An autofocusing method for dynamic surface-enhanced Raman spectroscopy detection realized by optimized hill-climbing algorithm with long time stable hotspots

In the manual dynamic surface-enhanced Raman spectroscopy (D-SERS) detection process, it is difficult to focus on sample drop due to the constantly changing hotspot and easy judgment method. In this paper, we proposed an automatic focusing method based on long time stable hotspot with aid of optimization of hill-climbing algorithm and achieved on a designed device. First, set up a high temperature accelerating evaporation process to obtain hotspot and then cool to a low temperature rapidly to maintain it. Then, the spectral intensity was used as a focus of feedback signal in optimized hill-climbing algorithm to drive the sample stage to move up and down to adjust the depth of the laser on the samples to realize automatic focusing. As a result, the hotspot can be maintained for 5 min, and the autofocusing result can be achieved within 9 s, while the sensitivity was improved with two orders of magnitude in D-SERS detection of crystal violet (CV) compared with manual focusing.