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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Single-Molecule Tracking Measurements Reveal the Detailed Mechanisms of Molecular Diffusion in Solvent Mixtures under Nanoconfinement

Understanding mass transport mechanisms in nanopores is important for developing advanced materials for chemical separations, chemical sensing, and energy storage. This paper reports a novel imaging platform that is employed for the first time to investigate the detailed diffusion dynamics of single rhodamine B (RhB) dye molecules confined within solution-filled cylindrical anodic aluminum oxide (AAO) nanopores. The imaging platform relies on illumination of horizontally-oriented AAO nanopores in a highly inclined and laminated optical (HILO) light sheet microscopy geometry. The method was used to investigate the translational and orientational dynamics of single rhodamine B (RhB) molecules within horizontally-oriented 5- and 10-nm diameter AAO nanopores filled with water–ethanol mixtures. The established platform enabled the observation of one-dimensional motion along the pore axis involving occasional short- or long-term immobilization at the single-molecule level. Analysis of cumulative squared-displacement distributions revealed fast (5 – 30 µm²/s), intermediate (1 – 5 µm²/s), and slow (< 1 µm²/s) diffusion components. From the effects of mixture composition and pore size on the contributions of these three components, we inferred that the fast, intermediate, and slow components could be assigned to desorption-mediated hopping, crawling, and wiggling motions, respectively. The platform based on the horizontally-oriented AAO nanopores also permitted single-molecule emission polarization measurements that revealed the negligible steric confinement of individual diffusing RhB molecules within the AAO nanopores. The imaging platform based on AAO membranes and HILO microscopy provided a unique means to investigate how solvation-mediated surface interactions and nanoconfinement govern molecular transport in nanoporous environments.

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

Quantum Sieving for Isotopic Separations of Gases Using Porous Materials─30 Years of Progress

Here, this paper reviews theoretical and experimental efforts to establish microporous materials that can be used to separate isotopologues of molecular gases such as H 2 and D 2 . Emphasis is placed on use of simplified models to highlight the quantum phenomena that make these separations possible. In equilibrium adsorption, differences in zero point energy in the adsorbed states of molecules favor binding of heaver isotopologues (e.g. D 2 relative to H 2 ). Experimental data showing this effect was reported as early as 1933, but the theoretical work of Beenakkers et al. in 1995 [Chem. Phys. Lett. 232 (1995) 379-382] spurred modern efforts to develop materials with strong so-called quantum sieving. In porous materials where the transition state for molecular diffusion is more strongly confined than the energy minima associated with equilibrium adsorption, differences in zero point energies between these two sites can lead to isotopic differences in molecular diffusivities. This effect favors diffusion of heavier species (e.g. D 2 ) relative to lighter species (e.g. H 2 ). This so-called kinetic quantum sieving has been observed experimentally in porous carbons and in porous organic cage materials. We show that quantum tunneling, which favors hopping of lighter species across energy barriers, diminishes the strength of kinetic quantum sieving but that it appears to make only a small contribution to the net molecular diffusivities in many porous materials of practical interest.

Sholl, David S. [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

Geometry-complete diffusion for 3D molecule generation and optimization

Abstract Generative deep learning methods have recently been proposed for generating 3D molecules using equivariant graph neural networks (GNNs) within a denoising diffusion framework. However, such methods are unable to learn important geometric properties of 3D molecules, as they adopt molecule-agnostic and non-geometric GNNs as their 3D graph denoising networks, which notably hinders their ability to generate valid large 3D molecules. In this work, we address these gaps by introducing the Geometry-Complete Diffusion Model (GCDM) for 3D molecule generation, which outperforms existing 3D molecular diffusion models by significant margins across conditional and unconditional settings for the QM9 dataset and the larger GEOM-Drugs dataset, respectively. Importantly, we demonstrate that GCDM’s generative denoising process enables the model to generate a significant proportion of valid and energetically-stable large molecules at the scale of GEOM-Drugs, whereas previous methods fail to do so with the features they learn. Additionally, we show that extensions of GCDM can not only effectively design 3D molecules for specific protein pockets but can be repurposed to consistently optimize the geometry and chemical composition of existing 3D molecules for molecular stability and property specificity, demonstrating new versatility of molecular diffusion models. Code and data are freely available on GitHub .

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

Temperature-Dependent Molecular Diffusional Properties in Deep Eutectic Solvents and Eutectogels

Eutectogels (ETGs) prepared from deep eutectic solvents (DESs), a gelator, and water have many uses in separations, catalysis, and energy storage systems. In these applications, temperature-dependent molecular diffusional properties and intermolecular interactions play a critical role in their function. Diffusional properties of Alexa Fluor 633 and ATTO 647N were measured across a range of temperatures in choline chloride:2glycerol DESs comprised of one molar equivalent of choline chloride and two molar equivalents of glycerol (also known as glyceline) as well as ETGs made from this DES, a xanthan gum gelator, and 10% w/w water or 20% w/w water. Fluorescence recovery after photobleaching (FRAP) was employed to evaluate potential changes in molecular diffusion within DESs and ETGs from 20 to 100 °C. Surprisingly, the ETGs have a larger sample viscosity but also exhibit faster molecular diffusion when compared to the dry DES. This is attributed to macroscopic properties of the ETGs (e.g., pores, three-dimensional structure). The FRAP data also show an irreversible temperature-dependent decrease in the diffusion coefficient of both fluorophores in the ETGs. This is consistent with differential scanning calorimetry data of the ETG, which shows a shift to a more negative glass transition temperature (−36 °C to −47 °C) after the first cooling/heating cycle. Raman data reveal no detectable changes in the intermolecular interactions in either the DESs or ETGs as a function of temperature or water content. Finally, the findings on temperature- and water-dependent diffusional properties of DESs and ETGs provide a foundation for optimizing the use of these materials across various applications, particularly where repeated heating/cooling cycles may be used.

alcohols↗
DOE OSTI2024

Onset of kinetic effects on Rayleigh–Taylor instability: Advective–diffusive asymmetry

In nature and engineering applications, the Rayleigh–Taylor instability (RTI) occurs over a wide range of Atwood, Reynolds, Mach, and Knudsen numbers. At low Atwood, Mach, and Knudsen numbers, the classic advective instability causes quasi-symmetric bubble and spike growth on the two sides of the interface. However, recent findings suggest that at high degrees of rarefaction, advective effects are suppressed and molecular diffusion leads to planar growth of the density fronts on either side of the interface. This study aims to investigate the flow physics of the transition from advective to diffusive behavior, focusing on the onset of the kinetic effects. Using the gas kinetic methodology, RTI is simulated over a range of Knudsen and Mach numbers in the transition regime. The simulation results reveal the various stages of transformation from advective instability to diffusive transport. For the first time, the study demonstrates the existence of a Knudsen–Mach parameter regime where the bubble side exhibits advective instability, while the other side shows a planar density front due to molecular diffusion, rather than the canonical advective spike shape. The dominance of different mechanisms on the two sides of the interface leads to the advective–diffusive asymmetry. In conclusion, the findings of this study can lead to a more comprehensive understanding of RTI over a wide range of Mach and Knudsen numbers.

42 ENGINEERING↗
DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗
DOE OSTI2025

Role of pore dilation in molecular transport through the nuclear pore complex: Insights from polymer scaling theory

The nuclear pore complex (NPC), a channel within the nuclear envelope filled with intrinsically disordered proteins, regulates the transport of macromolecules between the nucleus and the cytoplasm. Recent studies have highlighted the NPC’s ability to adjust its diameter in response to the membrane tension, underscoring the importance of exploring how variations in pore size influence molecular transport through the NPC. In this study, we investigated the relationship between pore size and transport rate and proposed a mathematical model describing this connection. We began by theoretically analyzing how the pore size scales with the characteristic dimensions of the mesh-like structure within the pore. By introducing key assumptions about how the meshwork structure influences molecular diffusion, we derived a mathematical expression for the transport rate based on the size of the pore and the transported molecules. To validate our model, we conducted Brownian dynamics simulations using a coarse-grained representation of the NPC. These simulations, performed across a range of pore sizes, demonstrated strong agreement with our model’s predictions, confirming its accuracy and applicability. Our model is specifically tailored for small-to-medium-sized molecules, approximately 5 nanometers in size, making it relevant to a wide range of transcription factors and signaling molecules. It also extends to molecules with weak and transient interactions with FG-Nups, such as importin-β. By presenting this model formula, our study offers a quantitative framework for analyzing the effects of pore dilation on nucleocytoplasmic transport.

Biochemistry & Molecular Biology↗
DOE OSTI2025

CO 2 Capture Characteristics of Hyperbranched Poly(alkylene imine): A Molecular Dynamics Simulation Approach

This study explores the CO 2 capture characteristics of hyperbranched poly(ethylenimine) (HB-PEI) and poly- (propyleneimine) (HB-PPI) through molecular dynamics simulations using density functional theory-calibrated force fields. Key features such as density, free volume, glass transition temperature, CO 2 /H 2 O distribution, and molecular diffusion are systematically investigated to elucidate structure−function relationships under dry and hydrated conditions. HB-PEI demonstrates a slightly higher density and lower free volume compared to HB-PPI yet shows superior CO 2 capture due to the high amine concentration. Glass transition analysis indicates a higher thermal mobility in HBPEI, enhancing the CO 2 diffusivity. Pair correlation and coordination analyses confirm a stronger affinity of CO 2 with primary and secondary amines, particularly in hydrated environments where water competes with CO 2 for binding sites. Despite its more compact structure, HB-PEI outperformed HB-PPI in CO 2 and H 2 O transport, as confirmed by higher diffusion coefficients across all hydration levels. These findings highlight a critical balance among polymer architecture, amine accessibility, and hydration in designing next-generation solid amine sorbents for efficient direct air capture applications.

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

Molecular Modeling and Molecular Dynamics Simulation of a Packed and Intact Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semipermeable shell proteins and are packed full of enzyme cargoes and metabolites as they fulfill their function. Coupling together recent SAXS and proteomics work, it is possible to develop molecular models for these microcompartments and interrogate enzyme and metabolite dynamics within. Our primary goal of this study is to quantify the permeability of metabolite glyceraldehyde-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP) across the BMC shell through classical molecular dynamics simulation. The Haliangium ochraceum model of BMC shell (PDB: 6MZX) was used to model an intact BMC of approximately 10 million atoms. Working at this scale presented its own challenges in managing large data sets, with multiple challenges and hardware advances discussed that facilitated this work. Over approximately 750 ns of aggregate simulation, we see multiple permeation events for these metabolites that were added at high concentration through the pores present within BMC shell tiles. When compared to independent permeability estimates for the same metabolites determined through replica exchange umbrella sampling simulations, the permeabilities varied by approximately 3 orders of magnitude. Regardless, the permeability coefficients for both G3P and DHAP are highly similar and very high, such that only very small concentration gradients can be maintained across the BMC shell between the cytosol and BMC interior. The large simulation systems also facilitated comparisons for molecular diffusivity in the crowded environment within the BMC shell. By our estimates, the viscosity within a packed BMC shell is at least 10-fold higher than it would be in neat solution and is the real driver for varying permeability estimates we obtained through simulation. These findings will be used as design inputs for future bioengineering efforts to make products from BMCs, highlighting how permeable BMC shells can be.

Diffusion↗
DOE OSTI2025

Facilitating Screening of MOFs for Mixed Matrix Membranes Using Machine Learning and the Maxwell Model

Metal organic framework (MOF)-based mixedmatrix membranes (MMMs), which embed MOF particles in polymer matrices, combine the advantages of polymeric and inorganic membranes. Multiple previous studies have used the Maxwell model together with molecular simulations and machine learning (ML) to predict the performance of MOF/polymer MMMs. However, the assumption of rigid MOF frameworks in molecular simulations limited the accuracy of the data used in the predictions, particularly in predicting molecular diffusivities. We developed a novel workflow integrating ML models with consideration of MOF flexibility to predict the permeability and selectivity of 131,722 MMMs for CO 2 /CH 4 , O 2 /N 2 and He/H 2 separations. The full range of achievable MMM performance within the Maxwell model was analyzed, and several promising MOFs were identified using this workflow. This approach offers an efficient tool for screening any polymer and MOF combination in gas separation applications.

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

Solid-State Side-Chain Functionalization of Conjugated Polymers for Expanded Chemical and Functional Versatility

Conjugated polymers that integrate diverse chemical functionalities with high electronic performance are essential for advanced organic electronic, optoelectronic, and biointerfaced technologies. Achieving such multifunctionality typically requires grafting functional units onto polymer side chains. However, conventional solution-phase approaches remain constrained by solubility limitations, side-chain-induced packing disruptions, and challenges in preserving charge transport. Here, we introduce a solid-state side-chain functionalization strategy that exploits a swellable polar side-chain architecture and azide–alkyne click chemistry to enable efficient molecular diffusion and reaction throughout predeposited polymer thin films. This approach substantially broadens the chemical compatibility of graftable units and mitigates the adverse effects on the electrical property. Moreover, the method supports spatially selective functionalization within a continuous film, enabling the patterned incorporation of chemically distinct groups to produce spatially defined optical properties. Here, this solid-state strategy thus provides a versatile platform for constructing conjugated polymers with expanded chemical versatility, preserved electronic performance, and programmable spatial functionality.

Conjugated polymers↗
DOE OSTI2026

Structured electrolytes facilitate Grotthuss-type transport for enhanced proton-coupled electron transfer reactions

Concentrated hydrogen-bonded electrolytes (CoHBEs) are structured, electrochemically stable, less-volatile alternatives to aqueous and dilute nonaqueous electrolytes, however, with high viscosities that limit molecular diffusion. This work provides an understanding of the proton conduction mechanism in CoHBEs based on mixtures of acids and azoles and establishes a link between the structurally dictated transport properties and the proton-coupled electron transfer (PCET) reaction rates that can be leveraged for enhancing electrochemical reactions. Diffusion and relaxation NMR studies suggest a breaking of the viscosity–conductivity tradeoff, where at high azole concentrations (>45 mol%), Grotthuss transport is more likely with lowered proton transfer energy barriers between the azole and the acid according to the machine learning (ML) accelerated ab initio path integral MD (AI-PIMD) simulations. Proton conduction pathways are found to be switchable between the hydrogen bonding networks of the acid and the azole, with imidazole chain forming structures better facilitating Grotthuss hopping. Supported by small-angle neutron scattering studies, the chains are found to have six member molecules on average with maximum of 3 to 4 imidazole/imidazoliums at 50 to 60 mol%. Despite their high viscosities, the measured PCET rates for quinones and phenazines measured in the protic CoHBEs present relatively high electron transfer rate constants (k 0 ~ 10 −4 cm/s), validated by rotating disc electrode and scanning electrochemical microscopy measurements. The results demonstrate that strategic tuning of hydrogen-bond donor–acceptor interactions enables the decoupling of proton transport and viscosity, thereby impacting PCET reactions.

electrokinetics↗
DOE OSTI2024

High-Fidelity Simulation of the Light-to-Dense Stratification Transient in the HiRJET Facility

Density stratification in a large enclosure is a crucial phenomenon to heat transfer and sustainable passive heat removal of a sodium fast reactor during reactivity transients. However, engineering turbulence models were identified to have unsatisfactory performance in predicting propagation of a stratified front. Yet, the scarcity of high-resolution data for stratification hampers the development of models. To explor e applications of leveraging direct numerical simulation (DNS) data to support turbulence model development, this work conducted DNS using NekRS to study a long stratification transient in the High-Resolution Jet (HiRJET) experimental facility. Here, this work considers an experiment run where light fluid is injected into a tank containing a denser fluid with a relative density difference of 1.5%. Formation of the stratified layer is identified as impingement of the buoyant jet promoting mixing of the two fluids. Based on the transient statistics, transport of the concentration can be characterized by regions with dominating effects of turbulent mixing, buoyant dissipation, and molecular diffusion, respectively, as moving away from the elevation of jet impingement. Concentration near the stratified front also exhibits oscillation at Brunt-Väisälä frequency. Preliminary validation of the simulation showed encouraging agreement of the concentration distribution with the reference experiment.

buoyant mixing↗
DOE OSTI2024

Probing Supercritical Phase Transition using Ultrafast X-ray Diagnostics (Final Technical Report)

Over recent years, several hypotheses have been put forward to elucidate supercritical transition states. Despite significant progress on the fundamental understanding of fluids at these supercritical conditions, important questions concerning the microstructure and dynamical processes remain. A particular research issue is hereby the fundamental understanding of the morphology of the molecular microstructure and its effect on the macroscopic behaviour and thermodynamic response functions. It is widely believed that the supercritical state is homogeneous without structural and dynamic observables to distinguish between a liquid and a vapor. However, recent investigations have identified regions of distinct liquid-like or vapor-like properties even under supercritical conditions. Specifically, it was shown that the transition between liquid-like and vapor-like states occurs across an extension to the coexistence line, marked by almost discontinuous changes in fluid properties. This transition was first identified experimentally by Nishikawa and Tanaka and stands in contrast to the classical presentation of the supercritical state space as a featureless, homogeneous domain. Structurally, the most important properties of supercritical fluids are the dynamic heterogeneities and local density fluctuations that are present within the fluid state at the microscopic level. These inhomogeneities are associated with the formation of molecular clusters of various sizes with liquid-like properties separated by voids of unbound gas-phase molecules which continuously restructure itself at picosecond timescales. By utilizing ultrafast X-ray Photon Correlation Spectroscopy (XPCS) at the Linac Coherent Light Source (LCLS) and X-ray synchrotron measurements as an experimental probe of these structural changes at the molecular level we seek to elucidate the higher-order phase transition from a liquid-like to a vapor-like state in the region extending the critical point. Open questions we seek to address particularly with XPCS are: (i) the underlying mechanisms responsible for the density fluctuations at supercritical conditions and how these dynamical processes at the molecular level affect the thermodynamic response functions and (ii) on what timescales do dynamical processes evolve that are associated with thermalization, molecular diffusion, and intermolecular cluster transfer.

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

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
DOE OSTI2025

Diffusion-mediated passing of molecular species in linear nanopores constrained by orientational alignment

For diffusion-mediated catalytic conversion reactions in materials with narrow linear nanopores, e.g., mesoporous silica MCM-41, a key parameter is the propensity for product species to be able to pass reactant species and thus to efficiently exit the pore. For elongated species, this can require orientational alignment with the pore axis. In this work, we perform benchmark analyses for such solution-phase systems where one of these species is elongated in order to quantify the dependence of this passing propensity, P, on pore diameter and on the rotational diffusion coefficient, Dr, of the elongated species. In particular, we consider the passing of a spherical and an elongated spherocylindrical shaped species in a cylindrical pore in an implicit solvent, where these species cannot overlap. Passing is mediated by diffusive Brownian motion of these species as described by strongly damped Langevin dynamics. We quantify scaling of P for pore width just above the threshold where passing is sterically blocked, and also reveal a significant decrease in P for lower Dr. We also consider the dependence of P on the aspect ratio of the elongated species and obtain an exact result in the limiting regime of large aspect ratio.

Brownian motion↗
DOE OSTI2025

Mapping structures and dynamics with frequency-correlated diffusion exchange

Understanding molecular motion in diffusion-driven complex environments is critical for designing sustainable materials and improving chemical processes. Here, we introduce a multidimensional nuclear magnetic resonance (NMR) method that captures how molecular populations exchange across different dynamic regimes. By extending the modulated gradient spin-echo technique to include frequency-frequency correlations, our approach reveals diffusion pathways that are otherwise obscured in heterogeneous systems. Implemented on a unilateral NMR magnet, the method eliminates gradient pulsing constraints and accesses dynamics in the kilohertz regime. We apply this technique to swelling and acid-catalyzed deconstruction of cross-linked and linear polymers to observe how structural heterogeneity evolves over time. By linking molecular motion to topology and chemical state, we extract physical metrics such as fractal surface dimensionality and reaction wavefront velocity, properties inaccessible with standard diffusion measurements. This work expands the capabilities of NMR for probing soft matter, with implications for polymer recycling and materials design.

Fricke, Sophia N. [University of California, Berke↗