拣-浮联合的煤系战略性金属全粒级分选预富集装备与工艺数据集

煤系战略性金属普遍存在丰度低、分布离散、嵌布关系复杂等特征，已超出现有常规物理分选技术的处理能力。针对上述难题，项目开展了富镓锂煤矸石中金属赋存相的识别特征与分选响应机制研究，构建并实现了高适配性的分选工艺与装备系统，赋存相回收率达到60%以上，显著提升了煤系金属的资源利用率，同时有效降低了后续富集提取环节的能耗与成本，提升了工艺流程整体的技术经济性，相关成果处于国际领先水平。数据集围绕煤系战略性金属拣选—浮选联合分选与预富集过程中的装备设计与工艺试验开展，系统汇集了以镓、锂等为代表的煤系战略性金属分选预富集过程中形成的关键数据资源，主要包括：分选装备的结构设计资料与实物图片、分选工艺试验数据、原矿、精矿与尾矿的元素含量及赋存相检测数据以及相关论文及专利成果等支撑性资料。数据采集时间为2022年6月至2025年6月，采集地点包括中国矿业大学实验室及沈阳隆基电磁科技股份有限公司等试验基地。数据集中涉及的原矿、精矿与尾矿样品由中国矿业大学研制的XRT–XRF智能融合拣选装备及超级浮选机产生，产品元素含量及赋存相检测数据通过电感耦合等离子体质谱分析（ICP-MS）和全岩黏土矿物分析等方法获取。所有测试过程均严格遵循相关测试规范与操作流程，数据真实可靠、可重复性良好。本数据集总体数据量为 143 MB。Strategic metal resources in coal measures are characterized by low abundance, scattered distribution and complex embedding relationships, which surpass the processing capacity of current conventional physical separation technologies. In response to these challenges, this project conducted research on the identification characteristics of occurrence phases and separation response mechanism of metals in Ga- and Li-rich coal gangue, developed and implemented a highly adaptable separation process and equipment system. The recovery rate of occurrence phases exceeded 60%, significantly boosting the resource utilization efficiency of strategic metals in coal measures, effectively cutting down the energy consumption and costs in subsequent enrichment and extraction stages, and improving the overall techno-economic performance of the entire separation process. The relevant achievements have reached the internationally leading level. This dataset centers on equipment design and process tests for the combined sorting-flotation separation and pre-enrichment process of strategic metals in coal measures. It systematically compiles key data resources generated during the sorting and pre-enrichment of strategic metals in coal measures, with Ga, Li and other elements as typical representatives, mainly including: structural design documents and physical images of separation equipment, separation process test data, element content and occurrence phase detection data of raw ore, concentrate and tailings, as well as supporting materials such as relevant papers and patent achievements. The data was collected between June 2022 and June 2025, with collection sites including laboratories of the China University of Mining and Technology and test bases such as Shenyang Longji Electromagnetic Technology Co., Ltd. The raw ore, concentrate and tailings samples included in this dataset were produced by the XRT-XRF intelligent integrated sorting equipment and super flotation machine developed by the China University of Mining and Technology. The element content and occurrence phase detection data of the products were acquired via methods including Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and whole-rock clay mineral analysis. All test procedures strictly comply with relevant test specifications and operating protocols, ensuring that the data is authentic, reliable and exhibits excellent repeatability. The total data volume of this dataset is 143 MB.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于煤系战略性金属（如镓、锂）的拣选-浮选联合分选预富集工艺与装备，旨在解决金属丰度低、分布离散等难题，提升资源利用率并降低能耗成本。数据集包含装备设计资料、工艺试验数据、元素含量及赋存相检测数据等关键资源，采集于2022年至2025年间的实验室和试验基地，数据真实可靠。