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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reducing Ohmic Resistances in Membrane Capacitive Deionization Using Micropatterned Ion-Exchange Membranes, Ionomer Infiltrated Electrodes, and Ionomer-Coated Nylon Meshes

Membrane capacitive deionization (MCDI) is an emerging water desalination platform that is compact, electrified, and does not require high-pressure piping. Herein, highly conductive poly(phenylene alkylene) ion-exchange membranes (IEMs) are micropatterned with different surface geometries for MCDI. The micropatterned membranes increase the interfacial area with the liquid stream leading to a 700 mV reduction in cell voltage when operating at constant current (2 mA cm -2 ; 2000 ppm NaCl feed) while improving the energy normalized adsorbed salt (ENAS) value by 1.4 times. Combining the micropatterned poly(phenylene alkylene) IEMs with poly(phenylene alkylene) ionomer-filled electrodes reduces the cell voltage by 1000 mV and improves the ENAS values by 2.3 times relative to the base case. This reduction in cell voltage allows for higher current density operation (i.e., 3–4 mA cm -2 ) . The reduction in cell voltage is ascribed to the ameliorating ohmic resistances related to ion transport at the membrane-process stream interface and in the carbon cloth electrode. Finally, porous ionic conductors are implemented into the spacer channel with flat and micropatterned IEM configurations and ionomer infiltrated electrodes. For the configuration with flat IEMs, the porous ionic conductor improves ENAS values across the current density regime (2–4 mA cm -2 ), while for micropatterned IEMs it gets improved only at 4 mA cm -2 .

42 ENGINEERING↗
DOE OSTI2025

Mesh-like structure integrated core-shell-shell nanocomposites for enhanced stability and performance in carbon capture

Carbon capture is essential for mitigating climate change, yet most sorbents struggle to combine high capacity with chemical stability. Here we report core-shell-shell (CSS) nanocomposites that integrate adsorption efficiency with exceptional robustness. The design couples a metal-organic framework (MOF) core, which enriches local CO 2 concentration, with a polyamine shell that is reorganized into a porous, ordered network through entanglement with an outer covalent organic framework (COF) shell. This hierarchical architecture enables dual amine functionalization via sequential “click” and Schiff-base reactions, achieving a CO 2 uptake of 3.4 mmol g −1 at 1 bar. The COF outer layer also acts as a protective barrier, suppressing humidity interference and doubling cycling stability under simulated flue gas. Remarkably, the nanocomposites maintain structural integrity after one week in strongly acidic (3 M HNO 3 ) or basic (NaOH, pH=14) environments, underscoring their chemical resilience. By uniting high capacity, cycling durability, and environmental tolerance, this CSS strategy offers a versatile platform for next-generation carbon capture materials.

Yang, Sizhuo [Lawrence Berkeley National Laborator↗
DOE OSTI2026

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)↗