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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 73 records · Page 4

Single-Molecule Fluorescence Investigations of Solute Transport Dynamics in Nanostructured Membrane Separation Materials

Many materials used for membrane separations comprise of nanoscale structures such as pores and domains. Such nanostructures often control the solute permeability and selectivity of separation membranes. Thus, for future development of highly efficient separation membranes, it is important to understand the structural and chemical properties of these nanostructures, and also their influences on solute transport dynamics. For the last two decades, single-molecule fluorescence techniques have been used to measure the detailed dynamics of solute molecules diffusing in various nanostructured materials, giving valuable insights into molecular transport mechanisms influenced by nanoscale material heterogeneity. This Perspective will discuss recent single-molecule fluorescence studies on solute diffusion in materials relevant to membrane separations, including dense polymer films and nanoporous materials. These studies have revealed the formation and properties of nanostructures, and unique transport dynamics of solute molecules manipulated by their confinement and partitioning to the nanostructures, which play key roles in membrane separations. Furthermore, this Perspective will also point out scientific challenges toward thorough understanding of molecular-level mechanisms in membrane separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tardigrade-examples V0.1.0

Tardigrade-examples is a repository of computational workflows that exercise the Tardigrade software package. The Tardigrade software package is an implementation of Eringen’s micromorphic continuum theory with capabilities to support multiscale material modeling. These capabilities include homogenization through the Micromorphic Filter, calibration of micromorphic material models, and macroscale simulation in Tardigrade-MOOSE. This repository investigates continuum upscaling of various direct numerical simulations (DNS) conducted in Abaqus finite element (FE), Ratel FE, and GEOS material point method (MPM) software. Verification of the upscaling workflow is first investigated by considering DNS of trivial stress states for homogeneous materials, results of which indicate that classical continuum behavior is recovered as expected. DNS of heterogeneous materials are then considered.

Allard, Thomas↗

Mechanical and Thermophysical Properties of 3D-Printed SiC before and after Neutron Irradiation – FY21

This report presents the mechanical and thermophysical properties of 3D-printed SiC before and after neutron irradiation that have been evaluated to assess the fuel matrix material for the Transformational Challenge Reactor (TCR). The TCR fuel form consists of an additively-manufactured silicon carbide (SiC) matrix and uranium nitride tristructural isotropic (UN TRISO) fuel particles, which is manufactured through a newly developed processing route combining binderjet 3D printing, TRISO fuel particle loading, and chemical vapor infiltration (CVI). Because the fuel matrix is a primary component of the TCR core and its response to mechanical and thermal loads during operation is one of the most influential factors on the integrity of TCR core, testing and evaluation have focused on producing mechanical and thermophysical properties data for the binderjet/CVI SiC. Baseline mechanical and thermophysical properties were measured from the disk specimens printed for different and sizes orientations, which included equibiaxial flexural failure strength, elastic constants, thermal diffusivity and conductivity, density, and the coefficient of thermal expansion. Flexural failure strength datasets showed similar Weibull distributions regardless of sample variants including different orientations. The mean failure strengths of the 3D-printed SiC variants were in the range of 280–310 MPa, which are slightly lower than that of the chemical vapor deposition (CVD) SiC. Thermophysical test results showed that specific heat and thermal expansion are not sensitive to the build direction of SiC samples, while thermal conductivity is highly dependent on the build direction and can be correlated to the anisotropic character of the 3D-printed SiC. Neutron irradiation tests were carried out on the 3D-printed 6-mm diameter SiC disk specimens. Irradiation was carried to 2.3 dpa over a temperature range of 360–880°C. No significant degradation in strength was observed in SiC after irradiations in various conditions and with different orientations. Anisotropy that had been observed in the thermal conductivity of 3D-printed SiC prior to irradiation vanished after irradiation as the irradiation defect thermal resistivity accumulated in the material. Electron microscopy of the microstructure after neutron irradiation showed distinct defect morphologies in the heterogenous material, but no evidence for irradiation-induced cracking or degradation in the microstructure was observed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A First Principles Approach to Spectral Phonon Transport in Heterostructures

Understanding thermal transport across interfaces which give rise to a thermal resistance (also known as Kapitza resistance) is a critical issue affecting the development of nanotechnologies. Much modern and emergent nanotechnology consist of adjacent materials, and phonon mediated heat transfer governs thermal behavior across internal interfaces in these devices. The physics of thermal transport in solids are governed both by phenomena occurring at the atomic scale and interactions with the material's microstructure. The forecasting of fundamental quantities such as temperature, heat flux and thermal conductivity typically employs the semi-classical Boltzmann transport equation to predict the macroscopic behavior of materials in terms of the microscopic dynamics of its heat carriers. Kapitza resistance was first discovered in liquid helium experiments and has led to a fundamental research thrust in micro and nano-scale heat transport, the behavior of thermal carriers across internal interfaces. Thermal interfacial resistance (TIR) is a widely studied phenomenon, first engaged by Swartz and Pohl through their development of the acoustic and diffuse mismatch methods, then continued through myriad efforts with varying methods and approaches in an attempt to resolve carrier behavior at thermal interfaces. Many of the fundamental approaches to TIR have been at the nanoscale, and research is conducted with molecular dynamics (MD) and density functional theory (DFT) methods. The limitations of these methods is system size; atomistic methods tend to be limited to system sizes of 100,000 atoms or less. Larger length-scale methods have also been pursued, based on the principles of acoustic or diffuse mismatch, but not all include simulation of TIR using a full phonon band spectrum, or temperature dependent methods. Our approach to enabling phonon transport in layered materials draws upon our previous work of demonstrating spectrally coupled phonon transport in homogeneous and heterogeneous materials. We use a semi-analytical approach in which the Bose-Einstein (B-E) statistics set the strength of the phonon radiance in a frequency group, but the B-E statistics are informed with information from the transport system. The B-E statistics in a single frequency group feels the influence of all the groups through the spatial temperature. We also include a new field term which is an indicator of the amount of non-equilibrium behavior of the phonon spectrum---this is added to the phonon source term in all groups to ensure closure and conservation of energy, as the phonon groups in the transport system and the analytical systems are coupled. This work builds upon our previous approach by adding a phonon coupling term at an internal interface, using the principles of the DMM through transmission and reflection coefficients. In this work, the coefficients are determined through computing a common temperature at the interface, influenced by the phonon band structure of both materials, in effect, providing mixing between the two material systems and using the common temperature to set the strength of the phonon radiance at the boundaries on either side of the interface. Our approach uses material properties computed along various crystallographic orientations, and while some isotropy is built into the interface condition, the material properties weight the phonon distributions in the proper crystalline direction. Greater resolution of phonon behavior in proximity to an interface, and more accurate predictions of TIR are obtained. While it is true the assumption of diffuse mismatch can yield inconsistent results compared to experiment especially at low temperatures, this work focuses on room temperature and beyond effects, for future applications in nuclear fuel, or thermoelectric devices; a modified mismatch approach may be feasible if applied properly. Additionally, our methods focus on bridging mesoscale to engineering scale

36 MATERIALS SCIENCE↗

Microstructural diversity and digestion yields of select bituminous and subbituminous coals as raw material candidates for carbon fiber precursor production

Here, this work investigates the use of coals as raw materials for carbon fiber precursor production as a new alternative to coal utilization. Coal being a highly complex and heterogeneous material with different macerals and minerals complicates this task. Extensive microstructural characterization as well as preliminary digestion studies are performed on three bituminous coals (Herrin and Springfield from the Illinois Basin and the Blue Gem from the Central Appalachians) and one subbituminous coal from the Powder River Basin (Monarch), as raw material candidates. The subbituminous coal was richer in oxygen, lower in sulfur, and had a higher volatile matter yield. Microstructural investigations were performed using X-ray diffraction, X-ray/neutron computed tomography, scanning electron microscopy with energy dispersive spectroscopy, and petrology. Mild solvent extraction studies were conducted using creosote and decant oil as solvents in microreactors. The extraction yield was sensitive to temperature and time (350 to 450 °C between 30 and 120 mins.) for both creosote and decant oil digestions. While the Blue Gem coal had more desirable microstructural properties with less mineral content and cleaner macerals, it had the lowest coal conversion to quinoline soluble ‘liquid’ (of the bituminous coals). The lower coal conversion yield was hypothesized to be connected to the lack of FeS2 which could act as a catalyst when Fe is liberated from the structure under solvent extraction conditions. The Herrin and Springfield coals revealed similar microstructures and coal conversion efficiencies (higher than Blue Gem). These coals were the most promising candidates for further examination from this first approximations study. The subbituminous Monarch coal, however, was deemed less suitable due to poor coal conversion and less desirable microstructures. Additionally, the presented results with combined microstructural data from multiple length scales established a framework necessary for a first approximations study in this new coal utilization approach.

01 COAL, LIGNITE, AND PEAT↗

U-net architected deep material network training with microstructure local field information

The Deep Material Network (DMN) has recently emerged as a powerful reduced-order modeling framework for simulating the mechanical response of heterogeneous materials such as composites. Unlike most data-driven approaches that directly learn a material’s response under prescribed loading, the DMN acts as a homogenization operator, learning the kinematic constraints and mechanical interactions of the underlying microstructure. However, traditional DMN training relies exclusively on homogenized effective properties derived from Direct Numerical Simulations (DNS), discarding the rich local field data that govern microstructural interactions. In this work, we extend the DMN framework to incorporate such local field information into the offline training process. Utilizing a U-Net architecture, we augment the DMN training objective to include the first and second statistical moments of the local stress fields obtained from linear DNS. This ensures that the learned network topology not only fits the effective stiffness but also accurately reflects the internal local stress and strain partitioning of the microstructure. The results confirm that supervising the localization process during training yields a superior surrogate model, reducing local prediction errors by an order of magnitude and significantly improving generalization to unseen nonlinear constitutive behaviors compared to traditional DMNs.

36 MATERIALS SCIENCE↗

Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy

Recent developments integrating micromechanics and neural networks offer promising paths for rapid predictions of the response of heterogeneous materials with similar accuracy as direct numerical simulations. The deep material network is one such approaches, featuring a multi-layer network and micromechanics building blocks trained on anisotropic linear elastic properties. Once trained, the network acts as a reduced-order model, which can extrapolate the material’s behavior to more general constitutive laws, including nonlinear behaviors, without the need to be retrained. However, current training methods initialize network parameters randomly, incurring inevitable training and calibration errors. Here, we introduce a way to visualize the network parameters as an analogous unit cell and use this visualization to “quilt” patches of shallower networks to initialize deeper networks for a recursive training strategy. The result is an improvement in the accuracy and calibration performance of the network and an intuitive visual representation of the network for better explainability.

97 MATHEMATICS AND COMPUTING↗

Nonempirical Range-Separated Hybrid Functional with Spatially Dependent Screened Exchange

Electronic structure calculations based on density functional theory (DFT) have successfully predicted numerous ground-state properties of a variety of molecules and materials. However, exchange and correlation functionals currently used in the literature, including semilocal and hybrid functionals, are often inaccurate to describe the electronic properties of heterogeneous solids, especially systems composed of building blocks with large dielectric mismatch. Here, in this study, we present a dielectric-dependent range-separated hybrid functional, screened-exchange range-separated hybrid (SE-RSH), for the investigation of heterogeneous materials. We define a spatially dependent fraction of exact exchange inspired by the static Coulomb-hole and screened-exchange (COHSEX) approximation used in many-body perturbation theory, and we show that the proposed functional accurately predicts the electronic structure of several nonmetallic interfaces, three- and two-dimensional, pristine, and defective solids and nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cambered Bipyridyl Ligand with Extended Aryl System Enables Electrochemical Reduction of Carbon Dioxide and Bicarbonate by Mn(bpy)(CO) 3 Br-type Catalyst Immobilized on Carbon Nanotubes

Heterogeneous materials containing molecular catalytic sites show promise for electrocatalytic reduction of CO 2 to energy-enriched carbon products. Interactions between the catalyst and the heterogeneous support increasingly are recognized as important in governing product selectivity and rate. Recent work on Mn(R-bpy)(CO) 3 Br type catalysts immobilized on multiwalled carbon nanotubes (MWCNT) demonstrated control of electrocatalytic behavior with steric modification of the molecular catalyst. Phenyl groups installed in the 4,4' positions of the bipyridine ligand (ph-bpy) maximized performance through π–π interactions with the MWCNT support. Herein we report the outcome of extending the ligand π system with Mn(nap-bpy)(CO) 3 Br (nap-bpy = 4,4'-di(naphthalen-1-yl)-2,2'-bipyridine) and Mn(pyr-bpy)(CO) 3 Br (pyr-bpy = 4,4'-di(pyren-1-yl)-2,2'-bipyridine) immobilized on MWCNT. We demonstrate exceptional electrocatalysis with Mn(nap-bpy)(CO) 3 Br/MWCNT (FE CO > 92%; J CO = 16.5 mA/cm 2 ) and find that this catalyst electrochemically reduces bicarbonate in the absence of deliberately added CO 2 at a remarkable overall selectivity of >80% for carbon products (FE HCOO – = 52% and FE CO = 29%). We show diminishing returns to simply adding aromatic character to the bipyridyl ligand with Mn(pyr-bpy)(CO) 3 Br/MWCNT and observe a unique cambering of the Mn(nap-bpy)(CO) 3 Br bipyridyl ligand that we believe enables selective catalysis. Mechanistic studies were carried out on Mn(nap-bpy)(CO) 3 Br/MWCNT using a novel thin-film infrared spectroelectrochemical (IR-SEC) technique. These experiments observe the immobilized Mn(nap-bpy)(CO) 3 Br undergo single electron reduction to a Mn-centered radical that binds CO 2 in a reduction-coupled process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Irradiation stability and thermomechanical properties of 3D-printed SiC

Neutron irradiation tests were carried out on 3D-printed SiC derived from binderjet additive manufacturing and chemical vapor infiltration. Irradiation was carried to 2.3 dpa over a temperature range of 400–850 °C. Anisotropy that had been observed in the thermal conductivity of 3D-printed SiC prior to irradiation vanished after irradiation as the irradiation defect thermal resistivity accumulated in the material. No degradation in strength was observed in the material before or after irradiation, at various temperatures, or in different orientations. Electron microscopy of the microstructure after neutron irradiation showed distinct defect morphologies in the heterogenous material, but no evidence for irradiation-induced cracking or degradation in the microstructure was observed.

36 MATERIALS SCIENCE↗

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.

Tabassum, Anika↗

P- and S-Wave velocity and Indirect Tensile Measurements for Alluvium in Support of the Source Physics Experiments

Mechanical properties on alluvium blocks and core samples were determined to support the Source Physics Experiment Dry Alluvium Geology experimental series. Because material was not available directly from the experimental location, the alluvium blocks and core samples are intended to serve as surrogate material . P - and S - wave velocity was measured on cubes cut from the alluvium blocks and core with the intention to study variation from water content and measured direction (material anisotropy). Indirect tensile tests were conducted dry and with moisture ranging from 6 to 9.1%. For the range of water content tested, increasing moisture level resulted in slower P - and S - wave velocities. P - and S - wave variability is less influenced by material heterogeneity than moisture content. P - wave velocity ranges from 629 m/s to 2599 m/s and S - wave velocity ranges from 288 m/s to 1200 m/s. Counter to the velocity measurement findings, material variability on indirect tensile strength has a greater effect than moisture content. Compared to dry strength and at moisture levels from 6 to 9% the block's tensile strength was lowered by at least a factor of 5. Indirect tensile strength for the first block averaged 0.35 MPa and 0.25 MPa for dry and 8.9% moisture respectively. For the second block indirect tensile strength averaged 0.05 MPa for both dry and 6.4% moisture.

36 MATERIALS SCIENCE↗

Electronic and Vibrational Coherence in Heterogeneous Electron Transfer (Final Report)

Interfacial electron transfer reactions constitute key physical phenomena central to a variety of energy related transport and conversion processes such as catalysis, photocatalysis, photovoltaics, energy storage, molecular electronics, etc. Heterogeneous material systems like organic/inorganic interfaces are of particular interest because they provide great potential to tailor properties according to application specific requirements. While electron transfer dynamics has been studied intensively in heterogeneous systems many questions remain unanswered. The significance of electronic-vibrational coupling and coherence is one aspect that has yet to be fully explored. The objective of this project is to develop and implement new ultrafast spectroscopic techniques based on pump four-wave mixing spectroscopy (pump-FWM) for studying the dynamics of vibrational coupling and coherence in heterogeneous electron transfer (HET) at molecule/semiconductor interfaces. The implementation of the spectroscopic setup allows to explore different four-wave mixing techniques and thus to identify a suitable approach to study the significance of vibrational as well as electronic coherence in HET.

14 SOLAR ENERGY↗

Role of Metal–Organic Framework Topology on Thermodynamics of Polyoxometalate Encapsulation

Polyoxometalates (POMs) are discrete anionic clusters whose rich redox properties, strong Brønsted acidity, and high availability of active sites poise them as potent catalysts for oxidation reactions. Here, metal–organic frameworks (MOFs) have emerged as tunable, porous platforms to immobilize POMs, thus increasing their solution stability and catalytic activity. While POM@MOF composite materials have been widely used for a variety of applications, little is known about the thermodynamics of the encapsulation process. Here, we utilize an up-and-coming technique in the field of heterogeneous materials, isothermal titration calorimetry (ITC), to obtain full thermodynamic profiles (ΔH, ΔS, ΔG, K a ) of POM binding. Six different 8-connected hexanuclear Zr-MOFs were investigated to determine the impact of MOF topology (csq, scu, the) on POM encapsulation thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Compositionally graded aluminum-silicon alloy fabricated via friction extrusion

Herein, a novel solid-phase gradient alloying technique was developed for a high throughput composition-microstructure-mechanical property assessment. Friction extrusion of a two-piece billet setup facilitated the formation of a seamless compositionally graded aluminum (Al)-silicon (Si) extrudate rod, with Si concentration in Al matrix gradually increasing from ~1 at% at one end to ~7 at% at the other end of the rod. We observed a strong dependence of the Al grain size, morphology, and texture on the Si concentration. The Si particles pinned the recrystallized grain boundaries resulting in refined (< 10 µm) and textured grains in the high Si content region, while the Al grains in the low Si region are equiaxed, randomly textured, and with a larger average size (~50 µm). The hardness of Al-Si gradient extrudate increases by ~50% percent with a 6 at% increase in Si content due to Hall Petch and particle strengthening effects. Our approach demonstrates the use of a solid phase processing technique to successfully produce a defect-free continuously compositionally graded bulk components thus overcoming the limitations of porosity and material heterogeneities commonly observed in other techniques such as by additive laser deposition.

36 MATERIALS SCIENCE↗

Safely probing the chemistry of Chernobyl nuclear fuel using micro-focus X-ray analysis

Detailed chemical analysis of the solidified molten fuel still residing in the stricken Chernobyl reactor unit 4 are inferred using multi-modal micro-focus X-ray analysis of a low-radioactivity proxy. A fascinating mixture of molten UO 2 , nuclear fuel cladding, concrete, stainless steel and other nuclear reactor components, these materials behaved like lava, solidifying to form a complex, highly radioactive glass-ceramic. Using element-specific chemical probes (micro-X-ray fluorescence and X-ray absorption spectroscopy), coupled with micro-diffraction analysis, the crystalline phase assemblage of simulants of these heterogeneous materials was established, which included “chernobylite” and a range of compositions in the (U 1-x Zr x )O 2 solid solution. Novel insight to nuclear accident fuel chemistry was obtained by establishing the oxidation state and local coordination of uranium not only in these crystalline phases, but uniquely in the amorphous fraction of the material, which varied depending on the history of the nuclear lava as it flowed through the reactor. This study demonstrates that micro-focus X-ray analysis of very small fractions of material can yield rich chemical information, which can be applied to nuclear-melt down materials to aid decommissioning and nuclear fuel management at nuclear accident sites.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Investigation of Molecular Diffusion at Block Copolymer Thin Films Using Maximum Entropy Method-Based Fluorescence Correlation Spectroscopy and Single Molecule Tracking

Fluorescence correlation spectroscopy (FCS) has been widely used to investigate molecular diffusion behavior in various samples. The use of the maximum entropy method (MEM) for FCS data analysis provides a unique means to determine multiple distinct diffusion coefficients without a priori assumption of their number. Comparison of the MEM-based FCS method (MEM-FCS) with another method will reveal its utility and advantage as an analytical tool to investigate diffusion dynamics. Herein, we measured diffusion of fluorescent probes doped into nanostructured thin films using MEM-FCS, and validated the results with single molecule tracking (SMT) data. The efficacy of the MEM code employed was first demonstrated by analyzing simulated FCS data for systems incorporating one and two diffusion modes with broadly distributed diffusion coefficients. The MEM analysis accurately afforded the number of distinct diffusion modes and their mean diffusion coefficients. These results contrasted with those obtained by fitting the simulated data to conventional two-component and anomalous diffusion models, which yielded inaccurate estimates of the diffusion coefficients. Subsequently, the MEM analysis was applied to FCS data acquired from hydrophilic dye molecules incorporated into microphase-separated polystyrene-block-poly(ethylene oxide) (PS-b-PEO) thin films characterized under a water-saturated nitrogen atmosphere. The MEM analysis revealed distinct fast and slow diffusion components attributable to molecules diffusing on the film surface and inside the film, respectively. SMT studies of the same materials yielded trajectories for mobile molecules that appear to follow the curved PEO microdomains. Diffusion coefficients obtained from the SMT data were consistent with those obtained for the slow diffusion component detected by MEM-FCS. Furthermore, these results highlight the utility of MEM-FCS and SMT for gaining complementary information on molecular diffusion processes in heterogeneous material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗