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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Copper Dendrites and Surface Engineering for Enhanced CO2 Reduction Research Report Paper

The electrocatalytic reduction of CO 2 (CO 2 R) into hydrocarbon fuels, such as ethylene and ethanol, provides an attractive pathway towards closing the industrial carbon cycle and producing chemicals using renewable electricity. Existing CO 2 R technologies can exhibit C 2+ product selectivity above 74% and operating current densities over 1.3 A/cm 2 , but none can achieve both simultaneously, limiting the commercial viability and scalability of this technology. Low CO 2 concentrations at the catalyst surface and competing side reactions such as the hydrogen evolution reaction (HER) inhibit C 2+ faradaic efficiencies and operational current densities. Additionally, the use of high surface area cathode geometries to increase operational current densities is under-investigated. In this work, we electrodeposit a macroporous copper dendrite film to form high surface area cathodes. These structures are then coated with a combination of hydrophobic/hydrophilic ionomers to achieve high electrochemically active surface areas (ECSA), form regions of intrinsic porosity, and maximize catalytic availability of CO 2 . Using these techniques, we hope to maximize C 2+ faradaic efficiencies (FE) and geometric partial current densities. The treated cathode compound macrostructure (~10μm-sized pores, and ~μm-long dendrites) and concomitant surface area allows increased geometric current densities while the ionomer coating simultaneously inhibits HER and increases hydrogen availability to improve C 2+ selectivity. Our results show that careful engineering of the catalyst-electrolyte interface can enhance CO 2 reduction product selectivity and efficiency.

10 SYNTHETIC FUELS↗
DOE OSTI2020

Sr 1-x Ca x Fe 1-y Co y O 3-δ as facile and tunable oxygen sorbents for chemical looping air separation

Abstract Chemical looping air separation (CLAS) is a promising technology for oxygen generation with high efficiency. The key challenge for CLAS is to design robust oxygen sorbents with suitable redox properties and fast redox kinetics. In this work, perovskite-structured Sr 1-x Ca x Fe 1-y Co y O 3 oxygen sorbents were investigated and demonstrated for oxygen production with tunable redox properties, high redox rate, and excellent thermal/steam stability. Cobalt doping at B site was found to be highly effective, 33% improvement in oxygen productivity was observed at 500 °C. Moreover, it stabilizes the perovskite structure and prevents phase segregation under pressure swing conditions in the presence of steam. Scalable synthesis of Sr 0.8 Ca 0.2 Fe 0.4 Co 0.6 O 3 oxygen sorbents was carried out through solid state reaction, co-precipitation, and sol-gel methods. Both co-precipitation and sol-gel methods are capable of producing Sr 0.8 Ca 0.2 Fe 0.4 Co 0.6 O 3 sorbents with satisfactory phase purity, high oxygen capacity, and fast redox kinetics. Large scale evaluation of Sr 0.8 Ca 0.2 Fe 0.4 Co 0.6 O 3 , using an automated CLAS testbed with over 300 g sorbent loading, further demonstrated the effectiveness of the oxygen sorbent to produce 95% pure O 2 with a satisfactory productivity of 0.04 g O2 g sorbent −1 h −1 at 600 °C.

25 ENERGY STORAGE↗
DOE OSTI2021

Scalable fabrication of high activity nanoporous copper powders for electrochemical CO 2 reduction via ball milling and dealloying

Electrochemical CO 2 reduction (ECR) is a promising technology to close the anthropic CO 2 circle using renewable energy to achieve carbon neutrality. Future commercialization of ECR will require the development of new catalyst synthesis routes that will allow significant upscaling of catalyst production from current research-level milligram quantities to the kilogram scale and beyond while maintaining the activity and selectivity demonstrated at the research level. Here, we report on generating and testing submicron-sized nanoporous copper (npCu) particles by using a scalable approach consisting of ball milling brittle Cu-based intermetallics followed by dealloying to add nanoporosity for high surface area. The resulting npCu particles have been tested in an industry-relevant large area (25 cm 2 ) electrolyzer platform and showed Faraday efficiencies (FE) for ethylene up to 34 % at current densities of 75–100 mA/cm 2 while keeping FE for hydrogen less than 30 %. Our results demonstrate that a combination of ball milling and dealloying is a promising approach to generate large quantities of high activity and high surface area npCu particles for ECR at an industry-relevant scale.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Reaction Optimization for Enzymatic Deconstruction of Industrially Relevant Nylon Composites

Plastics such as polyamides (PAs) possess unique physicochemical properties that make them indispensable in modern society. However, their energy‐intensive production and challenging end‐of‐life management highlight the urgent need for efficient recycling or remanufacturing solutions. Enzymatic depolymerization offers a promising route toward circular recycling, yet remains constrained by limited enzyme characterization, lack of validation under industrially relevant conditions and substrates, and overall performance. Here, we optimized the reaction conditions for three recently discovered nylon‐degrading enzymes. One of them, Nyl12, achieved product titers with PA6 and PA66 that exceed previously reported values, without enzyme engineering or substrate pretreatment. We further demonstrated the scalability of the process and its application to complex PA‐based materials used in microelectronic components. Analysis of substrate features, including surface area and particle size, revealed key parameters governing enzymatic activity and provided a framework for future pretreatment and process optimization efforts. In combination, these efforts provide a new benchmark for enzymatic nylon recycling.

nylon↗
DOE OSTI2022

GronOR: Scalable and Accelerated Nonorthogonal Configuration Interaction for Molecular Fragment Wave Functions

GronOR is a program package for nonorthogonal configuration interaction calculations. Electronic wave functions are constructed in terms of antisymmetrized products of multiconfiguration molecular fragment wave functions. The computational complexity of the nonorthogonal methodologies implemented in GronOR applied to large molecular assemblies requires a design that takes full advantage of massively parallel supercomputer architectures and accelerator technologies. This work describes the implementation strategy and resulting performance characteristics. In addition to parallelization and acceleration, the software development strategy includes aspects of fault resiliency and heterogeneous computing. The program was designed for large-scale supercomputers but also runs effectively on small clusters and workstations for small molecular systems. GronOR is available as open source to the scientific community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Introduction to Special Section: Machine Learning for Image-based Geologic Interpretation

Image-based geological interpretation has been a labor-intensive and time-consuming process because it requires well-trained geoscientists to identify geological structures, features, and textures from various types of images. These images include scanning electron microscopic images, optical microscopic images, optical photos, resistivity images, seismic volumes, remote-sensing images, etc. With fast-evolving machine learning (ML) technology and computing power in recent decades, computers can achieve nearhuman-level to super-human-level performance with scalable high efficiency in the computer vision field. These technological revolutions facilitated image-based geological interpretation in petroleum exploration and production. For example, a fault picking method applied to 3-D seismic volume data using deep learning can achieve superior performance in comparison to conventional auto-picking methods. In addition, under the new normal of low oil prices, the petroleum industry seeks cost-effective strategies such as automating traditionally labor-intensive processes. Nevertheless, the potential of applying ML to geological image interpretation is still facing a few key challenges including data scarcity, data distribution, poor data and/or label quality, data leakage, learning algorithms, model architecture, training methodologies, testing and evaluation metrics, hyper-parameters optimization, model drift, production deployment, and the like.

58 GEOSCIENCES↗
DOE OSTI2024

Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform

The goal of the Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform project is to derisk the manufacturing scalability for a high chip count heterogeneous smart lighting platform, with the potential to enable significant energy savings through dynamic directional light control and custom. Specifically, the project derisks the scalability of a disruptive new computer controlled microassembly fabrication process SRI International is developing, to address fundamental cost barriers to mass production of high chip count systems. This is key for enabling mass adoption and thus maximum societal energy savings impact. The LED light sheet technology is a smart illumination platform that can be applied to lighting, signage, and display. It has features and a form factor similar to bendable or conformal OLED light sheets but uses more efficient LEDs with a remote phosphor layer that is very close to the LED to deliver a luminous efficacy that exceeds 125 lumen/Watt and enable > 50% Lighting Application Efficiency (LAE) energy savings. During Budget Period 1 (BP1), all of the BP1 milestones were successfully completed: (M2.0.1) Design demonstrator details that will meet the final project goals, (M6.1.1) Show lighting output model can predict illuminance, spatial, spectral distribution for specific light-sheet designs and use case, (M3.2.1) Automated loading supports 200 chip arrays, and (M3.3.1) Finish first interconnect process run for 200 chip array. The BP1 Go/No-Go Decision Point (G/NG 1) 200 chip demonstrator sample was in the process of final assembly and test at the end of BP1 on December 31, 2023. The objective was successfully achieved on January 16, 2024, when a wired 200-chip sample underwent confirmation testing that demonstrated a 93.75% first pass electrical yield that successfully exceeded the 75% first-pass electrical yield BP1 G/NG requirement. In addition, all 93.75% of the sample devices lit up, further demonstrating the ability to assemble and transfer small LED chips without damaging their functionality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Methane Mitigator – Development of a Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry (Final Technical Report)

Researchers at West Virginia University completed a multi-year project under DE-FE0031865 entitled “Methane Mitigator – Development of a Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry”. An assessment of natural gas production site emission sources was completed to quantify the potential for emissions reductions and reductions in fuel consumption. The main sources of fugitive methane emissions at gas productions sites include condensate tanks, produced water tanks, gas compressor packing vents, pneumatic controller vents, and natural gas engine crankcase vents.

03 NATURAL GAS↗
DOE OSTI2025

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Engineering-Scale Validation of Novel Algae CO 2 Capture and Bioproducts Technology

The purpose of this project was to advance and scale the algae-based technology Helios-NRG has been developing for capture of CO 2 from the flue gas of coal-burning power plants with conversion of the CO 2 to high-value products. In order to encourage the process becoming commercial and be adoptable, it is essential that the cost of CO 2 be close to net zero or slightly revenue positive. Two methods to achieve this are reducing the cost of operations through efficiencies and selling of products derived from conversion. Helios and the project team partners have accomplished the goals of furthering the technology to be more scalable and substantially lower cost with a defined pathway for commercialization.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

A Novel Sustainable Process for Multilayer Graphene Synthesis Using CO 2 from Ambient Air

Graphene produced by different methods can present varying physicochemical properties and quality, resulting in a wide range of applications. The implementation of a novel method to synthesize graphene requires characterizations to determine the relevant physicochemical and functional properties for its tailored application. We present a novel method for multilayer graphene synthesis using atmospheric carbon dioxide with characterization. Synthesis begins with carbon dioxide sequestered from air by monoethanolamine dissolution and released into an enclosed vessel. Magnesium is ignited in the presence of the concentrated carbon dioxide, resulting in the formation of graphene flakes. These flakes are separated and enhanced by washing with hydrochloric acid and exfoliation by ammonium sulfate, which is then cycled through a tumble blender and filtrated. Raman spectroscopic characterization, FTIR spectroscopic characterization, XPS spectroscopic characterization, SEM imaging, and TEM imaging indicated that the graphene has fifteen layers with some remnant oxygen-possessing and nitrogen-possessing functional groups. The multilayer graphene flake possessed particle sizes ranging from 2 µm to 80 µm in diameter. BET analysis measured the surface area of the multilayer graphene particles as 330 m 2 /g, and the pore size distribution indicated about 51% of the pores as having diameters from 0.8 nm to 5 nm. This study demonstrates a novel and scalable method to synthesize multilayer graphene using CO 2 from ambient air at 1 g/kWh electricity, potentially allowing for multilayer graphene production by the ton. The approach creates opportunities to synthesize multilayer graphene particles with defined properties through a careful control of the synthesis parameters for tailored applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Webinar: Modular Nuclear Power: The Microreactor Revolution

Many times smaller than traditional nuclear reactors, microreactors can be made in a factory and shipped wherever needed. This innovative approach to energy production has huge potential to bring electricity to remote areas, support regions affected by natural disasters, and provide right-sized, scalable power to our energy grid. Learn what they are, how they work, and their benefits in this webinar, featuring Piyush Sabharwall, distinguished staff nuclear research scientist and technical area lead for the DOE Office of Nuclear Energy's Microreactor R&D Program at Idaho National Laboratory.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Semi‐Continuous Ex Situ Carbon Dioxide Mineralization in Produced Water for Calcite Production

ABSTRACT The mineralization of carbon dioxide (CO 2 ) to stable carbonate products is a desirable process for carbon capture utilization and storage (CCUS). However, improving the process economics through creative use of available reactants is necessary to develop a scalable mineralization process. This study details the development of a semi‐continuous CO 2 mineralization process that uses flue gas as a point CO 2 source, produced water (PW) as an alkaline source of Ca 2+ , and NaOH effluent (potentially sourced from integration with the chlor‐alkali process. Operating at a controlled pH allowed for both complete reaction of available Ca 2+ (100% carbonation potential or 9.9 g CO 2 .L –1 PW brine) and for reproducible control of the produced calcium carbonate (CaCO 3 ) product. A full factorial design of experiments was implemented to study the effects of reaction temperature, pH, and gaseous CO 2 concentration on the mineralization and CO 2 capture rates as well as product crystalline structure and morphology. A maximum CO 2 capture rate of 0.315 ± 0.007 kg.L –1 .d –1 was achieved at 25°C and 25% CO 2 . CO 2 gas to liquid phase mass transport is believed to be the rate limiting step. With improved reactor design and optimization, the proposed semi‐continuous mineralization process shows promise for scaling to a pilot scale CO 2 capture technology.

Bennett, Quinn [Institute for Sustainable Energy &↗
DOE OSTI2024

Synergistic Thermo-Microbial-Electrochemical (T-MEC) Approach for Drop-In Fuel Production from Wet Waste

This project successfully developed and demonstrated the synergistic thermo-microbial-electrochemical (T-MEC) process, converting food waste into sustainable biofuels while achieving self-sustaining wastewater treatment and hydrogen production. By integrating hydrothermal liquefaction (HTL) and microbial electrolysis cells (MECs), the project advanced waste-to-fuel technology and expanded the understanding of sustainable waste valorization. It established a scalable framework for achieving high carbon efficiency, effective pollutant removal, and energy recovery, showcasing the potential of combining biological, thermal, and electrochemical systems to optimize resource recovery and reduce environmental impacts. The project demonstrated the technical effectiveness of the T-MEC process, achieving over 50% improvement in carbon efficiency and reducing waste processing costs by more than 25% compared to anaerobic digestion (AD). The HTL pilot reactor processed food waste at 90 kg/h, producing up to 200 L/day of biocrude oil with high conversion efficiency. A critical desalting step in pretreatment prevented catalyst fouling, enabling efficient hydrotreating with 100% deoxygenation and denitrogenation and sulfur reduction to <15 ppm. This positioned the kerosene fraction as a strong candidate for sustainable aviation fuel (SAF). The MECs achieved rapid startup, 86.4% COD removal, and hydrogen production rates of 1.8 L H 2 /L cat /day, among the highest recorded for pilot-scale systems. The integrated process achieved 65% carbon efficiency to biocrude and 58% to finished fuels, outperforming AD's 41% and 33% efficiencies for biogas and natural gas vehicle fuels. System analysis highlighted economic potential, with minimum fuel selling prices (MFSP) decreasing from $\$$25/GGE at 5 tpd to $\$$10/GGE at 500 tpd due to economies of scale. Future work will focus on reducing MEC material and membrane costs, enhancing performance through higher current densities, and creating tailored operational strategies for diverse feedstocks. Optimization of the integrated system will improve scalability and feasibility, positioning the T-MEC process as a competitive solution for converting wet waste into sustainable fuels and clean water. Beyond its technical and economic achievements, the project offers significant public benefits. The T-MEC process provides a sustainable alternative to landfilling and incineration, reducing greenhouse gas emissions and conserving resources. Converting waste into SAF and renewable fuels supports decarbonization in the transportation sector, advancing energy independence and reducing reliance on fossil fuels. Additionally, the process minimizes environmental pollutants, transforming them into valuable products like hydrogen and fuels, contributing to a cleaner and more sustainable future.

09 BIOMASS FUELS↗
DOE OSTI2022

Understanding slurry formulations to guide solution-processing of solid electrolytes

Scalable processing of thin solid electrolytes is crucial for engineering solid-state batteries with practical energy densities. To leverage existing battery production infrastructure, pathways for solution processing of solid electrolyte films must be investigated. Here, roll-to-roll compatible film preparation of aluminum-doped lithium lanthanum zirconate oxide was studied. Four slurry configurations accounting for different solvent properties and solid loadings were evaluated to investigate the ternary interactions within the dispersions. Rheological and coating stability analyses were carried out on the processed slurries. The analysis and characterization indicated that improved component interactions within the ethanol/toluene system result in homogenized distribution of the particles, binder, and plasticizer, and enable the extraction of free-standing thin films with thicknesses of 20 μm and large area (>15 in. 2 ). The drawbacks and opportunities of several protocols for high temperature sintering of the dried green films were investigated. This study highlights the importance of engineering dispersions during the development of processing protocols for solid electrolytes and provides guidelines for the best practices that can be leveraged for solution processing–based fabrications for a wide range of solid electrolyte materials.

25 ENERGY STORAGE↗
DOE OSTI2021

TBAA20: Task-Based Algorithms and Applications

The new challenges posed by Exascale system architectures have resulted in difficulty achieving a desired scalability using traditional distributed ­memory runtimes. Task­-based programming models show promise in addressing these challenges, providing application developers with a productive and performant approach to programming on next generation systems. Empirical studies show that task-based models can overcome load ­balancing issues that are inherent to traditional distributed ­memory runtimes, and that task-­based runtimes perform comparably to those systems when balanced. This panel is designed to explore the advantages of task-­based programming models on modern and future HPC systems from an industry, university, and national lab perspective. It aims at gathering application experts and proponents of these models to present concrete and practical examples of using task­-based runtimes to overcome the challenges posed by Exascale system architectures. This report describes the objectives, activities, and outcomes of the panel TBAA: Task­-Based Algorithms and Applications which was held at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 20) on November 18, 2020.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Dashboard for Marine Energy Site Assessment and Monitoring

The marine energy (ME) industry presently relies upon fragmented site assessment solutions that require high resource expenditure for deployment at each site and do not leverage the wealth of readily available tools and information. A wave energy resource assessment dashboard, currently in development, will substantially improve siting, permitting, operations, and maintenance of ME projects by providing an integrated solution that is a one-stop-shop for a developer’s needs. The Site Energy Assessment and MOnitoring Dashboard (SEAMOD) will be of commercial interest to anyone seeking to deploy an ME project and is easily expandable to include tidal and wind energy site assessments. The integrated dashboard is being developed using state-of-the-art database and cloud computing methods and data-assimilative modeling tools that can be coupled with low-cost, rapidly deployable wave buoys and environmental sensing hardware. The combined software and hardware dashboard will reduce wave energy site characterization and wave climate monitoring costs by more than 60 percent and provide assessments that meet international industry standards. To realize a thriving global ME industry, the physical environment at a potential deployment site must be understood, not only for resource characterization, but also for optimization of device and power conversion performance. SEAMOD directly addresses these needs with a commercially marketable product. SEAMOD is a low-cost solution that provides comprehensive ME resource assessments, baseline environmental monitoring, and offshore characterizations required for successful ME development. The key technical objectives for Phase I were a series of software development goals, which when implemented with monitoring solutions, produced an initial proof-of-concept low-cost wave energy resources dashboard. In Phase II, the development of the prototype SEAMOD continued. The basic framework employed was the development of a revised dashboard and monitoring tool customized for ME applications by focusing on IEC site assessment and method requirements. Development was focused on the integration of full hindcast metocean products to provide hindcast resource characterization and environmental information. The final integrated dashboard provides a low-cost solution that delivers comprehensive, scalable, industry-standard energy resource assessments and offshore characterizations required for successful ME development. The integrated dashboard offers visibility of the most recent site modeling, measurements, and historical data. The application and integration of consensus-based standards for wave energy resource assessment, as determined by the International Electrotechnical Commission (IEC), are crucial for the impact and value of SEAMOD. SEAMOD includes monthly, seasonal, and yearly statistics, as well as the total 30-year record, offering temporal resolution of the IEC parameters to aid potential developers in determining the available wave energy resources in their area of interest.

16 TIDAL AND WAVE POWER↗