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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Modeling Ring-Opening Polymerization with Machine-Learned Committors

Many important industrial and biological processes depend on ring-opening polymerization (ROP), including large-scale production polymers, such as nylon 6, and a variety of biodegradable polymers and high-performance resins. Large-scale simulations (>200K atoms) of ROP were performed using a deep neural network-based method that captured the effect of the local chemical environment of the reactive sites using training data from quantum chemical methods. The utility of this method was demonstrated by modeling the cationic ROP of bis-benzoxazine, a promising resin for use in advanced high-temperature application composites (>200°C). Density functional theory calculations were used to map out the various ring opening and polymerization reaction paths that occur during the thermal processing of bis-benzoxazine. The probabilities of these reactions, as a function of local atomic configurations, were used to construct committor functions using a neural network approach. The learned committor functions were then used to determine when a particular reaction occurred within the REACTER framework for reactive molecular dynamics simulations. The experimentally observed exotherm that occurs during bis-benzoxazine ROP was captured in an effective manner in the simulations by imposing a local heating of the system that corresponds to the enthalpy of reaction for each reaction. The dependence of the final polymer morphology on the ROP reaction temperature was analyzed at the molecular scale. The results presented in this work indicate that machine-learned committor functions are a promising approach for incorporating high-fidelity reactivity criteria that capture the effect of local chemical environments into large-scale polymerization simulations.

machine learning, polymer simulations, molecular d↗
DOE OSTI2021

Framework for predicting the fractionation of complex liquid feeds via polymer membranes

The separation of complex liquid hydrocarbon mixtures was recently demonstrated using the glassy polymer SBAD-1, showing that small molecule fractionation is possible by such organic membrane materials. Here, in this work, we develop a framework that will enable workable predictions of permeate flux and composition in complex hydrocarbon liquids through intrinsically porous glassy polymers. The predictions are made by incorporating experimentally-derived unary sorption and diffusion parameters in a Maxwell-Stefan framework coupled with multicomponent sorption models and various distinct diffusion phenomena. Across the range of sorption and diffusion phenomena considered, both the conventional Flory-Huggins model and the proposed Langmuir + Flory-Huggins sorption model combined with a simple average guest diffusivity or a more complex free-volume theory-based transport resulted in the lowest prediction error for three chosen multicomponent separations. The proposed Maxwell-Stefan framework simply requires pure component transport parameters to allow a fast approximation of the separation of multicomponent liquid hydrocarbon feeds that can potentially be extended to more complex feeds such as crude oil fractions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Microstructure of the combustion zone: Thin-binder AP-polymer sandwiches

Experimental results are summarized for systematic quench-burning tests on ammonium perchlorate-HC binder sandwiches with binder thicknesses in the range 10 - 150 microns. Tests included three binders (polysulfide, polybutadiene-acrylonitrile, and hydroxy terminated polybutadiene), and pressures from 1.4 to 14 MPa. In addition, deflagration limits were determined in terms of binder thickness and pressure. Results are discussed in terms of a qualitative theory of sandwich burning consolidated from various sources. Some aspects of the observed results are explained only speculatively.

Price, E. W.↗
DOE OSTI2023

Manipulating Organic Semiconductor Morphology with Visible Light

A method is presented to manipulate the final morphology of roll-to-roll slot-die coated poly(3-hexylthiophene) (P3HT) by optically exciting the p-type polymer in solution while coating. These results provide a comprehensive picture of the entire knowledge chain, from demonstrating how to apply the authors’ method to a fundamental understanding of the changes in morphology and physical properties induced by exciting P3HT while coating. By combining results from density functional theory and molecular dynamics simulations with a variety of X-ray experiments, absorption spectroscopy, and THz spectroscopy, the relationship between morphology and physical properties of the thin film is demonstrated. Specifically, in P3HT films excited with light during deposition, changes in crystallinity and texture with more face-on orientation and increased out-of-plane charge mobility are observed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of Salt Aggregation in Perfluoroether Electrolytes

Electrolytes comprised of polymers mixed with salts have great potential for enabling the use of Li metal anodes in batteries for increased safety. Ionic conductivity is one of the key performance metrics of these polymer electrolytes and achieving high room-temperature conductivity remains a challenge to date. For a bottom-up design of the polymer electrolytes, we must first understand how the structure of polyelectrolytes on a molecular level determines their properties. Here, we use classical molecular dynamics to study the solvation structure and ion diffusion in electrolytes composed of a short-chain perfluoroether with LiFSI or LiTFSI salts. Density functional theory is also used to provide some insights into the structures and energies of the salt interactions with the perfluoroether. We observe the formation of aggregates of salts in the fluorinated systems even at low salt concentrations. The fluorine-fluorine attraction in the solvent is the governing factor for creating the salt aggregates. The aggregates’ size and lifetime change with concentration and anion. These simulations provide an insight into the structure and dynamics of perfluoroether based electrolytes that can be used to improve Li-ion batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

The Effect of Thin Film Adhesives on Mode I Interlaminar Fracture Toughness in Carbon Fiber Composites with Shape Memory Alloy Inserts

Shape Memory Alloy (SMA) was placed within Polymer Matrix Composite (PMC) panels alongside film adhesives to examine bonding. Double cantilever beam (DCB) testing was performed using ASTM D5528. C-scanning was performed before testing, modal acoustic emissions (MAE) were monitored during testing, and microscopy performed post-test. Data was analyzed using modified beam theory (MBT), compliance calibration (CC) and modified compliance calibration (MCC) methods. Fracture toughness for control specimens was higher than previously reported due to fiber-bridging. Specimens with SMAs and adhesives stabilized crack propagation. Results revealed SMA-bridging; a phenomenon mimicking fiber-bridging which increased the load and fracture toughness of SMA specimens.

Derek J Quade↗
DOE OSTI2026

Molecular insights into CO 2 -to-bicarbonate transformation in functionalized anion exchange ionomers for electrochemical separations

Bipolar membrane (BPM) electrochemical processes are a promising platform for carbon dioxide (CO 2 ) separations, but the molecular level thermodynamic and kinetic understanding of CO 2 -to-bicarbonate (HCO 3 − ) transformation remain poorly understood. This study employs a multiscale computational approach to systematically explore the adsorption and reactive transformation of CO 2 in five anion exchange ionomer systems. Classical molecular dynamics (MD) simulation results demonstrate that polymers with imidazolium groups significantly reduce CO 2 diffusion and enhance (OH − )–CO 2 interactions due to stronger electrostatic and π-interactions. Compared to the commonly used quaternary ammonium ionomers, imidazolium-functionalized ionomers show improved CO 2 proximity and interaction strength. Ab initio MD and density functional theory (DFT) calculations reveal that the benzyl-substituted imidazolium (IM-Ben) substantially reduces the energy barrier for HCO 3 − formation (∼72 meV lower) compared to the alkyl-substituted IM-nBu, while also mitigating imidazolium deprotonation under moderate hydration conditions. Transition state analysis shows IM-Ben forms more extensive hydrogen-bonding networks, which stabilize the transition state structure and contribute to a lower energy barrier for bicarbonate formation. These findings highlight the advantage of the adjacent benzyl moiety in enabling efficient CO 2 -to-bicarbonate transformation via hydrated hydroxide ion counterions, offering mechanistic insights and clear molecular design principles for optimizing anion exchange ionomers at bipolar membrane interfaces for electrochemical CO 2 separation applications.

Bipolar membranes, Reactive transformation of CO2,↗
NASA NTRS1985

Viscoelastic behavior and life-time predictions

Fiber reinforced plastics were considered for many structural applications in automotive, aerospace and other industries. A major concern was and remains the failure modes associated with the polymer matrix which serves to bind the fibers together and transfer the load through connections, from fiber to fiber and ply to ply. An accelerated characterization procedure for prediction of delayed failures was developed. This method utilizes time-temperature-stress-moisture superposition principles in conjunction with laminated plate theory. Because failures are inherently nonlinear, the testing and analytic modeling for both moduli and strength is based upon nonlinear viscoelastic concepts.

Dillard, D. A.↗
NASA NTRS1991

Micromechanics for ceramic matrix composites

The fiber substructuring concepts and the micromechanics equations that are embedded in the Ceramic Matrix Composite Analyzer (CEMCAN) computer code are described as well as the code itself, its current features and capabilities, and some examples to demonstrate the code's versatility. The methodology is equally applicable to metal matrix and polymer matrix composites. The prediction of ply mechanical and thermal properties agree very well with the existing models in the Integrated Composite Analyzer and the Ceramic Matrix Composite Analyzer, lending credence to the fiber substructuring approach. Fiber substructuring can capture greater local detail than conventional unit-cell-based micromechanical theories. It offers promise in simulating complex aspects of micromechanics in ceramic matrix composites.

Murthy, P. L. N.↗
DOE OSTI2024

Vapor Infiltration Synthesis of Indium Sulfide Magic Size Cluster

The energetically favorable formation of atomically precise clusters, known as magic size clusters, in the solution phase enables a precision nanoscale synthesis with exquisite uniformity. Here, we report the synthesis of magic size clusters via vapor infiltration of atomic layer deposition precursors directly in a polymer thin film. Sequential infiltration of trimethylindium vapor and hydrogen sulfide gas into poly(methyl methacrylate) leads to the formation of clusters with uniform properties consistent with a magic size cluster-In 6 S 6 (CH 3 ) 6 . While an increase in cluster size might be expected with additional sequential infiltration cycles of the reactive In and S precursors, uniform properties consistent with magic size clusters form in multiple polymers under a range of processing conditions. Ultraviolet-visible absorption spectra of In 6 S 6 (CH 3 ) 6 are largely independent of the number of sequential infiltration cycles and exhibit air stability, both of which are attributed to an energetically favorable synthetic pathway that is evaluated with density functional theory.

atomic layer deposition↗
DOE OSTI2025

Manipulation of intramolecular hydrogen bonds in conjugated pseudoladder polymer for semiconductivity and solution-processability

The conformational coplanarity and local rigidity of π-conjugated backbones are critical for the semiconducting performance of organic electronic materials. The conformational coplanarity and local rigidity of π-conjugated backbones are critical for the semiconducting performance of organic electronic materials. While fusing the aromatic system into a ladder-type structure effectively enhances these properties, it also often results in poor solution processability and hence limits their transition to device application. To address this challenge, an intramolecularly hydrogen-bonded pseudoladder polymer (HPLP) system based on alternating hydrogen bond donating benzobisimidazole (BBI) and hydrogen bond accepting benzodifuran (BDF) units, is designed and synthesized. A Boc-protected precursor of HPLP allows for feasible solution processing of the polymer into thin films. Subsequently, in situ thermal Boc-deprotection generates the HPLP polymer, in which intramolecular hydrogen bonds form between each pair of neighboring repeating units, inducing coplanarity and rigidity throughout the entire backbone. This process is accompanied by a significant red-shift of the absorption spectrum, reduced bandgap, and enhanced rigidity, as confirmed by NMR, UV-Vis, and density functional theory analyses. HPLP films exhibit a three-order-of-magnitude enhancement in charge carrier mobility compared to the Boc-protected precursor and demonstrate excellent solvent resistance in organic thin-film transistors.

Miranda, Octavio↗
DOE OSTI2022

Limiting Current Density in Single-Ion-Conducting and Conventional Block Copolymer Electrolytes

The limiting current density of a conventional polymer electrolyte (PS-PEO/LiTFSI) and a single-ion-conducting polymer electrolyte (PSLiTFSI-PEO) was measured using a new approach based on the fitted slopes of the potential obtained from lithium-polymer-lithium symmetric cells at a constant current density. The results of this method were consistent with those of an alternative framework for identifying the limiting current density taken from the literature. We found the limiting current density of the conventional electrolyte is inversely proportional to electrolyte thickness as expected from theory. The limiting current density of the single-ion-conducting electrolyte was found to be independent of thickness. There are no theories that address the dependence of the limiting current density on thickness for single-ion-conducting electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Hot piston ring/cylinder liner materials: Selection and evaluation

In current designs of the automotive (kinematic) Stirling engine, the piston rings are made of a reinforced polymer and are located below the pistons because they cannot withstand the high temperatures in the upper cylinder area. Theoretically, efficiency could be improved if hot piston rings were located near the top of the pistons. Described is a program to select piston ring and cylinder coating materials to test this theory. Candidate materials were screened, then subjected to a pin or disk friction and wear test machine. Tests were performed in hydrogen at specimen temperatures up to 760 C to simulate environmental conditions in the region of the hot piston ring reversal. Based on the results of these tests, a cobalt based alloy, Stellite 6B, was chosen for the piston rings and PS200, which consists of a metal-bonded chromium carbide matrix with dispersed solid lubricants, was chosen as the cylinder coating. Tests of a modified engine and a baseline engine showed that the hot ring reduced specific fuel consumption by up to 7 percent for some operating conditions and averaged about 3 percent for all conditions evaluated. Related applications of high-temperature coatings for shaft seals and as back-up lubricants are also described.

Sliney, Harold E.↗
DOE OSTI2021

Spatiotemporal mapping of mesoscopic liquid dynamics

The study of liquid dynamics at mesoscopic scales is still strewn with difficulty due to limitations in theory and experiment. Historically, significant attention has been given to the analysis of space-time correlation functions and their frequency-Fourier transforms at a few discrete wave numbers. The massive computing power afforded by modern high performance computing clusters and the advent of a wide-angle neutron spin-echo spectrometer, however, have unlocked a more intuitive and fruitful approach to this problem. Using molecular dynamics simulations, here we demonstrate the benefits of spatiotemporally mapping intermediate scattering functions on a dense grid of correlation times and wave numbers. Four model systems are investigated: a Lennard-Jones liquid, a coarse-grained bead-spring polymer, a molten sodium chloride, and a poly(ethylene oxide) melt. We show that the spatiotemporal mapping approach is particularly useful for elucidating the mesoscopic dynamics in these liquids, where several underlying mechanisms, such as molecular relaxations, hydrodynamic modes, and nonhydrodynamic excitations, are potentially at play. Therefore, compared to the traditional method, direct visualization of density space-time correlation functions on two-dimensional color maps permits appraisals of complicated dynamical behavior at mesoscales in a global manner. For example, the scaling relations between space and time for different types of molecular motions can be straightforwardly identified on these plots, without any model-dependent analysis. Additionally, we show how theoretical ideas regarding collective mesoscopic dynamics, such as the classical hydrodynamic theory, the convolution approximation, and a recently proposed phenomenological model, can be discussed in terms of the global features of spatiotemporal maps of intermediate scattering functions. The new perspective offered by the spatiotemporal mapping method should prove useful for the study of liquid dynamics in general.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Dynamics of Bottlebrush Polymers in Solution by Neutron Spin Echo Spectroscopy

In this work, we present dynamical and morphological studies on poly(dimethylsiloxane) (PDMS)-based bottlebrush polymers in solution. A combination of small-angle neutron scattering (SANS), pulsed field gradient nuclear magnetic resonance (PFG NMR), and neutron spin echo (NSE) spectroscopy was used to identify structural changes inherent in changing the side-chain length while keeping the backbone constant. These morphological changes are mirrored in the diffusion coefficient determined by PFG NMR, resulting in two coefficients for the elongated and one for the more spherical sample. Faster motions are tracked by NSE using the advantage of time- and length-scale resolutions with the diffusion coefficient predetermined by PFG NMR. Hereby, the sample with short side chains relaxes like wormlike micelles considering the longitudinal direction, whereas the dynamics along the radial extension shows a much stronger Q-dependence as known from any theory. The dynamical behavior within the blob region, covered with the more spherical sample, follows the predictions of Zimm as well as of Zilman and Granek (ZG).

36 MATERIALS SCIENCE↗
DOE OSTI2026

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modeling Sorption of Water and Vanadium Cations by Ion-Exchange Membranes

We develop a macroscopic model for sorption of ions and solvent by ion-exchange membranes and use it to investigate how different membranes behave when exposed to electrolytes for vanadium flow batteries. The model combines a classical expression for the Gibbs free energy of a moderately concentrated electrolyte containing several ions with a term that describes elastic swelling of a polymer membrane. Parameters describing pairwise interactions between mobile ions and fixed membrane ions were fit to published experimental data and discussed in the context of the competition for sites in ion-exchange membranes. The model provides insights into why sorption of vanadium cations by Nafion is lower than predicted by Donnan theory and why switching to an anion-exchange membrane does not dramatically reduce vanadium sorption.

Electrochemistry↗