Deep learning based ultrasonic reconstruction of rough surface morphology.

This paper introduces a methodology to recover the morphology of a complex rough surface from ultrasonic pulse echo measurements with an array of equidistant sensors using the one dimensional convolution neural network (1DCNN). The neural network is trained by the datasets simulated from high-fidelity finite element simulations for surfaces with a range of roughness parameters and is tested on both numerical and real experimental data. To assess the performance of our proposed method, the rough surface reconstruction results from the deep learning approach are compared with those obtained from conventional ultrasonic array imaging methods. Unlike array imaging-based methods that require a large number of sensors (e.g., 128, 64 or 32), the deep learning-based method uses pulse echo signals and can achieve accurate results with much fewer sensors. The developed deep learning approach has the potential to enable low-cost, accurate, and real-time reconstruction of complex surface profiles.

A multi-GPU and CUDA-aware MPI-based spectral element formulation for ultrasonic wave propagation in solid media.

In this paper, we introduce a new multi-GPU-based spectral element (SE) formulation for simulating ultrasonic wave propagation in solids. To maximize communication efficiency, we purposely developed, based on CUDA-aware MPI, two novel message exchange strategies which allow the common nodal forces of different subdomains to be shared between different GPUs in a direct manner, as opposed to via CPU hosts, during central difference-based time integration steps. The new multi-GPU and CUDA-aware MPI-based formulation is benchmarked against a multi-CPU core and classical MPI-based counterpart, demonstrating a remarkable acceleration in each and every stage of the computation of ultrasonic wave propagation, namely matrix assembly, time integration and message exchange. More importantly, both the computational efficiency and the degree-of-freedom limit of the new formulation are actually scalable with the number of GPUs used, potentially allowing larger structures to be computed and higher computational speeds to be realized. Finally, the new formulation was used to simulate the interaction between Lamb waves and randomly shaped thickness loss defects on plates, showing its potential to become an efficient, accurate and robust technique for addressing the propagation of ultrasonic waves in realistic engineering structures.

Polysaccharide-based aerogels for thermal insulation and superinsulation: An overview.

To reduce energy losses due to the insufficient thermal insulation is one of the current "hot" topics. Various commercial porous materials are used with the best conductivity around 0.03-0.04 W/(m·K). Aerogels are the only known materials with "intrinsic" thermal superinsulating properties, i.e. with thermal conductivity below that of air in ambient conditions (0.025 W/(m·K)). The classical thermal superinsulating aerogels are based on silica and some synthetic polymers, with conductivity 0.014-0.018 W/(m·K). Aerogels based on natural polymers are new materials created at the beginning of the 21st century. Can bio-aerogels possess thermal superinsulating properties? What are the bottlenecks in the development of bio-aerogels as new high-performance thermal insulationing materials? We try to answer these questions by analyzing thermal conductivity of bio-aerogels reported in literature.

Tailoring the morphology and properties of starch aerogels and cryogels via starch source and process parameter.

Porous starch materials with various morphology and properties were made via starch dissolution, retrogradation and drying either with supercritical CO2 ("aerogels") or lyophilisation ("cryogels"). Their properties were correlated with the rheological response of retrograded starch gels and crystallinity of aerogels and cryogels. All starch cryogels possess very low density (0.07 - 0.16 g/cm3), very large macropores and low specific surface area (around 3-13 m2/g). Their morphology is mainly the replica of sublimated ice crystals. The properties of starch aerogels strongly depend on starch source: the lowest density (around 0.1 g/cm3) and highest specific surface area (170-250 m2/g) was recorded for pea starch aerogels and the highest density (0.3-0.6 g/cm3) and lowest specific surface area (7-90 m2/g) for waxy maize starch aerogels. The morphology and properties of starch aerogels are interpreted by amylose and amylopectin evolution during retrogradation.

Biorefinery Approach for Aerogels.

According to the International Energy Agency, biorefinery is "the sustainable processing of biomass into a spectrum of marketable bio-based products (chemicals, materials) and bioenergy (fuels, power, heat)". In this review, we survey how the biorefinery approach can be applied to highly porous and nanostructured materials, namely aerogels. Historically, aerogels were first developed using inorganic matter. Subsequently, synthetic polymers were also employed. At the beginning of the 21st century, new aerogels were created based on biomass. Which sources of biomass can be used to make aerogels and how? This review answers these questions, paying special attention to bio-aerogels' environmental and biomedical applications. The article is a result of fruitful exchanges in the frame of the European project COST Action "CA 18125 AERoGELS: Advanced Engineering and Research of aeroGels for Environment and Life Sciences".

Bismaleimide bridged silsesquioxane aerogels with excellent heat resistance: effect of sol-gel solvent polarity.

Due to the poor heat-resistance and intrinsic weakness of the bridging moieties in aerogel matrixes, it remains greatly challenging to fabricate highly thermostable and toughened silsesquioxane aerogels. By utilizing bismaleimide as the bridging part and optimizing the solvent polarity, lightweight (ρ < 0.09 g cm-3), compressible (80% strain) and superhydrophobic (CA ≈ 150°) bismaleimide bridged silsesquioxane aerogels (BMIT-BSAs) are constructed. The microstructure and compressive modulus of BMIT-BSAs can be tuned by the sol-gel solvents with different polarities. Moreover, stable low-temperature wettability at -196 °C and a significantly increased initial deposition temperature of 336 °C for both N2 and O2 atmospheres were measured, demonstrating the wide temperature tolerance of BMIT-BSAs.