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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Opportunities and challenges in thermochemical conversion of municipal solid waste: A comprehensive review

Recent advancements in thermochemical conversion processes have elucidated new pathways for converting municipal solid waste into valuable resources. This review explores the primary thermochemical conversion methods, including combustion, gasification, pyrolysis, torrefaction, hydrothermal carbonization, and hydrothermal liquefaction, emphasizing their potential roles in waste management and energy recovery. Key challenges including feedstock variability, ash behavior, and scale-up limitations are discussed alongside opportunities for hybrid systems and circular economy integration. A comparative analysis of research publications indicates a significant focus on thermochemical pathways within the broader context of municipal solid waste research, underscoring the growing interest in these technologies. Recent advancements in each thermochemical process, alongside their operational, technical, and economic challenges, are discussed. Comparative data reveal that torrefaction enhances the hydrophobicity and grindability of municipal solid waste components, though its energy densification benefits are more modest than those observed in biomass. Hydrothermal carbonization and liquefaction are highlighted for their ability to process high-moisture and heterogeneous waste streams. The review also synthesizes recent findings on reactor configurations, emissions control, and synergistic effects in co-processing municipal solid waste fractions. The findings underscore the importance of developing standardized protocols for municipal solid waste characterization and the need for innovative hybrid systems to improve efficiency.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Sustainable aviation fuels from biomass and biowaste via bio- and chemo-catalytic conversion: Catalysis, process challenges, and opportunities

Sustainable aviation fuel (SAF) production from biomass and biowaste streams is an attractive option for decarbonizing the aviation sector, one of the most-difficult-to-electrify transportation sectors. Despite ongoing commercialization efforts using ASTM-certified pathways (e.g., lipid conversion, Fischer-Tropsch synthesis), production capacities are still inadequate due to limited feedstock supply and high production costs. New conversion technologies that utilize lignocellulosic feedstocks are needed to meet these challenges and satisfy the rapidly growing market. Combining bio- and chemo-catalytic approaches can leverage advantages from both methods, i.e., high product selectivity via biological conversion, and the capability to build C-C chains more efficiently via chemical catalysis. Herein, conversion routes, catalysis, and processes for such pathways are discussed, while key challenges and meaningful R&D opportunities are identified to guide future research activities in the space. Bio and chemo-catalytic conversion primarily utilize the carbohydrate fraction of lignocellulose, leaving lignin as a waste product. This makes lignin conversion to SAF critical in order to utilize whole biomass, thereby lowering overall production costs while maximizing carbon efficiencies. Thus, lignin valorization strategies are also reviewed herein with vital research areas identified, such as facile lignin depolymerization approaches, highly integrated conversion systems, novel process configurations, and catalysts for the selective cleavage of aryl C–O bonds. The potential efficiency improvements available via integrated conversion steps, such as combined biological and chemo-catalytic routes, along with the use of different parallel pathways, are identified as key to producing all components of a cost-effective, 100% SAF.

09 BIOMASS FUELS↗
DOE OSTI2023

Uncertainty quantification of a deep learning fuel property prediction model

Deep learning models are being widely used in the field of combustion. Given the black-box nature of typical neural network based models, uncertainty quantification (UQ) is critical to ensure the reliability of predictions as well as the training datasets, and for a principled quantification of noise and its various sources. Deep learning surrogate models for predicting properties of chemical compounds and mixtures have been recently shown to be promising for enabling data-driven fuel design and optimization, with the ultimate goal of improving efficiency and lowering emissions from combustion engines. In this study, UQ is performed for a multi-task deep learning model that simultaneously predicts the research octane number (RON), Motor Octane Number (MON), and Yield Sooting Index (YSI) of pure components and multicomponent blends. The deep learning model is comprised of three smaller networks: Extractor 1, Extractor 2, and Predictor, and a mixing operator. The molecular fingerprints of individual components are encoded via Extractor 1 and Extractor 2, the mixing operator generates fingerprints for mixtures/blends based on linear mixing operation, and the predictor maps the fingerprint to the target properties. Two different classes of UQ methods, Monte Carlo ensemble methods and Bayesian neural networks (BNNs), are employed for quantifying the epistemic uncertainty. Combinations of Bernoulli and Gaussian distributions with DropConnect and DropOut techniques are explored as ensemble methods. All the DropConnect, DropOut and Bayesian layers are applied to the predictor network. Aleatoric uncertainty is modeled by assuming that each data point has an independent uncertainty associated with it. The results of the UQ study are further analyzed to compare the performance of BNN and ensemble methods. Although this study is confined to UQ of fuel property prediction, the methodologies are applicable to other deep learning frameworks that are being widely used in the combustion community.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

The HydroBio Dataset: a new data resource for evaluating existing and potential hydropower capacity and freshwater biodiversity in the conterminous United States

Hydropower is a critical source of affordable and reliable electricity and energy system stability services in the United States. Opportunities to expand US hydropower production include retrofitting existing non-powered dams to produce power, retrofitting existing hydropower dams to improve efficiency or increase capacity, or constructing new hydropower infrastructure on currently unregulated river reaches. We created the HydroBio Dataset, which summarizes existing and potential hydropower capacity and freshwater biodiversity at the sub-basin scale in the conterminous US to contextualize existing and potential grid contributions with the freshwater ecosystems in which dams are situated. We demonstrate a use-case of this dataset by rescaling and comparing potential non-powered dam nominal capacity to rarity-threat-weighted freshwater species richness for sub-basins where both types of data exist. On average, normalized freshwater biodiversity exceeded normalized potential non-powered dam nominal capacity in these sub-basins. Potential non-powered dam nominal capacity was concentrated in sub-basins in the Upper Mississippi and Ohio hydrologic regions while freshwater biodiversity was concentrated in the South Atlantic-Gulf, Ohio, and Tennessee hydrologic regions. Additionally, non-powered dams and existing hydropower dams are located in sub-basins with similar indices of freshwater biodiversity. The HydroBio Dataset adds an additional ecological dimension of context to our understanding of current and potential future US hydropower capabilities and is a valuable decision support tool for stakeholders tasked with balancing gains in services to the US power grid with the public and environmental benefits of freshwater ecosystems.

Biodiversity↗
DOE OSTI2023

Concurrent reaction-bonded joining and densification of additively manufactured silicon carbide by liquid silicon infiltration

Here, in this study, additive-manufactured silicon carbide preforms were joined and densified by reaction bonding via liquid silicon infiltration. The silicon carbide preforms were first printed by binder jetting additive manufacturing. To demonstrate concurrent joining and densification, two preforms with carbon or parchment papers at the interface were concurrently joined and infiltrated by liquid silicon. Results showed a robust interface with thicknesses ranging from 150 to 500 µm, depending on the paper type and the number of paper layers. High-energy synchrotron X-ray revealed that β-phase silicon carbide was formed inside the interface. Finally, two additively manufactured samples with complicated channel geometry were successfully joined. Energy dispersive spectroscopy of the interface of the channeled samples showed a consistent and robust joining. This concurrent approach of joining and densification enables efficiency improvement of fabricating silicon carbide parts with complicated geometries and widens geometry freedom for additive manufacturing of silicon carbide.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Polymer informatics: Current status and critical next steps

Artificial intelligence (AI) based approaches are beginning to impact several domains of human life, science and technology. Polymer informatics is one such domain where AI and machine learning (ML) tools are being used in the efficient development, design and discovery of polymers. Surrogate models are trained on available polymer data for instant property prediction, allowing screening of promising polymer candidates with specific target property requirements. Questions regarding synthesizability, and potential (retro)synthesis steps to create a target polymer, are being explored using statistical means. Data-driven strategies to tackle unique challenges resulting from the extraordinary chemical and physical diversity of polymers at small and large scales are being explored. Other major hurdles for polymer informatics are the lack of widespread availability of curated and organized data, and approaches to create machine-readable representations that capture not just the structure of complex polymeric situations but also synthesis and processing conditions. Methods to solve inverse problems, wherein polymer recommendations are made using advanced AI algorithms that meet application targets, are being investigated. As various parts of the burgeoning polymer informatics ecosystem mature and become integrated, efficiency improvements, accelerated discoveries and increased productivity can result. Here in this paper, we review emergent components of this polymer informatics ecosystem and discuss imminent challenges and opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Design and simulation of n -type solar cells based on an iodine-doped CdTe absorber using SCAPS-1D

The performance of conventional p-type CdTe solar cells has plateaued in recent years, motivating exploration of n-type absorbers. Here, we evaluate a homojunction solar cell employing iodine-doped CdTe (CdTe:I) as the absorber in a Ti 3 C 2 T x MXene/p-CdTe:As/n-CdTe:I/indium structure through SCAPS-1D simulations and prototype devices. Optimized simulations predict efficiencies above 25% for thin CdTe:I absorbers (~0.7 μm). In contrast, the first prototype achieved only ~1.36% efficiency with V OC = 0.48 V, J SC = 6.45 mA/cm 2 and FF = 43.8%. When the simulation is adjusted to match the actual device structure, and the effective illumination is reduced to account for front-side light loss, the predicted V OC (0.48 V) and JSC (6.74 mA/cm 2 ) closely reproduce the experimental values. This suggests that the device performance is primarily limited by reduced front-side photon transmission and other material non-idealities. These results highlight the promise of iodine-doped n-type CdTe and identify clear pathways for further efficiency improvement.

14 SOLAR ENERGY↗
DOE OSTI2021

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Multicriterion benefit evaluation methodology for safety enhancements in nuclear power plants and application for FLEX strategies

Here we propose a multicriterion benefit evaluation (MCBE) methodology for evaluating costs and benefits of implementing safety enhancements in nuclear power plants. The MCBE methodology establishes a comprehensive evaluation scope using multiple evaluation criteria (including public risk, occupational risk, plant revenue, and plant cost) and multiple contexts (including plant normal operations, incidents, and accidents). The MCBE methodology formulates a benefit or cost element as the product of a monetary consequence and its occurrence-likelihood change. The MCBE methodology also incorporates a decision maker’ preferences toward occurrence likelihood and monetary consequence into cost and benefit estimations through a modified usage of cumulative prospect theory. This paper applies the MCBE methodology to the implementation of diverse and flexible coping strategy (FLEX) in a generic nuclear power plant as an illustrative example. The FLEX benefits are evaluated through three types of influence paths: plant safety enhancement, risk-informed activities, and potential additional credit of FLEX in supporting plant operation and maintenance-efficiency improvement. The benefit-to-cost ratio (BCR) of FLEX implementation is calculated. Sensitivity analyses are conducted to examine the impacts of modeling assumptions and input parameter values on the BCR.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

A non-fueled nuclear-heated rod for in-pile transient boiling studies

Separate-effects boiling experiments have recently been conducted in the Transient Reactor Test Facility at Idaho National Laboratory to investigate transient heating and irradiation effects on cladding-to-coolant heat transfer. Specifically, transient critical heat flux (CHF) remains an important area of research, and better understanding of this phenomenon has potential for improving predictive models related to operational and safety limits. Consequently, this knowledge is expected to improve efficiency of light-water reactor operations. A novel borated nuclear-heated rodlet (BNHR) was designed to enable observation of transient cladding-to-coolant heat transfer phenomena. The final BNHR design takes a surrogate approach, wherein nuclear heating is induced by 10 B(n, α) reactions rather than derived from fissions in a fueled specimen. The structure of the BNHR consists of a hollowed out borated (B nat ~ 2.05 wt %) stainless steel tube with an hourglass-shaped outer surface, capped at both ends with non-borated stainless steel. This geometry allows for inner-rodlet instrumentation and generation of the highest nuclear heating rates near the center of the rodlet to ensure onset of boiling near instrumentation for real-time observation. A novel approach to measuring the nuclear energy deposition rate in the BNHR separate and apart from the influence of the coolant, termed the n-a thermometer, is also detailed in this paper. This device has demonstrated excellent repeatability, and measurements indicate predictive modeling results for energy deposition in the BNHR rod agree within a 10% margin of the experiment measurements. In conclusion, these results give confidence that the BNHR design has successfully met experiment objectives.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Optical properties of differing nanolayered structures of divalent europium doped barium fluoride thin films synthesized by pulsed laser deposition

Optically-active thin films are employed in a variety of applications, such as LEDs and photovoltaics, due to their ability to act as up- or down-photon energy converters. Their performance depends critically on their composition and structure; thus, the use of novel synthesis techniques that allow for their control at the nanoscale level can result in improved efficiency and practicality. Here, layered thin films consisting of Eu 2+ - doped BaF 2 nanocrystalline layers separated by amorphous Al 2 O 3 were synthesized via sequential pulsed laser deposition using three separate targets for the different components; this synthesis technique provides precise control of layer thickness at the nanoscale along with dopant distribution within the film. Cross-sectional transmission electron microscopy analysis verified the desired nano-layering. Post-deposition heat treatments in a nitrogen atmosphere resulted in samples exhibiting steady emission with a broad peak ranging from 400 to 600 nm and a shoulder at 410 nm. The CIE 1931 chromaticity coordinates are x = 0.26-0.29 and y = 0.32-0.35 and vary as a function of the sample configuration. Because the chromaticity coordinates are close to those of a pure white light (x = 0.33, y = 0.33), these films demonstrate advantageous properties for applications with UV-pumped white light LEDs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Radiation-induced molecular hydrogen gas generation in the presence of aluminum alloy 1100

The United States government currently manages nearly 13 metric tons of aluminum-clad spent nuclear fuel (SNF) without a long-term storage solution, so a fundamental understanding of corrosion processes occurring on aluminum alloy surfaces is of utmost importance to plan for extended (>50 years) interim dry storage of aluminum-clad SNF. While thermal and chemical corrosion processes are well characterized for aluminum, radiation effects are not. To help understand the impacts of radiation on aluminum-clad SNF, here the radiation-induced molecular hydrogen gas (H 2 ) generation from pristine and pre-corroded aluminum alloy 1100 (Al-1100) coupons have been studied. Corrosion of coupons was achieved by submerging coupons in water at 95 °C for 29 days, yielding a ~5 μm boehmite/bayerite oxide film. Pre-corroded coupons were exposed to cobalt-60 gamma radiation to absorbed doses of up to 1.0 MGy under a variety of conditions: cover-gas composition (argon, nitrogen, or air), relative humidity (0, 50, and 100%), and temperature (ambient, 100, and 200 °C). Post-irradiation measurements demonstrated that the yield of H 2 was directly attributable to the presence of the Al-1100 coupons and their physisorbed water with dependence on absorbed gamma dose, relative humidity, and cover-gas composition. No H 2 was quantified in the presence of air, while both nitrogen and argon environments afforded higher H 2 yields with increasing relative humidities. This was attributed to the greater availability of adsorbed water for radiolytic processes. Irradiation of pre-corroded Al-1100 coupons at different temperatures under 0% relative humidity argon conditions yielded statistically equivalent H 2 yields for ambient temperatures and 100 °C. However, irradiation at 200 °C promoted a 3 to 4-fold increase in the yield of H 2 , possibly due to the transformation of bayerite to boehmite and/or improved efficiency of H • and H 2 release from oxide surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimization and Techno-Economic Comparison of Regenerators and Recuperators in sCO2 Recompression Brayton Cycles for Concentrating Solar Power Applications

Supercritical CO2 power cycles might be capable of providing the cost reductions and efficiency improvements necessary to reach concentrating solar power (CSP) cost targets, but require large, highly effective recuperators. Fixed-bed regenerators are a periodic heat exchanger that could be an effective yet low-cost alternative to these recuperators. This study presents a techno-economic comparison of regenerators and recuperators for a 100 MWe supercritical CO2 power cycle for CSP applications. We quantify the levelized cost of energy (LCOE) for the power plant with both types of heat exchangers, and explore sensitivity of LCOE to parameters such as CSP-specific capital costs, power cycle component capital costs, and regenerator valve replacements costs. Results indicate that the incumbent printed circuit heat exchangers achieve the lowest LCOE, unless the upper extreme of PCHE capital cost and lower extremes of regenerator and valve capital and O&M costs are realized. Sensitivity analysis also illustrates that the primary heat exchanger cost is the most influential of power cycle components, and that CSP component capital cost is more influential than power cycle capital costs. This illustrates the importance of reducing the cost of heliostats, receivers, and thermal energy storage for achieving CSP LCOE targets.

OTHER INSTRUMENTATION,SOLAR ENERGY↗
DOE OSTI2021

Mitigation of J–V distortion in CdTe solar cells by Ga-doping of MgZnO emitter

Distortions in the current–voltage curves of CdTe-based thin-film solar cells with MgZnO emitter layers are not uncommon. Even when such distortions are very subtle with standard sunlight, they can be greatly accentuated by the removal of short-wavelength photons with optical filters, and the dark-curve turn-on voltage can be noticeably increased. The strong suggestion is that good J–V curves with full-spectrum light often rely on photogeneration of electrons from trap states in the MgZnO emitter. When the carrier concentration of the CdTe absorber is increased with external doping, there is a corresponding need for a larger MgZnO carrier concentration. Based on the assumption that the emitter carrier concentration needs to be comparable to that of the absorber, Ga-doping of the MgZnO was shown to very nearly eliminate the large filtered-light distortions and is arguably superior to MgZnO that relies on photogeneration. In addition, it was shown that photogeneration and recovery in MgZnO is relatively slow, so that without Ga-doping, the cell efficiency improves gradually for most of an hour in the light, and the turn-on voltage of the dark curve increases on a similar time scale when the light is removed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Design, development and analysis of large-area industrial silicon solar cells featuring a full area polysilicon based passivating contact on the rear and selective passivating contacts on the front

We present SERIS’ biPoly™ technology platform on large-area (M2), n-type rear-junction silicon solar cells featuring selective poly-Si/SiOx based passivated contacts on the front side and full-area poly-Si/SiOx contacts on the rear. The selective poly-Si ‘fingers’ are formed using an industrial ink-jet masking process followed by wet-chemical etching. The metal contacts are formed by an industrial screen-printing process using high-temperature fire-though metal pastes. We obtain excellent passivation on the front and rear surfaces, resulting in iVoc values between 720 mV and 730 mV on unmetallized solar cells. After high-temperature metallization, we achieve 22% efficiency on solar cells with selective poly-Si fingers on the front. We further develop the model for biPoly™ solar cells and with the help of a detailed loss analysis and simulations, identify the various loss components to identify the device modifications required for efficiency improvements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Crack mitigation and wear performance of high-strength steel coatings deposited by high-speed laser cladding

This article investigates the fabrication of defect-free Rockit® 606, a high‑carbon, vanadium- and chromium-enriched precipitation-hardening martensitic steel coating, using high-speed laser cladding (HSLC). Compared to conventional laser cladding, HSLC offers higher deposition efficiency, improved coating quality, minimal thermal distortion, and a reduced heat-affected zone. Various HSLC parameters—including laser power, travel speed, powder feed rate, and overlap distance—were optimized to achieve superior coating properties. Microstructural analysis revealed solidification cracks in coatings deposited on carburized steel, regardless of processing parameters. However, preheating the substrate to 250 °C effectively eliminated cracking by reducing thermal gradients. The coatings exhibited a columnar dendritic microstructure, with coarser dendrites near the substrate and finer dendrites towards the surface. Hardness measurements confirmed that all coatings significantly exceeded the industry-specified threshold of 60 HRC, with preheating having minimal effect on overall hardness distribution. Reciprocating sliding wear tests demonstrated a substantial improvement in wear resistance for the defect-free HSLC coatings compared to baseline carburized steel. These findings underscore the potential of HSLC for producing high-performance, wear-resistant coatings suitable for industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Sustainable Seaweed Biotechnology Solutions for Carbon Capture, Composition, and Deconstruction

Seaweeds or macroalgae are attractive candidates for carbon capture, while also supplying a sustainable photosynthetic bioenergy feedstock, thanks to their cultivation potential in offshore marine farms. Seaweed cultivation requires minimal external nutrient requirements and allows for year-round production of biomass. Despite this potential, there remain significant challenges associated with realizing large-scale, sustainable agronomics, as well as in the development of an efficient biomass deconstruction and conversion platform to fuels and products. Recent biotechnology progress in the identification of enzymatic deconstruction pathways, tailored to complex polymers in seaweeds, opens up opportunities for more complete utilization of seaweed biomass components. Effective, scalable, and economically viable conversion processes tailored to seaweed are discussed and gaps are identified for yield and efficiency improvements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Modeling and design of III-V heterojunction solar cells for enhanced performance

Heterojunctions can increase the efficiency of solar cell devices relative to homojunctions, but there is a large parameter space with significant tradeoffs that must be considered. Here, we present an experimental and computational study of III-V heterojunction solar cells and show how the emitter doping, emitter band gap, and heteroband offsets impact device efficiency. Efficiency is maximized by pushing the junction depletion region into the wider band gap material while minimizing the effects of heteroband offsets through optimized choice of emitter band gap, emitter electron affinity, and/or emitter doping density. We use these results to guide optimization of devices grown by halide vapor phase epitaxy, achieving 27% efficiency in a GaAs/GaInPAs heterojunction device. We also show that heterojunctions yield proportionally larger efficiency improvements in lower-quality materials. Although the modeling was developed and validated using III-V materials, the results are theoretically applicable to materials systems outside III-Vs.

14 SOLAR ENERGY↗