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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Theoretical study of production of unique glasses in space

The potential of producing the glassy form of selected materials in the weightless, containerless nature of space processing is examined through the development of kinetic relationships describing nucleation and crystallization phenomena. Transformation kinetics are applied to a well-characterized system (SiO2), an excellent glass former (B2O3), and a poor glass former (Al2O3) by conventional earth processing methods. Viscosity and entropy of fusion are shown to be the primary materials parameters controlling the glass forming tendency. For multicomponent systems diffusion-controlled kinetics and heterogeneous nucleation effects are considered. An analytical empirical approach is used to analyze the mullite system. Results are consistent with experimentally observed data and indicate the promise of mullite as a future space processing candidate.

Larsen, D. C.↗
DOE OSTI2021

FY21 Status Report on the Molten Salt Thermal Properties Database (MSTDB) Development

This report describes the thermodynamic assessments for the ZrF 4 -BeF 2 , AlCl 3 -NaCl, AlCl3-KCl and the PuCl 3 -CsCl pseudo-binary subsystems. Calculation results are compared to the inputs used to optimize the adjustable model parameters. The data came from experimental studies reported in the open literature, from the MSR research community, and/or computational results generated within the NEAMS program and from collaborators. The models from the thermodynamic assessment of these salt systems are integrated into the MSTDB-TC (Molten Salt Thermal Properties Database-Thermochemical). A brief description of the companion MSTDB-TP (Molten Salt Thermal Properties Database-Thermophysical) is given along with an overview of the approach for predicting both thermodynamic and thermophysical property behavior of multicomponent systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Modeling of Multicomponent Trace Contaminant Adsorption on Activated Carbon

Modeling of multicomponent trace contaminant adsorption on activated carbon for spacecraft life support applications presents challenges due to the very low contaminant concentrations in cabin air coupled with very strong adsorption of heavier components such as cyclic polydimethylsiloxanes. Both gas-phase and solid-phase micropore mass transfer resistances can be important, and competitive interactions between adsorbed components can result in behavior such as roll-up where lighter components displaced by heavier components have a higher concentration at the outlet than at the inlet. This paper describes the further development of a dynamic trace contaminant adsorption model based on Ideal Adsorbed Solution Theory (IAST). Alternative 1-dimensional and 2-dimensional versions of the model are described with different mass transfer resistance and driving force assumptions. Optimization of solution methods for speed and stability is also described. Mass balance equations are scaled to provide sensitivity over the wide range of component concentrations in cabin air. Model parameters are estimated from isotherm and breakthrough test data on single adsorbate and binary adsorbate systems. Multicomponent results are compared against predictions of a heritage model used extensively by NASA for trace contaminant control system (TCCS) carbon bed sizing. Finally, efforts to implement the model in a second software platform for wider access are described.

Kevin E Lange↗
DOE OSTI2020

Computational thermodynamics and its applications

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or un- stable, when interacting with the surroundings. In this overview, fundamentals of thermodynamics are briefly reviewed through the combination of first and second laws of thermodynamics for open and nonequilibrium systems to demonstrate that the reversible equilibrium and irreversible nonequilibrium thermodynamics can be integrated to enhance the power and utilities of thermodynamics. The recent progresses in computational thermodynamics, the remaining challenges, and potential impacts in broad scientific fields are discussed here. It is shown that computational thermodynamics enables the modeling of thermodynamics of a state as a function of both external and internal variables and quantitative calculations of a broad range of properties of a multicomponent system in terms of first and second derivatives of energy, including not only equilibrium states when there are no driving forces for any internal processes and but also non-equilibrium states with driving forces for internal processes. Consequently, external constraints such as fixed strain and internal degree of freedoms such as ordering and defects can be described in a coherent framework and applied to materials design. Furthermore, two important but largely overlooked aspects in thermodynamics will be discussed, i.e. the rigorous application of statistical thermodynamics with the probability of configurations and their contributions to system properties, and the applications of second derivatives of energy with respect to either two extensive variables or two potentials or a mixture of them in terms of understanding and predicting emergent behaviors, critical phenomena, kinetic coefficients, and mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Inverse Thermodynamics: Designing Interactions for Targeted Phase Behavior

The traditional goal of inverse self-assembly is to design interactions that drive particles toward a desired target structure. However, achieving successful self-assembly also requires tuning the thermodynamic conditions under which the structure is stable. In this work, we extend the inverse design paradigm to explicitly address this challenge by developing a framework for inverse thermodynamics, i.e., the design of interaction potentials that realize specific thermodynamic behavior. As a step in this direction, using patchy particle mixtures as a model system, we demonstrate how precise control over both bonding topology and bond energetics enables the programming of targeted phase behavior. In particular, we establish design principles for azeotropic demixing and show how to create mixtures that exhibit azeotropy at any prescribed composition. Our predictions are validated through Gibbs-ensemble simulations [Panagiotopoulos, Mol. Phys. 1987, 61, 813−826]. These results highlight the necessity of coupling structural design with thermodynamic engineering, and provide a blueprint for controlling complex phase behavior in multicomponent systems.

Azeotropes↗
NASA NTRS2000

Onset of Convection Due to Surface Tension Variations in Multicomponent and Binary Fluid Layers

Under certain conditions, such as in thin liquid films or microgravity, surface tension variations along a free surface can induce convection. Convection onset due to surface tension variation is important to many terrestrial technological processes in addition to microgravity materials processing applications. Examples include coating, drying crystallization, solidification, liquid surface contamination, and containerless processing. In double-diffusive and multicomponent systems, the spatial variations of surface tension are associated with two or more stratifying agencies, respectively. For example, both temperature and species (concentration) gradients are associated with convection in the solidification of binary alloys or salt ponds. The direction of the two (or more) gradients has a profound effect on the nature of the flow at or slightly beyond the onset of convection. Our recent work at the NASA Lewis Research Center focused on characterizing surface-tension-induced onset of convection, often referred to as Marangoni-Benard convection. Exact solutions for the stationary neutral stability of multicomponent fluid layers with interfacial deformation were derived. These solutions also permit the computation of a boundary curve that separates the long and finite wavelength instabilities. Computing points along this boundary using the exact solution (when possible) is more efficient than the typical numerical approaches, such as finite difference or spectral methods. Above the curve, a long wavelength instability was predicted, suggesting that convection would occur principally through one large flow cell in the layer, whereas below the curve, finite wavelength instabilities occur which suggest multiple finite-sized circulation cells. For many common liquids with layer depths greater than 100 mm, finite wave instability is predicted under terrestrial conditions; however, with little exception, long wavelength instability is predicted in microgravity for the identical fluid systems.

Skarda, J. Raymond Lee↗
DOE OSTI2022

Element-specific first order reversal curves measured by magnetic transmission x-ray microscopy

The first-order reversal curve (FORC) method is a macroscopic measurement technique that can be used to extract quantitative and microscopic properties of hysteretic systems. Using magnetic transmission x-ray microscopy (MTXM), local element-specific FORC measurements are performed on a 20 nm thick film of CoTb. The FORCs measured with microscopy reveal a step-by-step domain evolution under the magnetic field cycling protocol and provide a direct visualization of the mechanistic interpretation of FORC diagrams. They are compared with magnetometry FORCs and show good quantitative agreement. Furthermore, the high spatial resolution and element-specific sensitivity of MTXM provide new capabilities to measure FORCs in small regions or specific phases within multicomponent systems, including buried layers in heterostructures. The ability to perform FORCs on very small features is demonstrated with the MTXM-FORC measurement of a rectangular microstructure with vortex-like Landau structures. This work demonstrates the confluence of two uniquely powerful techniques to achieve quantitative insight into nanoscale magnetic behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Revisit the VEC criterion in high entropy alloys (HEAs) with high-throughput ab initio calculations: A case study with Al-Co-Cr-Fe-Ni system

Valence electron concentration (VEC) was treated as a useful parameter to predict the stability of solid solution phases. However, the available experimental data to support this criterion is far from enough. In the current study, the high-throughput ab initio modeling is applied to investigate the relative stability of FCC and BCC single crystals of the Al-Co-Cr-Fe-Ni high entropy alloys (HEAs) by using the special quasi-random structure (SQS) approach. Furthermore, the predictions start with pure elements of the Al-Co-Cr-Fe-Ni system and are continued with binaries, ternaries, and quaternary compositions, which come up with 180 compositions (360 structures). After that, the reliability of the VEC criterion is testified. The results show that the VEC criterion not only works for the stable structure but also works effectively for metastable structure when both FCC and BCC are not thermodynamic stable. However, it is found that the old VEC criterion proposed by Guo et al. fails to work effectively for compositions containing high concentrations of light-weight metals such as Al at VEC<5. To solve this problem, the present work proposes a new VEC rule to define the stability of FCC and BCC structures at the ground state. With the implementation of the new VEC rule, the effectiveness of the VEC rule (EVEC) of both FCC and BCC structures is enhanced, especially for pure elements and binary compositions, indicating that this rule does not only work effectively for multicomponent systems but also works for low-order systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bridging confined phase behavior of CH 4 -CO 2 binary systems across scales

Phase behavior of confined fluids may deviate significantly from that of the bulk fluid due to the fluid-wall interactions being a significant portion of all intermolecular interactions under confinement. Despite recent advancements in understanding confined phase behavior of pure fluids, confined phase behavior of mixtures remains an understudied topic. In this work, we examine the confined phase behavior of a CH 4 -CO 2 binary system by combining Monte Carlo (MC) simulations, a cubic equation of state (EoS), and the lattice Boltzmann method (LBM). First, the effects of confinement on density and phase distribution in nano-size pores are established using Gibbs Ensemble MC calculations, which produce precise results of liquid and vapor confined pressures and account for the modification of the phase change location. By comparing the phase envelopes of bulk and confined mixtures at a fixed temperature, here it is observed that the phase envelopes shrink with reductions in pore size. Based on this observation, we extend a modified Peng-Robinson EoS, which was originally developed for pure fluids under confinement, to mixtures via van-der-Waals-type mixing rules and by accounting for shifts in the critical properties of confined CH 4 -CO 2 . The resulting phase envelopes are in good agreement with the MC data. In addition, a local density model is used in combination with the confined EoS to calculate adsorption isotherms of CH 4 -CO 2 mixtures and to characterize the behavior of confined matter in nanopores. Finally, we incorporate this EoS in a multicomponent multiphase LBM that uses a pseudopotential model to represent intermolecular forces. This workflow utilizes multiscale simulation techniques to bridge the behavior of multicomponent systems across scales and to shed light on the confined phase behavior of CH 4 -CO 2 binary systems.

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

Nanoscale and Element-Specific Lattice Temperature Measurements Using Core-Loss Electron Energy-Loss Spectroscopy

Measuring nanoscale local temperatures, particularly in vertically integrated and multicomponent systems, remains challenging. Spectroscopic techniques like X-ray absorption and core-loss electron energy-loss spectroscopy (EELS) are sensitive to lattice temperature, but understanding thermal effects is nontrivial. This work explores the potential for nanoscale and element-specific core-loss thermometry by comparing the Si L2,3 edge’s temperature- dependent redshift against plasmon energy expansion thermometry (PEET) in a scanning TEM. Using density functional theory (DFT), time-dependent DFT, and the Bethe−Salpeter equation, we ab initio model both the Si L 2,3 and plasmon redshift. We find that the core-loss redshift occurs due to bandgap reduction from electron−phonon renormalization. Our results indicate that despite lower core-loss signal intensity compared to plasmon features, core-loss thermometry has key advantages and can be more accurate through standard spectral denoising. Specifically, we show that the Varshni equation easily interprets the core-loss redshift for semiconductors, which avoids plasmon spectral convolution for PEET in complex junctions and interfaces. We also find that core-loss thermometry is more accurate than PEET at modeling thermal lattice expansion in semiconductors, unless the specimen’s temperature-dependent dielectric properties are fully characterized. Furthermore, core-loss thermometry has the potential to measure nanoscale heating in multicomponent materials and stacked interfaces with elemental specificity at length scales smaller than the plasmon’s wave function.

Bethe–Salpeter equation↗
DOE OSTI2026

Thermal Gradient Effects on Redox Evolution and Volatility-Driven Fractionation in Ternary U/Ce/Cs Condensates

Understanding how thermal history influences redox evolution and chemical fractionation is essential for characterizing high-temperature condensation in complex materials, including nuclear debris. Here, we tested the hypothesis that distinct thermal regimes in a plasma flow reactor influence redox pathways and elemental partitioning in ternary U/Ce/Cs systems. A configurable plasma flow reactor was modified with an external tube furnace to impose two distinct thermal gradients: continuous ambient cooling and a furnace-assisted thermal hold-up near 1400 K followed by rapid cooling. Transmission electron microscopy characterized phase identity, morphology, and nanoscale element distributions, while inductively coupled plasma-mass spectrometry quantified bulk elemental ratios. Across both thermal regimes, uranium and cerium condensed as UO 2 and CeO 2 as dominant refractory oxide products. Uranium partially oxidized to α-UO 3 during extended ambient cooling, while furnace-assisted hold-up preserved UO 2 and produced partial reduction of cerium to Ce 2 O 3 . Cesium remained volatile upstream and condensed later in the reactor, forming Cs 2 O and Cs-uranate phases with the highest incorporation after thermal hold-up. Bulk ICP-MS measurements supported these observations. U/Ce ratios remained comparatively stable and Cs displayed delayed and apparent transient enrichment that matched the nanoscale measurements. This integrated approach provides a quantitative method for linking thermal gradients to redox evolution and volatility-driven fractionation. These results show how the plasma flow reactor can identify where equilibrium descriptions remain adequate and where kinetic effects from residence time and temperature history must be considered when interpreting condensation behavior in multicomponent systems.

and nuclear chemistry↗
DOE OSTI2020

Multiscale Understanding and Architecture Design of High Energy/Power Lithium-Ion Battery Electrodes

Among various commercially available energy storage devices, lithium-ion batteries (LIBs) stand out as the most compact and rapidly growing technology. This multicomponent system operates on coupled dynamics to reversibly store and release electricity. With the hierarchical electrode architectures inside LIBs, versatile functionality can be realized by design, while considerable difficulties remain to be solved to fully exploit the capability of each constituent. With the rapid electrification of the transportation sector and an urgent need to overhaul electric grids in the context of renewable energy penetration, demands for concomitant high energy and high power batteries are continuously increasing. Although building an ideal battery requires effort from multiple scientific and engineering aspects, it is imperative to gain insight into multiscale transport behaviors arising in both spatial and temporal dimensions, and enable their harmonic integration inside the whole battery system. In this progress report, recent research efforts on characterizing and understanding transport kinetics in LIBs are reviewed covering a broad range of electrode materials and length scales. Further, to demonstrate the crucial role of such information in revolutionary electrode design, examples of innovative high energy/power electrodes are provided with their unique hierarchical porous architectures highlighted. To conclude, perspectives on further approaches toward advanced thick electrode designs with fast kinetics and tailored properties are discussed.

25 ENERGY STORAGE↗
DOE OSTI2022

Characterizing the Geometry and Quantifying the Impact of Nanoscopic Electrocatalyst/Semiconductor Interfaces under Solar Water Splitting Conditions

The materials that are receiving the most attention in photoelectrochemical water splitting are metallic nanoparticle electrocatalysts (np-EC) attached to the surface of a semiconductor (SC) light absorber. In these multicomponent systems, the interface between the semiconductor and electrocatalysts critically affects performance. However, the np-EC/SC interface remains poorly understood as it is complex on atomic scales, dynamic under reaction conditions, and inaccessible to direct experimental probes. This contribution sheds light on how the electrocatalyst/semiconductor interface evolves under reaction conditions by investigating the behavior of nickel electrocatalysts (as nanoparticles and films) deposited on silicon semiconductors. Rigorous electrochemical experiments, interfacial atomistic characterization, and computational modeling are combined to demonstrate critical links between the atomistic features of the interface and the overall performance. It is shown that electrolyte-induced atomistic changes to the interface lead to (1) modulation of the charge carrier fluxes and a dramatic decrease in the electron/hole recombination rates and (2) a change in the barrier height of the interface. Additionally, the critical roles of nonidealities and electrocatalyst coverage due to interfacial geometry are explored. Each of these factors must be considered to optimize the design of metal/semiconductor interfaces which are broadly applicable to photoelectrocatalysis and photovoltaic research.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A thermochemical database from high-throughput first-principles calculations and its application to analyzing phase evolution in AM-fabricated IN718

A comprehensive thermochemical database is constructed based on high–throughput first-principles phonon calculations of over 3000 atomic structures in limited concentrations in Ni, Fe, and Co alloys involving a total of 26 elements including Al, B, C, Cr, Cu, Hf, La, Mn, Mo, N, Nb, O, P, Re, Ru, S, Si, Ta, Ti, V, W, Y, and Zr, providing thermochemical data largely unavailable from existing experiments. Here, the database can be employed to predict the equilibrium phase compositions and fractions directly from first-principles by minimizing the chemical potential of a multicomponent system with a fixed overall chemical composition and a fixed temperature. It is applied to the additively manufactured nickel-based IN718 superalloy to analyze the phase evolution with temperature. IN718 is known for its great performance in tensile, fatigue, creep, and rupture strength, combined with easy fabrication and corrosion resistance. In particular, we successfully predicted the formation of L1 0 -FeNi, γ’-Ni 3 (Fe,Al), α-Cr, δ-Ni 3 (Nb,Mo), γ”-Ni 3 Nb, and η-Ni 3 Ti at low temperatures (below 680 K), γ’-Ni 3 Al, δ-Ni 3 Nb, γ”-Ni 3 Nb, α-Cr, and γ-Ni(Fe,Cr,Mo) at intermediate temperatures (between 680 and 1140 K), and δ-Ni 3 Nb and γ-Ni(Fe,Cr,Mo) at high temperatures (above 1140 K) in IN718. These predictions are validated by EDS mapping of compositional distributions and corresponding identifications of phase distributions. The database is expected to be a valuable source for future thermodynamic analysis and microstructure prediction of alloys involving the 26 elements.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A modified scheil approach for nucleation-dependent solidification pathways

As-solidified microstructures of near-eutectic alloys often contain multiple primary phases that are not expected from equilibrium phase diagrams. Such microstructures are caused by cooling-rate-dependent solidification pathways, a factor not captured by the Scheil–Gulliver model or variations thereof. Here, we present a model and algorithm that incorporate the critical nucleation undercooling for each solid phase into the Scheil–Gulliver model. We hypothesize that the non-equilibrium microstructure formation is primarily governed by a nucleation-competition mechanism. This mechanism accounts for both stable/metastable phase selection and primary-phase formation within eutectic regions driven by asymmetric nucleation barriers. The model is validated against a hypereutectic Al-Fe alloy, where it successfully reproduces the observed microstructural constituents, revealing the key dependencies of solidification microstructure on nucleation kinetics. Applicability to multicomponent systems is demonstrated through a hypereutectic Al–Fe–Si ternary alloy, where the model successfully predicts divorced eutectic microstructures and the associated oscillatory solidification pathways along univariant lines. As a result, the proposed framework establishes a nucleation-dependent computational approach for interpreting and predicting solidification microstructures.

Alloy design↗
DOE OSTI2020

Dynamics of polymer segments, polymer chains, and nanoparticles in polymer nanocomposite melts: A review

The addition of nanoparticles (NPs) to a polymer matrix, forming a polymer nanocomposite (PNC), is known to alter the microscopic dynamic processes of both species which leads to unique macroscopic material properties of the PNC. Because the NPs and polymers have overlapping characteristic length, time, and energy scales, the interactions within these materials are complex and the dynamics are interrelated. In this review, we present an overview of experimental, simulation, and theoretical results that probe multi-scale polymer and nanoparticle dynamics in polymer nanocomposites and navigate the dense parameter space presented by these multicomponent systems. Although a variety of PNC systems are mentioned, we focus this discussion on linear thermoplastics filled with hard spherical or cylindrical NPs in the melt state. We begin by introducing PNCs, the dynamic processes within them, and the importance of dynamics for properties and processing. At the smallest length and time scales, we discuss segmental dynamics in PNCs, including the role of polymer attributes, NP attributes, and NP-polymer interactions. Then, we present measurements of collective motions and intermediate (Rouse) dynamics in various PNC materials. At longer length and time scales, we discuss polymer center-of-mass diffusion in PNCs with either spherical or anisotropic NPs. We then explore the dynamics of the NPs in PNCs and polymer melts, including theoretical predictions, simulation results, and experimental observations. Lastly, we note some of the remaining challenges in probing dynamics in PNC materials and fundamentally studying PNCs more generally.

36 MATERIALS SCIENCE↗