Global strategic level supply planning of materials critical to clean energy technologies - A case study on indium

Abstract

Many clean energy technologies depend on some rare materials, and significant concerns about the sufficient supply of these materials have been raised recently. Most of the rare materials are so called by-product materials, and thus their supplies heavily rely on the demand of base metals. This study develops a generic mixed integer linear programming to investigate global strategic level capacity and production planning for both base and by-product materials. Other decisions relevant to capacity expansions and productions are also considered, The model is demonstrated using indium as a case study. Indium is a key material needed by two emerging clean energy applications, copper indium gallium selenide photovoltaics and light-emitting diode lighting. Supply of indium exclusively depends on primary zinc production, and concerns have been raised on whether there will be sufficient supply to support widespread applications of these two technologies. Capacity expansions of indium refinery facilities can be the first solution to overcome its supply risk. All the decisions included in the model are numerically analyzed. Sensitivity of all the parameters to the total cost are also studied. Indium content in the ore, inflation rates, and discount rates are found to have significant impac