Extensively explored for their distinctive pseudocapacitance characteristics,MXenes,a distinguished group of 2D materials,have led to remarkable achievements,particularly in the realm of energy storage devices.This wo...Extensively explored for their distinctive pseudocapacitance characteristics,MXenes,a distinguished group of 2D materials,have led to remarkable achievements,particularly in the realm of energy storage devices.This work presents an innovative Pseudocapacitive Sensor.The key lies in switching the energy storage kinetics from pseudocapacitor to electrical double layer capacitor by employing the change of local pH(-log[H^(+)])in MXene-based flexible supercapacitors during bending.Pseudocapacitive sensing is observed in acidic electrolyte but absent in neutral electrolyte.Applied shearing during bending causes liquid-crystalline MXene sheets to increase in their degree of anisotropic alignment.With blocking of H+mobility due to the higher diffusion barrier,local pH increases.The electrochemical energy storage kinetics transits from Faradaic chemical protonation(intercalation)to non-Faradaic physical adsorption.We utilize the phenomenon of capacitance change due to shifting energy storage kinetics for strain sensing purposes.The developed highly sensitive Pseudocapacitive Sensors feature a remarkable gauge factor(GF)of approximately 1200,far surpassing conventional strain sensors(GF:~1 for dielectric-cap sensor).The introduction of the Pseudocapacitive Sensor represents a paradigm shift,expanding the application of pseudocapacitance from being solely confined to energy devices to the realm of multifunctional electronics.This technological leap enriches our understanding of the pseudocapacitance mechanism of MXenes,and will drive innovation in cutting-edge technology areas,including advanced robotics,implantable biomedical devices,and health monitoring systems.展开更多
The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quali...The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality forecasting.Meteorological data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the CCMM.In this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean Peninsula.The nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological DA.When the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner domain.This indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological predictions.Compared to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with DA.The effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the case.Therefore,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.展开更多
基金supported by NRF-2021M3H4A1A03047333 and NRF-2022R1F1A1075084 of the National Research Foundation(NRF)of Korea funded by the Ministry of Science and ICT,Koreasupported by Semiconductor-Secondary Battery Interfacing Platform Technology Development Project of NNFC.
文摘Extensively explored for their distinctive pseudocapacitance characteristics,MXenes,a distinguished group of 2D materials,have led to remarkable achievements,particularly in the realm of energy storage devices.This work presents an innovative Pseudocapacitive Sensor.The key lies in switching the energy storage kinetics from pseudocapacitor to electrical double layer capacitor by employing the change of local pH(-log[H^(+)])in MXene-based flexible supercapacitors during bending.Pseudocapacitive sensing is observed in acidic electrolyte but absent in neutral electrolyte.Applied shearing during bending causes liquid-crystalline MXene sheets to increase in their degree of anisotropic alignment.With blocking of H+mobility due to the higher diffusion barrier,local pH increases.The electrochemical energy storage kinetics transits from Faradaic chemical protonation(intercalation)to non-Faradaic physical adsorption.We utilize the phenomenon of capacitance change due to shifting energy storage kinetics for strain sensing purposes.The developed highly sensitive Pseudocapacitive Sensors feature a remarkable gauge factor(GF)of approximately 1200,far surpassing conventional strain sensors(GF:~1 for dielectric-cap sensor).The introduction of the Pseudocapacitive Sensor represents a paradigm shift,expanding the application of pseudocapacitance from being solely confined to energy devices to the realm of multifunctional electronics.This technological leap enriches our understanding of the pseudocapacitance mechanism of MXenes,and will drive innovation in cutting-edge technology areas,including advanced robotics,implantable biomedical devices,and health monitoring systems.
基金Supported by the National Research Foundation of Korea(2021R1A2C1012572)funded by the South Korean government(Ministry of Science and ICT)Yonsei Signature Research Cluster Program of 2023(2023-22-0009)National Institute of Environmental Research(NIER-2022-01-02-076)funded by the Ministry of Environment(MOE)of the Republic of Korea。
文摘The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality forecasting.Meteorological data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the CCMM.In this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean Peninsula.The nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological DA.When the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner domain.This indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological predictions.Compared to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with DA.The effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the case.Therefore,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.
