High-Toughness Inorganic Solid Electrolytes via the Use of Reduced Graphene Oxide
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This work investigates the role of a carbon nanophase on the local mechanical behavior of nanocarbon metal matrix composites (NCMCs) produced through an electrocharge-assisted process. Nanoindentation experiments on single crystal Al, Al 1350 parent alloys, and Al 1350 NCMCs revealed variable mechanical properties, caused by an interplay between microstructure and graphitic reinforcements. TEM and AFM studies also reveal nanoscale structural changes based on the incorporation of a carbon nanophase. In order to decouple the effects of the aforementioned mechanical behaviors, molecular dynamics nanoindentation simulations were performed on the (111) surface of Al and Al NCMC samples containing semi-infinite graphene nanoribbons to examine the evolution of plasticity over time. Findings indicate that the arrangement of a finite graphene nanophase within a host matrix can alter plasticity mechanisms and therefore yield strength in near-surface mechanical behavior with little effect on elastic properties. Here, this understanding enables further study into tunable bulk properties of Al-based NCMCs while isolating microstructural effects and reinforcement effects of the carbon phase. Such an understanding will lead to application-specific material geometries ranging from highperforming vehicle structures to next-generation electrical devices.
With increased energy density and cost advantage, ultrahigh-nickel layered oxides (LiNi x M 1-x O 2 , x = 0.9 - 1.0) are becoming front-runner as cathodes for next-generation lithium-based batteries, yet their commercialization is blocked both by severe capacity fade and exponentially aggravated air degradation. Thus, it is imperative to find effective solutions to address these issues simultaneously. Here, a significant enhancement in both the cycling and air storage stability of the ultrahigh-Ni cathode LiNi 0.94 Co 0.06 O 2 is achieved via a distinctive phosphoric acid treatment strategy. The modified cathode displays remarkably improved capacity retention (from 36 % to 80 % after 1,000 cycles) and rate capability (from 0 to 105 mA h g -1 at 30C rate) in pouch cells. Impressively, the modified cathode, after air storage for 450 days, maintains the morphology and 92% of the initial capacity of the fresh sample with excellent cyclability. Comprehensive interphase and structural analyses reveal that the enhanced electrochemical performance is due to a highly stabilized electrode/electrolyte interphase that suppresses electrode corrosion and lattice reconstruction. The excellent air stability results from an adsorption-buffering effect enabled by phosphoric acid to air attack. Finally, the study demonstrates an engineering pathway to improve the cycling and air stability, facilitating the practical viability of high-capacity, affordable, ultrahigh-Ni cathodes in lithium-based batteries.
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Recent experimental and simulation studies have shown that polymer–nanoparticle (NP) composites (PNCs) with ultra-high NP loading (>50%) exhibit remarkable mechanical properties and dramatic increases in polymer glass-transition temperature, viscosity, and thermal stability compared to the bulk polymer. These deviations in macroscopic properties suggest a slowdown in both segmental and chain-scale polymer dynamics due to confinement. In this work, we examine the polymer conformations and dynamics in these PNCs using molecular dynamics simulations of both unentangled and entangled coarse-grained polymers in random-close-packed NP packings with varying polymer fill fractions. We find that the changes in the polymer dynamics depend on the number of NPs in contact with a polymer segment. Using the number of polymer–NP contacts and different polymer chain conformations as criteria for categorization, we further examine the polymer dynamics at multiple length scales to show the high level of dynamic heterogeneity in PNCs with ultra-high NP loading.
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Polymer nanoparticle composites (PNCs) with ultrahigh loading of nanoparticles (NPs) (>50%) have been shown to exhibit markedly improved strength, stiffness, and toughness simultaneously compared to the neat systems of their components. Recent experimental studies on the effect of polymer fill fraction in these highly loaded PNCs reveal that even at low polymer fill fractions, hardness and modulus increase significantly. In this work, we aim to understand the origin of these performance enhancements by examining the dynamics of both polymer and NPs under tensile deformation. We perform molecular dynamics simulations of coarse-grained, glassy polymer in random-close-packed NP packings with a varying polymer fill fraction. We characterize the mechanical properties of the PNC systems, compare the NP rearrangement behavior, and study the polymer segmental and chain-level dynamics during deformation below the polymer glass transition. Finally, our simulation results confirm the experimentally observed increase in modulus at low polymer fill fractions, and we provide evidence that the source of mechanical enhancement is the polymer bridging effect.
Nanoparticle-embedded plastic scintillators are an emerging technology for fast, large-area, high-resolution radiation detection and imaging. Here, this study investigates the properties of such composites, focusing on the effects of the quantum dot (QD) concentration on the radioluminescence (RL) intensity, spectra, and dynamics. Experiments using CdSe/CdS QDs in a polymer reveal a superlinear increase in RL with the QD concentration despite optical losses from inner filtering and interparticle interactions. When corrected for inner filtering, RL shows a quadratic concentration dependence, consistent with simple analytical models of improving the secondary electron capture. Practically, the benefits of high QD concentrations are muted by optical losses, but the findings apply to other systems with insulating hosts. In addition to manipulating emission for large effective Stokes shifts, future improvements may come from hosts with higher stopping power and better charge transport, which enable more effective funneling of excitations but without concomitant optical losses associated with high nanoparticle concentrations.
An unprecedented four-dimensional (4D) printing process allowing high-performance and shape memory thermoset to be printed, for the first time, by fused deposition modeling (FDM) with isotropic properties has been achieved. Here, bisphenol A-based epoxy and benzoxazine were formulated to a low-temperature thermoplastic and high-temperature thermoset resin, which is melt-extrudable and can be postcured into covalently cross-linked material. Carbon nanotube (CNT) was added in the resin to work as both mechanical enhancement filler and rheology modifier to prevent shape deformation during postcuring process. The cross-layer reaction fuses individual layers into an integrity, thus eliminating layer delamination induced by FDM, offering isotropic mechanical properties regardless of the printing orientations. The highly cross-linked network provides outstanding mechanical strength and superb thermal stability. The excellent shape memory performance with fast recovery rate and large recovery degree is also obtained in the three-dimensional (3D) printed composites.
The underlying microscopic response of filler networks in reinforced rubber to dynamic strain is not well understood due to the experimental difficulty of directly measuring filler network behavior in samples undergoing dynamic strain. This difficulty can be overcome with in situ X-ray photon correlation spectroscopy (XPCS) measurements. The contrast between the silica filler and the rubber matrix for X-ray scattering allows us to isolate the filler network behavior from the overall response of the rubber. This in situ XPCS technique probes the microscopic breakdown and reforming of the filler network structure, which are responsible for the nonlinear dependence of modulus on strain, known in the rubber science community as the Payne effect. These microscopic changes in the filler network structure have consequences for the macroscopic material performance, especially for the fuel efficiency of tire tread compounds. In this work, we elucidate the behavior with in situ dynamic strain XPCS experiments on industrially relevant, vulcanized rubbers filled (13 vol %) with novel air-milled silica of ultrahigh-surface area (UHSA) (250 m 2 /g). The addition of a silane coupling agent to rubber containing this silica causes an unexpected and counterintuitive increase in the Payne effect and decrease in energy dissipation. For this rubber, we observe a nearly two-fold enhancement of the storage modulus and virtually equivalent loss tangent compared to a rubber containing a coupling agent and conventional silica. Interpretation of our in situ XPCS results simultaneously with interpretation of traditional dynamic mechanical analysis (DMA) strain sweep experiments reveals that the debonding or yielding of bridged bound rubber layers is key to understanding the behavior of rubber formulations containing the silane coupling agent and high-surface area silica. These results demonstrate that the combination of XPCS and DMA is a powerful method for unraveling the microscale filler response to strain which dictates the dynamic mechanical properties of reinforced soft matter composites. With this combination of techniques, we have elucidated the great promise of UHSA silica when used in concert with a silane coupling agent in filled rubber. Such composites simultaneously exhibit large moduli and low hysteresis under dynamic strain.
Here we report a facile method to produce isolatable hollow-core elastomeric vesicles, “nanoballoons”, prepared via block copolymer self-assembly in a polymer blend. Poly(isoprene-block-dimethylsiloxane) (PI-PDMS) diblock copolymers are blended with PDMS homopolymers (h-PDMS) as a “solvent” phase to template the self-assembly of PDMS-tethered vesicles with PI walls. The walls are subsequently crosslinked to yield mechanically stabilized elastomeric vesicles. The h-PDMS inner-core and matrix are separated from the vesicles by dialysis to yield the matrix-free nanoballoons. These objects, 0.3 – 1 μm in diameter, can be further reincorporated into a crosslinkable PDMS. Throughout the self-assembly, recovery, and reincorporation processes we apply several techniques including solvent dispersion/dynamic light scattering (DLS) measurements, transmission electron microscopy (TEM)/energy-dispersive X-ray spectroscopy (EDS), and small-angle X-ray scattering (SAXS) to provide a consilient body of evidence that the nanoballoon morphology is retained. Furthermore, this work presents advanced nanomanufacturing schema that illustrate the decoupling of the thermodynamic and dynamic factors that govern macromolecular self-assembly from the environment in which the self-assembled objects are deployed.
The remarkable defect tolerant nature of inorganic cesium halide perovskites leading to near unity photoluminescence (PL) quantum yield (QY) and narrow emission linewidth across the entire visible spectrum, have provided a tantalizing platform for a development of a plethora of light-emitting applications. Recently, lower dimensional (2D, 1D, and 0D) perovskites have attracted further attention due to the enhanced thermal, photo and chemical stability as compared to their three-dimensional (3D) analogues. Combination of the external size quantization and internal octahedral organization provides a unique opportunity to study and harness “multidimensional” electronic properties engineered both on atomic scale and the nanoscale. However, crucial research to understand the elementary charge carrier dynamics in lower dimensional perovskites lags far behind the enormous effort to incorporate them into optoelectronic devices. In this Perspective, we provide a review of recent developments that focus on studies of the dynamics of excitonic complexes in Cs-based perovskite nanocrystals using single-particle time-resolved PL spectroscopy and photon correlation measurements. Single photon statistical studies not only offer the unprecedented level of detail to directly assess various recombination pathways but also provide insights into specifics of carrier’s localization. Further, we discuss the underlying physicochemical processes that govern PL emission and draw attention to a number of attributes within this class of the materials, especially lower-dimensional perovskites that may indicate the common origin of the PL emission, as well as provide a route map for the vast unexplored territories where single particle spectroscopy can be a powerful tool to unravel crucial information.
Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend’s composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.
Cellulose nanofibrils (CNF) with 2D silicate nanoplatelet reinforcement readily form multifunctional composites by vacuum-assisted self-assembly from hydrocolloidal mixtures. The final nanostructure is formed during drying. The crystalline nature of CNF and montmorillonite (MTM) made it possible to use synchrotron X-ray scattering (WAXS, SAXS) to monitor structural development during drying from water and from ethanol. Nanostructural changes in the CNF and MTM crystals were investigated. Changes in the out-of-plane orientation of CNF and MTM were determined. Residual drying strains previously predicted from theory were confirmed in both cellulose and MTM platelets due to capillary forces. The formation of tactoid platelet stacks could be followed. We propose that after filtration, the constituent nanoparticles in the swollen, solid gel already have a “fixed” location, although self-assembly and ordering processes take place during drying.
Polymer-grafted nanoparticles (PGNPs) represent a versatile class of hybrid nanomaterials, in which nanoparticle cores and tethered polymer coronas are integrated into structurally programmable building blocks. Rapid advances in nanoparticle surface functionalization and surface-initiated polymerization have enabled increasingly precise control over the nanoparticle core composition and brush architecture, greatly expanding the accessible structural and functional landscape of PGNPs. This review summarizes recent progress in the modular design and structural regulation of PGNPs, with an emphasis on nanoparticle platforms and associated surface functionalization strategies, polymer brush synthesis and architectural control, and the structure−property relationships that govern PGNP behavior. Emerging applications are further highlighted, including additive manufacturing, self-healing materials, membrane-based gas separations, and battery-related systems, where PGNPs provide unique opportunities to couple nanoscale interfacial design with macroscopic performance. Finally, future opportunities are discussed for extending PGNP concepts to increasingly complex, multifunctional, and application-oriented hybrid materials.
Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.