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Volume 30
Issue 22
10.3390/molecules30224396
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Nitric Acid Leaching for Magnesium Extraction from Asbestos Ore Waste: From DoE to Predictive Modeling and Cost-Efficient Optimization

by
Nikolay S. Ivanov
1,*,
Oleg S. Kholkin
1,
Arlan Z. Abilmagzhanov
1,
Iskander E. Adelbayev
1,
Sergey K. Oparin
1,
Nataliya Ivanova
1 and
Vladislav Kudryashov
1,2,*
1
Laboratory of Applied Research, D.V. Sokolskiy Institute of Fuel, Catalysis and Electrochemistry JSC, Almaty 050010, Kazakhstan
2
Renewable Energy Lab, National Laboratory Astana, Nazarbayev University, Astana 010000, Kazakhstan
*
Authors to whom correspondence should be addressed.
Molecules 2025, 30(22), 4396; https://doi.org/10.3390/molecules30224396 (registering DOI)
Submission received: 26 September 2025 / Revised: 11 November 2025 / Accepted: 12 November 2025 / Published: 13 November 2025
Review Reports Versions Notes

Abstract

Kazakhstan’s asbestos industry produces over 3 million tons of waste annually. The primary component of asbestos ore waste (AOW) is magnesium rich minerals. In this study, the extraction of magnesium from AOW with nitric acid (HNO3) was for the first time systematically studied. A series of experiments were conducted to optimize acid concentration (300–600 g/L), leaching temperature (55–95 °C), leaching time (60–180 min), solid-to-liquid ratio (1:3–1:7), and particle size, with the overall goal of maximizing magnesium extraction and cost efficiency. Our results provide dependence of magnesium extraction in the order of acid concentration  >  temperature  >  time  >  solid-to-liquid ratio, while particle size was found to be negligible. The cost-efficiency optimization demonstrated the positive impact of the relatively low acid concentrations (< 450 g/L) and temperatures between 65 and 85 °C, while the Protodyakonov model validated a linear dependence of the extraction rate on temperature and acid concentration. Our model demonstrates that extraction efficiencies of up to 90% can be achieved while reducing reagent use and lowering the overall cost of magnesium production. Leaching of magnesium by HNO3 also opens a pathway to a closed-cycle process, due to the formation of magnesium nitrate. The thermal decomposition of Mg(NO3)2 provides valuable products such as MgO and NO2 reused in HNO3 regeneration for subsequent cycles. The proposed model predicts magnesium extraction from asbestos ore depending on leaching parameters with reasonable accuracy.
Keywords: asbestos; leaching; mathematical planning; magnesium oxide; ecology; modeling; cost-efficiency optimization asbestos; leaching; mathematical planning; magnesium oxide; ecology; modeling; cost-efficiency optimization

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MDPI and ACS Style

Ivanov, N.S.; Kholkin, O.S.; Abilmagzhanov, A.Z.; Adelbayev, I.E.; Oparin, S.K.; Ivanova, N.; Kudryashov, V. Nitric Acid Leaching for Magnesium Extraction from Asbestos Ore Waste: From DoE to Predictive Modeling and Cost-Efficient Optimization. Molecules 2025, 30, 4396. https://doi.org/10.3390/molecules30224396

AMA Style

Ivanov NS, Kholkin OS, Abilmagzhanov AZ, Adelbayev IE, Oparin SK, Ivanova N, Kudryashov V. Nitric Acid Leaching for Magnesium Extraction from Asbestos Ore Waste: From DoE to Predictive Modeling and Cost-Efficient Optimization. Molecules. 2025; 30(22):4396. https://doi.org/10.3390/molecules30224396

Chicago/Turabian Style

Ivanov, Nikolay S., Oleg S. Kholkin, Arlan Z. Abilmagzhanov, Iskander E. Adelbayev, Sergey K. Oparin, Nataliya Ivanova, and Vladislav Kudryashov. 2025. "Nitric Acid Leaching for Magnesium Extraction from Asbestos Ore Waste: From DoE to Predictive Modeling and Cost-Efficient Optimization" Molecules 30, no. 22: 4396. https://doi.org/10.3390/molecules30224396

APA Style

Ivanov, N. S., Kholkin, O. S., Abilmagzhanov, A. Z., Adelbayev, I. E., Oparin, S. K., Ivanova, N., & Kudryashov, V. (2025). Nitric Acid Leaching for Magnesium Extraction from Asbestos Ore Waste: From DoE to Predictive Modeling and Cost-Efficient Optimization. Molecules, 30(22), 4396. https://doi.org/10.3390/molecules30224396

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