Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies

Area of Science:

• Materials Science
• Environmental Science
• Chemical Engineering

Background:

• Engineered nanomaterials (ENMs) offer advanced properties but pose risks difficult to predict and manage.
• Existing decision-making tools fail to capture ENM uncertainties like variable forms, environmental behavior, and economic factors.
• The complexity of ENM integration necessitates innovative optimization strategies.

Purpose of the Study:

• To adapt investment portfolio optimization models for engineered nanomaterials (ENMs).
• To optimize the use of ENMs in renewable energy technologies and electric vehicle components.
• To evaluate the cumulative impacts of ENM portfolios on system performance and sustainability.

Main Methods:

• Adapted an investment portfolio optimization model for ENM selection and use.
• Evaluated cumulative impacts of ENM material portfolios in case studies.
• Analyzed organic photovoltaic cells (OPVs) and lithium-ion batteries (LIBs) for renewable energy and electric vehicles.

Main Results:

• ENM adoption is influenced by material performance, variance, resource use, environmental impact, and economic trade-offs.
• Optimized ENM portfolios can enhance energy technology system performance.
• The model demonstrates a method for balancing multiple ENM attributes.

Conclusions:

• A portfolio optimization approach effectively manages ENM uncertainties for improved decision-making.
• Sustainable ENM integration in clean energy applications can extend product lifespans and reduce fossil fuel dependence.
• ENMs can substitute scarce materials, contributing to resource efficiency and environmental benefits.