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Laser-induced incandescence (LII) of soot has developed into a popular method for making in situ measurements of soot volume fraction and primary particle sizes. However, there is still a lack of understanding regarding the generation and interpretation of the cooling signals. To model heat transfer from the heated soot particles to the surrounding gas, knowledge of the collision-based cooling as well as reactive events, including oxidation (exothermic) and evaporation (endothermic) is essential. We have simulated LII of soot using the ReaxFF reactive force field for hydrocarbon combustion. Soot was modeled as a stack of four graphene sheets linked together using sp(3) hybridized carbon atoms. To calculate the thermal accommodation coefficient of various gases with soot, graphene sheets of diameter 40 Å were used to create a soot particle containing 2691 atoms, and these simulations were carried out using the ReaxFF version incorporated into the Amsterdam Density Functional program. The reactive force field enables us to simulate the effects of conduction, evaporation, and oxidation of the soot particle on the cooling signal. Simulations were carried out for both reactive and nonreactive gas species at various pressures, and the subsequent cooling signals of soot were compared and analyzed. To correctly model N(2)-soot interactions, optimization of N-N and N-C-H force field parameters against DFT and experimental values was performed and is described in this paper. Subsequently, simulations were performed in order to find the thermal accommodation coefficients of soot with various monatomic and polyatomic gas molecules like He, Ne, Ar, N(2), CO(2), and CH(4). For all these species we find good agreement between our ReaxFF results and previously published accommodation coefficients. We thus believe that Molecular Dynamics using the ReaxFF reactive force field is a promising approach to simulate the physical and chemical aspects of soot LII.

Sensor designs found in nature are optimal due to their evolution over millions of years, making them well-suited for sensing applications. However, replicating these complex, three-dimensional (3D), biomimetic designs in artificial and flexible sensors using conventional techniques such as lithography is challenging. In this paper, we introduce a new processing paradigm for the simplified fabrication of flexible sensors featuring complex and bioinspired structures. The proposed fabrication workflow entailed 3D-printing a metallic mold with complex and intricate 3D features such as a micropillar and a microchannel, casting polydimethylsiloxane (PDMS) inside the mold to obtain the desired structure, and drop-casting piezoresistive graphene nanoplatelets into the predesigned microchannel to form a flexible strain gauge. The graphene-on-PDMS strain gauge showed a high gauge factor of 37 as measured via cyclical tension-compression tests. The processing workflow was used to fabricate a flow sensor inspired by hair-like ‘cilia’ sensors found in nature, which comprised a cilia-inspired pillar and a cantilever with a microchannel that housed the graphene strain gauge. The sensor showed good sensitivity against both tactile and water flow stimuli, with detection thresholds as low as 12 µm in the former and 58 mm/s in the latter, demonstrating the feasibility of our method in developing flexible flow sensors.

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