Unlocking the potential: analyzing 3D microstructure of small-scale cement samples from space using deep learning.

Due to the prohibitive cost of transporting raw materials into Space, in-situ materials along with cement-like binders are poised to be employed for extraterrestrial construction. A unique methodology for obtaining microstructural topology of cement samples hydrated in microgravity environment at the International Space Station (ISS) is presented here. Distinctive Scanning Electron Microscopy (SEM) micrographs of hardened tri-calcium silicate (C3S) samples were used as exemplars in a deep learning-based microstructure reconstruction framework. The proposed method aids in generation of an ensemble of microstructures that is inherently statistical in nature, by utilizing sparse experimental data such as the C3S samples hydrated in microgravity. The hydrated space-returned samples had exhibited higher porosity content (~70 %) with the portlandite phase assuming an elongated plate-like morphology. Qualitative assessment of the volumetric slices from the reconstructed volumes showcased similar visual characteristics to that of the target 2D exemplar. Detailed assessment of the reconstructed volumes was carried out using statistical descriptors, and was further compared against micro-CT virtual data. The reconstructed volumes captured the unique microstructural morphology of the hardened C3S samples of both space-returned and ground-based samples, and can be directly employed as Representative Volume Element (RVE) to characterize mechanical/transport properties.

Tuning Interparticle Contacts and Transport Properties of Maghemite-Thermoset Nanocomposites by Applying Oscillating Magnetic Fields.

Conductive nanofillers, if integrated in an organized manner, can improve the transport properties of polymer matrices without compromising on their light weight. However, the relationship between the particle assemblies and transport properties of such nanocomposites, especially the competing effects of connected nanofiller pathways compared to resistances at interparticle contacts, has not been quantitatively studied. In this work, with the model nanocomposite of maghemite nanoparticles in epoxy, a novel fabrication method has been demonstrated to align nanofillers and control the interparticle contact amount within such a nanofiller assembly, using nanoparticle surface functionalization and oscillating magnetic field application. The nanofiller assembly cross-sectional areas were measured by processing micro-CT images and compared with the measured electrical and thermal properties of the nanocomposites. In terms of thermal transport, when the nanofiller assembly cross-sectional area was small, the dominance of conductivity pathways was observed up to ∼4.7 vol %, while interfacial thermal resistance began to dominate when the nanofiller assembly cross-sectional area became larger than 2700 µm2.

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.

Thin films with ultra-low thermal expansion.

Ultra-low coefficient of thermal expansion (CTE) is an elusive property, and narrow temperature ranges of operation and poor mechanical properties limit the use of conventional materials with low CTE. We structured a periodic micro-array of bi-metallic cells to demonstrate ultra-low effective CTE with a wide temperature range. These engineered tunable CTE thin film can be applied to minimize thermal fatigue and failure of optics, semiconductors, biomedical sensors, and solar energy applications.

Thermal conduction in aligned carbon nanotube-polymer nanocomposites with high packing density.

Nanostructured composites containing aligned carbon nanotubes (CNTs) are very promising as interface materials for electronic systems and thermoelectric power generators. We report the first data for the thermal conductivity of densified, aligned multiwall CNT nanocomposite films for a range of CNT volume fractions. A 1 vol % CNT composite more than doubles the thermal conductivity of the base polymer. Denser arrays (17 vol % CNTs) enhance the thermal conductivity by as much as a factor of 18 and there is a nonlinear trend with CNT volume fraction. This article discusses the impact of CNT density on thermal conduction considering boundary resistances, increased defect concentrations, and the possibility of suppressed phonon modes in the CNTs.

Multi-physics damage sensing in nano-engineered structural composites.

Non-destructive evaluation techniques can offer viable diagnostic and prognostic routes to mitigating failures in engineered structures such as bridges, buildings and vehicles. However, existing techniques have significant drawbacks, including poor spatial resolution and limited in situ capabilities. We report here a novel approach where structural advanced composites containing electrically conductive aligned carbon nanotubes (CNTs) are ohmically heated via simple electrical contacts, and damage is visualized via thermographic imaging. Damage, in the form of cracks and other discontinuities, usefully increases resistance to both electrical and thermal transport in these materials, which enables tomographic full-field damage assessment in many cases. Characteristics of the technique include the ability for real-time measurement of the damage state during loading, low-power operation (e.g. 15 °C rise at 1 W), and beyond state-of-the-art spatial resolution for sensing damage in composites. The enhanced thermographic technique is a novel and practical approach for in situ monitoring to ascertain structural health and to prevent structural failures in engineered structures such as aerospace and automotive vehicles and wind turbine blades, among others.

Characterization of exposures to nanoscale particles and fibers during solid core drilling of hybrid carbon nanotube advanced composites.

This work investigated exposures to nanoparticles and nanofibers during solid core drilling of two types of advanced carbon nanotube (CNT)-hybrid composites: (1) reinforced plastic hybrid laminates (alumina fibers and CNT); and (2) graphite-epoxy composites (carbon fibers and CNT). Multiple real-time instruments were used to characterize the size distribution (5.6 nm to 20 microm), number and mass concentration, particle-bound polyaromatic hydrocarbons (b-PAHs), and surface area of airborne particles at the source and breathing zone. Time-integrated samples included grids for electron microscopy characterization of particle morphology and size resolved (2 nm to 20 microm) samples for the quantification of metals. Several new important findings herein include generation of airborne clusters of CNTs not seen during saw-cutting of similar composites, fewer nanofibers and respirable fibers released, similarly high exposures to nanoparticles with less dependence on the composite thickness, and ultrafine (< 5 nm) aerosol originating from thermal degradation of the composite material.

Inter-carbon nanotube contact in thermal transport of controlled-morphology polymer nanocomposites.

Directional thermal conductivities of aligned carbon nanotube (CNT) polymer nanocomposites were calculated using a random walk simulation with and without inter-CNT contact effects. The CNT contact effect has not been explored for its role in thermal transport, and it is shown here to significantly affect the effective transport properties including anisotropy ratios. The primary focus of the paper is on the non-isotropic heat conduction in aligned-CNT polymeric composites, because this geometry is an ideal thermal layer as well as constituting a representative volume element of CNT-reinforced polymer matrices in hybrid advanced composites under development. The effects of CNT orientation, type (single-versus multi-wall), inter-CNT contact, volume fraction and thermal boundary resistance on the effective conductivities of CNT composites are quantified. It is found that when the CNT-CNT thermal contact is taken into account, the maximum effective thermal conductivity of the nanocomposites having their CNTs parallel to the heat flux decreases by approximately 4 times and approximately 2 times for the single-walled and the multi-walled CNTs, respectively, at 20% CNT volume fraction.