Automated in situ diagnoses
The operation of traditional in situ toolsets demands significant time investments and intensive involvement from researchers for tasks such as site selection, execution of repetitive operations, and data analysis. Recent advancements in in situ diagnostic technologies have dramatically shortened the experiment data collection period, reducing durations from days to merely hours or minutes. Moreover, these modern instruments are equipped with user-friendly input/output (I/O) interfaces that support customizable automated operations, greatly enhancing the efficiency of data acquisition. These technological improvements facilitate a more feasible establishment of correlations between different experimental parameters and deepen the understanding of complex processes, elucidating the underlying reaction mechanisms.
Our objective is to establish a comprehensive research framework that integrates automated data acquisition, quantitative analysis, and process prediction. This study will focus on developing automated instrument operation protocols, multi-dimensional specimen stages and vessels correlated to automated operations, and AI-driven data analysis methods for enhanced precision and efficiency.
