Electrochemical discharge machining (ECDM) is an emerging special processing technology for non-conductive hard and brittle materials, but it may encounter the problem of tool wear due to its process characteristics, which affects the processing accuracy. In this study, in the non-machining state, the tungsten carbide spiral cathode with a diameter of 400 μm was selected to analyze the influencing mechanism of the process parameters on tool wear, and a suitable voltage range for the processing was obtained. The influence of the cathode’s loss behavior on the film formation time and the average current of spark discharge was discussed based on the current signal. The results show that the tool wear mainly appears from the bottom to the end and edge tip of the protrusion. Loss is mainly in the form of local material melting or gasification at high temperature. In addition, the loss may shorten the film formation time, but the effect on the average current of spark discharge is small.

Full-inorganic CsPbIBr2 optoelectronic devices have received huge attention in energy technology owing to their prime photovoltaic properties and promising thermal stability. However, CsPbIBr2 perovskite films obtained by conventional spin coating always have bad morphology, poor crystallinity, and thin thickness, which subsequently reduced the device performance. In this work, an assistant solution, isopropanol solution containing different organic iodide salts (FAI), was successfully introduced during the spin coating process, where isopropanol solution acted as the effective anti-solvent and FAI was used as the surface passivator. A film with suitable thickness (500 nm) with a pure-phase perovskite film having an average grain size of 600 nm and high coverage and being pinhole-free could be created by further controlling and optimizing the CsPbIBr2 crystals. The high-quality CsPbIBr2 film resulted in greatly impeded charge recombination and increased charge transfer and extraction efficiency. Therefore, a power conversion efficiency (PCE) of about 9% was obtained, which is 110% enhanced compared to that of the pristine device. In addition, the proposed CsPbIBr2 perovskite solar cells showed excellent long-term stability by encapsulation, which could show a 10% initial PCE loss after storing in the ambient environment for 1000 h. This work indicates that the adopted strategy is an effective and huge potential technology to improve photovoltaic performance, which can be further applied in other inorganic photovoltaic fields.

Skin cancer is one of the most deadly cancer types with considerable number of patients.Image analysis has largely improved the automated diagnosis accuracy for malignant melanoma and other pigmented skin lesions, compared to unaided visual examination. Recent popular solution for automated skin lesion classification is using deep neural networks, trained from large amounts of professional annotated data, but that largely limits the model's scalability. This paper exploits transfer learning for skin lesion classification task with the help of labeled data from another domain (source), and proposes a multi-view filtered transfer learning network to strongly represent discriminative information from different image views with reasonable weighing strategy. This method also evaluates the importance for each source images, which can learn useful knowledge with neglecting negative samples from source domain. The extensive skin lesion classification experiments demonstrate our method can effectively solve Melanoma and Seborrheic Keratosis classification tasks with outstanding extensibility, and the discussion of the major components also testifies the improvements of our proposed multi-view filtered transfer learning approach.

Different cathode materials have different surface chemical components and machining capacities, which may finally result in different machining quality and machining efficiency of workpieces. In this paper, in order to investigate the influence of cathode materials on the electrochemical machining of thin-walled workpiece made of 304 stainless steel, five cylindrical electrodes are used as the target working cathodes of electrochemical machining to conduct experiments and research, including 45# steel, 304 stainless steel, aluminum alloy 6061, brass H62, and tungsten steel YK15. The stray current corrosion, taper, and material removal rate were used as the criteria to evaluate the drilling quality of efficiency of a thin-walled workpiece made of 304 stainless steel. The research results show that from the perspectives of stray current corrosion and taper, aluminum alloy 6061 is an optimal tool cathode, which should be used in the electrochemical machining of thin-walled workpieces made of 304 stainless steel; on the aspect of material removal rate, the 45# steel, 304 stainless steel, and aluminum alloy 6061 present close material removal rates, all of which are higher than that of brass H62 and tungsten steel YK15. Based on comprehensive consideration of both machining quality and machining efficiency, the aluminum alloy 6061 is the best option as the cathode tool in the electrochemical machining of thin-walled workpieces made of 304 stainless steel.

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The electrochemical discharge machining process is affected by many factors, so the machining process is difficult to be qualitatively analyzed. In order to further understand the characteristics of the electrochemical discharge machining process and better master the machining skills, based on the image features, this article uses the SVM algorithm to build an electrochemical discharge machining system, and uses image feature recognition technology to effectively control the electrochemical discharge machining process. Moreover, this article analyzes the laser back-wet etching process mechanism and discusses the material removal mechanism of electrochemical discharge machining according to the three processes of bubble generation, gas layer formation, and spark discharge removal material. In addition, this article analyzes the system performance according to the actual situation and displays the results through statistical methods. The research results show that the electrochemical discharge machining system based on image features and SVM algorithm constructed in this paper has a good effect, and it can be applied to the management and control of the electrochemical discharge machining process.

The laser gas oxidising of Ti-6Al-4V surface was studied. Confocal laser scanning microscopy techniques were used to investigate its two-and three-dimensional surface topographies. Gas flow behaviour was simulated to define the minimum O 2 concentration required for Ti-6Al-4V to self-sustain combustion. To understand the flow behaviour of the Ti-6Al-4V fluid, a highspeed camera monitored the evolution of the Ti-6Al-4V fluid, and the flow behaviour was simulated. Experimental and simulation results show that Ti-6Al-4V can self-sustain combustion with a high O 2 to Ar gas flow ratio, and the oxidising layer is rough with macroscopic cracks, while a low O 2 to Ar gas flow ratio results in a smooth oxidising layer without cracks. Ti-6Al-4V can self-sustain combustion when the O 2 concentration exceeds 65%. Furthermore, the laser molten pool and self-sustaining combustion zone mix and flow together, and a large self-sustaining combustion zone leads to a low convection velocity.

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