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Tan, K., Li, C., Liu, J., Qu, H., Xia, L., Hu, Y., et al. (2014). A novel method using a complex surfactant for in-situ leaching of low permeable sandstone uranium deposits. Hydrometallurgy, 150, 99–106.
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Hu, K., Wang, Q., Tao, G., Wang, A., & Ding, D. (2011). Experimental Study on Restoration of Polluted Groundwater from in Situ Leaching Uranium Mining with Sulfate Reducing Bacteria and ZVI-SRB. Procedia Earth and Planetary Science, 2, 150–155.
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Shayakhmetov, N. M., Alibayeva, K. A., Kaltayev, A., & Panfilov, I. (2023). Enhancing uranium in-situ leaching efficiency through the well reverse technique: A study of the effects of reversal time on production efficiency and cost. Hydrometallurgy, 219, 106086.
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Pastukhov, A. M., Rychkov, V. N., Smirnov, A. L., Skripchenko, S. Y., & Poponin, N. A. (2014). Purification of in situ leaching solution for uranium mining by removing solids from suspension. Minerals Engineering, 55, 1–4.
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Zhou, Y., Li, G., Xu, L., Liu, J., Sun, Z., & Shi, W. (2020). Uranium recovery from sandstone-type uranium deposit by acid in-situ leaching – an example from the Kujieertai. Hydrometallurgy, 191, 105209.
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YI, Z. -ji, LIAN, B., YANG, Y. -qun, & ZOU, J. -ling. (2009). Treatment of simulated wastewater from in situ leaching uranium mining by zerovalent iron and sulfate reducing bacteria. Transactions of Nonferrous Metals Society of China, 19, 840.
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Qiu, W., Yang, Y., Song, J., Que, W., Liu, Z., Weng, H., et al. (2023). What chemical reaction dominates the CO2 and O2 in-situ uranium leaching?: Insights from a three-dimensional multicomponent reactive transport model at the field scale. Applied Geochemistry, 148, 105522.
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Haque, N., & Norgate, T. (2014). The greenhouse gas footprint of in-situ leaching of uranium, gold and copper in Australia. Journal of Cleaner Production, 84, 382–390.
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Jana, A., Unni, A., Ravuru, S. S., Das, A., Das, D., Biswas, S., et al. (2022). In-situ polymerization into the basal spacing of LDH for selective and enhanced uranium adsorption: A case study with real life uranium alkaline leach liquor. Chemical Engineering Journal, 428, 131180.
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Wang, B., Luo, Y., Qian, J. -zhong, Liu, J. -hui, Li, X., Zhang, Y. -hong, et al. (2023). Machine learning–based optimal design of the in-situ leaching process parameter (ISLPP) for the acid in-situ leaching of uranium. Journal of Hydrology, 626, 130234.
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