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Abstract Active oxygen highly affects the efficiency and stability of perovskite solar cells (PSCs) owing to the capacity to either passivate defects or decompose perovskite lattice. To better understand the in‐depth interaction, we demonstrate for the first time that photooxidation mechanism in all‐inorganic perovskite film dominates the phase deterioration kinetics by forming superoxide species in the presence of light and oxygen, which is significantly different from that in organic‒inorganic hybrid and even tin‐based perovskites. In all‐inorganic perovskites, the superoxide species prefer to oxidize longer and weaker Pb‒I bond to PbO and I2, leaving the much stable CsPbBr3 phase. From this chemical proof‐of‐concept, we employ an organic bioactive factor, Tanshinone IIA, as a superoxide sweeper to enhance the environmental tolerance of inorganic perovskite, serving as a “skincare” agent for anti‐aging organisms. Combined with another key point on healing defective lattice, the best carbon‐based all‐inorganic CsPbI2Br solar cell delivers an efficiency as high as 15.12% and superior stability against oxygen, light, humidity, and heat attacks. This method is also applicable to enhance the efficiency of p‒i‒n inverted (Cs0.05MA0.05FA0.9)Pb(I0.93Br0.07)3 cell to 23.46%. These findings not only help us understand the perovskite decomposition mechanisms in depth but also provide a potential strategy for advanced PSC platforms.

BackgroundMany screening and diagnostic methods are currently available for biliary atresia (BA), but the early and accurate diagnosis of BA remains a challenge with existing methods. This study aimed to use deep learning algorithms to intelligently analyze the ultrasound image data, build a BA ultrasound intelligent diagnostic model based on the convolutional neural network, and realize an intelligent diagnosis of BA.MethodsA total of 4,887 gallbladder ultrasound images of infants with BA, non-BA hyperbilirubinemia, and healthy infants were collected. Two mask region convolutional neural network (Mask R-CNN) models based on different backbone feature extraction networks were constructed. The diagnostic performance between the two models was compared through good-quality images at the image level and the patient level. The diagnostic performance between the two models was compared through poor-quality images. The diagnostic performance of BA between the model and four pediatric radiologists was compared at the image level and the patient level.ResultsThe classification performance of BA in model 2 was slightly higher than that in model 1 in the test set, both at the image level and at the patient level, with a significant difference of p = 0.0365 and p = 0.0459, respectively. The classification accuracy of model 2 was slightly higher than that of model 1 in poor-quality images (88.3% vs. 86.4%), and the difference was not statistically significant (p = 0.560). The diagnostic performance of model 2 was similar to that of the two radiology experts at the image level, and the differences were not statistically significant. The diagnostic performance of model 2 in the test set was higher than that of the two radiology experts at the patient level (all p

BackgroundPrevious models for differentiating benign and malignant thyroid nodules(TN) have predominantly focused on the characteristics of the nodules themselves, without considering the specific features of the thyroid gland(TG) in patients with Hashimoto’s thyroiditis(HT). In this study, we analyzed the clinical and ultrasound radiomics(USR) features of TN in patients with HT and constructed a model for differentiating benign and malignant nodules specifically in this population.MethodsWe retrospectively collected clinical and ultrasound data from 227 patients with TN and concomitant HT(161 for training, 66 for testing). Two experienced sonographers delineated the TG and TN regions, and USR features were extracted using Python. Lasso regression and logistic analysis were employed to select relevant USR features and clinical data to construct the model for differentiating benign and malignant TN. The performance of the model was evaluated using area under the curve(AUC), calibration curves, and decision curve analysis(DCA).ResultsA total of 1,162 USR features were extracted from TN and the TG in the 227 patients with HT. Lasso regression identified 14 features, which were used to construct the TN score, TG score, and TN+TG score. Univariate analysis identified six clinical predictors: TI-RADS, echoic type, aspect ratio, boundary, calcification, and thyroid function. Multivariable analysis revealed that incorporating USR scores improved the performance of the model for differentiating benign and malignant TN in patients with HT. Specifically, the TN+TG score resulted in the highest increase in AUC(from 0.83 to 0.94) in the clinical prediction model. Calibration curves and DCA demonstrated higher accuracy and net benefit for the TN+TG+clinical model.ConclusionUSR features of both the TG and TN can be utilized for differentiating benign and malignant TN in patients with HT. These findings highlight the importance of considering the entire TG in the evaluation of TN in HT patients, providing valuable insights for clinical decision-making in this population.

The Haxi gold deposit located in the Hatu–Saertuohai metallogenic belt of the west Junggar region, China, is a newly discovered gold deposit with proven reserves of ∼10 tons of gold and an average grade of 6.70 g/t. Primarily, the deposit is hosted in the early Carboniferous Tailegula Formation, controlled by the NEE-trending Anqi fault. The gold ore bodies contain gold-bearing quartz veins and altered basalt. The ore mineral is dominated by abundant sulfides, such as pyrite, arsenopyrite, chalcopyrite, and a little gersdorffite. To date, three types of fluid inclusion in quartz veins have been identified: liquid–gas (V-type), CO2–H2O (C-type), and liquid–rich (L-type). The ore-forming fluids exhibit medium homogenization temperatures (Th) of 226 °C–325 °C with low salinities of 2.24–9.34 wt% NaCl equivalent and low densities from 0.72 to 0.88 g/cm3. The δD values range from −115.3‰ to −100.7‰, with an average value of −109.1‰; the δ18O values range from 11.3‰ to 12.2‰, with an average value of 11.8‰; and the δ34S values in sulfide range from 0.3‰ to 1.8‰, with an average of 1.2‰. The average values of 206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb in sulfide are 18.059, 15.547, and 37.996, respectively. To summarize, the metallogenic fluids were derived not from a single source but from late magmatic–hydrothermal fluid mixed with paleo-atmospheric water; furthermore, the ore-forming materials principally originated from a crust–mantle mixed source. The Pb model age calculated using Hautman’s formula is 347–365 Ma, leading to the speculation that the metallogenic period may be Devonian–Carboniferous.

All-inorganic perovskite nanocrystals (NCs) of CsPbX3 (X = Cl, Br, I) are promising for displays due to wide color gamut, narrow emission bandwidth, and high photoluminescence quantum yield (PLQY). However, pure red perovskite NCs prepared by mixing halide ions often result in defects and spectral instabilities. We demonstrate a method to prepare stable pure red emission and high-PLQY-mixed-halide perovskite NCs through simultaneous halide-exchange and ligand-exchange. CsPbBr3 NCs with surface organic ligands are first synthesized using the ligand-assisted reprecipitation (LARP) method, and then ZnI2 is introduced for anion exchange to transform CsPbBr3 to CsPbBrxI3−x NCs. ZnI2 not only provides iodine ions but also acts as an inorganic ligand to passivate surface defects and prevent ion migration, suppressing non-radiative losses and halide segregation. The luminescence properties of CsPbBrxI3−x NCs depend on the ZnI2 content. By regulating the ZnI2 exchange process, red CsPbBrxI3−x NCs with organic/inorganic hybrid ligands achieve near-unity PLQY with a stable emission peak at 640 nm. The CsPbBrxI3−x NCs can be combined with green CsPbBr3 NCs to construct white light-emitting diodes with high-color gamut. Our work presents a facile ion exchange strategy for preparing spectrally stable mixed-halide perovskite NCs with high PLQY, approaching the efficiency limit for display or lighting applications.

Chromite is a strategic mineral resource for many countries, and chromite deposit occurrences are widespread in the ultramafic rocks of the Yarlung Zangbo ophiolite belt, particularly in the harzburgite unit of the mantle section. Conducting field surveys in complex and poorly accessible terrain is challenging, expensive, and time-consuming. Remote sensing is an advanced method of achieving modern geological work and is a powerful technical means of geological research and mineral exploration. In order to delineate outcrops of chromite-bearing mantle peridotite, the present research study integrates seven image-enhancement techniques, including optimal band combination, decorrelation stretching, band ratio, independent component analysis, principal component analysis, minimum noise fraction, and false color composite, for the interpretation of Landsat8 OLI and WorldView-2 satellite data. This integrated approach allows the effective discrimination of chromite-containing peridotite outcrops in the Luobusa area, Tibet. The interpretation results derived from these integrated image-processing techniques were systematically verified in the field and formed the basis of the feature selection process of different lithologies supported by the support vector machine algorithm. Furthermore, the distribution range of the ferric contamination anomaly is detected through the de-interference abnormal principal component thresholding technique, which shows a high spatial matching relationship with mantle peridotite. This is the first study to utilize Landsat8 OLI and WorldView-2 remote sensing satellite data to explore the largest chromite deposit in China, which enriches the research methods for the chromite deposits in the Luobusa area. Accordingly, the results of this investigation indicate that the integration of information extracted from image-processing algorithms using remote sensing data could be a broadly applicable tool for prospecting chromite ore deposits associated with ophiolitic complexes in mountainous and inaccessible regions such as Tibet’s ophiolitic zones.

IntroductionThe accurate assessment of the stages of hepatic fibrosis in children with biliary atresia (BA) before performing Kasai portoenterostomy (KPE) is of utmost importance. Some studies demonstrated that ultrasound elastography can be used to assess the stages of hepatic fibrosis by detecting liver stiffness. Therefore, the aim of this work was to explore the usefulness of sound touch elastography (STE) for preoperatively assessing liver cirrhosis in infants with BA.MethodsA total of 189 children from the Hunan Children’s Hospital with highly suspected BA were selected for this study, and their preoperative liver STE values and related clinical data were collected. The pathological results of the liver stages were considered as the gold standard. Spearman correlation was used to analyze the correlation between each parameter and the stage of hepatic fibrosis, and the receiver operator characteristic (ROC) curve was used to analyze the diagnostic performance for cirrhosis of each parameter.ResultsAmong the selected 189 patients with suspected BA, 159 were included in this study and were composed of 3 at hepatic fibrosis stage F1, 45 at stage F2, 41 at stage F3, and 70 at stage F4, while no patients at stage F0 were present. Spearman correlation analysis showed that the liver STE value had the highest correlation with the stage of hepatic fibrosis, with a correlation coefficient of 0.813 (P < 0.001). The liver STE value had the highest diagnostic performance for hepatic cirrhosis compared to other biomarkers of serum fibrosis; the area under the ROC curve was 0.899 when the best cut-off value was 14.57 kPa. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 78.6, 84.3, 79.7, 83.3, and 81.8%, respectively.ConclusionThe liver STE value has a high correlation with the stage of hepatic fibrosis in children with BA. STE has a good diagnostic performance in evaluating cirrhosis before KPE in children with BA.

Metal halide perovskites have become a research highlight in the optoelectronic field due to their excellent properties. The perovskite light-emitting diodes (PeLEDs) have achieved great improvement in performance in recent years, and the construction of quasi-2D perovskites by incorporating large-size organic cations is an effective strategy for fabricating efficient PeLEDs. Here, we incorporate the fluorine meta-substituted phenethylammonium bromide (m-FPEABr) into CsPbBr3 to prepare quasi-2D perovskite films for efficient PeLEDs, and study the effect of fluorine substitution on regulating the crystallization kinetics and phase distribution of the quasi-2D perovskites. It is found that m-FPEABr allows the transformation of low-n phases to high-n phases during the annealing process, leading to the suppression of n = 1 phase and increasing higher-n phases with improved crystallinity. The rational phase distribution results in the formation of multiple quantum wells (MQWs) in the m-FPEABr based films. The carrier dynamics study reveals that the resultant MQWs enable rapid energy funneling from low-n phases to emission centers. As a result, the green PeLEDs achieve a peak external quantum efficiency of 16.66% at the luminance of 1279 cd m−2. Our study demonstrates that the fluorinated organic cations would provide a facile and effective approach to developing high-performance PeLEDs.