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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 199 records · Page 11

Harnessing dimethyl ether with ultra-low-grade heat for scaling-resistant brine concentration and fractional crystallization

Solvent-driven separations may enable scalable concentration of hypersaline brines, supporting a circular resource economy from the extraction of lithium and rare earth elements from spent battery and magnet leachates. This work analyses a novel solvent-driven water extraction (SDWE) system employing dimethyl ether (DME) and ultra-low-grade heat for brine concentration and fractional crystallization. SDWE exploits DME’s unique properties: (1) a low dielectric constant that promotes water solubility over charged solutes by a factor of 10 3 , and (2) a high volatility that facilitate efficient DME reconcentration with ultra-low-grade heat. The techno-economic viability of SDWE is assessed with a computational framework that encompasses a liquid–liquid separator and a solvent concentrator. We integrate the extended universal quasichemical model with the virial equation of state to predict the compositions of the complex three-phase DME-water mixture at vapor–liquid and liquid–liquid equilibrium. Subsequently, we optimize the thermodynamic and economic performance of SDWE, by controlling the interstage flash pressure, heat source temperature, and the number of concentrating stages. DME-based SDWE concentrates an input saline feed to 5.5 M and regenerates over 99 % of the DME using ultra-low-grade heat below 50 °C, with a DME/water selectivity ratio of 125. Here our calculations reveal that optimal performance is achieved at interstage flash pressures of 0.4 – 0.5 bar for heat source temperatures between 323–373 K, with improved exergetic efficiencies at lower temperatures. At a heat source temperature of 323 K and an interstage pressure of 0.489 bar, DME-driven SDWE achieves an optimal thermodynamic efficiency of 20.5 % and a projected specific cost of US$ 1.93 m -3 . These specific costs suggest that SDWE is competitive with commercialized thermal distillation technologies, while mitigating the traditional risks associated with scaling in heat and mass exchangers with hypersaline brines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics

Experimental soil heating experiments have found a consistent increase in soil-surface CO 2 emissions ( F s ), but inconsistent soil organic carbon (SOC) responses. Interpretation of heating effects is complicated by spatial heterogeneity and soil moisture, nitrogen availability, and microbial and plant responses. Here we applied a mechanistic ecosystem model to interpret heating impacts on a California forest subjected to 1 m deep, 4°C heating. The model accurately simulated control-plot CO 2 fluxes, SOC stocks, fine root biomass, soil moisture, and soil temperature, and the observed increases in F s and decreases in fine root biomass. We show that a complex suite of interactions can lead to a consistent increase in F s (~17%) over the 5-year study period, with very small changes in SOC stocks (<1%). Modeled increases in leaf water stress from soil drying reduced GPP and NPP. The resulting reduction in leaf and fine root allocation increased fine root litter inputs to the soil and reduced root exudation. Soil heating led to about a 50% larger increase in root autotrophic respiration than in heterotrophic respiration, with the heating effect on both these fluxes decreasing over the simulation period. Increased heterotrophic respiration led to increased soil N availability and plant N uptake. These heating responses are mechanistically linked, of magnitudes that can affect ecosystem dynamics, and long-term observations of them are rarely made. Therefore, we conclude that a coupled observational and mechanistic modeling framework is needed to interpret manipulation experiments, and to improve projections of climate change impacts on terrestrial ecosystem carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

The Tiny Heater: Creating Heat with Hybrid Nano-Antennas [LDRD HQ Highlights Article]

SRNL scientists demonstrate that an electromagnetic field, either as a light or magnetic field, is selectively coupled to shape-selective hybrid nano-antennas for efficient thermal processes. Localized heating occurs extremely fast, reducing the ‘wasted' thermal load on the environment. Being non-contact, efficient, and highly selective, the required input energy is greatly diminished. By strategically placing nano-antennas at desired locations, heat can be controlled at the nano-level. The location for nano-antennas, and the subsequent energy deposition, may be fine-tuned through specific chemical, steric, or magnetic interactions. The nano-antennas, composed of combinations of plasmonic, magnetic, and hydride components, are used for controlled release of hydrogen isotopes, chemotherapy drugs, environmental contaminants, enhanced catalytic processes, (bio)imaging and therapeutics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Thermo-Hydrological Modeling of Thermal Energy Storage in a Depleted Oil Reservoir

Thermal energy storage in oil and gas reservoirs leverages the existing surface and subsurface infrastructure, which can pave the way for economic production of geothermal energy. Existing studies on geothermal energy storage are focused mostly on the use of aquifers with more homogeneous rock and fluid properties. Coupling of heat and fluid flow in a multiphase-multicomponent system, such as an oil reservoir, is imperative especially if existing oil field assets need to be repurposed as required for a sustainable energy transition. The objective is to model the subsurface thermo-hydrological processes associated with reservoir performance and operational sustainability. The model evaluates formation pressure and temperature within the reservoir and at the injection/production wells during multiple charge and discharge cycles. Hot water (approximately 200 degrees C) heated by Concentrating Solar Power (CSP) at high pressure is injected into the existing oil reservoir for storage and produced as thermal energy for power generation, which will be accompanied by enhanced oil recovery. To demonstrate the coupled fluid and heat flow during the injection/production cycle in the subsurface reservoir, TOUGH3 (developed by Berkeley Lab) is used to simulate the thermo-hydrological (TH) processes in a multiphase, multicomponent system. Two well geometries are considered within the reservoir grid: 1) a single-well huff-n-puff system (same well is used for injection and production), and 2) an isolated injection-production well doublet. Seasonal charge and discharge cycling are implemented based on the scheduling specified in the model input file. The model reports pressure, temperature, enthalpy, liquid fluxes, heat fluxes, pore velocities, and changes in porosity & permeability due to temperature and pressure variations during the cyclic Reservoir Thermal Energy Storage (RTES) operations. The results from the simulations can be used to optimize the operational parameters (such as well spacing and injection/production rates) and round-trip efficiency for surface power-plants coupled with thermal energy storage over time. They can also serve as important inputs for levelized cost of storage estimations. The research will help to design and integrate surface renewable energy sources, such as concentrating solar power (CSP), with RTES to help balance out power supply and demand on the grid.

CSP↗

Sorbent Regeneration via Radiofrequency-Assisted Dielectric Heating for Direct Air Capture of CO 2

Direct air capture (DAC) of CO 2 is a negative emission technology that utilizes sorbents requiring a regeneration step for repeated ab(/d)sorption–desorption cycles. Here we report an unconventional approach to desorb captured CO 2 from a porous sorbent using radiofrequency (RF) irradiation for dielectric heating and targeted energy transfer, thus enabling modularity and promoting renewable energy input. Regeneration of composites of functional ionic liquid and metal–organic framework with high CO 2 capacity and enhanced transport is demonstrated under conditions relevant to DAC. RF-assisted dielectric heating at the megahertz frequency range shows effective absorption of electromagnetic energy and consequently rapid release of the captured CO 2 .

Ionic liquids↗

Corrigendum: Thermal dynamics in the flux-coordinate independent turbulence code GRILLIX

Here, we have discovered that one of the original articles findings, that the actual choice of the dimensionless parameter χ ∥i0 for the ion heat conductivity seemed to play no role for the simulation results, was not physical. Instead, due to a mistake in the handling of input parameters, χ ∥i0 was actually not used in the code – the dimensionless electron heat conductivity χ ∥e0 was used instead.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Analyzing the Impact of Future Weather Data on Energy Consumption in Weatherization Assistant

This study supports the mission of the U.S. Department of Energy’s Weatherization Assistance Program (WAP), which aims to increase the energy efficiency of dwellings and reduce their total residential expenditures. Specifically, we examine how projected future climate conditions may affect residential building energy performance by integrating future weather data into the National Energy Audit Tool (NEAT). Since WAP evaluates the cost-effectiveness of retrofit measures over lifespans of up to 30 years, accounting for evolving climate conditions is increasingly important. To reflect future household energy demands, this study replaces historically based Typical Meteorological Year (TMY3) weather inputs with Future Typical Meteorological Year (fTMY) datasets derived from global climate model (GCM) projections. A simulation-based framework was established to enable NEAT analysis under future weather conditions. This workflow involves converting EPW-format weather files into JSON inputs compatible with NEAT and generating degree-hour metrics needed for load calculations. The fTMY dataset used in this study was developed by Oak Ridge National Laboratory through downscaling of six GCMs under different emission scenarios and covers the period from 2020 to 2100. In contrast, the TMY3 dataset is based on historical weather data from 1961 to 1990. Simulations were conducted for benchmark single-family prototype buildings across ASHRAE climate zones 1–7, which cover all regions of the U.S. except the subarctic Zone 8 in northern Alaska, evaluating both heating and cooling loads under TMY3 and fTMY conditions. Four foundation types were tested, while heating systems were standardized, as NEAT does not differentiate thermal energy load by HVAC system type in its load calculations. Results show that fTMY weather input consistently yield lower heating loads and higher cooling loads across most locations, aligning with expected climate warming trends. Notably, colder regions such as zones 6A, 6B, and 7 experience marked reductions in heating load, while warmer and transitional zones, such as 2A (Lufkin, TX) and 3C (San Francisco, CA), have substantial increases in cooling loads. Although this study does not directly assess the performance of retrofit measures under future climate conditions, it provides a critical foundation for doing so. By quantifying shifts in baseline (i.e., pre-retrofit case) energy loads between historical and future weather files, the study highlights the importance of integrating climate-responsive data into audit tools. These findings will inform future efforts to evaluate the long-term effectiveness and cost-effectiveness of weatherization measures under changing climate conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A proposed methodology to reduce heat pump size with integrated thermal energy storage

Thermal energy storage (TES) offers a unique storage solution wherein heat is stored for later use to thermally condition an application. Heat pumps (HPs) move heat from relatively cold to a relatively hot with an input of work. Integrating TES into a HP system adds a third temperature body, and the HP can be selectively coupled to operate between any two: a constant temperature application, a temporally fluctuating ambient temperature, or a constant temperature TES. Since the HP-TES system enables operation under different conditions depending on the pair of temperature bodies, changes in efficiency and capacity can be expected. Thus, TES can shift HP operation to more favorable conditions to deliver heat to the application. Consequently, TES increases the apparent capacity of the HP which might enable a nominally smaller HP to be used effectively. This paper outlines a method by which TES can reduce the size of a HP without sacrificing heat delivered to the application. The method is demonstrated for a building cooling application which realized a reduction in nominal HP size from 3 tons to 2.4 tons.

Hirschey, Jason↗

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

The daily as-run thermal analysis for the Advanced Gas Reactor (AGR)-5/6/7 experiment was documented in ECAR-5633 (Hawkes 2021). A finite element model was created for the entire test train, which consisted of five capsules. The fuel compacts, graphite holders, stainless-steel capsule walls, and all other major components were individually modeled, including all thermocouples (TCs). Daily heat rates for each compact and component in the model were input from daily as-run physics analyses. Daily gas compositions for each capsule were also input. The thermal conductivity of the compacts and graphite holders varied with fast neutron fluence. Gas mixture thermal conductivity was implemented using experimentally attained values from the literature. Fluence and temperature-dependent thermal conductivity was used for the graphite components and the fuel compacts. Radiation heat transfer was implemented. The model was tuned in an attempt to match the TC readings during the first cycle by adjusting the Neolube (graphite lubricant) thickness.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantitative Analysis and Prediction of Thermal Runaway Metrics of High-Nickel Oxide Cathodes by Machine Learning Models

The pursuit of higher energy density in lithium-ion batteries has made high-nickel (Ni) layered oxides leading cathode candidates for next-generation electric vehicles. However, their poor thermal stability, particularly at Ni contents ≥ 90%, increases the risk of cathode-initiated thermal runaway. Furthermore, we present a data-driven framework combining linear and nonlinear machine learning models to predict key thermal runaway descriptors from a high-throughput differential scanning calorimetry database. With cathode composition and state of charge (SOC) as input features, the ensemble model accurately predicts peak temperature, heat release, and peak heat flow. SHAP analysis identifies Ni content and SOC as the dominant factors controlling thermal runaway temperature, while SOC primarily governs heat release and peak heat flow. Al, Mg, and Mn improve thermal stability by strengthening metal–oxygen bonding and delaying structural transformation, whereas B mainly reduces heat release through surface passivation. Validation with a new cathode composition confirms accurate prediction of SOC-dependent thermal runaway behavior and critical SOC.

25 ENERGY STORAGE↗

SAS4A/SASSYS-1 Modeling Improvements for the Transition to Natural Circulation

SAS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over fifty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. In recent years, SAS has undergone a number of improvements to enable improved safety analyses that meet end users’ modernized needs while complying with the current regulatory environment. Improvements made in versions 5.6 and 5.7 released within the last year include the development of anisotropic Reynolds number dependent loss coefficients throughout the core and heat transport systems, the ability to distinguish the transition friction factor from the fully developed laminar and turbulent friction factors, and timedependent direct coolant and wall heating for pipe-like elements in the heat transport systems. While it was possible to capture loss coefficients, friction factors, and heat transfer from an element to a heat sink within SAS in previous versions of the code, users were required to end the simulation and restart it to adjust the input to account for any significant changes to the values during the transient. With these improvements, users can better capture flow reversal, pump heating, and the transition from forced to natural circulation without being limited to constant orifice coefficients, constant heat sinks, or the need to restart the simulation and modify input. In order to demonstrate the application of these improvements, a loss of flow transient is simulated for the Advanced Burner Test Reactor (ABTR).

SAS4A/SASSYS-1↗

Quantitative trait locus (QTL) mapping and transcriptome profiling identify QTLs and candidate genes associated with heat stress response during reproductive development in Camelina sativa

Camelina sativa (L.) Crantz is a low-input oilseed crop that has great potential in providing sustainable feedstock for biofuels and bioproducts. Climate change is threatening production of camelina with rising global temperatures. Elucidating the genetic response to high temperatures is essential for successful breeding of heat-tolerant camelina varieties. Here, we report a combinatorial approach to identifying candidate genes associated with heat stress by quantitative trait locus (QTL) mapping and comparative transcriptome profiling. A population of recombinant inbred lines (RILs) was grown in a controlled growth chamber under the high-temperature regimes for 14 days beginning at the onset of the reproductive stage. Several traits related to seed production were evaluated at maturity. The QTL analysis identified several regions with co-located traits on chromosomes 8, 10, and 12. Two RILs with contrasting phenotypic responses to heat stress were chosen for gene expression profiling via RNA sequencing. Multiple pathways and genes were found to be strongly affected by heat stress, and many genes expressed differently between the two RILs. Several genes identified within the QTL regions were considered strong candidates that may control heat tolerance during reproduction in camelina. These studies provide resources for future studies that may assist in improving the heat tolerance of camelina.

60 APPLIED LIFE SCIENCES↗

Pathways towards break even for low convergence ratio direct-drive inertial confinement fusion

Following indirect-drive experiments which demonstrated promising performance for low convergence ratios (below 17), previous direct-drive simulations identified a fusion-relevant regime which is expected to be robust to hydrodynamic instability growth. This paper expands these results with simulated implosions at lower energies of 100 and 270 kJ, and ‘hydrodynamic equivalent’ capsules which demonstrate comparable convergence ratio, implosion velocity and in-flight aspect ratio without the need for cryogenic cooling, which would allow the assumptions of one-dimensional-like performance to be tested on current facilities. A range of techniques to improve performance within this regime are then investigated, including the use of two-colour and deep ultraviolet laser pulses. Finally, further simulations demonstrate that the deposition of electron energy into the hotspot of a low convergence ratio implosion through auxiliary heating also leads to significant increases in yield. Results include break even for 1.1 MJ of total energy input (including an estimated 370 kJ of short-pulse laser energy to produce electron beams for the auxiliary heating), but are found to be highly dependent upon the efficiency with which electron beams can be created and transported to the hotspot to drive the heating mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

RELAP5-3D Simulation of PG-27 Test at the HTTF Facility

The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a quarter scaled integral-effect test facility designed to examine the transient phenomena occurring in a Modular Hight Temperature Gas-cooled Reactor (MHTGR). It is specifically designed to handle the pressurized and depressurized conduction cooldown (PCC and DCC) events. The PCC event is an accident scenario in which there is a loss of forced convection of the coolant through the system. However, the pressure boundary remains intact. This study focuses on the Reactor Excursions and Leak Analysis Program (RELAP)5-3D simulation of the PG-27 test (PCC phenomena) and the sensitivity of those simulations from the material properties and primary helium mass flow rate standpoint. The aim is to capture a reasonable one-dimensional picture of a three dimensional phenomena. The simulation will help in the code assessment and in understanding the various unknown parameters involved. The presented results will demonstrate the code is able to capture the detailed one-dimensional physics accurately. However, input parameters to the code (i.e., the primary mass flow rate, refractory material thermal conductivity, and heat capacity at elevated temperatures) impact the fuel temperature the most. This work will discuss the sensitivity of simulations to the identified input parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Thermal and structural analysis of a new WEST reciprocating probe head with Titanium-Zirconium-Molybdenum armour material

The Tore Supra tokamak was transformed into an X-point divertor fusion device in the frame of the WEST (W-for tungsten-Environment in Steady-state Tokamak) project, launched in support of the ITER tungsten divertor strategy. WEST began operation in 2017. A new reciprocating probe head, equipped with a Titanium-Zirconium-Molybdenum (TZM) heat shield, was recently built and operated on WEST during the C9 Campaign in early 2024. TZM was chosen as armour material for its very good mechanical properties between 700 °C and 1400 °C. This material was already extensively used for probe heads and other plasma facing components on the Alcator C-Mod tokamak. Here, this paper presents the design of the new WEST probe head. It is equipped with tungsten filaments that can be heated to emit electrons and provide a direct measurement of the plasma potential in the scrape-off layer, and it is also equipped with a pair of Langmuir probes. The probe plunges vertically into the plasma, reaches its maximum dive depth, then returns to its protected resting position in about 0.25 s. Thermal loads are calculated using as input the thermal properties of TZM and radial profiles of the heat flux measured in the past by other reciprocating probes, and scaled upwards to the expected heat loads in the WEST scrape-off layer. An analytical estimation of Electromagnetic (EM) loads will also be presented, as well as a thermal and structural analysis of the probe for 15 cycles at maximum plunge depth. The probe is observed by an infrared camera. Comparisons between the heat flux deduced by the Langmuir probe and the infrared radiance of the probe housing during plasma exposure are finally presented.

Diagnostic↗

Strain age cracking in a simulated heat affected zone of Inconel 740H laser-powder bed fusion components

Inconel® 740H components produced via laser-powder-bed fusion (L-PBF) additive manufacturing are ideal for supercritical CO2 primary heat exchangers. Arc welding is often needed, and subsequent post-weld heat treatment aging at 790–840 °C is required to improve strength via gamma prime (γ’) precipitation; however, strain age cracking (SAC) can occur in the heat affected zone (HAZ) during this process. This study uses stress relaxation testing at 800 °C on simulated HAZ specimens from vertically and horizontally built L-PBF IN740H to assess SAC susceptibility across heating rates of 40–3480 °C/h and weld-induced strains of 3–10 %. Vertical builds require greater mechanical energy input and exhibit longer times to fracture than horizontal builds, and time to fracture occurs sooner at slower heating rates. Creep voids were observed in γ’-denuded regions along grain boundaries, and cracking propagated along migrated grain boundaries and at interfaces between elongated secondary phases (γ’ or carbides) and the γ-matrix.

14 SOLAR ENERGY↗