Planar solid oxide fuel cells (SOFCs) were designed, fabricated and characterized in order to develop a (1) cost-effective method for fabrication of thin electrolyte layers, (2) hermetic sealing and (3) stable interconnects. Electrophoretic deposition (EPD) was discovered to be an excellent method for fabricating dense electrolyte layers of about 5m thick on porous non-conducting substrates. The EPD process was thoroughly studied from proof-of-concept to statistical reproducibility, deposition mechanism, modeling and process optimization. Deposition on non-conducting substrates was found to follow many of the same fundamental trends as that on conductive substrates except for the voltage efficiency and detailed charge transfer mechanism. Eventually, the process was optimized such that an SOFC was fabricated that achieved 1.1W/cm2 at 850C. Further, a novel sealless planar SOFC was designed that incorporates a hermetic interface between the electrolyte and interconnect similar to tubular and honeycomb designs. The hermetic interface successfully acted as a blocking electrode under DC polarization, indicating its potential to act as a sealant. Leakage rates across the interface were 0.027sccm at 750c, similar to polycrystalline mica seals. Through a process of tape casting and lamination, a two-cell stack without sealant was fabricated and achieved a power density of 75mW/cm2 at 750C. Finally, the degradation rate of silver and silver-based interconnects was studied under static and dual-atmosphere conditions. Corrosion of silver grain boundaries along with sublimation losses results in the formation of large pores, resulting in up to 30 of anode oxidation after 8hrs testing at 750c. Further stability studies indicated that silver-based interconnects would be better suited for applications at operating temperatures less than 650C.

Improvements in performance, reliability and durability as well as reductions in production costs, remain critical prerequisites for the commercialization of proton exchange membrane fuel cells. In this thesis, a computational framework for fuel cell analysis and optimization is presented as an innovative alternative to the time consuming trial-and-error process currently used for fuel cell design. The framework is based on a two-dimensional through-the-channel isothermal, isobaric and single phase membrane electrode assembly (MEA) model. The model input parameters are the manufacturing parameters used to build the MEA: platinum loading, platinum to carbon ratio, electrolyte content and gas diffusion layer porosity. The governing equations of the fuel cell model are solved using Netwon's algorithm and an adaptive finite element method in order to achieve quadratic convergence and a mesh independent solution respectively. The analysis module is used to solve two optimization problems: i) maximize performance; and, ii) maximize performance while minimizing the production cost of the MEA. To solve these problems a gradient-based optimization algorithm is used in conjunction with analytical sensitivities. The presented computational framework is the first attempt in the literature to combine highly efficient analysis and optimization methods to perform optimization in order to tackle large-scale problems. The framework presented is capable of solving a complete MEA optimization problem with state-of-the-art electrode models in approximately 30 minutes. The optimization results show that it is possible to achieve Pt-specific power density for the optimized MEAs of 0.422 $g_{Pt}/kW$. This value is extremely close to the target of 0.4 $g_{Pt}/kW$ for large-scale implementation and demonstrate the potential of using numerical optimization for fuel cell design.

Improvements in performance, reliability and durability as well as reductions in production costs, remain critical prerequisites for the commercialization of proton exchange membrane fuel cells. In this thesis, a computational framework for fuel cell analysis and optimization is presented as an innovative alternative to the time consuming trial-and-error process currently used for fuel cell design. The framework is based on a two-dimensional through-the-channel isothermal, isobaric and single phase membrane electrode assembly (MEA) model. The model input parameters are the manufacturing parameters used to build the MEA: platinum loading, platinum to carbon ratio, electrolyte content and gas diffusion layer porosity. The governing equations of the fuel cell model are solved using Netwon's algorithm and an adaptive finite element method in order to achieve quadratic convergence and a mesh independent solution respectively. The analysis module is used to solve two optimization problems: i) maximize performance; and, ii) maximize performance while minimizing the production cost of the MEA. To solve these problems a gradient-based optimization algorithm is used in conjunction with analytical sensitivities. The presented computational framework is the first attempt in the literature to combine highly efficient analysis and optimization methods to perform optimization in order to tackle large-scale problems. The framework presented is capable of solving a complete MEA optimization problem with state-of-the-art electrode models in approximately 30 minutes. The optimization results show that it is possible to achieve Pt-specific power density for the optimized MEAs of 0.422 $g_{Pt}/kW$. This value is extremely close to the target of 0.4 $g_{Pt}/kW$ for large-scale implementation and demonstrate the potential of using numerical optimization for fuel cell design.