Prevalence of RUNX1 gene alterations in de novo adult acute myeloid leukemia

BACKGROUND Acute myeloid leukemia(AML)is a complicated disease with uncontrolled hematopoietic precursor proliferation induced by various genetic alterations.Runt-related transcription factor-1(RUNX1)is commonly disrupted by chromosomal translocations in hematological malignancies.AIM To characterize RUNX1 gene rearrangements and copy number variations in newly diagnosed adult AML patients,with an emphasis on the impact of clinical and laboratory features on the outcome.METHODS Fluorescence in situ hybridization was used to test RUNX1 gene alterations in 77 newly diagnosed adult AML cases.NPM1,FLT3/ITD,FLT3/TKD,and KIT mutations were tested by PCR.Prognostic clinical and laboratory findings were studied in relation to RUNX1 alterations.RESULTS RUNX1 abnormalities were detected by fluorescence in situ hybridization in 41.6%of patients:20.8%had translocations,22.1%had amplification,and 5.2%had deletion.Translocations prevailed in AML-M2(P=0.019)with a positive expression of myeloperoxidase(P=0.031),whereas deletions dominated in M4 and M5 subtypes(P=0.008)with a positive association with CD64 expression(P=0.05).The modal chromosomal number was higher in cases having amplifications(P=0.007)and lower in those with deletions(P=0.008).RUNX1 abnormalities were associated with complex karyotypes(P<0.001)and were mutually exclusive of NPM1 mutations.After 44 months of follow-up,RUNX1 abnormalities affected neither patients’response to treatment nor overall survival.CONCLUSION RUNX1 abnormalities were mutually exclusive of NPM1 mutations.RUNX1 abnormalities affected neither patients’response to treatment nor overall survival.

Autonomous sortie scheduling for carrier aircraft fleet under towing mode

Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.

Sub-6GHz Assisted mmWave Hybrid Beamforming with Self-Supervised Learning

In this paper,we propose a sub-6GHz channel assisted hybrid beamforming(HBF)for mmWave system under both line-of-sight(LOS)and non-line-of-sight(NLOS)scenarios without mmWave channel estimation.Meanwhile,we resort to the selfsupervised approach to eliminate the need for labels,thus avoiding the accompanied high cost of data collection and annotation.We first construct the dense connection network(DCnet)with three modules:the feature extraction module for extracting channel characteristic from a large amount of channel data,the feature fusion module for combining multidimensional features,and the prediction module for generating the HBF matrices.Next,we establish a lightweight network architecture,named as LDnet,to reduce the number of model parameters and computational complexity.The proposed sub-6GHz assisted approach eliminates mmWave pilot resources compared to the method using mmWave channel information directly.The simulation results indicate that the proposed DCnet and LDnet can achieve the spectral efficiency that is superior to the traditional orthogonal matching pursuit(OMP)algorithm by 13.66% and 10.44% under LOS scenarios and by 32.35% and 27.75% under NLOS scenarios,respectively.Moreover,the LDnet achieves 98.52% reduction in the number of model parameters and 22.93% reduction in computational complexity compared to DCnet.

高精度两步分支混合CORDIC算法设计及FPGA实现

CORDIC(坐标旋转数字计算机)算法是一种用于计算三角函数和其他数学运算的算法,被广泛应用于数字信号处理、计算机图形学等领域。CORDIC算法仅需要加减和移位运算,特别适合布署在硬件平台。传统CORDIC算法的局限在于迭代次数过多,虽然不少研究对此进行了优化,但也增加了硬件开销且易造成精度丢失。为此,基于Hybrid CORDIC算法和Double step branching CORDIC算法,给出了一种CORDIC优化算法——高精度两步分支混合CORDIC(HD CORDIC)算法。该算法在迭代次数上减少到N/4+“1”(N为微旋转角度个数及位宽),并给出了新的混合角度集的划分公式,以达到ε<2-(N-2)的高精度,与基本CORDIC算法(ε<2-(N-1))相近,且不用计算缩放因子K。HD CORDIC算法采用流水线结构,流水线级数仅为N/4+3(不含缩放因子补偿操作的基本CORDIC算法为N+2)。采用Verilog对所提算法进行了硬件实现,并在XILINX Zynq-7000 xc7z100ffv900-2 FPGA平台上进行了综合,实验评估显示,当输入角度位宽为16时,工作频率为315.66 MHz,完成1次正余弦函数运算仅需6个时钟周期。相比于XILINX CORDIC IP,HD CORDIC算法处理时间减少了59.13%,LUT开销减少了55.74%,Register开销减少了80.24%,功耗降低了35.99%。

颈椎前路Hybrid手术和颈椎后路单开门椎管扩大成形术治疗多节段脊髓型颈椎病临床疗效分析

目的:分析颈椎前路Hybrid手术和颈椎后路单开门椎管扩大成形术(EODL)治疗多节段脊髓型颈椎病的疗效,探讨多节段脊髓型颈椎病患者手术方式的选择。方法:对2017年7月—2020年7月在首都医科大学附属北京中医医院手术治疗的70例多节段脊髓型颈椎病患者进行回顾性分析,根据手术方式不同,分为前路组35例和后路组35例,前路组患者行Hybrid手术[颈椎前路椎间盘切除融合术(ACDF)联合人工颈椎间盘置换术(ACDR)],后路组患者行EODL。记录2组患者住院时间、手术时间、术中出血量和术后引流量,通过日本骨科协会(JOA)评分、JOA改善率、颈椎残障功能指数(NDI)、疼痛视觉模拟评分(VAS)和术后满意度评分进行疗效评价,统计2组患者术后并发症发生情况。结果:与后路组比较,前路组患者术中出血量、术后引流量、住院时间和手术时间均明显减少(P<0.01),术前各项评分差异无统计学意义(P>0.05)。末次随访时,与后路组比较,前路组患者JOA评分和JOA改善率明显升高(P<0.01),NDI评分和VAS评分明显降低(P<0.01)。与术前比较,末次随访时2组患者JOA评分明显升高(P<0.01),NDI和VAS评分均明显降低(P<0.01)。按术后满意度评分评价,2组患者术后满意度均较高。2组患者术后并发症发生率比较差异无统计学意义(P>0.05)。结论:颈椎前路Hybrid手术和EODL在治疗多节段脊髓型颈椎病方面均取得了较为满意的疗效。Hybrid手术具有出血量少和手术时间短等优点,临床上应根据患者实际情况选择最适宜的术式。

溅射技术与基体偏压对TiB_(x)涂层结构和力学性能的影响

目的改善TiB_(x)涂层的残余应力,提高其力学性能。方法采用不同的磁控溅射技术(dcMS、HiPMS、Hybrid)和基体偏压制备TiB_(x)涂层。通过电子探针显微分析仪(EPMA)测试TiB_(x)涂层的化学成分,采用扫描电子显微镜(SEM)和X射线衍射仪(XRD)表征涂层的表面形貌、组织结构特征、相组成和择优取向,通过sin^(2)ψ法、纳米压痕仪和洛氏压痕法分别测试TiB_(x)涂层的残余应力、纳米硬度和膜层/基体结合强度。结果溅射技术和基体偏压对TiB_(x)涂层的组织结构和力学性能都有着显著的影响。在基体旋转条件下,不同溅射技术和基体偏压制备的涂层均呈现出TiB_(2)-(001)择优取向。随基体偏压的升高,涂层的残余应力呈现出先增大、后减小的规律。偏压相同时,HiPIMS技术制备的TiB_(x)涂层具有最高的残余应力。随着基体偏压的增加,TiB_(x)涂层的纳米硬度和弹性模量不断增加,在偏压为–130 V时,Hybrid-TiB_(x)涂层具有最高的纳米硬度(40.1GPa)。偏压相同时,dcMS-TiB_(x)和Hybrid-TiB_(x)涂层表现出优异的膜层/基体结合强度(HF1-HF2级),而HiPIMS涂层表现出较差的膜层/基体结合强度(HF1-HF4级)。结论溅射技术和基体偏压对TiB_(x)涂层的微观组织结构和力学性能有着重要的影响,Hybrid模式结合了dcMS模式和HiPMS模式的优点,Hybrid-TiB_(x)涂层呈现出最优的综合力学性能(高的纳米硬度、沉积速率和膜层/基体结合强度)。

Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

In Situ Atomic Reconstruction Engineering Modulating Graphene-Like MXene-Based Multifunctional Electromagnetic Devices Covering Multi-Spectrum

With the diversified development of big data,detection and precision guidance technologies,electromagnetic(EM)functional materials and devices serving multiple spectrums have become a hot topic.Exploring the multispectral response of materials is a challenging and meaningful scientific question.In this study,MXene/TiO_(2)hybrids with tunable conduction loss and polarization relaxation are fabricated by in situ atomic reconstruction engineering.More importantly,MXene/TiO_(2)hybrids exhibit adjustable spectral responses in the GHz,infrared and visible spectrums,and several EM devices are constructed based on this.An antenna array provides excellent EM energy harvesting in multiple microwave bands,with|S11|up to−63.2 dB,and can be tuned by the degree of bending.An ultra-wideband bandpass filter realizes a passband of about 5.4 GHz and effectively suppresses the transmission of EM signals in the stopband.An infrared stealth device has an emissivity of less than 0.2 in the infrared spectrum at wavelengths of 6-14μm.This work can provide new inspiration for the design and development of multifunctional,multi-spectrum EM devices.

Accelerating Oxygen Electrocatalysis Kinetics on Metal-Organic Frameworks via Bond Length Optimization

Metal-organic frameworks(MOFs)have been developed as an ideal platform for exploration of the relationship between intrinsic structure and catalytic activity,but the limited catalytic activity and stability has hampered their practical use in water splitting.Herein,we develop a bond length adjustment strategy for optimizing naphthalene-based MOFs that synthesized by acid etching Co-naphthalenedicarboxylic acid-based MOFs(donated as AE-CoNDA)to serve as efficient catalyst for water splitting.AE-CoNDA exhibits a low overpotential of 260 mV to reach 10 mA cm^(−2)and a small Tafel slope of 62 mV dec^(−1)with excellent stability over 100 h.After integrated AE-CoNDA onto BiVO_(4),photocurrent density of 4.3 mA cm^(−2)is achieved at 1.23 V.Experimental investigations demonstrate that the stretched Co-O bond length was found to optimize the orbitals hybridization of Co 3d and O 2p,which accounts for the fast kinetics and high activity.Theoretical calculations reveal that the stretched Co-O bond length strengthens the adsorption of oxygen-contained intermediates at the Co active sites for highly efficient water splitting.

Regulatable Orthotropic 3D Hybrid Continuous Carbon Networks for Efficient Bi-Directional Thermal Conduction

Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer efficiency of vertically oriented carbon structures is a challenging task.Herein,an orthotropic three-dimensional(3D)hybrid carbon network(VSCG)is fabricated by depositing vertically aligned carbon nanotubes(VACNTs)on the surface of a horizontally oriented graphene film(HOGF).The interfacial interaction between the VACNTs and HOGF is then optimized through an annealing strategy.After regulating the orientation structure of the VACNTs and filling the VSCG with polydimethylsi-loxane(PDMS),VSCG/PDMS composites with excellent 3D thermal conductive properties are obtained.The highest in-plane and through-plane thermal conduc-tivities of the composites are 113.61 and 24.37 W m^(-1)K^(-1),respectively.The high contact area of HOGF and good compressibility of VACNTs imbue the VSCG/PDMS composite with low thermal resistance.In addition,the interfacial heat-transfer efficiency of VSCG/PDMS composite in the TIM performance was improved by 71.3%compared to that of a state-of-the-art thermal pad.This new structural design can potentially realize high-performance TIMs that meet the need for high thermal conductivity and low contact thermal resistance in interfacial heat-transfer processes.

MicroRNA-502-3p regulates GABAergic synapse function in hippocampal neurons

Gamma-aminobutyric acid(GABA)ergic neurons,the most abundant inhibitory neurons in the human brain,have been found to be reduced in many neurological disorders,including Alzheimer's disease and Alzheimer's disease-related dementia.Our previous study identified the upregulation of microRNA-502-3p(miR-502-3p)and downregulation of GABA type A receptor subunitα-1 in Alzheimer's disease synapses.This study investigated a new molecular relationship between miR-502-3p and GABAergic synapse function.In vitro studies were perfo rmed using the mouse hippocampal neuronal cell line HT22 and miR-502-3p agomiRs and antagomiRs.In silico analysis identified multiple binding sites of miR-502-3p at GABA type A receptor subunitα-1 mRNA.Luciferase assay confirmed that miR-502-3p targets the GABA type A receptor subunitα-1 gene and suppresses the luciferase activity.Furthermore,quantitative reve rse transcription-polymerase chain reaction,miRNA in situ hybridization,immunoblotting,and immunostaining analysis confirmed that overexpression of miR-502-3p reduced the GABA type A receptor subunitα-1 level,while suppression of miR-502-3p increased the level of GABA type A receptor subunitα-1 protein.Notably,as a result of the overexpression of miR-502-3p,cell viability was found to be reduced,and the population of necrotic cells was found to be increased.The whole cell patch-clamp analysis of human-GABA receptor A-α1/β3/γ2L human embryonic kidney(HEK)recombinant cell line also showed that overexpression of miR-502-3p reduced the GABA current and overall GABA function,suggesting a negative correlation between miR-502-3p levels and GABAergic synapse function.Additionally,the levels of proteins associated with Alzheimer s disease were high with miR-502-3p overexpression and reduced with miR-502-3p suppression.The present study provides insight into the molecular mechanism of regulation of GABAergic synapses by miR-502-3p.We propose that micro-RNA,in particular miR-502-3p,could be a potential therapeutic to rget to modulate GABAergic synapse function in neurological disorders,including Alzheimer's disease and Alzheimer's diseaserelated dementia.

Hybrid手术对Stanford B型主动脉夹层疗效的研究进展

主动脉夹层主要通过使用假体移植物的开胸手术修复来治疗。在过去的10年里,胸主动脉腔内修复术(TEVAR)已成为一种创伤更小、潜在更安全的治疗方法。然而,单一的微创腔内修复术在缺乏足够的锚定区的Stanford B型主动脉夹层(TBAD)患者上有其局限性。因此,结合了外科手术及胸主动脉腔内修复术的Hy‐brid手术(或称为杂交手术),通过外科手段重建左颈总动脉和左锁骨下动脉的弓上分流术,再结合微创腔内修复术,显著减少患者在外科手术中并发症的发生率,且提高了那些常规胸主动脉腔内修复术缺乏理想锚定区患者的生存率。

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

Ag-integrated mixed metallic Co-Fe-Ni-Mn hydroxide composite as advanced electrode for high-performance hybrid supercapacitors

Direct growth of redox-active noble metals and rational design of multifunctional electrochemical active materials play crucial roles in developing novel electrode materials for energy storage devices.In this regard,silver(Ag)has attracted great attention in the design of efficient electrodes.Inspired by the house/building process,which means electing the right land,it lays a strong foundation and building essential columns for a complex structure.Herein,we report the construction of multifaceted heterostructure cobalt-iron hydroxide(CFOH)nanowires(NWs)@nickel cobalt manganese hydroxides and/or hydrate(NCMOH)nanosheets(NSs)on the Ag-deposited nickel foam and carbon cloth(i.e.,Ag/NF and Ag/CC)substrates.Moreover,the formation and charge storage mechanism of Ag are described,and these contribute to good conductive and redox chemistry features.The switching architectural integrity of metal and redox materials on metallic frames may significantly boost charge storage and rate performance with noticeable drop in resistance.The as-fabricated Ag@CFOH@NCMOH/NF electrode delivered superior areal capacity value of 2081.9μA h cm^(-2)at 5 mA cm^(-2).Moreover,as-assembled hybrid cell based on NF(HC/NF)device exhibited remarkable areal capacity value of 1.82 mA h cm^(-2)at 5 mA cm^(-2)with excellent rate capability of 74.77%even at 70 mA cm^(-2)Furthermore,HC/NF device achieved maximum energy and power densities of 1.39 mW h cm^(-2)and 42.35 mW cm^(-2),respectively.To verify practical applicability,both devices were also tested to serve as a self-charging station for various portable electronic devices.

Activation Redistribution Based Hybrid Asymmetric Quantization Method of Neural Networks

The demand for adopting neural networks in resource-constrained embedded devices is continuously increasing.Quantization is one of the most promising solutions to reduce computational cost and memory storage on embedded devices.In order to reduce the complexity and overhead of deploying neural networks on Integeronly hardware,most current quantization methods use a symmetric quantization mapping strategy to quantize a floating-point neural network into an integer network.However,although symmetric quantization has the advantage of easier implementation,it is sub-optimal for cases where the range could be skewed and not symmetric.This often comes at the cost of lower accuracy.This paper proposed an activation redistribution-based hybrid asymmetric quantizationmethod for neural networks.The proposedmethod takes data distribution into consideration and can resolve the contradiction between the quantization accuracy and the ease of implementation,balance the trade-off between clipping range and quantization resolution,and thus improve the accuracy of the quantized neural network.The experimental results indicate that the accuracy of the proposed method is 2.02%and 5.52%higher than the traditional symmetric quantization method for classification and detection tasks,respectively.The proposed method paves the way for computationally intensive neural network models to be deployed on devices with limited computing resources.Codes will be available on https://github.com/ycjcy/Hybrid-Asymmetric-Quantization.

Enhancing rock fragmentation prediction in mining operations:A hybrid GWO-RF model with SHAP interpretability

In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hybrid predictive model named GWO-RF.This model combines the grey wolf optimization(GWO)algorithm with the random forest(RF)technique to predict the D_(80)value,a critical parameter in evaluating rock fragmentation quality.The study is conducted using a dataset from Sarcheshmeh Copper Mine,employing six different swarm sizes for the GWO-RF hybrid model construction.The GWO-RF model’s hyperparameters are systematically optimized within established bounds,and its performance is rigorously evaluated using multiple evaluation metrics.The results show that the GWO-RF hybrid model has higher predictive skills,exceeding traditional models in terms of accuracy.Furthermore,the interpretability of the GWO-RF model is enhanced through the utilization of SHapley Additive exPlanations(SHAP)values.The insights gained from this research contribute to optimizing blasting operations and rock fragmentation outcomes in the mining industry.

Ground threat prediction-based path planning of unmanned autonomous helicopter using hybrid enhanced artificial bee colony algorithm

Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.

Dual-ion carrier storage through Mg^(2+) addition for high-energy and long-life zinc-ion hybrid capacitor

Cation additives can efficiently enhance the total electrochemical capabilities of zinc-ion hybrid capacitors (ZHCs).However their energy storage mechanisms in zinc-based systems are still under debate.Herein,we modulate the electrolyte and achieve dual-ion storage by adding magnesium ions.And we assemble several Zn//activated carbon devices with different electrolyte concentrations and investigate their electrochemical reaction dynamic behaviors.The zinc-ion capacitor with Mg^(2+)mixed solution delivers 82 mAh·g^(-1)capacity at 1 A·g^(-1) and maintains 91%of the original capacitance after 10000 cycling.It is superior to the other assembled zinc-ion devices in single-component electrolytes.The finding demonstrates that the double-ion storage mechanism enables the superior rate performance and long cycle lifetime of ZHCs.

Manipulating d-d orbital hybridization induced by Mo-doped Co_(9)S_(8) nanorod arrays for high-efficiency water electrolysis

Precisely refining the electronic structure of electrocatalysts represents a powerful approach to further optimize the electrocatalytic performance.Herein,we demonstrate an ingenious d-d orbital hybridization concept to construct Mo-doped Co_(9)S_(8) nanorod arrays aligned on carbon cloth(CC)substrate(abbreviated as Mo-Co_(9)S_(8)@CC hereafter)as a high-efficiency bifunctional electrocatalyst toward water electrolysis.It has experimentally and theoretically validated that the 4d-3d orbital coupling between Mo dopant and Co site can effectively optimize the H_(2)O activation energy and lower H^(*)adsorption energy barrier,thereby leading to enhanced hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)activities.Thanks to the unique electronic and geometrical advantages,the optimized Mo-Co_(9)S_(8)@CC with appropriate Mo content exhibits outstanding bifunctional performance in alkaline solution,with the overpotentials of 75 and 234 mV for the delivery of a current density of 10 mA cm^(-2),small Tafel slopes of 53.8 and 39.9 mV dec~(-1)and long-term stabilities for at least 32 and 30 h for HER and OER,respectively.More impressively,a water splitting electrolylzer assembled by the self-supported Mo-Co_(9)S_(8)@CC electrode requires a low cell voltage of 1.53 V at 10 mA cm^(-2)and shows excellent stability and splendid reversibility,demonstrating a huge potential for affordable and scalable electrochemical H_(2) production.The innovational orbital hybridization strategy for electronic regulation herein provides an inspirable avenue for developing progressive electrocatalysts toward new energy systems.

Electrostatic Interaction-directed Construction of Hierarchical Nanostructured Carbon Composite with Dual Electrical Conductive Networks for Zinc-ion Hybrid Capacitors with Ultrastability

Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.