X-ray tomography has provided a non-destructive means for microstructure characterization in three and four dimensions. A stochastic procedure to accurately reconstruct material microstructure from limited-angle X-ray tomographic projections is presented and its utility is demonstrated by reconstructing a variety of distinct heterogeneous materials and elucidating the information content of different projection data sets. A small number of projections (e.g. 20–40) are necessary for accurate reconstructions via the stochastic procedure, indicating its high efficiency in using limited structural information.

Phase-change materials (PCMs) are of broad interest for thermal storage and management applications. For energy-dense storage with fast thermal charging/discharging rates, a PCM should have a suitable melting temperature, large enthalpy of fusion, and high thermal conductivity. To simultaneously accomplish these traits, we custom design nanocomposites consisting of phase-change Bi nanoparticles embedded in an Ag matrix. We precisely control nanoparticle size, shape, and volume fraction in the composite by separating the nanoparticle synthesis and nanocomposite formation steps. We demonstrate a 50–100% thermal energy density improvement relative to common organic PCMs with equivalent volume fraction. We also tune the melting temperature from 236–252 °C by varying nanoparticle diameter from 8.1–14.9 nm. Importantly, the silver matrix successfully prevents nanoparticle coalescence, and no melting changes are observed during 100 melt–freeze cycles. The nanocomposite’s Ag matrix also leads to very high thermal conductivities. For example, the thermal conductivity of a composite with a 10% volume fraction of 13 nm Bi nanoparticles is 128 ± 23 W/m-K, which is several orders of magnitude higher than typical thermal storage materials. We complement these measurements with calculations using a modified effective medium approximation for nanoscale thermal transport. These calculations predict that the thermal conductivity of composites with 13 nm Bi nanoparticles varies from 142 to 47 W/m-K as the nanoparticle volume fraction changes from 10 to 35%. Larger nanoparticle diameters and/or smaller nanoparticle volume fractions lead to larger thermal conductivities.

The tapered joints of modular hip implants are prone to fretting and crevice-corrosion. This can lead to total failure in under a year, especially for heavier, more active implant recipients. In this study, fractography of a failed Profemur Z implant showed that a life limiting fatigue crack was nucleated on the anterolateral surface of the implant's neck. The fatigue crack nucleation area appeared to have both more fretting damage and a higher corrosion rate than on other surfaces of the neck.

Design of novel infrastructure materials requires a proper understanding of the influence of microstructure on the desired performance. The priority is to seek new and innovative ways to develop sustainable infrastructure materials using natural resources and industrial solid wastes in a manner that is ecologically sustainable and yet economically viable. Structural materials are invariably designed based on mechanical performance. Accurate prediction of effective constitutive behavior of highly heterogeneous novel structural materials with multiple microstructural phases is a challenging task. This necessitates reliable classification and characterization of constituent phases in terms of their volume fractions, size distributions and intrinsic elastic properties, coupled with numerical homogenization technique. This paper explores a microstructure-guided numerical framework that derives inputs from nanoindentation and synchrotron x-ray tomography towards the prediction of effective constitutive response of novel sustainable structural materials so as to enable microstructure-guided design.

Colloidal nanocrystals are a technologically important class of nanostructures whose phase change properties have been largely unexplored. Here we report on the melting behavior of In, Sn, and Bi nanocrystals dispersed in a polymer matrix. This polymer matrix prevents the nanocrystals from coalescing with one another and enables previously unaccessed observations on the melting behavior of colloidal nanocrystals. We measure the melting temperature, melting enthalpy, and melting entropy of colloidal nanocrystals with diameters of approximately 10 to 20 nm. All of these properties decrease as nanocrystal size decreases, although the depression rate for melting temperature is comparatively slower than that of melting enthalpy and melting entropy. We also observe an elevated melting temperature during the initial melt-freeze cycle that we attribute to surface stabilization from the organic ligands on the nanocrystal surface. Broad endothermic melting valleys and very large supercoolings in our calorimetry data suggest that colloidal nanocrystals exhibit a significant amount of surface pre-melting and low heterogeneous nucleation probabilities during freezing.

Metal matrix composites (MMCs) offer high strength, high stiffness, low density, and good fatigue resistance, while maintaining cost an acceptable level. Fatigue resistance of MMCs depends on many aspects of composite microstructure. Fatigue crack growth behavior is particularly dependent on the reinforcement characteristics and matrix microstructure. The goal of this work is to obtain a fundamental understanding of fatigue crack growth behavior in SiC particle-reinforced 2080 Al alloy composites. In situ X-ray synchrotron tomography was performed on two samples at low (R = 0.1) and at high (R = 0.6) R-ratios. The resulting reconstructed images were used to obtain three-dimensional (3D) rendering of the particles and fatigue crack. Behaviors of the particles and crack, as well as their interaction, were analyzed and quantified. Four-dimensional (4D) visual representations were constructed to aid in the overall understanding of damage evolution.