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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Understanding the Design Space of Sparse/Dense Multiphase Dataflows for Mapping Graph Neural Networks on Spatial Accelerators

Graph Neural Networks (GNNs) have garnered a lot of recent interest because of their success in learning representations from graph-structured data across several critical applications in cloud and HPC. Owing to their unique compute and memory characteristics that come from an interplay between dense and sparse phases of computations, the emergence of reconfigurable dataflow (aka spatial) accelerators offers promise for acceleration by mapping optimized dataflows (i.e., computation order and parallelism) for both phases. The goal of this work is to characterize and understand the design-space of dataflow choices for running GNNs on spatial accelerators in order for the compilers to optimize the dataflow based on the workload. Specifically, we propose a taxonomy to describe all possible choices for mapping the dense and sparse phases of GNNs spatially and temporally over a spatial accelerator, capturing both the intra-phase dataflow and the inter-phase (pipelined) dataflow. Using this taxonomy, we do deep-dives into the cost and benefits of several dataflows and perform case studies on implications of hardware parameters for dataflows and value of flexibility to support pipelined execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Solid Amine CO2 Adsorbent Degradation: Insights from Experiments and Atomistic Simulations

Direct air capture (DAC) has received significant attention this decade as a viable solution to limit global warming, although large-scale deployment is currently not economically feasible. To reach the ambitious cost target set by the U.S. of $100/ton CO2 captured and stored, significant improvements must be made to sorbent lifetime and capacity. Aminosilanes grafted onto silica supports are promising candidates for deployment in DAC systems due to their relatively high oxidative stability and low regeneration temperature. Despite myriad advancements in the field, there still exists a fundamental knowledge gap relating sorbent structure to performance. In this work, we grafted various aminosilanes onto the highly porous silica SBA-15 and characterized both oxidative stability and CO2 capacity. Material properties systematically investigated included amine moiety (primary vs. secondary), silane group structure, number of linkages to the silica support, and co-addition of impregnated amines (e.g., PEI), among others. A fixed bed system was used to execute accelerated degradation studies in the presence of humidity and varying temperatures to simulate realistic operating conditions. Atomistic simulations were combined with the experimental results to gain mechanistic insight, ultimately informing the design of next-generation materials

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Novel polyoxometalate based Catalytic Materials for Proton Exchange Membrane fuel cells

This research project will focus on the design and fabrication of cost-effective catalytic materials and substrates suitable for polymer-electrolyte membrane-based fuel cells. Our emphasis centers on the utilization of carbon-based substrates, where covalently binding catalysts offer enhancements in catalytic efficiency, including improved reactant absorption and enhanced charge-transfer interactions

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Method for Rapid Modeling of Distortion in Laser Powder Bed Fusion Metal Additive Manufacturing Parts

The simulation and modeling of part-level distortion and residual stress in diverse metal additive manufacturing (AM) geometries has great potential to enable the rapid adoption of this technology in engineering design. Moreover, the use of additive manufacturing component libraries (CLs) offer a computationally efficient means of quantifying these part-level defects resultant from AM processing. We report on how the individual simulations of simple shapes, potential entries in a CL, can be superimposed to provide an indication of distortion and residual stresses in complex geometries. Laser powder bed fusion AM was used to construct test geometries of varied shapes and their combinations in the form of CLs in an effort to characterize location-dependent and feature-dependent distortion distributions. Blue light scanning was used to experimentally measure 3D distortions in order to investigate the interaction between the component shapes and local boundary conditions. Overall, part-level distortions were highly dependent on test component geometry, local boundary conditions, and shape combination. Commercial finite element software was used to verify experimental trends and to make predictions of distortion. The use of CLs resulted in over 20 times savings in computational cost while reproducing overall trends in distortion for test geometry assemblies. Therefore, it is anticipated that the use of CLs for L-PBF AM geometries has demonstrated potential to facilitate efficient simulations of full component AM assemblies, thereby reducing the need for costly trial-and-error-type experimental analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ultrafast Correlation Energy Estimator

A virtually no-cost method is proposed that can compute the correlation energies of general, covalently bonded, organic, and inorganic molecules (including conjugated π-electron systems) with a well-defined dominant Lewis structure at the accuracy of 99.5% of the near-exact values determined by the coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] in the complete-basis-set (CBS) limit. This Correlation Energy Per Bond (CEPB) method assigns a partial correlation energy to each bond type (characterized by the identities of the two atoms forming the bond and its integer bond order) and to a lone pair, regardless of the bond length, bond angle, sp-hybridization, π-electron conjugation, ionicity, noncovalent interactions, etc. At its current stage, the method is mainly suitable for near-equilibrium geometries. The correlation energies per bond are determined by a fit to the CCSD(T)/CBS benchmarks. It can neither improve the equilibrium structures nor discern conformers or positional isomers, yet its accuracy for reaction energies rivals that of the second-order Møller–Plesset perturbation theory, which is far more expensive. Its promising performance underscores the possibility that surprisingly compact, chemically intuitive molecular fragments exist into which correlation energies can be partitioned, leading to various ultrafast correlation-energy estimators tailored to different purposes.

Binding energy↗
DOE OSTI2025

Functional Design of Peptide Materials Based on Supramolecular Cohesion

Peptide materials offer a broad platform to design biomimetic soft matter, and filamentous networks that emulate those in extracellular matrices and the cytoskeleton are among the important targets. Given the vast sequence space, a combination of computational approaches and readily accessible experimental techniques is required to design peptide materials efficiently. Here, we report here on a strategy that utilizes this combination to predict supramolecular cohesion within filaments of peptide amphiphiles, a property recently linked to supramolecular dynamics and consequently bioactivity. Using established coarse-grained simulations on 10,000 randomly generated peptide sequences, we identified 3500 likely to self-assemble in water into nanoscale filaments. Atomistic simulations of small clusters were used to further analyze this subset of sequences and identify mathematical descriptors that are predictive of intermolecular cohesion, which was the main purpose of this work. We arbitrarily selected a small cohort of these sequences for chemical synthesis and verified their fiber morphology. With further characterization, we were able to link the latent heat associated with fiber to micelle transitions, an indicator of cohesion and potential supramolecular dynamicity within the filaments, to calculated hydrogen bond densities in the simulation clusters. Based on validation from in situ synchrotron X-ray scattering and differential scanning calorimetry, we conclude that the phase transitions can be easily observed by very simple polarized light microscopy experiments. We are encouraged by the methodology explored here as a relatively low-cost and fast way to design potential functions of peptide materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Vertical GaN Superjunction Diode on Sapphire with Kilovolt Dynamic Breakdown Voltage

The development of superjunction structures for use in vertical wide bandgap power devices promise to break the 1-D material limits. Additionally, the possibility of utilizing heteroepitaxial GaN-on-Sapphire wafer for vertical devices can significantly trim the material and device cost. This work introduces a quasi-vertical GaN-on-Sapphire superjunction PN diode design utilizing sputtered p-NiO on the etched GaN fins for superjunction formation. DC breakdown voltage is shown to vary with superjunction charge imbalance and significantly exceed the expected 1-D planar limit of 350V given the epilayer design used. A maximum breakdown voltage of 840 V is extracted for near charge balance conditions limited by leakage current. Dynamic breakdown of the device is characterized as a function of reverse voltage slew rate. A maximum dynamic breakdown voltage of 1160 V under a reverse voltage slew rate of 2000 V/μs is found.

Porter, Matthew↗
DOE OSTI2022

Mass transfer coefficients, kL, and air-CO2 ingassing rates in 3.4 m2 and 1-acre raceway ponds.

The US DOE 2016 Billion Ton Update (Langholtz 2016) projected that CO2 in flue-gas from power plants or similar sources would limit U.S. algal biofuel potential to under 5 billion gallons gasoline equivalent (gge) per year, due to lack of sufficient land, water and other requirements near such flue gas sources. 2nd generation carbon capture technologies are proposed to overcome this constraint (Davis 2017), and could expand this resource potential nearly 10-fold, assuming CO2 costs near the future, 2025 DOE NETL, goal of $40/metric ton CO2. An alternative pathway is the direct uptake of air CO2 into the algal ponds through an increase in the air-CO2 transfer rate resulting from the reaction of CO2 with hydroxide ions. However, such a ‘chemical enhancement’ in mass transfer depends on a high pH in the culture, and, by extension, the ability of microalgae to maintain high rates of carbon assimilation under such conditions. Abiotic experiments characterized the air-CO2 mass-transfer rate in 1-acre and 3.4 m2 raceway ponds as a function of pH, with rates approaching 10 g C/m2-day at pH 12 in the brackish water tested, equivalent to a biomass productivity potential of near 20 g AFDW/m2-day (@ 0.47 g C/g AFDW). The mass transfer rate was found to be nearly independent of the mass-transfer coefficient, indicating that at turbulence levels achievable in typical raceway ponds, the system is reaction rate, rather than diffusion limited. In biotic trials with an unknown green microalga, biomass productivity in ponds receiving CO2 from only direct surface air-CO2 exchange averaged 5 +/- 0.5 g AFDW/m2-day in August - September central California conditions, about half-that of experimental controls fertilized with supplemental CO2. pH in the air-only treatment reached a maximum of 10.5, supporting a model predicted air-CO2 ingassing rate between 2-3 g C/m2-day, consistent with the observed biomass carbon assimilation rate. Results suggest that unique alkaliphilic strains are required if reliant on direct in-pond air-CO2 transfer for algal inorganic carbon supply, and that reaching an economically viable biomass productivity will require strains that thrive at pH 11 and above.

09 BIOMASS FUELS↗
DOE OSTI2025

Hydropower Biological Evaluation Toolset (HBET) Version 3.0: User Guide

The Hydropower Biological Evaluation Tools (HBET) software package, developed by Pacific Northwest National Laboratory (PNNL), is designed to assemble, organize, and process data collected by Sensor Fish and live fish. HBET enable users to characterize the hydraulic conditions of hydropower structures and estimate fish injury and mortality rates from various stressors. Future updates of the software may support other technologies, such as bead tracking in physical models and computational fluid dynamics. The HBET program can be customized to analyze different hydraulic applications, including turbines, spillways, weirs, pumped storage, and other user-defined functions, and therefore, help researchers, turbine designers, hydropower operators, and regulators better evaluate hydropower structures regarding their environmental sustainability and cost-effectiveness. Added content to the user guide about the new feature for predicting absolute injury rates.

13 HYDRO ENERGY↗
DOE OSTI2021

A review of functions, attributes, properties and measurements for the quality control of proton exchange membrane fuel cell components

Quality control (QC) is an essential part of fuel cell technology industrialization, providing means to reduce cost of components, enhancing the reliability of the final product, and offering specification guidance for new entrants in the supply chain. The membrane electrode assembly (MEA), including membrane, catalyst layer (CL), and gas diffusion layer (GDL), as well as bipolar plate (BP), are key components of a proton exchange membrane (PEM) fuel cell, and the attributes of each component strongly correlate with the cell performance and longevity. To ensure the quality of the fuel cell, it is of great importance to characterize the properties with respect to the standardization of component/sub-component specifications. In collaboration with the fuel cell industry, this work aims at establishing compendiums of attributes, or so-called books of attributes, of key fuel cell components for the QC of PEM fuel cells through reviewing, identifying, categorizing, and prioritizing the main attributes/properties that determine their functionalities. The books of attributes for the major PEM fuel cell components include catalyst coated membrane (CCM) as a sub-assembly, GDL, and BP. To address the full spectrum of fuel cell components, gaskets and sub-gaskets are also included.

25 ENERGY STORAGE↗
DOE OSTI2022

Molten salt electrolysis and room temperature ionic liquid electrochemical processes for refining rare earth metals: Environmental and economic performance comparison

Circularizing end of life products such as electronic waste can open a new source for rare earth elements (REEs) that will decrease the demand pressure on conventional virgin production. The last step to produce REEs consists of a refining process to convert rare earth oxide (REO) to REE metal. One promising technology is processing REO via a room temperature ionic liquid, which is characterized by low energy requirements in contrast to existing REEs extraction processes. In this work, life cycle and techno-economic assessments are performed and compared against molten salt electrolysis. Here, the results show that both processes have advantages and disadvantages in terms of environmental performance, and that they are similarly competitive in terms of economic performance. A breakeven analysis suggests that future research should focus on coupling the production of REOs with the refining processes to attempt to lower REO cost and make them economically feasible in the U.S.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗
DOE OSTI2024

An approach to combine neutron and ion irradiation data to accelerate material qualification for nuclear reactors

Next-generation nuclear power plants are generally characterized by higher operating temperatures, increased neutron fluences and energies, and distinct corrosive coolant environments versus the existing light water reactor fleet. Whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. Because microstructure has a large impact on bulk material properties, limited neutron irradiation data at lower damage levels can in principle be combined with accelerated ion testing results and modeling and simulation to form an accurate prediction of microstructure evolution and select properties under different neutron irradiation conditions and at higher damage levels. The objective of this work is to present a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame. A brief review of the regulatory landscape for materials in nuclear environments is presented, followed by additional overviews to understand the current state of the art for correlation of materials properties across radiation environments using experimental and computational methodologies. Finally, the roles of academia, national laboratories, and industry in the advancement of this accelerated materials qualification framework are discussed as a path forward, with possible case studies presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

La–Sr–Co oxide catalysts for oxygen evolution reaction in anion exchange membrane water electrolyzer: The role of electrode fabrication on performance and durability

Anion exchange membrane water electrolysis is an attractive technology for low-cost generation of “green” hydrogen by combining the use of noble metal-free catalysts with pure water feed. By thus addressing main drawbacks of the liquid alkaline electrolysis and proton exchange membrane water electrolysis, anion exchange membrane water electrolysis stands an excellent chance of replacing the two technologies. The development of active and stable platinum group metal (PGM)-free catalysts for oxygen evolution reaction (OER) is crucial for making anion exchange membrane water electrolyzers (AEMWEs) practical. For this work, we synthesized, characterized and tested two La–Sr–Co oxide-based OER catalysts. First, we characterized the catalysts by XRD, SEM, and N 2 physisorption and assessed their OER activity in a three-electrode cell. Next, we focused on electrode fabrication, demonstrating the importance of catalyst-ink application to the porous transport layers (PTLs) and a key role of adding a binder to the catalyst ink to prevent the catalyst detachment from the PTL in pure water. We tested three membrane electrode assemblies prepared using different formulations of the anode catalyst ink. The results show that the optimum ink formulation is essential for the performance on pure-water feed by maximizing OH - conductivity of the catalyst layer and catalyst-membrane interface.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Investigating the Effects of Copper Impurity Deposition on the Structure and Electrochemical Behavior of Hydrogen Evolution Electrocatalyst Materials

Electrolysis of impure water (such as seawater) has recently garnered research interest as it may enable hydrogen production at reduced costs. However, the tendency of impurity ions and other species to degrade electrocatalysts and membranes within an electrolyzer is a serious challenge. Here, we investigate the effects of copper impurities of varying concentrations on the hydrogen evolution reaction (HER) using platinum electrocatalysts. A decrease of current density is observed with an increasing copper concentration. By comparing the effect of ionic impurities on current density at different concentrations, we gain insight into how impurities can interfere with the HER at different potentials. Surface characterization of the electrodes reveals differences in the morphology and extent of copper deposition on HER-active platinum vs inactive gold electrodes. This enables an improved understanding of how copper nucleates and grows on the two types of electrodes under different electrochemical conditions while also confirming deposition in low-concentration cases, as present in seawater. The results indicate that copper electrodeposition competes with the HER, and the nature of copper electrodeposition varies depending on the electrocatalytic activity of the electrode. This study provides insight toward catalyst design that can withstand the effects of impurity-induced degradation over extended use.

08 HYDROGEN↗
DOE OSTI2023

Critical Contribution of Imbalanced Charge Loss to Performance Deterioration of Si-Based Lithium-Ion Cells during Calendar Aging

Increasing the energy density of lithium-ion batteries, and thereby reducing costs, is a major target for industry and academic research. One of the best opportunities is to replace the traditional graphite anode with a high-capacity anode material, such as silicon. However, Si-based lithium-ion batteries have been widely reported to suffer from a limited calendar life for automobile applications. Heretofore, there lacks a fundamental understanding of calendar aging for rationally developing mitigation strategies. Both open-circuit voltage and voltage-hold aging protocols were utilized to characterize the aging behavior of Si-based cells. Particularly, a high-precision leakage current measurement was applied to quantitatively measure the rate of parasitic reactions at the electrode/electrolyte interface. The rate of parasitic reactions at the Si anode was found 5 times and 15 times faster than those of LiNi 0.8 Mn 0.1 Co 0.1 O 2 and LiFePO 4 cathodes, respectively. Here, the imbalanced charge loss from parasitic reactions plays a critical role in exacerbating performance deterioration. In addition, a linear relationship between capacity loss and charge consumption from parasitic reactions provides fundamental support to assess calendar life through voltage-hold tests. These new findings imply that longer calendar life can be achieved by suppressing parasitic reactions at the Si anode to balance charge consumption during calendar aging.

25 ENERGY STORAGE↗
DOE OSTI2022

Fabrication of Polymer Membrane-Suspended Microstructures on Printed Circuit Boards

When microelectromechanical systems are manufactured in high densities, the necessary routing layer structures can become complex and thus expensive if executed in silicon technology. If, additionally, the microstructures are also to be fabricated suspended on membranes, complex thinning processes become necessary to form these often rather fragile membranes. Here, a novel fabrication concept is demonstrated that allows for the fabrication of membrane-suspended microstructures using standard microfabrication techniques directly integrated with printed circuit boards (PCB) by laminating polyimide (PI) films over cavities in the PCB. This results in cost-effective routing layer fabrication and direct compatibility with common electronic component standards such as SMT (surface-mount technology) and THT (through-hole technology). To illustrate the capabilities of the fabrication process, we fabricated an array of membrane suspended microheaters. Individual platinum microheater elements are suspended on PI membranes that are 25 μm thick and 500 μm in diameter. The fabricated PCB carries a 10x10 array of suspended microheaters on an area of 26,mm x 26,mm. Here, the characterization of the microheater array shows that a yield of 86% functional microheaters was achieved. An individual microheater shows an almost linear heating characteristic at least up to 200°C demonstrating the viability of the technique for creating functional membrane-suspended microstructures on a PCB. [2021-0226]

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A Multi-Objective Bayesian Optimized Human Assessed Multi-Target Generated Spectral Recommender System for Rapid Pareto Discoveries of Material Properties

Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.

Biswas, Arpan↗