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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Donnan potential revealed

Selective transport of solutes across a membrane is critical for many biological, water treatment and energy conversion and storage systems. When a charged membrane is equilibrated with an electrolyte, an unequal distribution of ions arises between phases, generating the so-called Donnan electrical potential at the solution/membrane interface. The Donnan potential results in the partial exclusion of co-ion, providing the basis of permselectivity. Although there are well-established ways to indirectly estimate the Donnan potential, it has been widely reported that it cannot be measured directly. Here we report the first direct measurement of the Donnan potential of an ion exchange membrane equilibrated with salt solutions. Our results highlight the dependence of the Donnan potential on external salt concentration and counter-ion valence, and show a reasonable agreement with current theoretical models of IEMs, which incorporate ion activity coefficients. By directly measuring the Donnan potential, we eliminate ambiguities that arise from limitations inherent in current models.

25 ENERGY STORAGE↗
DOE OSTI2023

Network stability of FKM rubber compounds under hydrogen pressure

Fluorocarbon-based rubber (FKM) compounds are typically utilized in the aeronautical industry due to its exceptional chemical and thermal resistance and recently has drawn significant interest from the hydrogen community for various hydrogen applications, but there exists little data evaluating its hydrogen compatibility. In this paper, a formulated FKM compound was exposed to ultrahigh hydrogen pressure (90 MPa) and analyzed by attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy and crosslinking densities by solvent swelling measurement. ATR-FTIR spectroscopic data demonstrated that high-pressure hydrogen not only caused cleavages in polymer backbone and cross linkages, but also induced additional degradation of FKM compounds by breaking intermolecular hydrogen bonding between carboxylic acids, which were produced during rubber molding and post curing processes. This hydrogen pressure-driven degradation was significantly higher towards the core of the material than at the surface due to its weaker bonding between polymers and fillers.

Polymers, hydrogen, stability, degradation, Charac↗
DOE OSTI2024

Bond length alternation of π -conjugated polymers predicted by the Fermi–Löwdin orbital self-interaction correction method

π-conjugated polymers have been used in a wide range of practical applications, partly due to their unique properties that originate in the delocalization of electrons through the polymer backbone. The level of delocalization can be characterized by the induced bond length alternation (BLA), with shorter BLA connected with strong delocalization and vice versa. The accurate description of this structural parameter can be considered a benchmark for testing the capability of different electronic structure methods for self-interaction error (SIE) removal and electron correlation inclusion. Density functional theory (DFT), in its local or semi-local flavors, suffers from SIE and, thus, underestimates the BLA compared to self-interaction-free methods. In this work, we utilize the Fermi–Löwdin orbital self-interaction correction (FLOSIC) method for one-electron self-interaction removal to characterize the BLA of five oligomers with increasing length extrapolated to the polymeric limit. We compare the self-interaction-free BLA to several DFT approximations, Møller–Plesset second-order perturbation theory (MP2), and the BLA obtained with the domain based local pair natural orbital CCSD(T) [DLPNO-CCSD(T)] approximation. Our findings show that FLOSIC corrects for the small BLA given by (semi-)local DFT approximations, but it tends to overcorrect with respect to CAM-B3LYP, MP2, and DLPNO-CCSD(T).

Chemistry↗
DOE OSTI2020

Genomic Analysis Enlightens Agaricales Lifestyle Evolution and Increasing Peroxidase Diversity

Abstract As actors of global carbon cycle, Agaricomycetes (Basidiomycota) have developed complex enzymatic machineries that allow them to decompose all plant polymers, including lignin. Among them, saprotrophic Agaricales are characterized by an unparalleled diversity of habitats and lifestyles. Comparative analysis of 52 Agaricomycetes genomes (14 of them sequenced de novo) reveals that Agaricales possess a large diversity of hydrolytic and oxidative enzymes for lignocellulose decay. Based on the gene families with the predicted highest evolutionary rates—namely cellulose-binding CBM1, glycoside hydrolase GH43, lytic polysaccharide monooxygenase AA9, class-II peroxidases, glucose–methanol–choline oxidase/dehydrogenases, laccases, and unspecific peroxygenases—we reconstructed the lifestyles of the ancestors that led to the extant lignocellulose-decomposing Agaricomycetes. The changes in the enzymatic toolkit of ancestral Agaricales are correlated with the evolution of their ability to grow not only on wood but also on leaf litter and decayed wood, with grass-litter decomposers as the most recent eco-physiological group. In this context, the above families were analyzed in detail in connection with lifestyle diversity. Peroxidases appear as a central component of the enzymatic toolkit of saprotrophic Agaricomycetes, consistent with their essential role in lignin degradation and high evolutionary rates. This includes not only expansions/losses in peroxidase genes common to other basidiomycetes but also the widespread presence in Agaricales (and Russulales) of new peroxidases types not found in wood-rotting Polyporales, and other Agaricomycetes orders. Therefore, we analyzed the peroxidase evolution in Agaricomycetes by ancestral-sequence reconstruction revealing several major evolutionary pathways and mapped the appearance of the different enzyme types in a time-calibrated species tree.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Compression Analysis of Materials via in situ X-ray Computed Tomography

X-ray computed tomography (X-ray CT) is an analytical technique used in materials science to non– destructively characterize features in a variety of materials like polymers, metals, composites, and explosives. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of material characteristics.This is more effective when combinedwith a load cell to expose the material to realworld stimuli to understand material characteristics and morphological behavior in situ. This study focused on using in situ X-ray CT to understand the material characteristics and morphological changes of sugar prills and a lattice under a compressive load. Sugar prills are used as a surrogate to analyze explosives in a safer and less expensiveway. The sugar prills were found to be brittle and shattered when compressed via the CT renderings and the stress/strain information. The lattices are used as both the basis and ground truth comparison for the development of models to predict the morphological and material characteristic changes that occur as a result of loading. The lattice was found to have weak regions due to low polymer interlayer fusion in these regions during the printing process. It was also found that under the initial compression the lattice demonstrated elastic behavior as its cellular structure was intact until the cellular structure started to collapse causing yielding in the lattice. Additionally, the analysis of the sugar prills and lattice demonstrate the information that can be gleaned from in situ X-ray CT experiments that would be lost in traditional pre- and post-mortem X-rayCT analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High Performance Ionene Architectures for Membrane Separations (Final Technical Report)

Our DOE BES research grant (DE-SC0018181, 8/15/17-2/28/22) focused on the synthesis, characterization, and performance of a new class of polymers known as high-performance (HP)-ionenes as gas separation membranes, including associated computational studies. This research resulted in 11 peer-reviewed journal publications with an additional ~7 manuscripts currently in review or under preparation for submission. This DOE BES funding has also resulted in 3 U.S. patent applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Data-Driven Tailoring Optimization of Thermoset Polymers Using Ultrasonics and Machine Learning

Thermoset polymers are highly demanded for their structural robustness, thermal stability, and chemical resistance. Tailoring the properties of these polymers for high-performance applications is often preferred to designing brand-new polymers. However, the traditional destructive techniques used to characterize their properties as a function of manufacturing parameters are expensive and time-consuming. A novel non-destructive, data-driven method leveraging ultrasonics and machine learning techniques to tailor the properties of thermosets as a function of the manufacturing parameters is demonstrated. Thermoset epoxy samples with varying curing temperatures (15–40 °C) and curing agent amounts (±40%) were manufactured and tested. Their curing kinetics were monitored by determining the sound speed in the material in real time, while the longitudinal modulus of the samples was determined post-cure. Machine learning models were developed using a k-nearest neighbors algorithm. These models were implemented to predict the curing and final elastic properties using the manufacturing parameters, i.e., stoichiometry and curing temperature, and vice versa. Understanding and modeling how these parameters affect the cure kinetics and final properties will allow for efficient and reliable optimization of thermoset tailoring and manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chlorine Validation through Critical Integral Experiments

An increased interest in the validation of chlorine nuclear data, specifically 35Cl, in recent years has led to the prioritization of conducting chlorine critical experiments for nuclear data validation and criticality safety evaluations. A previous experiment was conducted with PVC and CPVC (chlorinated polyvinyl chloride) to reduce the margin of subcriticality for PF-4 operations with aqueous plutonium chloride solutions. Challenges in determining the composition of specific polymers, namely the CPVC, made it difficult to characterize, and therefore benchmark. Additional materials that were utilizable for chlorine validation were not immediately clear, as form, strength, purity, and composition are all important. A series of possible absorber materials were identified and studied, but ultimately granular sodium chloride was chosen. In addition to the needs of LANL’s PF-4 other industry collaborators have brought attention to the need for chlorine validation. Specifically, the need for HEU electrorefining with LiCl salts at Y-12 was taken into consideration for this experiment, with the experimental configurations being finely tuned to best meet their needs. Needs for validation were also presented by Idaho National Lab (INL) and TerraPower for validation of their Molten Chloride Reactor Experiment (MCRE) and Molten Chloride Fast Reactor (MCFR) and have also been considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Influence of strain-rate on the response of elastomeric architected materials

Architected materials have shown substantial promise in impact mitigation and protective applications, and there has accordingly been great interest in better characterizing their response at elevated strain rates due to impact. There remains ambiguity regarding the contribution of inertial and material responses to strain rate sensitivity, and, in particular, when these effects begin to gain dominance in the impact response of an architected material. The response of soft polymer architected materials as a function of strain rate, in particular, has been little investigated. We characterize the experimental impact response of four soft polymer architected lattice geometries across varying strain rates in the intermediate strain rate regime (∼10 3 s −1 ) using split-Hopkinson pressure bar loading and high speed video characterization of the resulting deformation fields. In conclusion, our results highlight the interplay of influence between constituent material, lattice geometry, length scale, and strain rate in determining the onset of significant inertia effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Combinatorial Membrane Synthesis: Fundamentals of Hybrid Metal-Organic Brush (MOB) Membranes for Organic Solvent Nanofiltration (Renewal)

(a) Goals: The goals of our current 3-year research project are (i) expansion of the novel modification technique Single Electron Transfer- Living Radical Polymerization (SET-LRP) to graft polymer brushes on a polyimide stable support followed by characterization and testing of the ensuing membrane (ii) stiffen brush network utilizing (a) metal organic frameworks and (b) covalent bonds formed as a result of crosslinking the grafted brush network. (b) Approach: The approach taken for this research was: (i) to graft branches terminated with a carboxyl group on each bristle (or bristle branch) allowing (a) metal immobilization to form MOF-like structures between branches or (b) crosslink bristles using aliphatic or aromatic diamines; (ii) to test the performance of the membranes using organic dyes, pure solvents (alcohols) and industrially relevant organic solvent separations; and (iii) to characterize these modified brush membranes. (c) Findings: The significant findings from the past one year are summarized below (papers resulting from this work are listed below and in D. PUBLICATIONS and relevant references are found in E. REFERENCES.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Characterization and engineering of a two-enzyme system for plastics depolymerization

Significance Deconstruction of recalcitrant polymers, such as cellulose or chitin, is accomplished in nature by synergistic enzyme cocktails that evolved over millions of years. In these systems, soluble dimeric or oligomeric intermediates are typically released via interfacial biocatalysis, and additional enzymes often process the soluble intermediates into monomers for microbial uptake. The recent discovery of a two-enzyme system for polyethylene terephthalate (PET) deconstruction, which employs one enzyme to convert the polymer into soluble intermediates and another enzyme to produce the constituent PET monomers (MHETase), suggests that nature may be evolving similar deconstruction strategies for synthetic plastics. This study on the characterization of the MHETase enzyme and synergy of the two-enzyme PET depolymerization system may inform enzyme cocktail-based strategies for plastics upcycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Integrating Emerging Polymer Chemistries for the Advancement of Recyclable, Biodegradable, and Biocompatible Electronics

Abstract Through advances in molecular design, understanding of processing parameters, and development of non‐traditional device fabrication techniques, the field of wearable and implantable skin‐inspired devices is rapidly growing interest in the consumer market. Like previous technological advances, economic growth and efficiency is anticipated, as these devices will enable an augmented level of interaction between humans and the environment. However, the parallel growing electronic waste that is yet to be addressed has already left an adverse impact on the environment and human health. Looking forward, it is imperative to develop both human‐ and environmentally‐friendly electronics, which are contingent on emerging recyclable, biodegradable, and biocompatible polymer technologies. This review provides definitions for recyclable, biodegradable, and biocompatible polymers based on reported literature, an overview of the analytical techniques used to characterize mechanical and chemical property changes, and standard policies for real‐life applications. Then, various strategies in designing the next‐generation of polymers to be recyclable, biodegradable, or biocompatible with enhanced functionalities relative to traditional or commercial polymers are discussed. Finally, electronics that exhibit an element of recyclability, biodegradability, or biocompatibility with new molecular design are highlighted with the anticipation of integrating emerging polymer chemistries into future electronic devices.

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

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Processing behavior evolution of recycled polypropylene: An integrated experimental and Computer-Aided engineering simulation study

Polypropylene (PP) comprises 21% of global plastics production and 18% of plastics waste, yet less than 1% of solid-waste PP is recycled in the United States (U.S.), representing significant environmental and economic challenges. Mechanical recycling, the most prevalent recycling method, subject's materials to thermomechanical stresses, which typically degrade polymer properties, affecting the quality of polymer products. This study replicates the impact of mechanical recycling through multiple extrusion cycles to examine the effects on PP's processing behavior. Dynamic scanning calorimetry (DSC) measurements showed stable melting behavior across all processing conditions, while crystallization analysis exhibited consistent shifts in kinetic parameters. Rheological characterization demonstrated progressive viscosity reductions through successive cycles, particularly pronounced at elevated reprocessing temperatures. Here, the integration of this experimental data into injection molding simulations showed that recycled PP maintains viable processing characteristics. Our findings establish quantitative correlations between processing history and material behavior, enabling optimization of processing parameters directly rather than relying on trial-and-error approaches. While these results reflect idealized recycling conditions with minimal contamination, they provide a framework for understanding fundamental property evolution during mechanical recycling.

42 ENGINEERING↗
DOE OSTI2024

Structural Effects on Solubility and Crystallinity in Polyamide Ionomers

Although polyamides have been an industrial staple for decades, their solubility and processability remain limited due to the strong hydrogen bonding between amide groups. Here, we report a family of polyamides in which aryl rings, alkyl spacers, sulfonate groups, and amide linkages are regularly spaced along the polymer backbone, allowing us to probe the structural elements that affect processability. We accessed these polymers through a synthetic route based on an expanded diamine monomer and characterized them through a range of physical and spectroscopic techniques. Our results show that the combination of sulfonate groups with increased amide content results in highly soluble polymers, which can dissolve in polar solvents such as water, methanol, and N,N-dimethylformamide. Infrared spectroscopy on the solid polymers shows that the aliphatic amides engage in hydrogen bonding with the sulfonate groups, thus inhibiting ion aggregation, crystallization, and microphase separation. These findings expand the avenue to sulfonate-containing polyamide chemistry and provide design rules for the synthesis of more processable ionic polyamides.

amides↗
DOE OSTI2025

Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. Here, this work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

Constitutive modeling↗