A reasonable classification of deposits holds great significance for identifying prospecting targets and deploying exploration. The world ’s keen demand for lithium resources has expedited the discovery of numerous n...A reasonable classification of deposits holds great significance for identifying prospecting targets and deploying exploration. The world ’s keen demand for lithium resources has expedited the discovery of numerous novel lithium resources. Given the presence of varied classification criteria for lithium resources presently, this study further ascertained and classified the lithium resources according to their occurrence modes, obtaining 10 types and 5 subtypes of lithium deposits(resources) based on endogenetic and exogenetic factors. As indicated by surveys of Cenozoic exogenetic lithium deposits in China and abroad,the formation and distribution of the deposits are primarily determined by plate collision zones, their primary material sources are linked to the anatectic magmas in the deep oceanic crust, and they were formed primarily during the Miocene and Late Paleogene. The researchers ascertained that these deposits,especially those of the salt lake, geothermal, and volcanic deposit types, are formed by unique slightly acidic magmas, tend to migrate and accumulate toward low-lying areas, and display supernormal enrichment. However, the material sources of lithium deposits(resources) of the Neopaleozoic clay subtype and the deep brine type are yet to be further identified. Given the various types and complex origins of lithium deposits(resources), which were formed due to the interactions of multiple spheres, it is recommended that the mineralization of exogenetic lithium deposits(resources) be investigated by integrating tectono-geochemistry, paleoatmospheric circulation, and salinology. So far, industrialized lithium extraction is primarily achieved in lithium deposits of the salt lake, clay, and hard rock types. The lithium extraction employs different processes, with lithium extraction from salt lake-type lithium deposits proving the most energy-saving and cost-effective.展开更多
The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application Th...The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application This is because the model requires a strong correlation between the system characteristic sequences That reduces the applicability of the model.To solve this problem,this paper proposes a novel multi-variate grey model.This model does not require a certain correlation between system characteristic sequences and has higher applicability Through numerical integration,a two-point trapezoidal formula,and a recursive method,thetime-response expressions ofthetwo model forms are obtained Some properties of the proposed model are further discussed Finally,the validity of the proposed model is evaluated by using two real cases related to China's invention patent development.Theresultsshow that the novel models outperformother models inbothsimulation and prediction applications.展开更多
基金funded by the major research program of the of National Natural Science Foundation of China entitled Metallogenic Mechanisms and Regularity of the Lithium Ore Concentration Area in the Zabuye Salt Lake, Tibet (91962219)Science and Technology Major Project of the Tibet Autonomous Region ’s Science and Techonlogy Plan (XZ202201ZD0004G01)a geological survey project of China Geological Survey (DD20230037)。
文摘A reasonable classification of deposits holds great significance for identifying prospecting targets and deploying exploration. The world ’s keen demand for lithium resources has expedited the discovery of numerous novel lithium resources. Given the presence of varied classification criteria for lithium resources presently, this study further ascertained and classified the lithium resources according to their occurrence modes, obtaining 10 types and 5 subtypes of lithium deposits(resources) based on endogenetic and exogenetic factors. As indicated by surveys of Cenozoic exogenetic lithium deposits in China and abroad,the formation and distribution of the deposits are primarily determined by plate collision zones, their primary material sources are linked to the anatectic magmas in the deep oceanic crust, and they were formed primarily during the Miocene and Late Paleogene. The researchers ascertained that these deposits,especially those of the salt lake, geothermal, and volcanic deposit types, are formed by unique slightly acidic magmas, tend to migrate and accumulate toward low-lying areas, and display supernormal enrichment. However, the material sources of lithium deposits(resources) of the Neopaleozoic clay subtype and the deep brine type are yet to be further identified. Given the various types and complex origins of lithium deposits(resources), which were formed due to the interactions of multiple spheres, it is recommended that the mineralization of exogenetic lithium deposits(resources) be investigated by integrating tectono-geochemistry, paleoatmospheric circulation, and salinology. So far, industrialized lithium extraction is primarily achieved in lithium deposits of the salt lake, clay, and hard rock types. The lithium extraction employs different processes, with lithium extraction from salt lake-type lithium deposits proving the most energy-saving and cost-effective.
基金Supported bythe National Natural Science Foundation of China(71701105)the Major Program of the National Social Science Fund of China(17ZDA092)+1 种基金the Key Research Project of Philosophy and Social Sciences in Universities of Jiangsu Province(2018SJZDI111)Key Projects of Open Topics of Jiangsu Productivity Society in2020(JSSCL2020A004)。
文摘The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application This is because the model requires a strong correlation between the system characteristic sequences That reduces the applicability of the model.To solve this problem,this paper proposes a novel multi-variate grey model.This model does not require a certain correlation between system characteristic sequences and has higher applicability Through numerical integration,a two-point trapezoidal formula,and a recursive method,thetime-response expressions ofthetwo model forms are obtained Some properties of the proposed model are further discussed Finally,the validity of the proposed model is evaluated by using two real cases related to China's invention patent development.Theresultsshow that the novel models outperformother models inbothsimulation and prediction applications.
