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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Satellite servicing: A business opportunity?

The possibilities of satellite servicing as a business opportunity are examined. The service rate which a user must be charged to yield a reasonable return is derived and then compared against the market's willingness to pay that rate. Steps taken to provide the basis from which the service rate could be derived include: (1) constructing a hypothetical on orbit servicing business offering both on orbit and associated ground services; (2) estimating the total on orbit service business potential by analyzing mission models to the year 2000; and (3) setting up ground rules to bound the conduct of the business. Using this basic information service demand (business volume) cost to set up the business, costs for operation and maintenance tax rates and desired rate of return are estimated to determine the user charge. Sensitivity of the service rate to various parameters are also assessed. The time span for the business venture runs from 1986 through 2000 with service to 1991 provided via the orbiter and by a space station beyond 1991. This point analysis shows about five years of negative cash flow, with steady profits thereafter.

Wong, R. E.↗
DOE OSTI2020

Greenhouse gas consequences of the China dual credit policy

For over ten years, China has been the largest vehicle market in the world. In order to address energy security and air quality concerns, China issued the Dual Credit policy to improve vehicle efficiency and accelerate New Energy Vehicle adoption. In this paper, a market-penetration model is combined with a vehicle fleet model to assess implications on greenhouse gas (GHG) emissions and energy demand. Here we use this integrated modeling framework to study several scenarios, including hypothetical policy tweaks, oil price, battery cost and charging infrastructure for the Chinese passenger vehicle fleet. The model shows that the total GHGs of the Chinese passenger vehicle fleet are expected to peak in 2032 under the Dual Credit policy. A significant reduction in GHG emissions is possible if more efficient internal combustion engines continue to be part of the technology mix in the short term with more New Energy Vehicle penetration in the long term.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗
DOE OSTI2022

Experimental Evaluation of Thermal Storage Performance of a Dual-Purpose Underground Thermal Battery

A geothermal heat pump (GHP) system is an energy-efficient building heating and cooling technology with great potential for reducing energy consumption and decarbonization. However, applications of GHP are still limited due to the high cost, of which 30% is related to the cost of installing the conventional vertical bore ground heat exchangers, which are usually installed in boreholes 60 meters deep. A dual-purpose underground thermal battery (DPUTB) has been developed to offer a low-cost ground heat exchanger with a built-in thermal storage capacity. The DPUTB innovatively integrates a shallow-bore ground heat exchanger (the outer tank), which can be installed in a borehole less than 6 m deep, with thermal energy storage (TES) (the inner tank). DPUTB has the potential to reduce the cost of a ground source heat pump system while allowing shifting the electric demand of the building served by the GHP system from peak to off-peak hours of the electric grid by charging and discharging the thermal storage. A lab-scale (1:125 in volume) DPUTB prototype was built. Phase change material (PCM) was added to increase the thermal storage capacity and maintain the supply water temperature from the TES within the desired range for direct cooling operation during the discharge period. As PCMs are critical to the TES performance of the DPUTB, this study compared the influence of different PCMs (including salt hydrate and organic PCMs) on the discharge performance of the DPUTB. The thermal State of Charge (SoC) of the DPUTB was used to compare the performance resulting from using different PCMs. Test results indicate that the organic PCM (Methyl Laurate) outperforms salt-hydrate PCMs due to a lower melting temperature and a narrower melting temperature range during the phase change process. The results of this study provide a guide for PCM selection and the optimal design of DPUTB.

Wang, Lingshi↗
DOE OSTI2024

Electromagnetic shower separation in LArTPCs: study of the calorimetric method at LArIAT

This thesis reports a study of the prospects of using calorimetry for separating photon- from electron-initiated electromagnetic (EM) showers in liquid argon time projection chambers (LArTPCs), a prevalent need for neutrino oscillation experiments based on the LArTPC technology as $\gamma$-initiated showers are a significant background to electron neutrino ($\nu_e$) events, whose signature is electron showers. From events simulated in the LArIAT (Liquid Argon In A Testbeam) experiment's detector, we quantitatively evaluated the dependence of the calorimetric separation on the initial momentum and position (along the beamline) of the primary particle. We could conclude that the separation is more efficient if the primary particle is created inside the chamber, whereas the impact of the momentum is not as significant. Furthermore, a first step was taken towards applying the calorimetric method to the showers measured in LArIAT. A convolutional neural network (CNN) trained on simulation was deployed to find EM showers among the events collected by the experiment. The charge deposition at the beginning of the showers found is centered at a plausible value, although the width of the distribution demands further inquiry.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Multilayer Electrodes with Metalized Polymer Current Collector for High-Energy Lithium-Ion Batteries with Extreme-Fast-Charging Capability

The pursuit of batteries capable of extreme fast charging (XFC), that also satisfy high energy and safety criteria, poses a significant challenge to current lithium-ion battery technologies. Additionally, the increasing demand for aluminum (Al) and copper (Cu) in electrification, and vehicle light weighting is driving these metals towards near-critical status in the medium term. This study introduced metalized polymer films by depositing an Al or Cu thin layer onto two sides of a polyethylene terephthalate (PET) film – named mPET/Al and mPET/Cu, as lightweight, cost-effective alternatives to traditional metal current collectors in LIBs. We have utilized current collectors that significantly reduce weight (by 73%), thickness (by 33%), and cost (by 85%) compared to traditional metal foil counterparts. We conducted an extensive evaluation of their mechanical and electrical properties, including in-plane and through-plane resistivities, affirming their suitability for the roll-to-roll battery manufacturing process. Additionally, a novel XFC testing protocol was employed to thoroughly assess the cells' (both half and full-cell) performance across various C-rates and under long-term tests. These advancements have the potential to enhance energy density to 280 Wh/kg at the electrode level under 10-minute charging at 6C. Through testing, including a novel XFC protocol across various C-rates and long-term cycling (up to 1000 cycles) in different cell configurations, we have demonstrated the superior performance of these metalized polymer films. Notably, mPET/Cu and mPET/Al foils exhibited comparable capacities to conventional cells under XFC, with the mPET cells showing a 27% improvement in energy density at 6C and maintaining significant energy density after 1000 cycles. This study underscored the potential of mPET foils to revolutionize the roll-to-roll battery manufacturing process and significantly advance the performance metrics of LIBs in EV applications. Moreover, our results suggest that there is potential to enhance the performance of mPET foils, especially mPET/Al, by optimizing the manufacturing process to achieve higher conductivity.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Influence of Diffuse and Ground-Reflected Irradiance on the Spectral Modeling of Solar Reference Cells

Thermal Energy Storage (TES) is a key component for solar thermal applications to bridge the gap between the demand for thermal energy and the supply of solar energy, whose availability depends on the time of day and season. Thus, cost-effective packed-bed thermal containers filled with a solid storage medium have been proposed for high-temperature sensible heat storage as materials are abundant and relatively cheap. Thus, it is necessary to investigate their performance and temperature profiles during the charge-discharge cycle. Several models are available for this purpose. Typically, the more detailed a model, the greater the computational effort required to solve it, and hence a time-efficient model is needed to prevent excessively long computation times for long-term analysis. At the more basic level, the common Hughes E-NTU model and the less realistic simplified Infinite-NTU model are very important for their less time and computational effort. In this paper, the appropriateness of employing the Infinite-NTU model was evaluated to investigate the performance of a typical and scalable rock-bed TES as a case study. The results presented provide a methodology to quickly test the validity of the model and predict the temperature profile for the case under study. Accordingly, such simple charge-discharge cycle thermal performance predictions are important to plan, design, and rapidly deploy a reliable and economical solar thermal system for the supply of valuable heat to high-temperature demanding applications of power generation and industrial processes as part of a rapid shift towards non-polluting renewable energy. Keywords: Solar Thermal, TES, Packed-bed, NTU model, Temperature profile

PV modeling↗
DOE OSTI2024

An Empirical Validation of a Constrained Bin Packing Algorithm for a Home Energy Management System

The increasing number of intelligent electrical appliances and home energy management systems provide a big opportunity for demand response services from residential and small commercial buildings to the grid. Simultaneously, direct control of individual devices by utilities can cause communication bottlenecks, as well as coordination and privacy concerns. These challenges can be addressed by combining the constituent devices into a single house battery equivalent for the purposes of demand response, using Minkowski sum and a 2d bin packing problem. However, the well-studied traditional problems have not been tested in a real house, as implementation carries significant challenges of its own. We deploy the packing problem on residential devices in a controllable house. We report the barriers we found, such as charge forecast and scalability of the algorithm, and discuss our solutions. The study serves as an intermediate step between existing theoretical research and possible future steps, such as prototype deployments of systems that provide residential demand response.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2017

Mass Spectra Deconvolution of Gaseous Mixtures Containing Volatile Organic Compounds

The Spacecraft Atmosphere Monitor (S.A.M.) analyzes all gaseous pollutants in the 1-150Th mass-to-charge range based on their positive-ion mass spectra. Of particular interest is the Trace Gas Analysis (TGA) mode of operation in which S.A.M detects minute amounts of volatile organic compounds (VOC). Pollutant component of the ambient air is sampled on demand in twenty full mass spectra per second. All spectra is accumulated in two-second intervals by an on-board Field Programmable Gate Arrays (FPGA) unit. Mass spectra represents the number of detected fragment ions in a given mass-to-charge ratio channel. Electron impact ionization of neutral molecules results in creation of numerous fragment ions and most of organic compounds will contribute several identical fragments. Despite the presence of these molecular isobars, we developed the deconvolution algorithm capable of identifying target species based on their characteristic fragmentation patterns. We investigate the efficiency of deconvolution algorithm as a function of mass resolution with which mass spectrum is acquired. Higher the mass resolution, better the chances are to distinguish between stereoisomers using their fragmentation propensities, but also results in higher data volumes to be processed by a set of small footprint software stacks hosted by an on-board computer. Finding the balance between deconvolution accuracy and generated data volume under time constrains and limited computing resources is the main topic of this study.

Darrach, M.↗
DOE OSTI2021

Exploring Charged Defects in Ferroelectrics by the Switching Spectroscopy Piezoresponse Force Microscopy

Monitoring the charged defect concentration at the nanoscale is of critical importance for both the fundamental science and applications of ferroelectrics. However, up-to-date, high-resolution study methods for the investigation of structural defects, such as transmission electron microscopy, X-ray tomography, etc., are expensive and demand complicated sample preparation. Here, with an example of the lanthanum-doped bismuth ferrite ceramics, a novel method is proposed based on the switching spectroscopy piezoresponse force microscopy (SSPFM) that allows probing the electric potential from buried subsurface charged defects in the ferroelectric materials with a nanometer-scale spatial resolution. When compared with the composition-sensitive methods, such as neutron diffraction, X-ray photoelectron spectroscopy, and local time-of-flight secondary ion mass spectrometry, the SSPFM sensitivity to the variation of the electric potential from the charged defects is shown to be equivalent to less than 0.3 at% of the defect concentration. Additionally, the possibility to locally evaluate dynamics of the polarization screening caused by the charged defects is demonstrated, which is of significant interest for further understanding defect-mediated processes in ferroelectrics.

42 ENGINEERING↗
DOE OSTI2023

Multiplexed photoinjector optimization for high-repetition-rate free-electron lasers

The multiplexing capabilities of superconducting X-ray free-electron lasers (FELs) have gained much attention in recent years. The demanding requirements for photon properties from multiple undulator lines necessitate more flexible beam manipulation techniques to achieve the goal of “beam on demand”. In this paper, we investigate a multiplexed configuration for the photoinjector of high-repetition-rate FELs that aims to simultaneously provide low-emittance electron beams of different charges. A parallel, multi-objective genetic algorithm is implemented for the photoinjector parameter optimization. The proposed configuration could drastically enhance the flexibility of beam manipulation to improve multiplexing capabilities and realize the full potential of the facility.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Monthly Sewer Monitoring Report for LLNL Livermore Site, April 2020

Lawrence Livermore National Laboratory (LLNL) collects effluent samples from its sewer outfall at the B196 Sewer Monitoring Station (SMS). Effluent flow-proportional composite samples are collected at the SMS on a daily (midnight-to-midnight), weekly (Thursday through Wednesday), and “monthly” (composited from daily) basis; effluent grab samples are also collected each month at that same location. Certified contract laboratories analyzes these compliance samples, and results (Tables 1–3) are used to establish LLNL compliance with the 2019–2020 Wastewater Discharge Permit (Permit 1250) granted by the City of Livermore Water Resources Division (WRD). Supplemental analyses for biochemical oxygen demand (BOD) and total suspended solids (TSS) are performed onsite and reported (Table 4) for the calculation and assessment of sewer service charges. Quarterly, effluent is sampled for metals (24-hour composite) and cyanide (grab sample) concentrations (mg/L). The results are presented in Table 5. In addition to the sampling noted above, the SMS continuously monitors LLNL sewage effluent in real-time for flow rate, pH, metals, and radioactivity. Standard measurement methods are used to monitor flow and pH to determine permit compliance. Unique nonstandard analytical methods monitor for the presence of metals and radioactivity using x-ray fluorescence (XRF) and gamma spectroscopy, respectively. If an anomalous condition is detected by the monitoring system, an alarm activates LLNL’s Sewer Diversion Facility (SDF) and Livermore Water Reclamation Plant (LWRP) operators are notified that a potential release has occurred.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Low-cost buffer storage for solar industrial steam applications

Motivation and importance: Many industrial process heat consumers operate throughout the day, and deep decarbonization with solar energy requires thermal energy storage. Thermal energy storage provides an additional operational benefit of firm delivery of steam – essential to reducing the risk of costly production interruptions. The group of process heat consumers that use steam for biofuels production for the California transportation fuels market is incentivized through the Low Carbon Fuel Standard (LCFS) to reduce their carbon intensity through the use of solar steam. Examples include ethanol and dimethyl ether production. The production of these and other fuels involves distillation driven by steam reboilers with steam pressures in the range 100-280 psig. These pressures can be delivered from the type of thermal energy storage that has been the focus of this project – a steam accumulator Sunvapor, Inc. (SVI) calls a “Bullet Steam Accumulator” or “BSA TM ”. Our project adds to the understanding of the design and integration of steam accumulators charged by solar thermal energy in a biofuels production facility, and similar facilities that consume process steam. The fuel application requires a demanding level of Process Safety Management not found in other steam applications. The type of steam accumulator SVI engineered and built integrates steam generation and storage in one vessel to reduce cost. Achieving a first of a kind permit to operate such a first device has also added to the understanding of the industrial application of such systems. Goals: The overall goal of the project has been to demonstrate the advantages that a “Bullet Steam Accumulator” (BSA™) can provide to solar steam integration with a manufacturing process. The industrial host has already been convinced of the potential of the available solar steam to lower than carbon intensity score. They have been interviewed for a number of publications such as that tout the advantages SVI’s system brings to their operations. Accomplishments: At the end of 2023 Sunvapor placed in service the country’s first industrial solar boiler with thermal energy storage. At the same time, this placement in service represents the first pilot commercial system to decarbonize biofuels production through the use of solar thermal energy. While the full technical effectiveness will be shown as soon as the customer’s plant is able to consume the available steam, the economic feasibility was indicated early in the project when the combination of costs and steam pricing required to meet investor expectations was determined. The project represents a reference pilot from which a full-scale commercial system may be expanded. This pilot is a necessary first step in providing the full potential benefits to the public, including decarbonization of transportation fuels. The decarbonization of the separation steps in fuels production may be the most cost-effective and nearest term solar fuel. Co-benefits include a reduction of air pollutants such as NOx and particulate matter, and job creation for the construction, operation and maintenance of industrial solar facilities.

14 SOLAR ENERGY↗
DOE OSTI2022

Coupling a Lagrangian–Eulerian Spark-Ignition (LESI) model with LES combustion models for engine simulations

In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO 2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

R&D Insights for Extreme Fast Charging of Medium- and Heavy-Duty Vehicles: Insights from the NREL Commercial Vehicles and Extreme Fast Charging Research Needs Workshop, August 27-28, 2019

As battery costs have declined and battery performance has improved, the applicability of vehicle electrification has expanded beyond passenger cars to the commercial vehicle sector. However, due to the larger batteries that would be needed for the medium- and heavy-duty (MDHD) sector, the electric charging capabilities to serve these larger commercial vehicles will need to be substantially more powerful than light-duty chargers. More specifically, such 'extreme fast charging' (XFC) will likely need to reach the megawatt scale to provide a full charge in less than 30 minutes in some applications. In addition, the combined cost of electrified vehicles and charging must be competitive with the costs of petroleum-based technologies and other alternatives to encourage widespread adoption of battery electric vehicles (BEVs) among MDHD fleets. Most of these fleets have a commercial mission and demand low total cost of ownership (TCO) (which motivates minimal refueling times) and high performance from their vehicles.

25 ENERGY STORAGE↗
DOE OSTI2024

Quantitative local state of charge mapping by operando electrochemical fluorescence microscopy in porous electrodes

We introduce operando quantitative electrochemical fluorescence state of charge mapping (QEFSM), a non-invasive technique to study operating electrochemical systems along with a new design of optically transparent microfluidic redox flow cells compatible with the most demanding optical requirements. QEFSM allows quantitative mappings of the concentration of a particular oxidation state of a redox-active species within a porous electrode during its operation. In this study, we used confocal microscopy to map the fluorescence signal of the reduced form of 2,7-anthraquinone disulfonate (AQDS) in a set of multistep-chronoamperometry experiments. Calibrating these images and incorporating an analytical model of quinhydrone heterodimer formation with no free parameters, and accounting for the emission of each species involved, we determined the local molecular concentration and the state of charge (SOC) fields within a commercial porous electrode during operation. With this method, electrochemical conversion and species advection, reaction and diffusion can be monitored at heretofore unprecedented transverse and axial resolution (1 μm and 25 μm, respectively) at frame rates of 0.5 Hz, opening new routes to understanding local electrochemical processes in porous electrodes. Here, we observed pore-scale SOC inhomogeneities appearing when the fraction of electroactive species converted in a single pass through the electrode becomes large.

42 ENGINEERING↗
DOE OSTI2026

Understanding Electric Vehicle Range and Charging Needs: Interactions Between Ambient Temperature, Commute Patterns, and State-of-Charge Usage

Electric vehicle (EV) performance can vary substantially under real-world operating conditions, particularly due to ambient temperature effects on energy consumption, battery behavior, and thermal management requirements. This study quantifies how weather conditions, daily driving patterns, and State-of-Charge (SOC) usage strategies jointly influence EV driving range, charging frequency, and overall energy efficiency. A detailed and experimentally validated Autonomie vehicle model is developed, integrating a powertrain, a mono-zonal cabin model, and a battery electro-thermal model. Three battery sizes (200-, 300-, and 400-mile homologated ranges) are assessed across five commute profiles (20–200 miles) and six ambient temperatures (−18 °C to 50 °C), including scenarios with and without preconditioning. Results show that extreme temperatures could significantly decrease the maximum achievable range by up to 55% in cold conditions (−18 °C) and 40% in hot conditions (50 °C), relative to moderate conditions. Larger battery packs retain a greater fraction of their nominal range under thermal stress, while smaller packs experience sharper relative penalties due to the higher contribution of thermal loads to total energy demand. The analysis further demonstrates that limiting operation to partial SOC windows (e.g., 80–20%), a common real-world practice, significantly reduces achievable range and increases charging frequency, particularly in cold weather. Thermal preconditioning while plugged in is shown to mitigate these effects for short trips, reducing energy consumption by up to 31% in hot conditions and 7% in cold conditions. The findings demonstrate how climate, SOC usage behavior, and thermal management jointly shape the practical driving capability of EVs, highlighting the importance of efficient thermal management and realistic user charging strategies for ensuring reliable EV operation across diverse climatic scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

EVI-EnSitePy (Electric Vehicle Infrastructure – Energy Estimation and Site Optimization Tool in Python) [EVI-X Modeling Suite] [SWR-25-07]

EVI-EnSitePy is a comprehensive agent-based tool designed for the analysis and design of high-power charging sites, encompassing a wide array of site agents including Electric Vehicles (EVs), chargers, energy storage units (ESS), renewable energy resources (DER), and loads. This versatile tool offers diverse functionalities and a modular modeling approach, allowing detailed configuration of agents based on power ratings, port numbers, energy capacities, demand requirements, charger interfaces, and flexibility to customize the tool for project specific goals. By simulating agent interactions and employing various metrics, EVI-EnSitePy enables the assessment of site performance, exploration of energy management systems (EMS), and implementation of innovative EV charging policies. Utilizing EV charge schedules and arrival states, the tool performs thorough charging site simulations, with outputs consisting of agent and site-level power profiles and statistical metrics. Employing a tree graph structure, EVI-EnSitePy supports nested site structures and power distribution modeling. The tool's ability to generate charging schedules deterministically or via stochastic analysis further enhances its versatility. Through its features and capabilities, EVI-EnSitePy offers a powerful platform for informed decision-making in the realm of high-power charging site design and operation.

Jackson, Derek [National Renewable Energy Laborato↗