Time-of-flight secondary ion mass spectrometry research advances from a effective bibliometric method.

Due to the ability for high-resolution molecular imaging and chemical analysis with spatial resolution, time-of-flight secondary ion mass spectrometry (TOF-SIMS) is an extremely powerful surface analysis technique that is commonly used for chemical and biological analysis. The R-based bibliometric analysis is presented for the evaluation of the advancement of the TOF-SIMS research. The proposed approach enables flexible data processing and extensive quantitative analysis of the trends of the research, making it superior to commonly used visualization tools like VOSviewer. The results of the analysis reveal that significant improvements have been made in the last ten years for both small molecules (m/z < 300) and large molecules (m/z > 300). Single cell analysis, in situ interface analysis, and microfluidics are emerging trends for TOF-SIMS analysis. The study also presents an approach to leverage the power of big data and machine learning for peak analysis of complex data sets.