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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Hybrid stochastic synapses enabled by scaled ferroelectric field-effect transistors

Achieving brain-like density and performance in neuromorphic computers necessitates scaling down the size of nanodevices emulating neuro-synaptic functionalities. However, scaling nanodevices results in reduction of programming resolution and emergence of stochastic non-idealities. While prior work has mainly focused on binary transitions, in this work, we leverage the stochastic switching of a three-state ferroelectric field-effect transistor to implement a long-term and short-term two-tier stochastic synaptic memory with a single device. Experimental measurements are performed on a scaled 28 nm high-k metal gate technology-based device to develop a probabilistic model of the hybrid stochastic synapse. In addition to the advantage of ultra-low programming energies afforded by scaling, our hardware–algorithm co-design analysis reveals the efficacy of the two-tier memory in comparison to binary stochastic synapses in on-chip learning tasks—paving the way for algorithms exploiting multi-state devices with probabilistic transitions beyond deterministic ones.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1986

Hydrodynamic aspects of shark scales

Ridge morphometrices on placoid scales from 12 galeoid shark species were examined in order to evaluate their potential value for frictional drag reduction. The geometry of the shark scales is similar to longitudinal grooved surfaces (riblets) that have been previously shown to give 8 percent skin-friction reduction for turbulent boundary layers. The present study of the shark scales was undertaken to determine if the physical dimensions of the ridges on the shark scales are of the right magnitude to be used by the sharks for drag reduction based on previous riblet work. The results indicate that the ridge heights and spacings are normally maintained between the predicted optimal values proposed for voluntary and burst swimming speeds throughout the individual's ontogeny. Moreover, the species which might be considered to be the faster posses smaller and more closely spaced ridges that based on the riblet work would suggest a greater frictional drag reduction value at the high swimming speeds, as compared to their more sluggish counterparts.

Raschi, W. G.↗
DOE OSTI2024

Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints

Abstract Dimension reduction techniques are an essential part of the climate analyst’s toolkit. Due to the enormous scale of climate data, dimension reduction methods are used to identify major patterns of variability within climate dynamics, to create compelling and informative visualizations, and to quantify major named modes such as El Niño–Southern Oscillation. Principal components analysis (PCA), also known as the method of empirical orthogonal functions (EOFs), is the most commonly used form of dimension reduction, characterized by a remarkable confluence of attractive mathematical, statistical, and computational properties. Despite its ubiquity, PCA suffers from several difficulties relevant to climate science: high computational burden with large datasets, decreased statistical accuracy in high dimensions, and difficulties comparing across multiple datasets. In this paper, we introduce several variants of PCA that are likely to be of use in climate sciences and address these problems. Specifically, we introduce non-negative , sparse , and tensor PCA and demonstrate how each approach provides superior pattern recognition in climate data. We also discuss approaches to comparing PCA-family results within and across datasets in a domain-relevant manner. We demonstrate these approaches through an analysis of several runs of the E3SM climate model from 1991 to 1995, focusing on the simulated response to the Mt. Pinatubo eruption; our findings are consistent with a recently identified stratospheric warming fingerprint associated with this type of stratospheric aerosol injection.

Weylandt, Michael↗
DOE OSTI2025

Measurements and kinetic modeling of O 2 vibrational kinetics in O 2 –Ar mixtures partially dissociated by a Ns pulse discharge

Vibrational kinetics of O 2 is studied during the O atom recombination in an O 2 –Ar mixture, partially dissociated by a burst of ns discharge pulses in a heated plasma flow reactor. The time-resolved temperature in the discharge afterglow is determined by Rayleigh scattering. Time-resolved O atom number density is measured by ps Two-Photon absorption Laser Induced Fluorescence, calibrated in xenon. Time-resolved vibrational level populations of molecular oxygen, O 2 (v= 8–20), are measured by ps Laser Induced Fluorescence (LIF), with the absolute calibration by NO LIF. Time-resolved ozone number density is monitored by broadband UV absorption. The results are compared with the predictions of a state-specific kinetic model. The experimental data indicate a rapid initial decay of O 2 (v) populations generated by electron impact in the discharge, due to the vibration-translation (V–T) relaxation by O atoms. This is followed by a slower population reduction, on the time scale much longer compared to that for V–T relaxation or vibration-vibration (V–V) exchange. Both O atoms and the O 2 (v) populations decay on the same time scale, indicating that chemical reactions initiated by the O atom recombination result in the generation of vibrationally excited O 2 molecules. These trends are reproduced by the kinetic model, which shows that the reaction of O atoms with ozone is the dominant pathway of O 2 (v) generation at the present conditions. The predicted relative O 2 (v) populations are close to the experimental results, but absolute number densities differ from the experimental data. This is likely due to uncertainties in the absolute calibration of LIF measurements and in the spectroscopic model used in the data reduction. The present work demonstrates the capability for the absolute, time-resolved measurements of vibrationally excited O 2 in recombining gas flows, to quantify the energy partition in the recombination reactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2023

Sidelobe Modeling and Mitigation for A Three Mirror Anastigmat Cosmic Microwave Background Telescope

Telescopes measuring cosmic microwave background (CMB) polarization on large angular scales require exquisite control of systematic errors to ensure the fidelity of the cosmological results. In particular, far-sidelobe contamination from wide angle scattering is a potentially prominent source of systematic error for large aperture microwave telescopes. Here we describe and demonstrate a ray-tracing-based modeling technique to predict far sidelobes for a three mirror anastigmat telescope designed to observe the CMB from the South Pole. Those sidelobes are produced by light scattered in the receiver optics subsequently interacting with the walls of the surrounding telescope enclosure. After comparing simulated sidelobe maps and angular power spectra for different enclosure wall treatments, we propose a highly scattering surface that would provide more than an order of magnitude reduction in the degree-scale far-sidelobe contrast compared to a typical reflective surface. We conclude by discussing the fabrication of a prototype scattering wall panel and presenting measurements of its angular scattering profile.

Ian Gullett↗
DOE OSTI2023

Direct observation of the local microenvironment in inhomogeneous CO 2 reduction gas diffusion electrodes via versatile pOH imaging

In this study, we report how the micrometer-scale morphology of a carbon dioxide reduction (CO 2 R) gas diffusion electrode (GDE) affects the mass transport properties and with it, the local CO 2 R performance. We developed a technique to probe the microenvironment in a CO 2 R GDE via local pOH imaging with time- and three-dimensional spatial, micrometer-scale resolution. The local activity of hydroxide anions (OH - ), represented by the pOH value, around a GDE in contact with an aqueous electrolyte is a crucial parameter that governs the catalytic activity and CO 2 R selectivity. Here, we use fluorescence confocal laser scanning microscopy (CLSM) to create maps of the local pOH around a copper GDE by combining two ratiometric fluorescent dyes, one of which is demonstrated as a pOH sensor for the first time in this work. We observe that the local pOH decreases when current is applied due to the creation of OH - as a byproduct of CO 2 R. Interestingly, the pOH is lower inside microtrenches compared to the electrode surface and decreases further as trenches become more narrow due to enhanced trapping of OH - . We support our experimental results with multiphysics simulations that correlate exceptionally well with measurements. These simulations additionally suggest that the decreased pOH inside microcavities in the surface of a CO 2 R GDE leads to locally enhanced selectivity towards multicarbon (C 2+ ) products. This study suggests that narrow microstructures on the length scale of 5 μm in a GDE surface serve as local CO 2 R hotspots, and thus highlights the importance of a GDE's micromorphology on the CO 2 R performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Measurements of Infrared and Acoustic Source Distributions in Jet Plumes

The aim of this investigation was to use the linear phased array (LPA) microphones and infrared (IR) imaging to study the effects of advanced nozzle-mixing techniques on jet noise reduction. Several full-scale engine nozzles were tested at varying power cycles with the linear phased array setup parallel to the jet axis. The array consisted of 16 sparsely distributed microphones. The phased array microphone measurements were taken at a distance of 51.0 ft (15.5 m) from the jet axis, and the results were used to obtain relative overall sound pressure levels from one nozzle design to the other. The IR imaging system was used to acquire real-time dynamic thermal patterns of the exhaust jet from the nozzles tested. The IR camera measured the IR radiation from the nozzle exit to a distance of six fan diameters (X/D(sub FAN) = 6), along the jet plume axis. The images confirmed the expected jet plume mixing intensity, and the phased array results showed the differences in sound pressure level with respect to nozzle configurations. The results show the effects of changes in configurations to the exit nozzles on both the flows mixing patterns and radiant energy dissipation patterns. By comparing the results from these two measurements, a relationship between noise reduction and core/bypass flow mixing is demonstrated.

Agboola, Femi A.↗
NASA NTRS2000

Advanced Subsonic Technology (AST) Separate-Flow High-Bypass Ratio Nozzle Noise Reduction Program Test Report

NASA s model-scale nozzle noise tests show that it is possible to achieve a 3 EPNdB jet noise reduction with inwardfacing chevrons and flipper-tabs installed on the primary nozzle and fan nozzle chevrons. These chevrons and tabs are simple devices and are easy to be incorporated into existing short duct separate-flow nonmixed nozzle exhaust systems. However, these devices are expected to cause some small amount of thrust loss relative to the axisymmetric baseline nozzle system. Thus, it is important to have these devices further tested in a calibrated nozzle performance test facility to quantify the thrust performances of these devices. The choice of chevrons or tabs for jet noise suppression would most likely be based on the results of thrust loss performance tests to be conducted by Aero System Engineering (ASE) Inc. It is anticipated that the most promising concepts identified from this program will be validated in full scale engine tests at both Pratt & Whitney and Allied-Signal, under funding from NASA s Engine Validation of Noise Reduction Concepts (EVNRC) programs. This will bring the technology readiness level to the point where the jet noise suppression concepts could be incorporated with high confidence into either new or existing turbofan engines having short-duct, separate-flow nacelles.

Low, John K. C.↗
DOE OSTI2020

SNS: A Solution-Based Nonlinear Subspace Method for Time-Dependent Model Order Reduction

Several reduced order models have been successfully developed for nonlinear dynamical systems. To achieve a considerable speed-up, a hyper-reduction step is needed to reduce the computational complexity due to nonlinear terms. Many hyper-reduction techniques require the construction of nonlinear term basis, which introduces a computationally expensive offline phase. A novel way of constructing nonlinear term basis within the hyper-reduction process is introduced. In contrast to the traditional hyper-reduction techniques where the collection of nonlinear term snapshots is required, the SNS method avoids collecting the nonlinear term snapshots. Instead, it uses the solution snapshots that are used for building a solution basis, which enables avoiding an extra data compression of nonlinear term snapshots. As a result, the SNS method provides a more efficient offline strategy than the traditional model order reduction techniques, such as the DEIM, GNAT, and ST-GNAT methods. The SNS method is theoretically justified by the conforming subspace condition and the subspace inclusion relation. It is useful for model order reduction of large-scale nonlinear dynamical problems to reduce the offline cost. It is especially useful for ST-GNAT that has shown promising results, such as a good accuracy with a considerable online speed-up for hyperbolic problems in a recent paper by Choi and Carlberg [SIAM J. Sci. Comput., 41 (2019), pp. A26--A58], because ST-GNAT involves an expensive offline cost related to collecting nonlinear term snapshots. Error analysis for the SNS method is presented. Numerical results support that the accuracy of the solution from the SNS method is comparable to the traditional methods and a considerable speed-up (i.e., a factor of two to a hundred) is achieved in the offline phase.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Cloud adjustments from large-scale smoke–circulation interactions strongly modulate the southeastern Atlantic stratocumulus-to-cumulus transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (~1–2 K) and greatly enhanced moisture (>2 g kg -1 ) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Cloud Adjustments From Large-Scale Smoke–Circulation Interactions Strongly Modulate the Southeastern Atlantic Stratocumulus-to-Cumulus Transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (∼1–2 K) and greatly enhanced moisture (>2 g kg−1) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

southeast Atlantic Ocean↗
DOE OSTI2022

Future-proofing photovoltaics module reliability through a unifying predictive modeling framework

Solar energy, especially photovoltaics (PV), plays a significant role in the global energy transition required for decarbonization. Technological advancements in increasing efficiencies coupled with cost reductions through economies of scale made PV a cost-competitive energy source set to exceed the milestone of 1 TW globally deployed capacity in 2022. However, ongoing downward price pressure coupled with increasing service life expectations creates tremendous challenges for reliability engineers in ensuring the safe and reliable operation of PV modules and systems over the anticipated service life. Today's reliability research efforts aim for module lifetimes of up to 50 years. Still, our current tools fall short in accurately assessing degradation mechanisms and failure modes over such extended periods. We argue that the well-established PV reliability learning cycle needs to be accelerated to keep up with the rapid technological advancements and high expectations that are put on PV and its role in the global energy transition. In this article, we explore the evolution of the PV reliability learning cycle and highlight the significance that predictive modeling capabilities will have on future PV module reliability. We propose creating a unifying modeling framework - which once established will enable the holistic assessment of PV module reliability, accelerate the PV reliability learning cycle, and bring us closer to quantitative service life predictions of PV modules.

14 SOLAR ENERGY↗
DOE OSTI2021

Statistical learning for predicting density–matrix-based electron dynamics

In this study, we consider the problem of learning density-dependent molecular Hamiltonian matrices from time series of electron density matrices, all in the context of Hartree–Fock theory. Prior work developed a solution to this problem for small molecular systems with density and Hamiltonian matrices of size at most 6 × 6. Here, using a battery of techniques, we scale prior methods to larger molecular systems with, for example, 29 × 29 matrices. This includes systems that either have more electrons or are expressed in large basis sets such as 6-311++G**. Scaling the method to larger systems enhances its relevance for realistic applications in chemistry and physics. To achieve this scaling, we apply dimensionality reduction, ridge regression and analytic computation of Hessians. Through the combination of these techniques, we are able to learn Hamiltonians by minimizing an objective function that encodes local propagation error. Importantly, these learned Hamiltonians can then be used to predict electron dynamics for thousands of steps: When we use our learned Hamiltonians to numerically solve the time-dependent Hartree–Fock equation, we obtain predicted dynamics that are in close quantitative agreement with ground truth dynamics. This includes field-off trajectories similar to the training data and field-on trajectories outside of the training data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Thermodynamic origin of the pressure-induced Invar effect: General criterion and experimental study of Fe 68 ⁢Pd 32

Synchrotron X-ray diffraction measurements were performed on 57 Fe 68 Pd 32 at multiple pressures and two temperatures in a diamond-anvil cell. Between 4 and 11GPa, the thermal expansion was zero or slightly negative. This pressure-induced Invar effect was studied further with 57 Fe nuclear forward scattering and nuclear resonant inelastic X-ray scattering to obtain information on the pressure-induced changes in both the magnetization and the phonon density of states. Magnetic entropy and phonon entropy were obtained from these results, the latter with additional measurements from inelastic neutron scattering to account for the contributions from Pd atoms. The dependencies of these entropies on pressure gave the magnetic and phonon contributions to thermal expansion. These canceled in the region of pressure-induced Invar behavior, even though they individually increased by more than a factor of 2 below the Curie pressure. The behavior of phonons gives evidence for spin-phonon interactions in Fe 68 Pd 32 . A general explanation of the pressure-induced Invar effect is presented, showing that Invar behavior is typically expected at a pressure P* below a magnetic transition at pressure PC. The difference in pressure P C − P* scales with the fractional reduction in magnetic exchange interaction divided by the average Gr¨uneisen parameter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Online Adaptive Algorithm for Constraint Energy Minimizing Generalized Multiscale Discontinuous Galerkin Method

Here in this research, we propose an online basis enrichment strategy within the framework of a recently developed constraint energy minimizing generalized multiscale discontinuous Galerkin method. Combining the technique of oversampling, one makes use of the information of the current residuals to adaptively construct basis functions in the online stage to reduce the error of multiscale approximation. A complete analysis of the method is presented, which shows the proposed online enrichment leads to a fast convergence from multiscale approximation to the fine-scale solution. The error reduction can be made sufficiently large by suitably selecting oversampling regions and the number of oversampling layers. Further, the convergence rate of the enrichment algorithm depends on a factor of exponential decay regarding the number of oversampling layers and a user-defined parameter. Numerical results are provided to demonstrate the effectiveness and efficiency of the proposed online adaptive algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

State of the art in low-temperature and high-temperature electrolysis

Water electrolysis is gaining traction in large-scale applications, with production of multiple technologies scaling to hundreds and thousands of megawatts of new electrolyzer capacity annually. Low-temperature electrolysis has dominated the electrolyzer market for decades, but still only represents a small amount of the overall hydrogen market, due to the higher production costs versus hydrogen derived from fossil fuels. Advances are needed in capital cost and efficiency to close the cost gap, especially for energy applications. Similarly, while high-temperature electrolyzers can operate more efficiently, reducing the operating cost, they still need further scale-up and cost reduction to compete in these markets. Understanding the recent advances in each and the priority research directions is important to focus and accelerate innovation, and will be discussed in this article. The different advantages and disadvantages of each of these technologies will also be reviewed; there will likely be applications for each in the overall deployment of renewable hydrogen.

36 MATERIALS SCIENCE↗
DOE OSTI2021

International Meeting on Fuel Cell and Electrolyzer Quality Control: Summary Report

Quality control (QC) for both polymer electrolyte membrane fuel cell and electrolysis membrane electrode assembly (MEA) materials is a key challenge for scale-up and cost reduction. Developing methods for detecting defects, as well as measuring critical material properties and understanding the impact of as-manufactured variations in these materials on cell performance and lifetime, are critical barriers. To help address these needs, the National Research Council Canada (NRC), Fraunhofer Institute for Solar Energy Systems (ISE), and the National Renewable Energy Laboratory (NREL) have organized and facilitated a series of workshops on the topic, bringing together industry, academia, and research institutions from North America and Europe. Prior workshops in Canada and Germany have focused on the status of quality tool capabilities and identification of needed developments for fuel cells. These meetings have garnered an excellent response and follow-on attendance, with over 100 unique attendees.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Recyclable Design for Retaining High Solar Absorptivity of the Media in CSP

Efficient thermal energy storage is pivotal to lowering the levelized cost of electricity (LCOE) for Concentrating Solar Power (CSP) plants. In solid-particle systems, however, prolonged high-temperature service degrades particle solar absorptivity, eroding overall efficiency. This project demonstrates a hydrogen-assisted recovery process that reliably restores absorptivity to >90 %, offering a practical route to sustain long-term CSP performance. Bench-scale investigations mapped the reduction kinetics of optically faded particles across hydrogen concentrations, temperatures, and residence times. Coupling mass-spectrometric monitoring with machine-learning optimization minimized energy demand while maximizing absorptivity gain. The resulting process window—moderate hydrogen partial pressures, 15–30 min dwell times, and temperatures well below initial calcination levels—cuts energy consumption well below that of incumbent re-blackening methods. A prototype recovery reactor processed multiple 2 kg batches with repeatable outcomes, confirming scalability and operational robustness. Integrated techno-economic analysis indicates material and operating cost reductions exceeding 15 % relative to conventional particle replacement or chemical re-coating, translating directly into lower LCOE for next-generation CSP facilities. By uniting fundamental reaction-kinetics insight with pragmatic engineering, this work advances the solid-particle pathway, delivering a cost-effective, field-deployable solution to one of CSP’s key durability challenges and strengthening the commercial outlook for high-temperature renewable power.

14 SOLAR ENERGY↗