Search for: All records

Metal additive manufacturing (AM) is gaining increasing attention from academia and industry due to its unique advantages compared to the traditional manufacturing process. Parts quality inspection is playing a crucial role in the AM industry, which can be adopted for product improvement. However, the traditional inspection process has relied on manual recognition, which could suffer from low efficiency and potential bias. This study presented a convolutional neural network (CNN) approach toward robust AM quality inspection, such as good quality, crack, gas porosity, and lack of fusion. To obtain the appropriate model, experiments were performed on a series of architectures. Moreover, data augmentation was adopted to deal with data scarcity. L2 regularization (weight decay) and dropout were applied to avoid overfitting. The impact of each strategy was evaluated. The final CNN model achieved an accuracy of 92.1%, and it took 8.01 milliseconds to recognize one image. The CNN model presented here can help in automatic defect recognition in the AM industry. 

Abstract Utilizing plasmon‐generated hot carriers to drive chemical reactions has emerged as a popular topic in solar photocatalysis. However, a complete description of the underlying mechanism of hot‐carrier transfer in photochemical processes remains elusive, particularly for those involving hot holes. Photoelectrochemistry enables to localize hot holes on photoanodes and hot electrons on photocathodes and thus offers an approach to separately explore the hole‐transfer dynamics and electron‐transfer dynamics. This review summarizes a comprehensive understanding of both hot‐hole and hot‐electron transfers from photoelectrochemical studies on plasmonic electrodes. Additionally, working principles and applications of spectroelectrochemistry are discussed for plasmonic materials. It is concluded that photoelectrochemistry provides a powerful toolbox to gain mechanistic insights into plasmonic photocatalysis. 

Abstract Sulfide solid‐state electrolytes have remarkable ionic conductivity and low mechanical stiffness but suffer from relatively narrow electrochemical and chemical stability with electrodes. Therefore, pairing sulfide electrolytes with the proper cathode is crucial in developing stable all‐solid‐state Li batteries (ASLBs). Herein, one type of thioantimonate ion conductor, Li_6+xGe_xSb_1−xS₅I, with different compositions is systematically synthesized and studied, among these compositions, an outstanding ionic conductivity of 1.6 mS cm⁻¹is achieved with Li_6.6Ge_0.6Sb_0.4S₅I. To improve the energy density and advance the interface compatibility, a metal sulfide FeS₂cathode with a high theoretical capacity (894 mAh g⁻¹) and excellent compatibility with sulfide electrolytes is coupled with Li_6.6Ge_0.6Sb_0.4S₅I in ASLBs without additional interface engineering. The structural stabilities of Li_6.6Ge_0.6Sb_0.4S₅I and FeS₂during cycling are characterized by operando energy dispersive X‐ray diffraction, which allows rapid collection of structural data without redesigning or disassembling the sealed cells and risking contamination by air. The electrochemical stability is assessed, and a safe operating voltage window ranging from 0.7≈2.4 V (vs. In–Li) is confirmed. Due to the solid confinement in the ASLBs, the Fe⁰aggregation and polysulfides shuttle effects are well addressed. The ASLBs exhibit an outstanding initial capacity of 715 mAh g⁻¹at C/10 and are stable for 220 cycles with a high capacity retention of 84.5% at room temperature.