In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses...In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses,some properties and some equivalent characterizations of G_(C)-X-injective modules are investigated,and we also show that the triple(■,cores■,■)is a weak co-AB-context.As an application,two complete cotorsion pairs and a new model structure in Mod S are given.展开更多
High-voltage electric pulse(HVEP)rock fragmentation has demonstrated substantial potential for sustainable fracturing of hard rocks owing to its energy efficiency.The transient nature and highly disruptive characteris...High-voltage electric pulse(HVEP)rock fragmentation has demonstrated substantial potential for sustainable fracturing of hard rocks owing to its energy efficiency.The transient nature and highly disruptive characteristics of its physical fracturing process render experimental investigation of the underlying rock-breaking mechanisms challenging.However,existing numerical studies lack comprehensive models that precisely link electrical breakdown phenomena with mechanical disintegration processes.This study combines COMSOL electrical breakdown simulations with four-dimension lattice spring model(4D-LSM)mechanical analysis to establish a coupled HVEP rock fragmentation model.The core concept of the model construction is to import the temperature field of the plasma channel obtained from the electrical breakdown into the mechanical solver to realize the precise connection between the two stages.The validated numerical model elucidates the full process of HVEP-induced fragmentation under varying electrical parameters.Furthermore,the effects of confining pressure and mineral grain size on fragmentation behavior have been investigated.Finally,parametric simulations across 25 electrical parameter combinations demonstrate the critical role of electrode spacing optimization in achieving energy-efficient rock fragmentation.These findings provide a predictive tool for designing efficient HVEP systems in deep resource extraction and mineral processing engineering.展开更多
Manganese-based Prussian blue analogues(MnFePBAs),renowned for their high redox potential and dual redox-active sites,often fail to fully realize their intrinsic performance in zinc-ion batteries(ZIBs).In this work,th...Manganese-based Prussian blue analogues(MnFePBAs),renowned for their high redox potential and dual redox-active sites,often fail to fully realize their intrinsic performance in zinc-ion batteries(ZIBs).In this work,the underlying causes of the instability of monoclinic K^(+) -containing MnFePBA(KMnFePBA)cathodes in aqueous electrolytes were investigated.To prevent irreversible phase transitions,a lowconcentration,flame-retardant organic electrolyte operable under open-air conditions was developed.Utilizing triethyl phosphate(TEP)as the electrolyte solvent,the KMnFePBA cathode exhibited two distinct redox peaks at approximately 1.83 and 1.70 V,coupled with a high reversible capacity of -130 m A h g^(-1).The TEP electrolyte offers not only flame-retardant and anti-drying properties but also benefits from the inclusion of trace amounts of water,which enhances the redox kinetics.The optimized electrolyte enables Zn||KMnFePBA batteries to operate reversibly without structural degradation,function effectively across a wide temperature range,and suppress Zn dendrite formation by modulating the zinc-ion solvation structure and interfacial environment.This study presents a practical electrolyte engineering strategy for stabilizing monoclinic MnFePBA cathodes while simultaneously extending the lifespan of Zn anodes in ZIBs.展开更多
Mango is a plant with high economic value in the agricultural industry;thus,it is necessary to maximize the productivity performance of the mango plant,which can be done by implementing artificial intelligence.In this...Mango is a plant with high economic value in the agricultural industry;thus,it is necessary to maximize the productivity performance of the mango plant,which can be done by implementing artificial intelligence.In this study,a lightweight object detection model will be developed that can detect mango plant conditions based on disease potential,so that it becomes an early detection warning system that has an impact on increasing agricultural productivity.The proposed lightweight model integrates YOLOv7-Tiny and the proposed modules,namely the C2S module.The C2S module consists of three sub-modules such as the convolutional block attention module(CBAM),the coordinate attention(CA)module,and the squeeze-and-excitation(SE)module.The dataset is constructed by eight classes,including seven classes of disease conditions and one class of health conditions.The experimental result shows that the proposed lightweight model has the optimal results,which increase by 13.15% of mAP50 compared to the original model YOLOv7-Tiny.While the mAP50:95 also achieved the highest results compared to other models,including YOLOv3-Tiny,YOLOv4-Tiny,YOLOv5,and YOLOv7-Tiny.The advantage of the proposed lightweightmodel is the adaptability that supports it in constrained environments,such as edge computing systems.This proposedmodel can support a robust,precise,and convenient precision agriculture system for the user.展开更多
Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefo...Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefore,a hybrid model(WM-ResNet50)integrating data enhancement,a deep convolutional neural network(CNN),and convolutional block attention modules(CBAM)was proposed.Firstly,an MS system was established at the Xieqiao coal mine in Anhui Province,China.MS waveforms and injection parameters were acquired during grouting.Secondly,signals were categorized based on time-frequency characteristics to build a dataset,which was divided into training,validation,and test sets at a ratio of 4:1:1.Subsequently,the performance of WM-ResNet50 was evaluated based on indices such as individual precision,total accuracy,recall,and loss function.The results indicated that WMResNet50 achieved an average recognition accuracy of 94.38%,surpassing that of a simple CNN(90.04%),ResNet18(91.72%),and ResNet50(92.48%).Finally,WM-ResNet50 was applied to monitor the whole process at laboratory tests and field cases.Both results affirmed the feasibility and effectiveness of MS inversion in predicting actual slurry diffusion ranges within deep rock layers.By comparison,it was revealed that the MS sources classified by WM-ResNet50 matched grouting records well.A solution to address insufficient diffusion under long-borehole grouting has been proposed.WM-ResNet50′s accuracy was validated through in-situ coring and XRD analysis for cement-based hydration products.This study provides a beneficial reference for similar rock signal processing and in-field grouting practices.展开更多
In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this pape...In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.展开更多
WiFi-based human activity recognition(HAR)provides a non-intrusive approach for ubiquitous monitoring;however,achieving both high accuracy and robustness simultaneously remains a significant challenge.This paper propo...WiFi-based human activity recognition(HAR)provides a non-intrusive approach for ubiquitous monitoring;however,achieving both high accuracy and robustness simultaneously remains a significant challenge.This paper proposes a Convolutional Neural Network with Enhanced Convolutional Block Attention Module(CNN-ECBAM)framework.The approach systematically converts raw Channel State Information(CSI)into pseudo-color images,effectively preserving essential signal characteristics for deep neural network processing.The core innovation is an Enhanced Convolutional Block Attention Module(ECBAM),tailored to CSI data characteristics,which integrates Efficient Channel Attention(ECA)and Multi-Scale Spatial Attention(MSSA).By employing learnable adaptive fusion weights,it achieves dynamic synergy between channel and spatial features,enabling the network to capture highly discriminative spatiotemporal patterns.The ECBAM module is integrated into a unified Convolutional Neural Network(CNN)to form the overall CNN-ECBAM model.Experimental results on the UT-HAR and NTU-Fi_HAR datasets demonstrate that CNN-ECBAM achieves competitive performance in recognition accuracy and outperforms mainstream baseline models.Specifically,it attains 99.20%accuracy on UT-HAR(surpassing ResNet-18 at 98.60%)and achieves 100%accuracy on NTU-Fi_HAR(exceeding GAF-CNN at 99.62%).These results validate the effectiveness of the proposed method for high-precision and reliable WiFi-based HAR.展开更多
Lithium-ion batteries are essential for modern energy storage,yet achieving simultaneous high-temperature and high-voltage operation remains challenging due to interfacial compatibility.In this study,we introduce a po...Lithium-ion batteries are essential for modern energy storage,yet achieving simultaneous high-temperature and high-voltage operation remains challenging due to interfacial compatibility.In this study,we introduce a polyetherimide(PEI)-polyimide(PI)functional coating on the separator that enhances wettability,thermal stability,and mechanical strength,while markedly improving cathode stability under harsh conditions.By integrating theoretical calculations with experimental validation,we demonstrate that the PEI/PI coating modulates the solvation structure of lithium-ions,thereby facilitating the interfacial desolvation process.More importantly,the PEI/PI layer regulates electrolyte decomposition at the interface,promoting the formation of a uniform and thermally stable cathode-electrolyte interphase.Consequently,LiCoO_(2)cathodes exhibit improved cycling performance at 60°C.Overall,this work underscores the pivotal role of separator coatings in governing interfacial chemistry and provides a viable strategy for designing high-performance lithium-ion batteries capable of enduring both high temperatures and high.展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
As battery technology evolves and demand for efficient energy storage solutions,aqueous zinc ion batteries(AZIBs)have garnered significant attention due to their safety and environmental benefits.However,the stability...As battery technology evolves and demand for efficient energy storage solutions,aqueous zinc ion batteries(AZIBs)have garnered significant attention due to their safety and environmental benefits.However,the stability of cathode materials under high-voltage conditions remains a critical challenge in improving its energy density.This review systematically explores the failure mechanisms of high-voltage cathode materials in AZIBs,including hydrogen evolution reaction,phase transformation and dissolution phenomena.To address these challenges,we propose a range of advanced strategies aimed at improving the stability of cathode materials.These strategies include surface coating and doping techniques designed to fortify the surface properties and structure integrity of the cathode materials under high-voltage conditions.Additionally,we emphasize the importance of designing antioxidant electrolytes,with a focus on understanding and optimizing electrolyte decomposition mechanisms.The review also highlights the significance of modifying conductive agents and employing innovative separators to further enhance the stability of AZIBs.By integrating these cutting-edge approaches,this review anticipates substantial advancements in the stability of high-voltage cathode materials,paving the way for the broader application and development of AZIBs in energy storage.展开更多
The absence of efficient ion transport pathways in composite solid-state electrolytes(CSEs)usually results in low ionic conductivity,which remains a great challenge for developing solid-state lithiummetal batteries(SL...The absence of efficient ion transport pathways in composite solid-state electrolytes(CSEs)usually results in low ionic conductivity,which remains a great challenge for developing solid-state lithiummetal batteries(SLMBs).Herein,we report achieving accelerated Li^(+)conduction in CSEs by a novel activation of the interfacial dipole layer.Polycationic ionic liquids and polyacrylonitrile with highly polar functional groups(-C≡N)are utilized to modulate the interfacial dipole layer in MOF-based CSEs,facilitating long-range pathways for the connectivity of Li^(+)conduction and enhancing rapid transport kinetics.The as-synthesized CSEs exhibit a high ionic conductivity of 0.59 mS cm^(-1)and a lithium transfer number of 0.85.The assembled SLMBs(Li/CSE/LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2))delivered a high-capacity retention of 88.7%with a minimal discharge voltage attenuation of 17.1 mV after 500 cycles(0.03 mV per cycle)at0.5 C.This work offers an effective approach to creating interpenetrating lithium-ion transport pathways with rapid ion transport kinetics for solid-state electrolytes,thereby advancing the development of solidstate lithium metal batteries.展开更多
Owing to the outstanding optoelectronic properties of perovskite materials,perovskite solar cells(PSCs)have been widely studied by academic organizations and industry corporations,with great potential to become the ne...Owing to the outstanding optoelectronic properties of perovskite materials,perovskite solar cells(PSCs)have been widely studied by academic organizations and industry corporations,with great potential to become the next-generation commercial solar cells.However,critical challenges remain in preserving high efficiency practical large-scale commercialized PSCs:a)the long-term stability of the cell materials and devices,b)lead leakage,and c)methods to scale the cells for larger area applications.This paper summarizes the prior-art strategies to address the above challenges,including the latest studies on the traditional glass-glass and thin-film encapsulation methods to better improve the reliability of PSCs,new technologies for preventing lead leakage,and geometric improvement strategies to enhance the reliability,efficiency,and performance of perovskite solar modules(PSMs).Through these strategies,the device achieved enhanced performance in long-term stability tests.The encapsulation resulted in a high lead leakage inhibition rate of up to 99%,and the PSMs possessed a geometric fill factor of 99.6%and a power conversion efficiency(PCE)of 20.7%.The dramatic improvement of efficiency and reliability of perovskite solar cells and modules indicate the great potential for mass production and commer-cialization of perovskite solar applications in the near future.展开更多
This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in ...This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance.The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules.This enables accurate determination of the optimal timing for postfailure corrective maintenance.To optimize the maintenance strategy,the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate.The model considers multiple cost factors,including inspection costs,preventive maintenance costs,restorative maintenance costs,and penalty costs associated with delayed fault detection.Through this optimization framework,the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions.Comparative analysis demonstrates that the twostage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models.When evaluated against traditional maintenance approaches,including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies,the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components.The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization,leading to enhanced power generation performance.These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance.展开更多
This article introduces a novel 20 V radiation-hardened high-voltage metal-oxide-semiconductor field-effect transistor(MOSFET)driver with an optimized input circuit and a drain-surrounding-source(DSS)structure.The inp...This article introduces a novel 20 V radiation-hardened high-voltage metal-oxide-semiconductor field-effect transistor(MOSFET)driver with an optimized input circuit and a drain-surrounding-source(DSS)structure.The input circuit of a conventional inverter consists of a thick-gate-oxide n-type MOSFET(NMOS).These conventional drivers can tolerate a total ionizing dose(TID)of up to 100 krad(Si).In contrast,the proposed comparator input circuit uses both a thick-gate-oxide p-type MOSFET(PMOS)and thin-gate-oxide NMOS to offer a high input voltage and higher TID tolerance.Because the thick-gate-oxide PMOS and thin-gate-oxide NMOS collectively provide better TID tolerance than the thick-gate-oxide NMOS,the circuit exhibits enhanced TID tolerance of>300 krad(Si).Simulations and experimental date indicate that the DSS structure reduces the probability of unwanted parasitic bipolar junction transistor activation,yielding a better single-event effect tolerance of over 81.8 MeVcm^(2)mg^(-1).The innovative strategy proposed in this study involves circuit and layout design optimization,and does not require any specialized process flow.Hence,the proposed circuit can be manufactured using common commercial 0.35μm BCD processes.展开更多
Expanding the cutoff voltage of layered oxide cathodes for sodium-ion batteries(SIBs)is crucial for overcoming their existing energy density limitations.However,cationic/anodic redox-triggered multiple phase transitio...Expanding the cutoff voltage of layered oxide cathodes for sodium-ion batteries(SIBs)is crucial for overcoming their existing energy density limitations.However,cationic/anodic redox-triggered multiple phase transitions and unfavorable interfacial side reactions accelerate capacity and voltage decay.Herein,we present a straightforward melting plus reactive wetting strategy using H_(3)BO_(3)for surface modification of O_(3)-type Na_(0.9)Cu_(0.12)Ni_(0.33)Mn_(0.4)Ti_(0.15)O_(2)(CNMT).The transformation of H_(3)BO_(3)from solid to liquid under mild heating facilitates the uniform dispersion and complete surface coverage of CNMT particles.By neutralizing the residual alkali and extracting Na^(+)from the CNMT lattice,H_(3)BO_(3)forms a multifunctional Na_(2)B_(2)O_(5)-dominated layer on the CNMT surface.This Na_(x)B_(y)O_(z)(NBO)layer plays a positive role in providing low-barrier Na^(+)transport channels,suppressing phase transitions,and minimizing the generation of O_(2)/CO_(2)gases and resistive byproducts.As a result,at a charge cutoff voltage of 4.5 V,the NBO-coated CNMT delivers a high discharge capacity of 149,1 mAh g^(-1)at 10 mA g^(-1)and exhibits excellent cycling stability at 100 mA g^(-1)over 200 cycles with a higher capacity retention than that of pristine CNMT(86,4%vs,62.1%).This study highlights the effectiveness of surface modification using lowmelting-point solid acids,with potential applications for other layered oxide cathode materials to achieve stable high-voltage cycling.This proposed strategy opens new avenues for the construction of highquality coatings for high-voltage layered oxide cathodes in SIBs.展开更多
Solid-state lithium batteries have become a research hotspot in the field of large-scale energy storage due to their excellent safety performance.The development of high-voltage positive electrode materials matched wi...Solid-state lithium batteries have become a research hotspot in the field of large-scale energy storage due to their excellent safety performance.The development of high-voltage positive electrode materials matched with lithium metal anode have advanced the energy density of solid-state lithium batteries close to or even exceeding that of lithium batteries based on a liquid electrolyte,which is expected to be commercialized in the future.However,in high voltage conditions(>4.3 V),the decomposition of electrolyte components,structural degradation,and interface side reactions significantly reduce battery performance and hinder its further development.This review summarizes the latest research progress of inorganic electrolytes,polymer electrolytes,and composite electrolytes in high-voltage solid-state lithium batteries.At the same time,the designs of high-voltage polymer gel electrolyte and high-voltage quasi solid-state electrolyte are introduced in detail.In addition,interface engineering is crucial for improving the overall performance of high-voltage solid-state batteries.Finally,we highlight the challenges faced by high-voltage solid-state lithium batteries and put forward our own views on future research directions.This review offers instructive insights into the advancement of high-voltage solid-state lithium batteries for large-scale energy storage applications.展开更多
Lithium-ion capacitors(LICs)combine the high power dens-ity of electrical double-layer capacitors with the high energy density of lithium-ion batteries.However,they face practical limitations due to the narrow operati...Lithium-ion capacitors(LICs)combine the high power dens-ity of electrical double-layer capacitors with the high energy density of lithium-ion batteries.However,they face practical limitations due to the narrow operating voltage window of their activated carbon(AC)cathodes.We report a scalable thermal treatment strategy to develop high-voltage-tolerant AC cathodes.Through controlled thermal treatment of commer-cial activated carbon(Raw-AC)under a H_(2)/Ar atmosphere at 400-800℃,the targeted reduction of degradation-prone functional groups can be achieved while preserving the critical pore structure and increasing graph-itic microcrystalline ordering.The AC treated at 400℃(HAC-400)had a significant increase in specific capacity(96.0 vs.75.1 mAh/g at 0.05 A/g)and better rate capability(61.1 vs.36.1 mAh/g at 5 A/g)in half-cell LICs,along with an 83.5%capacity retention over 7400 cycles within an extended voltage range of 2.0-4.2 V in full-cell LICs.Scalability was demonstrated by a 120 g batch production,enabling fabrication of pouch-type LICs with commercial hard carbon anodes that delivered a higher energy density of 28.3 Wh/kg at 1 C,and a peak power density of 12.1 kW/kg compared to devices using raw AC.This simple,industry-compatible approach may be used for producing ad-vanced cathode materials for practical high-performance LICs.展开更多
Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address ...Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address this challenge,a mushroom recognition method was proposed based on an erase module integrated into the EL-DenseNet model.EL-DenseNet,an extension of DenseNet,incorporated an erase attention module designed to enhance sensitivity to visible features.The erase module helped eliminate complex backgrounds and irrelevant information,allowing the mushroom body to be preserved and increasing recognition accuracy in cluttered environments.Considering the difficulty in distinguishing similar mushroom species,label smoothing regularization was employed to mitigate mislabeling errors that commonly arose from human observers.This strategy converted hard labels into soft labels during training,reducing the model’s overreliance on noisy labels and improving its generalization ability.Experimental results showed that the proposed EL-DenseNet,when combined with transfer learning,achieved a recognition accuracy of 96.7%for mushrooms in occluded and complex backgrounds.Compared with the original DenseNet and other classic models,this approach demonstrated superior accuracy and robustness,providing a promising solution for intelligent mushroom recognition.展开更多
Thermal batteries are a type of thermally activated reserve battery,where the cathode material significantly influences the operating voltage and specific capacity.In this work,Cu_(2)O–CuO nanowires are prepared by i...Thermal batteries are a type of thermally activated reserve battery,where the cathode material significantly influences the operating voltage and specific capacity.In this work,Cu_(2)O–CuO nanowires are prepared by in-situ thermal oxidation method onto Cu foam,which are further coated with a carbon layer derived from polydopamine(PDA).The morphology of the nanowires has been examined using scanning electron microscopy(SEM)and transmission electron microscopy(TEM).The material shows a kind of core–shell structure,with CuO as the shell and Cu_(2)O as the core.To further explore the interaction between the material and lithium-ion(Li^(+)),the Lit adsorption energies of CuO and Cu_(2)O were calculated,revealing a stronger affinity of Li^(+) for CuO.The unique core–shell nanowire structure of Cu_(2)O–CuO can provide a good Li^(+)adsorption with the outer layer CuO and excellent structural stability with the inner layer Cu_(2)O.When applied in thermal batteries,Cu_(2)O–CuO–C nanowires exhibit specific capacity and specific energy of 326 mAh g^(-1)and 697 Wh kg^(-1)at a cut-off voltage of 1.5 V both of which are higher than those of Cu_(2)O–CuO(238 mAh g^(-1)and 445 Wh kg^(-1)).The discharge process includes the insertion of lithium ions and subsequent reduction reactions,ultimately resulting in the formation of lithium oxide and copper.展开更多
文摘In this paper,we introduce the notion of G_(C)-X-injective modules,where X denotes a class of left S-modules and C represents a faithfully semidualizing bimodule.Under the condition that X satisfies certain hypotheses,some properties and some equivalent characterizations of G_(C)-X-injective modules are investigated,and we also show that the triple(■,cores■,■)is a weak co-AB-context.As an application,two complete cotorsion pairs and a new model structure in Mod S are given.
基金financial support from the National Natural Science Foundation of China(Nos.52209144 and 12472405).
文摘High-voltage electric pulse(HVEP)rock fragmentation has demonstrated substantial potential for sustainable fracturing of hard rocks owing to its energy efficiency.The transient nature and highly disruptive characteristics of its physical fracturing process render experimental investigation of the underlying rock-breaking mechanisms challenging.However,existing numerical studies lack comprehensive models that precisely link electrical breakdown phenomena with mechanical disintegration processes.This study combines COMSOL electrical breakdown simulations with four-dimension lattice spring model(4D-LSM)mechanical analysis to establish a coupled HVEP rock fragmentation model.The core concept of the model construction is to import the temperature field of the plasma channel obtained from the electrical breakdown into the mechanical solver to realize the precise connection between the two stages.The validated numerical model elucidates the full process of HVEP-induced fragmentation under varying electrical parameters.Furthermore,the effects of confining pressure and mineral grain size on fragmentation behavior have been investigated.Finally,parametric simulations across 25 electrical parameter combinations demonstrate the critical role of electrode spacing optimization in achieving energy-efficient rock fragmentation.These findings provide a predictive tool for designing efficient HVEP systems in deep resource extraction and mineral processing engineering.
基金supported by the National Natural Science Foundation of China(22409002,62371003)the Open Research Fund of Songshan Lake Materials Laboratory(2023SLABFN18)+1 种基金Anhui Provincial Natural Science Foundation(2308085QB46)Scientific Research Foundation of Education Department of Anhui Province of China(2023AH051109,2022AH010025)。
文摘Manganese-based Prussian blue analogues(MnFePBAs),renowned for their high redox potential and dual redox-active sites,often fail to fully realize their intrinsic performance in zinc-ion batteries(ZIBs).In this work,the underlying causes of the instability of monoclinic K^(+) -containing MnFePBA(KMnFePBA)cathodes in aqueous electrolytes were investigated.To prevent irreversible phase transitions,a lowconcentration,flame-retardant organic electrolyte operable under open-air conditions was developed.Utilizing triethyl phosphate(TEP)as the electrolyte solvent,the KMnFePBA cathode exhibited two distinct redox peaks at approximately 1.83 and 1.70 V,coupled with a high reversible capacity of -130 m A h g^(-1).The TEP electrolyte offers not only flame-retardant and anti-drying properties but also benefits from the inclusion of trace amounts of water,which enhances the redox kinetics.The optimized electrolyte enables Zn||KMnFePBA batteries to operate reversibly without structural degradation,function effectively across a wide temperature range,and suppress Zn dendrite formation by modulating the zinc-ion solvation structure and interfacial environment.This study presents a practical electrolyte engineering strategy for stabilizing monoclinic MnFePBA cathodes while simultaneously extending the lifespan of Zn anodes in ZIBs.
基金supported by National Science and Technology Council(NSTC)Taiwan,Grant No.NSTC 113-2221-E-167-023.
文摘Mango is a plant with high economic value in the agricultural industry;thus,it is necessary to maximize the productivity performance of the mango plant,which can be done by implementing artificial intelligence.In this study,a lightweight object detection model will be developed that can detect mango plant conditions based on disease potential,so that it becomes an early detection warning system that has an impact on increasing agricultural productivity.The proposed lightweight model integrates YOLOv7-Tiny and the proposed modules,namely the C2S module.The C2S module consists of three sub-modules such as the convolutional block attention module(CBAM),the coordinate attention(CA)module,and the squeeze-and-excitation(SE)module.The dataset is constructed by eight classes,including seven classes of disease conditions and one class of health conditions.The experimental result shows that the proposed lightweight model has the optimal results,which increase by 13.15% of mAP50 compared to the original model YOLOv7-Tiny.While the mAP50:95 also achieved the highest results compared to other models,including YOLOv3-Tiny,YOLOv4-Tiny,YOLOv5,and YOLOv7-Tiny.The advantage of the proposed lightweightmodel is the adaptability that supports it in constrained environments,such as edge computing systems.This proposedmodel can support a robust,precise,and convenient precision agriculture system for the user.
基金financial support from the National Natural Science Foundation of China(Nos.52204089,52374082)the Young Elite Scientists Sponsorship Program(No.2023QNRC001)by China Association for Science and Technology(CAST).
文摘Microseismic(MS)monitoring is an effective technique to detect mining-induced rock fractures.However,recognizing grouting-induced signals is challenging due to complex geological conditions in deep rock plates.Therefore,a hybrid model(WM-ResNet50)integrating data enhancement,a deep convolutional neural network(CNN),and convolutional block attention modules(CBAM)was proposed.Firstly,an MS system was established at the Xieqiao coal mine in Anhui Province,China.MS waveforms and injection parameters were acquired during grouting.Secondly,signals were categorized based on time-frequency characteristics to build a dataset,which was divided into training,validation,and test sets at a ratio of 4:1:1.Subsequently,the performance of WM-ResNet50 was evaluated based on indices such as individual precision,total accuracy,recall,and loss function.The results indicated that WMResNet50 achieved an average recognition accuracy of 94.38%,surpassing that of a simple CNN(90.04%),ResNet18(91.72%),and ResNet50(92.48%).Finally,WM-ResNet50 was applied to monitor the whole process at laboratory tests and field cases.Both results affirmed the feasibility and effectiveness of MS inversion in predicting actual slurry diffusion ranges within deep rock layers.By comparison,it was revealed that the MS sources classified by WM-ResNet50 matched grouting records well.A solution to address insufficient diffusion under long-borehole grouting has been proposed.WM-ResNet50′s accuracy was validated through in-situ coring and XRD analysis for cement-based hydration products.This study provides a beneficial reference for similar rock signal processing and in-field grouting practices.
基金supported by the Gansu Provincial Department of Education Industry Support Plan Project(2025CYZC-018).
文摘In order to address the challenges posed by complex background interference,high miss-detection rates of micro-scale defects,and limited model deployment efficiency in photovoltaic(PV)module defect detection,this paper proposes an efficient detection framework based on an improved YOLOv11 architecture.First,a Re-parameterized Convolution(RepConv)module is integrated into the backbone to enhance the model’s sensitivity to fine-grained defects—such as micro-cracks and hot spots—while maintaining high inference efficiency.Second,a Multi-Scale Feature Fusion Convolutional Block Attention Mechanism(MSFF-CBAM)is designed to guide the network toward critical defect regions by jointly modeling channel-wise and spatial attention.This mechanism effectively strengthens the specificity and robustness of feature representations.Third,a lightweight Dynamic Sampling Module(DySample)is employed to replace conventional upsampling operations,thereby improving the localization accuracy of small-scale defect targets.Experimental evaluations conducted on the PVEL-AD dataset demonstrate that the proposed RMDYOLOv11 model surpasses the baseline YOLOv11 in terms of mean Average Precision(mAP)@0.5,Precision,and Recall,achieving respective improvements of 4.70%,1.51%,and 5.50%.The model also exhibits notable advantages in inference speed and model compactness.Further validation on the ELPV dataset confirms the model’s generalization capability,showing respective performance gains of 1.99%,2.28%,and 1.45%across the same metrics.Overall,the enhanced model significantly improves the accuracy of micro-defect identification on PV module surfaces,effectively reducing both false negatives and false positives.This advancement provides a robust and reliable technical foundation for automated PV module defect detection.
基金Supported by Anhui Provincial Engineering Research Center for Sports and Health Information Monitoring Technology(KF2023012)。
文摘WiFi-based human activity recognition(HAR)provides a non-intrusive approach for ubiquitous monitoring;however,achieving both high accuracy and robustness simultaneously remains a significant challenge.This paper proposes a Convolutional Neural Network with Enhanced Convolutional Block Attention Module(CNN-ECBAM)framework.The approach systematically converts raw Channel State Information(CSI)into pseudo-color images,effectively preserving essential signal characteristics for deep neural network processing.The core innovation is an Enhanced Convolutional Block Attention Module(ECBAM),tailored to CSI data characteristics,which integrates Efficient Channel Attention(ECA)and Multi-Scale Spatial Attention(MSSA).By employing learnable adaptive fusion weights,it achieves dynamic synergy between channel and spatial features,enabling the network to capture highly discriminative spatiotemporal patterns.The ECBAM module is integrated into a unified Convolutional Neural Network(CNN)to form the overall CNN-ECBAM model.Experimental results on the UT-HAR and NTU-Fi_HAR datasets demonstrate that CNN-ECBAM achieves competitive performance in recognition accuracy and outperforms mainstream baseline models.Specifically,it attains 99.20%accuracy on UT-HAR(surpassing ResNet-18 at 98.60%)and achieves 100%accuracy on NTU-Fi_HAR(exceeding GAF-CNN at 99.62%).These results validate the effectiveness of the proposed method for high-precision and reliable WiFi-based HAR.
基金supported by the Shenzhen Science and Technology Planning Project(Grant No.JSGG20220831095604008)the National Natural Science Foundation of China(Grant No.51902296)+2 种基金the National Center for International Research of Electric Vehicle Power Batteries and Materials(Grant No.2015B01015)the Guangdong Key Laboratory of Design and Calculation of New Energy Materials(Grant No.2017B030301013)the Shenzhen Key Laboratory of New Energy Resources Genome Preparation and Testing(Grant No.ZDSYS201707281026184).
文摘Lithium-ion batteries are essential for modern energy storage,yet achieving simultaneous high-temperature and high-voltage operation remains challenging due to interfacial compatibility.In this study,we introduce a polyetherimide(PEI)-polyimide(PI)functional coating on the separator that enhances wettability,thermal stability,and mechanical strength,while markedly improving cathode stability under harsh conditions.By integrating theoretical calculations with experimental validation,we demonstrate that the PEI/PI coating modulates the solvation structure of lithium-ions,thereby facilitating the interfacial desolvation process.More importantly,the PEI/PI layer regulates electrolyte decomposition at the interface,promoting the formation of a uniform and thermally stable cathode-electrolyte interphase.Consequently,LiCoO_(2)cathodes exhibit improved cycling performance at 60°C.Overall,this work underscores the pivotal role of separator coatings in governing interfacial chemistry and provides a viable strategy for designing high-performance lithium-ion batteries capable of enduring both high temperatures and high.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
基金supported by the Exchange Program of Highend Foreign Experts of Ministry of Science and Technology of People’s Republic of China(No.G2023041003L)the Natural Science Foundation of Shaanxi Provincial Department of Education(No.23JK0367)+1 种基金the Scientific Research Startup Program for Introduced Talents of Shaanxi University of Technology(Nos.SLGRCQD2208,SLGRCQD2306,SLGRCQD2133)Contaminated Soil Remediation and Resource Utilization Innovation Team at Shaanxi University of Technology。
文摘As battery technology evolves and demand for efficient energy storage solutions,aqueous zinc ion batteries(AZIBs)have garnered significant attention due to their safety and environmental benefits.However,the stability of cathode materials under high-voltage conditions remains a critical challenge in improving its energy density.This review systematically explores the failure mechanisms of high-voltage cathode materials in AZIBs,including hydrogen evolution reaction,phase transformation and dissolution phenomena.To address these challenges,we propose a range of advanced strategies aimed at improving the stability of cathode materials.These strategies include surface coating and doping techniques designed to fortify the surface properties and structure integrity of the cathode materials under high-voltage conditions.Additionally,we emphasize the importance of designing antioxidant electrolytes,with a focus on understanding and optimizing electrolyte decomposition mechanisms.The review also highlights the significance of modifying conductive agents and employing innovative separators to further enhance the stability of AZIBs.By integrating these cutting-edge approaches,this review anticipates substantial advancements in the stability of high-voltage cathode materials,paving the way for the broader application and development of AZIBs in energy storage.
基金financially supported by the National Natural Science Foundation of China(22408239)the National Natural Science Foundation of China(51904193)+3 种基金the Sichuan Science and Technology Program(2024NSFSC0987)the Fundamental Research Funds for the Central Universities(No.YJ202280)support from the Australian Research Council(ARC)through the ARC Linkage project(LP200200926)ARC Discover project(DP240102176)。
文摘The absence of efficient ion transport pathways in composite solid-state electrolytes(CSEs)usually results in low ionic conductivity,which remains a great challenge for developing solid-state lithiummetal batteries(SLMBs).Herein,we report achieving accelerated Li^(+)conduction in CSEs by a novel activation of the interfacial dipole layer.Polycationic ionic liquids and polyacrylonitrile with highly polar functional groups(-C≡N)are utilized to modulate the interfacial dipole layer in MOF-based CSEs,facilitating long-range pathways for the connectivity of Li^(+)conduction and enhancing rapid transport kinetics.The as-synthesized CSEs exhibit a high ionic conductivity of 0.59 mS cm^(-1)and a lithium transfer number of 0.85.The assembled SLMBs(Li/CSE/LiNi_(0.9)Co_(0.05)Mn_(0.05)O_(2))delivered a high-capacity retention of 88.7%with a minimal discharge voltage attenuation of 17.1 mV after 500 cycles(0.03 mV per cycle)at0.5 C.This work offers an effective approach to creating interpenetrating lithium-ion transport pathways with rapid ion transport kinetics for solid-state electrolytes,thereby advancing the development of solidstate lithium metal batteries.
基金supported by the National Natural Science Foundation of China(No.62404041)the Natural Science Foundation of Jiangsu Province of China(No.BK20230830).
文摘Owing to the outstanding optoelectronic properties of perovskite materials,perovskite solar cells(PSCs)have been widely studied by academic organizations and industry corporations,with great potential to become the next-generation commercial solar cells.However,critical challenges remain in preserving high efficiency practical large-scale commercialized PSCs:a)the long-term stability of the cell materials and devices,b)lead leakage,and c)methods to scale the cells for larger area applications.This paper summarizes the prior-art strategies to address the above challenges,including the latest studies on the traditional glass-glass and thin-film encapsulation methods to better improve the reliability of PSCs,new technologies for preventing lead leakage,and geometric improvement strategies to enhance the reliability,efficiency,and performance of perovskite solar modules(PSMs).Through these strategies,the device achieved enhanced performance in long-term stability tests.The encapsulation resulted in a high lead leakage inhibition rate of up to 99%,and the PSMs possessed a geometric fill factor of 99.6%and a power conversion efficiency(PCE)of 20.7%.The dramatic improvement of efficiency and reliability of perovskite solar cells and modules indicate the great potential for mass production and commer-cialization of perovskite solar applications in the near future.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance.The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules.This enables accurate determination of the optimal timing for postfailure corrective maintenance.To optimize the maintenance strategy,the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate.The model considers multiple cost factors,including inspection costs,preventive maintenance costs,restorative maintenance costs,and penalty costs associated with delayed fault detection.Through this optimization framework,the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions.Comparative analysis demonstrates that the twostage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models.When evaluated against traditional maintenance approaches,including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies,the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components.The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization,leading to enhanced power generation performance.These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance.
基金supported by the National Natural Science Foundation of China(U2241221).
文摘This article introduces a novel 20 V radiation-hardened high-voltage metal-oxide-semiconductor field-effect transistor(MOSFET)driver with an optimized input circuit and a drain-surrounding-source(DSS)structure.The input circuit of a conventional inverter consists of a thick-gate-oxide n-type MOSFET(NMOS).These conventional drivers can tolerate a total ionizing dose(TID)of up to 100 krad(Si).In contrast,the proposed comparator input circuit uses both a thick-gate-oxide p-type MOSFET(PMOS)and thin-gate-oxide NMOS to offer a high input voltage and higher TID tolerance.Because the thick-gate-oxide PMOS and thin-gate-oxide NMOS collectively provide better TID tolerance than the thick-gate-oxide NMOS,the circuit exhibits enhanced TID tolerance of>300 krad(Si).Simulations and experimental date indicate that the DSS structure reduces the probability of unwanted parasitic bipolar junction transistor activation,yielding a better single-event effect tolerance of over 81.8 MeVcm^(2)mg^(-1).The innovative strategy proposed in this study involves circuit and layout design optimization,and does not require any specialized process flow.Hence,the proposed circuit can be manufactured using common commercial 0.35μm BCD processes.
基金supported by the National Natural Science Foundation of China(22169002 and 22469003)the Chongzuo Key Research and Development Program of China(20241205 and 20231204)the Counterpart Aid Project for Discipline Construction from Guangxi University(2023M02)。
文摘Expanding the cutoff voltage of layered oxide cathodes for sodium-ion batteries(SIBs)is crucial for overcoming their existing energy density limitations.However,cationic/anodic redox-triggered multiple phase transitions and unfavorable interfacial side reactions accelerate capacity and voltage decay.Herein,we present a straightforward melting plus reactive wetting strategy using H_(3)BO_(3)for surface modification of O_(3)-type Na_(0.9)Cu_(0.12)Ni_(0.33)Mn_(0.4)Ti_(0.15)O_(2)(CNMT).The transformation of H_(3)BO_(3)from solid to liquid under mild heating facilitates the uniform dispersion and complete surface coverage of CNMT particles.By neutralizing the residual alkali and extracting Na^(+)from the CNMT lattice,H_(3)BO_(3)forms a multifunctional Na_(2)B_(2)O_(5)-dominated layer on the CNMT surface.This Na_(x)B_(y)O_(z)(NBO)layer plays a positive role in providing low-barrier Na^(+)transport channels,suppressing phase transitions,and minimizing the generation of O_(2)/CO_(2)gases and resistive byproducts.As a result,at a charge cutoff voltage of 4.5 V,the NBO-coated CNMT delivers a high discharge capacity of 149,1 mAh g^(-1)at 10 mA g^(-1)and exhibits excellent cycling stability at 100 mA g^(-1)over 200 cycles with a higher capacity retention than that of pristine CNMT(86,4%vs,62.1%).This study highlights the effectiveness of surface modification using lowmelting-point solid acids,with potential applications for other layered oxide cathode materials to achieve stable high-voltage cycling.This proposed strategy opens new avenues for the construction of highquality coatings for high-voltage layered oxide cathodes in SIBs.
基金supported by the National Key R&D Program of China(2024YFA1211100)the National Natural Science Foundation of China(52301278,22479080,52202254,92372001,22393900,and 92372203)+2 种基金the Natural Science Foundation of Jiangsu Province(BK20230937,BK20220966)the Science and Technology Plans of Tianjin(23JCYBJC00170,24JCJQJC00220,and 24ZXZSSS00390)the Fundamental Research Funds for the Central Universities(02063253167,30922010708)。
文摘Solid-state lithium batteries have become a research hotspot in the field of large-scale energy storage due to their excellent safety performance.The development of high-voltage positive electrode materials matched with lithium metal anode have advanced the energy density of solid-state lithium batteries close to or even exceeding that of lithium batteries based on a liquid electrolyte,which is expected to be commercialized in the future.However,in high voltage conditions(>4.3 V),the decomposition of electrolyte components,structural degradation,and interface side reactions significantly reduce battery performance and hinder its further development.This review summarizes the latest research progress of inorganic electrolytes,polymer electrolytes,and composite electrolytes in high-voltage solid-state lithium batteries.At the same time,the designs of high-voltage polymer gel electrolyte and high-voltage quasi solid-state electrolyte are introduced in detail.In addition,interface engineering is crucial for improving the overall performance of high-voltage solid-state batteries.Finally,we highlight the challenges faced by high-voltage solid-state lithium batteries and put forward our own views on future research directions.This review offers instructive insights into the advancement of high-voltage solid-state lithium batteries for large-scale energy storage applications.
文摘Lithium-ion capacitors(LICs)combine the high power dens-ity of electrical double-layer capacitors with the high energy density of lithium-ion batteries.However,they face practical limitations due to the narrow operating voltage window of their activated carbon(AC)cathodes.We report a scalable thermal treatment strategy to develop high-voltage-tolerant AC cathodes.Through controlled thermal treatment of commer-cial activated carbon(Raw-AC)under a H_(2)/Ar atmosphere at 400-800℃,the targeted reduction of degradation-prone functional groups can be achieved while preserving the critical pore structure and increasing graph-itic microcrystalline ordering.The AC treated at 400℃(HAC-400)had a significant increase in specific capacity(96.0 vs.75.1 mAh/g at 0.05 A/g)and better rate capability(61.1 vs.36.1 mAh/g at 5 A/g)in half-cell LICs,along with an 83.5%capacity retention over 7400 cycles within an extended voltage range of 2.0-4.2 V in full-cell LICs.Scalability was demonstrated by a 120 g batch production,enabling fabrication of pouch-type LICs with commercial hard carbon anodes that delivered a higher energy density of 28.3 Wh/kg at 1 C,and a peak power density of 12.1 kW/kg compared to devices using raw AC.This simple,industry-compatible approach may be used for producing ad-vanced cathode materials for practical high-performance LICs.
文摘Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address this challenge,a mushroom recognition method was proposed based on an erase module integrated into the EL-DenseNet model.EL-DenseNet,an extension of DenseNet,incorporated an erase attention module designed to enhance sensitivity to visible features.The erase module helped eliminate complex backgrounds and irrelevant information,allowing the mushroom body to be preserved and increasing recognition accuracy in cluttered environments.Considering the difficulty in distinguishing similar mushroom species,label smoothing regularization was employed to mitigate mislabeling errors that commonly arose from human observers.This strategy converted hard labels into soft labels during training,reducing the model’s overreliance on noisy labels and improving its generalization ability.Experimental results showed that the proposed EL-DenseNet,when combined with transfer learning,achieved a recognition accuracy of 96.7%for mushrooms in occluded and complex backgrounds.Compared with the original DenseNet and other classic models,this approach demonstrated superior accuracy and robustness,providing a promising solution for intelligent mushroom recognition.
基金supported by National Natural Science Foundation of China(Nos.52374298)National Natural Science Foundation of Chongqing(Nos.CSTB2023NSCQ-MSX0662)Beijing Natural Science Foundation(Nos.L243019).
文摘Thermal batteries are a type of thermally activated reserve battery,where the cathode material significantly influences the operating voltage and specific capacity.In this work,Cu_(2)O–CuO nanowires are prepared by in-situ thermal oxidation method onto Cu foam,which are further coated with a carbon layer derived from polydopamine(PDA).The morphology of the nanowires has been examined using scanning electron microscopy(SEM)and transmission electron microscopy(TEM).The material shows a kind of core–shell structure,with CuO as the shell and Cu_(2)O as the core.To further explore the interaction between the material and lithium-ion(Li^(+)),the Lit adsorption energies of CuO and Cu_(2)O were calculated,revealing a stronger affinity of Li^(+) for CuO.The unique core–shell nanowire structure of Cu_(2)O–CuO can provide a good Li^(+)adsorption with the outer layer CuO and excellent structural stability with the inner layer Cu_(2)O.When applied in thermal batteries,Cu_(2)O–CuO–C nanowires exhibit specific capacity and specific energy of 326 mAh g^(-1)and 697 Wh kg^(-1)at a cut-off voltage of 1.5 V both of which are higher than those of Cu_(2)O–CuO(238 mAh g^(-1)and 445 Wh kg^(-1)).The discharge process includes the insertion of lithium ions and subsequent reduction reactions,ultimately resulting in the formation of lithium oxide and copper.
