Unveiling the Intrinsic Photophysics in Quasi-Two-Dimensional Perovskites.

The two-dimensional (2D) perovskites have drawn intensive attention due to their unique stability and outstanding optoelectronic properties. However, the debate surrounding the spatial phase distribution and band alignment among different 2D phases in the quasi-2D perovskite has created complexities in understanding the carrier dynamics, hindering material and device development. In this study, we employed highly sensitive transient absorption spectroscopy to investigate the carrier dynamics of (BA)2(MA)n-1PbnI3n+1 quasi-2D Ruddlesden-Popper perovskite thin films, nominally prepared as n = 4. We observed the carrier-density-dependent electron and hole transfer dynamics between the 2D and three-dimensional (3D) phases. Under a low carrier density within the linear response range, we successfully resolved three ultrafast processes of both electron and hole transfers, spanning from hundreds of femtoseconds to several picoseconds, tens to hundreds of picoseconds, and hundreds of picoseconds to several nanoseconds, which can be attributed to lateral-epitaxial, partial-epitaxial, and disordered-interface heterostructures between 2D and 3D phases. By considering the interplay among the phase structure, band alignment, and carrier dynamics, we have proposed material synthesis strategies aimed at enhancing the carrier transport. Our results not only provide deep insights into an accurate intrinsic photophysics of quasi-2D perovskites but also inspire advancements in the practical application of these materials.

Multi-phenotype response and cadmium detection of rice stem under toxic cadmium exposure.

Rice stem is the sole conduit for cadmium translocation from underground to aboveground. The presence of cadmium can trigger responses of rice stem multi-phenotype, affecting metabolism, reducing yield, and altering composition, which is related to crop growth, food safety, and new energy utilization. Exploring the adversity response of plant phenotypes can provide a reliable assessment of growth status. However, the phytotoxicity and mechanism of cadmium stress on rice stem remain unclear. Here, we systematically revealed the response mechanisms of cadmium accumulation, adversity physiology, and morphological characteristic in rice stem under cadmium stress for the first time with concentration gradients of CK, 5, 25, 50, and 100 µM, and duration gradients of Day 5, Day 10, Day 15, and Day 20. The results indicated that cadmium stress led to a significant increase in cadmium accumulation, accompanied by the adversity response in stem phenotypes. Specifically, cadmium can cause fluctuations in soluble protein and disturbance of malondialdehyde (MDA), which reflects lipid peroxidation induced by cadmium accumulation. Lipid peroxidation inhibited rice growth by causing (1) a reduction in stem length, diameter, and weight, (2) suppression of air cavity, vascular bundle, parenchyma, and epidermal hair, and (3) disruption of cell structure. Furthermore, rapid detection of cadmium was realized based on the combination of laser-induced breakdown spectroscopy (LIBS) and machine learning, which took less than 3 min. The established qualitative model realized the precise discrimination of cadmium stress degrees with a prediction accuracy exceeding 92 %, and the quantitative model achieved the outstanding prediction effect of cadmium, with Rp of 0.9944. This work systematically revealed the phytotoxicity of cadmium on rice stem multi-phenotype from a novel perspective of lipid peroxidation and realized the rapid detection of cadmium in rice stem, which provided the technical tool and theoretical foundation for accurate prevention and efficient control of heavy metal risks in crops.

X-Site Substituted 2D Cs2 Pb(SCN)2 Br2 Perovskites for X-Ray Detection.

2D Ruddlesden-Popper (RP) perovskites have been intensively investigated due to their superior stability and outstanding optoelectrical properties. However, investigations on 2D RP perovskites are mainly focused on A-site substituted perovskites and few reports are on X-site substituted perovskites especially in X-ray detection field. Here, X-site substituted 2D RP perovskite Cs2 Pb(SCN)2 Br2 polycrystalline wafers are prepared and systematically studied for X-ray detection. The obtained wafers show a large resistivity of 2.0 × 1010 Ω cm, a high ion activation energy of 0.75 eV, a small current drift of 2.39 × 10-6 nA cm-1 s-1 V-1 , and charge carrier mobility-lifetime product under X-ray as high as 1.29 × 10-4 cm2 V-1 . These merits enable Cs2 Pb(SCN)2 Br2 wafer detectors with a sensitivity of 216.3 µC Gyair -1 cm-2 , a limit of detection of 42.4 nGyair s-1 , and good imaging ability with high spatial resolution of 1.08 lp mm-1 . In addition, Cs2 Pb(SCN)2 Br2 wafer detectors demonstrate excellent operational stability under high working field up to 2100 V cm-1 after continuous X-ray irradiation with a total dose of 45.2 Gyair . The promising features such as short octahedral spacing and weak ion migration will open up a new perspective and opportunity for SCN-based 2D perovskites in X-ray detection.

Filamentous cyanobacteria and hydrophobic protein in extracellular polymeric substances facilitate algae-bacteria aggregation during partial nitrification.

In algae-bacteria symbiotic wastewater treatment, the excellent settling performance of algae-bacteria aggregates is critical for biomass separation and recovery. Here, the composition of extracellular polymeric substances (EPS), microbial profiles, and functional genes of algae-bacteria aggregates were investigated at different solid retention times (SRTs) (10, 20, and 40 d) during partial nitrification in photo sequencing bioreactors (PSBRs). Results showed that SRTs greatly influenced the nitrogen transformation and the formation and morphological structure of algae-bacteria aggregates. The highest nitrite accumulation, the largest particle size (~1.54 mm) and the best settling performance were observed for the algae-bacteria aggregates in the PSBR with an SRT of 10 d, where the abundant occurrence of filamentous cyanobacteria with the highest ratio of chlorophyll a/b and the lowest EPS amount with the highest protein-to-polysaccharide ratio were observed. In particular, the EPS at 10 d of SRT contained a higher amount of protein-related hydrophobic groups and a lower ratio of α-helix/(ß-sheet + random coil), indicating a looser protein structure, which might facilitate the formation and stabilization of algae-bacteria aggregates. Moreover, algal-bacterial aggregation greatly depended on the composition and evolution of filamentous cyanobacteria (unclassified _o__Oscillatoriales and Phormidium accounted for 56.29 % of the identified algae at SRT 10 d). The metagenomic analysis further revealed that functional genes related to amino acid metabolism (e.g., genes of phenylalanine, tyrosine, and tryptophan biosynthesis) were expressed at high levels within 10 d of SRT. Overall, this study demonstrates the influence of EPS structures and filamentous cyanobacteria on algae-bacteria aggregation and reveals the biological mechanisms driving photogranule structure and function.

Regulating 3D Phase in Quasi-2D Perovskite Films for High-Performance and Stable Photodetectors.

The charge transport in quasi-2D perovskites limits their applications despite the superior stability and optoelectronic properties. Herein, a novel strategy is proposed to enhance the charge transport by regulating 3D perovskite phase in quasi-2D perovskite films. The carbohydrazide (CBH) as an additive is introduced into (PEA)2 MA3 Pb4 I13 precursors, which slows down the crystallization process and improves the phase ratio and crystal quality of the 3D phase. This structure change results in a significant improvement in charge transport and extraction, leading to the device demonstrating an almost 100% internal quantum efficiency, a peak responsivity of 0.41 A W-1 , and a detectivity of 1.31 × 1012 Jones at 570 nm under 0 V bias. Furthermore, the air and moisture stability of (PEA)2 MA3 Pb4 I13 films is not deteriorated but gets significantly improved due to the better crystal quality and the passivation of defects by the residual CBH molecule. This work demonstrates a strategy for improving the charge transport properties of quasi-2D perovskites and also sheds light on solving the stability issue of 3D perovskite films via the proper passivation or additives, which will inspire the fast development of the perovskite community.

Function analysis of GhWRKY53 regulating cotton resistance to verticillium wilt by JA and SA signaling pathways.

WRKY transcription factors (TFs) play an important role in regulating the mechanism of plant self-defense. However, the function of most WRKY TFs in upland cotton (Gossypium hirsutum) is still unknown. Hence, studying the molecular mechanism of WRKY TFs in the resistance of cotton to Verticillium dahliae is of great significance to enhancing cotton disease resistance and improving its fiber quality. In this study, Bioinformatics has been used to characterize the cotton WRKY53 gene family. we analyzed the GhWRKY53 expression patterns in different resistant upland cotton cultivars treated with salicylic acid (SA) and methyl jasmonate (MeJA). Additionally, GhWRKY53 was silenced using a virus-induced gene silencing (VIGS) to determine the contribution of GhWRKY53 to V. dahliae resistance in cotton. The result showed that GhWRKY53 mediated SA and MeJA signal transduction pathways. After VIGS of the GhWRKY53, the ability of cotton to resist V. dahliae decreased, indicating that the GhWRKY53 could be involved in the disease resistance mechanism of cotton. Studies on the levels of SA and jasmonic acid (JA) and their related pathway genes demonstrated that the silencing of GhWRKY53 inhibited the SA pathway and activated the JA pathway, thereby reducing the resistance of plants to V. dahliae. In conclusion, GhWRKY53 could change the tolerance of upland cotton to V. dahliae by regulating the expression of SA and JA pathway-related genes. However, the interaction mechanism between JA and SA signaling pathways in cotton in response to V. dahliae requires further study.

Effects of Chemical Valences of Sulfur on the Performance of CsFAMA Perovskite Solar Cells.

The low electrical conductivity and the high surface defect density of the TiO2 electron transport layer (ETL) limit the quality of the following perovskite (PVK) layers and the power conversion efficiency (PCE) of corresponding perovskite solar cells (PSCs). Sulfur was reported as an effective element to passivate the TiO2 layer and improve the PCE of PSCs. In this work, we further investigate the effect of chemical valences of sulfur on the performance of TiO2/PVK interfaces, CsFAMA PVK layers, and solar cells using TiO2 ETL layers treated with Na2S, Na2S2O3, and Na2SO4, respectively. Experimental results show that the Na2S and Na2S2O3 interfacial layers can enlarge the grain size of PVK layers, reduce the defect density at the TiO2/PVK interface, and improve the device efficiency and stability. Meanwhile, the Na2SO4 interfacial layer leads to a smaller perovskite grain size and a slightly degraded TiO2/PVK interface and device performance. These results indicate that S2- can obviously improve the quality of TiO2 and PVK layers and TiO2/PVK interfaces, while SO42- has little effects, even negative effects, on PSCs. This work can deepen the understanding of the interaction between sulfur and the PVK layer and may inspire further progress in the surface passivation field.

Trends in digital detection for the quality and safety of herbs using infrared and Raman spectroscopy.

Herbs have been used as natural remedies for disease treatment, prevention, and health care. Some herbs with functional properties are also used as food or food additives for culinary purposes. The quality and safety inspection of herbs are influenced by various factors, which need to be assessed in each operation across the whole process of herb production. Traditional analysis methods are time-consuming and laborious, without quick response, which limits industry development and digital detection. Considering the efficiency and accuracy, faster, cheaper, and more environment-friendly techniques are highly needed to complement or replace the conventional chemical analysis methods. Infrared (IR) and Raman spectroscopy techniques have been applied to the quality control and safety inspection of herbs during the last several decades. In this paper, we generalize the current application using IR and Raman spectroscopy techniques across the whole process, from raw materials to patent herbal products. The challenges and remarks were proposed in the end, which serve as references for improving herb detection based on IR and Raman spectroscopy techniques. Meanwhile, make a path to driving intelligence and automation of herb products factories.

Probing the Genuine Carrier Dynamics of Semiconducting Perovskites under Sunlight.

Understanding the nature of photogenerated carriers and their subsequent dynamics in semiconducting perovskites is important for the development of solar cell materials and devices. However, most ultrafast dynamic measurements on perovskite materials were conducted under high carrier densities, which likely obscures the genuine dynamics under low carrier densities in solar illumination conditions. In this study, we presented a detailed experimental study of the carrier density-dependent dynamics in hybrid lead iodide perovskites from femtosecond to microsecond using a highly sensitive transient absorption (TA) spectrometer. From the dynamic curves with low carrier density in the linear response range, we observed two fast trapping processes that occurred in less than 1 ps and tens of picoseconds, attributed to the shallow traps, and two slow decays with lifetimes of hundreds of nanoseconds and longer than 1 µs, related to the trap-assisted recombination and trapping at deep traps. Further TA measurements clearly show that PbCl2 passivation can effectively reduce both shallow and deep trap densities. These results provide insights into the intrinsic photophysics of semiconducting perovskites with direct implications for photovoltaic and optoelectronic applications under sunlight.

Improving the Performance and High-Field Stability of FAPbBr3 Single Crystals in X-Ray Detection with Chenodeoxycholic Acid Additive.

Organometal halide perovskite single crystals are one of the most promising radiation detection materials due to their unique advantages of high absorption coefficient, long carrier diffusion length, and low defect density. However, the severe ion migration in perovskites deteriorates the X-ray detection performance under longtime and high-field operating conditions. This work reports an effective additive of chenodeoxycholic acid (CDCA), which can suppress the ion migration and improve the performance and the operational stability of FAPbBr3 single crystals (SCs) in X-ray detection significantl. The CDCA molecules in precursors effectively suppress the decomposition of FA ions, resulting in a better crystal orientation and stoichiometry. The trace amounts of CDCA residues in FAPbBr3 SCs improve the thermal stability and effectively suppress the ion migration. The resulting detector shows an impressive X-ray sensitivity up to 21 386.88 µC Gyair -1 cm-2 under -500 V and a detection limit of 15.23 nGyair s-1 . The response current of the detector at 225 V cm-1 field is barely changed under the 7200 s irradiation with a dose rate of 1.949 mGyair s-1 . This work provides insights for the additive selection and improving the operational stability of perovskite single crystals for commercial applications.

Fault Early Warning Model for High-Speed Railway Train Based on Feature Contribution and Causal Inference.

The demands for model accuracy and computing efficiency in fault warning scenarios are increasing as high-speed railway train technology continues to advance. The black box model is difficult to interpret, making it impossible for this technology to be widely adopted in the railway industry, which has strict safety regulations. This paper proposes a fault early warning machine learning model based on feature contribution and causal inference. First, the contributions of the features are calculated through the Shapley additive explanations model. Then, causal relationships are discovered through causal inference models. Finally, data from causal and high-contribution time series are applied to the model. Ablation tests are conducted with the Naïve Bayes, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and other models in order to confirm the efficiency of the method based on early warning data regarding the on-site high-speed train traction equipment circuit board failure. The findings indicate that the strategy improves the evaluation markers, including the early warning accuracy, precision, recall, and F1 score, by an average of more than 10%. There is a 35% improvement in the computing efficiency, and the model can provide feature causal graph verification for expert product decision-making.

End-to-End Fusion of Hyperspectral and Chlorophyll Fluorescence Imaging to Identify Rice Stresses.

Herbicides and heavy metals are hazardous substances of environmental pollution, resulting in plant stress and harming humans and animals. Identification of stress types can help trace stress sources, manage plant growth, and improve stress-resistant breeding. In this research, hyperspectral imaging (HSI) and chlorophyll fluorescence imaging (Chl-FI) were adopted to identify the rice plants under two types of herbicide stresses (butachlor (DCA) and quinclorac (ELK)) and two types of heavy metal stresses (cadmium (Cd) and copper (Cu)). Visible/near-infrared spectra of leaves (L-VIS/NIR) and stems (S-VIS/NIR) extracted from HSI and chlorophyll fluorescence kinetic curves of leaves (L-Chl-FKC) and stems (S-Chl-FKC) extracted from Chl-FI were fused to establish the models to detect the stress of the hazardous substances. Novel end-to-end deep fusion models were proposed for low-level, middle-level, and high-level information fusion to improve identification accuracy. Results showed that the high-level fusion-based convolutional neural network (CNN) models reached the highest detection accuracy (97.7%), outperforming the models using a single data source (<94.7%). Furthermore, the proposed end-to-end deep fusion models required a much simpler training procedure than the conventional two-stage deep learning fusion. This research provided an efficient alternative for plant stress phenotyping, including identifying plant stresses caused by hazardous substances of environmental pollution.

Therapeutic effects of shaogan fuzi decoction in rheumatoid arthritis: Network pharmacology and experimental validation.

Shaogan Fuzi Decoction (SGFD), one of the classical prescriptions of Chinese Medicine, has a long history in the treatment of rheumatoid arthritis (RA), but definitive studies on its efficacy and mechanism of action are lacking. This study aims to elucidate the pharmacodynamic role of SGFD against RA and the potential mechanisms based on a combination of network pharmacology and experimental verification. The RA model in rats was induced by intradermal injection of bovine type Ⅱ collagen and incomplete Freund's adjuvant at the tail root. SGFD was administered once a day by oral gavage for 4 weeks. After SGFD administration, rat's arthritis index (AI) score and paw swelling decreased to some extent, and synovial inflammation, vascular hyperplasia, and cartilage destruction of the ankle joint were improved. Simultaneously, thymus and spleen index and serum levels of C-reactive protein (CRP) were lowered. Network pharmacology revealed that quercetin, kaempferol, naringenin, formononetin isorhamnetin and licochalcone A were the potentialiy active components, and IL6, TP53, TNF, PTGS2, MAPK3 and IL-1ß were potential key targets for SGFD in the treatment of RA. Ingredients-targets molecular docking showed that the components had the high binding activity to these target proteins. The mechanism of SGFD for RA involves various biological functions and is closely correlated with TNF signaling pathway, Osteoclast differentiation, T cell receptor signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, NF-κB signaling pathway, toll-like receptor signaling pathway, and so on. Western blot and ELISA showed that the expression of toll-like receptor 4 (TLR4), nuclear factor kappa-B (NF-κB) p65, phosphorylated c-Jun N-terminal kinase (p-JNK), p-p38, phosphorylated extracellular regulated kinase (p-ERK) and TNF-α was significantly upregulated in the synovium of RA rats, and the levels of serum inflammatory factors were significantly increased. SGFD inhibits the activation of the TLR4/NF-κB/MAPK pathway and the expression/production of pro-inflammatory cytokines. In summary, SGFD could improve the symptoms and inflammatory response in collagen-induced arthritis (CIA) rat model. The mechanism might be related to the regulation of TLR4/MAPKs/NF-κB signaling pathway and the reduction of inflammatory factor release, which partially confirms the results predicted by network pharmacology.

Supplementation of polyphenol-rich grapes attenuates colitis, colitis-associated colon cancer, and disease-associated dysbiosis in mice, but fails to mitigate colitis in antibiotic-treated mice.

Polyphenols are known to interact with gut microbes that play key roles in maintaining gut health, but the role of gut microbiota modulation by polyphenols in mitigating colonic diseases is not fully established. We hypothesize that the interaction of polyphenols with the gut microbiota contributes to the attenuation of colitis and colitis-associated colon cancer (CAC). To test this hypothesis, we examined the effects of dietary supplementation of polyphenol-rich grape powder (GP) on azoxymethane (AOM) and dextran sulfate sodium (DSS)-induced colitis, CAC, and the gut microbiota in mice (study 1), and further compared anti-colitis effects of GP in regular and antibiotic-treated mice (study 2). Compared to the control diet that has matched non-polyphenol contents, 10% GP, but not 3% GP, attenuated AOM-DSS-induced colitis and tumor multiplicity by 29% (P<.05). Ten percent GP increased gut bacterial evenness and counteracted CAC-induced decrease of bacterial evenness and changes in microbial composition. Remarkably, the estimated gut bacterial functional profiles of healthy mice and diseased mice fed 10% GP were similar, and both were significantly different from those of diseased mice fed the control diet. Furthermore, 10% GP increased the relative abundance of butyrate-producing bacteria in the Lachnospiraceae family and enhanced the concentrations of fecal butyrate. Additionally, 10% GP mitigated DSS-induced colitis in conventional mice, but not the antibiotic-treated, gut microbe-depleted mice. Collectively, our studies demonstrate that grape polyphenols alleviate colonic diseases and prevent disease-associated dysbiosis, and their interaction with the gut microbiota may play a causative role in the protection of gut health.

Quantitative Extraction and Evaluation of Tomato Fruit Phenotypes Based on Image Recognition.

Tomato fruit phenotypes are important agronomic traits in tomato breeding as a reference index. The traditional measurement methods based on manual observation, however, limit the high-throughput data collection of tomato fruit morphologies. In this study, fruits of 10 different tomato cultivars with considerable differences in fruit color, size, and other morphological characters were selected as samples. Constant illumination condition was applied to take images of the selected tomato fruit samples. Based on image recognition, automated methods for measuring color and size indicators of tomato fruit phenotypes were proposed. A deep learning model based on Mask Region-Convolutional Neural Network (R-CNN) was trained and tested to analyze the internal structure indicators of tomato fruit. The results revealed that the combined use of these methods can extract various important fruit phenotypes of tomato, including fruit color, horizontal and vertical diameters, top and navel angles, locule number, and pericarp thickness, automatically. Considering several corrections of missing and wrong segmentation cases in practice, the average precision of the deep learning model is more than 0.95 in practice. This suggests a promising locule segmentation and counting performance. Vertical/horizontal ratio (fruit shape index) and locule area proportion were also calculated based on the data collected here. The measurement precision was comparable to manual operation, and the measurement efficiency was highly improved. The results of this study will provide a new option for more accurate and efficient tomato fruit phenotyping, which can effectively avoid artificial error and increase the support efficiency of relevant data in the future breeding work of tomato and other fruit crops.

Activation of persulfate via Mn doped Mg/Al layered double hydroxide for effective degradation of organics: Insights from chemical and structural variability of catalyst.

Considerable interest has been focusing on the activation of peroxydisulfate (PDS) by layered double hydroxide (LDH) for degradation of organic pollutants. However, understanding the structure and chemistry of LDH by which the activation of PDS could achieve a high degradation efficiency of organic compounds is an unsolved and fundamental question in advanced oxidation processes (AOPs), and one which, if harnessed, could enable the rational design of LDH with desired material properties. In this work, Mg/Al-LDH was synthesized with variable structures and compositions through doping different proportions of Mn2+. We advanced to understand this question of how LDH by these characteristics can affect the activation of PDS for degradation of organic pollutants. At a relatively low dosage of Mn (˂ 1%) in Mg/Al-LDH, the degradation rate of phenol by LDH activated PDS increased with the increase content of Mn, which was achieved by an increase of catalytic sites in Mg/Al-LDH interlayer. Rather, higher content of Mn (˃ 1%) significantly lowered the degradation performance of phenol as the decrease of interlayer space resulted in reduction of PDS intercalation in LDH and the formation of secondary Mn-related minerals (i.e., Mn3O4) led to meaningless consumption of PDS. Finally, the degradation of phenol by LDH activated PDS followed a non-radical (1O2) mechanism. Our ability to quantify how the chemical and structural variability of LDH influence the activation of PDS for organic degradation could mark an important step toward synthesis strategies for advanced catalysts.

Using a System Pharmacology Method to Search for the Potential Targets and Pathways of Yinqiaosan against COVID-19.

The first reported case of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei, China. Thereafter, it spread through China and worldwide in only a few months, reaching a pandemic level. It can cause severe respiratory illnesses such as pneumonia and lung failure. Since the onset of the disease, the rapid response and intervention of traditional Chinese medicine (TCM) have played a significant role in the effective control of the epidemic. Yinqiaosan (YQS) was used to treat COVID-19 pneumonia, with good curative effects. However, a systematic overview of its active compounds and the therapeutic mechanisms underlying its action has yet to be performed. The purpose of the current study is to explore the compounds and mechanism of YQS in treating COVID-19 pneumonia using system pharmacology. A system pharmacology method involving drug-likeness assessment, oral bioavailability forecasting, virtual docking, and network analysis was applied to estimate the active compounds, hub targets, and key pathways of YQS in the treatment of COVID-19 pneumonia. With this method, 117 active compounds were successfully identified in YQS, and 77 potential targets were obtained from the targets of 95 compounds and COVID-19 pneumonia. The results show that YQS may act in treating COVID-19 pneumonia and its complications (atherosclerosis and nephropathy) through Kaposi sarcoma-related herpesvirus infection and the AGE-RAGE signaling pathway in diabetic complications and pathways in cancer. We distinguished the hub molecular targets within pathways such as TNF, GAPDH, MAPK3, MAPK1, EGFR, CASP3, MAPK8, mTOR, IL-2, and MAPK14. Five of the more highly active compounds (acacetin, kaempferol, luteolin, naringenin, and quercetin) have anti-inflammatory and antioxidative properties. In summary, by introducing a systematic network pharmacology method, our research perfectly forecasts the active compounds, potential targets, and key pathways of YQS applied to COVID-19 and helps to comprehensively clarify its mechanism of action.

Nucleation Engineering in Sprayed MA3Bi2I9 Films for Direct-Conversion X-ray Detectors.

Metal halide perovskite and its derivatives show great promise in X-ray detection. However, large-scale fabrication of high-quality thick perovskite films is still full of challenges due to the complicated crystal nucleation process that always introduces lots of cracks or pinholes in the final perovskite film. Here, a MA3Bi2I9 film was fabricated by the cost-effective, scalable spraying process, and MACl was used as an additive to effectively tune the crystallization process. As a result, a dense MA3Bi2I9 film constituted by large grains was obtained, which has a high carrier mobility of ∼1 cm2 V-1 s-1 and a large activation energy (Ea) for ion migration of 0.91 eV. Thanks to the outstanding optoelectronic characteristics, X-ray detectors with a configuration of ITO/MA3Bi2I9/Au show a sensitivity of 35 µC Gyair-1 cm-2 and a limit of detection (LoD) of 0.14 µGyairs-1, which is outstanding compared with commercial α-Se detectors.

Driver mutations in ADGRL3 are involved in the evolution of ependymoma.

Although there have been recent advances in the molecular pathology of ependymomas, little is known about the underlying molecular evolution during its development. Here, we assessed the clinical, pathological and molecular evolutionary process of ependymoma recurrence in a 9-year-old patient who had seven recurrences of supratentorial ependymoma and died from intracranial multiregional recurrences at the age of 19 years old. Whole-genome sequencing (WGS) of 7 tumor samples (1 primary and 6 subsequent recurrent tumors) was performed to elucidate the mutation landscape and identify potential driver mutations for tumor evolution. The genetic profiles of the seven tumor specimens showed significant heterogeneity and suggested a highly branched evolutionary pattern. The mutational signatures and chromothripsis changed with treatments. Strikingly, adhesion G protein-coupled receptor L3 (ADGRL3, also known as Latrophilins 3, LPNH3) was found to be consistently mutated during the entire disease process. However, Sanger sequencing of other 78 ependymoma patients who underwent surgery at our institution showed no genetic alteration of ADGRL3, as found in the present case. The mRNA levels of ADGRL3 were significantly lower in ependymomas (n = 36), as compared with normal brain tissue (n = 3). Grade III ependymomas had the lowest ADGRL3 expression. Moreover, ependymomas with lower mRNA level of ADGRL3 had shorter overall survival. Our findings, therefore, demonstrate a rare evolutionary process of ependymoma involving ADGRL3.

Bridging Effects of Sulfur Anions at Titanium Oxide and Perovskite Interfaces on Interfacial Defect Passivation and Performance Enhancement of Perovskite Solar Cells.

Interfacial defects at the electron transport layer (ETL) and perovskite (PVK) interface are critical to the power conversion efficiency (PCE) and stabilities of the perovskite solar cells (PSCs) via significantly affecting the quality of both interface contacts and PVK layers. Here, we demonstrate a simple ionic bond passivation method, employing Na2S solution treatment of the surface of titanium dioxide (TiO2) layers, to effectively passivate the traps at the TiO2/Cs0.05(MA0.15FA0.85)0.95Pb(Br0.15I0.85)3 PVK interface and enhance the performance of PSCs. X-ray photoelectron spectroscopy and other characterizations show that the Na2S treatment introduced S2- ions at the TiO2/PVK interface, where S2- ions effectively bridged the TiO2 ETL and the PVK layer via forming chemical bonds with Ti atoms and with uncoordinated Pb atoms and resulted in the reduced defect density and improved the crystallinity of PVK layers. In addition, the S2- ions can effectively enlarge the grain size of the PVK layers. The average PCE of solar cells is improved from 15.77 to 19.06% via employing the Na2S-treated TiO2 layers. This work demonstrates a simple and facile interface passivation method using ionic bond passivation to afford high-performance PSCs. The bridging effect of S2- ions may inspire the further exploration of the ionic bond passivation and sulfur-based passivation materials.