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Forecasting demand data for critical materials.

Kyle Foster1, Nehika Mathur2

  • 1Miami University, 501 E. High Street, Oxford, OH 45056, United States.

Data in Brief
|November 4, 2024
PubMed
Summary

Demand for critical materials like Gallium, Indium, and Cobalt in clean energy technologies is projected using the Bass Diffusion Model. This analysis provides crucial data for understanding future market dynamics and mitigating supply chain risks for solar photovoltaics, electric vehicles, and wind turbines.

Keywords:
Bass diffusion modelCobalt, galliumIndiumMarket dynamicscritical materials

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Area of Science:

  • Materials Science
  • Energy Technology
  • Economics

Background:

  • Gallium, Indium, and Cobalt are critical materials essential for clean energy technologies like solar photovoltaics (PVs), electric vehicles (EVs), and wind turbines (WTs).
  • These materials face supply chain risks, leading to uncertainty in future supply, demand, and pricing.
  • Understanding market dynamics is crucial for mitigating these risks and ensuring the widespread adoption of clean energy.

Purpose of the Study:

  • To project the future demand for Gallium, Indium, and Cobalt until 2050.
  • To provide data sets for these critical materials to inform market analysis.
  • To contribute to understanding the future market parameters of these materials and related clean energy products.

Main Methods:

  • Application of the Bass Diffusion Model to forecast material demand.
  • Generation of three distinct data sets for each material (Gallium, Indium, Cobalt).
  • Projection period extends to the year 2050.

Main Results:

  • Demand projections for Gallium, Indium, and Cobalt until 2050 have been generated.
  • The study provides three data sets for each critical material.
  • This data serves as a foundation for analyzing future market dynamics.

Conclusions:

  • The generated demand data is a key step towards understanding future market parameters for critical materials.
  • This analysis can help mitigate uncertainties related to supply, demand, and pricing.
  • Further research can build upon this data to explore supply and price dynamics.