Understanding creep suppression mechanisms in polymer nanocomposites through machine learning.

While recent efforts have shown how local structure plays an essential role in the dynamic heterogeneity of homogeneous glass-forming materials, systems containing interfaces such as thin films or composite materials remain poorly understood. It is known that interfaces perturb the molecular packing nearby, however, numerous studies show the dynamics are modified over a much larger range. Here, we examine the dynamics in polymer nanocomposites (PNCs) using a combination of simulations and experiments and quantitatively separate the role of polymer packing from other effects on the dynamics, as a function of distance from the nanoparticle surfaces. After showing good qualitative agreement between the simulations and experiments in glassy structure and creep compliance, we use a machine-learned structure indicator, softness, to decompose polymer dynamics in our simulated PNCs into structure-dependent and structure-independent processes. With this decomposition, the free energy barrier for polymer rearrangement can be described as a combination of packing-dependent and packing-independent barriers. We find both barriers are higher near nanoparticles and decrease with applied stress, quantitatively demonstrating that the slow interfacial dynamics is not solely due to polymer packing differences, but also the change of structure-dynamics relationships. Finally, we present how this decomposition can be used to accurately predict strain-time creep curves for PNCs from their static configuration, providing additional insights into the effects of polymer-nanoparticle interfaces on creep suppression in PNCs.

Solid with infused reactive liquid (SWIRL): A novel liquid-based separation approach for effective CO2 capture.

Economical CO2 capture demands low-energy separation strategies. We use a liquid-infused surface (LIS) approach to immobilize reactive liquids, such as amines, on a textured and thermally conductive solid substrate with high surface-area to volume ratio (A/V) continuum geometry. The infused, micrometer-thick liquid retains that high A/V and directly contacts the gas phase, alleviating mass transport resistance typically encountered in mesoporous solid adsorbents. We name this LIS class "solid with infused reactive liquid" (SWIRL). SWIRL-amine requires no water dilution or costly mixing unlike the current liquid-based commercial approach. SWIRL-tetraethylenepentamine (TEPA) shows stable, high capture capacities at power plant CO2 concentrations near flue gas temperatures, preventing energy-intensive temperature swings needed for other approaches. Water vapor increases CO2 capacity of SWIRL-TEPA without compromising stability.

Predicting Hemiwicking Dynamics on Textured Substrates.

The ability to predict liquid transport rates on textured surfaces is key to the design and optimization of devices and processes such as oil recovery, coatings, reaction-separation, high-throughput screening, and thermal management. In this work we develop a fully analytical model to predict the propagation coefficients for liquids hemiwicking through micropillar arrays. This is carried out by balancing the capillary driving force and a viscous resistive force and solving the Navier-Stokes equation for representative channels. The model is validated against a large data set of experimental hemiwicking coefficients harvested from the literature and measured in-house using high-speed imaging. The theoretical predictions show excellent agreement with the measured values and improved accuracy compared to previously proposed models. Furthermore, using lattice Boltzmann (LB) simulations, we demonstrate that the present model is applicable over a broad range of geometries. The scaling of velocity with texture geometry, implicit in our model, is compared against experimental data, where good agreement is observed for most practical systems. The analytical expression presented here offers a tool for developing design guidelines for surface chemistry and microstructure selection for liquid propagation on textured surfaces.

Creep attenuation in glassy polymer nanocomposites with variable polymer-nanoparticle interactions.

The use of nanoparticle reinforced polymer matrices in continuous fiber composites for infrastructure applications requires a comprehensive understanding of viscoelastic creep. Critical parameters affecting the mechanical reinforcement offered by nanoparticles include nanoparticle size and concentration, as well as the interaction between the nanoparticle surface and polymer matrix. Here, we study the viscoelastic creep of nanocomposite systems comprised of glassy thermoplastic polymers and spherical silica nanoparticles of varying sizes and surface functionalization using a dynamic mechanical analysis (DMA) accelerated testing methodology. Significant differences in the nanoparticle dispersions in these nanocomposites were observed via transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) and are attributed to differences in the polymer-polymer and polymer-particle interaction strengths. The DMA measurements indicate a decrease in compliance at short times with increased nanoparticle loading that is largely independent of nanoparticle dispersion morphology and polymer-particle interaction strength. Conversely, long term creep behavior shows a much stronger dependence on these parameters with the creep onset time increasing by up to three orders of magnitude. For similar nanoparticle loadings, the time to critical deformation in systems with well-distributed, networked nanoparticle morphologies was larger by an order of magnitude compared to systems exhibiting strong nanoparticle aggregation. The networked systems delayed the time to critical deformation by three orders of magnitude over that of neat polymer. The increase in time to critical deformation is also greater in composites with smaller nanoparticles at similar loadings, which we attribute to the development of percolated nanoparticle networks. These results demonstrate the significant effects polymer-particle interactions and dispersion morphologies can have on the long-term creep compliance of thermoplastic nanocomposites.

Aligned carbon nanotube morphogenesis predicts physical properties of their polymer nanocomposites.

Carbon nanostructure (CNS) based polymer nanocomposites (PNCs) are of interest due to the superior properties of the CNS themselves, scale effects, and the ability to transfer these properties anisotropically to the bulk material. However, measurements of physical properties of such materials are not in agreement with theoretical predictions. Recently, the ability to characterize the 3D morphology of such PNCs at the nanoscale has been significantly improved, with rich, quantitative data extracted from tomographic transmission electron microscopy (TEM). In this work, we use new, nanoscale quantitative 3D morphological information and stochastic modeling to re-interpret experimental measurements of continuous aligned carbon nanotube (A-CNT) PNC properties as a function of A-CNT packing/volume fraction. The 3D tortuosity calculated from tomographic reconstructions and its evolution with volume fraction is used to develop a novel definition of waviness that incorporates the stochastic nature of CNT growth. The importance of using randomly wavy CNTs to model these materials is validated by agreement between simulated and previously-measured PNC elastic moduli. Secondary morphological descriptors such as CNT-CNT junction density and inter-junction distances are measured for transport property predictions. The scaling of the junction density with CNT volume fraction is observed to be non-linear, and this non-linearity is identified as the primary reason behind the previously unexplained scaling of aligned-CNT PNC longitudinal thermal conductivity. By contrast, the measured electrical conductivity scales linearly with volume fraction as it is relatively insensitive to junction density beyond percolation. This result verifies prior hypotheses that electrical conduction in such fully percolated and continuous CNT systems is dominated by the bulk resistivity of the CNTs themselves. This combination of electron tomographic data and stochastic simulations is a powerful method for establishing a predictive capability for nanocomposite structure-property relations, making it an essential aid in understanding and tailoring the next-generation of advanced composites.

Multiscale Polymer Dynamics in Hierarchical Carbon Nanotube Grafted Glass Fiber Reinforced Composites.

Carbon nanotube (CNT) grafted glass fiber reinforced epoxy nanocomposites (GFRP) present a range of stiffnesses (MPa to GPa) and length scales (µm to nm) at the fiber-matrix interface. The contribution of functionalized CNT networks to the local and bulk polymer dynamics is studied here by using a combination of torsion dynamical mechanical thermal analysis (DMTA), positron annihilation lifetime spectroscopy (PALS), and neutron scattering (NS) measurements. DMTA measurements highlight a reduction in the storage modulus (G') in the rubbery region and an asymmetric broadening of the loss modulus (G″) peak in the α-transition region. NS measurements show a suppressed hydrogen mean-square displacement (MSD) in the presence of glass fibers but a higher hydrogen MSD after grafting functionalized CNTs onto fiber surfaces. PALS measurements show greater free volume characteristics in the presence of the functionalized CNT modified composites, supporting the view that these interface layers increase polymer mobility. While NS and DMTA are sensitive to different modes of chain dynamics, the localization of functionalized nanotubes at the fiber interface is found to affect the distribution of polymer relaxation modes without significantly altering the thermally activated relaxation processes.

Toward 3D Printed Hydrogen Storage Materials Made with ABS-MOF Composites.

The push to advance efficient, renewable, and clean energy sources has brought with it an effort to generate materials that are capable of storing hydrogen. Metal-organic framework materials (MOFs) have been the focus of many such studies as they are categorized for their large internal surface areas. We have addressed one of the major shortcomings of MOFs (their processibility) by creating and 3D printing a composite of acrylonitrile butadiene styrene (ABS) and MOF-5, a prototypical MOF, which is often used to benchmark H2 uptake capacity of other MOFs. The ABS-MOF-5 composites can be printed at MOF-5 compositions of 10% and below. Other physical and mechanical properties of the polymer (glass transition temperature, stress and strain at the breaking point, and Young's modulus) either remain unchanged or show some degree of hardening due to the interaction between the polymer and the MOF. We do observe some MOF-5 degradation through the blending process, likely due to the ambient humidity through the purification and solvent casting steps. Even with this degradation, the MOF still retains some of its ability to uptake H2, seen in the ability of the composite to uptake more H2 than the pure polymer. The experiments and results described here represent a significant first step toward 3D printing MOF-5-based materials for H2 storage.

Metastable morphological states of catalytic nanoparticles.

During the catalytic synthesis of graphene, nanotubes, fibers, and other nanostructures, many intriguing phenomena occur, such as phase separation, precipitation, and analogs of capillary action. Here, we demonstrate, using in situ, real-time transmission electron microscope imaging and modeling, that the catalytic nanoparticles display functional, metastable states, reminiscent of some protein ensembles in vivo. As a carbon nanostructure grows, the nanoparticle elongates due to an energetically favorable metal-carbon interaction that overrides the surface energy increase of the metal. The formation of subsequent nested tubes, however, drives up the particle's free energy, but the particle remains trapped until an accessible free energy surface allows it to exit the tube. During this time, the nanoparticle continues to catalyze tube growth internally to the nested structure. This universal nonequilibrium thermodynamic cycle of elongation and retraction is heavily influenced by tapering of the structure, which, ultimately, determines the final product and catalyst lifetime. Our results provide a unifying framework to interpret similar phenomena for other catalytic reactions, such as during CO oxidation and boron nitride tube growth, and suggest routes to the practical optimization of such processes.

Determination of atomic positions from time resolved high resolution transmission electron microscopy images.

For many reaction processes, such as catalysis, phase transformations, nanomaterial synthesis etc., nanoscale observations at high spatial (sub-nanometer) and temporal (millisecond) resolution are required to characterize and comprehend the underlying factors that favor one reaction over another. The combination of such spatial and temporal resolution (up to 600 µs), while rich in information, produces a large number of snapshots, each of which must be analyzed to obtain the structural (and thereby chemical) information. Here we present a methodology for automated quantitative measurement of real-time atomic position fluctuations in a nanoparticle. We leverage a combination of several image processing algorithms to precisely identify the positions of the atomic columns in each image. A geometric model is then used to measure the time-evolution of distances and angles between neighboring atomic columns to identify different phases and quantify local structural fluctuations. We apply this technique to determine the atomic-level fluctuations in the relative fractions of metal and metal-carbide phases in a cobalt catalyst nanoparticle during single-walled carbon nanotube (SWCNT) growth. These measurements provided a means to obtain the number of carbon atoms incorporated into and released from the catalyst particle, thereby helping resolve carbon reaction pathways during SWCNT growth. Further we demonstrate the use of this technique to measure the reaction kinetics of iron oxide reduction. Apart from reducing the data analysis time, the statistical approach allows us to measure atomic distances with sub-pixel resolution. We show that this method can be applied universally to measure atomic positions with a precision of 0.01 nm from any set of atomic-resolution video images. With the advent of high time-resolution direct detection cameras, we anticipate such methods will be essential in addressing the metrology problem of quantifying large datasets of time-resolved images in future.

Tuning the High-Temperature Wetting Behavior of Metals toward Ultrafine Nanoparticles.

The interaction between metal nanoparticles (NPs) and their substrate plays a critical role in determining the particle morphology, distribution, and properties. The pronounced impact of a thin oxide coating on the dispersion of metal NPs on a carbon substrate is presented. Al2 O3 -supported Pt NPs are compared to the direct synthesis of Pt NPs on bare carbon surfaces. Pt NPs with an average size of about 2 nm and a size distribution ranging between 0.5 nm and 4.0 nm are synthesized on the Al2 O3 coated carbon nanofiber, a significant improvement compared to those directly synthesized on a bare carbon surface. First-principles modeling verifies the stronger adsorption of Pt clusters on Al2 O3 than on carbon, which attributes the formation of ultrafine Pt NPs. This strategy paves the way towards the rational design of NPs with enhanced dispersion and controlled particle size, which are promising in energy storage and electrocatalysis.

Bioinspired Bouligand cellulose nanocrystal composites: a review of mechanical properties.

The twisted plywood, or Bouligand, structure is the most commonly observed microstructural motif in natural materials that possess high mechanical strength and toughness, such as that found in bone and the mantis shrimp dactyl club. These materials are isotropically toughened by a low volume fraction of soft, energy-dissipating polymer and by the Bouligand structure itself, through shear wave filtering and crack twisting, deflection and arrest. Cellulose nanocrystals (CNCs) are excellent candidates for the bottom-up fabrication of these structures, as they naturally self-assemble into 'chiral nematic' films when cast from solutions and possess outstanding mechanical properties. In this article, we present a review of the fabrication techniques and the corresponding mechanical properties of Bouligand biomimetic CNC nanocomposites, while drawing comparison to the performance standards set by tough natural composite materials.This article is part of a discussion meeting issue 'New horizons for cellulose nanotechnology'.

Effect of cellulose nanocrystals on crystallization kinetics of polycaprolactone as probed by Rheo-Raman.

The development of biocompatible polymer nano-composites that enhance mechanical properties while maintaining thermoplastic processability is a longstanding goal in sustainable materials. When the matrix is semi-crystalline, the nanoparticles may induce significant changes to crystallization kinetics and morphology due to their ability to act as nucleating agents. To fully model this behavior in a process line, an understanding of the relationship between crystallinity and modulus is required. Here, we introduce a scalable model system consisting of surface-compatibilized cellulose nanocrystals (CNC) dispersed into poly(ε-caprolactone) (PCL) and study the effects of nanoparticle concentration on isothermal crystallization kinetics. The dispersion is accomplished by exchange of the Na+ of sulfated cellulose nanocrystals by tetra-butyl ammonium cations (Bu4N+) followed by melt mixing via twin-screw extrusion. Crystallization kinetics are measured through the recently developed rheo-Raman instrument which extracts the relationship between the growth of the transient mechanical modulus and that of crystallinity. With extrusion and increasing CNC content, we find the expected enhancement of crystallization rate, but we moreover find a significant change in the relative kinetics of increase in modulus versus crystallinity. We analyze this via generalized effective medium theory which allows computation of a critical percolation threshold ξ c and discuss the results in terms of a change in nucleation density and a change in the anisotropy of crystallization.

Enhanced durability of carbon nanotube grafted hierarchical ceramic microfiber-reinforced epoxy composites.

As carbon nanotube (CNT) infused hybrid composites are increasingly identified as next-generation aerospace materials, it is vital to evaluate their long-term structural performance under aging environments. In this work, the durability of hierarchical, aligned CNT grafted aluminoborosilicate microfiber-epoxy composites (CNT composites) are compared against baseline aluminoborosilicate composites (baseline composites), before and after immersion in water at 25 °C (hydro) and 60 °C (hydrothermal), for extended durations (90 d and 180 d). The addition of CNTs is found to reduce water diffusivities by approximately 1.5 times. The mechanical properties (bending strength and modulus) and the damage sensing capabilities (DC conductivity) of CNT composites remain intact regardless of exposure conditions. The baseline composites show significant loss of strength (44 %) after only 15 d of hydrothermal aging. This loss of mechanical strength is attributed to fiber-polymer interfacial debonding caused by accumulation of water at high temperatures. In situ acoustic and DC electrical measurements of hydrothermally aged CNT composites identify extensive stress-relieving micro-cracking and crack deflections that are absent in the aged baseline composites. These observations are supported by SEM images of the failed composite cross-sections that highlight secondary matrix toughening mechanisms in the form of CNT pullouts and fractures which enhance the service life of composites and maintain their properties under accelerated aging environments.

Chain dynamics and nanoparticle motion in attractive polymer nanocomposites subjected to large deformations.

The effect of large deformation on the chain dynamics in attractive polymer nanocomposites was investigated using neutron scattering techniques. Quasi-elastic neutron backscattering measurements reveal a substantial reduction of polymer mobility in the presence of attractive, well-dispersed nanoparticles. In addition, large deformations are observed to cause a further slowing down of the Rouse rates at high particle loadings, where the interparticle spacings are slightly smaller than the chain dimensions, i.e. in the strongly confined state. No noticeable change, however, was observed for a lightly confined system. The reptation tube diameter, measured by neutron spin echo, remained unchanged after shear, suggesting that the level of chain-chain entanglements is not significantly affected. The shear-induced changes in the interparticle bridging reflect the slow nanoparticle motion measured by X-ray photon correlation spectroscopy. These results provide a first step for understanding how large shear can significantly affect the segmental motion in nanocomposites and open up new opportunities for designing mechanically responsive soft materials.

Direct evidence of atomic-scale structural fluctuations in catalyst nanoparticles.

Rational catalyst design requires an atomic scale mechanistic understanding of the chemical pathways involved in the catalytic process. A heterogeneous catalyst typically works by adsorbing reactants onto its surface, where the energies for specific bonds to dissociate and/or combine with other species (to form desired intermediate or final products) are lower. Here, using the catalytic growth of single-walled carbon nanotubes (SWCNTs) as a prototype reaction, we show that the chemical pathway may in-fact involve the entire catalyst particle, and can proceed via the fluctuations in the formation and decomposition of metastable phases in the particle interior. We record in situ and at atomic resolution, the dynamic phase transformations occurring in a Cobalt catalyst nanoparticle during SWCNT growth, using a state-of-the-art environmental transmission electron microscope (ETEM). The fluctuations in catalyst carbon content are quantified by the automated, atomic-scale structural analysis of the time-resolved ETEM images and correlated with the SWCNT growth rate. We find the fluctuations in the carbon concentration in the catalyst nanoparticle and the fluctuations in nanotube growth rates to be of complementary character. These findings are successfully explained by reactive molecular dynamics (RMD) simulations that track the spatial and temporal evolution of the distribution of carbon atoms within and on the surface of the catalyst particle. We anticipate that our approach combining real-time, atomic-resolution image analysis and molecular dynamics simulations will facilitate catalyst design, improving reaction efficiencies and selectivity towards the growth of desired structure.

Rapid Large-Scale Assembly and Pattern Transfer of One-Dimensional Gold Nanorod Superstructures.

The utility of gold nanorods for plasmonic applications largely depends on the relative orientation and proximity of the nanorods. Though side-by-side or chainlike nanorod morphologies have been previously demonstrated, a simple reliable method to obtain high-yield oriented gold nanorod assemblies remains a significant challenge. We present a facile, scalable approach which exploits meniscus drag, evaporative self-assembly, and van der Waals interactions to precisely position and orient gold nanorods over macroscopic areas of 1D nanostructured substrates. By adjusting the ratio of the nanorod diameter to the width of the nanochannels, we demonstrate the formation of two highly desired translationally ordered nanorod patterns. We further demonstrate a method to transfer the aligned nanorods into a polymer matrix which exhibits anisotropic optical properties, allowing for rapid fabrication and deployment of flexible optical and electronic materials in future nanoscale devices.

Small Particle Driven Chain Disentanglements in Polymer Nanocomposites.

Using neutron spin-echo spectroscopy, x-ray photon correlation spectroscopy, and bulk rheology, we studied the effect of particle size on the single-chain dynamics, particle mobility, and bulk viscosity in athermal polyethylene oxide-gold nanoparticle composites. The results reveal a ≈25% increase in the reptation tube diameter with the addition of nanoparticles smaller than the entanglement mesh size (≈5 nm), at a volume fraction of 20%. The tube diameter remains unchanged in the composite with larger (20 nm) nanoparticles at the same loading. In both cases, the Rouse dynamics is insensitive to particle size. These results provide a direct experimental observation of particle-size-driven disentanglements that can cause non-Einstein-like viscosity trends often observed in polymer nanocomposites.

Dielectric Characterization of Confined Water in Chiral Cellulose Nanocrystal Films.

A known deterrent to the large-scale development and use of cellulose nanocrystals (CNCs) in composite materials is their affinity for moisture, which has a profound effect on dispersion, wetting, interfacial adhesion, matrix crystallization, water uptake, and hydrothermal stability. To quantify and control the hydration and confinement of absorbed water in CNCs, we studied sulfated-CNCs neutralized with sodium cations and CNCs functionalized with less hydrophilic methyl(triphenyl)phosphonium cations. Films were cast from water suspensions at 20 °C under controlled humidity and drying rate, yielding CNC materials with distinguishably different dielectric properties and cholesteric structures. By controlling the evaporation rate, we obtained self-assembled chiral CNC films with extended uniformity, having helical modulation length (nominal pitch) tunable from 1300 to 600 nm. SEM imaging and UV-vis-NIR total reflectance spectra revealed tighter and more uniform CNC packing in films cast at slow evaporation rates or having lower surface energy when modified with phosphonium. The dielectric constant was measured by a noncontact microwave cavity perturbation method and fitted to a classical mixing model employing randomly oriented ellipsoidal water inclusions. The dielectric constant of absorbed water was found to be significantly smaller than that for free liquid indicating a limited mobility due to binding with the CNC "matrix". In the case of hydrophilic Na-modified CNCs, a decreasing pitch led to greater anisotropy in the shape of moisture inclusions (ellipsoidal to platelet-like) and greater confinement. In contrast, the structure of hydrophobic phosphonium-modified CNC films was found to have reduced pitch, yet the shape of confined water remained predominantly spherical. These results provide a useful perspective on the current state of understanding of CNC-water interactions as well as on CNC self-assembly mechanisms. More broadly, we believe that our results are beneficial for the realization of CNC-based functional materials and composites.

Giant Surface Conductivity Enhancement in a Carbon Nanotube Composite by Ultraviolet Light Exposure.

Carbon nanotube composites are lightweight, multifunctional materials with readily adjustable mechanical and electrical properties-relevant to the aerospace, automotive, and sporting goods industries as high-performance structural materials. Here, we combine well-established and newly developed characterization techniques to demonstrate that ultraviolet (UV) light exposure provides a controllable means to enhance the electrical conductivity of the surface of a commercial carbon nanotube-epoxy composite by over 5 orders of magnitude. Our observations, combined with theory and simulations, reveal that the increase in conductivity is due to the formation of a concentrated layer of nanotubes on the composite surface. Our model implies that contacts between nanotube-rich microdomains dominate the conductivity of this layer at low UV dose, while tube-tube transport dominates at high UV dose. Further, we use this model to predictably pattern conductive traces with a UV laser, providing a facile approach for direct integration of lightweight conductors on nanocomposite surfaces.

Trade-off between the Mechanical Strength and Microwave Electrical Properties of Functionalized and Irradiated Carbon Nanotube Sheets.

Carbon nanotube (CNT) sheets represent a novel implementation of CNTs that enable the tailoring of electrical and mechanical properties for applications in the automotive and aerospace industries. Small molecule functionalization and postprocessing techniques, such as irradiation with high-energy particles, are methods that can enhance the mechanical properties of CNTs. However, the effect that these modifications have on the electrical conduction mechanisms has not been extensively explored. By characterizing the mechanical and electrical properties of multiwalled carbon nanotube (MWCNT) sheets with different functional groups and irradiation doses, we can expand our insights into the extent of the trade-off that exists between mechanical strength and electrical conductivity for commercially available CNT sheets. Such insights allow for the optimization of design pathways for engineering applications that require a balance of material property enhancements.