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Results for “Polyimide Composites”

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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23 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Molecular-Level Insights into the Influence of Ionic Liquids on the Structure and Dynamics of Neutral and Charged Polyimides

We use all-atom molecular dynamics simulations to investigate how increasing ionic functionalization influences polyimide (PI) behavior in ionic liquid (IL) solvation environments. Here, we examine three polymer systems with varying charge densities: a neutral polyimide [N−PI] containing imidazole rings and progressively introduce charge through quaternization to create singly [C−PI] + and doubly charged [C−2PI] 2+ variants across a wide range of IL concentration (0−90 wt %). Through comprehensive structural, mechanical, and electrostatic analyses, we reveal that polymer charge density plays a central role in shaping IL organization and interaction with the polymer matrix. At low IL content, charged systems exhibit strong electrostatic complexation, leading to chain compaction, localized ESP environments, and elevated dielectric constants. As IL concentration increases, the effect of the different polymer charge states becomes less significant. Notably, an intermediate composition regime at approximately 50 wt % IL is associated with changes in IL-rich domain connectivity and overall system behavior across all three PI systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Collection, release, and detection of analytes with polymer composite sampling materials

A unique fiber core sampler composition, related systems, and techniques for designing, making, and using the same are described. The sampler is used to interface with existing field instrumentation, such as Ion Mobility Spectrometer (IMS) equipment. Desired sampler characteristics include its: stiffness/flexibility; thermal mass and conductivity; specific heat; trace substance collection/release dependability, sensitivity and repeatability; thickness; reusability; durability; stability for thermal cleaning; and the like. In one form the sampler has a glass fiber core with a thickness less than 0.3 millimeter that is coated with a polymer including one or more of: polymeric organofluorine, polyimide, polyamide, PolyBenzlmidazole (PBI), PolyDiMethylSiloxane (PDMS), sulfonated tetrafluoroethylene (PFSA) and Poly(2,6-diphenyl-p-phenylene Oxide) (PPPO). Multiple polymer coatings with the same or different polymer types may be included, core/substrate surface functionalization utilized, and/or the core/substrate may be at partially filled with thermally conductive particles.

Addleman, Raymond S.↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Dielectric properties of neutron and proton irradiated polymeric nanocomposite insulation for superconducting magnets of fusion power plants

Studies on radiation-resistant electrical insulation for superconducting magnets of nuclear fusion power plants are discussed. Metal oxide nanoparticle-incorporated organic polymer composite (MONAP) insulation films were manufactured and studied for their dielectric breakdown strength after exposure to neutrons and proton radiation at varying levels. Samples with up to 5 wt% of nanoparticles (NPs) of SiO 2 , MgO, and ZrO 2 were studied. The samples were exposed to radiation of up to 2 × 10 16 neutrons/cm 2 and 200 Mrad of protons. The addition of the nanoparticles improved the radiation resistance of the MONAP, and the performance depended on the type of NPs and the radiation exposure. Dielectric breakdown measurements at 77 K showed little degradation. Enhancement of dielectric strength was observed in some instances.

36 MATERIALS SCIENCE↗