Aqueous zinc metal batteries (AZMBs) are hindered by uncontrolled dendrites and side reactions during commercialization,despite their advantages of safety and high capacity density.Herein,we propose the electrical fee...Aqueous zinc metal batteries (AZMBs) are hindered by uncontrolled dendrites and side reactions during commercialization,despite their advantages of safety and high capacity density.Herein,we propose the electrical feedback strategy to restrain the Zn dendrites resulting from the"tip effect"and optimize interfacial Zn^(2+)distribution to accelerate electrodeposition kinetics by using the lithium niobate (LNO) layer.Specifically,at the bumps of the zinc anode,the ferroelectric LNO is polarized by the locally strong electric field,which in turn counteracts the"tip effect".In this way,the dynamic polarization of LNO can repair the uneven tip electric field to achieve uniform and flat zinc deposition.In addition,owing to the interaction between Nb and Zn^(2+),a higher concentration of Zn^(2+)near the zincophilic LNO@Zn surface is obtained for the rapid electrochemical reaction kinetics of plating.Considering the aforementioned advantages,the LNO@Zn anode harvests stable cycling over 1200 h at 10 mA cm^(-2)with a superior cumulative capacity of 5800 mAh cm^(-2).Assembled with the a-MnO_(2) cathode,the full cell using LNO@Zn anode exhibits the slower capacity decay (0.054%per cycle) during 1000 cycles.This strategy provides a perspective for stabilizing zinc metal anodes through dynamic electrical response and interfacial ion redistribution effect.展开更多
To derive critical signal features from intracranial electroencephalograms of epileptic patients in order to design instructions for feedback-type electrical stimulation systems.The Detrended Fluctuation Analysis(DFA)...To derive critical signal features from intracranial electroencephalograms of epileptic patients in order to design instructions for feedback-type electrical stimulation systems.The Detrended Fluctuation Analysis(DFA)exponent is chosen as the classification exponent,and the disparities between indicators representing distinct seizure states and the classification efficacy of rudimentary machine learning models are computed.The DFA exponent exhibited a statistically significant variation among the pre-ictal,ictal period,and post-ictal stages.The Linear Discriminant Analysis model demonstrates the highest accuracy among the three basic machine learning models,whereas the Naive Bayesian model necessitates the least amount of computational and storage space.The set of DFA exponents is employed as an intermediary variable in the machine learning process.The resultant model possesses the capability to function as a feedback trigger program for electrical stimulation systems of the feedback variety,specifically within the domain of neural modulation in epilepsy.展开更多
基金supported by the National Natural Science Foundation of China (52172159)the Postdoctoral Fellowship Program of CPSF (GZB20230631)。
文摘Aqueous zinc metal batteries (AZMBs) are hindered by uncontrolled dendrites and side reactions during commercialization,despite their advantages of safety and high capacity density.Herein,we propose the electrical feedback strategy to restrain the Zn dendrites resulting from the"tip effect"and optimize interfacial Zn^(2+)distribution to accelerate electrodeposition kinetics by using the lithium niobate (LNO) layer.Specifically,at the bumps of the zinc anode,the ferroelectric LNO is polarized by the locally strong electric field,which in turn counteracts the"tip effect".In this way,the dynamic polarization of LNO can repair the uneven tip electric field to achieve uniform and flat zinc deposition.In addition,owing to the interaction between Nb and Zn^(2+),a higher concentration of Zn^(2+)near the zincophilic LNO@Zn surface is obtained for the rapid electrochemical reaction kinetics of plating.Considering the aforementioned advantages,the LNO@Zn anode harvests stable cycling over 1200 h at 10 mA cm^(-2)with a superior cumulative capacity of 5800 mAh cm^(-2).Assembled with the a-MnO_(2) cathode,the full cell using LNO@Zn anode exhibits the slower capacity decay (0.054%per cycle) during 1000 cycles.This strategy provides a perspective for stabilizing zinc metal anodes through dynamic electrical response and interfacial ion redistribution effect.
基金funded with the Key Project of Beijing Municipal Commission of Science and Technology(Z221100007422016)the Joint Project of Beijing Natural Science Foundation(L222107)the Sailing Project of Beijing Hospitals Authority in Clinical Medicine Development(ZLRK202319).
文摘To derive critical signal features from intracranial electroencephalograms of epileptic patients in order to design instructions for feedback-type electrical stimulation systems.The Detrended Fluctuation Analysis(DFA)exponent is chosen as the classification exponent,and the disparities between indicators representing distinct seizure states and the classification efficacy of rudimentary machine learning models are computed.The DFA exponent exhibited a statistically significant variation among the pre-ictal,ictal period,and post-ictal stages.The Linear Discriminant Analysis model demonstrates the highest accuracy among the three basic machine learning models,whereas the Naive Bayesian model necessitates the least amount of computational and storage space.The set of DFA exponents is employed as an intermediary variable in the machine learning process.The resultant model possesses the capability to function as a feedback trigger program for electrical stimulation systems of the feedback variety,specifically within the domain of neural modulation in epilepsy.
