Leveraging Large Language Models to Address Data Scarcity in Machine Learning: Applications in Graphene Synthesis

Machine learning in materials science faces challenges due to limited experimental data, as generating synthesis data is costly and time-consuming, especially with in-house experiments. Mining data from existing literature introduces issues like mixed data quality, inconsistent formats, and variatio