Organic Semiconductor

Organic semiconductors are materials whose electrical conductivity is intermediate between that of metals and insulators, finding applications in electronics, light-emitting diodes, and photovoltaics. Current research heavily utilizes machine learning, particularly graph neural networks and ensemble methods, to predict and optimize their properties, such as energy levels and charge mobility, often employing novel molecular representations like hypergraphs to capture complex structural features. This data-driven approach accelerates the discovery and design of high-performance organic semiconductors, enabling the development of more efficient and sustainable technologies.