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Reinforcement Learning Approach To High Efficiency Thermophotovoltaic Filter Design by Amir Teimouri is a document available to read on EtoBox.
This research article presents a deep reinforcement learning (DRL) approach to design high-efficiency multilayer optical filters for thermophotovoltaic (TPV) systems, which convert thermal radiation into electricity. The DRL framework optimizes filter designs to selectively transmit above-bandgap photons while reflecting others, achieving predicted TPV efficiencies exceeding 50% for silicon PV cells at emitter temperatures below 1500 °C. This method offers a scalable, data-driven pathway for developing adva
- Author
- Amir Teimouri
- Language
- EN