Brandon T. Motes | Searcharxiv

arXiv2025

Predicting Trends in $V_{OC}$ Through Rapid, Multimodal Characterization of State-of-the-Art p-i-n Perovskite Devices

Perovskite photovoltaic technologies are approaching commercial deployment, yet single junction and tandem architectures both still have significant room to improve power conversion efficiency and stability. The ability to perform rapid screening of material quality after altering processing conditions is critical to accelerating the optimization and commercialization of perovskite-based technologies. Currently, researchers utilize a wide range of stand-alone metrology tools to isolate sources of power loss throughout a device stack, which can be slow and labor intensive. Here, we demonstrate the use of a multimodal metrology approach to rapidly determine the maximum achievable and predicted open circuit voltages of > 100 perovskite devices during fabrication. Acquisition of these different data are facilitated by combining them into a single integrated measurement platform. We show that these data and automated analysis can be used to rapidly understand and ultimately predict quantitative trends in open circuit voltages of state-of-the-art devices architectures. The data and automated analysis workflow presented provides a reliable approach to quickly identify absorber and charge transport layer combinations that can lead to improved open circuit voltages.

cond-mat.mtrl-sci↗

arXiv2021

Accurate Determination of Semiconductor Diffusion Coefficient Using Optical Microscopy

Energy carrier transport and recombination in emerging semiconductors can be directly monitored with optical microscopy, leading to the measurement of the diffusion coefficient (D), a critical property for design of efficient optoelectronic devices. D is often determined by fitting a time-resolved expanding carrier profile after optical excitation using a Mean Squared Displacement (MSD) Model. Although this approach has gained widespread adoption, its utilization can significantly overestimate D due to the non-linear recombination processes that artificially broaden the carrier distribution profile. Here, we simulate diffusive processes in both excitonic and free carrier semiconductors and present revised MSD Models that take into account second-order (i.e. bimolecular) and third-order (i.e. Auger) processes to accurately recover D for various types of materials. For perovskite thin films, utilization of these models can reduce fitting error by orders of magnitude, especially for commonly deployed excitation conditions where carrier densities are > 5x10$^1$$^6$ cm$^-$$^3$. In addition, we show that commonly-deployed MSD Models are not well-suited for the study of films with microstructure, especially when boundary behavior is unknown and feature sizes are comparable to the diffusion length. Finally, we find that photon recycling only impacts energy carrier profiles on ultrashort time scales or for materials with fast radiative decay times. We present clear strategies to investigate energy transport in disordered materials for more effective design and optimization of electronic and optoelectronic devices.

physics.app-ph↗