Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-ind...Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.展开更多
In recent years,the new energy storage system,such as lithium ion batteries(LIBs),has attracted much attention.In order to meet the demand of industrial progress for longer cycle life,higher energy density and cost ef...In recent years,the new energy storage system,such as lithium ion batteries(LIBs),has attracted much attention.In order to meet the demand of industrial progress for longer cycle life,higher energy density and cost efficiency,a quantity of research has been conducted on the commercial application of LIBs.However,it is difficult to achieve satisfying safety and cycling performance simultaneously.There may be thermal runaway(TR),external impact,overcharge and overdischarge in the process of battery abuse,which makes the safety problem of LIBs more prominent.In this review,we summarize recent progress in the smart safety materials design towards the goal of preventing TR of LIBs reversibly from different abuse conditions.Benefiting from smart responsive materials and novel structural design,the safety of LIBs can be improved a lot.We expect to provide a comprehensive reference for the development of smart and safe lithium-based battery materials.展开更多
Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can a...Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.展开更多
Laser-induced breakdown spectroscopy(LIBS) is a promising analytical spectroscopy technology based on spectroscopic analysis of the radiation emitted by laser-produced plasma.However, for quantitative analysis by LIBS...Laser-induced breakdown spectroscopy(LIBS) is a promising analytical spectroscopy technology based on spectroscopic analysis of the radiation emitted by laser-produced plasma.However, for quantitative analysis by LIBS, the so-called self-absorption effects on the spectral lines, which affect plasma characteristics, emission line shapes, calibration curves, etc, can no longer be neglected. Hence, understanding and determining the self-absorption effects are of utmost importance to LIBS research. The purpose of this review is to provide a global overview of self-absorption in LIBS on the issues of experimental observations and adverse effects,physical mechanisms, correction or elimination approaches, and utilizations in the past century.We believe that better understanding and effective solving the self-absorption effect will further enhance the development and maturity of LIBS.展开更多
In the present work, we have studied the temporal evolution of aluminum alloy plasma produced by the fundamental (1064 nm) of a Q-switched Nd:YAG laser by placing the target material in air at atmospheric pressure. Th...In the present work, we have studied the temporal evolution of aluminum alloy plasma produced by the fundamental (1064 nm) of a Q-switched Nd:YAG laser by placing the target material in air at atmospheric pressure. The four Al I-neutral lines at 308.21, 309.27, 394.40 and 369.15 nm as well as Al II-ionic lines at 281.61, 385.64 and 466.30 nm are used for the determination of the electron temperature Te using Saha-Boltzmann plot method. The neutral aluminum lines were found to suffer from optical thickness which manifested itself on the form of scattered points around the Saha-Boltzmann line. The isolated optically thin hydrogen Hα-line at 656.27 nm appeared in the spectra under the same experimental conditions was used to correct the Al I-lines which contained some optical thickness. The measurements were repeated at different delay times ranging from 1 to 5 μs. The comparison between the deduced electron temperatures from aluminum neutral lines before correction against the effect self-absorption to that after correction revealed a precise value in temperature. The results sure that, in case of the presence of self-absorption effect the temperature varies from (1.4067 - 1.2548 eV) as the delay time is varied from 0 to 5 μs. Whereas, in the case of repairing against the effect, it varies from (1.2826 - 0.8961 eV) for the same delay time variation.展开更多
Coffee is one of the most consumed and commercialized crops in the world, which is why there is a potential risk to find arabica coffee (an expensive variety) adulterated with robusta coffee (a cheaper variety). The c...Coffee is one of the most consumed and commercialized crops in the world, which is why there is a potential risk to find arabica coffee (an expensive variety) adulterated with robusta coffee (a cheaper variety). The currently used technique for certifying coffee, High Performance Liquid Chromatography (HPLC), requires the sample to be subjected to a chemical treatment prior to analysis;in addition, the equipment is bulky and can not be moved easily. Laser Induced Breakdown Spectroscopy (LIBS) is a technique which does not require that samples be subjected to a chemical pretreatment, and equipment is small and portable, this can save valuable time in coffee trading. The purpose of this research was to demonstrate that LIBS can be applied to solve various problems related with the coffee authentication. Green coffee pills with different concentrations of arabica and robusta varieties were analyzed by LIBS, the results were used in the construction of calibration curves for the detection of the degree of simulated adulteration in coffee. It was found that the relative intensities of Ca (392.4 nm), Sr (407.1 nm), N (500.5 nm) and Na (588.7 nm), as well as the intensity ratios of Ca II (392.4 nm)/N I (500.5 nm), Sr I (407.1 nm)/N I (500.5 nm)and N I (500.5 nm)/Na I (588.7 nm) can be used for this purpose. It is concluded that the differentiation of coffee and the detection of its adulteration is possible with the use of LIBS. Further, with the use of an Artificial Neural Network (ANN) of type Multilayer Perceptron, it was possible to correctly classify the spectra of arabica and robusta roasted coffee.展开更多
Lithium,as the lightest and lowest potential metal,is an ideal "battery metal" and the core strategic metal of the new energy industry revolution.Recovering lithium from spent lithium batteries(LIBs)has beco...Lithium,as the lightest and lowest potential metal,is an ideal "battery metal" and the core strategic metal of the new energy industry revolution.Recovering lithium from spent lithium batteries(LIBs)has become one of the significant approaches to obtaining lithium resources.At present,the lithium extraction being generally placed at the last step of the spent LIBs recovery process has puzzles such as high acid consumption,low Li recovery purity and low recovery efficiency.Selective lithium extraction at the first step of the recovery process can effectively solve those puzzles.Since lithium leaching is a non-spontaneous reaction requiring additional energy to achieve,it is found that these methods can be divided into five ways according to the different types of energy driving the reaction occurring:(ⅰ)electric energy driving lithium extraction;(ⅱ) chemical energy driving lithium extraction;(ⅲ) mechanical energy driving lithium extraction;(ⅳ) thermal energy driving lithium extraction;(ⅴ) other energy driving lithium extraction.Through the analysis of the principle,reaction process and results of recovering lithium methods can provide a few directions for scholars’ subsequent research.It is necessary to speed up the exploration of the principle of these methods.It is expected that this study could provide a reference for the research on the selective lithium extraction.展开更多
Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superp...Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal uncertainty.By selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification performance.When applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,respectively.These results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.展开更多
To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the...To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the depletion of fossil fuels have become significant global problems.Lithium-ion batteries(LIBs)have been distinguished themselves from alternative energy storage technologies for electric vehicles(EVs) due to superior qualities like high energy and power density,extended cycle life,and low maintenance cost to a competitive price.However,there are still certain challenges to be solved,like EV fast charging,longer lifetime,and reduced weight.For fast charging,the multi-stage constant current(MSCC) charging technique is an emerging solution to improve charging efficiency,reduce temperature rise during charging,increase charging/discharging capacities,shorten charging time,and extend the cycle life.However,there are large variations in the implementation of the number of stages,stage transition criterion,and C-rate selection for each stage.This paper provides a review of these problems by compiling information from the literature.An overview of the impact of different design parameters(number of stages,stage transition,and C-rate) that the MSCC charging techniques have had on the LIB performance and cycle life is described in detail and analyzed.The impact of design parameters on lifetime,charging efficiency,charging and discharging capacity,charging speed,and rising temperature during charging is presented,and this review provides guidelines for designing advanced fast charging strategies and determining future research gaps.展开更多
The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is stil...The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.展开更多
基金financially supported by the National Key R&D Program Projects of China (No.2021YFB3202402)National Natural Science Foundation of China (No.62173321)。
文摘Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.
基金support by,National Key Research and Development Program(2023YFB2503700 and 2023YFC3008804)the Beijing Municipal Science&Technology Commission No.Z231100006123003+1 种基金the National Science Foundation of China(22071133)the Beijing Natural Science Foundation(No.Z220020).
文摘In recent years,the new energy storage system,such as lithium ion batteries(LIBs),has attracted much attention.In order to meet the demand of industrial progress for longer cycle life,higher energy density and cost efficiency,a quantity of research has been conducted on the commercial application of LIBs.However,it is difficult to achieve satisfying safety and cycling performance simultaneously.There may be thermal runaway(TR),external impact,overcharge and overdischarge in the process of battery abuse,which makes the safety problem of LIBs more prominent.In this review,we summarize recent progress in the smart safety materials design towards the goal of preventing TR of LIBs reversibly from different abuse conditions.Benefiting from smart responsive materials and novel structural design,the safety of LIBs can be improved a lot.We expect to provide a comprehensive reference for the development of smart and safe lithium-based battery materials.
基金financial supports from National Natural Science Foundation of China(No.62205172)Huaneng Group Science and Technology Research Project(No.HNKJ22-H105)Tsinghua University Initiative Scientific Research Program and the International Joint Mission on Climate Change and Carbon Neutrality。
文摘Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.
基金supported by National Key R&D Program of China (2017YFA0304203)Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China (IRT13076)+1 种基金National Natural Science Foundation of China (NSFC) (Nos. 61475093, 61875108, 61775125)Major Special Science and Technology Projects in Shanxi Province (MD2016-01)
文摘Laser-induced breakdown spectroscopy(LIBS) is a promising analytical spectroscopy technology based on spectroscopic analysis of the radiation emitted by laser-produced plasma.However, for quantitative analysis by LIBS, the so-called self-absorption effects on the spectral lines, which affect plasma characteristics, emission line shapes, calibration curves, etc, can no longer be neglected. Hence, understanding and determining the self-absorption effects are of utmost importance to LIBS research. The purpose of this review is to provide a global overview of self-absorption in LIBS on the issues of experimental observations and adverse effects,physical mechanisms, correction or elimination approaches, and utilizations in the past century.We believe that better understanding and effective solving the self-absorption effect will further enhance the development and maturity of LIBS.
文摘In the present work, we have studied the temporal evolution of aluminum alloy plasma produced by the fundamental (1064 nm) of a Q-switched Nd:YAG laser by placing the target material in air at atmospheric pressure. The four Al I-neutral lines at 308.21, 309.27, 394.40 and 369.15 nm as well as Al II-ionic lines at 281.61, 385.64 and 466.30 nm are used for the determination of the electron temperature Te using Saha-Boltzmann plot method. The neutral aluminum lines were found to suffer from optical thickness which manifested itself on the form of scattered points around the Saha-Boltzmann line. The isolated optically thin hydrogen Hα-line at 656.27 nm appeared in the spectra under the same experimental conditions was used to correct the Al I-lines which contained some optical thickness. The measurements were repeated at different delay times ranging from 1 to 5 μs. The comparison between the deduced electron temperatures from aluminum neutral lines before correction against the effect self-absorption to that after correction revealed a precise value in temperature. The results sure that, in case of the presence of self-absorption effect the temperature varies from (1.4067 - 1.2548 eV) as the delay time is varied from 0 to 5 μs. Whereas, in the case of repairing against the effect, it varies from (1.2826 - 0.8961 eV) for the same delay time variation.
文摘Coffee is one of the most consumed and commercialized crops in the world, which is why there is a potential risk to find arabica coffee (an expensive variety) adulterated with robusta coffee (a cheaper variety). The currently used technique for certifying coffee, High Performance Liquid Chromatography (HPLC), requires the sample to be subjected to a chemical treatment prior to analysis;in addition, the equipment is bulky and can not be moved easily. Laser Induced Breakdown Spectroscopy (LIBS) is a technique which does not require that samples be subjected to a chemical pretreatment, and equipment is small and portable, this can save valuable time in coffee trading. The purpose of this research was to demonstrate that LIBS can be applied to solve various problems related with the coffee authentication. Green coffee pills with different concentrations of arabica and robusta varieties were analyzed by LIBS, the results were used in the construction of calibration curves for the detection of the degree of simulated adulteration in coffee. It was found that the relative intensities of Ca (392.4 nm), Sr (407.1 nm), N (500.5 nm) and Na (588.7 nm), as well as the intensity ratios of Ca II (392.4 nm)/N I (500.5 nm), Sr I (407.1 nm)/N I (500.5 nm)and N I (500.5 nm)/Na I (588.7 nm) can be used for this purpose. It is concluded that the differentiation of coffee and the detection of its adulteration is possible with the use of LIBS. Further, with the use of an Artificial Neural Network (ANN) of type Multilayer Perceptron, it was possible to correctly classify the spectra of arabica and robusta roasted coffee.
基金financially supported by the National Key Research and Development Program of China(2019YFC1907900)the Key Project of Research and Development Plan of Jiangxi Province(20201BBE51007)the National Science Fund for Distinguished Young Scholars(52125002)。
文摘Lithium,as the lightest and lowest potential metal,is an ideal "battery metal" and the core strategic metal of the new energy industry revolution.Recovering lithium from spent lithium batteries(LIBs)has become one of the significant approaches to obtaining lithium resources.At present,the lithium extraction being generally placed at the last step of the spent LIBs recovery process has puzzles such as high acid consumption,low Li recovery purity and low recovery efficiency.Selective lithium extraction at the first step of the recovery process can effectively solve those puzzles.Since lithium leaching is a non-spontaneous reaction requiring additional energy to achieve,it is found that these methods can be divided into five ways according to the different types of energy driving the reaction occurring:(ⅰ)electric energy driving lithium extraction;(ⅱ) chemical energy driving lithium extraction;(ⅲ) mechanical energy driving lithium extraction;(ⅳ) thermal energy driving lithium extraction;(ⅴ) other energy driving lithium extraction.Through the analysis of the principle,reaction process and results of recovering lithium methods can provide a few directions for scholars’ subsequent research.It is necessary to speed up the exploration of the principle of these methods.It is expected that this study could provide a reference for the research on the selective lithium extraction.
基金financial support from the Scientific Research Program for Young Talents of China National Nuclear Corporation(2020)National Natural Science Foundation of China(Nos.51906124 and 62205172)+1 种基金Shanxi Province Science and Technology Department(No.20201101013)Guoneng Bengbu Power Generation Co.,Ltd(No.20212000001)。
文摘Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal uncertainty.By selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification performance.When applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,respectively.These results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.
文摘To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the depletion of fossil fuels have become significant global problems.Lithium-ion batteries(LIBs)have been distinguished themselves from alternative energy storage technologies for electric vehicles(EVs) due to superior qualities like high energy and power density,extended cycle life,and low maintenance cost to a competitive price.However,there are still certain challenges to be solved,like EV fast charging,longer lifetime,and reduced weight.For fast charging,the multi-stage constant current(MSCC) charging technique is an emerging solution to improve charging efficiency,reduce temperature rise during charging,increase charging/discharging capacities,shorten charging time,and extend the cycle life.However,there are large variations in the implementation of the number of stages,stage transition criterion,and C-rate selection for each stage.This paper provides a review of these problems by compiling information from the literature.An overview of the impact of different design parameters(number of stages,stage transition,and C-rate) that the MSCC charging techniques have had on the LIB performance and cycle life is described in detail and analyzed.The impact of design parameters on lifetime,charging efficiency,charging and discharging capacity,charging speed,and rising temperature during charging is presented,and this review provides guidelines for designing advanced fast charging strategies and determining future research gaps.
基金supported by the National Key Research and Development Program of China(No.2019YFD0901701)National Natural Science Foundation of China(Nos.12174359and 61975190)Provincial Key Research and Development Program of Shandong,China(No.2019GHZ010)。
文摘The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.