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

Chul Hun Choi, Joonyup Eun, Jinjian Cao, Seokcheon Lee, Fu Zhao

Research output: Contribution to journalArticle

4 Citations (Scopus)

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 impact on the total cost.

Original languageEnglish
Pages (from-to)950-964
Number of pages15
JournalEnergy
Volume147
DOIs
Publication statusPublished - 2018 Mar 15
Externally publishedYes

Fingerprint

Strategic materials
Indium
Planning
Byproducts
Metal refineries
Gallium
Linear programming
Ores
Light emitting diodes
Costs
Zinc
Lighting
Copper
Metals

Keywords

  • By-product material
  • Clean energy technology
  • Critical material
  • Global supply planning
  • Indium
  • Mixed integer linear programming

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Pollution
  • Energy(all)
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

Cite this

Global strategic level supply planning of materials critical to clean energy technologies – A case study on indium. / Choi, Chul Hun; Eun, Joonyup; Cao, Jinjian; Lee, Seokcheon; Zhao, Fu.

In: Energy, Vol. 147, 15.03.2018, p. 950-964.

Research output: Contribution to journalArticle

Choi, Chul Hun ; Eun, Joonyup ; Cao, Jinjian ; Lee, Seokcheon ; Zhao, Fu. / Global strategic level supply planning of materials critical to clean energy technologies – A case study on indium. In: Energy. 2018 ; Vol. 147. pp. 950-964.
@article{db73055246fa4598a9896152fb671223,
title = "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 impact on the total cost.",
keywords = "By-product material, Clean energy technology, Critical material, Global supply planning, Indium, Mixed integer linear programming",
author = "Choi, {Chul Hun} and Joonyup Eun and Jinjian Cao and Seokcheon Lee and Fu Zhao",
year = "2018",
month = "3",
day = "15",
doi = "10.1016/j.energy.2018.01.063",
language = "English",
volume = "147",
pages = "950--964",
journal = "Energy",
issn = "0360-5442",
publisher = "Elsevier Limited",

}

TY - JOUR

T1 - Global strategic level supply planning of materials critical to clean energy technologies – A case study on indium

AU - Choi, Chul Hun

AU - Eun, Joonyup

AU - Cao, Jinjian

AU - Lee, Seokcheon

AU - Zhao, Fu

PY - 2018/3/15

Y1 - 2018/3/15

N2 - 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 impact on the total cost.

AB - 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 impact on the total cost.

KW - By-product material

KW - Clean energy technology

KW - Critical material

KW - Global supply planning

KW - Indium

KW - Mixed integer linear programming

UR - http://www.scopus.com/inward/record.url?scp=85041638950&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041638950&partnerID=8YFLogxK

U2 - 10.1016/j.energy.2018.01.063

DO - 10.1016/j.energy.2018.01.063

M3 - Article

AN - SCOPUS:85041638950

VL - 147

SP - 950

EP - 964

JO - Energy

JF - Energy

SN - 0360-5442

ER -