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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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A biomarker panel of 12 genes based on expression levels. Methods for calculating prognostic scores and patient ranking based on their score and divided into two equal sized cohorts. Kaplan-Meier analysis and a log-rank test were used to determine differences in survival.
The present work reports on the development of techniques for in-field fast-neutron radiography measurements using the associated-particle imaging (API) method. The API method employs alpha-neutron coincidences from the d+t→α+n reaction to enable fast neutron transmission imaging with excellent contrast using a wide cone beam. However, for field radiography applications, the API method is burdened by the need for the relative positions of the source and detector to be known. Fortunately, these relative positions can be inferred from transmission data. The inferred positions also enable accurate stitching of multiple images into a composite image even when using a low-resolution detector panel and acquiring images having few overlapping pixels. The developed techniques address analysis of measurements where (1) the source and detector panel are separately hand positioned rather than held in registration by a gantry, (2) multiple detector panel positions within the “coincident cone” of tagged neutrons are required to piece together an image of an item of interest, and (3) normalization measurements that have identical source-detector positioning but without the inspected object are not possible. The present work will describe the system calibrations (including timing calibrations and neutron direction calibrations) necessary for subsequent analyses, the method of locating the detector in the coincident cone of neutrons with millimeter precision using the timing and directions of coincident neutrons, the method of calculating a normalization image for a given detector panel position, and the method used to project multiple images into a common image.
A system for controlling a rotation of one or more solar panels about an axis of rotation, comprising one or more solar panels defining a longitudinal axis, one or more bellows actuators coupled to the one or more solar panels and defining an axis of rotation parallel to the longitudinal axis of the panels, a fluid source, a first valve circuit coupled to the bellows actuators and the fluid source, a second valve circuit coupled to the bellows actuators and the fluid source, and a controller, wherein introduction or release of fluid from one or more of the bellows actuators is configured to cause rotation of the one or more actuators about the axis of rotation.
Abstract Photovoltaic (PV) modules are a key technology to aid the imminent transition from carbon‐based energy. End‐of‐life crystalline silicon PV modules produce a waste stream that is predominantly landfilled due to the recycling challenges associated with PV reuse economics. Current practices recycle the aluminum frame and repurpose the junction box but landfill the rest of the module. The primary challenge in recycling the remaining module is finding a technoeconomically viable method for separating the silicon and glass from the ethylene vinyl acetate (EVA) layers. This issue will rapidly expand with time as it is estimated that flat glass production for solar panels is currently unable to meet the demand for PV. Current literature suggests that chemical, thermal, and mechanical delamination offer economically feasible solutions under ideal circumstances. In this work we evaluate these methods using end‐of‐life panels and assess the economic viability. The technoeconomic study presented here suggests the most economically viable option for disposing of end‐of‐life solar panels, given current technology, is landfilling. Thermal delamination may offer an alternative route in the future. Financial incentives, which can be quantified with this work, may be required to kickstart PV recycling to help bridge externalities around environmental impact.
The structures that surround and support optical components play a key role in the performance of the overall optical system. For aerospace applications, creating an opto-mechanical structure that is athermal, lightweight, robust, and can be quickly developed from concept through to hardware is challenging. This project demonstrates a design and fabrication method for optical structures using origami-style folded, photo-etched sheetmetal pieces that are micro-welded to each other or to 3d printed metal components. Thin flexures, critical for athermal mounting of optics, can be thinner with sheetmetal than from standard machining, which leads to more compact designs and the ability to mount smaller optics. Building a structure by starting with the thinnest features, then folding that thin material to make the ''thicker'' sections is the opposite of standard machining (cutting thin features from thicker blocks). A design method is shown with mass savings of >90%, and stiffness to weight ratio improvements of 5x to 10x compared to standard methods for space systems hardware. Designs and processes for small, flexured, actively aligned systems are demonstrated as are methods for producing lightweight, structural, Miura-core sandwich panels in both flat and curved configurations. Concepts for deployable panels and component hinges are explored, as is a lens subcell with tunable piston movement with temperature change and an ultralight sunshade.
We report groundwater is a relevant source of drinking and agricultural water in many regions of the world, but many aquifers have been unsustainably over-drafted and polluted. This has significant environmental, health, and economic implications. We rely on panel analysis, with small-sample corrections for cluster-robust variance estimation and hypothesis testing, to investigate the dynamics of groundwater extraction. We focus on California, yet our approach could be helpful to analyze the dynamics of groundwater extraction in other groundwater-reliant regions of the world. In California, over-reliance on groundwater has led to significant overdraft, affecting long-term water supply reliability and groundwater pumping costs. It further caused subsidence and infrastructure damage, harmed groundwater-dependent ecosystems, and threatened the sustainability of groundwater resources in the state. We use panel data of the 56 California Water Plan planning areas over the 1998–2015 period. We concentrate on agricultural and urban water use and the major water projects in the state, to provide a better understanding of the relationships between groundwater extraction and water use and supply. Results suggest that reducing agricultural water in Central California and urban water in Southern California could reduce groundwater extraction in these regions by approximately the same amount of the reduced water. Other opportunities to reduce the stress on the groundwater resources in the state are available for other regions, yet with lower benefits. Results also suggest that a decrease in deliveries from the Central Valley Project to the southern part of the Central Valley would increase groundwater extraction by approximately the same proportion. Changes in deliveries from the major water projects in the state, as well as from other sources of surface water, would also have some, yet lower impacts on groundwater extraction in the Central and Southern California.
Gain insight from an exploration of the potential value of demand response (DR) in future power systems. Using hourly DR resource estimates by sub-sector, electrical end-use, and grid service, we incorporate virtual generator models of DR resources into large-scale production cost models, and analyze the grid-level impacts in terms of the ability of DR to reduce system costs and potentially help integrate renewables or reduce system emissions. Additionally, we examine the value of DR, its revenue, and how these change under different system conditions. In this panel session, we will describe our input data and modeling methods, provide an overview of the production cost models used, and summarize key results from analyses in Florida and the western United States. Findings include variations in DR value by end-use and geography, an ability to increase economic PV deployment potential in high penetration systems, and mixed emissions outcomes depending on system composition and fuel prices.
Domestic biomass crops such as sorghum, switchgrass, Miscanthus, and poplar can provide United States industries with renewable feedstocks while also supporting low-input farming systems and strengthening supply chains for biofuels, biochemicals and biomaterials. The U.S. leads globally in biomass crop genomics, yet progress in engineering traits is constrained by slow, genotype-dependent transformation methods and lengthy Design-Build-Test-Learn (DBTL) cycles. At a May 2025 workshop, a panel of experts recommended establishing a DOE Plant Transformation Capability (PTC) to overcome these barriers. The PTC would unite two missions: advancing research to achieve genotype-independent, automated methods, and delivering scalable transformation services through a user-facility model. With expected gains of 10–100x in efficiency, including transformation and cost reduction, the PTC would accelerate the path from discovery to engineered plants, expand community access and training, and support downstream applications and workflows including field trials and regulatory navigation. By enabling rapid and predictable crop engineering, the PTC would strengthen U.S. supply chains, enhance industrial competitiveness, and ensure that DOE’s genomic investments deliver national impact.
Abstract Genetic monitoring of Pacific salmon in the Columbia River basin provides crucial information to fisheries managers that is otherwise challenging to obtain using traditional methods. Monitoring programs such as genetic stock identification (GSI) and parentage‐based tagging (PBT) involve genotyping tens of thousands of individuals annually. Although rare, these large sample collections inevitably include misidentified species, which exhibit low genotyping success on species‐specific Genotyping‐in‐Thousands by sequencing (GT‐seq) panels. For laboratories involved in large‐scale genotyping efforts, diagnosing non‐target species and reassigning them to the appropriate monitoring program can be costly and time‐consuming. To address this problem, we identified 19 primer pairs that exhibit consistent cross‐species amplification among salmonids and contain 51 species informative variants. These genetic markers reliably discriminate among 11 salmonid species and two subspecies of Cutthroat Trout and have been included in species‐specific GT‐seq panels for Chinook Salmon, Coho Salmon, Sockeye Salmon, and Rainbow Trout commonly used for Pacific salmon genetic monitoring. The majority of species‐informative amplicons (16) were newly identified from the four existing GT‐seq panels, thus demonstrating a low‐cost approach to species identification when using targeted sequencing methods. A species‐calling script was developed that is tailored for routine GT‐seq genotyping pipelines and automates the identification of non‐target species. Following extensive testing with empirical and simulated data, we demonstrated that the genetic markers and accompanying script accurately identified species and are robust to missing genotypic data and low‐frequency, shared polymorphisms among species. Finally, we used these tools to identify Coho Salmon incidentally caught in the Columbia River Chinook Salmon sport fishery and used PBT to determine their hatchery of origin. These molecular and computing resources provide a valuable tool for Pacific salmon conservation in the Columbia River basin and demonstrate a cost‐effective approach to species identification for genetic monitoring programs.
Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.
This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.
Measuring air infiltration through the external building envelope as well as between adjacent zones within a building is important since air leakage is related to increased energy use and poor indoor air quality (IAQ). State of the art methods can determine both leakages, however it can be both time consuming and labor intensive as it requires running both guarded and compartmentalization tests. This paper presents our work on developing a simplified testing procedure to determine power law flow equation leakage parameters of both external and internal boundaries of tested zones. The proposed Zonal Multipoint Pressure Test (ZMPT) method modulates airflow in the zone using a variable airflow measurement panel (mounted in either a window or the door), and solving the mass balance equations for the leakage parameters. ZMPT results were compared to conventional test results and found to correlate to within +/-7%.
Panels of 8-, 9- and 12-biomarker for diagnostic and prognostic methods to determine a subject's radiation exposure and discriminates between persons who have been exposed to radiation only, inflammation stress only, or a combination of the two.
The increasing frequency of extreme weather events poses significant risks to power distribution systems, leading to widespread outages and severe economic and social consequences. This paper presents a novel simulation framework for assessing and enhancing the resilience of power distribution networks under such conditions. Resilience is estimated through Monte Carlo simulations, which simulate extreme weather scenarios and evaluate the impact on infrastructure fragility. Due to the proprietary nature of power network topology, a distribution network is synthesized using publicly available data. To generate the weather scenarios, an extreme weather generation method is developed. To enhance resilience, renewable resources such as solar panels and energy storage systems (batteries in this study) are incorporated. A customized Genetic Algorithm is proposed to determine the optimal locations and capacities for solar panels and battery installations, maximizing resilience while balancing cost constraints. Experiment results demonstrate that on a large-scale synthetic distribution network with more than 300,000 nodes and 300,000 edges, the proposed framework can efficiently evaluate the resilience, and enhance the resilience through the installations of distributed energy resources (DERs), providing utilities with valuable insights for community-level power system resilience estimation and enhancement.
Diversitak, a company based in Detroit, MI, has developed a proprietary, low specific gravity, carbon fiber-reinforced epoxy (CFRE) under U.S. patent number 9,963,58832. Preliminary testing on this new material conducted in collaboration with ArcelorMittal Steel Company proved out the CFRE concept. A thin layer of this CFRE was applied to a stamped sheet of steel with residual stamping oils from a mill, in a time corresponding to automotive processing (e.g., ~15 seconds), and processed following automotive e-coat procedures (phosphating + 175–200°C heating), to complete the curing. No problems with adherence or performance were noted. While the CFRE does add weight to a thin gauge steel panel, it weighs much less than what is displaced by using thicker conventional mild steel gauges. The application of the coating showed a significant increased dent resistance, oil canning resistance, and part stiffness.This current two-year project was designed to mature this new technology to near manufacturing readiness to reduce the weight of a vehicle and lower the cost of weight reduction. The process involves the use of thinner gauge steels than are currently used. The collaborative development team included two industrial manufacturers: Diversitak and ArcelorMittal Steel Company; LightMAT; and two National Laboratories: Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL). The team developed a new manufacturing process to reduce the weight of a vehicle and lower the cost of weight reduction, as well as a better understanding of how to apply the coating so that it will perform to a high standard in-service. The team also performed an in-depth study to determine the long-term durability of the materials manufactured using this technology and well-known automotive industry standard tests.The overall process involved stiffening the thinner gauge steel by applying the CFRE on only one side. To accomplish this goal, the optimal reinforcement fiber length and fiber concentration was first determined. This was followed by measuring the coefficient of thermal expansion (CTE) in all three directions, so it could be fed into manufacturing models and methods for rapidly and inexpensively applying the coating. This was followed by panel level evaluations of the coating and steel combination, and then by full part demonstration of the technology on door panels. The final step was corrosion testing of the parts.ArcelorMittal characterized the advanced high strength steel (AHSS) (e.g., metallurgy-heat treatment for required AHSS properties as a function of the sheet thickness, state of internal stress) and quantified CFRE adhesion to the steel as a function of sheet preparation (e.g., rolling and stamping).ORNL optimized the fiber length, fiber concentration, and coating thickness for best vehicle function and performance at the least cost. Along with the suppliers, ORNL developed a durable CFRE application process (e.g., gun material, design, robotic dispensing process) and identified the adhesion stability of the CFRE during process holding. An approach to ensure that application/curing timing conforms to conventional assembly line speed and plant cycle times was determined. ORNL also determined the CTE of the material in all three directions and performed material scanning electron microscopy (SEM) analyses.INL characterized the corrosion properties of the steel panels coated with CFRE. The panels were investigated for corrosion resistance and stability as replacement materials used in automotive body panels to reduce mass. The coupons tested at INL were supplied by Diversitak after an optimized CFRE formulation was achieved in the already coated form for corrosion testing.
Concentrated photovoltaics (CPV) have the potential to significantly enhance the energy conversion utilization of solar panels and reduce solar generation costs, making them a crucial area of advancement in solar power generation technology. However, the concentration of sunlight can lead to overheating of solar panels, resulting in a notable reduction in both the efficiency of solar power generation and the lifespan of the panels. This challenge remains the predominant technical hurdle that hinders the application of concentrated photovoltaic power generation technology. In this study, we propose a new cooling method for concentrated photovoltaic power generation systems via an integrated approach of incorporating Phase-Change Thermal Storage (PCTS) and Thermoelectric Generator (TEG) technology. This new method not only enhances the overall system's electricity generation efficiency but also effectively resolves the technical challenge of concentrated photovoltaic panel overheating issues, ensuring the continuity of concentrated photovoltaic power generation and extending the lifespan of solar panels and their components. In order to make full use of the wasted heat generated by photovoltaic power generation and effectively improve the power generation efficiency of the system, this work developed a phase change heat storage device based on a phase change material. This device uses the temperature difference between day and night to recover wasted heat from photovoltaic power generation. Through integration with the thermoelectric power generation system, thermal energy can be converted into electrical energy. In addition, the Peltier effect of thermoelectric materials is used to construct a photovoltaic panel overheating protection system, which significantly improves the reliability and service life of the system.
Concentrated photovoltaics (CPV) have the potential to significantly enhance the energy conversion utilization of solar panels and reduce solar generation costs, making them a crucial area of advancement in solar power generation technology. However, the concentration of sunlight can lead to overheating of solar panels, resulting in a notable reduction in both the efficiency of solar power generation and the lifespan of the panels. This challenge remains the predominant technical hurdle that hinders the application of concentrated photovoltaic power generation technology. In this study, we propose a new cooling method for concentrated photovoltaic power generation systems via an integrated approach of incorporating Phase-Change Thermal Storage (PCTS) and Thermoelectric Generator (TEG) technology. This new method not only enhances the overall system's electricity generation efficiency but also effectively resolves the technical challenge of concentrated photovoltaic panel overheating issues, ensuring the continuity of concentrated photovoltaic power generation and extending the lifespan of solar panels and their components. In order to make full use of the wasted heat generated by photovoltaic power generation and effectively improve the power generation efficiency of the system, this work developed a phase change heat storage device based on a phase change material. This device uses the temperature difference between day and night to recover wasted heat from photovoltaic power generation. Through integration with the thermoelectric power generation system, thermal energy can be converted into electrical energy. In addition, the Peltier effect of thermoelectric materials is used to construct a photovoltaic panel overheating protection system, which significantly improves the reliability and service life of the system.
(Section 5.1) Composites made from Arkema’s Elium® thermoplastic resin and Johns Manville fiberglass were researched during this project for applications in wind blade manufacturing. A techno-economic model was developed to model this wind blade manufacturing process using these materials in place of traditional composites made with thermoset resin. This model was based on manufacturing a 61.5-meter wind blade, which showed a 4.7% reduction in wind blade cost as compared traditional thermoset materials. These cost savings were not from the thermoplastic material costing less than traditional thermoset materials, but rather from decreased capital costs, faster cycle times and reduced energy requirements and labor costs. (Section 5.2) An infusion and curing model was developed for thermoplastic composite wind blades using PAM-RTM. The primary goal was to demonstrate the infusion simulation for the Elium® resin system on a 13-meter wind blade. Additionally, the exotherm temperature was predicted and compared to measurements, which showed model results within 10% of actual measurements. (Section 5.3) Composite laminate panels and composite sandwich panels with a balsa core were produced; specimens were cut and characterized. Similar composite specimens were made with Elium® thermoplastic resin and Hexion thermoset epoxy (RIMR135/RIMH1366) to enable comparisons between these resin systems. The static test methods included: tensile, compression, in-plane shear, interlaminar shear, flexural, sandwich core shear flexure, and single cantilever beam tests for sandwich beams. Fatigue testing at room temperature was completed to composite laminate panels at a stress ratio of R=0.1 and R=10. In addition, fatigue testing to laminate panels was completed at -30°C, and at room temperature after conditioning specimens at 70°C and 90% relative humidity. Overall, mechanical test results from Elium® composites are similar to epoxy composites. (Section 5.4) Elium composite panels were produced with intentional defects such as voids and nonwetting of fibers to begin to understand performance sensitivity to defects. A thermal digital image correlation (TDIC) method provides high spatial resolution strain field at elevated temperatures and can be used to identify defective regions within composite panels. Flexural modulus differences of 21% were seen between defect and non-defect panels. Other Elium® composite panels were forced to be defective by boiling the resin after infusion, which created voids throughout the composite laminate. X-ray computed tomography scanning was used to view the internal structure of the defect panels. Defect panels had a significant reduction in fatigue life as compared to baseline panels produced without intentional defects. (Section 5.5) Lap shear specimens were fabricated to compare the lap shear strength of an off-the-shelf adhesive (Plexus MA590) and two new adhesives developed by Arkema (Bostik SAF30 90 and Bostik SAF30 120). ISO standard 4587:2003 was used to standardize the testing method and sample fabrication. Lap shear specimens were made at 1mm, 3mm, and 10mm thicknesses. The Bostik adhesive lap shear test results were similar to Plexus for all thicknesses. (Section 5.6) Fiber-reinforced polymer (FRP) composites are typically used in high-performance applications (e.g., aerospace), and their expansion into high-volume industries (e.g. consumer automotive and wind turbine blade manufacturer or similar) is hindered by their cost and a lack of efficient manufacturing techniques. Monitoring the curing process of these composites during manufacturing can improve the efficiency of the process, and therefore reduce the manufacturing cost. Cure monitoring techniques were developed that use probabilistic estimation methods and surface temperature measurements made using infrared cameras. These techniques enable real-time monitoring of the infusion process to locate manufacturing flaws, and they can, potentially, estimate residual stresses in the part. Their commercialization will help facilitate expansion of FRP composites in high-volume industries. (Section 5.7) A 13-meter composite wind blade was produced with Elium® resin and Johns Manville fiberglass; this blade was made with VARTM processing similar to how megawatt-scale wind blades are currently manufactured, but no post-mold heating was used for this thermoplastic composite blade. The wind blade underwent full-scale validation for static loading (4-different load orientations) and flapwise fatigue loading to simulate 20-years of operational loads. The thermoplastic composite wind blade withstood the loading without any noted issues and performed similar to results from a previous full-scale validation to an equivalent epoxy composite wind blade produced with the same blade molds. (Section 5.8) A study was conducted to determine the feasibility of recycling composite wind turbine blade components fabricated with glass fiber reinforced Elium® thermoplastic resin. Dissolution, which is a process unique to thermoplastic matrices, allows recovery of both the polymer matrix and full-length glass fibers, while maintaining their stiffness and strength throughout the recovery process. The economics of recycling is favorable if 50% of the glass fiber is recovered and resold for a process of $\$$ 0.28/kg, and 90% of the resin is recovered and resold at a price of $\$$ 2.50/kg.(Section 10) Recommendations are outlined for commercializing thermoplastic resin for composite wind blade production, in addition to recommended areas for future research.