<div>With the rapid development of clean energy technologies, various bottlenecks on supplies of related critical materials emerged. Since supply chains of critical materials often involved with multiple layers of markets with different characteristics, to better identify bottlenecks and increase critical material availability, it is vital to have better understanding and projection on these markets.</div><div>Agent-based modeling is a bottom-up approach that can imitate heterogenous objects in a changing environment. Therefore, it is an excellent tool to simulate markets with fierce competition and fast revolution. This work demonstrates the application of agent-based modeling by discussing three different topics related to critical material demand and supply induced by clean energy products.</div><div>The first application focused on LED residential lighting market. LED lighting market grew rapidly and introduced potential demand on several critical materials including indium. The work modeled consumers as heterogenous and irrational agents in network purchasing new bulbs based</div>

<p>As society works to reduce its reliance on fossil fuels, the demand for renewable energy and clean energy technologies continues to grow rapidly. Lessons learned from the ongoing electronics waste crisis necessitate closing material loops to secure supply chains and redirect valuable resources away from the landfills.</p><p> </p><p>Inspired by the principles of industrial ecology, the circularization of renewables is demonstrated by applying the notion of Life Cycle Symbiosis (LCS), an extension of Industrial Symbiosis (IS). This is achieved by identifying waste streams that may have value as potential raw material/feedstock and the subsequent development of industrial synergies in the context of end of life (EoL) photovoltaics (PVs). Per metric ton of EoL PVs, the avoided global warming potential (GWP) and ecotoxicity impacts were calculated to be as high as 2750 kg CO₂ eq and 32,000 CTUe respectively, while the water savings and electricity savings were over 37,000 m³ and 3600 MJ. Building upon this work, a hybrid multi objective optimization (MOO) method was proposed to support the creation of industrial synergistic networks or eco industrial parks (EIPs). The hybrid method addresses the challenges associated with the early design and development stages of EIPs (supply, demand, potential synergies, etc.), and also those in relation to considering multiple conflicting sustainability objectives.</p><p> </p><p>Apart from addressing material scarcity, rising pollution levels and exposure to toxins, recovery and circularization may also contribute towards stabilizing feedstock prices. Supply chains for renewables and clean energy technologies are brittle because of risks associated with possible supply deficits stemming from complex geo-political situations and oligopolies. This can translate to price fluctuations among high-value, critical materials on which clean energy technologies rely. In order to ensure a smooth transition to a clean energy technologies, and one that is also sustainable, it is vital to assess the impact of these very complexities on the market dynamics for the critical material feedstocks. To this end, a system dynamics model has been developed to capture price trends of rare earth elements (REEs) used in EVs under varying market scenarios. The proposed model aims to aid automobile manufacturers in developing effective business strategies as they work towards electrifying their vehicle fleets.</p><p>This thesis reports on the development of some strategies rooted in industrial ecology to prevent renewables and clean energy technologies from themselves becoming environmental liabilities in the future.</p>