Performance Limits of Indoor Photovoltaics Based on Disordered Organic Semiconductors and Perovskites
Austin Kay a, Maura Fitzsimons a, Gregory Burwell a, Paul Meredith a, Ardalan Armin a, Oskar Sandberg a
a Sustainable Advanced Materials (Sêr-SAM), Department of Physics, Swansea University, Singleton Park, Swansea SA2 8PP, United Kingdom
Materials for Sustainable Development Conference (MATSUS)
Proceedings of MATSUS Fall 2023 Conference (MATSUSFall23)
#AppPV - Application Targets for Next Generation Photovoltaics
Torremolinos, Spain, 2023 October 16th - 20th
Organizers: Ardalan Armin and Marina Freitag
Oral, Austin Kay, presentation 141
DOI: https://doi.org/10.29363/nanoge.matsus.2023.141
Publication date: 18th July 2023

Due to a number of desirable attributes, including tailorable optical properties and scalable, low-embodied energy fabrication techniques, next-generation photovoltaics based on organic semiconductors and perovskites show great potential for a variety of niche applications. Indoor photovoltaics (IPVs) are one such application; in the coming decades, IPVs promise to reduce the carbon footprint associated with networked Internet-of-Things devices by recycling low-intensity, artificial light (generated by, e.g., LEDs and fluorescent lamps) to power them.[1] Due to the relative infancy of the field, however, the performance limits of organic semiconductors and perovskites in indoor applications are poorly understood, and the most suitable photo-active materials are yet to be identified. In the work presented here, we therefore step beyond the conventional Shockley-Queisser model to present a thermodynamic limit of IPV performance that accounts for the effects of intrinsic material characteristics, including sub-gap absorption, energetic disorder, and non-radiative open-circuit voltage loss.[2-4] Following this, we present a methodology that utilizes a device’s photovoltaic external quantum efficiency spectrum and its open-circuit voltage under one-Sun conditions to predict its performance under illumination by any spectrum, at any intensity.[5] We apply this methodology to current state-of-the-art photovoltaics (including inorganics, organics, and perovskites) to predict which could perform best under typical indoor light sources.

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