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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.

About this Dataset

Updated: 2025-04-06
Metadata Last Updated: 2024-07-25 00:00:00
Date Created: N/A
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Dataset Owner: N/A

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Title Forecasting demand data for critical materials
Description 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.
Modified 2024-07-25 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords Bass Diffusion Model; market dynamics; Cobalt , Gallium , Indium
{
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    "accessLevel": "public",
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Nehika Mathur"
    },
    "programCode": [
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    ],
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-3442",
    "title": "Forecasting demand data for critical materials",
    "description": "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.",
    "language": [
        "en"
    ],
    "distribution": [
        {
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            "mediaType": "application\/pdf",
            "title": "Demand forecast graph_Gallium"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-3442\/BassModel_Indium-graph.pdf",
            "mediaType": "application\/pdf",
            "title": "Demand forecast graph_Indium"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-3442\/BassModel_Cobalt-graph.pdf",
            "mediaType": "application\/pdf",
            "title": "Demand forecast graph_Cobalt"
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            "mediaType": "application\/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "title": "Forecasted demand (global)_Gallium"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-3442\/BassModel_Indium-2006-2050.xlsx",
            "mediaType": "application\/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "title": "Demand forecast (global)_Indium"
        },
        {
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            "title": "Demand forecast (global)_Cobalt"
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        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-3442\/BassModel_Gallium.ipynb",
            "mediaType": "application\/octet-stream",
            "title": "Python code_demand_Gallium"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-3442\/BassModel_Indium.ipynb",
            "mediaType": "application\/octet-stream",
            "title": "Python code_demand_Indium"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-3442\/BassModel_Cobalt.ipynb",
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            "title": "Historical demand data (Global) for Gallium, Indium and Cobalt"
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        "name": "National Institute of Standards and Technology"
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        "Gallium",
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}