Journal of Materials Informatics, Год журнала: 2025, Номер 5(3)

Опубликована: Май 28, 2025

The development of advanced optoelectronic materials constitutes a pivotal frontier in modern energy and communication technologies, facilitating critical energy-photon-electron interconversion processes that underpin sustainable infrastructures high-performance electronic devices. However, the discovery optimization novel face substantial hurdles arising from complicated structure-property interdependencies, prohibitive costs, protracted innovation cycles. Conventional empirical approaches computational simulations usually exhibit limited efficacy addressing escalating demands for with superior stability, economic viability, customizable properties. integration machine learning (ML) high-throughput screening has emerged as transformative strategy to address these challenges. By rapidly processing large multidimensional datasets predicting material properties such structure, thermodynamic charge transport behaviors, ML offers unprecedented capabilities efficient rational design materials. This review provides comprehensive overview cutting-edge ML-driven methodologies emphasis on workflows, data strategies, model frameworks. We also discuss challenges prospects applications, particularly standardization, interpretability closed-loop experimental validation. further propose potential artificial intelligence autonomous laboratories build powerful pipeline advance

Язык: Английский