Advances in Laser-induced Breakdown Spectroscopy for Real-time Monitoring

Laser-Induced Breakdown Spectroscopy (LIBS)technology, a type of atomic emission spectrometry analysis that utilizes a laser as an excitation source, has undergone rapid development in recent years owing to its rapid, in-situ, multi-element detection capabilities and minimal sample preparation.Although its sensitivity is generally lower than that of inductively coupled plasma mass spectrometry (ICP-MS) and some other techniques, LIBS-by virtue of its deployment flexibility, portability, and the foregoing attributes-is better suited to online monitoring.This work summarizes the latest research progress of LIBS in the field of real-time monitoring and provides a comprehensive comparative analysis of the strengths and weaknesses of LIBS relative to XRF, ICP-MS, and other related techniques, specifically focusing on industrial raw material/product quality control during manufacturing, in situ elemental analysis during laser processing, and environmental pollutant emissions tracking.Across these applications, LIBS exhibits variable detection stability and sensitivity: in industrial settings, relative standard deviations (RSDs) typically remain below 15% (with minor elements reaching 15-30%), while detection limits (LODs) predominantly range at ppm levels (with limited ppblevel achievements).Environmental monitoring shows RSDs heavily dependent on instrumentation and field conditions, with reported LODs spanning ng/m to mg/m (air pollutants), g/L to mg/L (water quality), and mg/kg (soil analysis).This work also explores the practical challenges encountered during the implementation of LIBS across various domains.In the industrial sector, the primary obstacles involve suboptimal detection accuracy and stability, stemming from high solid-surface complexity, the difficulties of liquid metal analysis, contamination of metallurgical molds, and harsh operating environments.Within the field of laser processing, the challenges mainly arise from the instability of the welding molten pool and the ambiguity in defining thresholds for determining the extent of machining.Conversely, environmental monitoring is primarily constrained by relatively low sensitivity when analyzing gaseous and liquid states.Finally, targeted solutions corresponding to the specific technical challenges in each field are proposed.Future developments in signal enhancement are anticipated to overcome current technical constraints, enabling robust high-sensitivity, multi-element detection in complex sample systems.Atom.Spectrosc.2026, 47(1), 141-174. Phosphate ore---LIBS technology has shown high competitive potential in the mineral industry compared to existing online analyzers (e.g., PGNAA). 24Sulfur ore, copper ore, nickel ore, etc.Dual-pulse LIBS A 2-2.5 fold enhancement of sulfur spectral signals was achieved, with a minimum detectable sulfur content of less than 1%. 25Phosphate ore, magnesium ore, copper ore, nickel ore, etc.---A field-portable LIBS industrial analyzer was developed, which offers advantages of real-time continuous measurement and low safety risks compared to conventional laboratory-based LIBS technology, as well as XRF and PGNAA analytical techniques.26 Iron ore, nickel ore, and phosphate ore PCA, PCR PCA and PCR models were employed for multi-element quantitative analysis of iron ore, and phosphorus content in ores was analyzed for the first time by combining LIBS data with PCA.27 Iron ore slurry Slurry circulation system A slurry circulation system was developed, which successfully improved the repeatability of LIBS online monitoring and reduced interference caused by sample splashing, sedimentation, and other issues during ore slurry flotation.Average RSD: Fe 6.96% LOD: Fe 0.075 wt.% 28 Atom.Spectrosc.2026, 47(1), 141-174.Table. 2 The contributions of various studies in the field of LIBS for real-time monitoring of coal materials Methods Contributions Refs Multi-CCD module LIBS with pulseto-pulse intensity normalization and data filtering preprocessing.Demonstrated the capability for rapid coal composition analysis and the potential of LIBS equipment for real-time monitoring.40 Design of a commercial-grade LIBS analyzer.Conducted one month of independent testing, demonstrating excellent operational stability. 41Development of an automated LIBS analytical system.Showcased higher efficiency for online detection compared to traditional techniques (e.g., JIS-M8814) and the ability to detect carbon under high-pressure, harsh conditions.42 Real-time LIBS monitoring device for Unburned Carbon (UC).Utilized real-time UC data as a feedback factor for stabilizing boiler combustion to achieve quality control; field deployment at a power plant proved effectiveness.43Online in-situ LIBS analysis.Following 4 months of field measurements and comparison with PGNAA results, the precision and error levels were found to be comparable to traditional techniques. 20PCA analysis of data generated by LIBS monitoring equipment.Confirmed the feasibility of replacing PGNAA and XRF for coal quality monitoring; detailed linear ranges for various elements and identified trace elements (e.g., Na, K); recommended nanopowder for calibration and provided procedures to address signal nonlinearity.44Online LIBS monitoring equipment integrated with Temperature Neural Networks.Field-tested an online analysis system, proving the feasibility of coal ash composition measurement and the possibility of predicting coal slagging using the integrated model. 45Automated LIBS analytical prototype.Reviewed progress in online equipment for pulverized coal and fly ash UC; developed a prototype using second-order polynomial multivariate inverse regression to mitigate matrix effects. 9,46Large Depth-of-Field (DOF) LIBS system based on reflective mirrors.Simulated coal-fired power plant environments in the laboratory to test the equipment; the mirrorbased design significantly improved system flexibility. 47 LIBS coupled with Artificial Neural Networks (ANN).Laboratory simulation of industrial power plant conditions; demonstrated excellent consistency between predicted and standard values after ANN processing.48 Double-pulse LIBS (DP-LIBS).Successfully enhanced sulfur spectral line intensity via DP-LIBS in a helium environment (R 2 =0.992,LOD=0.038wt.%, RMSECV=0.143wt.%).49 Physical constraint preparation of coal powder with PLSR model for LIBS data prediction.Improved detection repeatability through physical constraints; the best average Relative Standard Deviation (RSD) was <5%.50