Physics-Constrained Transfer-Matrix Optimization of Diffused Regions in Bifacial p⁺-n-n⁺ Crystalline-Silicon Solar...

Physics-based models are useful for the analysis and optimization of crystalline-silicon solar cells when many device designs must be evaluated. This paper presents a compact transfer-matrix framework for one-dimensional carrier transport and physics-constrained optimization in bifacial p+-n-n+ crystalline-silicon solar cells under front-side illumination. The model includes a distributed optical generation profile, explicit emitter, base, and rear-field regions, surface recombination, doping-dependent mobility, Auger recombination, band-gap narrowing, sheet and contact resistances, and external series and shunt losses. The front and rear dopant distributions are described by complementary-error-function profiles, so their junction depths follow from the diffusion parameters and base concentration instead of being independent optimization variables. The solver is verified in limiting transport conditions and with tabulated generation data. The complete model is then calibrated against the reported photovoltaic figures of merit of an experimental bifacial n-type passivated-emitter and rear-totally-diffused (n-PERT) solar cell, which serves as the reference device and is subsequently applied to global optimization. The calibration reproduces a short-circuit current density of Jsc=39.20mA/cm2, an open-circuit voltage of Voc=653.1mV, a fill factor of 0.783, and an efficiency of 20.05%. For the 180 µm reference geometry, the optimized design reaches an efficiency of 20.63%. Independent optimizations for wafer thicknesses of 160, 180, and 200 µm produce a consistent family of solutions with efficiency gains of approximately 0.56-0.60 percentage points. These gains result from the higher open-circuit voltage and fill factor despite a moderate reduction in short-circuit current density, while the optimized total series resistance remains nearly constant. The framework provides a physically interpretable method for combining carrier-transport modeling, experimental calibration, inverse design, and repeated global optimization.