Boron-doped diamond (BDD) thin film electrodes have great application potential in water treatment. However, the high electrode energy consumption due to high resistance directly limits the application range of existing BDD electrodes. In this paper, the BDD/graphene/BDD (DGD) sandwich structure electrode was prepared, which effectively improved the conductivity of the electrode. Meanwhile, the sandwich electrode can effectively avoid the degradation of electrode performance caused by the large amount of non-diamond carbon introduced by heavy doping, such as the reduction of the electrochemical window and the decrease of physical and chemical stability. The microstructure and composition of the film were characterized by scanning electron microscope (SEM), atomic force microscopy (AFM), Raman spectroscopy, and transmission electron microscopy (TEM). Then, the degradation performance of citric acid (CA), catechol, and tetracycline hydrochloride (TCH) by DGD electrodes was systematically studied by total organic carbon (TOC) and Energy consumption per unit TOC removal (EC_TOC). Compared with the single BDD electrode, the new DGD electrode improves the mobility of the electrode and reduces the mass transfer resistance by 1/3, showing better water treatment performance. In the process of dealing with Citric acid, the step current of the DGD electrode was 1.35 times that of the BDD electrode, and the energy utilization ratio of the DGD electrode was 2.4 times that of the BDD electrode. The energy consumption per unit TOC removal (EC_TOC) of the DGD electrode was lower than that of BDD, especially Catechol, which was reduced to 66.9% of BDD. The DGD sandwich electrode, as a new electrode material, has good electrochemical degradation performance and can be used for high-efficiency electrocatalytic degradation of organic pollutants.

In order to investigate the competitive interaction between nanoparticles and twin, the eutectic Si microstructures in Al–10Si (wt. %) base alloys with exclusive and combined addition of Sr and Sb are characterized by combined TEM and atom probe tomography (APT). The chemical short range order in Sb–Sb and Sb–Sr pairs is revealed by ab initio molecular dynamics simulation, which promotes the formation of clusters and nanoparticles. The coexistence of nanoparticles and twins is observed in Sb containing alloys, with a negative correlation in the corresponding number density, owing to the competitive stacking of precursors and individual atoms at the solid–liquid interface. Large size particles around 70 nm with a uniform distribution of Sr atoms are formed in Al–10Si–0.35Sb–0.015Sr (wt. %) alloys, due to the precursor aggregation and homogeneous nucleation in the droplets that nucleation are depressed. A model for the formation of nanoparticles and their interaction with twins is proposed.

Boron-doped diamond thin films exhibit extensive applications in chemical sensing, in which the performance could be further enhanced by nano-structuring of the surfaces. In order to discover the relationship between diamond nanostructures and properties, this paper is dedicated to deep learning target detection methods. However, great challenges, such as noise, unclear target boundaries, and mutual occlusion between targets, are inevitable during the target detection of nanostructures. To tackle these challenges, DWS-YOLOv8 (DCN + WIoU + SA + YOLOv8n) is introduced to optimize the YOLOv8n model for the detection of diamond nanostructures. A deformable convolutional C2f (DCN_C2f) module is integrated into the backbone network, as is a shuffling attention (SA) mechanism, for adaptively tuning the perceptual field of the network and reducing the effect of noise. Finally, Wise-IoU (WIoU)v3 is utilized as a bounding box regression loss to enhance the model’s ability to localize diamond nanostructures. Compared to YOLOv8n, a 9.4% higher detection accuracy is achieved for the present model with reduced computational complexity. Additionally, the enhancement of precision (P), recall (R), mAP@0.5, and mAP@0.5:0.95 is demonstrated, which validates the effectiveness of the present DWS-YOLOv8 method. These methods provide effective support for the subsequent understanding and customization of the properties of surface nanostructures.

Bacterial colonies detecting and counting is tedious and time-consuming work. Fortunately CNN (convolutional neural network) detection methods are effective for target detection. The bacterial colonies are a kind of small targets, which have been a difficult problem in the field of target detection technology. This paper proposes a small target enhancement detection method based on double CNNs, which can not only improve the detection accuracy, but also maintain the detection speed similar to the general detection model. The detection method uses double CNNs. The first CNN uses SSD_MOBILENET_V1 network with both target positioning and target recognition functions. The candidate targets are screened out with a low confidence threshold, which can ensure no missing detection of small targets. The second CNN obtains candidate target regions according to the first round of detection, intercepts image sub-blocks one by one, uses the MOBILENET_V1 network to filter out targets with a higher confidence threshold, which can ensure good detection of small targets. Through the two-round enhancement detection method has been transplanted to the embedded platform NVIDIA Jetson AGX Xavier, the detection accuracy of small targets is significantly improved, and the target error detection rate and missed detection rate are reduced to less than 1%.

Polishing pad conditioners are of critical importance in chemical mechanical polishing (CMP), acting as a key determinant of CMP efficiency and an indispensable consumable in the polishing process. In addition to acid–alkali resistance and outstanding stability, stringent requirements are also imposed on the physical properties of conditioners, including high hardness and wear resistance. Diamond films, with their exceptional comprehensive performance, can satisfactorily fulfill these demanding specifications. In this work, to investigate the bonding strength and wear resistance of diamond films deposited on a silicon carbide (SiC) substrate, four groups of diamond films with distinct processing parameters were synthesized via hot wire chemical vapor deposition (HWCVD) on SiC substrates. Nano-scratch tests were employed to characterize the bonding strength at the diamond film/SiC substrate interface, while wear tests under humid conditions with a 500 g load, accompanied by in-depth analysis of the associated wear mechanisms, were conducted. The results demonstrate that diamond films exhibit tremendous application potential as CMP pad conditioners in CMP processes.