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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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Heat metrics and thresholds reshape population exposure and inequality signals
Extreme heat is intensifying worldwide, yet estimates of heat hazard and exposure inequality depend on both the heat metric and how extreme days are defined. Using summer 2022 across the Mediterranean, we quantify population heat exposure with four metrics—land surface temperature (LST), air temperature (Ta), heat index (HI), and wet-bulb globe temperature (WBGT)—under absolute (fixed-value) and relative (anomaly-based) thresholds. Under absolute thresholds, total heat exposure differs by more than two orders of magnitude across metrics (31.3 billion person-days for Ta vs 0.3 billion for HI). Geographic hotspots also diverge: WBGT concentrates in humid coastal North Africa (e.g. the Nile Delta), whereas Ta and LST are more widespread. Under relative thresholds, exposure totals converge and cross-metric hotspot agreement increases (e.g. Ta–WBGT top-tercile overlap increases from 10.7% to 29.0%), shifting hotspots toward densely populated southern Europe. Crucially, the exposure–deprivation relationship also reverses across threshold frameworks: absolute thresholds concentrate exposure in more deprived North Africa and the Middle East, whereas relative thresholds shift the burden toward less-deprived European cities. This sensitivity is decision-relevant: city rankings based on WBGT exposure duration are almost completely reordered when switching threshold frameworks. Threshold choice therefore systematically reshapes hotspot patterns and inequality signals. Reporting both absolute and relative exposures can reveal hidden hotspots and support more targeted heat-risk monitoring and intervention planning.
Numerical simulation of frost formation and heat transfer on fin-and-tube heat exchangers in turbulent cross-flow
Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050 ≤ R e D , avg ≤ 4800 , with the characteristic length being the outer diameter of the tube and the velocity being the bulk fluid velocity between the plates (fins). Computational fluid dynamics simulations are employed to resolve the interactions between turbulent airflow and the frost layer. Our approach incorporates a modified immersed boundary method and a slow-time acceleration technique to address the complex dynamic interface between the continuously evolving frost layer and the flowing air stream. Our findings indicate that frost forms more on the sides of the finned surfaces (plates) and less on the tubes themselves. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.
NIOBIUM-1% ZIRCONIUM, NATURAL-CIRCULATION, BOILING-POTASSIUM CORROSION LOOP TEST
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Computational modeling of coupled mechanical damage and electrochemistry in ternary oxide composite electrodes
Performance degradation of ternary layered oxide cathodes largely originates from their loss of structural integrity in cyclic usage. Mechanical damage, such as intergranular fracture of the active particles, is not only a mechanical cleavage process but also interferes with electrochemical kinetics such as infiltration of liquid electrolyte, surface corrosion of the constituent primary particles, and may eventually isolate the primary grains from the electron conducting network. Here, in this work, we develop a computational framework that integrates electrochemistry of a LiNi x Mn y Co 1−x−y O 2 (NMC) composite cathode with mechanical damage of the active particles. To fully examine the intricate chemomechanical behavior of the electrode, we evaluate the effects of the anisotropic material properties, the influence of mechanical potential on Li transport, and the concurrent intergranular fracture and electrolyte penetration along the grain boundaries upon multiple cycles. Electrolyte infiltration benefits capacity retention but aggravates further mechanical damage by corrosion. Structural failure mostly occurs in the first charging due to the anisotropic mechanical strain between the primary grains, while the resulting damage remains stable in the later few cycles. The results are consistent with experimental observations and the integration of electrochemistry and mechanical failure enables a step further understanding of the complex mechanism of battery degradation.
Advanced Model Development for Large Eddy Simulation of Oxy-Combustion and Supercritical Carbon Dioxide Power Cycles
A joint experimental and numerical study is performed to observe the characteristics of a supercritical carbon dioxide turbulent mixing layer in the presence of strong nonlinearities in the thermodynamic and transport properties. A bespoke experimental setup is designed and employed for this purpose and provides insight into macroscopic mixing behavior. The mixing is experimentally observed using two techniques: shadowgraphy and spontaneous Raman scattering. Qualitative and quantitative intensity fields obtained via these techniques yield instantaneous and mean density data. Spanwise temperature data is also collected using analogue resistance temperature detectors. These measurements are used to quantify the level of mixed material within the field. The experimental data are supplemented by a companion high-fidelity numerical study. The numerical results are obtained through fully resolved, three-dimensional direct numerical simulation. The numerical dataset permits observation of the near-field mixing characteristics, which are difficult to measure experimentally due to the rapid dynamics and sharp thermophysical gradients in this area. Qualitative field visualizations are presented, followed by quantitative mixed material results and observations regarding thermodynamic property trends at select locations within the field. One-dimensional spectra of the turbulent kinetic energy and solenoidal dissipation are provided to observe the spectral characteristics of the flow. Reynolds stress anisotropy is analyzed graphically through anisotropy invariance maps (Lumley triangles). The mixing quantification, spectral data and anisotropy analysis of a flow at these thermodynamic conditions represent the main outcomes of the work.
Efficient Leaching of Metal Ions from Spent Li-Ion Battery Combined Electrode Coatings Using Hydroxy Acid Mixtures and Regeneration of Lithium Nickel Manganese Cobalt Oxide
Extensive use of Li-ion batteries in electric vehicles, electronics, and other energy storage applications has resulted in a need to recycle valuable metals Li, Mn, Ni, and Co in these devices. In this work, an aqueous mixture of glycolic and lactic acid is shown as an excellent leaching agent to recover these critical metals from spent Li-ion laptop batteries combined with cathode and anode coatings without adding hydrogen peroxide or other reducing agents. An aqueous acid mixture of 0.15 M in glycolic and 0.35 M in lactic acid showed the highest leaching efficiencies of 100, 100, 100, and 89% for Li, Ni, Mn, and Co, respectively, in an experiment at 120 °C for 6 h. Subsequently, the chelate solution was evaporated to give a mixed metal-hydroxy acid chelate gel. Pyrolysis of the dried chelate gel at 800 °C for 15 h could be used to burn off hydroxy acids, regenerating lithium nickel manganese cobalt oxide, and the novel method presented to avoid the precipitation of metals as hydroxide or carbonates. The Li, Ni, Mn, and Co ratio of regenerated lithium nickel manganese cobalt oxide is comparable to this metal ratio in pyrolyzed electrode coating and showed similar powder X-ray diffractograms, suggesting the suitability of α-hydroxy carboxylic acid mixtures as leaching agents and ligands in regeneration of mixed metal oxide via pyrolysis of the dried chelate gel.
ResStock Measure Documentation: Residential Two-Stage Geothermal Heat Pump (4.0 COP, 20.5 EER) With Light Envelope Improvements
This report is part of series describing a variety of different ResStock(TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Residential Two-Stage Geothermal Heat Pump (4.0 COP, 20.5 EER) With Light Envelope Improvements" measure upgrade methodology and briefly discusses key results. All results can be accessed on the ResStock Open Energy Data Initiative "End-Use Load Profiles for the U.S. Building Stock" data lake and on the data viewer at resstock.nlr.gov.
ResStock Measure Documentation: Residential Variable-Speed Geothermal Heat Pump (4.4 COP, 30.9 EER) With Light Envelope Improvements
This report is part of series describing a variety of different ResStock™ measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Residential Variable-Speed Geothermal Heat Pump (4.4 COP, 30.9 EER) with Light Envelope Improvements" measure upgrade methodology and briefly discusses key results. All results can be accessed on the ResStock Open Energy Data Initiative "End-Use Load Profiles for the U.S. Building Stock" data lake and on the data viewer at resstock.nlr.gov.
Developing affordable and efficient heating devices for enhanced live cell imaging in confocal microscopy
Temperature control is crucial for live cell imaging, particularly in studies involving plant responses to high ambient temperatures and thermal stress. This study presents the design, development, and testing of two cost-effective heating devices tailored for confocal microscopy applications: an aluminum heat plate and a wireless mini-heater. The aluminum heat plate, engineered to integrate seamlessly with the standard 160 mm × 110 mm microscope stage, supports temperatures up to 36°C, suitable for studies in the range of non-stressful warm temperatures (e.g., 25-27°C forArabidopsis thaliana) and moderate heat stress (e.g., 30-36°C forA. thaliana). We also developed a wireless mini-heater that offers rapid, precise heating directly at the sample slide, with a temperature increase rate over 30 times faster than the heat plate. The wireless heater effectively maintained target temperatures up to 50°C, ideal for investigating severe heat stress and heat shock responses in plants. Both devices performed well in controlled studies, including the real-time analysis of heat shock protein accumulation and stress granule formation inA. thaliana. Our designs are effective and affordable, with total construction costs lower than $300. This accessibility makes them particularly valuable for small laboratories with limited funding. Future improvements could include enhanced heat uniformity, humidity control to mitigate evaporation, and more robust thermal management to minimize focus drift during extended imaging sessions. These modifications would further solidify the utility of our heating devices in live cell imaging, offering researchers reliable, budget-friendly tools for exploring plant thermal biology.
Preliminary Assessment for the Electric Load Shifting Potential of Integrating Thermal Energy Storage with Heat Pumps in Residential Buildings in Texas of United States
The widespread adoption of electric-driven heat pumps for heating and cooling is expected to significantly increase electric demand. Cooling electric demand will result in an increase in peak hours electric loads, placing additional strain on the grid during peak hours. This challenge, combined with the current rapidly increasing demand from data centers, exacerbates the electric demand duck curve problem. Integrating thermal energy storage (TES) with heat pump can shift electric use for heating and cooling from peak to off-peak hours of the electric grid, which can help flatten the daily electric demand profile of a building. This paper presents a novel design that integrates heat pump with TES (HP-TES), which uses phase change materials (PCM). Heat pump charges TES by melting or freezing PCM during off-peak hours when there is no thermal demand from the building. TES is then discharged (i.e., by freezing or melting PCM) during peak hours to provide a more favorable heat source or heat sink for the heat pump to meet the thermal demand of the building with lower electricity use than conventional air-source heat pumps. Computer simulations were developed to predict the performance of HP-TES applied to a typical single-family house in the US. The building-level simulation results were scaled up to preliminarily assess the aggregated impacts of deploying HP-TES across all single-family houses in Texas of the United States, including reduction of peak demand of the electric grid.
Conserved Macromolecular Architecture of Poplar Secondary Cell Walls Revealed by ssNMR and Atomistic Modeling
The macromolecular architecture of plant secondary cell walls governs wood's mechanical and biochemical properties, yet its natural intra-species variability remains poorly characterized. Here, we combined 13C solid-state NMR (ssNMR), multivariate statistical analysis, and molecular modeling to profile nanoscale structure across 13 genetically diverse Populus trichocarpa genotypes grown in 13C-enriched atmospheres. SsNMR-derived phenotypes spanning composition, structure, mobility, and inter-polymer proximities reveal a conserved architecture, with a subtle yet coordinated variation organizing into dominant structural and secondary mobility axes. A representative atomistic model captures these features and reproduces experimental metrics. Molecular dynamics simulations support a weak but consistent positive correlation between cellulose abundance and crystalline-like order, with interior cellulose chains enriched in tg (trans-gauche) conformations without expanding crystalline cores. Together, experiment and simulation reveal a genetically buffered, broadly conserved nanoscale architecture across genotypes, where subtle fine-tuning of cellulose bundling and matrix packing balances mechanical performance with biological function.
Selective depolymerization of polyolefin copolymer via high-entropy alloy catalyzed pyrolysis in a double-layered ultrafast heating reactor
Chemical recycling of polyolefin copolymers (PCPs) is essential for mitigating plastic pollution, yet achieving selective depolymerization into C 2 –C 3 monomers at high productivity remains challenging. Here, we introduce a double-layered ultrafast heating reactor (DUHR) that integrates Joule heating with a high-entropy alloy (HEA) catalyst composed of near-equimolar Co, Cu, Fe, Mn, and Ni. We achieve highly selective depolymerization of PCP into ethylene and propylene, yielding a 70% non-condensable fraction. Significant aromatic fractions form via radical-driven pathways—a behavior distinct from conventional externally heated pyrolyzers—highlighting DUHR's ability to generate reactive species and modulate reaction pathways. Furthermore, these findings demonstrate an effective strategy for chemical recycling of real-world plastic waste for polyolefin circularity and sustainable resource recovery.
A Probabilistic Approach to Load Modeling for Central HVAC Systems in Large Commercial Buildings for Retrofit Decisions Under Uncertainty
Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated through strong predictive performance on unseen data and physically interpretable insights into load behavior. This data-driven, probabilistic load profile serves as a robust and flexible input for subsequent system simulations, enabling a more confident and statistically sound analysis of retrofit potential.
Implementing Induction-Heated Time-at-Temperature Testing Workflows for Irradiated Materials
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Fast-running Model of Thermal Runaway Propagation with Heat and Mass Transfer Within an Enclosure
This material will be presented at the Interagency Advanced Power Group (IAPG) Chemical Working Group and Safety Panel Meeting. IAPG serves as the premier organization coordinating the collaboration and information exchange of advanced power research and development within the U.S. government.
First Principles Study of Aluminum Doped Polycrystalline Silicon as a Potential Anode Candidate in Li‐ion Batteries
Addressing sustainable energy storage remains crucial for transitioning to renewable sources. While Li‐ion batteries have made significant contributions, enhancing their capacity through alternative materials remains a key challenge. Micro‐sized silicon is a promising anode material due to its tenfold higher theoretical capacity compared to conventional graphite. However, its substantial volumetric expansion during cycling impedes practical application due to mechanical failure and rapid capacity fading. A novel approach is proposed to mitigate this issue by incorporating trace amounts of aluminum into the micro‐sized silicon electrode using ball milling. Density functional theory (DFT) is employed to establish a theoretical framework elucidating how grain boundary sliding, a key mechanism involved in preventing mechanical failure is facilitated by the presence of trace aluminum at grain boundaries. This, in turn, reduces stress accumulation within the material, reducing the likelihood of failure. To validate the theoretical predictions, capacity retention experiments are conducted on undoped and Al‐doped micro‐sized silicon samples. In conclusion, the results demonstrate significantly reduced capacity fading in the doped sample, corroborating the theoretical framework and showcasing the potential of aluminum doping for improved Li‐ion battery performance.
Tensorized Interior Radiative Heat Transfer for a Scalable and Calibrated Building Energy Simulator
Building energy simulation is a critical tool for developing and testing advanced control strategies, such as Reinforcement Learning (RL), to provide demand flexibility and affordable energy costs. The recently introduced Smart Buildings Control Suite (sbsim) provides a lightweight, scalable, and data-calibrated simulation environment based on a 2D finite-difference model. However, the initial model primarily focused on conductive and convective heat transfer, neglecting the significant impact of long-wave radiative heat exchange between interior surfaces. This paper presents a significant extension to the sbsim framework by incorporating a physically-grounded model for interior radiative heat transfer. Our primary contribution is the development and integration of a fully tensorized radiative heat transfer module, which preserves the computational efficiency and scalability of the original simulator. This was achieved by developing a pipeline for view factor calculation, including an algorithm to identify directly seeing surfaces within complex floor plans, and formulating the net radiation equations for efficient execution on modern hardware accelerators. We validate the numerical accuracy of our tensorized implementation by comparing its results against a traditional iterative approach, demonstrating identical outcomes. This enhancement increases the physical fidelity of sbsim, enabling more accurate training of RL agents for building energy optimization.