Made from L-Arginine-Stabilized Silica Nanoparticles

Colloidal crystals made from sub-100 nm silica nanoparticles have provided a versatile platform for the template-assisted synthesis of three-dimensionally interconnected semiconducting, metallic, and magnetic replicas. However, the detailed structure of these materials has not yet been characterized. Here, we investigated the structures of colloidal crystalline films and germanium replicas by scanning electron microscopy and small angle X-ray scattering. The structures of colloidal crystals made by evaporative assembly depends on the size of L-arginine-capped silica nanoparticles. Particles smaller than ~31 nm diameter assemble into non-close-packed arrangements (bcc) whereas particles larger than 31 nm assemble into random close-packed structures with disordered hexagonal phase. Polycrystalline films of these materials retain their structures and long-range order upon infiltration at high temperature and pressure, and the structure is preserved in Ge replicas. The shear force during deposition and dispersity of silica nanoparticles contributes to the size-based variation in the structure and to the size of crystal domains in the colloidal crystal films.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Chemical and elemental mapping of spent nuclear fuel sections by soft X-ray spectromicroscopy

Soft X-ray spectromicroscopy at the O K -edge, U N 4,5 -edges and Ce M 4,5 -edges has been performed on focused ion beam sections of spent nuclear fuel for the first time, yielding chemical information on the sub-micrometer scale. To analyze these data, a modification to non-negative matrix factorization (NMF) was developed, in which the data are no longer required to be non-negative, but the non-negativity of the spectral components and fit coefficients is largely preserved. The modified NMF method was utilized at the O K -edge to distinguish between two components, one present in the bulk of the sample similar to UO 2 and one present at the interface of the sample which is a hyperstoichiometric UO 2+ x species. The species maps are consistent with a model of a thin layer of UO 2+ x over the entire sample, which is likely explained by oxidation after focused ion beam (FIB) sectioning. In addition to the uranium oxide bulk of the sample, Ce measurements were also performed to investigate the oxidation state of that fission product, which is the subject of considerable interest. Analysis of the Ce spectra shows that Ce is in a predominantly trivalent state, with a possible contribution from tetravalent Ce. Atom probe analysis was performed to provide confirmation of the presence and localization of Ce in the spent fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗
DOE OSTI2025

Automated qualification data tool for high temperature metallic materials

This report describes a framework for storing, processing, and displaying qualification data for high temperature mechanical properties. The framework automates the process of generating design data from mechanical test results, for example for a data qualification report for the ASME Boiler \& Pressure Vessel Code. The framework has three parts: a data storage model with common formats for several types of typical mechanical property tests, a backend based on the \pycreep Python library for correlating and extrapolating the data to generate design material properties and allowable stresses, and a demonstration user interface for displaying, sorting, and filtering the data and exploring different options for modeling the design mechanical properties. The report discusses the options available for data processing, with illustrations from real test data on Alloy 617, Alloy 709, Alloy 740H, and Laser-Powder Bed Fusion 316H. The framework is complete for ASME type data analysis and will be used to store test data generated by the Department of Energy, Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies sponsored qualification programs. Future work could extend the tool to other types of material properties and/or expand the demo user interface to make it accessible across the AMMT program.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multi-resolution enhancement for full-spectrum neural representations

Scientific data acquisition continues to outpace storage and analysis capabilities, making voxel-basedrepresentations increasingly intractable. Implicit neural representations (INRs) offer a promising solutionby encoding signals through coordinate-based neural networks, serving as surrogates of data, withcomputational and storage requirements scaling with network complexity rather than data dimensionality.However, smaller INRs struggle to faithfully represent multiscale structures, high-frequency informationand fine textures that constitute a large proportion of scientific measurements. We propose WIEN-INR, atheoretically guided hierarchical INR framework that distributes modelling across resolution scales andenables improved representation capacity through a novel enhancement network to recover subtle details.This multiscale architecture allows smaller networks to retain the full spatial-frequency content of thesignal as well as preserve training efficiency and lower storage cost. Evaluated on distinct raw experimentalmeasurements across scales and complexities, WIEN-INR represents a practical step towards a broaderadoption of neural representations in scientific workflows, delivering compact, robust and high-fidelityrepresentations.

Ni, Yuan [SLAC National Accelerator Laboratory (SL↗
DOE OSTI2020

Heterotic backgrounds via generalised geometry: moment maps and moduli

We describe the geometry of generic heterotic backgrounds preserving minimal supersymmetry in four dimensions using the language of generalised geometry. They are characterised by an SU(3) × Spin(6 + n) structure within O(6, 6 + n) x $\mathbb{R}$ + generalised geometry. Supersymmetry of the background is encoded in the existence of an involutive subbundle of the generalised tangent bundle and the vanishing of a moment map for the action of diffeomorphisms and gauge symmetries. We give both the superpotential and the Kähler potential for a generic background, showing that the latter defines a natural Hitchin functional for heterotic geometries. Intriguingly, this formulation suggests new connections to geometric invariant theory and an extended notion of stability. Finally we show that the analysis of infinitesimal deformations of these geometric structures naturally reproduces the known cohomologies that count the massless moduli of supersymmetric heterotic backgrounds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

New candidates for regulated gene integrity revealed through precise mapping of integrative genetic elements

Abstract Integrative genetic elements (IGEs) are mobile multigene DNA units that integrate into and excise from host bacterial genomes. Each IGE usually targets a specific site within a conserved host gene, integrating in a manner that preserves target gene function. However, a small number of bacterial genes are known to be inactivated upon IGE integration and reactivated upon excision, regulating phenotypes of virulence, mutation rate, and terminal differentiation in multicellular bacteria. The list of regulated gene integrity (RGI) cases has been slow-growing because IGEs have been challenging to precisely and comprehensively locate in genomes. We present software (TIGER) that maps IGEs with unprecedented precision and without attB site bias. TIGER uses a comparative genomic, ping-pong BLAST approach, based on the principle that the IGE integration module (i.e. its int-attP region) is cohesive. The resultant IGEs from 2168 genomes, along with integrase phylogenetic analysis and gene inactivation tests, revealed 19 new cases of genes whose integrity is regulated by IGEs (including dut, eccCa1, gntT, hrpB, merA, ompN, prkA, tqsA, traG, yifB, yfaT and ynfE), as well as recovering previously known cases (in sigK, spsM, comK, mlrA and hlb genes). It also recovered known clades of site-promiscuous integrases and identified possible new ones.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Experimental Limit on Nonlinear State-Dependent Terms in Quantum Theory

Linear time evolution is one of the fundamental postulates of quantum theory. Past theoretical attempts to introduce nonlinearity into quantum evolution have violated causality. However, a recent theory has introduced nonlinear state-dependent terms in quantum field theory, preserving causality [D. E. Kaplan and S. Rajendran, Phys. Rev. D 105, 055002 (2022)]. We report the results of an experiment that searches for such terms. Our approach, inspired by the Everett many-worlds interpretation of quantum theory, correlates a binary macroscopic classical voltage with the outcome of a projective measurement of a quantum bit, prepared in a coherent superposition state. Measurement results are recorded in a bit string, which is used to control a voltage switch. Presence of a nonzero voltage reading in cases of no applied voltage is the experimental signature of a nonlinear state-dependent shift of the electromagnetic field operator. We implement blinded measurement and data analysis with three control bit strings. Control of systematic effects is realized by producing one of the control bit strings with a classical random-bit generator. The other two bit strings are generated by measurements performed on a superconducting qubit in an IBM Quantum processor and on a N 15 nuclear spin in a nitrogen-vacancy center in diamond. Our measurements find no evidence for electromagnetic quantum state-dependent nonlinearity. We set a bound on the parameter that quantifies this nonlinearity | ε γ | < 4.7 × 10 - 11 , at 90% confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

“Tailing” Phenomenon During Polymer Propagation at The Milne Point Polymer Flood

Chemical flooding simulators traditionally assume that polymer retention follows the Langmuir isotherm, while fractional-flow calculations assume concentration-independent retention. Both models predict a delay in propagation of the polymer front (in proportion to the retention value), followed by a rapid rise in produced polymer concentration to the injected level. In contrast, laboratory retention studies for the Milne Point polymer flood (North Slope of Alaska) consistently show virtually no delay in polymer propagation, a rapid rise in produced polymer to 70-90% of the injected concentration, followed by produced concentration gradually approaching the injected value over many pore volumes. From a practical viewpoint, this behavior means that retention causes no significant delay in propagation of the polymer bank (and therefore the oil bank), but the effective viscosity and displacement efficiency are less than originally planned. This paper explores why this polymer “tailing” phenomenon occurs. During core floods, effluent was analyzed for brine-tracer concentration, viscosity, total organic carbon, and total nitrogen. The latter three items allowed three independent measures of polymer concentration and polymer retention. Experiments were performed with Milne Point core material, oil, brine, and conditions. Mechanistic experiments were also performed with packs of glass beads with controlled levels of various minerals. In Milne Point cores, the presence of the tailing phenomenon was not sensitive to flow rate, polymer concentration, core heterogeneity, or whether the core was preserved, cleaned of oil, or cleaned and resaturated with oil, or cleaned, re-saturated and aged with oil. The three independent measures of polymer concentration confirmed that the tailing phenomenon was not an artifact associated with polymer degradation or detection interferences. Tailing was also observed during mechanistic floods using glassbead packs when sufficient levels of illite or kaolinite were present. This observation was consistent with high levels of illite noted in Milne Point cores. The tailing was not noted during mechanistic floods that contained beads with montmorillonite, chlorite, calcium carbonate, dolomite, siderite, pyrite, or calcium sulfate. A model is proposed to account for the tailing phenomenon. This work suggests that mineralogy analysis (especially for illite and kaolinite) may reveal whether tailing should be accounted for during simulations of polymer propagation/retention in a given field application.

Seright, Randy↗
DOE OSTI2024

Evidence of non-isentropic release from high residual temperatures in shocked metals measured with ultrafast x-ray diffraction

Shock experiments are widely used to understand the mechanical and electronic properties of matter under extreme conditions. However, after shock loading to a Hugoniot state, a clear description of the post-shock thermal state and its impacts on materials is still lacking. We used diffraction patterns from 100-fs x-ray pulses to investigate the temperature evolution of laser-shocked Al–Zr metal film composites at time delays ranging from 5 to 75 ns driven by a 120-ps short-pulse laser. We found significant heating of both Al and Zr after shock release, which can be attributed to heat generated by inelastic deformation. A conventional hydrodynamic model that employs (i) typical descriptions of Al and Zr mechanical strength and (ii) elevated strength responses (which might be attributed to an unknown strain rate dependence) did not fully account for the measured temperature increase, which suggests that other strength-related mechanisms (such as fine-scale void growth) could play an important role in thermal responses under shock wave loading/unloading cycles. Our results suggest that a significant portion of the total shock energy delivered by lasers becomes heat due to defect-facilitated plastic work, leaving less converted to kinetic energy. This heating effect may be common in laser-shocked experiments but has not been well acknowledged. High post-shock temperatures may induce phase transformation of materials during shock release. Another implication for the study is the preservability of magnetic records from planetary surfaces that have a shock history from frequent impact events.

42 ENGINEERING↗
DOE OSTI2026

Testing Recommendations for Thermal Failure Analysis

Minimizing ranges of uncertainty in failure QOIs is vital for making informed engineering decisions. To improve our decision-making ability, it is necessary to have a QOI representation that captures more complex failure modes. Capturing the physics of complex time-dependent temperature failure in explicit detail can be computationally and experimentally expensive. To avoid this blooming of complication and costs, an empirical QOI component-level failure/damage model may be sufficient to help identify component-level failure. In this context, failure and damage are abstractions of more complicated processes that lead to the cessation of normal operating behavior, not a representation of mechanical damage, such as void formation. Such a model requires minimal increases in computational cost and experimental burden. The proposed QOI serves as an indicator that something has likely failed, similar to the previous critical failure temperatures or pressures. This QOI will not replace any existing failure QOIs. It will be calculated alongside them, allowing for preservation of legacy style QOI measurements with new context from the new QOI.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Comparison of point cloud and image-based models for calorimeter fast simulation

Score based generative models are a new class of generative models that have been shown to accurately generate high dimensional calorimeter datasets. Recent advances in generative models have used images with 3D voxels to represent and model complex calorimeter showers. Point clouds, however, are likely a more natural representation of calorimeter showers, particularly in calorimeters with high granularity. Furthermore, point clouds preserve all of the information of the original simulation, more naturally deal with sparse datasets, and can be implemented with more compact models and data files. In this work, two state-of-the-art score based models are trained on the same set of calorimeter simulation and directly compared.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Ultra-Long Distance BOTDA Sensor System Employing Hybrid Amplification and Advanced Noise Reduction Techniques

Brillouin Optical Time Domain Analysis (BOTDA) sensor system play a pivotal role in distributed sensing, which enables precise measurements of strain and temperature across extensive fiber lengths. Nonetheless, challenges emerge as distances grow due to signal attenuation and noise interference resulting in measurement errors. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond 10’s of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through the integration of distributed Raman amplification, inline amplification using erbium-doped fiber amplifiers (EDFA), and advanced noise reduction techniques. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. This approach proves particularly advantageous in BOTDA systems, where accurate measurement of Brillouin scattering signals is paramount for long-range sensing, while concurrently safeguarding high spatial resolutions. In summary, this research has shown a holistic exploration of extending BOTDA's distance sensing capabilities up to 150 km with spatial resolutions of 8 meters.

Bhatta, Hari↗