HARNESSING ADVANCED MATERIALS AND EXTRACTIVE METALLURGY FOR OPTIMIZING MINERAL AND ENERGY RESOURCE VALUE CHAINS

Rahadian  Nopriantoko

doi:10.30556/imj.Vol28.No2.2025.1641

Authors

Rahadian Nopriantoko PEP Bandung

DOI:

https://doi.org/10.30556/imj.Vol28.No2.2025.1641

Keywords:

advanced materials, extractive metallurgy, sustainability, mineral and energy, resource value chains

Abstract

This research examines recent advancements in advanced materials and extractive metallurgy for optimizing mineral and energy resource value chains. The study's purpose is to synthesize current research, emerging technologies, and future prospects in resource value chain optimization. The novelty lies in the comprehensive analysis of synergies between advanced materials, innovative extractive techniques, and cutting-edge technologies like AI and biotechnology. A systematic literature review methodology was employed, focusing on peer-reviewed papers from 2018 onwards, with data extracted and analyzed using standardized forms and qualitative software. Key findings include significant improvements in extraction efficiency and selectivity through nanostructured materials and high-performance membranes, with lab-scale efficiency increases of 50-70% translating to 20-30% in industrial settings. Bio-inspired techniques in extractive metallurgy have shown promise, reducing energy consumption by up to 40% in some processes. The integration of AI and machine learning has demonstrated potential for optimizing complex ore beneficiation, improving overall recovery rates. The study discusses challenges in scaling up laboratory innovations to industrial applications and the need to address hidden environmental costs of new technologies. Limitations include the exclusion of non-English studies and potential delays in reflecting very recent advancements. This review contributes to the field by offering insights for researchers, industry professionals, and policymakers to foster sustainable and efficient resource utilization practices, highlighting the transformative potential of integrating advanced materials, extractive metallurgy innovations, and emerging technologies in reshaping resource value chains.

References

Al-Attas, T.A., Ali, S.A., Zahir, M.H., Xiong, Q., Al-Bogami, S.A., Malaibari, Z.O., Razzak, S.A. and Hossain, M.M. (2019) ‘Recent advances in heavy oil upgrading using dispersed catalysts’, Energy & Fuels, 33(9), pp. 7917–7949. Available at: https://doi.org/10.1021/acs.energyfuels.9b01532.

Awan, U. (2020) ‘Industrial ecology in support of sustainable development goals’, in Responsible consumption and production. Springer, pp. 370–380. Available at: https://doi.org/10.1007/978-3-319-95726-5_18.

Bacelo, H., Pintor, A.M.A., Santos, S.C.R., Boaventura, R.A.R. and Botelho, C.M.S. (2020) ‘Performance and prospects of different adsorbents for phosphorus uptake and recovery from water’, Chemical Engineering Journal, 381, p. 122566. Available at: https://doi.org/10.1016/j.cej.2019.122566.

Badiuzzaman, M. and Rafiquzzaman, M. (2020) ‘Automation and robotics: A review of potential threat on unskilled and lower skilled labour unemployment in highly populated countries’, International Business Management, 14(1), pp. 16–24.

Bahrami, A., Schierning, G. and Nielsch, K. (2020) ‘Waste recycling in thermoelectric materials’, Advanced Energy Materials, 10(19), p. 1904159. Available at: https://doi.org/10.1002/aenm.201904159.

Batra, R., Song, L. and Ramprasad, R. (2020) ‘Emerging materials intelligence ecosystems propelled by machine learning’, Nature Reviews Materials, 6(8), pp. 655–678. Available at: https://doi.org/10.1038/s41578-020-00255-y.

Botte, G.G. (2014) ‘Electrochemical manufacturing in the chemical industry’, Interface magazine, 23(3), pp. 49–55. Available at: https://doi.org/10.1149/2.F04143if.

Chan, C.H., Sun, M. and Huang, B. (2022) ‘Application of machine learning for advanced material prediction and design’, EcoMat, 4(4), p. e12194. Available at: https://doi.org/10.1002/eom2.12194.

Chen, J., Tang, D., Zhong, S., Zhong, W. and Li, B. (2020) ‘The influence of micro-cracks on copper extraction by bioleaching’, Hydrometallurgy, 191, p. 105243. Available at: https://doi.org/10.1016/j.hydromet.2019.105243.

Council, N.R., Policy, Affairs, G., Education, B. on H., Earth, D. on, Studies, L., Sciences, B. on E. and Resources, C. on E. (2013) Emerging workforce trends in the U.S. energy and mining industries: A call to action. Washington, D.C.: National Academies Press. Available at: https://doi.org/10.17226/18250.

Dong, Z., Mattocks, J.A., Deblonde, G.J.-P., Hu, D., Jiao, Y., Cotruvo, J.A. and Park, D.M. (2021) ‘Bridging hydrometallurgy and biochemistry: A protein-based process for recovery and separation of rare earth elements’, ACS Central Science, 7(11), pp. 1798–1808. Available at: https://doi.org/10.1021/acscentsci.1c00724.

Fernández-Yáñez, P., Romero, V., Armas, O. and Cerretti, G. (2021) ‘Thermal management of thermoelectric generators for waste energy recovery’, Applied Thermal Engineering, 196, p. 117291. Available at: https://doi.org/10.1016/j.applthermaleng.2021.117291.

Galati, F. and Bigliardi, B. (2019) ‘Industry 4.0: Emerging themes and future research avenues using a text mining approach’, Computers in Industry, 109, pp. 100–113. Available at: https://doi.org/10.1016/j.compind.2019.04.018.

Ghassa, S., Farzanegan, A., Gharabaghi, M. and Abdollahi, H. (2020) ‘Novel bioleaching of waste lithium ion batteries by mixed moderate thermophilic microorganisms, using iron scrap as energy source and reducing agent’, Hydrometallurgy, 197, p. 105465. Available at: https://doi.org/10.1016/j.hydromet.2020.105465.

Gholami, A., Asgari, K., Khoshdast, H. and Hassanzadeh, A. (2022) ‘A hybrid geometallurgical study using coupled Historical Data (HD) and Deep Learning (DL) techniques on a copper ore mine’, Physicochemical Problems of Mineral Processing, 58(3). Available at: https://doi.org/10.37190/ppmp/147841.

Gideon Oluseyi Daramola, Boma Sonimiteim Jacks, Olakunle Abayomi Ajala and Abiodun Emmanuel Akinoso (2024) ‘AI applications in reservoir management: Optimizing production and recovery in oil and gas fields’, Computer Science & IT Research Journal, 5(4), pp. 972–984. Available at: https://doi.org/10.51594/csitrj.v5i4.1083.

Gkika, D.A., Mitropoulos, A.C. and Kyzas, G.Z. (2022) ‘Why reuse spent adsorbents? The latest challenges and limitations’, Science of The Total Environment, 822, p. 153612. Available at: https://doi.org/10.1016/j.scitotenv.2022.153612.

Gomes, C.P., Selman, B. and Gregoire, J.M. (2019) ‘Artificial intelligence for materials discovery’, MRS Bulletin, 44(7), pp. 538–544. Available at: https://doi.org/10.1557/mrs.2019.158.

Han, P., Teo, W.Z. and Yew, W.S. (2022) ‘Biologically engineered microbes for bioremediation of electronic waste: Wayposts, challenges and future directions’, Engineering Biology, 6(1), pp. 23–34. Available at: https://doi.org/10.1049/enb2.12020.

Hashemi, R., Nassar, N.N. and Pereira Almao, P. (2014) ‘Nanoparticle technology for heavy oil in-situ upgrading and recovery enhancement: Opportunities and challenges’, Applied Energy, 133, pp. 374–387. Available at: https://doi.org/10.1016/j.apenergy.2014.07.069.

Hu, Y., Florek, J., Larivière, D., Fontaine, F. and Kleitz, F. (2018) ‘Recent advances in the separation of rare earth elements using mesoporous hybrid materials’, The Chemical Record, 18(7–8), pp. 1261–1276. Available at: https://doi.org/10.1002/tcr.201800012.

Humphreys, D. (2015) The remaking of the mining industry. London: Palgrave Macmillan UK. Available at: https://doi.org/10.1057/9781137442017.

Jang, H. and Topal, E. (2020) ‘Transformation of the Australian mining industry and future prospects’, Mining Technology, 129(3), pp. 120–134. Available at: https://doi.org/10.1080/25726668.2020.1786298.

Kadulkar, S., Sherman, Z.M., Ganesan, V. and Truskett, T.M. (2022) ‘Machine learning–Assisted design of material properties’, Annual Review of Chemical and Biomolecular Engineering, 13(1), pp. 235–254. Available at: https://doi.org/10.1146/annurev-chembioeng-092220-024340.

Li, B., Wang, X., Wei, Y., Wang, H. and Barati, M. (2018) ‘Extraction of copper from copper and cadmium residues of zinc hydrometallurgy by oxidation acid leaching and cyclone electrowinning’, Minerals Engineering, 128, pp. 247–253. Available at: https://doi.org/10.1016/j.mineng.2018.09.007.

Mahandra, H., Faraji, F. and Ghahreman, A. (2021) ‘Novel extraction process for gold recovery from thiosulfate solution using phosphonium ionic liquids’, ACS Sustainable Chemistry & Engineering, 9(24), pp. 8179–8185. Available at: https://doi.org/10.1021/acssuschemeng.1c01705.

Mandelman, F.S. and Zlate, A. (2022) ‘Offshoring, automation, low-skilled immigration, and labor market polarization’, American Economic Journal: Macroeconomics, 14(1), pp. 355–389. Available at: https://doi.org/10.1257/mac.20180205.

Miriyala, S.S. and Mitra, K. (2020) ‘Deep learning based system identification of industrial integrated grinding circuits’, Powder Technology, 360, pp. 921–936. Available at: https://doi.org/10.1016/j.powtec.2019.10.065.

Nasaruddin, R.R., Chen, T., Yao, Q., Zang, S. and Xie, J. (2021) ‘Toward greener synthesis of gold nanomaterials: From biological to biomimetic synthesis’, Coordination Chemistry Reviews, 426, p. 213540. Available at: https://doi.org/10.1016/j.ccr.2020.213540.

Nopriantoko, R. (2024a) ‘Green approaches to extractive metallurgy: A novel synthesis of sustainable practices’, Metalurgi, 39(1), p. 37. Available at: https://doi.org/10.55981/metalurgi.2024.748.

Nopriantoko, R. (2024b) Rekayasa sistem termal dan energi. Edited by H. Wijayanti. Sukabumi: CV Jejak (Jejak Publisher).

Pan, Y., Liu, R., Luo, L., Song, Z., Pan, J. and Li, H. (2023) ‘Rapid and selective gold stripping from electronic waste with yolk–shell-structured ion-imprinted magnetic mesoporous nanorobots for efficient water decontamination’, ACS Sustainable Chemistry & Engineering, 11(40), pp. 14723–14733. Available at: https://doi.org/10.1021/acssuschemeng.3c02969.

Pyzer-Knapp, E.O., Pitera, J.W., Staar, P.W.J., Takeda, S., Laino, T., Sanders, D.P., Sexton, J., Smith, J.R. and Curioni, A. (2022) ‘Accelerating materials discovery using artificial intelligence, high performance computing and robotics’, npj Computational Materials, 8(1), p. 84. Available at: https://doi.org/10.1038/s41524-022-00765-z.

Ratvik, A.P., Mollaabbasi, R. and Alamdari, H. (2022) ‘Aluminium production process: from Hall–Héroult to modern smelters’, ChemTexts, 8(2), p. 10. Available at: https://doi.org/10.1007/s40828-022-00162-5.

Schippers, A., Hedrich, S., Vasters, J., Drobe, M., Sand, W. and Willscher, S. (2013) ‘Biomining: Metal Recovery from Ores with Microorganisms’, in A. Schippers, F. Glombitza, and W. Sand (eds) Geobiotechnology I (Metal-related Issues). Advances i. Berlin Heidelberg: Springer Berlin Heidelberg, pp. 1–47. Available at: https://doi.org/10.1007/10_2013_216.

Tan, Q., Li, J. and Zeng, X. (2015) ‘Rare earth elements recovery from waste fluorescent lamps: A Review’, Critical Reviews in Environmental Science and Technology, 45(7), pp. 749–776. Available at: https://doi.org/10.1080/10643389.2014.900240.

Wang, S., Yang, L., He, G., Shi, B., Li, Y., Wu, H., Zhang, R., Nunes, S. and Jiang, Z. (2020) ‘Two-dimensional nanochannel membranes for molecular and ionic separations’, Chemical Society Reviews, 49(4), pp. 1071–1089. Available at: https://doi.org/10.1039/C9CS00751B.

Xiong, Z., Cui, Y., Liu, Z., Zhao, Y., Hu, M. and Hu, J. (2020) ‘Evaluating explorative prediction power of machine learning algorithms for materials discovery using k-fold forward cross-validation’, Computational Materials Science, 171, p. 109203. Available at: https://doi.org/10.1016/j.commatsci.2019.109203.

Zhao, F., Liu, Y., Lu, N., Xu, T., Zhu, G. and Wang, K. (2021) ‘A review on upgrading and viscosity reduction of heavy oil and bitumen by underground catalytic cracking’, Energy Reports, 7, pp. 4249–4272. Available at: https://doi.org/10.1016/j.egyr.2021.06.094.

Zhao, Y., Wu, M., Guo, Y., Mamrol, N., Yang, X., Gao, C. and Van der Bruggen, B. (2021) ‘Metal-organic framework based membranes for selective separation of target ions’, Journal of Membrane Science, 634, p. 119407. Available at: https://doi.org/10.1016/j.memsci.2021.119407.

Zhironkina, O. and Zhironkin, S. (2023) ‘Technological and intellectual transition to mining 4.0: A review’, Energies, 16(3), p. 1427. Available at: https://doi.org/10.3390/en16031427.

Zhu, J., Hou, J., Uliana, A., Zhang, Y., Tian, M. and Van der Bruggen, B. (2018) ‘The rapid emergence of two-dimensional nanomaterials for high-performance separation membranes’, Journal of Materials Chemistry A, 6(9), pp. 3773–3792. Available at: https://doi.org/10.1039/C7TA10814A.

Zwart, S. and Baker, M. (2018) Improving productivity and job quality of low-skilled workers in the United Kingdom. OECD. Available at: https://doi.org/10.1787/14dfd584-en.