Filament-induced breakdown spectroscopy signal enhancement using optical wavefront control

Filament-induced breakdown spectroscopy (FIBS) is an analytical method that holds significant promise for remote sensing. In FIBS, it is desirable to maximize the intensity and improve the reproducibility of a selected spectroscopic feature. We demonstrate the use of wavefront control in conjunction with a genetic algorithm in FIBS of metallic copper and show that this approach can increase the efficacy of filament-induced breakdown signal production. Through wavefront optimization, we enhance the intensity of a chosen characteristic spectroscopic feature of copper by a factor of approximately 3 when performing filamentation over a 1-meter distance. The relative standard deviation of signal intensity is reduced from-17% to-12% after optimization. We find that modification of the wavefront by introduction of astigmatism and coma maximizes the signal intensity, and these aberrations appear in two distinct trials of the genetic algorithm. We compare these findings to previous work on multiple filament control and discuss the possible mechanisms that lead to signal enhancement associated with both the beam amplitude and phase profile. A broader use of wavefront control with feedback may improve the performance of FIBS in remote sensing applications.

Automated summary

Filament-induced breakdown spectroscopy (FIBS) shows promise for remote sensing applications by utilizing wavefront control and genetic algorithms to enhance the intensity and reproducibility of spectroscopic features in metallic copper. Through wavefront optimization, a chosen characteristic spectroscopic feature of copper can be increased by approximately threefold over a one-meter distance, while reducing the relative standard deviation of signal intensity. The introduction of astigmatism and coma to modify the wavefront maximizes signal intensity, demonstrating potential for improved FIBS performance in remote sensing with broader use of wavefront control and feedback mechanisms.