Revealing unusual bandgap shifts with temperature and bandgap renormalization effect in phase-stabilized metal halide perovskites

Hybrid organic-inorganic metal halide perovskites are emerging materials in photovoltaics, whose bandgap is one of the most crucial parameters governing their light harvesting performance. Here we present temperature and photocarrier density dependence of the bandgap in two phase-stabilized perovskite thin films (MA0.3FA0.7PbI3 and MA0.3FA0.7Pb0.5Sn0.5I3) using photoluminescence and absorption spectroscopy. Contrasting bandgap shifts with temperature are observed between the two perovskites. By utilizing X-ray diffraction and in situ high pressure photoluminescence spectroscopy, we show that the thermal expansion plays only a minor role on the large bandgap blueshift due to the enhanced structural stability in our samples. Our first-principles calculations further demonstrate the significant impact of thermally induced lattice distortions on the bandgap widening and reveal that the anomalous trends are caused by the competition between the static and dynamic distortions. Additionally, both the bandgap renormalization and band filling effects are directly observed for the first time in fluence-dependent photoluminescence measurements and are employed to estimate the exciton effective mass. Our results provide new insights into the basic understanding of thermal and charge-accumulation effects on the band structure of hybrid perovskites

Construction of machine learning models based on transrectal ultrasound combined with contrast-enhanced ultrasound to predict preoperative regional lymph node metastasis of rectal cancer

Purpose: Constructing a machine learning model based on transrectal ultrasound (TRUS) combined with contrast-enhanced ultrasound (CEUS) to predict preoperative regional lymph node metastasis (RLNM) of rectal cancer and provide new references for decision-making. Materials and methods: 233 patients with rectal cancer were enrolled and underwent TRUS and CEUS prior to surgery. Clinicopathological and ultrasound data were collected to analyze the correlation of RLNM status, clinical features and ultrasound parameters. A 75% training set and 25% test set were utilized to construct seven machine learning algorithms. The DeLong test was used to assess the model's diagnostic performance, then chose the best one to predict RLNM of rectal cancer. Results: The diagnostic performance was most dependent on the following: MMT difference (36), length (30), location (29), AUC ratio (27), and PI ratio (24). The prediction accuracy, sensitivity, specificity, precision, and F1 score range of KNN, Bayes, MLP, LR, SVM, RF, and LightGBM were (0.553–0.857), (0.000–0.935), (0.600–1.000), (0.557–0.952), and (0.617–0.852), respectively. The LightGBM model exhibited the optimal accuracy (0.857) and F1 score (0.852). The AUC for machine learning analytics were (0.517–0.941, 95% CI: 0.380–0.986). The LightGBM model exhibited the highest AUC (0.941, 95% CI: 0.843–0.986), though no statistic significant showed in comparison with the SVM, LR, RF, and MLP models (P > 0.05), it was significantly higher than that of the KNN and Bayes models (P < 0.05). Conclusion: The LightGBM machine learning model based on TRUS combined with CEUS may help predict RLNM prior to surgery and provide new references for clinical treatment in rectal cancer

Experimental Demonstration of the Impact of the Parameters of Floating Guard Ring on Planar InP&#x002F;InGaAs-Based Avalanche Photodiodes&#x2019; Performance and Its Optimization

Suppression pre-breakdown in planar separated absorption, grading, charge and multiplication (SAGCM) avalanche photodiodes (APDs) with the help of Floating Guard Ring (FGR) is still a research hotspot. In this paper, a lattice-matched InP&#x002F;InGaAs-based SAGCM structure is grown by Metal-Organic Chemical Vapor Deposition and thus the planar 50 &#x03BC;m photosensitive area APDs with different FGR structures are fabricated using zinc diffusion process. The effects of the different lengths of FGR (4 &#x03BC;m, 8 &#x03BC;m, 12 &#x03BC;m, 16 &#x03BC;m), and the different distances between FGR and the Zn diffused p&#x002B; region (4 &#x03BC;m, 6 &#x03BC;m, 8 &#x03BC;m, 10 &#x03BC;m) on the optoelectrical characteristics are deeply studied. The results from optical microscope, scanning electron microscope and current-voltage curves reveal that there is an optimal length and distance for the punch-through and breakdown voltage. Furthermore, the nA-level dark current, gain (M) of up to 10 at breakdown voltage, responsibility as high as 9.01 A&#x002F;W at M &#x003D; 10 and quantum efficiency equaling to 72&#x0025; are also tested and calculated, proving the good performance of our devices. The optimized FGR parameters and related structure are expected to be helpful for obtaining high-performance, small-size InP&#x002F;InGaAs-based APDs