Proceedings of International Conference on Perovskite Thin Film Photovoltaics and Perovskite Photonics and Optoelectronics (NIPHO25)
Publication date: 24th April 2025
Perovskite photovoltaics have achieved remarkable efficiencies, yet critical challenges remain in optimizing charge transport layers and stabilizing lead-free perovskite materials. In this contribution, we present a unified computational framework to address some of these challenges, combining electronic structure theory, molecular dynamics, and interfacial modeling to bridge molecular design with device performance.
Hole transporting materials (HTMs) play a pivotal role in perovskite solar cells (PSCs), governing charge extraction and device stability. While the relationship between molecular structure and charge transport has been widely studied, the impact of dynamic disorder, morphological complexity, and interfacial interactions remains less understood. A multiscale protocol to probe these effects on both planar (IDIDF) and spherical (spiro-OMeTAD) HTMs will be presented, revealing how non-covalent interactions and thermal fluctuations modulate electronic couplings and hole mobilities. The behavior in real devices is studied by considering both crystalline and amorphous phases[1].
A key challenge in doped HTMs is mitigating Li+ migration, which degrades performance over time. By studying the perovskite/HTM interphase, we rationalized the superior stability and performance of next-generation HTMs compared to spiro-OMeTAD provided their enhanced molecular flexibility and intermolecular interactions (e.g., S···O contacts) with the perovskite passivation layer, reducing Li+ diffusion while maintaining efficient hole extraction[2].
Beyond charge transport layers, we applied computational methods to engineer the photoactive layer itself. Tin halide perovskites are promising lead-free alternatives, but their synthesis often yields mixed 2D nanosheets and 3D nanocrystals, complicating property control. Using ab initio molecular dynamics and thermodynamic analysis, we unravel the formation pathways of these nanostructures, linking precursor chemistry to dimensionality and phase stability[3].
By integrating these studies, we established a comprehensive strategy to optimize PSCs from molecular to device scales. This work highlights the transformative potential of computational modeling in accelerating materials discovery and device engineering.