Submicron scale temperature sensors are crucial for a range of applications,particularly in micro and na-noscale environments.One promising solution involves the use of active whispering gallery mode(WGM)microresonato...Submicron scale temperature sensors are crucial for a range of applications,particularly in micro and na-noscale environments.One promising solution involves the use of active whispering gallery mode(WGM)microresonators.These resonators can be remotely excited and read out using free-space structures,simplifying the process of sensing.In this study,we present a submicron-scale temperature sensor with a remarkable sensitivity up to 185 pm/℃based on a trian-gular MAPbI3 nanoplatelet(NPL)laser.Notably,as temperature changes,the peak wavelength of the laser line shifts lin-early.This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser.The optical modes are confined within the perovskite NPL,which measures just 85 nm in height,due to total internal reflec-tion.Our NPL laser boasts several key features,including a high Q of~2610 and a low laser threshold of about 19.8μJ·cm^(−2).The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors.This advancement paves the way for significant prog-ress in the development of ultrasmall temperature sensors,opening new possibilities across various fields.展开更多
Rechargeable magnesium batteries(RMBs),as one of the most promising candidates for efficient energy storage devices with high energy,power density and high safety,have attracted increasing attention.However,searching ...Rechargeable magnesium batteries(RMBs),as one of the most promising candidates for efficient energy storage devices with high energy,power density and high safety,have attracted increasing attention.However,searching for suitable cathode materials with fast diffusion kinetics and exploring their magnesium storage mechanisms remains a great challenge.Cu S submicron spheres,made by a facile low-temperature synthesis strategy,were applied as the high-performance cathode for RMBs in this work,which can deliver a high specific capacity of 396mAh g^(-1)at 20 mA g^(-1) and a remarkable rate capacity of 250 m Ah g^(-1)at 1000 mA g^(-1).The excellent rate performance can be assigned to the nano needle-like particles on the surface of Cu S submicron spheres,which can facilitate the diffusion kinetics of Mg^(2+).Further storage mechanism investigations illustrate that the Cu S cathodes experience a two-step conversion reaction controlled by diffusion during the electrochemical reaction process.This work could make a contribution to the study of the enhancement of diffusion kinetics of Mg2+and the reaction mechanism of RMBs.展开更多
With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order ...With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network(ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model(PTM) nominal parameters has been done to compare with ANN(trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.展开更多
Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to ...Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.展开更多
文摘Submicron scale temperature sensors are crucial for a range of applications,particularly in micro and na-noscale environments.One promising solution involves the use of active whispering gallery mode(WGM)microresonators.These resonators can be remotely excited and read out using free-space structures,simplifying the process of sensing.In this study,we present a submicron-scale temperature sensor with a remarkable sensitivity up to 185 pm/℃based on a trian-gular MAPbI3 nanoplatelet(NPL)laser.Notably,as temperature changes,the peak wavelength of the laser line shifts lin-early.This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser.The optical modes are confined within the perovskite NPL,which measures just 85 nm in height,due to total internal reflec-tion.Our NPL laser boasts several key features,including a high Q of~2610 and a low laser threshold of about 19.8μJ·cm^(−2).The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors.This advancement paves the way for significant prog-ress in the development of ultrasmall temperature sensors,opening new possibilities across various fields.
基金the support from the Fundamental Research Funds for the Central Universities of Chongqing University(No.2020CDCGCL005)。
文摘Rechargeable magnesium batteries(RMBs),as one of the most promising candidates for efficient energy storage devices with high energy,power density and high safety,have attracted increasing attention.However,searching for suitable cathode materials with fast diffusion kinetics and exploring their magnesium storage mechanisms remains a great challenge.Cu S submicron spheres,made by a facile low-temperature synthesis strategy,were applied as the high-performance cathode for RMBs in this work,which can deliver a high specific capacity of 396mAh g^(-1)at 20 mA g^(-1) and a remarkable rate capacity of 250 m Ah g^(-1)at 1000 mA g^(-1).The excellent rate performance can be assigned to the nano needle-like particles on the surface of Cu S submicron spheres,which can facilitate the diffusion kinetics of Mg^(2+).Further storage mechanism investigations illustrate that the Cu S cathodes experience a two-step conversion reaction controlled by diffusion during the electrochemical reaction process.This work could make a contribution to the study of the enhancement of diffusion kinetics of Mg2+and the reaction mechanism of RMBs.
文摘With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network(ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model(PTM) nominal parameters has been done to compare with ANN(trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.
文摘Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.
