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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Characterization and Understanding of Thermal Transport in Stationary and Moving Particle Beds for Concentrating Solar Power

Concentrating solar power (CSP) coupled with thermal energy storage (TES) is being considered as an appealing solution to deliver stable, dispatchable, and inexpensive electricity generation from renewable solar energy. The heat from the HTF is stored in a TES system that is significantly less expensive and more scalable than electrochemical storage, enabling electricity generation when the sunlight is unavailable. The general concentrating solar thermal technologies are being pushed to higher temperature for higher efficiency and lower cost in a diverse range application in electricity generation (in CSP), industrial heating, and thermochemical fuel productions. Inert and abundant solid particles are becoming increasingly more important for these emerging applications. Heat transfer in both stationary and moving particle beds have been studied for many decades, revealing a great deal of insights on the mechanisms. Yet, there are still several unresolved problems from both fundamental understanding and technological applications points of view. In this Chapter, we will attempt to provide an up-to-date picture of thermal transport in stationary and moving particle beds. In both cases, we will review historical and contemporary developments in the theoretical, computational, and experimental aspects of heat transfer and related behaviors in particle beds. Here, we will discuss both the advancements and limitations of the existing studies and point to future developments towards deeper fundamental understandings and better engineering applications.

14 SOLAR ENERGY↗
DOE OSTI2023

Beam study on low dispersion CEBAF arcs

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab employs recirculating linac SRF technology to generate a high polarization 12 GeV electron beam for nuclear physics users. New opportunities to study multipass energy recovery have also emerged with the proposal of a 5-pass energy recovery demonstration, ER@CEBAF. New beam optics with minimized beta functions have been developed and tested to avoid collective beam instabilities for multi-pass beams and meet the beam requirements of the nuclear physics community. To enable energy recovery for a common arc beam transport of five passes, achromatic and isochronous arc optics conditions were satisfied by re-designing the transverse optics of CEBAF. This paper focuses on beam studies conducted to study the newly-designed, low-dispersion, lowest energy arcs for CEBAF operations and ER@CEBAF.

Neththikumara, I.↗
DOE OSTI2020

Specifying Calibration of Environmental Sensors

The emergence of the Internet of Things is resulting in an increased ability of devices and systems to share data and is generating increasing interest in integrating sensors into a variety of devices deployed in the built environment. The value of such data is a function of how the data can be used. Data-producing devices and systems that enable valuable use-cases in turn can be seen as more valuable. Lighting systems are particularly interesting platforms for integrated sensors. Both indoor and outdoor lighting devices are becoming more connected, and their location is often ideally suited for hosting environmental sensors that can characterize the properties of indoor or outdoor spaces in ways that support a wide variety of use cases, from improving air quality to supporting fault diagnostics and prediction. The value of environmental-sensor-driven use-cases and the lighting systems that house them is dependent to some degree on sensor accuracy. Environmental sensors utilize a wide variety of sensing techniques or technologies and have varying accuracy. More-accurate, laboratory-grade products or reference standards are often used to characterize, refine, calibrate, adjust, and monitor devices that are deployed, or are intended to be deployed, in physical spaces of interest. Sensors or reference standards need to be calibrated periodically to ensure that their use yields accurate measurements. Calibration needs, however, vary in sophistication, based on user and use-case requirements. This paper provides guidance for evaluating the performance of environmental sensors so as to ensure that they meet user or use-case needs. It describes best practices that have been developed for a) calibrating sensors to ensure some known level of accuracy, and b) determining whether calibration-laboratory accreditation meets user or use-case needs. Excerpts from laboratory scopes of accreditation are shared to reveal the diversity of terminology and format among them. In an effort to aid those who currently have sensors calibrated or who have new or changing needs for sensor calibration, rationale is provided for why a specification might be used to request calibration services that meet specific needs. Commercially available calibration-service providers that are accredited for environmental-sensor calibration are compared and contrasted, and a specification template that might be used for requesting this calibration is presented. The specification template should be tailored to meet each user’s needs. To illustrate, an example set of environmental-sensor test conditions (reflecting the planned usage of the device to be calibrated) is used to develop a customized calibration specification, and commercially available service providers are assessed in terms of their qualifications for calibration to that particular implementation of the specification template.

42 ENGINEERING↗
DOE OSTI2022

Enabling Floating Solar Photovoltaic (FPV) Deployment: Exploring the Operational Benefits of Floating Solar-Hydropower Hybrids

The Southeast (SE) Asia region is undergoing rapid energy sector transitions and exploring the potential role of renewables - including solar photovoltaics (PV) - as it becomes increasingly competitive as a result of technological advances and falling capital costs. Low-cost solar PV provides countries in the region with an option to meet increasing energy demand and diversify generation portfolios, complementing hydropower and thermal-dominant systems and strengthening energy security throughout the region. Floating solar PV (FPV) has emerged as an attractive application of solar PV that allows for systems to be floated on water bodies. Pairing FPV in hybrid systems with hydropower may also provide significant value for power systems in the region, beyond oft-cited co-benefits of stand-alone FPV. Despite growing interest in FPV systems, few applications of hybrid FPV-hydropower systems exist in SE Asia, and limited information is available about the co-benefits these systems may provide for potential adopters. This work, funded by the U.S. Agency for International Development (USAID) through the Advanced Energy Partnership for Asia, explores the value that hybrid FPV-hydropower systems may provide to the power systems of SE Asian countries. This work on the value of hybrid FPV-hydropower systems is accompanied by a recent report, Creating an Enabling Policy and Regulatory Environment for Floating Solar Photovoltaics: Review of Barriers to FPV Deployment in Southeast Asia, also focused on SE Asia.

14 SOLAR ENERGY↗
DOE OSTI2022

2022 Summer Resource Adequacy in the ERCOT Region

This report is a 2022 update to the National Energy Technology Laboratory (NETL) report that examined the potential system performance of the Electric Reliability Council of Texas (ERCOT) system during the summer of 2021. Anticipated summer reserve margins in ERCOT have risen year-over-year from the 15.7 percent reported in ERCOT’s Final Seasonal Assessment of Resource Adequacy (SARA) for Summer 2021 to 22.8 percent in the Final SARA for Summer 2022, driven mostly by increases in wind and solar generation. Using data from ERCOT’s 2022 Summer SARA, Capacity, Demand and Reserves (CDR) reports, and historical performance data obtained from ERCOT and Hitachi Energy Velocity Suite, six economic dispatch scenarios using PROMOD were developed to assess the risk to ERCOT of a load shedding event for Summer 2022. The results suggests that ERCOT may be facing a very tight resource adequacy situation, with the potential for a serious shortfall during the summer peak, usually the end of July through mid-August, if demand and generator outage rates significantly exceed peak levels. Under these conditions, ERCOT will need to call on its operating tools, including Energy Emergency Alerts (EEA) and calls to conserve electricity, to maintain reliability and continue serving load. Those measures alone may not be sufficient to avert a shedding of load.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Controlling Interfacial Energetics and Charge Transfer Rates in 2D Semiconductors: Fundamental Studies en Route to Photoelectrochemical Energy Conversion Beyond the Shockley-Queisser Limit (Final Scientific/Technical Report)

Current photovoltaic and solar-to-fuel technologies do not fully utilize the energy of sunlight because excess photon energy above the semiconductor band gap is rapidly lost as heat through hot-carrier thermalization. Overcoming this loss mechanism is critical, as hot-carrier-based energy conversion systems are predicted to exceed the conventional efficiency limit of ~33%. This project advanced fundamental understanding of hot-carrier energy conversion in two-dimensional (2D) semiconductors, with a focus on monolayer MoS 2 . Using a combination of electrochemical microscopy and in situ ultrafast spectroscopic measurements, this research directly demonstrated hot-carrier extraction from monolayer MoS 2 photoelectrodes in proof-of-concept liquid junction solar cells. These measurements established that hot-carrier transfer can compete with ultrafast carrier cooling at solid–liquid interfaces, providing unambiguous experimental evidence that hot-carrier extraction is feasible in atomically thin semiconductors under operating photoelectrochemical conditions. Beyond demonstration, the project identified design rules for tuning hot-carrier extraction rates relative to cooling rates in 2D semiconductor photoelectrodes. The outcomes of this research provide foundational thermodynamic and kinetic insights for the rational design of next-generation hot-carrier-enabled solar energy conversion systems. These findings have broad implications for photoelectrochemical solar fuels production, electrocatalysis, and emerging energy conversion architectures that seek to harness nonequilibrium charge carriers for enhanced efficiency.

14 SOLAR ENERGY↗
DOE OSTI2024

Ultrathin Boron Growth onto Nanodiamond Surfaces via Electrophilic Boron Precursors

Diamond as a templating substrate is largely unexplored, and the unique properties of diamond, including its large bandgap, thermal conductance, and lack of cytotoxicity, makes it versatile in emergent technologies in medicine and quantum sensing. Surface termination of an inert diamond substrate and its chemical reactivity are key in generating new bonds for nucleation and growth of an overlayer material. Oxidized high-pressure high temperature (HPHT) nanodiamonds (NDs) are largely terminated by alcohols that act as nucleophiles to initiate covalent bond formation when an electrophilic reactant is available. In this work, we demonstrate a templated synthesis of ultrathin boron on ND surfaces using trigonal boron compounds. Boron trichloride (BCl 3 ), boron tribromide (BBr 3 ), and borane (BH 3 ) were found to react with ND substrates at room temperature in inert conditions. BBr 3 and BCl 3 were highly reactive with the diamond surface, and sheet-like structures were produced and verified with electron microscopy. Surface-sensitive spectroscopies were used to probe the molecular and atomic structure of the ND constructs’ surface, and quantification showed the boron shell was less than 1 nm thick after 1–24 h reactions. Observation of the reaction supports a self-terminating mechanism, similar to atomic layer deposition growth, and is likely due to the quenching of alcohols on the diamond surface. X-ray absorption spectroscopy revealed that boron-termination generated midgap electronic states that were originally predicted by density functional theory (DFT) several years ago. DFT also predicted a negative electron surface, which has yet to be confirmed experimentally here. The boron-diamond nanostructures were found to aggregate in dichloromethane and were dispersed in various solvents and characterized with dynamic light scattering for future cell imaging or cancer therapy applications using boron neutron capture therapy (BNCT). The unique templating mechanism based on nucleophilic alcohols and electrophilic trigonal precursors allows for covalent bond formation and will be of interest to researchers using diamond for quantum sensing, additive manufacturing, BNCT, and potentially as an electron emitter.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Diversification of multipotential postmitotic mouse retinal ganglion cell precursors into discrete types

The genesis of broad neuronal classes from multipotential neural progenitor cells has been extensively studied, but less is known about the diversification of a single neuronal class into multiple types. We used single-cell RNA-seq to study how newly born (postmitotic) mouse retinal ganglion cell (RGC) precursors diversify into ~45 discrete types. Computational analysis provides evidence that RGC transcriptomic type identity is not specified at mitotic exit, but acquired by gradual, asynchronous restriction of postmitotic multipotential precursors. Some types are not identifiable until a week after they are generated. Immature RGCs may be specified to project ipsilaterally or contralaterally to the rest of the brain before their type identity emerges. Optimal transport inference identifies groups of RGC precursors with largely nonoverlapping fates, distinguished by selectively expressed transcription factors that could act as fate determinants. Our study provides a framework for investigating the molecular diversification of discrete types within a neuronal class.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Emergent Halperin–Saslow mode, gauge glass and quenched disorders in quantum Ising magnet TmMgGaO 4

Quenched disorders could bring novel quantum excitations and models to certain quantum magnets. Motivated by recent experiments on the quantum Ising magnet TmMgGaO 4 , we explore the effects of the quenched disorder and the interlayer coupling in this triangular lattice Ising antiferromagnet. It is pointed out that the weak quenched (nonmagnetic) disorder would convert the emergent 2D Berezinskii–Kosterlitz–Thouless (BKT) phase and the critical region into a U(1) gauge glass. There will be an emergent Halperin–Saslow mode associated with this gauge glass. Using the Imry-Ma’s renormalization group result, we explain the fate of the finite-field [Formula: see text] symmetry breaking transition at the low temperatures. The ferromagnetic interlayer coupling would suppress the BKT phase and generate a tiny ferromagnetism. With quenched disorders, this interlayer coupling changes the 2D gauge glass into a 3D gauge glass, and the Halperin–Saslow mode persists. This work merely focuses on addressing a phase regime in terms of emergent U(1) gauge glass behaviors and hope to inspire future works and thoughts in weakly disordered frustrated magnets in general.

Physics↗
DOE OSTI2024

Bridging the Gap Between LLMs and LNS with Dynamic Data Format and Architecture Codesign

Deep neural networks (DNNs) have achieved tremendous success in the past few years. However, their training and inference demand exceptional computational and memory resources. Quantization has been shown as an effective approach to mitigate the cost, with the mainstream data types reduced from FP32 to FP16/BF16 and recently FP8 in the latest NVIDIA H100 GPUs. With increasingly aggressive quantization, however, the conventional floating-point formats suffer from limited precision in representing numbers around zero. Recently, NVIDIA demonstrated the potential of using a Logarithmic Number System (LNS) for the next generation of tensor cores. While LNS mitigates the hurdles in representing small numbers, in this work we observed a mismatch between LNS and the emerging Large Language Models (LLM), where LLM exhibits significant outliers when directly adopting the LNS format. In this paper, we present a data-format/architecture codesign to bright this gap. On the format side, we propose a dynamic LNS format to flexibly represent outliers at a higher precision, by exploiting asymmetry in the LNS representation and identifying outliers through a per-vector basis. On the architecture side, for demonstration, we realize the dynamic LNS format in a systolic array, which can handle the irregularity of the outliers at runtime. We implement our approach on an Alveo U280 FPGA as a prototype. Experimental results show that our design can effectively handle the outliers and resolve the mismatch between LNS and LLM, contributing to an accuracy improvement of 15.4% and 16% over the floating-point and the original LNS baselines, using four state-of-the-art LLM models. Our observation and design lay a solid foundation for the large-scale adoption of the LNS format in the next-generation deep learning hardware.

Haghi, Pouya↗
DOE OSTI2022

AI-enhanced Codesign for Next-Generation Neuromorphic Circuits and Systems

This report details work that was completed to address the Fiscal Year 2022 Advanced Science and Technology (AS&T) Laboratory Directed Research and Development (LDRD) call for “AI-enhanced Co-Design of Next Generation Microelectronics.” This project required concurrent contributions from the fields of 1) materials science, 2) devices and circuits, 3) physics of computing, and 4) algorithms and system architectures. During this project, we developed AI-enhanced circuit design methods that relied on reinforcement learning and evolutionary algorithms. The AI-enhanced design methods were tested on neuromorphic circuit design problems that have real-world applications related to Sandia’s mission needs. The developed methods enable the design of circuits, including circuits that are built from emerging devices, and they were also extended to enable novel device discovery. We expect that these AI-enhanced design methods will accelerate progress towards developing next-generation, high-performance neuromorphic computing systems.

42 ENGINEERING↗
DOE OSTI2024

EMP Testing of NAE Magnetic Motor Starters

Sandia National Laboratories (SNL) performed a high-altitude nuclear electromagnetic pulse (HEMP) critical generation station component vulnerability test campaign with a focus on high-frequency, conducted early-time (E1) HEMP for the Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER). This report provides vulnerability test results to investigate component response and/or damage thresholds to reasonable HEMP threat levels that will help to inform site vulnerability assessments, mitigation planning, and modeling calibrations. This work details testing of North American Electric (NAE) magnetic motor starters to determine the effects of conducted HEMP environments. Motor starters are the control elements that provide power to motors throughout a generating plant; a starter going offline would cause loss of power to critical pumps and compressors, which could lead to component damage or unplanned plant outages. Additionally, failed starters would be unable to support plant startup. Six industrial motor starters were tested: two 2 horsepower (HP) starters with breaker disconnects and typical protection equipment, two 20 HP starters with breaker disconnects, and two 20 HP starters with fused disconnects. Each starter was placed in a circuit with a generator and inductive motor matching the starter rating. The conducted EMP insult was injected on the power cables passing through the motor starter, with separate tests for the generator and motor sides of the starter.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2020

Emergence of self-organized multivortex states in flocks of active rollers

Active matter, both synthetic and biological, demonstrates complex spatiotemporal self-organization and the emergence of collective behavior. A coherent rotational motion, the vortex phase, is of great interest because of its ability to orchestrate well-organized motion of self-propelled particles over large distances. However, its generation without geometrical confinement has been a challenge. Here, we show by experiments and computational modeling that concentrated magnetic rollers self-organize into multivortex states in an unconfined environment. We find that the neighboring vortices more likely occur with the opposite sense of rotation. Our studies provide insights into the mechanism for the emergence of coherent collective motion on the macroscale from the coupling between microscale rotation and translation of individual active elements. These results may stimulate design strategies for self-assembled dynamic materials and microrobotics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The implications of uncertain renewable resource potentials for global wind and solar electricity projections

Studies exploring long-term energy system transitions rely on resource cost-supply curves derived from estimates of renewable energy (RE) potentials to generate wind and solar power projections. However, estimates of RE potentials are characterized by large uncertainties stemming from methodological assumptions that vary across studies, including factors such as the suitability of land and the performance and configuration of technology. Based on a synthesis of modeling approaches and parameter values used in prior studies, we explore the implications of these uncertain assumptions for onshore wind and solar photovoltaic electricity generation projections globally using the Global Change Analysis Model. We show that variability in parametric assumptions related to land use (e.g. land suitability) are responsible for the most substantial uncertainty in both wind and solar generation projections. Additionally, assumptions about the average turbine installation density and turbine technology are responsible for substantial uncertainty in wind generation projections. Under scenarios that account for climate impacts on wind and solar energy, we find that these parametric uncertainties are far more significant than those emerging from differences in climate models and scenarios in a global assessment, but uncertainty surrounding climate impacts (across models and scenarios) have significant effects regionally, especially for wind. Our analysis suggests the need for studies focusing on long-term energy system transitions to account for this uncertainty.

14 SOLAR ENERGY↗
DOE OSTI2020

Toward Exascale: Overview of Large Eddy Simulations and Direct Numerical Simulations of Nuclear Reactor Flows with the Spectral Element Method in Nek5000

At the beginning of the last decade, Petascale supercomputers (i.e., computers capable of more than 1 petaFLOP) emerged. Now, at the dawn of exascale supercomputing, we provide a review of recent landmark simulations of portions of reactor components with turbulence-resolving techniques that this computational power has made possible. In fact, these simulations have provided invaluable insight into flow dynamics, which is difficult or often impossible to obtain with experiments alone. We focus on simulations performed with the spectral element method, as this method has emerged as a powerful tool to deliver massively parallel calculations at high fidelity by using large eddy simulation or direct numerical simulation. We also limit this paper to constant-property incompressible flow of a Newtonian fluid in the absence of other body or external forces, although the method is by no means limited to this class of flows. We briefly review the fundamentals of the method and the reasons it is compelling for the simulation of nuclear engineering flows. We review in detail a series of Petascale simulations, including the simulations of helical coil steam generators, fuel assemblies, and pebble beds. Even with Petascale computing, however, limitations for nuclear modeling and simulation tools remain. In particular, the size and scope of turbulence-resolving simulations are still limited by computing power and resolution requirements, which scale with the Reynolds number. In the final part of this paper, we discuss the future of the field, including recent advancements in emerging architectures such as GPUbased supercomputers, which are expected to power the next generation of high-performance computers.

computational fluid dynamics↗
DOE OSTI2024

Ultrafast Formation of Charge Transfer Trions at Molecular‐Functionalized 2D MoS 2 Interfaces

Abstract In this work, we investigate trion dynamics occurring at the heterojunction between organometallic molecules and a monolayer transition metal dichalcogenide (TMD) with transient electronic sum frequency generation (tr‐ESFG) spectroscopy. By pumping at 2.4 eV with laser pulses, we have observed an ultrafast hole transfer, succeeded by the emergence of charge‐transfer trions. This observation is facilitated by the cancellation of ground state bleach and stimulated emission signals due to their opposite phases, making tr‐ESFG especially sensitive to the trion formation dynamics. The presence of charge‐transfer trion at molecular functionalized TMD monolayers suggests the potential for engineering the local electronic structures and dynamics of specific locations on TMDs and offers a potential for transferring unique electronic attributes of TMD to the molecular layers.

Jing, Yuancheng↗
DOE OSTI2025

Energy innovation in the US buildings sector: Setting the stage and mapping the future

Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry.

Langevin, Jared↗