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The advances in the instrumented indentation equipments and the need to assess the properties of materials of small volume such as those constitute the micro-electro-mechanical devices, micro-electronic packages, and thin films have propelled the interest in material characterization via indentation tests. The load-displacement curves and their characteristics, namely, the curvature of the loading path, C, and the ratio of the remaining and total work done, WR / WT, can be conveniently obtained from finite element simulations for various elasto-plastic material properties. The paper reports the comparative study on two reverse neural networks algorithms involving several combinations of databases established from the results obtained from simulated indentation tests. The performance of each set of results is analyzed and the most appropriate algorithm identified and reported. The approach with the selected neural networks model has great potential in practical applications on the characterization of a small volume of materials.  相似文献   
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Two-dimensional TiO2 nanosheets were synthesized by atomic layer deposition (ALD) on dissolvable sacrificial polymer layer. The photocatalytic performance of free-standing TiO2 nanosheets prepared with different numbers of ALD cycles (100, 300, 500, and 1000) were investigated by evaluating the degradation rates of methyl orange solutions. It is shown that the photocatalytic activity increases due to Ti3+ defect and the locally ordered structures in amorphous TiO2 nanosheets. The difference in the surface areas of nanosheets may also play a crucial role in the photocatalytic activity. The results obtained in this work can have potential applications in fields like water splitting and dye-sensitized solar cells.  相似文献   
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