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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nanostructured Alumina Forming Austenitic Alloy (NAFA) Production using Advanced Manufacturing

Alumina-forming austenitic (AFA) alloys are well known for their exceptional corrosion-resistant properties due to the formation of a dense oxide scale beneficial in their application as a nuclear material. However, use of the alloys in core material applications is limited due to the high nickel-transmutation and helium generation rate in service, leading to swelling and reduced lifetimes. Enhancing the sink strength to pin gas bubbles and increasing gas management of the material may mitigate many of the degradation phenomena expected during alloy deployment (such as high-temperature helium embrittlement and cavity swelling for lead-cooled fast-reactor applications). Nanostructured materials are usually produced using a time-consuming and expensive batch process like mechanical alloying to achieve the fine homogenous distribution of nanoprecipitates throughout the matrix material. Integrating the nanoprecipitates in modern additive manufacturing processes has proven difficult, as the required nano-sizes or number densities cannot be achieved simultaneously. Efforts to increase the number density of precipitates by adding more precipitate-forming rare-earth elements led to agglomeration of such elements, while the nano-sized precipitates did not form in sufficient quantity when not enough rare-earth element was use. In this work a novel approach to advanced manufacturing and the fabrication of Nanostructured AFA (NAFA) materials was chosen. A dual precipitate-forming NAFA steel with a chemistry more suitable for advanced reactor applications was produced to create an environmentally resistant, high-sink-strength austenitic alloy for advanced reactor cladding applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nanostructured Alumina-Forming Austenitic Alloy (NAFA) Production Using Advanced Manufacturing

Alumina-forming austenitic (AFA) alloys are well known for their exceptional corrosion-resistant properties due to the formation of a dense oxide scale beneficial in their application as a nuclear material. However, use of the alloys in core material applications is limited due to the high nickel-transmutation and helium generation rate in service, leading to swelling and reduced lifetimes. Enhancing the sink strength to pin gas bubbles and increasing gas management of the material may mitigate many of the degradation phenomena expected during alloy deployment (such as high-temperature helium embrittlement and cavity swelling for lead-cooled fast-reactor applications). Nanostructured materials are usually produced using a time-consuming and expensive batch process like mechanical alloying to achieve the fine homogenous distribution of nanoprecipitates throughout the matrix material. Integrating the nanoprecipitates in modern additive manufacturing processes has proven difficult, as the required nano-sizes or number densities cannot be achieved simultaneously. Efforts to increase the number density of precipitates by adding more precipitate-forming rare-earth elements led to agglomeration of such elements, while the nano-sized precipitates did not form in sufficient quantity when not enough rare-earth element was use. In this work a novel approach to advanced manufacturing and the fabrication of Nanostructured AFA (NAFA) materials was chosen. A dual precipitate-forming NAFA steel with a chemistry more suitable for advanced reactor applications was produced to create an environmentally resistant, high-sink-strength austenitic alloy for advanced reactor cladding applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

On the connection between least squares, regularization, and classical shadows

Classical shadows (CS) offer a resource-efficient means to estimate quantum observables, circumventing the need for exhaustive state tomography. Here, we clarify and explore the connection between CS techniques and least squares (LS) and regularized least squares (RLS) methods commonly used in machine learning and data analysis. By formal identification of LS and RLS ``shadows'' completely analogous to those in CS---namely, point estimators calculated from the empirical frequencies of single measurements---we show that both RLS and CS can be viewed as regularizers for the underdetermined regime, replacing the pseudoinverse with invertible alternatives. Through numerical simulations, we evaluate RLS and CS from three distinct angles: the tradeoff in bias and variance, mismatch between the expected and actual measurement distributions, and the interplay between the number of measurements and number of shots per measurement. Compared to CS, RLS attains lower variance at the expense of bias, is robust to distribution mismatch, and is more sensitive to the number of shots for a fixed number of state copies---differences that can be understood from the distinct approaches taken to regularization. Conceptually, our integration of LS, RLS, and CS under a unifying ``shadow'' umbrella aids in advancing the overall picture of CS techniques, while practically our results highlight the tradeoffs intrinsic to these measurement approaches, illuminating the circumstances under which either RLS or CS would be preferred, such as unverified randomness for the former or unbiased estimation for the latter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

SQuaD: Smart Quantum Detection for Photon Recognition and Dark Count Elimination

Quantum detectors of single photons are an essential component for quantum information processing across computing, communication and networking. Today's quantum detection system, which consists of single photon detectors, timing electronics, control and data processing software, is primarily used for counting the number of single photon detection events. However, it is largely incapable of extracting other rich physical characteristics of the detected photons, such as their wavelengths, polarization states, photon numbers, or temporal waveforms. This work, for the first time, demonstrates a smart quantum detection system, SQuaD, which integrates a field programmable gate array (FPGA) with a neural network model, and is designed to recognize the features of photons and to eliminate detector dark-count. The SQuaD is a fully integrated quantum system with high timing-resolution data acquisition, onboard multi-scale data analysis, intelligent feature recognition and extraction, and feedback-driven system control. Our \name experimentally demonstrates 1) reliable photon counting on par with the state-of-the art commercial systems; 2) high-throughput data processing for each individual detection events; 3) efficient dark count recognition and elimination; 4) up to 100% accurate feature recognition of photon wavelength and polarization. Additionally, we deploy the SQuaD to an atomic (erbium ion) photon emitter source to realize noise-free control and readout of a spin qubit in the telecom band, enabling critical advances in quantum networks and distributed quantum information processing.

Linne, Karl C. [U. Chicago (main)] (ORCID:00090009↗
DOE OSTI2025

Operational optimization for multi-functional charging station with electric and hydrogen-powered vehicles

The rapid adoption of electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), combined with global efforts to reduce carbon emissions, has accelerated the development of EV charging and hydrogen refueling stations. In response to this demand, this paper introduces the concept of Multi-Functional Charging Station (MFCS) that integrates power generation, EV charging, battery swapping, and hydrogen refueling. A comprehensive operational model is developed for the MFCS that couples electricity and hydrogen conversion and storage technologies to enhance infrastructure utilization and improve overall system efficiency. The model also considers multiple revenue streams, including participation in energy and ancillary markets. To validate the effectiveness of the proposed model and evaluate its performance, a series of numerical experiments are conducted with different charger numbers, different electricity purchase limits, and different charger allocations. Numerical results demonstrate that shared charger configurations can lead to 8.11 % improvement in operational profit by improving resource utilization and reducing the number of depleted batteries at the end of operations compared to allocated charger setups. By varying the number of chargers, sensitivity analysis identifies diminishing marginal returns beyond about 45 chargers, suggesting it as an optimal sizing point under current settings. The integration of electricity and hydrogen conversion is also explored under scenarios with limited external electricity purchases. In conclusion, these findings indicate that optimizing charger allocation and energy management can significantly enhance station productivity and profitability, ultimately supporting the broader adoption of electrified and hydrogen-based transportation solutions.

Charging station↗
DOE OSTI2020

Integrated Electrochemical Decontamination and Etching System

Researchers at Los Alamos have developed a novel electrochemical technology consisting of several components in a system that provides a self-contained, efficient, semi- or fully automated, and flexible decontamination system for metals and metal alloys. Any number of novel system configurations are possible such as: 1) a recirculating bath to clean contaminated parts, 2) a recirculating solution through a suction head for larger parts or surfaces, and 3)injecting and removing the solution in/out of large containment tanks. The System is integrated with a proprietary contactor for separation of radioactive components. The decontamination system can also be used to etch steel alloys for increased adhesion of coatings. Coatings embedded with nanoparticles have also been developed and tested on these etched surfaces. We are seeking input from potential users or interested parties regarding the development of the technology.

42 ENGINEERING↗
DOE OSTI2025

Solving high-dimensional partial integral differential equations: The finite expression method

Partial integro-differential equations (PIDEs) have broad applications in the sciences, from electro-magnetism to options pricing. Here, in this paper, we introduce a new finite expression method (FEX) to solve PIDEs. This approach builds upon the original FEX and its inherent advantages with new advances: 1) A novel method of parameter grouping is proposed to reduce the number of coefficients in high-dimensional function approximation; 2) A Taylor series approximation method is implemented to significantly improve the computational efficiency and accuracy of the evaluation of the integral terms of PIDEs. The new FEX based method, denoted FEX-PG to indicate the addition of the parameter grouping (PG) step to the algorithm, provides both high accuracy and interpretable numerical solutions, with the outcome being an explicit equation that facilitates intuitive understanding of the underlying solution structures. These features are often absent in traditional methods, such as finite element methods (FEM) and finite difference methods, as well as in deep learning-based approaches. To benchmark our method against recent advances, we apply the new FEX-PG to solve benchmark PIDEs in the literature. In high-dimensional settings, FEX-PG exhibits strong and robust performance, achieving relative errors on the order of single precision machine epsilon, significantly outperforming existing approaches based on neural networks.

Combinatorial optimization↗
DOE OSTI2024

Integrating ytopt and libEnsemble to autotune OpenMC

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. In conclusion, the experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.

Autotuning↗
DOE OSTI2024

Modeling and Automation Framework for High IBR Integration in Large-Scale Power Systems

The increasing prevalence of power electronics- interfaced renewable generation sources is leading to a gradual replacement of traditional thermal generation-based synchronous machines. In this context, the modeling of a large-scale power grid that incorporates a significant number of inverter-based resources is crucial for understanding the dynamics and effects of these resources on the power system. This study investigates the positive sequence model of grid-following and grid-forming inverters. Additionally, this work explores the integration of distributed energy resources using population as an indicator of their relative geographic locations. To address challenge to integrate these inverter based resources into a realistic grid of the US Western interconnection, automation scripts are developed to streamline the process of replacing conventional generators with grid-following and grid-forming inverters, as well as allocating distributed energy resources. Different penetration levels of these inverters are considered, and their frequency regulation support following a disturbance is compared through dynamic simulations.

Lyu, Xue↗
DOE OSTI2022

Direct numerical simulation of hypersonic turbulent boundary layers: effect of spatial evolution and Reynolds number

Direct numerical simulations (DNS) are performed to investigate the spatial evolution of flat-plate zero-pressure-gradient turbulent boundary layers over long streamwise domains ( >300δ i , with δ i the inflow boundary-layer thickness) at three different Mach numbers, 2.5, 4.9 and 10.9, with the surface temperatures ranging from quasiadiabatic to highly cooled conditions. The settlement of turbulence statistics into a fully developed equilibrium state of the turbulent boundary layer has been carefully monitored, either based on the satisfaction of the von Kármán integral equation or by comparing runs with different inflow turbulence generation techniques. The generated DNS database is used to characterize the streamwise evolution of multiple important variables in the high-Mach-number, cold-wall regime, including the skin friction, the Reynolds analogy factor, the shape factor, the Reynolds stresses, and the fluctuating wall quantities. The data confirm the validity of many classic and newer compressibility transformations at moderately high Reynolds numbers (up to friction Reynolds number Re τ ≈1200 ) and show that, with proper scaling, the sizes of the near-wall streaks and superstructures are insensitive to the Mach number and wall cooling conditions. The strong wall cooling in the hypersonic cold-wall case is found to cause a significant increase in the size of the near-wall turbulence eddies (relative to the boundary-layer thickness), which leads to a reduced-scale separation between the large and small turbulence scales, and in turn to a lack of an outer peak in the spanwise spectra of the streamwise velocity in the logarithmic region.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Plastoquinone redox status influences carboxysome integrity via a RpaA ‐ and reactive oxygen species‐dependent regulatory network

SUMMARY Carboxysomes are bacterial microcompartments that encapsulate Rubisco and are a core component of the cyanobacterial carbon concentration mechanism (CCM). While carboxysome number, size, and spatial organization vary in different environmental conditions (CO 2 , light availability, redox state, temperature, and light quality), the molecular mechanisms underlying this potentially adaptive process remain elusive. Herein, we observe that mutants of the circadian rhythm/metabolism factor, Regulator of Phycobilisome Association A (RpaA), exhibit a striking breakdown of carboxysomes under certain environmental conditions. We find that conditions leading to overreduction of the plastoquinone (PQ) pool (mixotrophic growth, high irradiance, or chemical inhibition of electron transfer from PQ to the cytochromeb 6 fcomplex) are accompanied by an elevated generation of reactive oxygen species (ROS) and correlate with the loss of carboxysome integrity. Carboxysome breakdown is reversed by environmental conditions or chemical inhibitors that prevent PQ overreduction and accompanying ROS generation. Taken together, our data support a novel link between the redox status of the PQ pool and carboxysome integrity. Our results have implications for the fundamental understanding of cyanobacterial energy‐balancing pathways and may indicate new research directions for understanding how the carboxysome is remodeled in response to changing environments.

Plant Sciences↗
DOE OSTI2026

Direct electrode-to-electrode regeneration of end-of-life batteries via electrode–electrolyte interphase dissolution

Lithium-ion battery recycling remains constrained by processes that recover metals at the expense of electrode integrity, while even direct recycling typically requires shredding to black mass followed by binder removal, separation, and full electrode refabrication. Here, we introduce direct electrode-to-electrode regeneration (DEER), a simultaneous electrochemical regeneration of used NMC and graphite electrodes from end-of-life batteries in their intact form by dissolving the passivating electrode–electrolyte interphase (EEI). DEER employs 1,3-dimethyl-2-imidazolidinone (DMI), a high donor number solvent that creates a thermodynamic environment favorable for solubilizing redox inactive EEI components. DEER dissolves the thick EEI on both used electrodes while preserving electrode integrity, enabling up to 95% capacity regain and improved cycling stability with a residual LiF-rich interphase. Operando Raman, operando IR, and post-mortem NMR directly track the electrochemically driven dissolution of carbonate-derived EEI species in the used DMI-based recycling electrolyte. Technoeconomic and life-cycle analyses show that DEER reduces the cost of recycled cell manufacturing by 56% relative to pyro- and hydrometallurgy, while lowering energy use and greenhouse gas emissions. Overall, DEER establishes the first validated pathway to directly regenerate and reuse electrodes harvested from truly end-of-life batteries, converting the key interfacial bottleneck into a controllable dissolution process and opening a practical route toward electrode level circularity.

Kim, Kiwon [Cornell Univ., Ithaca, NY (United Stat↗
DOE OSTI2019

Dynamic spin localization and γ -magnets

Here, we explore an unusual type of quantum matter that can be realized by qubits having different physical origins. Interactions in this matter are described by essentially different coupling operators for all qubits. We show that the simplest such models, which can be realized with localized states in Dirac materials, satisfy integrability conditions that we use to describe pseudospin dynamics in a linearly time-dependent magnetic field. Generalizing to an arbitrary number of qubits, we construct a spin Hamiltonian, which we call the γ -magnet. This system does not conserve polarization of any spin and the net spin polarization. Nevertheless, for arbitrarily strong interactions, nonadiabatic dynamics, and any initial eigenstate, we find that quantum interference suppresses spin flips. This behavior resembles many-body localization but occurs in phase space of many spins rather than real space. This effect may not have a counterpart in classical physics and can be a signature of a new type of spin ordering, which is different from both disordered spin glasses and ordered phases of spin lattices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

GENESPACE tracks regions of interest and gene copy number variation across multiple genomes

The development of multiple chromosome-scale reference genome sequences in many taxonomic groups has yielded a high-resolution view of the patterns and processes of molecular evolution. Nonetheless, leveraging information across multiple genomes remains a significant challenge in nearly all eukaryotic systems. These challenges range from studying the evolution of chromosome structure, to finding candidate genes for quantitative trait loci, to testing hypotheses about speciation and adaptation. Here, we present GENESPACE, which addresses these challenges by integrating conserved gene order and orthology to define the expected physical position of all genes across multiple genomes. We demonstrate this utility by dissecting presence–absence, copy-number, and structural variation at three levels of biological organization: spanning 300 million years of vertebrate sex chromosome evolution, across the diversity of the Poaceae (grass) plant family, and among 26 maize cultivars. The methods to build and visualize syntenic orthology in the GENESPACE R package offer a significant addition to existing gene family and synteny programs, especially in polyploid, outbred, and other complex genomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration Strategy

EXECUTIVE SUMMARY The Light Water Reactor Sustainability Program Plant Modernization Pathway has been working with industry for a number of years to leverage digital technology to extend the life and improve the performance of the existing fleet through modernized technologies and improved processes for plant operation and power generation. This includes development of modernization solutions to improve reliability and economic performance while addressing US nuclear industry’s aging and obsolescence challenges. The objective of these efforts is to deliver a sustainable business model that enables US nuclear industry to remain competitive. Digital Infrastructure (DI) research has established a technical foundation for these efforts. This effort began with technical analysis and support for a safety-related instrumentation and control (I&C) pilot upgrade being performed at Constellation Energy Generation’s Limerick Nuclear Plant. The following publicly available reports were produced as part of this effort. • INL/EXT-20-61079, Vendor-Independent Design Requirements for a Boiling Water Reactor Safety System Upgrade [1] • INL/EXT-20-59371, Business Case Analysis for Digital Safety-Related Instrumentation & Control System Modernizations [2] • INL/EXT-20-59809, “Safety-Related Instrumentation and Control Pilot Upgrade: Initial Scoping Phase Implementation Report and Lessons Learned [3] • INL/RPT-23-72105, Safety-Related Instrumentation and Control Upgrade: Conceptual – Detailed Design Phase Report and Lessons Learned [4]

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Measurement of the inclusive WZ production cross section in pp collisions at $\sqrt{\textrm{s}}$ = 13.6 TeV

The inclusive WZ production cross section is measured in proton-proton collisions at a centre-of-mass energy of 13.6 TeV, using data collected during 2022 with the CMS detector, corresponding to an integrated luminosity of 34.7 fb −1 . The measurement uses multileptonic final states and a simultaneous likelihood fit to the number of events in four different lepton flavour categories: eee, ee μ , μμ e, and μμμ . The selection is optimized to minimize the number of background events, and relies on an efficient prompt lepton discrimination strategy. The WZ production cross section is measured in a phase space defined within a 30 GeV window around the Z boson mass, as σ total (pp → WZ) = 55.2 ± 1.2 (stat) ± 1.2 (syst) ± 0.8 (lumi) ± 0.3 (theo) pb. In addition, the cross section is measured in a fiducial phase space closer to the detector-level requirements. All the measurements presented in this paper are in agreement with standard model predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

A generative machine learning model for designing metal hydrides applied to hydrogen storage

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized hydrides, which constrains the discovery of optimal candidates. This work presents a framework that integrates causal discovery with a lightweight generative machine learning model to generate novel metal hydride candidates that may not exist in current databases. Using a dataset of 450 samples (270 training, 90 validation, and 90 testing), the model generates 1000 candidates. After ranking and filtering, six previously unreported chemical formulas and crystal structures are identified, four of which are validated by density functional theory simulations and show strong potential for future experimental investigation. Overall, the proposed framework provides a scalable and time-efficient approach for expanding hydrogen storage datasets and accelerating materials discovery.

generative model↗
DOE OSTI2021

Roles of miR-204 in retinal development and maintenance

Highlights: • miR-204 plays an important role in the development, maintenance, and diseases of the retina. • Various layers of the retina including RPE express miR-204. • Retinoblastoma, age-related macular degeneration, glaucoma and optic nerve injury are among the most common retinopathies caused by miR-204 dysfunction. • miR-204 target genes are involved in diverse signaling pathways crucial for retinal physiology. The retina is the innermost part of the eye of most vertebrates and it is essential for vision. The development, maintenance, and function of this laminated structure is tightly regulated by numerous genes. Deficiencies in the expression of these genes as well as deregulation of various molecular mechanisms can cause retinopathies and blindness. MicroRNAs (miRNAs) are one of the most important and effective molecular regulatory mechanisms that underlie the biology of the retina. miRNAs have specific functional roles in the development and maintenance of different retinal layers and retinal cell types. While previous studies have reported a large number of miRNAs linked to development, maintenance and diseases of the retina, no comprehensive study has properly discussed and integrated data from these studies. Given the particular importance of miR-204 in retinal biology, we intend to critically discuss the expression and functional significance of this miRNA in the development, maintenance, and pathologies of the retina. Moreover, we explore biological processes through which miR-204 influences retinal pathophysiology. This review highlights the crucial functions of miR-204 in the retina and suggests the putative mechanism of miR-204 action in retinal biology.

60 APPLIED LIFE SCIENCES↗