This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networ...This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networks.Unlike conventional Deep Reinforcement Learning(DRL)-based approaches for CW size adjustment,which often suffer from overestimation bias and limited exploration diversity,leading to suboptimal throughput and collision performance.Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions.First,SETL adopts a DDQN architecture(SETL-DDQN)to improve Q-value estimation accuracy and enhance training stability.Second,we incorporate a Gumbel distribution-driven exploration mechanism,forming SETL-DDQN(Gumbel),which employs the extreme value theory to promote diverse action selection,replacing the conventional-greedy exploration that undergoes early convergence to suboptimal solutions.Both models are evaluated through extensive simulations in static and time-varying IEEE 802.11 network scenarios.The results demonstrate that our approach consistently achieves higher throughput,lower collision rates,and improved adaptability,even under abrupt fluctuations in traffic load and network conditions.In particular,the Gumbel-based mechanism enhances the balance between exploration and exploitation,facilitating faster adaptation to varying congestion levels.These findings position Gumbel-enhanced DRL as an effective and robust solution for CW optimization in wireless networks,offering notable gains in efficiency and reliability over existing methods.展开更多
Combined pulsed laser(CPL),introduced in 1975 for target damage,integrates different lasers to achieve high peak power and pulse energy.However,despite decades of research,CPL remains unused for long-range target dama...Combined pulsed laser(CPL),introduced in 1975 for target damage,integrates different lasers to achieve high peak power and pulse energy.However,despite decades of research,CPL remains unused for long-range target damage due to the challenge of maintaining high peak power density over long distances.We note that a potential solution lies in leveraging the air filament generated by femtosecond laser,which can transmit peak power densities higher than 1014 W/cm^(2)under the power clamping effect.To address this,a concept of a femtosecond laser induced air filament-CW CPL for surface damage of ceramics was introduced.We found no surface changes in ceramic targets when irradiated with a CW laser alone.By way of contrast,the target can be penetrated in a very short time(20 ms)with the assistance of the femtosecond laser induced air filament.In this context,we employ high-speed shadow imaging,cross-timescale simulation models and macro-microscopic characterization,to elucidate the CPL damage mechanism.The optimal CPL,combining a 1 mJ femtosecond laser and a 500 W CW laser,yields a damage rate of 1.51×10^(7)μm^(3)/J,representing an improvement of approximately 175%compared to single femtosecond laser ablation and around 59%enhancement compared to coating-assisted CW laser ablation.Furthermore,the efficacy of the proposed femtosecond-CW CPL method is demonstrated in causing penetration damage of ceramic/metal composite material or direct damage of sapphire,showcasing its versatility in damaging applications.Consequently,the femtosecond-CW CPL ablation method presented in this paper holds great promise as a new type of damage method for transparent hard and brittle materials.展开更多
Transparent materials utilized as underwater optical windows are highly vulnerable to various forms of pollution or abrasion due to their intrinsic hydrophilic properties.This susceptibility is particularly pronounced...Transparent materials utilized as underwater optical windows are highly vulnerable to various forms of pollution or abrasion due to their intrinsic hydrophilic properties.This susceptibility is particularly pronounced in underwater environments where pollutants can impede the operation of these optical devices,significantly degrading or even compromising their optical properties.The glass catfish,known for its remarkable transparency in water,maintains surface cleanliness and clarity despite exposure to contaminants,impurities abrasion,and hydraulic pressure.Inspired by the glass catfish’s natural attributes,this study introduces a new solution named subaquatic abrasion-resistant and anti-fouling window(SAAW).Utilizing femtosecond laser ablation and electrodeposition,the SAAW is engineered by embedding fine metal bone structures into a transparent substrate and anti-fouling sliding layer,akin to the sturdy bones among catfish’s body.This approach significantly bolsters the window’s abrasion resistance and anti-fouling performance while maintaining high light transmittance.The sliding layer on the SAAW’s surface remarkably reduces the friction of various liquids,which is the reason that SAAW owns the great anti-fouling property.The SAAW demonstrates outstanding optical clarity even after enduring hundreds of sandpaper abrasions,attributing to the fine metal bone structures bearing all external forces and protecting the sliding layer of SAAW.Furthermore,it exhibits exceptional resistance to biological adhesion and underwater pressure.In a green algae environment,the window remains clean with minimal change in transmittance over one month.Moreover,it retains its wettability and anti-fouling properties when subjected to a depth of 30 m of underwater pressure for 30 d.Hence,the SAAW prepared by femtosecond laser ablation and electrodeposition presents a promising strategy for developing stable optical windows in liquid environments.展开更多
With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation wind...With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.展开更多
Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally...Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O_(3) pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.展开更多
With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant c...With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant challenges to information security.These techniques embed hidden information into speech streams,making detection increasingly difficult,particularly under conditions of low embedding rates and short speech durations.Existing steganalysis methods often struggle to balance detection accuracy and computational efficiency due to their limited ability to effectively capture both temporal and spatial features of speech signals.To address these challenges,this paper proposes an Efficient Sliding Window Analysis Network(E-SWAN),a novel deep learning model specifically designed for real-time speech steganalysis.E-SWAN integrates two core modules:the LSTM Temporal Feature Miner(LTFM)and the Convolutional Key Feature Miner(CKFM).LTFM captures long-range temporal dependencies using Long Short-Term Memory networks,while CKFM identifies local spatial variations caused by steganographic embedding through convolutional operations.These modules operate within a sliding window framework,enabling efficient extraction of temporal and spatial features.Experimental results on the Chinese CNV and PMS datasets demonstrate the superior performance of E-SWAN.Under conditions of a ten-second sample duration and an embedding rate of 10%,E-SWAN achieves a detection accuracy of 62.09%on the PMS dataset,surpassing existing methods by 4.57%,and an accuracy of 82.28%on the CNV dataset,outperforming state-of-the-art methods by 7.29%.These findings validate the robustness and efficiency of E-SWAN under low embedding rates and short durations,offering a promising solution for real-time VoIP steganalysis.This work provides significant contributions to enhancing information security in digital communications.展开更多
In this paper,an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check(SC-LDPC)codes.For the conventional sliding window decoder,the message retention mechanism causes u...In this paper,an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check(SC-LDPC)codes.For the conventional sliding window decoder,the message retention mechanism causes unreliable messages along the edges of belief propagation(BP)decoding in the current window to be kept for subsequent window decoding.To improve the reliability of the retained messages during the window transition,a reliable termination method is embedded,where the retained messages undergo more reliable parity checks.Additionally,decoding failure is unavoidable and even causes error propagation when the number of errors exceeds the error-correcting capability of the window.To mitigate this problem,a channel value reuse mechanism is designed,where the received channel values are utilized to reinitialize the window.Furthermore,considering the complexity and performance of decoding,a feasible sliding optimized window decoding(SOWD)scheme is introduced.Finally,simulation results confirm the superior performance of the proposed SOWD scheme in both the waterfall and error floor regions.This work has great potential in the applications of wireless optical communication and fiber optic communication.展开更多
Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security...Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.展开更多
Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories...Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.展开更多
Regulating the freedom and distribution of H_(2)O molecules has become the decisive factor in enlarging the electrochemical stability window(ESW)of aqueous electrolytes.Compared with the water in a bulk electrolyte,H_...Regulating the freedom and distribution of H_(2)O molecules has become the decisive factor in enlarging the electrochemical stability window(ESW)of aqueous electrolytes.Compared with the water in a bulk electrolyte,H_(2)O molecules at the electrode-electrolyte interface tend to directly split under bias potential.Therefore,the composition and properties of the interfacial microenvironment are the crux for optimizing ESW.Herein,we developed a heterogel electrolyte with wide ESW(4.88 V)and satisfactory ionic conductivity(4.4 mS/cm)inspired by the bicontinuous architecture and surfactant self-assembly behavior in the ionic liquid microemulsion-based template.This electrolyte was capable of expanding the ESW through the dynamic oil/water/electrode interface ternary structure,which enriched the oil phase and assembled the hydrophobic surfactant tails at the interface to prevent H_(2)O molecules from approaching the electrode surface.Moreover,the surfactant Tween 20 and polymer network effectively suppressed the activity of H_(2)O molecules through H-bond interactions,which was beneficial in expanding the operating voltage range and improving the temperature tolerance.The prepared gel electrolyte demonstrated unparalleled adaptability in various aqueous lithium-based energy storage devices.Notably,the lithium-ion capacitor showed an extended operating voltage of 2.2 V and could provide a high power density of 1350.36 W/kg at an energy density of 6 Wh/kg.It maintained normal power output even in the challenging harsh environment,which enabled 11,000 uninterrupted charge-discharge cycles at 0℃.This work focuses on the regulation of the interfacial microdomain and the restriction of the degree of freedom of H_(2)O molecules to boost the ESW of aqueous electrolytes,providing a promising strategy for the advancement of energy storage technologies.展开更多
文摘This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networks.Unlike conventional Deep Reinforcement Learning(DRL)-based approaches for CW size adjustment,which often suffer from overestimation bias and limited exploration diversity,leading to suboptimal throughput and collision performance.Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions.First,SETL adopts a DDQN architecture(SETL-DDQN)to improve Q-value estimation accuracy and enhance training stability.Second,we incorporate a Gumbel distribution-driven exploration mechanism,forming SETL-DDQN(Gumbel),which employs the extreme value theory to promote diverse action selection,replacing the conventional-greedy exploration that undergoes early convergence to suboptimal solutions.Both models are evaluated through extensive simulations in static and time-varying IEEE 802.11 network scenarios.The results demonstrate that our approach consistently achieves higher throughput,lower collision rates,and improved adaptability,even under abrupt fluctuations in traffic load and network conditions.In particular,the Gumbel-based mechanism enhances the balance between exploration and exploitation,facilitating faster adaptation to varying congestion levels.These findings position Gumbel-enhanced DRL as an effective and robust solution for CW optimization in wireless networks,offering notable gains in efficiency and reliability over existing methods.
基金supports from National Natural Science Foundation of China(Grant No.52105498)The science and technology innovation Program of Hunan Province(Grant No.2021RC3074)+2 种基金Advanced Laser Technology Laboratory of Anhui Province(AHL2022KF04)National Key R&D Program of China(Grant No.2023YFB14605500)Changsha Natural Science Foundation(kq2402089).
文摘Combined pulsed laser(CPL),introduced in 1975 for target damage,integrates different lasers to achieve high peak power and pulse energy.However,despite decades of research,CPL remains unused for long-range target damage due to the challenge of maintaining high peak power density over long distances.We note that a potential solution lies in leveraging the air filament generated by femtosecond laser,which can transmit peak power densities higher than 1014 W/cm^(2)under the power clamping effect.To address this,a concept of a femtosecond laser induced air filament-CW CPL for surface damage of ceramics was introduced.We found no surface changes in ceramic targets when irradiated with a CW laser alone.By way of contrast,the target can be penetrated in a very short time(20 ms)with the assistance of the femtosecond laser induced air filament.In this context,we employ high-speed shadow imaging,cross-timescale simulation models and macro-microscopic characterization,to elucidate the CPL damage mechanism.The optimal CPL,combining a 1 mJ femtosecond laser and a 500 W CW laser,yields a damage rate of 1.51×10^(7)μm^(3)/J,representing an improvement of approximately 175%compared to single femtosecond laser ablation and around 59%enhancement compared to coating-assisted CW laser ablation.Furthermore,the efficacy of the proposed femtosecond-CW CPL method is demonstrated in causing penetration damage of ceramic/metal composite material or direct damage of sapphire,showcasing its versatility in damaging applications.Consequently,the femtosecond-CW CPL ablation method presented in this paper holds great promise as a new type of damage method for transparent hard and brittle materials.
基金supported by the National Science Foundation of China under Grant Nos(Nos.12127806,62175195)the International Joint Research Laboratory for Micro/Nano Manufacturing and Measurement Technologies。
文摘Transparent materials utilized as underwater optical windows are highly vulnerable to various forms of pollution or abrasion due to their intrinsic hydrophilic properties.This susceptibility is particularly pronounced in underwater environments where pollutants can impede the operation of these optical devices,significantly degrading or even compromising their optical properties.The glass catfish,known for its remarkable transparency in water,maintains surface cleanliness and clarity despite exposure to contaminants,impurities abrasion,and hydraulic pressure.Inspired by the glass catfish’s natural attributes,this study introduces a new solution named subaquatic abrasion-resistant and anti-fouling window(SAAW).Utilizing femtosecond laser ablation and electrodeposition,the SAAW is engineered by embedding fine metal bone structures into a transparent substrate and anti-fouling sliding layer,akin to the sturdy bones among catfish’s body.This approach significantly bolsters the window’s abrasion resistance and anti-fouling performance while maintaining high light transmittance.The sliding layer on the SAAW’s surface remarkably reduces the friction of various liquids,which is the reason that SAAW owns the great anti-fouling property.The SAAW demonstrates outstanding optical clarity even after enduring hundreds of sandpaper abrasions,attributing to the fine metal bone structures bearing all external forces and protecting the sliding layer of SAAW.Furthermore,it exhibits exceptional resistance to biological adhesion and underwater pressure.In a green algae environment,the window remains clean with minimal change in transmittance over one month.Moreover,it retains its wettability and anti-fouling properties when subjected to a depth of 30 m of underwater pressure for 30 d.Hence,the SAAW prepared by femtosecond laser ablation and electrodeposition presents a promising strategy for developing stable optical windows in liquid environments.
文摘With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.
基金supported by the Natural Science Foundation of Henan Province[grant number:242300420115]Key Scientific Research Projects in Universities of Henan Province[grant number:23A330006].
文摘Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O_(3) pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.
基金supported in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LQ20F020004in part by the National College Student Innovation and Research Training Program under Grant 202313283002.
文摘With the rapid advancement of Voice over Internet Protocol(VoIP)technology,speech steganography techniques such as Quantization Index Modulation(QIM)and Pitch Modulation Steganography(PMS)have emerged as significant challenges to information security.These techniques embed hidden information into speech streams,making detection increasingly difficult,particularly under conditions of low embedding rates and short speech durations.Existing steganalysis methods often struggle to balance detection accuracy and computational efficiency due to their limited ability to effectively capture both temporal and spatial features of speech signals.To address these challenges,this paper proposes an Efficient Sliding Window Analysis Network(E-SWAN),a novel deep learning model specifically designed for real-time speech steganalysis.E-SWAN integrates two core modules:the LSTM Temporal Feature Miner(LTFM)and the Convolutional Key Feature Miner(CKFM).LTFM captures long-range temporal dependencies using Long Short-Term Memory networks,while CKFM identifies local spatial variations caused by steganographic embedding through convolutional operations.These modules operate within a sliding window framework,enabling efficient extraction of temporal and spatial features.Experimental results on the Chinese CNV and PMS datasets demonstrate the superior performance of E-SWAN.Under conditions of a ten-second sample duration and an embedding rate of 10%,E-SWAN achieves a detection accuracy of 62.09%on the PMS dataset,surpassing existing methods by 4.57%,and an accuracy of 82.28%on the CNV dataset,outperforming state-of-the-art methods by 7.29%.These findings validate the robustness and efficiency of E-SWAN under low embedding rates and short durations,offering a promising solution for real-time VoIP steganalysis.This work provides significant contributions to enhancing information security in digital communications.
基金supported by the National Natural Science Foundation of China (No.62275193)。
文摘In this paper,an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check(SC-LDPC)codes.For the conventional sliding window decoder,the message retention mechanism causes unreliable messages along the edges of belief propagation(BP)decoding in the current window to be kept for subsequent window decoding.To improve the reliability of the retained messages during the window transition,a reliable termination method is embedded,where the retained messages undergo more reliable parity checks.Additionally,decoding failure is unavoidable and even causes error propagation when the number of errors exceeds the error-correcting capability of the window.To mitigate this problem,a channel value reuse mechanism is designed,where the received channel values are utilized to reinitialize the window.Furthermore,considering the complexity and performance of decoding,a feasible sliding optimized window decoding(SOWD)scheme is introduced.Finally,simulation results confirm the superior performance of the proposed SOWD scheme in both the waterfall and error floor regions.This work has great potential in the applications of wireless optical communication and fiber optic communication.
基金supported by the National Undergraduate Innovation and Entrepreneurship Training Program of China(Project No.202510559076)at Jinan University,a nationwide initiative administered by the Ministry of Educationthe National Natural Science Foundation of China(NSFC)under Grant No.62172189.
文摘Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.
基金supported by the National Natural Science Foundation of China(32371028,32300822,U24A20373,and 82071177)the Shanghai Rising-Star Program(24QA2704800)+2 种基金the Shanghai Jiao Tong University 2030 InitiativeShanghai Municipal Health Commission(202340046)the Fund for Excellent Young Scholars of Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine.
文摘Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.
基金supported by the National Natural Science Foundation of China(Grant Nos.22032003 and 22072073)。
文摘Regulating the freedom and distribution of H_(2)O molecules has become the decisive factor in enlarging the electrochemical stability window(ESW)of aqueous electrolytes.Compared with the water in a bulk electrolyte,H_(2)O molecules at the electrode-electrolyte interface tend to directly split under bias potential.Therefore,the composition and properties of the interfacial microenvironment are the crux for optimizing ESW.Herein,we developed a heterogel electrolyte with wide ESW(4.88 V)and satisfactory ionic conductivity(4.4 mS/cm)inspired by the bicontinuous architecture and surfactant self-assembly behavior in the ionic liquid microemulsion-based template.This electrolyte was capable of expanding the ESW through the dynamic oil/water/electrode interface ternary structure,which enriched the oil phase and assembled the hydrophobic surfactant tails at the interface to prevent H_(2)O molecules from approaching the electrode surface.Moreover,the surfactant Tween 20 and polymer network effectively suppressed the activity of H_(2)O molecules through H-bond interactions,which was beneficial in expanding the operating voltage range and improving the temperature tolerance.The prepared gel electrolyte demonstrated unparalleled adaptability in various aqueous lithium-based energy storage devices.Notably,the lithium-ion capacitor showed an extended operating voltage of 2.2 V and could provide a high power density of 1350.36 W/kg at an energy density of 6 Wh/kg.It maintained normal power output even in the challenging harsh environment,which enabled 11,000 uninterrupted charge-discharge cycles at 0℃.This work focuses on the regulation of the interfacial microdomain and the restriction of the degree of freedom of H_(2)O molecules to boost the ESW of aqueous electrolytes,providing a promising strategy for the advancement of energy storage technologies.
