Forecasting demand data for critical materials

Clean energy technologies (e.g., solar, wind, EVs) are vital in our transition to a decarbonized energy grid. Many clean energy technologies rely on critical materials that are prone to supply chain risks. As the demand for clean energy technologies grows, so will the demand for these critical materials. Anticipating critical material market dynamics becomes crucial for change makers in developing effective strategies to scale up the implementation of clean energy generating technologies. This project identified and analyzed three materials critical to a clean economy and subsequently determines demand quantities (till 2050) for these materials via the Bass Diffusion Model. This work presents three datasets, namely the demand forecasts for critical materials, Gallium, Indium and Cobalt. Historical demand data was collected from scientific literature and used to compute the Bass model parameters, p and q, i.e., the coefficients of innovation and adoption respectively. The market size, N was based on previous work and the mean is assumed to be 50 million strong (lower limit:33 million and upper limit: 67 million). The Bass model was applied for all three cases and demand data has been forecasted for Gallium, Indium and Cobalt.