Partial Discharge Signal Pattern Recognition of Composite Insulation Defects in Cross-Linked Polyethylene Cables.

To investigate the pattern recognition of complex defect types in XLPE (cross-linked polyethylene) cable partial discharges and analyze the effectiveness of identifying partial discharge signal patterns, this study employs the variational mode decomposition (VMD) algorithm alongside entropy theories such as power spectrum entropy, fuzzy entropy, and permutation entropy for feature extraction from partial discharge signals of composite insulation defects. The mean power spectrum entropy (PS), mean fuzzy entropy (FU), mean permutation entropy (PE), as well as the permutation entropy values of IMF2 and IMF13 (Pe) are selected as the characteristic quantities for four categories of partial discharge signals associated with composite defects. Six hundred samples are selected from the partial discharge signals of each type of compound defect, amounting to a total of 2400 samples for the four types of compound defects combined. Each sample comprises five feature values, which are compiled into a dataset. A Snake Optimization Algorithm-optimized Support Vector Machine (SO-SVM) model is designed and trained, using the extracted features from cable partial discharge datasets as case examples for recognizing cable partial discharge signals. The identification outcomes from the SO-SVM model are then compared with those from conventional learning models. The results demonstrate that for partial discharge signals of XLPE cable composite insulation defects, the SO-SVM model yields better identification results than traditional learning models. In terms of recognition accuracy, for scratch and water ingress defects, SO-SVM improves by 14.00% over BP (Back Propagation) neural networks, by 5.66% over GA-BP (Genetic Algorithm-Back Propagation), and by 12.50% over SVM (support vector machine). For defects involving metal impurities and scratches, SO-SVM improves by 13.39% over BP, 9.34% over GA-BP, and 12.56% over SVM. For defects with metal impurities and water ingress, SO-SVM shows enhancements of 13.80% over BP, 9.47% over GA-BP, and 13.97% over SVM. Lastly, for defects combining metal impurities, water ingress, and scratches, SO-SVM registers increases of 11.90% over BP, 9.59% over GA-BP, and 12.05% over SVM.

In Situ Imaging of Two-Dimensional Crystal Growth Using a Heat-Resistant Optical Microscope.

Revealing low-dimensional material growth dynamics is critical for crystal growth engineering. However, in a practical high-temperature growth system, the crystal growth process is a black box because of the lack of heat-resistant imaging tools. Here, we develop a heat-resistant optical microscope and embed it in a chemical vapor deposition (CVD) system to investigate two-dimensional (2D) crystal growth dynamics. This in situ optical imaging CVD system can tolerate temperatures of ≤900 °C with a spatial resolution of ∼1 µm. The growth of monolayer MoS2 crystals was studied as a model for 2D crystal growth. The nucleation and growth process have been imaged. Model analysis and simulation have revealed the growth rate, diffusion coefficient, and spatial distribution of the precursor. More importantly, a new vertex-kink-ledge model has been suggested for monolayer crystal growth. This work provides a new technique for in situ microscopic imaging at high temperatures and fundamental insight into 2D crystal growth.

A novel nanoprobe for visually investigating the controversial role of miRNA-34a as an oncogene or tumor suppressor in cancer cells.

MiRNA-targeted therapy has become a hot topic in current cancer research. The key to this treatment strategy is to clarify the specific role of miRNA in cancer. However, the roles of some miRNAs acting as oncogenic or tumor suppressors are still controversial, which are influenced by different tumor types, even in the same cancer type. Hence, we designed a novel fluorescent nanoprobe based on polydopamine nanoparticles (PDA NPs) for simultaneously detecting caspase-3 and miRNA-34a within living cells. The specific role of miRNA-34a in different cancer cells could be further identified by studying the expression alterations of caspase-3 and miRNA-34a. Confocal imaging indicated that miRNA-34a indeed acted as a tumor suppressor in anticancer drug-treated MCF-7 and HeLa cells, where the effect of miRNA-34a remains controversial. The designed nanoprobe can offer a promising approach to ascertain the oncogenic or tumor-suppressing role of miRNA in different cancer cells with a simple visualization method, which has valuable implications for exploring the practicability of precision therapy focused on miRNA and evaluating the efficacy of new miRNA-targeted anticancer medications.

Progress on the in situ imaging of growth dynamics of two-dimensional materials.

One key issue to promote the industrialization of two-dimensional (2D) materials is to grow high-quality and large-scale 2D materials. Investigations of the growth mechanism and growth dynamics are of fundamental importance for the growth of 2D material, in which in situ imaging is highly needed. By applying different in situ imaging techniques, details for growth process, including nucleation and morphology evolution, can be obtained. This review summarizes the recent progress on the in situ imaging of 2D material growth, in which the growth rate, kink dynamics, domain coalescence, growth across the substrate steps, single-atom catalysis, and intermediates have been revealed.

Liquid Phase Edge Epitaxy of Transition-Metal Dichalcogenide Monolayers.

Precise monolayer epitaxy is important for two-dimensional (2D) semiconductors toward future electronics. Here, we report a new self-limited epitaxy approach, liquid phase edge epitaxy (LPEE), for precise-monolayer epitaxy of transition-metal dichalcogenides. In this method, the liquid solution contacts 2D grains only at the edges, which confines the epitaxy only at the grain edges and then precise monolayer epitaxy can be achieved. High-temperature in situ imaging of the epitaxy progress directly supports this edge-contact epitaxy mechanism. Typical transition-metal dichalcogenide monolayers (MX2, M = Mo, W, and Re; X = S or Se) have been obtained by LPEE with a proper choice of molten alkali halide solvents (AL, A = Li, Na, K, and Cs; L = Cl, Br, or I). Furthermore, alloying and magnetic-element doping have also been realized by taking advantage of the liquid phase epitaxy approach. This LPEE method provides a precise and highly versatile approach for 2D monolayer epitaxy and can revolutionize the growth of 2D materials toward electronic applications.

CdSSe Nano-Flowers for Ultrasensitive Raman Detection of Antibiotics.

Surface-enhanced Raman scattering (SERS) technique is widely used for the highly sensitive detection of trace residues due to its unparalleled signal amplification ability and plays an important role in food safety, environmental monitoring, etc. Herein, CdSSe nano-flowers (CdSSe NFs) are synthesized via the chemical vapor deposition (CVD) method. CdSSe NFs thin film is used as a SERS substrate with an ultralow limit of detection (LOD, 10-14 M), high apparent enhancement factor (EF, 3.62 × 109), and excellent SERS stability (relative standard deviation, RSD = 3.05%) for probe molecules of Rh6G. Further, CdSSe NFs substrate is successfully applied in the sensitive, quantitative, and label-free analysis of ciprofloxacin (CIP) and enrofloxacin (ENR) antibiotics, which exhibit LODs of below 0.5 ppb. This excellent SERS platform may be widely utilized for sensitive life science and environmental sensing.