Machine-Learning-Based Mapping and Ranking of Energy Materials in African Economies
Keywords:
Artificial Neural Networks (ANNs), Energy Materials, Critical Minerals, Africa, Machine Learning, Clean Energy Transition, Sustainable Resource Development
Abstract
The global transition toward clean energy and advanced technologies has led to a rapid increase in demand for critical energy materials, including cobalt, lithium, rare earth elements, and platinum group metals. Although Africa possesses a significant share of these strategic minerals, the continent remains underrepresented in structured, data-driven mineral mapping initiatives. This research introduces a machine-learning framework based on artificial neural networks (ANNs) to predict and prioritize the likelihood of energy material occurrences across African nations. As demonstrated in a 2023 Nature Communications article, machine learning frameworks can map infrastructure such as distribution grids using publicly available multi-modal data, including street view images, road networks, and building maps. The results of this study confirm established mineral hubs, such as the Democratic Republic of Congo and South Africa, while also highlighting underexplored regions with substantial hidden potential. By addressing a critical data and strategy gap, this work provides a reproducible and scalable approach to resource intelligence, offering practical benefits for investors, policymakers, and researchers aiming to align African mineral development with the global energy transition.
References
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34. Nkulu, C. B. L., Casas, L., Haufroid, V., et al. (2018). Sustainability of artisanal mining of cobalt in DR Congo. Nature Sustainability, 1(9), 495–504. DOI: 10.1038/s41893-018-0139-4
35. Frenzel, M., Kullik, J., Reuter, M. A., & Gutzmer, J. (2017). Raw material “criticality” – sense or nonsense? Journal of Physics D: Applied Physics, 50(12), 123002. DOI: 10.1088/1361-6463/aa5b64
36. Olivetti, E. A., Ceder, G., Gaustad, G. G., & Fu, X. (2018). Lithium-ion battery supply chain considerations: Analysis of potential bottlenecks in critical metals. Joule, 2(8), 1488–1501. DOI: 10.1016/j.joule.2018.05.008
2. Nakanwagi, S. (2023). Critical Minerals and the Global Energy Transition: Recognising Global South Perspectives. Global Energy Law and Sustainability, 4(1–2), 115–137. DOI: 10.3366/gels 2023.0096
3. Khan, K. A., Blueschke, D., Subhan, M., Çoban, M. N., Abbas, S., & Nassani, A. A. (2025). Does critical mineral dominance influence inclusive and sustainable development in the Global South? Evidence from quantile and machine learning methods. International Journal of Sustainable Development & World Ecology. DOI: 10.1080/13504509.2025.2590755
4. Pedro, A. M. A. (2021). Critical materials and sustainable development in Africa: Antonio M.A. Pedro (Q&A). One Earth, 4(3), 346–349. DOI: 10.1016/j.oneear.2021.02.018
5. Maduabuchi, C., Nsude, C., Eneh, C., Eke, E., Okoli, K., Okpara, E., ... & Harsito, C. (2023). Renewable energy potential estimation using climatic-weather-forecasting machine learning algorithms. Energies, 16(4), 1603. https://doi.org/10.3390/en16041603
6. Arrobas, D. L., Hund, K. L., McCormick, M. S., Ningthoujam, J., & Drexhage, J. R. (2017). The growing role of minerals and metals for a low-carbon future. World Bank Report. DOI: 10.1596/28312
7. Goodenough, K. M., Shaw, R. A., Deady, E. A., et al. (2025). Lithium pegmatites in Africa: A review. Economic Geology, 120(3), 513–539. DOI: 10.5382/econgeo 5133
8. Li, J., Sun, H., Lu, Y., Tong, X., Wu, X., & Zhou, Z. (2025). A review of rare earth elements resources in Africa. Minerals, 15(9), 980. DOI: 10.3390/min15090980
9. Gulley, A. L. (2022). One hundred years of cobalt production in the Democratic Republic of the Congo. Resources Policy, 79, 103007. DOI: 10.1016/j.resourpol.2022.103007
10. Cao, X., Sharmina, M., & Cuéllar-Franca, R. M. (2024). Sourcing cobalt in the Democratic Republic of the Congo for a responsible net-zero transition: Incentives, risks, and stakeholders. Resources Policy, 95, 105149. DOI: 10.1016/j.resourpol.2024.105149
11. Christian, I., Abah, E. O., Abel, J. E., Harsito, C., Omoniyi, M., & Boriwaye, T. (2025). Compatibility Study of Synthesized Materials for Thermal Transport in Thermoelectric Power Generation. American Journal of Innovation in Science and Engineering, 4(1), 49-63. https://doi.org/10.54536/ajise.v4i1.3948
12. Mavhunga, C. C. (2023). Africa’s move from raw material exports toward mineral value addition: Historical background and implications. MRS Bulletin, 48(5), 395–406. DOI: 10.1557/s43577-023-00534-3
13. Ajumobi, O. (2025). Safeguarding global health security amidst a scramble for Africa’s minerals for the clean energy transition. Globalization and Health, 21(1), 24. DOI: 10.1186/s12992-025-01102-x
14. Idogho, C., Abah, E. O., Onuhc, J. O., Harsito, C., Omenkaf, K., Samuel, A., ... & Ali, U. E. (2025). Machine Learning‐Based Solar Photovoltaic Power Forecasting for Nigerian Regions. Energy Science & Engineering, 13(4), 1922-1934. https://doi.org/10.1002/ese3.70013
15. Boafo, J., Dotsey, S., & Spencer, R. (2025). Energy transition diplomacy: The EU’s pursuit of Africa’s critical minerals for renewable energy – at whose expense? Energy Research & Social Science, 127, 104213. DOI: 10.1016/j.erss.2025.104213
16. Contreras, I. C., Khodadadzadeh, M., & Gloaguen, R. (2020). Multi-label classification for drill-core hyperspectral mineral mapping. ISPRS Archives (Photogrammetry & Remote Sensing), XLIII-B3-2020, 383–388. DOI: 10.5194/isprs-archives-XLIII-B3-2020-383-2020
17. Idogho, C. (2025). High-Temperature Performance of Ho–Sb–Te Thermoelectrics: Substrate Compatibility and Geometry-Driven Efficiency Optimization. The 4th International Electronic Conference on Processes, MDPI.10.3390/ecp2025
18. Tessema, A. (2017). Mineral systems analysis and artificial neural network modeling of chromite prospectivity in the Western Limb of the Bushveld Complex, South Africa. Natural Resources Research, 26(4), 465–488. DOI: 10.1007/s11053-017-9344-5
19. Nwaila, G. T., Zhang, S. E., Bourdeau, J. E., Carranza, E. J. M., Enslin, S., Manzi, M. S. D., ... & Ghorbani, Y. (2024). Mineral reconnaissance through scientific consensus: First national prospectivity maps for PGE–Ni–Cu–Cr and Witwatersrand-type Au deposits in South Africa. Natural Resources Research, 33, 2357–2384. DOI: 10.1007/s11053-024-10390-w
20. Sun, K., Chen, Y., Geng, G., Lu, Z., Zhang, W., Song, Z., ... & Zhang, Z. (2024). A review of mineral prospectivity mapping using deep learning. Minerals, 14(10), 1021. DOI: 10.3390/min14101021
21. Idoko, P. I., Ezeamii, G. C., Idogho, C., Peter, E., Obot, U. S., & Iguoba, V. A. (2024). Mathematical modeling and simulations using software like MATLAB, COMSOL and Python. Magna Scientia Advanced Research and Reviews, 12(2), 062-095. https://doi.org/10.30574/msarr.2024.12.2.0181
22. Chen, Z., Chen, J., Liu, T., Li, Y., Yin, Q., & Du, H. (2023). Regional quantitative mineral prospectivity mapping of W, Sn, and Nb-Ta based on integrated information in Rwanda, Central Africa. Minerals, 13(2), 189. DOI: 10.3390/min13020189
23. U.S. Geological Survey (2023). Mineral Commodity Summaries 2023. USGS Report. DOI: 10.3133/mcs2023
24. Permata, A. N. S., Idogho, C., Harsito, C., Thomas, I., & John, A. E. (2025). Compatibility in thermoelectric material synthesis and thermal transport. Unconventional Resources, 7, 100198. https://doi.org/10.1016/j.uncres.2025.100198
25. Sonter, L. J., Dade, M. C., Watson, J. E. M., & Valenta, R. K. (2020). Renewable energy production will exacerbate mining threats to biodiversity. Nature Communications, 11, 4174. DOI: 10.1038/s41467-020-17928-5
26. Jowitt, S. M., Mudd, G. M., & Thompson, J. F. H. (2020). Future availability of non-renewable metal resources and the influence of environmental, social, and governance conflicts on metal production. Communications Earth & Environment, 1(1), 13. DOI: 10.1038/s43247-020-0011-0
27. Permata, A. N. S., Idogho, C., Harsito, C., Prasetyo, A., & Delfianti, R. (2026). Numerical investigation and optimization of synthesized thermoelectric materials for power generation. Results in Engineering, 109011. https://doi.org/10.1016/j.rineng.2026.109011
28. Ali, S. H., Giurco, D., Arndt, N., et al. (2017). Mineral supply for sustainable development requires resource governance. Nature, 543(7645), 367–372. DOI: 10.1038/nature21359
29. Sovacool, B. K., Ali, S. H., Bazilian, M. D., Radley, B., Nemery, B., Okatz, J., & Mulvaney, D. (2020). Sustainable minerals and metals for a low-carbon future. Science, 367(6473), 30–33. DOI: 10.1126/science.aaz6003
30. Lundaev, V., Solomon, A. A., Le, T., Lohrmann, A., & Breyer, C. (2023). Review of critical materials for the energy transition: An analysis of global resources, production trends, and material circularity. Minerals Engineering, 203, 108282. DOI: 10.1016/j.mineng.2023.10828
31. Zhu, X., Zhang, S., Tang, Y., & Shi, C. (2022). A review of machine learning in processing remote sensing data for mineral exploration. Remote Sensing of Environment, 268, 112750. DOI: 10.1016/j.rse.2021.112750
32. Sovacool, B. K. (2019). The precarious political economy of cobalt: Balancing prosperity, poverty, and brutality in artisanal mining in the DRC. The Extractive Industries and Society, 6(3), 915–939. DOI: 10.1016/j.exis.2019.05.018
33. Hilson, G., & Maconachie, R. (2020). Artisanal and small-scale mining and the Sustainable Development Goals: Opportunities and new directions. Geoforum, 111, 125–128. DOI: 10.1016/j.geoforum.2020.01.013
34. Nkulu, C. B. L., Casas, L., Haufroid, V., et al. (2018). Sustainability of artisanal mining of cobalt in DR Congo. Nature Sustainability, 1(9), 495–504. DOI: 10.1038/s41893-018-0139-4
35. Frenzel, M., Kullik, J., Reuter, M. A., & Gutzmer, J. (2017). Raw material “criticality” – sense or nonsense? Journal of Physics D: Applied Physics, 50(12), 123002. DOI: 10.1088/1361-6463/aa5b64
36. Olivetti, E. A., Ceder, G., Gaustad, G. G., & Fu, X. (2018). Lithium-ion battery supply chain considerations: Analysis of potential bottlenecks in critical metals. Joule, 2(8), 1488–1501. DOI: 10.1016/j.joule.2018.05.008
Published
2026-02-01
How to Cite
Abah, E. O., & Idogho, C. (2026). Machine-Learning-Based Mapping and Ranking of Energy Materials in African Economies. European Journal of Science, Innovation and Technology, 6(1), 15-32. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/738
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