Summary
Recently, the growing popularity of internet of things (IoT) applications has garnered substantial interest in autonomous off-grid energy harvesters such as organic photovoltaics (OPVs) from indoor-available energy sources namely artificial lights. The success of IoT will rely on avoiding battery maintenance for the billions of sensors postulated to be deployed, using available renewable energy at deployment for powering the sensors. The discovery of novel organic materials and diverse device strategies led to a big leap in the power conversion efficiency (PCE) of OPVs up to 31% under indoor lights. Despite the augmented usefulness of indoor OPVs with record performance, several challenges thus far need to be attempted. The High-throughput optimization for indoor Organic Photovoltaic Energy Systems (HOPES) project introduces a novel concept of combining advanced high-throughput experimentation techniques with a standalone tunable light source. HOPES is interdisciplinary and multidisciplinary and includes the development of highly efficient indoor OPVs along with the scale-up property that is, integration of IoT devices with the high-performance OPV. In HOPES, the researcher will implement a computer-controlled light emitting source to achieve a desirable light spectrum by exploring a large library of illumination spectra. This will lead to achieving the highest possible PCE (> 40%) for a given OPV system. The traditional experimental techniques cannot meet the recent progress of indoor OPVs owing to their limitations of time and workforce. Thus, HOPES will explore a variety of materials at an unbeaten pace by combinatorial screening to reach the highest PCE in indoor OPVs. The researcher’s experience with the indoor OPVs will be combined with the host supervisor’s expertise in high-throughput experimentation to successfully implement HOPES. The advanced training gained during HOPES implementation will contribute to excelling the researcher's professional career.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101104491 |
| Start date: | 01-11-2023 |
| End date: | 31-05-2026 |
| Total budget - Public funding: | - 181 152,00 Euro |
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Original description
Recently, the growing popularity of internet of things (IoT) applications has garnered substantial interest in autonomous off-grid energy harvesters such as organic photovoltaics (OPVs) from indoor-available energy sources namely artificial lights. The success of IoT will rely on avoiding battery maintenance for the billions of sensors postulated to be deployed, using available renewable energy at deployment for powering the sensors. The discovery of novel organic materials and diverse device strategies led to a big leap in the power conversion efficiency (PCE) of OPVs up to 31% under indoor lights. Despite the augmented usefulness of indoor OPVs with record performance, several challenges thus far need to be attempted. The High-throughput optimization for indoor Organic Photovoltaic Energy Systems (HOPES) project introduces a novel concept of combining advanced high-throughput experimentation techniques with a standalone tunable light source. HOPES is interdisciplinary and multidisciplinary and includes the development of highly efficient indoor OPVs along with the scale-up property that is, integration of IoT devices with the high-performance OPV. In HOPES, the researcher will implement a computer-controlled light emitting source to achieve a desirable light spectrum by exploring a large library of illumination spectra. This will lead to achieving the highest possible PCE (> 40%) for a given OPV system. The traditional experimental techniques cannot meet the recent progress of indoor OPVs owing to their limitations of time and workforce. Thus, HOPES will explore a variety of materials at an unbeaten pace by combinatorial screening to reach the highest PCE in indoor OPVs. The researcher’s experience with the indoor OPVs will be combined with the host supervisor’s expertise in high-throughput experimentation to successfully implement HOPES. The advanced training gained during HOPES implementation will contribute to excelling the researcher's professional career.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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