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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluating Cryo–TEM Reconstruction Accuracy of Self–Assembled Polymer Nanostructures

Cryogenic transmission electron microscopy (cryo–TEM) combined with single particle analysis (SPA) is an emerging imaging approach for soft materials. However, the accuracy of SPA–reconstructed nanostructures, particularly those formed by synthetic polymers, remains uncertain due to potential packing heterogeneity of the nanostructures. In this study, the combination of molecular dynamics (MD) simulations and image simulations is utilized to validate the accuracy of cryo–TEM 3D reconstructions of self–assembled polypeptoid fibril nanostructures. Using CryoSPARC software, image simulations, 2D classifications, ab initio reconstructions, and homogenous refinements are performed. By comparing the results with atomic models, the recovery of molecular details is assessed, heterogeneous structures are identified, and the influence of extraction location on the reconstructions is evaluated. In conclusion, these findings confirm the fidelity of single particle analysis in accurately resolving complex structural characteristics and heterogeneous structures, exhibiting its potential as a valuable tool for detailed structural analysis of synthetic polymers and soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Percolated Ionic Aggregate Morphologies and Decoupled Ion Transport in Precise Sulfonated Polymers Synthesized by Ring-Opening Metathesis Polymerization

Here, we describe a set of precise single-ion conducting polymers that form self-assembled percolated ionic aggregates in glassy polymer matrices and have decoupled transport of metal cations. These precise single-ion conductors (SICs), synthesized by a scalable ring-opening metathesis polymerization, consist of a polyethylene backbone with a sulfonated phenyl group pendant on every fifth carbon and are fully neutralized by a counterion X + (Li + , Na + , or Cs + ). Experimental X-ray scattering measurements and fully atomistic molecular dynamics (MD) simulations are in good agreement. The MD simulations show that the ionic groups nanophase separate from the polymer backbone to form percolating ionic aggregates. Using graph theory, we find that within the Li + - and Na + -neutralized polymers the percolated aggregates exhibit planar and ribbon-like configurations at intermediate length scales, while the percolated aggregates within the Cs + -neutralized polymers are more isotropic. Electrical impedance spectroscopy measurements show that the ionic conductivities exhibit Arrhenius behavior, with conductivities of 10 –7 to 10 –6 S/cm at 180 °C. In the MD simulations, the cations move between sulfonate groups in the percolated aggregates, larger ions travel further, and overall cations travel further than the polymer backbones, indicating a decoupled ion-transport mechanism. Thus, the percolated ionic aggregates in these polymers can serve as pathways to facilitate decoupled ion motion through a glassy polymer matrix.

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

Machine learning prediction of glass transition temperature of conjugated polymers from chemical structure

Predicting the glass transition temperature (T g ) is of critical importance as it governs the thermomechanical performance of conjugated polymers (CPs). Here, we report a predictive modeling framework to predict T g of CPs through the integration of machine learning (ML), molecular dynamics (MD) simulations, and experiments. With 154 T g data collected, an ML model is developed by taking simplified “geometry” of six chemical building blocks as molecular features, where side-chain fraction, isolated rings, fused rings, and bridged rings features are identified as the dominant ones for T g . MD simulations further unravel the fundamental roles of those chemical building blocks in dynamical heterogeneity and local mobility of CPs at a molecular level. The developed ML model is demonstrated for its capability of predicting T g of several new high-performance solar cell materials to a good approximation. The established predictive framework facilitates the design and prediction of T g of complex CPs, paving the way for addressing device stability issues that have hampered the field from developing stable organic electronics.

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

How Topological Polymer Loops on the Nanoparticle Surface Control the Mechanical Properties of Nanocomposites

Carbon black (CB) and silica (SiO 2 ) filled elastomers are known to be the most successful polymer nanocomposites (PNCs) in industry, where “bound rubber (BR)” (i.e., polymer chains that are physically or chemically adsorbed on the nanofiller surface) plays a critical role in their reinforcement. Here, we report a molecular-scale mechanism underlying the “BR-induced reinforcement” by integrating neutron scattering experiments and molecular dynamics simulations. Simplified non-cross-linked SiO 2 -filled polybutadiene (PB) and CB-filled PB reveal the critical role of topological polymer loops in the BR for the enhanced mechanical performance. The average loop size on the SiO 2 surface modified with a silane coupling agent is much smaller than that on the CB surface and the loops on the SiO 2 surface are densely formed, preventing interdigitation with the matrix chains. On the other hand, the larger, uncrowded loops formed on the CB surface facilitate the interdigitation with the matrix polymer chains even near the filler surface. In this way, a strong connectivity is established between a matrix and a nanofiller, resulting in an adhesive filler–polymer interface. Furthermore, our findings shed light on rich and complex physics and materials design problems in PNCs, where the topological polymer structure on the nanofiller surface directly controls the macroscopic mechanical properties.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Research and test facilities

A description is given of each of the following Langley research and test facilities: 0.3-Meter Transonic Cryogenic Tunnel, 7-by 10-Foot High Speed Tunnel, 8-Foot Transonic Pressure Tunnel, 13-Inch Magnetic Suspension & Balance System, 14-by 22-Foot Subsonic Tunnel, 16-Foot Transonic Tunnel, 16-by 24-Inch Water Tunnel, 20-Foot Vertical Spin Tunnel, 30-by 60-Foot Wind Tunnel, Advanced Civil Transport Simulator (ACTS), Advanced Technology Research Laboratory, Aerospace Controls Research Laboratory (ACRL), Aerothermal Loads Complex, Aircraft Landing Dynamics Facility (ALDF), Avionics Integration Research Laboratory, Basic Aerodynamics Research Tunnel (BART), Compact Range Test Facility, Differential Maneuvering Simulator (DMS), Enhanced/Synthetic Vision & Spatial Displays Laboratory, Experimental Test Range (ETR) Flight Research Facility, General Aviation Simulator (GAS), High Intensity Radiated Fields Facility, Human Engineering Methods Laboratory, Hypersonic Facilities Complex, Impact Dynamics Research Facility, Jet Noise Laboratory & Anechoic Jet Facility, Light Alloy Laboratory, Low Frequency Antenna Test Facility, Low Turbulence Pressure Tunnel, Mechanics of Metals Laboratory, National Transonic Facility (NTF), NDE Research Laboratory, Polymers & Composites Laboratory, Pyrotechnic Test Facility, Quiet Flow Facility, Robotics Facilities, Scientific Visualization System, Scramjet Test Complex, Space Materials Research Laboratory, Space Simulation & Environmental Test Complex, Structural Dynamics Research Laboratory, Structural Dynamics Test Beds, Structures & Materials Research Laboratory, Supersonic Low Disturbance Pilot Tunnel, Thermal Acoustic Fatigue Apparatus (TAFA), Transonic Dynamics Tunnel (TDT), Transport Systems Research Vehicle, Unitary Plan Wind Tunnel, and the Visual Motion Simulator (VMS).

Source record↗
DOE OSTI2021

Ultrahigh thermal conductivity in three-dimensional covalent organic frameworks

Covalent organic frameworks (COFs) are a new, growing class of crystalline polymers with exceptional characteristics such as low density, mechanical strength, and flexibility. Taking three-dimensional (3D) COF-300 derivatives as an example, we apply molecular dynamics simulations to show that ultrahigh thermal conductivity (>15 W/(mK)) is achieved at a pore size of d = 0.63 nm. This is the first observation of such an outstanding intrinsic thermal conductivity of a 3D polymer in all directions. Further temperature-dependent thermal conductivity calculations and X-ray diffraction (XRD) patterns highlight the importance of maintaining microscopic order for a large thermal conductivity. We also demonstrate that the tunability and anisotropy in COFs provide sufficient room to engineer and obtain desired thermal conductivity. These findings provide a fundamental understanding of structure-thermal conductivity relation in COFs and shine a light on high-thermal-conductivity COFs for thermal management applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

All-Atom Modeling and Simulation of Biopolymer Interface: Dual Role of Antifouling Polymer Brushes

Antifouling polymer brushes are well-known for their exceptional resistance to unwanted protein adsorption. While experimental studies have extensively characterized protein–polymer brush interactions, computational investigations remain limited, largely due to the challenges in accurately modeling and integrating these complex, multicomponent systems without resorting to oversimplification. To address this challenge, this study presents one of the most comprehensive and realistic model systems to date, comprising the substrate, grafted polymers, and proteins. Our work interprets the interactions between polymer brush and protein based on realistic modeling without simplification. In particular, this study utilizes molecular modeling and simulation of polycationic and polyzwitterionic brushes─poly(dimethylaminoethyl methacrylate) (PDMAEMA), poly(2-(N-oxide-N,N-dimethylamino)ethyl methacrylate) (PNOMA), and poly(2-(N-3-sulfopropyl-N,N-dimethylammonium)ethyl methacrylate) (PSBMA)─grafted onto α-quartz substrates via polymerization initiator linkers. The brush models were developed to closely replicate experimentally synthesized samples and to provide detailed insights into structural and dynamical changes at the molecular level during protein adsorption. Using steered molecular dynamics simulations, we show that the PSBMA brush, due to its high local density, exhibits the greatest resistance to protein insertion. Cα root-mean-square deviation and interaction pattern analyses further reveal that the PSBMA brush also induces the most significant destabilization of lysozyme, while the PDMAEMA brush enhances protein stability through ion-mediated interactions. The PNOMA brush, while requiring the lowest force for protein adsorption, induces greater protein destabilization than the PDMAEMA brush, primarily due to electrostatic repulsion caused by a short carbon spacer length. Hydration analysis reveals that both the PSBMA brush and the lysozyme interacting with it exhibit the most rapid dehydration, attributed to the brush’s high local chain density, which results in the greatest lysozyme destabilization and the highest adsorption force. These findings highlight the dual role of antifouling polymer brushes: resisting protein adsorption and modulating protein structural dynamics. In conclusion, this study provides valuable insights for the rational design of next-generation antifouling materials and offers a framework for realistic model development in complex multicomponent systems.

Adsorption↗
DOE OSTI2023

Charge Concentration Limits the Hydrogen Evolution Rate in Organic Nanoparticle Photocatalysts

Colloidal organic nanoparticles have proven to be a promising class of photocatalyst for performing the Hydrogen Evolution Reaction (HER) due to their dispersibility in aqueous environments, their strong absorption within the visible region, and the tunabilty of their component materials' redox potentials. Currently, there is little understanding of how charge generation and accumulation in organic semiconductors change when these materials are formed into nanoparticles that share a high interfacial area with water, nor is it known what mechanism limits the hydrogen evolution efficiency in recent reports on organic nanoparticle photocatalysts. Herein, we use Time-Resolved Microwave Conductivity to study aqueous-soluble organic nanoparticles and bulk thin films composed of various blend ratios of the non-fullerene acceptor EH-IDTBR and conjugated polymer PTB7-Th and examine the relationship between composition, interfacial surface area, charge carrier dynamics, and photocatalytic activity. We quantitatively measure the rate of Hydrogen Evolution Reaction by nanoparticles composed of various donor:acceptor blend ratio compositions and find that the most active blend ratio displays a Hydrogen Quantum Yield of 0.83% per photon. Moreover, we find that nanoparticle photocatalytic activity corresponds directly to charge generation, and that nanoparticles have 3x more long-lived accumulated charges relative to bulk samples of the same material composition. Here these results suggest that, under our current reaction conditions, with approximately 3x solar flux, catalytic activity by these nanoparticles is limited by the concentration of electrons and holes in operando and not a finite number of active surface cites or the catalytic rate at the interface. This provides a clear design goal for the next generation of efficient photocatalytic nanoparticles.

08 HYDROGEN↗
NASA NTRS1986

Development of composite facets for the surface of a space-based solar dynamic concentrator

An account is given of the composite fabrication techniques envisioned for the production of mirror-quality substrates furnishing the specular reflectance required for the NASA Space Station's solar dynamic concentrator energy system. The candidate materials were graphite fiber-reinforced glass, aluminum, and polymer matrices whose surfaces would be coated with thin metal layers and with atomic oxygen degradation-inhibiting protective coatings to obtain the desired mirror surface. Graphite-epoxy mirror substrate samples have been found to perform satisfactorily for the required concentrator lifetime.

Ayers, Schuyler R.↗
NASA NTRS2007

NASA Tech Briefs, July 2007

Topics covered include: Miniature Intelligent Sensor Module; "Smart" Sensor Module; Portable Apparatus for Electrochemical Sensing of Ethylene; Increasing Linear Dynamic Range of a CMOS Image Sensor; Flight Qualified Micro Sun Sensor; Norbornene-Based Polymer Electrolytes for Lithium Cells; Making Single-Source Precursors of Ternary Semiconductors; Water-Free Proton-Conducting Membranes for Fuel Cells; Mo/Ti Diffusion Bonding for Making Thermoelectric Devices; Photodetectors on Coronagraph Mask for Pointing Control; High-Energy-Density, Low-Temperature Li/CFx Primary Cells; G4-FETs as Universal and Programmable Logic Gates; Fabrication of Buried Nanochannels From Nanowire Patterns; Diamond Smoothing Tools; Infrared Imaging System for Studying Brain Function; Rarefying Spectra of Whispering-Gallery-Mode Resonators; Large-Area Permanent-Magnet ECR Plasma Source; Slot-Antenna/Permanent-Magnet Device for Generating Plasma; Fiber-Optic Strain Gauge With High Resolution And Update Rate; Broadband Achromatic Telecentric Lens; Temperature-Corrected Model of Turbulence in Hot Jet Flows; Enhanced Elliptic Grid Generation; Automated Knowledge Discovery From Simulators; Electro-Optical Modulator Bias Control Using Bipolar Pulses; Generative Representations for Automated Design of Robots; Mars-Approach Navigation Using In Situ Orbiters; Efficient Optimization of Low-Thrust Spacecraft Trajectories; Cylindrical Asymmetrical Capacitors for Use in Outer Space; Protecting Against Faults in JPL Spacecraft; Algorithm Optimally Allocates Actuation of a Spacecraft; and Radar Interferometer for Topographic Mapping of Glaciers and Ice Sheets.

Source record↗
DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗
NASA NTRS2019

Materials and Processes for New Propulsion Systems with Reduced Environmental Impact

Aeronautics research at NASA Glenn Research Center includes development, characterization and modeling of high temperature, lightweight materials and fabrication processes for aircraft propulsion systems with increased efficiency and reduced emissions, fuel burn and noise. Current propulsion materials research includes Ceramic Matrix Composites and Environmental Barrier Coatings, Polymer Matrix Composites and Additive Manufacturing processes. This presentation will summarize recent progress and plans in these areas. Ceramic Matrix Composites for Turbine Components: As part of NASA's Aeronautics research, Glenn Research Center has developed Ceramic Matrix Composites for 2700 degrees Fahrenheit turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development of advanced fiber and matrix constituents that enabled this advancement will be reviewed, and characterization of the resulting improvements in mechanical properties and durability will be summarized. Progress toward the development and validation of models predicting the effects of the engine environment on durability of Ceramic Matrix Composites and Environmental Barrier Coatings will be summarized. Progress and plans for collaborative research with industry and other government agencies will be reviewed. Polymer Matrix Composites for Powertrain and Impact Protection: A lightweight, hybrid polymer matrix composite/steel gear concept for rotorcraft power transmission applications was evaluated at realistic speed, torque, and power conditions. Dynamic testing was performed at 5000 horsepower and 5400 revolutions per minute with no performance degradation. Test results demonstrated the potential of hybrid composite / metal gears to reduce gear weight by approximately 15 percent, enabling the implementation of multi-speed drive systems, which would otherwise have a weight penalty, for increased speed and efficiency. Results of post-test inspection and endurance tests will be presented. Separately, ballistic impact tests demonstrated improved damage tolerance in polymer matrix composites by incorporating lightweight, thermoplastic veil materials between selected composite plies during the composite fabrication process. Results of impact tests and post-test inspection will be presented. Additive Manufacturing for Electric Propulsion: Additive Manufacturing processes offer the potential to fabricate new, high power density electric motor designs with complex geometries, multi-material components and optimally designed components that would not be feasible with traditional manufacturing processes. High performance stator components using advanced 3-phase conductive coils were fabricated using direct printing with optimized silver pastes. Additional additive manufacturing methods are being used to fabricate rotors and motor housing components. Systems studies show that the higher performance and lower weight motors offer improved energy efficiency and reduced emissions. Improvements to motor performance resulting from optimized materials and component designs will be presented.

Additive Manufacturing↗
NASA NTRS1976

Space shuttle prototype check valve development

Contaminant-resistant seal designs and a dynamically stable prototype check valve for the orbital maneuvering and reaction control helium pressurization systems of the space shuttle were developed. Polymer and carbide seal models were designed and tested. Perfluoroelastomers compatible with N2O4 and N2H4 types were evaluated and compared with Teflon in flat and captive seal models. Low load sealing and contamination resistance tests demonstrated cutter seal superiority over polymer seals. Ceramic and carbide materials were evaluated for N2O4 service using exposure to RFNA as a worst case screen; chemically vapor deposited tungsten carbide was shown to be impervious to the acid after 6 months immersion. A unique carbide shell poppet/cutter seat check valve was designed and tested to demonstrate low cracking pressure ( 2.0 psid), dynamic stability under all test bench flow conditions, contamination resistance (0.001 inch CRES wires cut with 1.5 pound seat load) and long life of 100,000 cycles (leakage 1.0 scc/hr helium from 0.1 to 400 psig).

Tellier, G. F.↗
DOE OSTI2022

Mechanical joint performances of friction self-piercing riveted carbon fiber reinforced polymer and AZ31B Mg alloy

Carbon fiber reinforced polymer (CFRP) and AZ31B Mg alloy were joined by the friction self-piercing riveting (F-SPR) with different steel rivet shank sizes. With the increase of rivet shank size, lap shear fracture load and mechanical interlock distance increased. Ultrafine grains were formed at the joint in AZ31B as a result of dynamic recrystallization, which contributed to the higher hardness. Fatigue life of the CFRP-AZ31B joint was studied at various peak loads of 0.5, 1, 2, and 3 kN and compared with the resistance spot welded AZ31B-AZ31B from the open literature. The fatigue performance was better at higher peak load (>2 kN) and comparable to that of resistance spot welding of AZ31B to AZ31B at lower peak loads (<1 kN). From fractography, the crack initiation for lower peak load (<1 kN) case was observed at the fretting positions on the top and bottom surfaces of AZ31B sheet. When peak load was increased, fretting between the rivet and the top of AZ31B became more dominant to initiate a crack during fatigue testing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rheological Properties of Small-Molecular Liquids at High Shear Strain Rates

Molecular-scale understanding of rheological properties of small-molecular liquids and polymers is critical to optimizing their performance in practical applications such as lubrication and hydraulic fracking. We combine nonequilibrium molecular dynamics simulations with two unsupervised machine learning methods: principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE), to extract the correlation between the rheological properties and molecular structure of squalane sheared at high strain rates (10 6 –10 10 s -1 ) for which substantial shear thinning is observed under pressures P ϵ 0.1–955 MPa at 293 K. Intramolecular atom pair orientation tensors of 435 × 6 dimensions and the intermolecular atom pair orientation tensors of 61 × 6 dimensions are reduced and visualized using PCA and t-SNE to assess the changes in the orientation order during the shear thinning of squalane. Dimension reduction of intramolecular orientation tensors at low pressures P = 0.1,100 MPa reveals a strong correlation between changes in strain rate and the orientation of the side-backbone atom pairs, end-backbone atom pairs, short backbone-backbone atom pairs, and long backbone-backbone atom pairs associated with a squalane molecule. At high pressures P ≥ 400 MPa, the orientation tensors are better classified by these different pair types rather than strain rate, signaling an overall limited evolution of intramolecular orientation with changes in strain rate. Dimension reduction also finds no clear evidence of the link between shear thinning at high pressures and changes in the intermolecular orientation. The alignment of squalane molecules is found to be saturated over the entire range of rates during which squalane exhibits substantial shear thinning at high pressures.

36 MATERIALS SCIENCE↗