Robust Remote Sensing of Trace‐Level Heavy‐Metal Contaminants in Water Using Laser Filaments

Abstract

Water is the major natural resource that enables life on our planet. Rapid detection of water pollution that occurs due to both human activity and natural cataclysms is imperative for environmental protection. Analytical chemistry–based techniques are generally not suitable for rapid monitoring because they involve collection of water samples and analysis in a laboratory. Laser‐based approaches such as laser‐induced breakdown spectroscopy (LIBS) may offer a powerful alternative, yet conventional LIBS relies on the use of tightly focused laser beams, requiring a stable air–water interface in a controlled environment. Reported here is a proof‐of‐principle, quantitative, simultaneous measurement of several representative heavy‐metal contaminants in water, at ppm‐level concentrations, using ultraintense femtosecond laser pulses propagating in air in the filamentation regime. This approach is straightforwardly extendable to kilometer‐scale standoff distances, under adverse atmospheric conditions and is insensitive to the movements of the water surface due to the topography and water waves.

A Review of Femtosecond Laser-Induced Emission Techniques for Combustion and Flow Field Diagnostics

“…Filament-induced nonlinear spectroscopy (FINS) is a non-resonant spectroscopy technique, which utilizes the short-lifetime signal of the fs laser-induced filament. FINS technique has already demonstrated its potential application prospect in many fields [97,98], such as remote sensing of greenhouse gases [99], pollutants measurements in atmosphere [100], humidity monitoring [101], and heavy-metal contaminants detection in water [102]. The applications of FINS in combustion diagnostics have emerged in recent years.…”

Effect of the target positions on the rapid identification of aluminum alloys by using filament-induced breakdown spectroscopy combined with machine learning

“…It has been widely used in quantitative analysis of substances, detection of explosive substances, heavy metal pollution in water, biological fields, isotope detection, environmental detection, and other fields. [8][9][10][11][12][13][14] In recent years, FIBS combined with machine learning algorithms to detect and identify samples has attracted much attention. Kalam et al [15] used fs-LIBS and principal component analysis (PCA) to detect and identify explosive molecules (nitroimidazole and nitropyrazole).…”