Ambient Photovoltaics for Self-Powered and Self-Aware IoT
Marina Freitag a
a School of Natural and Environmental Sciences, Newcastle University, UK, Newcastle upon Tyne, Reino Unido, Newcastle upon Tyne, United Kingdom
Asia-Pacific International Conference on Perovskite, Organic Photovoltaics and Optoelectronics
Proceedings of Asia-Pacific International Conference on Perovskite, Organic Photovoltaics and Optoelectronics (IPEROP23)
Kobe, Japan, 2023 January 22nd - 24th
Organizers: Seigo Ito, Hideo Ohkita and Atsushi Wakamiya
Invited Speaker, Marina Freitag, presentation 029
Publication date: 21st November 2022

By 2025 about 75 billion IoT devices will be installed, of which the majority will reside indoors. It is therefore crucial to find an energy source that yields high efficiencies in this environment.1,2 The ambient photovoltaics will redefine the energy paradigm of the current digital revolution with Internet of Things (IoTs, wireless sensors) as current unsustainable designs are strongly limited by their choice of energy supply. Given the record performance of my hybrid photovoltaics in low and indoor lighting conditions, these devices will be ideal to power smart sensors for the IoTs, making them sustainable and independent from any external power sources.

We address the state-of-the-art materials for indoor photovoltaics, with a particular focus on dye-sensitized solar cells, and their effect on the architecture of next generation IoT devices and sensor networks. Dye-sensitized solar cells (DSCs) are known for efficient conversion of ambient light. Fast charge separation in a variety of organic dyes and tuneable energy levels in the versatile CuII/I redox systems combined with negligible recombination processes allow DSCs to maintain a high photovoltage under ambient light.2

We tailored dye-sensitized photovoltaic cells based on a copper (II/I) coordination complexes hole transport material for power generation under ambient lighting with an unprecedented conversion efficiency of PCE 38 %, at 1000 lux from a fluorescent lamp using a novel co-sensitization strategy3 and electrolyte modifications Under 1000 lux lighting, 64 cm2 photovoltaic area gives 152 J or 4.41 1020 photons sufficient energy for training and testing of an artificial neural network in less than 24 hours. Ambient light harvesters enable a new generation of self-powered and "smart" IoT device to be powered by a previously untapped energy source.4,5 The combination of ambient light harvesting with artificial intelligence enables the creation of completely autonomous, self-powered sensor systems for use in industry, healthcare, homes, and smart cities.


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