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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cell-Free Gene Expression: Methods and Applications

Cell-free gene expression (CFE) systems empower synthetic biologists to build biological molecules and processes outside of living intact cells. The foundational principle is that precise, complex biomolecular transformations can be conducted in purified enzyme or crude cell lysate systems. This concept circumvents mechanisms that have evolved to facilitate species survival, bypasses limitations on molecular transport across the cell wall, and provides a significant departure from traditional, cell-based processes that rely on microscopic cellular “reactors.” In addition, cell-free systems are inherently distributable through freeze-drying, which allows simple distribution before rehydration at the point-of-use. Furthermore, as cell-free systems are nonliving, they provide built-in safeguards for biocontainment without the constraints attendant on genetically modified organisms. These features have led to a significant increase in the development and use of CFE systems over the past two decades. Here, we discuss recent advances in CFE systems and highlight how they are transforming efforts to build cells, control genetic networks, and manufacture biobased products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Geochemical and Microstructural Characterization of Shale Rock: A Workflow for Site Evaluation for Energy–Fluids Storage

Shales are a central component of petroleum systems, as source, seal, and unconventional reservoir rocks. Unlike traditional unconventional shale, a newly emerging Caney Shale play is regarded as an unconventional of unconventional shales (UUS), due to its high content of fine-grained materials, lower reservoir porosity, dominance of nanopores, and a scarcity of visible natural fractures. Other developed unconventional shales such as the Woodford and Barnett have larger average pore size, higher porosity, and extensive natural fractures at core scale that contribute to reservoir quality. In this work, the Caney Shale was cored in entirety to characterize its interbedded ductile and reservoir intervals and establish criteria for their recognition. Representative ductile and reservoir intervals known as D2 and R3, respectively, were selected for detailed analysis including variations in elemental composition, mineralogy, facies, and the presence of natural fractures at well and core scales using X-ray fluorescence, X-ray diffraction, and thin section and core description. Characteristics of microstructure and microgeochemistry at nano- and microscales are compared using field emission scanning electron microscopy with energy dispersive spectroscopy and lowpressure nitrogen adsorption isotherms with fractal dimension analysis. The ductile (detrital clay-rich) member D2 is characterized by higher concentrations of Ti and Al and lower Si, while the reservoir R3 (possibly biogenic silica-accumulated) is characterized by lower Ti and Al and higher Si. Eight mixed carbonate–siliciclastic facies are recognized, and R3 shows a higher heterogeneity of facies stacking and average fracture abundance than D2. Further, R3 shows a more microscopically heterogeneous fabric/texture of matrix and a higher microporosity than D2 that has a higher pore surface heterogeneity. A fundamental understanding of the compositional and microstructural characteristics of UUS and further ductile/reservoir intervals will allow for a better assessment of reservoir quality, more effective production of hydrocarbons, and optimized selection of safe caprocks in carbon sequestration and subsurface hydrogen storage.

58 GEOSCIENCES↗
DOE OSTI2026

Multi-Spectroscopic Determination of Exchange Coupling, Zero-Field Splitting, and g-Matrices in Radical-Bridged Dinuclear Fe(III) Complexes

When the energy gap, Δ, between the lowest-lying spin manifolds within a spin-exchange coupled molecule approaches Δ/k B ≈ 300 K, the traditional temperature-dependence (T < 400 K) of the molar magnetic susceptibility is not always a reliable way to obtain a good estimate of intramolecular exchange couplings. We develop a spectroscopic approach capable of accurately parametrizing complex magnetic Hamiltonians by exploiting the separation of the anisotropy and exchange energy scales in strongly coupled magnetic molecules. Specifically, we combine inelastic neutron scattering, high-frequency electron paramagnetic resonance, far-infrared magneto-spectroscopy and magnetometry, and obtain detailed information about the magnetic properties of a series of diiron complexes derived from [[Fe(cth)] 2 (dxbq)] 3+ (H 2 dxbq: 2,5-dihydroxy-1,4-benzoquinone (x = h) or 3,6-dichloro-2,5-dihydroxy-1,4-benzoquinone (x = c), cth: 5,5,7,12,12,14-hexamethyl-1,4,8,11-tetraazacyclotetradecane). Well-isolated S = 9/2 ground states emerge due to strong direct antiferromagnetic exchange between the Fe 3+ centers (S = 5/2) and the radical bridging benzoquinone ligand (S = 1/2). The specific sensitivities and transition selection rules of the applied methods allow us to determine the parameters of the microscopic Hamiltonian including exchange coupling, fourth-order Stevens operators and g-factors. Our methodology is directly portable to other strongly coupled molecular compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

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

Contact Freezing of Water Droplets by Crystalline Organic Acids

The ability of water to freeze into ice crystals in mixed-phase clouds affects physical properties, including particle size, precipitation rates, and radiative properties. The presence of an insoluble particle at the surface of water droplets can promote ice nucleation at temperatures higher than that of pure water, even in the absence of a collision. However, contact freezing remains an underexplored mode of ice nucleation. Here, we present a study of atmospherically relevant organic acids and their role as effective ice-nucleating particles (INP) in contact mode using a Raman-microscope-equipped environmental chamber. We determined contact freezing temperatures induced by solid crystals of docosanol, adipic acid, cis-pinonic acid, fumaric acid, 4-hydroxybenzoic acid, palmitic acid, phthalic acid, sebacic acid, stearic acid, terephthalic acid, and vanillic acid. All solids except fumaric acid promoted contact freezing of water droplets at significantly higher temperatures than pure water in the chamber (−15.0 to −18.5 °C vs −21.3 °C). Physical and chemical properties were identified which correlate with greater effectiveness of INPs in the contact mode, including crystal lattice mismatch with ice, carbon number, and insolubility in water. In conclusion, we suggest that the presence of these organic solids in atmospheric aerosols may promote atmospheric ice nucleation at warm temperatures.

Clouds↗
DOE OSTI2026

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗
DOE OSTI2026

Nanostructuring and Underscreening of Bisalt Electrolytes with Dual-Anion Effects: Insights from Small-Angle Scattering Prepeak Analysis

Using small-angle neutron scattering, we studied the nanostructure of a prototypical D(H)-bonded network electrolyte, alkaline sodium aluminate bisalt, at concentrations up to solute volume fraction of ~0.5. Analysis of the structure factor prepeak at 0.1 < Q < 1.0 Å-1 showed that its evolution is associated with nanoscopic species distribution in water-anion network., with differences in characteristic distance d between OD- and Al(OD)4- anions related to their distinct sizes and interactions. When the solute volume fraction approached 0.5, a common/maximum value of ~4.5 Å was found for the correlation length ? that characterizes the electrostatic force in concentrated electrolyte solution before precipitation occurred. This implies that the solutions’ morphology and behavior at high concentrations may be governed by geometric factors, rather than the chemistry of the specific anion. Furthermore, the scaling of ? with concentration yielded an exponent of 1.25(1), suggesting that ? is limited to a few Å. By combining the current observations of structural heterogeneity at the nanoscale, with dynamic heterogeneity at the microscopic scale from our previous quasi-elastic neutron scattering study, we have established a structural origin of local “caging” and restricted structural relaxation processes. These local solvent-solute interactions not only control dynamics heterogeneity in concentrated electrolytes but also are responsible for crystallization processes in industrial setting, such as aluminum production and radioactive waste treatment.

Wang, Hsiu-Wen↗
DOE OSTI2024

Formation of Linear Plasmonic Heterotrimers Using Nanoparticle Docking to DNA Origami Cages

The fabrication of complex assemblies with interesting collective properties from plasmonic nanoparticles (NPs) is often challenging. While DNA-directed self-assembly has emerged as one of the most promising approaches to forming such complex assemblies, the resulting structures tend to have large variability in gap sizes and shapes, as the DNA strands used to organize these particles are flexible, and the polydispersity of the NPs leads to variability in these critical structural features. Here, we use a new strategy termed docking to DNA origami cages (D-DOC) to organize spherical NPs into a linear heterotrimer with a precisely defined geometrical arrangement. Instead of binding NPs to the exterior of the DNA templates, D-DOC binds the NPs to either the interior or the opening of a 3D cage, which significantly reduces the variability of critical structural features by incorporating multiple diametrically arranged capture strands to tether NPs. Additionally, such a spatial arrangement of the capture strand can work synergistically with shape complementarity to achieve tighter confinement. To assemble NPs via D-DOC, we developed a multistep assembly process that first encapsulates an NP inside a cage and then binds two other NPs to the openings. Microscopic characterization shows low variability in the bond angles and gap sizes. Both UV–vis absorption and surface-enhanced Raman scattering (SERS) measurements showed strong plasmonic coupling that aligned with predictions by electrodynamic simulations, further confirming the precision of the assembly. These results suggest D-DOC could open new opportunities in biomolecular sensing, SERS and fluorescence spectroscopies, and energy harvesting through the self-assembly of NPs into more complex 3D assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Resistance of Boron Nitride Nanotubes to Radiation-Induced Oxidation

We present unprecedented results on the damage thresholds and pathways for boron nitride nanotubes (BNNT) under the influence of energetic electrons in an oxidative gas environment, using an environmental aberration-corrected electron microscope over a range of oxygen pressures. We observe a damage cascade process that resists damage until a higher electron dose, compared with carbon nanotubes, initiating at defect-free BNNT sidewalls and proceeding through the conversion from crystalline nanotubes to amorphous boron nitride (BN), resisting oxidation throughout. We compare with prior results on the oxidation of carbon nanotubes and present a model that attributes the onset of damage in both cases to a physisorbed oxygen layer that reduces the threshold for damage onset. Surprisingly, increased temperatures offer protection against damage, as do electron dose rates that significantly exceed the oxygen dose rates, and our model attributes both effects to a physisorbed oxygen population.

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

Evolution and Degradation Patterns of Electrochemical Cells Based on the Analysis of Interfacial Phenomena at Li Metal Anode/Electrolyte Interfaces

In this work, we report the results of a theoretical–computational analysis of the solid electrolyte interphase (SEI) growth and degradation dynamics occurring in lithium metal batteries during cycling. We use ab initio-kinetic Monte Carlo simulations to generate a synthetic data set, which is analyzed by machine learning methods. We aim to determine: (i) how modifications in interfacial interaction energies between solid electrolyte interphase (SEI) blocks and between Li ions and SEI facets impact the Coulombic efficiency (CE) of the battery and (ii) what factors, including reactions, microscopic transport, and other interfacial events, may lead to cell performance “failure” during prolonged charge and discharge cycles, signaled as a sharp decay in the CE over cycling. The demonstration of our approach is done on a cell including a Li metal surface interfacing with a previously introduced state-of-the-art electrolyte, and the idea can be applied to any electrochemical system. Outcomes include the identification of the leading chemical, physical, and structural variables causing cell failure and relating them to the electrolyte formulation, thus paving the way to future more refined analysis and electrolyte design.

batteries↗
DOE OSTI2025

Comparing Machine Learning and Physics-Based Nanoparticle Geometry Determinations Using Far-Field Spectral Properties

Anisotropic metal nanostructures exhibit polarization-dependent light scattering, a property which has been widely studied and exploited to determine orientations of subwavelength structures using far-field microscopy. Here we explore the use of variational autoencoders (VAEs) to determine the geometries of gold nanorods (NRs) such as in-plane orientation and aspect ratio under linearly polarized dark-field illumination in an optical microscope. We enforce a shared latent space to connect two VAEs trained separately with polarized dark-field scattering spectra and electron microscopy images and achieve image prediction (shape, orientation, and size) of Au NRs using only polarized dark-field scattering spectra. We determine the geometrical parameters of orientational angle and aspect ratio quantitatively via both our dual-VAE and physics-based analysis on the input scattering spectra. We show that orientational angle prediction by dual-VAE performs well with only a small (~300 particle) training set, yielding a mean absolute error (MAE) of 14.4° and a concordance correlation coefficient (CCC) of 0.95. This performance is only marginally worse than the physics-based cos(2?) fitting approach between the scattering intensity and the polarizing angle, which achieves MAE of 8.78° and CCC of 0.99. Aspect ratio determination is also comparable for the dual-VAE and physics-based fitting comparison (MAE of 0.21 vs. 0.23 and CCC of 0.53 vs. 0.68). Here, this dual encoder-decoder architecture effectively exploits the structure-property relationships of plasmonic nanostructures to construct a cross-modal machine learning (ML) approach, providing a pathway to employ ML approaches to address other structure-property relationships in materials science.

Dark-field scattering↗
DOE OSTI2026

Dynamic Nuclear Polarization Enhanced 113 Cd Solid-State Nuclear Magnetic Resonance Spectroscopy Reveals CdSe Nanocrystals with Triangular Two-Dimensional Projections are Terminated by {100} Facets

Surface structure plays an important role in particle growth and determining the chemical and photophysical properties of semiconductor nanocrystals (NCs). Therefore, there is a need for structural tools that can characterize and detect different surface facets. Here, we sought to investigate the structure of {111} CdSe facets by applying dynamic nuclear polarization (DNP) enhanced 113 Cd and 77 Se solid-state nuclear magnetic resonance (SSNMR) spectroscopy to zinc-blende CdSe NCs that exhibit triangular two-dimensional (2D) projections within transmission electron microscope (TEM) images. It was originally hypothesized in the literature that these CdSe NCs were tetrahedral in shape and terminated by facets from the {111} family of lattice planes of the zinc-blende structure. Surprisingly, we observe 113 Cd NMR spectra indicating that the primary facets are from the {100} family of lattice planes. We also obtained DNP-enhanced 113 Cd and 77 Se SSNMR spectra of recently reported right trigonal bipyramidal (rTriBP) CdSe NCs grown by seeded growth. The 113 Cd NMR spectra rTriBP CdSe NCs are consistent with {100} surface facets. TEM images show that rTriBP NCs may also exhibit triangular 2D projections that are similar to the so-called tetrahedral NCs. Based upon these results, we conclude that the so-called tetrahedral NCs are predominantly terminated by {100} surface facets and most likely have the same shape as rTriBP NCs. These results highlight the need for multiple complementary techniques when assigning the shape and surface termination of NCs.

Santhiran, Anuluxan [Ames Laboratory (AMES), Ames,↗
DOE OSTI2026

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗
DOE OSTI2026

Long-Range Dispersion Governs the Behavior of Near-Critical Fluids: Universal Scaling and Implications for Accurate Molecular Simulation

Computer simulations of near-critical and supercritical fluids often deviate from experimental results, a discrepancy commonly attributed to force-field resolutions and inaccuracies. We demonstrate that these errors primarily stem from using finite cutoff schemes for dispersion interactions, which become effectively long-range as the correlation length grows near the critical point. By employing the smooth particle-mesh Ewald method to account for full long-range dispersion, we show that coarse-grained models can also achieve high quantitative accuracy for n-undecane and propylbenzene. This approach enables the precise determination of density fluctuations and correlation lengths, which exhibit universal critical scaling and depend on the molecular size and shape. Our findings resolve a longstanding debate in molecular simulations of near-critical fluids, establishing that capturing long-wavelength fluctuations is essential for bridging the gap between the microscopic behavior and macroscopic critical phenomena.

Chen, Guang↗
DOE OSTI2026

Tuning the Solvation and Solubility Properties of Molecularly Heterogeneous Nonionic Deep Eutectic Solvents via Interface Organization

Common separation techniques, such as liquid− liquid extraction, are usually used for extractions and purifications due to their industrial scalability and affordability. However, these well-established practices are hindered by low selectivity and challenges in recovering solutes and solvents. Deep eutectic solvents (DES), a fairly new type of solvent, have the potential to overcome these issues. DESs are binary mixtures whose physical properties can be tuned by selecting the appropriate precursors to facilitate and/or enhance processes such as extraction. A promising DES for selective separations is formed when lauric acid (LA) is mixed with N-methylacetamide (NMA). This LA-NMA DES has a heterogeneous microscopic structure that can solvate compounds with completely different polarities. This study explores how forming an organized structure on the mesoscale affects the solubility of nonpolar solutes in nonionic DESs. To this end, the molecular and mesoscale structures and their effect on the solubility and solvation properties are evaluated for the LA-NMA DES and two new DESs with slight chemical variations in their precursors. It is observed that the organization of the nonpolar DES domains and, consequently, of their interfaces directly relates to the solubility of nonpolar compounds. Specifically, correctly selecting the DES precursors that form organized nonpolar domains leads to an organized interface in which the nonpolar solutes are solvated, thereby increasing the solubility. Additionally, enhanced dissolution power was observed in a completely different DES with mesoscale order in its molecular structure and composed of menthol and lauric acid. The latter result further validates the proposed tunability of the DES dissolution power through organized interfaces, extending it beyond a specific DES family and opening the possibility of new extraction-tailored designer solvents.

Extraction↗
DOE OSTI2024

Theory of Ion-Mediated Segmental Localization, Activated Structural Relaxation, and the Glass Transition in Polymerized Ionic Liquids

Here we combine polymer integral equation theory for structural correlations with a force-level theory for activated segmental relaxation to construct a microscopic theory for how ions modify the onset of segmental localization, the polymer alpha relaxation time, and glass transition temperature, T g , in dry polymerized ionic liquids (PolyILs). Our most important findings concerning the behavior of T g are (i) a weak dependence on anion–cation Coulomb attraction strength due to strong decoupling of ion and segmental dynamics, (ii) strong reduction with increasing mobile ion size due to both plasticization effects and weakening of ion-modified monomer caging, and (iii) increase with backbone rigidity and intrachain dynamic cooperativity. We quantitatively estimate T g variations as ion size and polymer static and dynamic rigidity are widely varied. The experimental data of 19 PolyILs are organized into a specific pattern consistent with the theoretical predictions with glass transition temperatures varying over a very wide range (~250 K) as observed experimentally. Based on the theoretical results, suggestions are made concerning the search for high conductivity Li- or Na-based PolyILs based on further lowering of T g via new polymer synthesis. Calculations of the alpha time as a function of packing fraction reveal the dynamic fragility increases for larger mobile ions, a more flexible backbone, and/or a smaller degree of intrachain dynamic cooperativity, as a consequence of the increasing importance of collective elasticity in determining the activation barrier. An analysis of transient segmental localization and a crossover to activated dynamics reveals similar, but not identical, trends as predicted at the laboratory vitrification timescale.

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

Molecular Dynamics Simulation and Theoretical Analysis of Structural Relaxation, Bond Exchange Dynamics, and Glass Transition in Vitrimers

Vitrimers are a class of polymer networks featuring dynamic covalent cross-links that can undergo associative bond exchange. There has been recent interest in these materials due to their promise as recyclable thermosets or self-healing polymers because of the ability of vitrimer networks to rearrange at the molecular level and undergo macroscopic flow. However, the practical use of these materials often occurs in the supercooled regime or glassy state, where the implications of dynamic bonds are complicated by the interplay between slow activated segmental dynamics, cross-link (i.e., bond-exchange) kinetics, and ultimately material properties. Here, in this paper, we combine coarse-grained molecular dynamics simulation and microscopic statistical mechanical theory to understand how cross-linking kinetics affect material dynamics and how this couples to segmental relaxation of the polymeric network strands across a spectrum of length and time scales, especially in the supercooled regime. We characterize the Kuhn segmental alpha relaxation time and bond exchange time for vitrimer systems across various cross-link densities, temperatures, and bond exchange rates. Simulation and theory both exhibit a bending-up behavior for bond exchange time upon cooling, suggesting a coupling between bond exchange dynamics and segmental relaxation that intensifies with faster bond exchange kinetics. We also found bond exchange dynamics have an impact on Kuhn segment alpha relaxation time, which is most significant at higher cross-link densities. Both these effects are most prominent when the bond exchange time is similar to the Kuhn segment alpha relaxation time, and the resulting coupling of these two relaxation processes is tied to both the probability of a free end to find a bonded pair and the time scale of the constraints imposed by the dynamic cross-links. This relationship is reflected by a cross-link dependence of a theoretical parameter which represents the quantitative degree of coupling between bond exchange and segmental dynamics. Overall, the combination of simulation and theory clarifies the intricate interaction between bond kinetics and segmental relaxation and demonstrates the ability to provide molecular-level insights into vitrimer dynamics over a wide temperature range.

dynamic relaxation↗
DOE OSTI2024

Grazing Incidence Wide-Angle X-ray Scattering of Water Adsorption in Polyamide Barrier Layers of Reverse Osmosis Membranes

To understand the relationship between the intermolecular structure of aromatic polyamide (PA) scaffold and the water molecules in the barrier layers of reverse osmosis (RO) membranes, a grazing incidence wide-angle X-ray scattering (GIWAXS) study was carried out on freestanding PA thin films at varying relative humidity (RH) conditions. The scattering results were analyzed by an interference scattering model, containing a phase factor between a PA chain and an adsorbed water molecule. This model yielded good fits to the GIWAXS profiles where the water adsorption was found to vary linearly with RH. Atomistic molecular dynamics (MD) simulations were also performed to complement the experimental study. Furthermore, the simulations revealed that a rapid condensation layer initially formed on the PA film surface, followed by the slow water molecule diffusion inside the PA membrane. Sparse adsorbed water, isolated in subnanopores of the PA film adjacent to the polar atoms, even in very low quantities, modifies the X-ray scattering. Atomistic simulations at the microscopic scale provide partial support for several X-ray scattering findings.

36 MATERIALS SCIENCE↗