Interface engineering via Mott-Schottky analysis in photovoltaics: A review

Perovskite, oxide, organic, and dye-sensitised solar cells are studied from 2015 to 2025, and their current standing and future Mott-Schottky (MS) analysis in photovoltaic (PV) research are highlighted in this review. The incorporation of MS characterisation methodology with solar cell capacitance simulator one dimension (SCAPS-1D) simulations, ab-initio calculations, impedance spectroscopy, and nascent data-driven models is addressed. The MS approach will always be at the forefront in the extraction of the flat band potential, doping concentration, depletion region width, and built-in potential. This is the link between the energetics of the semiconductors and the charge transport of the solar cells and other PV. With MS-validated doping profile optimisation, interface engineering achieves (37.66%) power conversion efficiencies, 1.52 V (open-circuit voltages) and fill factors above (87%). Unfortunately, there are limitations of the frequency-dependent capacitance, parasitic elements, trap states, and non-ideal depletion layer of some architectures, like organic and hybrid ones. The MS and simulations to be used together, and machine learning adoption and analytical models to improve the electronic characterisation, have the potential to resolve the problems. This study offers a critical evaluation of current methods and inherent constraints in MS analysis, offering a strategic framework for the systematic design of efficient, durable, and sustainable solar technologies. • Comprehensive Mott-Schottky review (2015-2025): flat-band potential, doping density, and built-in potential in photovoltaics. • Integration of SCAPS 1D, ab initio, impedance spectroscopy enhances characterisation of perovskite, lead-free solar cells. • Connects >37% efficiency to doping 10¹⁰–10¹⁶ cm⁻³, flat-band –0.5 to 1.5 V; describes high efficiency device significance. • Proposes solutions to interpretive/empirical challenges: thin film topography, interfacial defects, frequency capacitance. • Identifies rational design potential: high-efficiency, stable, eco-friendly photovoltaics via interface modulation, ML models.