Document Type
Honors Thesis
Publication Date
Spring 5-8-2026
Abstract
Reliability and the lifecycle of energy materials have become key concerns for sustainable, decarbonized power systems [1]. More recent reports on photovoltaic (PV) device technologies, fuel cells, hydrogen storage, and novel composite materials have indicated that material deterioration is a constraint on large-scale exploitation and cost-effectiveness, rather than on energy conversion efficiency [2], [3]. The energy infrastructure of tomorrow needs to be smart and efficient; however, more to the point, it needs to be self-aware, self-diagnostic, and able to overcome any form of degradation before breaking down [4]. The US dilemma is also directly related to federal concerns. That is what the Department of Energy's Hydrogen Shot Initiative aims to achieve: reducing the price of clean hydrogen by half in 10 years to $1/kg [5]. Solid oxide fuel cells (SOFCs) and electrolyzers are bottlenecks in their effectiveness [6]. However, the nationwide impacts of the Inflation Reduction Act provide funding for solar and storage resiliency, and it is necessary to note that stable material performance must be an essential tool in creating energy security [6], [7]. With such efforts, the sustainability of renewable systems is achieved not only through the long life of materials but also through the efficiency of their energy conversion or storage [8]. At the international level, similar challenges are evident as the rapid digitalization and automation of infrastructure require a balanced advancement of monitoring systems and predictive analytics to maintain operational reliability [9]. Evidence from photovoltaic research shows that modules containing microcracks or affected by solder fatigue may experience significant power output losses despite being similarly rated, particularly when such defects are not detected promptly [10]. In fuel cell technologies, degradation mechanisms, including nickel particle coarsening, membrane thinning, and electrode delamination, accelerate performance instability and can ultimately lead to catastrophic failure [11]. In both cases, premature material degradation results in higher operating costs, compromised safety, and diminished environmental benefits. It follows that the transition to clean energy must extend beyond expanding generation capacity to ensuring the structural and functional integrity of the materials that underpin energy systems [12], [13].
Recommended Citation
Musah Mohammed, Osumanu, "ENERGY MATERIALS HEALTH MONITORING WITH INTERPRETABLE MACHINE LEARNING" (2026). Honors Theses. 10.
https://digitalcommons.mtech.edu/honors_theses/10