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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Logic in Memory Emulator

Logic in Memory Emulator (LiME) is a hardware/software tool specially designed for memory system evaluation and experiment. Emerging memories display a wide range of bandwidths, latencies, and capacities, making it challenging for the computer architect to navigate the design space of potential memory configurations, and for the application developer to assess performance implications of using such memories. With the LiME framework, architectural ideas can be prototyped in great detail yet with sufficient performance to support realistic evaluation on long running applications. LiME consists of two fundamental components: 1) the hardware and OS infrastructure for the emulator, and 2) a suite of benchmark applications to assist in characterizing the performance of current and future computer architectures. Some of the applications have been collected from other open source projects. Uses: Logging, replay and analysis of an application's memory behavior Evaluate impact of emerging memory technology on application performance. Emulate complex memory interactions in whole applications orders of magnitude faster than software simulation. Emulate acceleration hardware co-located with the memory subsystem. Features: Capture and log external memory accesses to a separate off-chip memory device without affecting application execution. Memory traces include the address, length, timestamp, and optionally the data for each transaction. Captured trace data can be saved to an SD card for off-line analysis. Configure a wide range of memory latencies in sub-nanosecond increments that encompass highbandwidth and storage class memories. Specify regions of interest (ROI) in applications to reduce the amount of trace data captured for analysis. Currently supports execution on Xilinx Zynq SoC which integrates an ARM processor with FPGA logic on a single device. Applications can be run under Linux or in bare metal mode on the ARM cores.

Jain, AbhishekK↗
DOE OSTI2024

Progress in development of characterization capabilities to evaluate candidate materials for direct air capture applications

As part of U.S. national efforts to combat the detrimental effect of global climate change, the National Institute of Standards and Technology (NIST) was recently tasked to support efforts in direct air capture (DAC) of carbon dioxide research and deployment. In order to develop test procedures, materials, and documentary standards, key characterization methods relevant to DAC materials have been investigated and used to identify desirable properties for a potential Standard Reference Material (SRM). Select amine-supported materials that previously showed potential for DAC applications have been characterized using commonly available laboratory methods. Further insights into the adsorption characteristics have been gained from developing and applying more specialized characterization tools ideal for probing low concentrations of carbon dioxide. A broad suite of capabilities that examine relevant properties under appropriate conditions gives the most profound insights into a material's specific performance. We advocate for even more specialized capabilities to be developed and standardized to quantitatively monitor the interactions of CO 2 with molecular species in complex and often disordered systems to advance DAC and support carbon dioxide reduction (CDR) in general.

carbon dioxide↗
DOE OSTI2025

Advanced Alkaline Membrane H 2 /Air Fuel Cell System with Novel Technique for Air CO 2 Removal

Over the course of this project, significant progress was achieved in developing the hydroxide exchange membrane fuel cell (HEMFC) and the electrochemically-driven CO₂ separator (EDCS), with a focus on improving performance, durability, and scalability. Key milestones were met, and the technology demonstrated potential for a wide range of applications, including fuel cell vehicles, direct air capture (DAC), and life support systems.

08 HYDROGEN↗
DOE OSTI2023

Dynamic study of direct CO 2 capture from indoor air using poly(ethylenimine)-impregnated fiber sorbents

Supported amine adsorbents are promising materials for direct air capture (DAC) of CO 2 due to their high CO 2 capacity and relatively low energy requirement for regeneration. For a DAC process, it is essential to properly define operating parameters to achieve high sorbent productivity (amount of CO 2 captured per unit quantity of sorbent material over unit time). It is furthermore essential to understand the kinetic behavior of the process under the influence of various operating conditions such as the inlet air velocity, sorbent composition, and humidity to select an effective range of operating conditions to maximize sorbent productivity. Here, the dynamic behavior of a DAC process is probed using a fixed fiber sorbent contactor containing poly(ethylenimine) (PEI)-impregnated composite silica/cellulose acetate (CA) fibers. Throughout this study, experiments are conducted using both simulated air (398 ppm CO 2 balanced by N 2 ) and real indoor air (~400–500 ppm CO 2 ). The experimental behavior of the fibers using simulated air and indoor air is compared, and the influence of the inlet air velocity on the breakthrough behavior is assessed. By changing operating conditions, the impact on the fiber sorbent productivity (mmol CO 2 g fiber –1 h –1 ) is quantified to identify conditions that could favor high rates of CO 2 removal. The kinetics of steam-assisted CO 2 desorption are studied, identifying achievable desorption times. Productivities of 1.2 mmol CO 2 g fiber –1 h –1 are obtained using an inlet air velocity of 1.1 m s –1 . Performance trends show that further increasing the inlet air velocity will likely lead to even higher productivities.

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

Breakthrough Conductivity Enhancement in Deep Eutectic Solvents via Grotthuss–Type Proton Transport

There is an increasing demand for the development of ion-conducting electrolytes for energy storage systems. Much attention is directed toward deep eutectic solvents as potential candidates. In the search for highly conductive systems, the possibility of designing deep eutectic solvents with Grotthuss-type proton transport is widely overlooked. Herein, ethaline, a mixture of choline chloride and ethylene glycol is used in a 1:2 molar ratio, to induce a significant conductivity increase with the addition of water and sulfuric acid (H 2 SO 4 ). The achieved breakthrough conductivity is analyzed experimentally and simulated with ab initio molecular dynamics (AIMD). At sufficient water content, an H-bonding network is formed that leads to a significant breakthrough conductivity based on H 2 SO 4 -derived proton transfer following the long-established Grotthuss proton transport mechanism. This result is substantiated by the positive deviation from the ideal KCl line in the Walden plot. Specifically, the data series positioned above the reference line indicates a Grotthuss mechanism in action. The AIMD simulations demonstrate proton transfer between water and ethylene glycol, supported by simulation frames captured at various times.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Engineering Calcium-Bearing Mineral/Hydrogel Composites for Effective Phosphate Recovery

Effectively recovering phosphate from wastewater streams and reutilizing it as a nutrient will critically support sustainability. Here, to capture aqueous phosphate, we developed novel mineral-hydrogel composites composed of calcium alginate, calcium phosphate (CaP), and calcium silicate (CSH) (CaP + CSH/Ca-Alg). The CaP + CSH/Ca-Alg composites were synthesized by dripping a sodium alginate (Na-Alg) solution with ionic precursors into a calcium chloride bath. To change the mineral seed’s properties, we varied the calcium bath concentrations and the ionic precursor (sodium dibasic phosphate (NaH 2 PO 4 ) and/or sodium silicate (Na 2 SiO 3 )) amounts and their ratios. The added CSH in the mineral-hydrogel composites resulted in the release of calcium and silicate ions in phosphate-rich solutions, increasing the saturation ratio with respect to calcium phosphate within the mineral-hydrogel composites. The CSH addition to the mineral-hydrogel composites doubled the phosphate removal rate while requiring lesser initial amounts of Ca and P materials for synthesis. Furthermore, by incorporating both CSH and CaP mineral seeds in composites, we achieved a final concentration of 0.25 mg-P/L from an initial 6.20 mg-P/L. Moreover, the mineral-hydrogel composites can remove phosphate even under CaP undersaturated conditions. This suggests their potential to be a widely applicable and environmentally-sustainable treatment and recovery method for nutrient-rich wastewater.

42 ENGINEERING↗
DOE OSTI2026

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

The Muon g-2 Experiment at Fermilab: Precision Measurements and Nonlinear Beam Dynamics

The Muon g-2 Experiment has achieved a significant milestone by measuring the positive muon anomalous magnetic moment to an unprecedented accuracy of 0.20 ppm, paving the way to a better understanding of particle physics, including beyond-the-Standard-Model possibilities. In the experiment, muons are circulated within a storage ring, and their anomalous precession frequency — the spin precession relative to momentum — is determined from decay positron time and energy data, captured using calorimeters. In support of accurate storage ring simulations, we performed high-order calculations of the field of the experiment's high-voltage quadrupoles. We also carried out accurate, transfer map–based calculations of the storage ring's chromaticity. These calculations are essential for understanding the beam dynamics effects in the Muon g-2 storage ring.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Delivery of LiH Shell for DANCE

Material for a new LiH shell for neutron shielding has been obtained for the Detector for Advanced Neutron Capture Experiments. This is a critical component for optimizing sensitivity of neutron capture experiments performed in support of Office of Experimental Sciences mission, particularly in the case of small, rare samples.

42 ENGINEERING↗
DOE OSTI2024

Environmental life-cycle analysis of hydrogen technology pathways in the United States

Hydrogen is a zero-carbon energy carrier with potential to decarbonize industrial and transportation sectors, but its life-cycle greenhouse gas (GHG) emissions depend on its energy supply chain and carbon management measures (e.g., carbon capture and storage). Global support for clean hydrogen production and use has recently intensified. In the United States, Congress passed several laws that incentivize the production and use of renewable and low-carbon hydrogen, such as the Bipartisan Infrastructure Law (BIL) in 2021 and the Inflation Reduction Act (IRA) in 2022, which provides tax credits of up to $3/kg depending on the carbon intensity of the produced hydrogen. A comprehensive life-cycle accounting of GHG emissions associated with hydrogen production is needed to determine the carbon intensity of hydrogen throughout its value chain. In the United States, Argonne’s R&D GREET ® (Greenhouse Gases, Regulated emissions, and Energy use in Technologies) model has been widely used for hydrogen carbon intensity calculations. This paper describes the major hydrogen technology pathways considered in the United States and provides data sources and carbon intensity results for each of the hydrogen production and delivery pathways using consistent system boundaries and most recent technology performance and supply chain data.

Elgowainy, Amgad↗
DOE OSTI2022

Ionic liquids for carbon capture

This article covers cutting-edge research in ionic liquid-based materials and their impact on carbon capture. Ionic liquids boast high thermal stability, low vapor pressure, and great tunability. They can be deployed as either sorbents or supported liquid membranes for carbon capture and other gas separations. Absorption of CO 2 in ionic liquids can be achieved via physisorption or chemisorption, depending on the strength of the interaction. For physisorption, both CO 2 -anion and cation–anion interactions are important factors in dictating CO 2 solubility. For chemisorption, the reactivity with CO 2 can be tuned by the basicity of the anion while the stability of the ionic liquid can be enhanced by controlling the cation. Marrying ionicity of ionic liquids with porosity leads to novel porous ionic liquids that feature unique properties for facilitating gas transport, while interfacing ionic liquids with microporous membranes allow the ions to gate the pores for selective gas transport. Further, composite materials of ionic liquids with crystalline materials such as metal–organic frameworks offer scalable heterogeneous interfaces to promote selectivity. Future opportunities include controlling the interaction with CO 2 and its transport at the charged or electrified interface with the ionic-liquid electric double layer, as well as combining CO 2 capture and conversion with ionic liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Emerging concepts in intermediate carbon dioxide emplacement to support carbon dioxide removal

Substantial upscaling of carbon dioxide capture is possible in the coming decades but existing solutions for storage are projected to be limited in annual capacity by as much as 2–10 GtCO 2 per year until mid-century. Temporary storage of CO 2 in a solid or liquid state could prove useful for filling this gap in capacity, until more permanent and ideally lucrative CO 2 sequestration options come online. There are several concepts for reversible solid-state and chemical CO 2 storage, but their advantages and limitations have yet to be reviewed in this context. This article focuses on the physical and chemical aspects of CO 2 storage via liquid and solid chemical carriers and sorbents, and gives an overview of the energetics around their use, as well as prospects for their future development. Exciting opportunities for coupling capture and medium to high maturity multi-year storage technologies could support carbon removal in the coming decades. Highlights of the analysis are the remarkable storage capacity of oxalic acid and formic acid (CO 2 -density of 1857 kg m –3 and 1152 kg m –3 , compared with condensed liquid CO 2 at 993–1096 kg m –3 , respectively), the relative scalability and compatibility of carbonate salts for stationary storage with direct air capture, and the potential promise of multiple carriers for CO 2 transportation. Solid sorbents do not achieve such ultra-high storage capacities, but could improve storage over compressed gas tanks on a capacity and energetics basis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Predicting a Key Catalyst-Performance Descriptor for Supported Metal Nanoparticles: Metal Chemical Potential

The chemical potential of metal atoms in supported nanoparticles provides a convenient descriptor of their performance as heterogeneous catalysts that captures the effects of particle size, support and alloying. Based on microcalorimetric measurements, the chemical potential is shown in this work to be predictable as a function of monometallic particle diameter and the adhesion energy of the particle to the support, and, for oxide supports, this adhesion energy correlates predictably with metal oxophilicity. These correlations provide predictions of metal chemical potential that can enable catalyst design. They also suggest an improvement in the Gibbs-Thomson relation for free-standing nanoparticles, whether metals or molecular solids.

metal/oxide interface↗
DOE OSTI2024

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗
DOE OSTI2023

NETL's Carbon Capture Retrofit Databases

This PowerPoint presentation summarizes the recently published Carbon Capture Retrofit Databases and their supporting documents, such as user guides and studies used to inform cost and performance estimates. NETL publications used to develop slide contents include Cost of Capturing CO2 from Industrial Sources, 2022; Industrial CCRD, 2022; Eliminating the Derate of Carbon Capture Retrofits, 2023; PC CCRD, 2023; Cost and Performance of Retrofitting NGCC Units for Carbon Capture, 2023; and NGCC CCRD, 2023.

Hughes, Sydney↗
DOE OSTI2020

Regional Geologic Cross Sections for Potential Storage and Containment Zones in the MRCSP Region [plus Plates 1-6]

The regional characterization work conducted by the Geoteams during the MRCSP Phase III project period (2010 –2019) focused on the following tasks: (1) refinement of geologic seals/reservoir systems; (2) assessment of Atlantic Coastal Plain and offshore opportunities; (3) expanded assessments of oil and gas fields, particularly as they relate to enhanced recovery opportunities; (4) regional support for implementation of carbon capture utilization and storage (CCUS) in the partnership area; and (5) communication and data sharing. This report, entitled Regional Geology, has been prepared in association with (4), regional support for implementation of CCUS in the partnership area..

58 GEOSCIENCES↗
DOE OSTI2020

Air-Stable Calcium Cyanamide-Supported Ruthenium Catalyst for Ammonia Synthesis and Decomposition

Efficient ammonia synthesis and decomposition processes under mild conditions are important to meet the expanding demand in major applications of ammonia as the energy carrier and to provide feedstock for chemical industry. In this study, we report that air-stable calcium cyanamide-supported ruthenium (Ru/CaCN 2 ) works as an efficient and stable catalyst for ammonia synthesis and decomposition. Ru/CaCN 2 exhibits greater catalytic performances for both reactions than Ru/Ca 2 N electride and Ru–Cs/MgO. The kinetic analysis for ammonia synthesis suggests that Ru/CaCN 2 exhibits low apparent activation energy and high resistance to hydrogen poisoning, which has characteristics similar to the kinetic parameters of Ru-supported electride catalyst. H 2 -temperature programmed reaction and temperature programmed desorption revealed that Ru promoted the formation of CN 2 vacancies on the CaCN 2 surface which in turn capture hydrogen as H – ions during the reaction. Density functional theory calculations provide insights into how the formation of CN 2 vacancies is promoted by Ru, which leads to the decrease in the work function of the CaCN 2 surface and the hydrogen capture at the Ru-support interface. These results suggest that the high catalytic performance of Ru/CaCN 2 can be attributed to the formation of a quasi-electride structure at the Ru–CaCN 2 interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗