CsZnPbBr3/ZnS core/shell perovskite nanocrystals for stable and efficient white light-emitting diodes.

The widespread applicability of perovskite nanocrystals (PeNCs) is impeded by their intrinsic instability. A promising solution is utilizing robust chalcogenides as a protective shell to shield the sensitive luminescent cores from the external environment. However, the inferior structural stability and surface lability of PeNCs usually lead to perovskite phase transition during shell growth. Herein, we introduced smaller Zn ions to partially replace Pb ions in perovskites, which reduces the Pb-X bond length and enhances the Pb-X bond energy for inner lattice stabilization. Simultaneously, extra oleylammonium bromide (OAmBr) was added to protect the labile surface of PeNCs by compensating for the detachment of ligands and the loss of surface Br ions. As a result, the dual strategies enable the epitaxial growth of a ZnS shell and significantly enhance the chemical stability of CsZnPbBr3/ZnS core/shell PeNCs. After three thermal cycles ranging from 300 to 450 K, the core/shell PeNCs retained 70% of their initial photoluminescence (PL) intensity. In stark contrast, the pristine CsPbBr3 PeNCs exhibit complete PL quenching after just the first temperature cycle. For practical applications, the green core/shell PeNCs were integrated with commercially available red-emitting phosphors on a blue-emitting InGaN chip to fabricate a white light-emitting diode (WLED), which demonstrates a high luminous efficacy (LE) of 61.3 lm W-1 and nearly constant Commission Internationale de l'Eclairage (CIE) coordinates under varying operating currents.

12.6 µm-Thick Asymmetric Composite Electrolyte with Superior Interfacial Stability for Solid-State Lithium-Metal Batteries.

Solid-state lithium metal batteries (SSLMBs) show great promise in terms of high-energy-density and high-safety performance. However, there is an urgent need to address the compatibility of electrolytes with high-voltage cathodes/Li anodes, and to minimize the electrolyte thickness to achieve high-energy-density of SSLMBs. Herein, we develop an ultrathin (12.6 µm) asymmetric composite solid-state electrolyte with ultralight areal density (1.69 mg cm-2) for SSLMBs. The electrolyte combining a garnet (LLZO) layer and a metal organic framework (MOF) layer, which are fabricated on both sides of the polyethylene (PE) separator separately by tape casting. The PE separator endows the electrolyte with flexibility and excellent mechanical properties. The LLZO layer on the cathode side ensures high chemical stability at high voltage. The MOF layer on the anode side achieves a stable electric field and uniform Li flux, thus promoting uniform Li+ deposition. Thanks to the well-designed structure, the Li symmetric battery exhibits an ultralong cycle life (5000 h), and high-voltage SSLMBs achieve stable cycle performance. The assembled pouch cells provided a gravimetric/volume energy density of 344.0 Wh kg-1/773.1 Wh L-1. This simple operation allows for large-scale preparation, and the design concept of ultrathin asymmetric structure also reveals the future development direction of SSLMBs.

5.1 µm Ion-Regulated Rigid Quasi-Solid Electrolyte Constructed by Bridging Fast Li-Ion Transfer Channels for Lithium Metal Batteries.

An ultra-thin quasi-solid electrolyte (QSE) with dendrite-inhibiting properties is a requirement for achieving high energy density quasi-solid lithium metal batteries (LMBs). Here, a 5.1 µm rigid QSE layer is directly designed on the cathode, in which Kevlar (poly(p-phenylene terephthalate)) nanofibers (KANFs) with negatively charged groups bridging metal-organic framework (MOF) particles are served as a rigid skeleton, and non-flammable deep eutectic solvent is selected to be encapsulated into the MOF channels, combined with in situ polymerization to complete safe electrolyte system with high rigidness and stability. The QSE with constructed topological network demonstrates high rigidity (5.4 GPa), high ionic conductivity (0.73 mS cm-1 at room temperature), good ion-regulated properties, and improved structural stability, contributing to homogenized Li-ion flux, excellent dendrite suppression, and prolonged cyclic performance for LMB. Additionally, ion regulation influences the Li deposition behavior, exhibiting a uniform morphology on the Li-metal surface after cycling. According to density-functional theory, KANFs bridging MOFs as hosts play a vital function in the free-state and fast diffusion dynamics of Li-ions. This work provides an effective strategy for constructing ultrathin robust electrolytes with a novel ionic conduction mode.

Machine learning-based prediction of the outcomes of cochlear implantation in patients with inner ear malformation.

OBJECTIVE: The objectives of this study are twofold: first, to visualize the structure of malformed cochleae through image reconstruction; and second, to develop a predictive model for postoperative outcomes of cochlear implantation (CI) in patients diagnosed with cochlear hypoplasia (CH) and incomplete partition (IP) malformation. METHODS: The clinical data from patients diagnosed with cochlear hypoplasia (CH) and incomplete partition (IP) malformation who underwent cochlear implantation (CI) at Beijing Tongren Hospital between January 2016 and August 2020 were collected. Radiological features were analyzed through 3D segmentation of the cochlea. Postoperative auditory speech rehabilitation outcomes were evaluated using the Categories of Auditory Performance (CAP) and the Speech Intelligibility Rating (SIR). This study aimed to investigate the relationship between cochlear parameters and postoperative outcomes. Additionally, a predictive model for postoperative outcomes was developed using the K-nearest neighbors (KNN) algorithm. RESULTS: In our study, we conducted feature selection by using patients' imaging and audiological attributes. This process involved methods such as the removal of missing values, correlation analysis, and chi-square tests. The findings indicated that two specific features, cochlear volume (V) and cochlear canal length (CDL), significantly contributed to predicting the outcomes of hearing and speech rehabilitation for patients with inner ear malformations. In terms of hearing rehabilitation, the KNN classification achieved an accuracy of 93.3%. Likewise, for speech rehabilitation, the KNN classification demonstrated an accuracy of 86.7%. CONCLUSION: The measurements obtained from the 3D reconstruction model hold significant clinical relevance. Despite the considerable variability in cochlear morphology across individuals, radiological features remain effective in predicting cochlear implantation (CI) prognosis for patients with inner ear malformations. The utilization of 3D segmentation techniques and the developed predictive model can assist surgeons in conducting preoperative cochlear structural measurements for patients with inner ear malformations. This, in turn, can offer a more informed perspective on the anticipated outcomes of cochlear implantation.

An Ultrahigh Modulus Gel Electrolytes Reforming the Growing Pattern of Li Dendrites for Interfacially Stable Lithium-Metal Batteries.

Gel polymer electrolytes (GPEs) have aroused intensive attention for their moderate comprehensive performances in lithium-metal batteries (LMBs). However, GPEs with low elastic moduli of MPa magnitude cannot mechanically regulate the Li deposition, leading to recalcitrant lithium dendrites. Herein, a porous Li7 La3 Zr2 O12 (LLZO) framework (PLF) is employed as an integrated solid filler to address the intrinsic drawback of GPEs. With the incorporation of PLF, the composite GPE exhibits an ultrahigh elastic modulus of GPa magnitude, confronting Li dendrites at a mechanical level and realizing steady polarization at high current densities in Li||Li cells. Benefiting from the compatible interface with anodes, the LFP|PLF@GPE|Li cells deliver excellent rate capability and cycling performance at room temperature. Theoretical models extracted from the topology of solid fillers reveal that the PLF with unique 3D structures can effectively reinforce the gel phase of GPEs at the nanoscale via providing sufficient mechanical support from the load-sensitive direction. Numerical models are further developed to reproduce the multiphysical procedure of dendrite propagation and give insights into predicting the failure modes of LMBs. This work quantitatively clarifies the relationship between the topology of solid fillers and the interface stability of GPEs, providing guidelines for designing mechanically reliable GPEs for LMBs.

Shearing Liquid-Crystalline MXene into Lamellar Membranes with Super-Aligned Nanochannels for Ion Sieving.

Ion-selective membranes are crucial in various chemical and physiological processes. Numerous studies have demonstrated progress in separating monovalent/multivalent ions, but efficient monovalent/monovalent ion sieving remains a great challenge due to their same valence and similar radii. Here, this work reports a two-dimensional (2D) MXene membrane with super-aligned slit-shaped nanochannels with ultrahigh monovalent ion selectivity. The MXene membrane is prepared by applying shear forces to a liquid-crystalline (LC) MXene dispersion, which is conducive to the highly-ordered stacking of the MXene nanosheets. The obtained LC MXene membrane (LCMM) exhibits ultrahigh selectivities toward Li+ /Na+ , Li+ /K+ , and Li+ /Rb+ separation (≈45, ≈49, and ≈59), combined with a fast Li+ transport with a permeation rate of ≈0.35 mol m-2 h-1 , outperforming the state-of-the-art membranes. Theoretical calculations indicate that in MXene nanochannels, the hydrated Li+ with a tetrahedral shape has the smallest diameter among the monovalent ions, contributing to the highest mobility. Besides, the weakest interaction is found between hydrated Li+ and MXene channels which also contributes to the ultrafast permeation of Li+ through the super-aligned MXene channels. This work demonstrates the capability of MXene membranes in monovalent ion separation, which also provides a facile and general strategy to fabricate lamellar membranes in a large scale.

A Readily Achieved Potentiostatic Method in Density Functional Theory Calculation for Improved Prediction of the Performance for Electrocatalytic Nitrogen Reduction Reaction.

Accurate prediction of the catalytic performance of nitrogen reduction reaction catalysts based on density functional theory (DFT) calculation is of great significance for developing catalytic materials for nitrogen fixation. However, the applied electrode potential induced the fixation of Fermi level and solvation effect are commonly ignored in the current computational hydrogen electrode method, which leads to the large deviation between the calculation predicted limit potential and the experimentally measured limit potential. In this work, the simple external iteration method is proposed to simulate the Fermi level of the catalysts that are fixed by the applied electrode potential, along with the hybrid solvent model to describe the strong interaction, such as hydrogen bond, between the solvent molecules and the intermediates. This method allowed the theoretical and experimental limit potentials to be in good agreement, indicating the significant effect of the electrode potential and solvation in the DFT calculation. These results will guide the calculation-based prediction of other reaction systems in the field of electrocatalysis.

Tuning the Stacking Modes of Ultrathin Two-Dimensional Metal-Organic Framework Nanosheet Membranes for Highly Efficient Hydrogen Separation.

Two-dimensional (2D) metal-organic framework (MOF) membranes are considered potential gas separation membranes of the next generation due to their structural diversity and geometrical functionality. However, achieving a rational structure design for a 2D MOF membrane and understanding the impact of MOF nanosheet stacking modes on membrane separation performance remain challenging tasks. Here, we report a novel kind of 2D MOF membrane based on [Cu2 Br(IN)2 ]n (IN=isonicotinato) nanosheets and propose that synergetic stacking modes of nanosheets have a significant influence on gas separation performance. The stacking of the 2D MOF nanosheets is controlled by solvent droplet dynamic behaviors at different temperatures of drop coating. Our 2D MOF nanosheet membranes exhibit high gas separation performances for H2 /CH4 (selectivity >290 with H2 permeance >520 GPU) and H2 /CO2 (selectivity >190 with H2 permeance >590 GPU) surpassing the Robeson upper bounds, paving a potential way for eco-friendly H2 separation.

Laser-induced nitrogen fixation.

For decarbonization of ammonia production in industry, alternative methods by exploiting renewable energy sources have recently been explored. Nonetheless, they still lack yield and efficiency to be industrially relevant. Here, we demonstrate an advanced approach of nitrogen fixation to synthesize ammonia at ambient conditions via laser-induced multiphoton dissociation of lithium oxide. Lithium oxide is dissociated under non-equilibrium multiphoton absorption and high temperatures under focused infrared light, and the generated zero-valent metal spontaneously fixes nitrogen and forms a lithium nitride, which upon subsequent hydrolysis generates ammonia. The highest ammonia yield rate of 30.9 micromoles per second per square centimeter is achieved at 25 °C and 1.0 bar nitrogen. This is two orders of magnitude higher than state-of-the-art ammonia synthesis at ambient conditions. The focused infrared light here is produced by a commercial simple CO2 laser, serving as a demonstration of potentially solar pumped lasers for nitrogen fixation and other high excitation chemistry. We anticipate such laser-involved technology will bring unprecedented opportunities to realize not only local ammonia production but also other new chemistries .

MXene-based Membranes for Drinking Water Production.

The soaring development of industry exacerbates the shortage of fresh water, making drinking water production an urgent demand. Membrane techniques feature the merits of high efficiency, low energy consumption, and easy operation, deemed as the most potential technology to purify water. Recently, a new type of two-dimensional materials, MXenes as the transition metal carbides or nitrides in the shape of nanosheets, have attracted enormous interest in water purification due to their extraordinary properties such as adjustable hydrophilicity, easy processibility, antifouling resistance, mechanical strength, and light-to-heat transformation capability. In pioneering studies, MXene-based membranes have been evaluated in the past decade for drinking water production including the separation of bacteria, dyes, salts, and heavy metals. This review focuses on the recent advancement of MXene-based membranes for drinking water production. A brief introduction of MXenes is given first, followed by descriptions of their unique properties. Then, the preparation methods of MXene membranes are summarized. The various applications of MXene membranes in water treatment and the corresponding separation mechanisms are discussed in detail. Finally, the challenges and prospects of MXene membranes are presented with the hope to provide insightful guidance on the future design and fabrication of high-performance MXene membranes.

Modified Diacetylmonoxime-Thiosemicarbazide Detection Protocol for Accurate Quantification of Urea.

Renewable photo-/electrocatalytic coreduction of CO2 and nitrate to urea is a promising method for high-value utilization of CO2 . However, because of the low yields of the urea synthesis by photo-/electrocatalysis process, the accurate quantification of low concentration urea is challenging. The traditional diacetylmonoxime-thiosemicarbazide (DAMO-TSC) method for urea detection has a high limit of quantification and accuracy, but it is easily affected by NO2 - in the solution, which limits its application scope. Thus, the DAMO-TSC method urgently requires a more rigorous design to eliminate the effects of NO2 - and accurately quantify urea in nitrate systems. Herein, a modified DAMO-TSC method is reported, which consumes NO2 - in solution through a nitrogen release reaction; hence, the remaining products do not affect the accuracy of urea detection. The results of detecting urea solutions with different NO2 - concentrations (within 30 ppm) show that the improved method can effectively control the error of urea detection within 3%.

Tuning the Phase Composition of Metal-Organic Framework Membranes for Helium Separation through Incorporation of Fullerenes.

Metal-organic framework (MOF) membranes have attracted significant research interest in gas separation, but efficient helium (He) separation remains a challenge due to the weak polarizability of He and the intrinsic pore size flexibility of MOFs. Herein, incorporated fullerenes (C60 and C70) were used to tune the crystallographic phase composition of ZIF-8 membranes, thus creating small and fixed apertures for selective He permeation. The fullerene-modified ZIF-8 (C60@ZIF-8 and C70@ZIF-8) membranes contain about 20% of the rigid-lattice ZIF-8_I-43m phase and have been prepared as 200-350 nm thick supported layers through electrochemical synthesis. They show a significantly enhanced molecular sieving for He/N2,CH4 together with a satisfactory He permeance of >200 GPU. Specifically, the He/N2 selectivity of the C70@ZIF-8 membrane is up to 30.4, which is much higher than that of the fullerene-free ZIF-8 membrane (5.1) and nearly an order of magnitude higher than those of other reported He-selective MOF membranes. A continuous long-term gas permeation test over 780 h under dry and humid conditions proved the excellent stability of the fullerene-modified ZIF-8 membranes. The general validity and versatility of the proposed strategy for MOF membrane preparation are also demonstrated by the enhancement of the separation performance of a fullerene-modified ZIF-76 membrane.

A Nitrogen Battery Electrode involving Eight-Electron Transfer per Nitrogen for Energy Storage.

Redox flow batteries have been discussed as scalable and simple stationary energy storage devices. However, currently developed systems encounter less competitive energy density and high costs, restricting their wider application. There is a lack of appropriate redox chemistry, preferably based on active materials that are abundant in nature and show high solubility in aqueous electrolytes. A nitrogen-centered redox cycle operating between the limiting species ammonia and nitrate via an eight-electron redox reaction stayed practically unnoticed, albeit its ubiquity in biological processes. Ammonia or nitrate are world-scale chemicals with high aqueous solubility, and are then comparably safe. We demonstrate here the successful implementation of such a nitrogen-based redox cycle between ammonia and nitrate with eight-electron transfer as a catholyte for Zn-based flow batteries, which continuously worked for 12.9 days with 930 charging-discharging cycles. A very competitive energy density of 577 Wh L-1 can be reached, which is well above most reported flow batteries (e.g. 8 times the standard Zn-bromide battery), demonstrating that the nitrogen cycle with eight-electron transfer can offer promising cathodic redox chemistry for safe, affordable, and scalable high-energy-density storage devices.

Semi-Sparsity for Smoothing Filters.

In this paper, we propose a semi-sparsity smoothing method based on a new sparsity-induced minimization scheme. The model is derived from the observations that semi-sparsity prior knowledge is universally applicable in situations where sparsity is not fully admitted such as in the polynomial-smoothing surfaces. We illustrate that such priors can be identified into a generalized L0-norm minimization problem in higher-order gradient domains, giving rise to a new "feature-aware" filter with a powerful simultaneous-fitting ability in both sparse singularities (corners and salient edges) and polynomial-smoothing surfaces. Notice that a direct solver to the proposed model is not available due to the non-convexity and combinatorial nature of L0-norm minimization. Instead, we propose to solve it approximately based on an efficient half-quadratic splitting technique. We demonstrate its versatility and many benefits to a series of signal/image processing and computer vision applications.

Fluorine-Stabilized Defective Black Phosphorene as a Lithium-Like Catalyst for Boosting Nitrogen Electroreduction to Ammonia.

Electrocatalytic N2 reduction reaction (NRR) is recognized as a zero-carbon emission method for NH3 synthesis. However, to date, this technology still suffers from low yield and low selectivity associated with the catalyst. Herein, inspired by the activation of N2 by lithium metal, a highly reactive defective black phosphorene (D-BPene ) is proposed as a lithium-like catalyst for boosting electrochemical N2 activation. Correspondingly, we also report a strategy for producing environmentally stable D-BPene by simultaneously constructing defects and fluorination protection based on topochemical reactions. Reliable performance evaluations show that the fluorine-stabilized D-BPene can induce a high NH3 yield rate of ≈70 µg h-1 mgcat. -1 and a high Faradaic efficiency of ≈26 % at -0.5 V vs. RHE in an aqueous electrolyte. This work not only exemplifies the first stable preparation and practical application of D-BPene , but also brings a new design idea for NRR catalysts.

Enabled Efficient Ammonia Synthesis and Energy Supply in a Zinc-Nitrate Battery System by Separating Nitrate Reduction Process into Two Stages.

The aqueous electrocatalytic reduction of NO3 - into NH3 (NitrRR) presents a sustainable route applicable to NH3 production and potentially energy storage. However, the NitrRR involves a directly eight-electron transfer process generally required a large overpotential (<-0.2 V versus reversible hydrogen electrode (vs. RHE)) to reach optimal efficiency. Here, inspired by biological nitrate respiration, the NitrRR was separated into two stages along a [2+6]-electron pathway to alleviate the kinetic barrier. The system employed a Cu nanowire catalyst produces NO2 - and NH3 with current efficiencies of 91.5 % and 100 %, respectively at lower overpotentials (>+0.1 vs. RHE). The high efficiency for such a reduction process was further explored in a zinc-nitrate battery. This battery could be specified by a high output voltage of 0.70 V, an average energy density of 566.7 Wh L-1 at 10 mA cm-2 and a power density of 14.1 mW cm-2 , which is well beyond all previously reported similar concepts.

Early prediction of sepsis using double fusion of deep features and handcrafted features.

Sepsis is a life-threatening medical condition that is characterized by the dysregulated immune system response to infections, having both high morbidity and mortality rates. Early prediction of sepsis is critical to the decrease of mortality. This paper presents a novel early warning model called Double Fusion Sepsis Predictor (DFSP) for sepsis onset. DFSP is a double fusion framework that combines the benefits of early and late fusion strategies. First, a hybrid deep learning model that combines both the convolutional and recurrent neural networks to extract deep features is proposed. Second, deep features and handcrafted features, such as clinical scores, are concatenated to build the joint feature representation (early fusion). Third, several tree-based models based on joint feature representation are developed to generate the risk scores of sepsis onset that are combined with an End-to-End neural network for final sepsis detection (late fusion). To evaluate DFSP, a retrospective study was conducted, which included patients admitted to the ICUs of a hospital in Shanghai China. The results demonstrate that the DFSP outperforms state-of-the-art approaches in early sepsis prediction.

Intrinsic Image Transfer for Illumination Manipulation.

This article presents a novel intrinsic image transfer (IIT) algorithm for image illumination manipulation, which creates a local image translation between two illumination surfaces. This model is built on an optimization-based framework composed of illumination, reflectance and content photo-realistic losses, respectively. Each loss is first defined on the corresponding sub-layers factorized by an intrinsic image decomposition and then reduced under the well-known spatial-varying illumination illumination-invariant reflectance prior knowledge. We illustrate that all losses, with the aid of an "exemplar" image, can be directly defined on images without the necessity of taking an intrinsic image decomposition, thereby giving a closed-form solution to image illumination manipulation. We also demonstrate its versatility and benefits to several illumination-related tasks: illumination compensation, image enhancement and tone mapping, and high dynamic range (HDR) image compression, and show their high-quality results on natural image datasets.

Depletion of microRNA-92a Enhances the Role of Sevoflurane Treatment in Reducing Myocardial Ischemia-Reperfusion Injury by Upregulating KLF4.

OBJECTIVE: As some articles have highlighted the role of microRNA-92a (miR-92a) in myocardial ischemia-reperfusion injury (MI/RI), this article aimed to investigate the effect of miR-92a on Sevoflurane (Sevo)-treated MI/RI via regulation of Krüppel-like factor 4 (KLF4). METHODS: An MI/RI rat model was established by ligating the left anterior descending coronary artery. The cardiac function, pathological changes of myocardial tissues, inflammatory response, oxidative stress and cardiomyocyte apoptosis in MI/RI rats were determined. KLF4 and miR-92a expression was detected in the myocardial tissue of rats, and the target relationship between miR-92a and KLF4 was confirmed. RESULTS: Sevo treatment alleviated myocardial damage, inflammatory response, oxidative stress response, and cardiomyocyte apoptosis, and improved cardiac function in MI/RI rats. miR-92a increased and KLF4 decreased in the myocardial tissue of MI/RI rats. KLF4 was targeted by miR-92a. Downregulation of miR-92a or upregulation of KLF4 further enhanced the effect of Sevo treatment on MI/RI. CONCLUSION: This study suggests that depletion of miR-92a promotes upregulation of KLF4 to improve cardiac function, reduce cardiomyocyte apoptosis and further enhance the role of Sevo treatment in alleviating MI/RI.