Discovery of high-energy-density materials via machine learning-assisted high-throughput virtual screening and experimental approach

Key Points

• New high-energy-density materials were identified through a combination of machine learning and experimental techniques.
• The approach utilized high-throughput screening methods to rapidly evaluate numerous material candidates for energy applications.
• Machine learning algorithms assisted in predicting the properties of materials based on virtual screening results.
• This discovery may enable the development of better energy storage solutions, benefiting various industries.