A mechanochemical method with SiO_(2)as the grinding aid was used to enhance the leaching efficiencies of Co and Li from spent lithium batteries(LIBs).Experiment results show that the optimal leaching efficiencies of ...A mechanochemical method with SiO_(2)as the grinding aid was used to enhance the leaching efficiencies of Co and Li from spent lithium batteries(LIBs).Experiment results show that the optimal leaching efficiencies of 94.91%for Co and 97.22%for Li were obtained under the parameters of SiO_(2)/LiCoO_(2)mass ratio of 1:1,grinding speed of 500 r/min and grinding time of 30 min in citric acid.Characterization results indicate that the surficial properties of LiCoO_(2)were changed after mechanochemical grinding treatment due to the newly generated surfaces on LiCoO_(2).Meanwhile,the incompletely coordinated atomic structure and defective lattice structure lead to the activation of LiCoO_(2).The reduction effect of carbon black on Co^(3+)under the action of mechanical forces increases its leaching efficiencies in the citric acid solution.The proposed process was found efficiently to recover Co and Li from LiCoO_(2).展开更多
An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image s...An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image segmentation.However,the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image segmentation.In this study,we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal powders.Firstly,an atrous convolution is introduced into our network to learn the image feature of multi-sized powders,which can reduce the missing segmentation of small-sized agglomerated particles.Then,a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge effect.The final comparative experimental results show that our method achieves the best results of 94.43%and 91.44%on AP50 and AP75 respectively among the comparison algorithms.In addition,in order to provide an effective method for particle size analysis of coal particles,we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.展开更多
Coal sludge slurry(CSS) is an alternative fuel and a potential competitive method for sludge reduction.Based on the researches of coal water slurry, we studied CSSs by using a wet-grinding process with different types...Coal sludge slurry(CSS) is an alternative fuel and a potential competitive method for sludge reduction.Based on the researches of coal water slurry, we studied CSSs by using a wet-grinding process with different types of regional municipal sludge(sludge) in an orthogonal experiment. The sludge type,sludge mixing proportion, dosage of dispersant, and grinding time were tested in this study. The results show that water content and its occurrence characteristics in the sludge have primary hindering influences on slurry ability. The range of fixed-viscosity concentrations with raw wet sludge is from 50.78%to 44.40%(by weight), while the range is from 53.35% to 51.51%(by weight) with dry sludge. All of the CSSs exhibit shear-thinning behaviors with different variation trends, especially the CSSs with more than 15%(by weight) raw wet sludge in it. Adding the same proportion of raw wet sludge increases the thixotropic properties of CSSs and the highest area of thixotropy loop is 3065 Pa/s, while the highest value of dry sludge is 1798 Pa/s. Hydrophilic group plays an important role in adsorbing water and building three-dimension networks with other particles, which is the main reason for CSS properties.Therefore, the mechanism can be used to find the way for making high quality CSS.展开更多
基金financially supported by the Key-Area Research and Development Program of Guangdong Province,China(No.2020B090919003)the National Natural Science Foundation of China(Nos.51574234,51904295)+2 种基金the Special Fund(Social Development)Project of Key Research and Development Plan of Jiangsu Province,China(No.BE2019634)the Science Foundation of Jiangsu Province,China(No.BK20180647)the Postdoctoral Science Foundation of China(No.2018M640538)。
文摘A mechanochemical method with SiO_(2)as the grinding aid was used to enhance the leaching efficiencies of Co and Li from spent lithium batteries(LIBs).Experiment results show that the optimal leaching efficiencies of 94.91%for Co and 97.22%for Li were obtained under the parameters of SiO_(2)/LiCoO_(2)mass ratio of 1:1,grinding speed of 500 r/min and grinding time of 30 min in citric acid.Characterization results indicate that the surficial properties of LiCoO_(2)were changed after mechanochemical grinding treatment due to the newly generated surfaces on LiCoO_(2).Meanwhile,the incompletely coordinated atomic structure and defective lattice structure lead to the activation of LiCoO_(2).The reduction effect of carbon black on Co^(3+)under the action of mechanical forces increases its leaching efficiencies in the citric acid solution.The proposed process was found efficiently to recover Co and Li from LiCoO_(2).
基金Supported by the Research and Development Project of Experimental Technology,China University of Mining and Technology(Study on mineral occurrence in coal based on SEM and EDS,S2023Y018)the National Natural Science Foundations of China under Grant 62371451.
文摘An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image segmentation.However,the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image segmentation.In this study,we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal powders.Firstly,an atrous convolution is introduced into our network to learn the image feature of multi-sized powders,which can reduce the missing segmentation of small-sized agglomerated particles.Then,a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge effect.The final comparative experimental results show that our method achieves the best results of 94.43%and 91.44%on AP50 and AP75 respectively among the comparison algorithms.In addition,in order to provide an effective method for particle size analysis of coal particles,we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.
基金supported by the National Natural Science Foundation of China (Nos. 51204179, 51204182)the Natural Science Foundation of Jiangsu Province of China (No. BK20141242)the Fundamental Research Funds for the Central Universities of China (No. 2014XT05)
文摘Coal sludge slurry(CSS) is an alternative fuel and a potential competitive method for sludge reduction.Based on the researches of coal water slurry, we studied CSSs by using a wet-grinding process with different types of regional municipal sludge(sludge) in an orthogonal experiment. The sludge type,sludge mixing proportion, dosage of dispersant, and grinding time were tested in this study. The results show that water content and its occurrence characteristics in the sludge have primary hindering influences on slurry ability. The range of fixed-viscosity concentrations with raw wet sludge is from 50.78%to 44.40%(by weight), while the range is from 53.35% to 51.51%(by weight) with dry sludge. All of the CSSs exhibit shear-thinning behaviors with different variation trends, especially the CSSs with more than 15%(by weight) raw wet sludge in it. Adding the same proportion of raw wet sludge increases the thixotropic properties of CSSs and the highest area of thixotropy loop is 3065 Pa/s, while the highest value of dry sludge is 1798 Pa/s. Hydrophilic group plays an important role in adsorbing water and building three-dimension networks with other particles, which is the main reason for CSS properties.Therefore, the mechanism can be used to find the way for making high quality CSS.
