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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Preliminary Evaluation of Joint Electricity-Hydrogen Concept of Operations

An initial thermal power dispatch (TPD) concept of operations was evaluated that couples a nuclear power plant to a nearby hydrogen production plant. GSE Systems’ generic pressurized water reactor full-scope simulator was modified with a TPD model comprised of a thermal power extraction and delivery system. A prototype human-system interface (HSI) was developed to interact with the TPD model and allow participants to execute the basic operating scenarios for normal operations. Four retired operators performed the evaluation, and due to COVID-19 travel restrictions, the original in-person experimental design was restructured to support a remote participator evaluation using a web meeting platform. Data from operator feedback, observations from the research team, and quantitative survey responses revealed that the initial TPD concept of operations is feasible. The operators were comfortable with the engineered system and HSI and could manage it without adverse impacts to reactor power, plant safety, or equipment. Findings are discussed in terms of both the TPD system design and HSI performance.

human factors↗
DOE OSTI2026

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Demonstration of a third-order hierarchy of topological states in a three-dimensional acoustic metamaterial

Classical wave systems have constituted an excellent platform for emulating complex quantum phenomena, such as demonstrating topological phenomena in photonics and acoustics. Recently, a new class of topological states localized in more than one dimension of a D -dimensional system, referred to as higher-order topological (HOT) states, has been reported, offering an even more versatile platform to confine and control classical radiation and mechanical motion. Here, we design and experimentally study a 3D topological acoustic metamaterial supporting third-order (0D) topological corner states along with second-order (1D) edge states and first-order (2D) surface states within the same topological bandgap, thus establishing a full hierarchy of nontrivial bulk polarization–induced states in three dimensions. The assembled 3D topological metamaterial represents the acoustic analog of a pyrochlore lattice made of interconnected molecules, and is shown to exhibit topological bulk polarization, leading to the emergence of boundary states.

Science & Technology - Other Topics↗
DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗
DOE OSTI2025

Ultra-thin photonic crystal slab metalenses [Invited]

We report a novel ultra-thin metalens design based on photonic crystal slab (PCS) resonance modes. We experimentally verified with a metalens structure based on amorphous silicon on a quartz material platform by implementing the optical guided resonance on the PCS. The PCS metalens designs feature an ultra-thin device layer of about 160 nm at an operation wavelength of 940 nm. A full 2π transmission phase transition is realized by varying the air hole sizes at the design wavelength. Metalens devices with different phase change gradients were designed and fabricated to achieve different NAs. A maximum of 86.4% focusing efficiency is achieved. Imaging capabilities are characterized, and clear images are observed within the field of view. The PC resonance-based phase modulation design can be applied to optical beam manipulation, phase plate design, imaging, and laser beam formation applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Agilent AgileBioFoundry CRADA (Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOF-MS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Therefore, our accomplishment in this CRADA improved the efficiency and accuracy of strain testing by developing and implementing fast analytical methods, robust processing tools, and software for predicting the best methods for UHPLC analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Rare earth separation in voltage-gated 2D MXene membranes

The separation of rare earth elements (REEs) has historically been a complicated and expensive process, producing significant amounts of pollution. To this end, MXene membranes (MXMs) have attracted researchers' interest. It has been demonstrated that MXMs are capable of separating ions and that it is possible to precisely control the separation rate by applying a voltage to the membrane. Indeed, due to their chemical nature, MXenes show outstanding electrical conductivity. However, the effect of applied voltage on the permeation rate and separation effects of iconic species remains an intriguing area of research. In this work, we demonstrate how applying different voltages (gate voltage) to a MXM affects the permeation rate of various REE ions. Our hypothesis to explain MXMs behavior towards REE is that under negative voltage, the interlayer spacing decreases due to attraction between charged MXene surfaces and intercalated cations, increasing the separation factor between REEs. Under positive voltage, the interlayer spacing increases due to repulsion between the MXene surfaces and intercalated cations. However, we demonstrate relatively poor separation capability for REEs at 1mM starting concentration and 1.0 V applied DC voltage (separation factor ~1-3). This study demonstrates the need for future experiments to observe varied experimental conditions and chemical functionalization to determine whether MXene membranes can be an efficient platform for REE separation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Development and implementation of high-throughput proteomic and metabolomics assays by using advanced chromatographic and mass spectrometric systems (CRADA Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOFMS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Overall, the project advanced rapid metabolomics by combining liquid chromatography, ion mobility spectrometry, and data-independent mass spectrometry with machine learning. This multidimensional approach uses retention time, collision cross-section, precursor mass, and fragment-ion information to distinguish chemically similar metabolites that can be difficult to resolve using conventional liquid- or gas-chromatography methods. The resulting workflow also provided automated metabolite-identification error estimates, addressing a recognized need for statistical confidence measures in metabolomics.

Petzold, Christopher [Lawrence Berkeley National L↗
DOE OSTI2021

Side-channel Leakage Assessment Metrics: A Case Study of GIFT Block Ciphers

Determination of an adequate level of security and providing subsequent mechanisms to achieve it, is one of the most pressing problems regarding embedded computing devices. While there are some solutions available for resource-rich computer systems, direct application of these solutions to resource-constrained environments are often unfeasible. The fundamental problem for such resource-constrained systems is the fact that current cryptographic algorithms utilize significant energy consumption and storage overhead. Both the cryptographic algorithm and its physical implementation affect the resilience of a cryptosystem against side-channel attacks. A side-channel attack represents a process that exploits leakages in order to extract sensitive information such as the key. This paper focuses on Correlation Power Analysis (CPA) which is side-channel attack based on the power consumption leakage. In 2016 the U.S. Commerce Department’s National Institute of Standards and Technology (NIST) initiated the call for proposals of new cryptographic algorithms to strengthen the cryptographic defense of networked devices against cyberattacks and to protect the data created by those innumerable device. This work evaluates S-boxes used by NIST candidates PICCOLO, GIFT, and PRESENT, as well as several S-box variants that demonstrated sufficient weaknesses against classical cryptanalysis, for a quantitative comparison in terms of resiliency to CPA attack. Three well-known theoretical metrics are evaluated: transparency order (TO and RTO), nonlinearity, and signal-to-noise (SNR) ratio, aiming to characterize the resistance of these S-boxes against adversaries exploiting physical leakages. Experimental results from attacks on an 8- bit XMEGA were obtained via the ChipWhisperer platform and of all the S-boxes evaluated, GIFT64 with a PICCOLO S-box was found to be the most susceptible to CPA. Results showed that variations in TO and RTO were not sufficient to ensure practical CPA resistance and that among S-boxes with equal non-linearity there were no significant differences in the TO and SNR variants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Side-channel Leakage Assessment Metrics: A Case Study of GIFT Block Ciphers

Determination of an adequate level of security and providing subsequent mechanisms to achieve it, is one of the most pressing problems regarding embedded computing devices. While there are some solutions available for resource-rich computer systems, direct application of these solutions to resource-constrained environments are often unfeasible. The fundamental problem for such resource-constrained systems is the fact that current cryptographic algorithms utilize significant energy consumption and storage overhead. Both the cryptographic algorithm and its physical implementation affect the resilience of a cryptosystem against side-channel attacks. A side-channel attack represents a process that exploits leakages in order to extract sensitive information such as the key. This paper focuses on Correlation Power Analysis (CPA) which is side-channel attack based on the power consumption leakage. In 2016 the U.S. Commerce Department’s National Institute of Standards and Technology (NIST) initiated the call for proposals of new cryptographic algorithms to strengthen the cryptographic defense of networked devices against cyberattacks and to protect the data created by those innumerable device. This work evaluates S-boxes used by NIST candidates PICCOLO, GIFT, and PRESENT, as well as several S-box variants that demonstrated sufficient weaknesses against classical cryptanalysis, for a quantitative comparison in terms of resiliency to CPA attack. Three well-known theoretical metrics are evaluated: transparency order (TO and RTO), nonlinearity, and signal-to-noise (SNR) ratio, aiming to characterize the resistance of these S-boxes against adversaries exploiting physical leakages. Experimental results from attacks on an 8- bit XMEGA were obtained via the ChipWhisperer platform and of all the S-boxes evaluated, GIFT64 with a PICCOLO S-box was found to be the most susceptible to CPA. Results showed that variations in TO and RTO were not sufficient to ensure practical CPA resistance and that among S-boxes with equal non-linearity there were no significant differences in the TO and SNR variants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Light-Induced Dynamic Frequency Shifting of Microwave Photons in a Superconducting Electro-Optic Converter

Hybrid superconducting-photonic microresonators are a promising platform for realizing microwave-to-optical transduction. However, the absorption of scattered photons by the superconductors leads to unintended microwave resonance-frequency variation and line-width broadening. Here, we experimentally study the dynamics of this effect and its impact on microwave-to-optics conversion in an integrated lithium niobate–superconductor hybrid-resonator platform. Here, we unveil an adiabatic frequency shifting of the intracavity microwave photons induced by the fast photoresponses of the thin-film superconducting resonator. As a result, the temporal and spectral responses of electro-optics transduction are modified and well described by our theoretical model. This work provides insights into the light-induced conversion dynamics that must be considered in future designs of hybrid superconducting-photonic system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Density measurements for the National Ignition Facility (NIF) opacity platform

The Opacity Platform on the National Ignition Facility (NIF) has been developed to measure opacities at varying densities and temperatures relevant to the solar interior and thermal cooling rates in white dwarf stars. The typical temperatures reached at NIF range between 150 and 210 eV, which allow these measurements to be performed experimentally. The captured opacities are crucial to validating radiation-hydrodynamic models that are used in astrophysics. The NIF opacity platform has a unique new capability that allows in situ measurement of the sample expansion. The sample expansion data are used to better understand the plasma conditions in our experiments by inferring the sample density throughout the duration of the laser drive. Here, we present the details of the density measurement technique, data analysis, and recent results for Fe and MgO.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

n-Propylbenzene Droplet Combustion: Experiments and Numerical Modeling

n-Propylbenzene (PB, C9H12, 432K boiling point) is important as a constituent in surrogates for some transportation fuels but little is understood about its droplet burning characteristics. We present an experimental and numerical study of a fuel droplet burning under conditions where the sole means of gas transport is fuel evaporation at the droplet surface thereby creating a one-dimensional gas transport that is amenable to detailed numerical modeling. The one-dimensional gas transport that results is amenable to detailed numerical modeling. Initial droplet diameters (Do) ranged from 0.3 mm to about 5 mm to better understand the mechanisms that control burning over such a wide range of Do. For Do < 1 mm droplets were burned while anchored to 14 m SiC fibers within a sealed container in free-fall during which time the droplets were ignited by spark discharge and the burning process recorded by video cameras. Larger and free-floating droplets were studied in the spaced-based platform of the orbiting International Space Station for Do > 1.0 mm which provided unlimited times for experimental observation. Measurements of droplet, flame and soot shell diameters were made and are discussed in the presentation. The experimental results showed formation of optically thick soot clouds developing during burning that required a robust image analysis algorithm to enable measurement of droplet diameter. The measured droplet diameters were well predicted by a numerical model that included soot formation, a PB kinetic mechanism comprising 576 species and 27369 reactions, unsteady gas and liquid transport, variable properties and radiative transport. Flame diameters showed more variability compared to the simulations, depending on how the flame was defined (peak gas temperature and OH concentration). Droplets burned slower as Do was increased and the PB sooting propensity increased with Do. Flame extinction was observed for Do > 3.3 mm indicating a strong effect of radiation as Do was increased compared to the smaller droplet diameters examined where extinction was not experimentally observed. For the largest droplets examined the possibility that the observed extinction is indicative of a transition to cool flame burning is still under investigation.

Guo, Songtao↗
DOE OSTI2023

Experimental and theoretical investigations of rotating algae biofilm reactors (RABRs): Areal productivity, nutrient recovery, and energy efficiency

Microalgae biofilms have been demonstrated to recover nutrients from wastewater and serve as biomass feedstock for bioproducts. However, there is a need to develop a platform to quantitatively describe microalgae biofilm production, which can provide guidance and insights for improving biomass areal productivity and nutrient uptake efficiency. Here, this paper proposes a unified experimental and theoretical framework to investigate algae biofilm growth on a rotating algae biofilm reactor (RABR). Experimental laboratory setups are used to conduct controlled experiments on testing environmental and operational factors for RABRs. We propose a differential–integral equation‐based mathematical model for microalgae biofilm cultivation guided by laboratory experimental findings. The predictive mathematical model development is coordinated with laboratory experiments of biofilm areal productivity associated with ammonia and inorganic phosphorus uptake by RABRs. The unified experimental and theoretical tool is used to investigate the effects of RABR rotating velocity, duty cycle (DC), and light intensity on algae biofilm growth, areal productivity, nutrient uptake efficiency, and energy efficiency in wastewater treatment. Our framework indicates that maintaining a reasonable light intensity range improves biomass areal productivity and nutrient uptake efficiency. Our framework also indicates that faster RABR rotation benefits biomass areal productivity. However, maximizing the nutrient uptake efficiency requires a reasonably low RABR rotating speed. Energy efficiency is strongly correlated with RABR rotating speed and DC.

09 BIOMASS FUELS↗
DOE OSTI2026

From Reproducible Edge–Cloud Experimentation to Real-World Practice: The E2Clab Experience

Reproducibility is already difficult in distributed systems; on the computing continuum, it becomes substantially harder. Applications that span sensing devices, edge and fog resources, and cloud platforms must be evaluated across heterogeneous hardware, variable network conditions, cross-layer orchestration decisions, and long-running workflow lifecycles. We use E2Clab as a case study to examine these challenges and their implications for experimental methodology. We explain why reproducible experimentation is harder on the continuum, then revisit E2Clab as an initial response based on explicit modeling of infrastructure, workflow lifecycle, and artifacts. Lastly, we discuss how its evolution toward more realistic application settings can be understood through the lens of Translational Computer Science. We argue that reproducible continuum experimentation requires methods that are rigorous enough for research while remaining adaptable to real-world practice.

42 ENGINEERING↗
DOE OSTI2025

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Platform for probing radiation transport properties of hydrogen at conditions found in the deep interiors of red dwarfs

We describe an experimental concept at the National Ignition Facility for specifically tailored spherical implosions to compress hydrogen to extreme densities (up to ∼800× solid density, electron number density ne∼4×1025 cm−3) at moderate temperatures (T∼200 eV), i.e., to conditions, which are relevant to the interiors of red dwarf stars. The dense plasma will be probed by laser-generated x-ray radiation of different photon energy to determine the plasma opacity due to collisional (free–free) absorption and Thomson scattering. The obtained results will benchmark radiation transport models, which in the case for free–free absorption show strong deviations at conditions relevant to red dwarfs. This very first experimental test of free–free opacity models at these extreme states will help to constrain where inside those celestial objects energy transport is dominated by radiation or convection. Moreover, our study will inform models for other important processes in dense plasmas, which are based on electron–ion collisions, e.g., stopping of swift ions or electron–ion temperature relaxation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Optimization of Functionally Graded Materials Using Additive Manufacturing: An Integrated Experimental and Computational Approach (Abbreviated Final Report)

Many advanced technologies, such as next-generation energy systems, aerospace vehicles, and defense platforms, require materials that can withstand extreme environments, including high temperatures, corrosion, and radiation, while remaining strong and lightweight. Traditionally, joining different materials to achieve these properties introduces weak, failure-prone interfaces and defects that limit performance. Our research aimed to overcome this challenge by using additive manufacturing, specifically directed energy deposition, to create functionally graded materials—components with smooth transitions between different metals. This approach eliminates sharp boundaries and allows for tailored material properties throughout a part.

36 MATERIALS SCIENCE↗