This study presents a multi-analytical spectroscopic methodology designed to characterize solid micro-inclusions trapped within complex evaporitic matrices, focusing on selenite gypsum crystals (CaSO4·2H2O) from the Mina Rica mine (Pulpí, Spain). Gypsum is regarded a high-priority a Martian analog, as recent findings by the Perseverance rover have confirmed the presence of calcium sulfates in various hydration states on the Martian surface. Furthermore, gypsum is a key target for geochemistry due to its high potential for material entrapment and long-term preservation (Wang et al., 2024 [1]). The primary objective is to evaluate the synergistic capability of complementary techniques to identify and spatially resolve distinct co-existing phases within mineral interlayers. For the first time, carbonaceous material has been detected within these specific crystals using Laser-Induced Breakdown Spectroscopy (LIBS). High-resolution depth profiling and spatial rastering demonstrated the potential of LIBS to track carbon signals despite a highly heterogeneous distribution. Complementary micro-Raman spectroscopy resolved the structural nature of this carbon, identifying it as an amorphous, disordered phase preferentially localized along the mineral cleavage planes. Furthermore, Raman analysis successfully identified co-existing iron carbonate (siderite) and iron oxyhydroxide micro-granules. While the spatial overlap of these phases frequently induces spectral interferences, the integration of elemental LIBS data and structural Raman deconvolution enables the effective differentiation between carbonate-bound carbon and independent amorphous carbonaceous residues. The latter enclosed in gypsum cristals may stem from the remobilization of bituminous compounds derived from metamorphic bedrock in phreatic conditions during crystallization. The results validate this dual-spectroscopic approach as a robust, low-destructive framework for indexing organic and inorganic fluid-transported inclusions in sub-surface sulfate deposits.
Retention of Hydrogen (H) isotopes in plasma-facing materials is a critical issue for nuclear safety and self-sufficiency in fusion devices operating with Deuterium-Tritium (DT) fuel mixture and tungsten (W) plasma-facing components. Its reliable detection, either in-situ or ex-situ, is of great importance for nuclear licensing and material characterisation after plasma exposure. However, we observed that in vacuum conditions, the Balmer-alpha line emission of Hydrogen (Hα) measured by Laser-Induced Breakdown Spectroscopy (LIBS) exhibit complex Doppler shifts in the laser-induced plasma (LIP), leading to significant spectral distortions. In this work, we report the first systematic study of Doppler shifts in Balmer-alpha line emission of hydrogen obtained by picosecond LIBS on W samples. Our results reveal not only Doppler shifts associated with single-velocity H atoms, but also, between delay time from 0 to 300 ns, distinct dual-wavelength shifts of the emission lines arising from the simultaneous presence of fast and slow H atoms in the LIP. The fast component exhibits a laser fluence-dependent shift, whereas the slow component shows the opposite behavior. Fast and slow H atoms can be temporally separated during detection due to their different velocities. Moreover, we infer, that in the near surface layer, fast H atom corresponds to surface-adsorbed H, while slow H atom may correspond to H present in the W bulk material. Building on these findings, we demonstrate a new approach for tuning the Balmer-alpha wavelength as function of laser fluence, making it possible to temporally isolate fast and slow H atoms and thereby suppress spectral interference. The Doppler characteristics additionally offer a potential spectroscopic tool using LIBS for distinguishing between H present at the surface and subsurface of the W bulk material. Utilizing this method, we successfully observed the dynamic adsorption kinetics of H on the W surface at a pressure level as low as 10−7 mbar. This work not only resolves a fundamental spectral distortion mechanism, but also provides guidelines for improving the accuracy of depth-resolved H isotopes detection in fusion-relevant plasma-facing materials (PFMs) utilizing LIBS measurements.
Cobalt-rich crust is a type of deep-sea metallic mineral resources which is considered as a vital source of metals for future green energies and high-tech industries. Laser-induced breakdown spectroscopy (LIBS) can perform a rapid and multi-elemental analysis of cobalt-rich crusts which is suitable for shipboard laboratories, but its quantitative performance is often hindered by spectral signal fluctuations and matrix effects. In this work, we evaluated the feasibility of spectral-acoustic data fusion combined with transfer learning for the quantitative LIBS analysis of cobalt-rich crusts under fluctuating LTSD conditions. Spectral signals and acoustic signals were simultaneously collected from a total of 39 samples, and a transfer learning strategy was employed at both the feature and instance levels. PLS regression models were established to assess the quantitative performances of Mn, Co, Cu and Ti in cobalt-rich crusts. It showed that for the validation data acquired at fluctuating LTSD conditions, the R¯P2 was improved from 0.917 to 0.948 and the RSD¯P was reduced from 14.08% to 10.55%, by using the spectral-acoustic data fusion combined with transfer learning. The RMSEP of Mn, Co, Cu, and Ti were 0.787%, 0.015%, 0.006%, and 0.106%, which were already close to the values obtained from constant LTSD conditions. The model interpretability was illustrated by visualizing the features extracted by SelectKBest algorithm and principal component analysis (PCA). This work provides a novel solution for LIBS analysis severely affected by spectral instability and physical matrix effects and could be potentially used for the on-board mineral analysis of deep-sea cobalt-rich crusts.
Accurate determination of sulfur speciation in insulating glass is often hindered by X-ray-induced beam damage. Although conductive carbon coating suppresses detectable sulfide (S2−) oxidation during S K-edge X-ray absorption fine structure (XAFS) measurements, its applicability to laboratory X-ray wavelength-dispersive X-ray fluorescence (WD-XRF) has not been sufficiently clarified. In this study, we found that the 15-nm carbon-coating condition previously shown to be effective for S K-edge XAFS did not provide a clear protective effect against S2− oxidation under prolonged WD-XRF conditions at 30 kV. To examine the origin of this limitation, we performed order-of-magnitude, constraint-based stoichiometric estimates comparing the required oxidant capacity with the available intrinsic electron-accepting capacity. Bulk-average analysis indicates that the Fe3+-based upper-limit electron-accepting capacity could plausibly account for the overall S2− loss. In contrast, local estimates within the S-Kα WD-XRF probing volume indicate a much larger oxidant demand than can be explained by the measured stable intrinsic acceptors under the adopted assumptions. Together with FT-IR results indicating no detectable net change in total H2O concentration after comparable WD-XRF irradiation, these results provide a stoichiometric constraint suggesting that simple surface-charge compensation alone is insufficient under the present WD-XRF conditions. The observations are consistent with additional irradiation-induced oxidizing pathways, potentially including defect-related hole centers and metal-mediated ionization processes, although these pathways were not directly identified in the present study. Accordingly, reliable sulfur speciation is best supported by minimized-exposure WD-XRF interpreted as the least-damaged practical approximation of the initial state, together with orthogonal validation using radiation-free wet chemical analysis.
Laser-Induced Breakdown Spectroscopy (LIBS) imaging has established itself as a powerful analytical technique for the spatial characterisation of elemental composition in complex, heterogeneous materials. Its key advantages, namely near-absence of sample preparation, high dynamic range, spatial resolution down to 10 μm, and acquisition rates exceeding 1 kHz, make it particularly well suited for archaeometric investigations. However, an important yet widely overlooked source of information lies in optical imaging: high-resolution visible images, whether acquired under plane-polarised or cross-polarised light, are routinely collected during petrographic examination but are seldom incorporated into the subsequent chemometric exploration of spectral data. In this work, we demonstrate that incorporating such an optical RGB image into a multimodal data fusion strategy substantially enhances the discriminatory power of chemometric tools when applied to LIBS hyperspectral imaging data. The strategy is illustrated on a historical mortar sample from the medieval Saint-Irénée Church, Lyon, France. The optical RGB image, acquired under cross-polarised light on a dedicated optical microscope, and the LIBS hyperspectral image were collected under geometrically incompatible conditions, differing in spatial resolution, field of view, and rotational orientation, which required a rigorous image registration step based on the Mutual Information (MI) metric and a One-Plus-One Evolutionary (OPO) optimiser. Following low-level data fusion and Frobenius block normalisation, PCA performed on the combined dataset revealed substantially richer phase discrimination compared to PCA applied to LIBS data alone. In particular, specific mineral grains that were optically distinguishable but spectrally degenerate in the LIBS-only PCA were successfully resolved after fusion, with novel principal components associating visible colour contrasts with subtle variations in trace-level elements. These results demonstrate that the integration of optical imaging with LIBS spectral data represents a straightforward, cost-effective, and highly effective analytical strategy for the investigation of complex cultural heritage materials, with direct applicability to any spectroscopic or spectrometric imaging workflow in which an optical image of the sample is available.
The aim of this study was to assess the potential of FTIR spectroscopy for monitoring biochemical changes in serum samples of individuals with carotid atherosclerosis following surgical intervention. Principal Component Analysis (PCA) of FTIR spectra from serum samples reveals distinct biochemical patterns at different time points: pre-surgery, 24 h post-surgery, and 48 h post-surgery. Two spectral ranges, 800–1800 cm−1 and 2800–3000 cm−1, were analyzed. PCA demonstrated that pre-surgery samples can be clearly differentiated from those taken 24 and 48 h post-surgery. However, no significant distinction was found between the 24-hour and 48-hour post-surgery samples. For the 800–1800 cm−1 range, the first principal component (PC1) explained 77.49% of the variance, highlighting the molecular vibrations of lipids, proteins, and carbohydrates. In the 2800–3000 cm−1 range, PC1 accounted for 94.89% of the variance, primarily reflecting lipid-related vibrations. These findings indicate a clear separation between pre-surgery and post-surgery samples, with the most significant variance explained by PC1. Additionally, the Boruta algorithm identified a key spectral range between 1506 cm−1 and 1673 cm−1, critical for distinguishing the samples. Classification models, including k-Nearest Neighbors, Gradient Boosting, Support Vector Machine, and Neural Network, demonstrated excellent performance in differentiating pre-surgery and post-surgery samples. However, the models struggled to distinguish between the 24-hour and 48-hour post-surgery time points. This suggests that FTIR spectroscopy may be useful for monitoring post-surgery recovery in carotid artery atherosclerosis, although subtle changes in the biochemical profile are challenging to detect between 24 and 48 h post-surgery.
Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) provides information on the molecular composition and structure of samples. The use of ATR-FTIR was evaluated for biochemical analysis and taxonomic differentiation of entomopathogenic nematodes (EPNs). Spectra were obtained from a small sample (pellet) of a nematode population recovered from commercial EPN packages, which was placed directly on the ATR plate. Differences in signal intensity at multiple peaks associated with biomolecules critical to the survival of EPN (trehalose, glycogen, and triglyceride) were measured and visualized using Non-Metric Multidimensional Scaling (nMDS) and Principal Component Analysis (PCA). Statistically significant differences in peak signal intensity were observed between EPN species for each biochemical parameter, providing a basis for assessing the likelihood of their performance success in the field conditions. The present study also evaluated FTIR analysis of EPN for taxonomic differentiation. Results demonstrate that FTIR can be used to identify and differentiate Steinernema and Heterorhabditis genera/species, offering a potentially faster, less expensive alternative to molecular identification techniques. Ultimately, this study demonstrates the efficacy of ATR-FTIR as a reliable method for assessing the biochemical suitability of EPN products for field applications and differentiating between EPNs.
Endometrial cancer (EC) is increasingly prevalent worldwide, highlighting the need for non-invasive blood-based diagnostic triage tools. ATR-FTIR spectroscopy enables rapid, label-free biochemical profiling of plasma or serum for experimental cancer detection. To date, no systematic review or meta-analysis has evaluated the experimental performance of infrared spectroscopy for discriminating EC from non-cancer in blood-based samples. This study synthesizes available evidence to characterize the strength, consistency, and heterogeneity of the underlying spectroscopic signal across preclinical and proof-of-concept studies. MEDLINE, Web of Science, EMBASE, Scopus, Google Scholar, and CENTRAL were searched without language restrictions. Eligible studies evaluated ATR-FTIR spectroscopy of plasma or serum using histopathology as the reference standard. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratios were estimated using a bivariate random-effects model, with assessment of heterogeneity, threshold effects, and publication bias. Five case–control studies comprising 1376 participants were included. For plasma-based analyses, pooled sensitivity was 0.61 (95% CI: 0.59–0.68) and specificity was 0.73 (95% CI: 0.69–0.76), with a diagnostic odds ratio of 4.23 (95% CI: 3.33–5.37). For serum-based analyses, pooled sensitivity and specificity were both 0.62 (95% CI: 0.59–0.65), with a diagnostic odds ratio of 2.65 (95% CI: 2.16–3.25). Substantial heterogeneity and significant threshold effects were observed. Current evidence supports reproducible spectroscopic differences between EC and non-cancer blood samples under experimental conditions. However, methodological heterogeneity and retrospective case–control study designs limit clinical interpretability. These findings provide a benchmark for future prospective validation rather than immediate clinical application.
Total reflection X-ray fluorescence (TXRF) is a useful technique for measuring elements in various samples. In this study, we applied maximum likelihood estimation (MLE) to predict the peak profile of a long-time measurement based on that of a short-time measurement, aiming to develop a useful method for improving analytical accuracy in rapid and in-situ TXRF measurements. We assumed that the observation of fluorescent X-ray events follows a Poisson distribution and approximated the peak profile as a Gaussian function; MLE was also applied to estimate a background profile. As a proof-of-concept study, single peaks for Pb and Au were estimated using the proposed method. Measurement times were set to 3, 5, 7 and 600 s, with the TXRF spectrum from the 600 s measurement serving as the standard spectrum. Using conventional count rates, the peak profiles from short- and long-time measurements significantly differed. However, applying the profile estimation method improved the repeatability of short-time measurements. We obtained the mean squared error (MSE) between the estimated and standard profiles. For the 7 s measurement of Pb, the MSE was improved by a factor of 20.1 by applying the proposed profile estimation method. A significant advantage is that this method requires only software modification without hardware modification, demonstrating high potential for practical use. Therefore, we developed an effective profile estimation method for performing high-accuracy TXRF analysis with short measurement times. This approach is expected to be useful for screening inspections and elemental analysis in various solutions.
In-situ lithium (Li) isotope analysis of lepidolite by laser ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) is essential for deciphering magmatic evolution and Li enrichment mechanisms in granitic pegmatites. However, the lack of matrix-matched reference materials (RMs) for Li-rich minerals necessitates a rigorous evaluation of current analytical protocols. In this study, we systematically optimized instrumental parameters and gas flow rates to balance 7Li sensitivity and signal-to-noise ratios. Our results indicate that incorporating N2 into the carrier gas significantly diminishes signal stability but enhances the signal-to-noise ratio. To ensure high analytical precision, a 7Li signal intensity exceeding 1.0 V is recommended. Long-term reproducibility tests using NIST SRM 610 yielded a precision of 0.56‰ (2SD). Comparative analyses of silicate glasses and tourmalines revealed substantial matrix effects during LA-MC-ICP-MS Li isotope measurements. While the introduction of water vapor (wet plasma conditions) effectively suppressed isotopic bias for low-Li samples, this approach proved insufficient for the precise determination of Li-rich minerals such as lepidolite with low-Li RMs used as calibration standard. Consequently, we demonstrate that in-situ Li isotope compositions in lepidolite are best achieved through stringent matrix-matching or the use of RMs with comparable matrices and Li concentrations under wet plasma conditions. To facilitate this, we propose and characterize five candidate lepidolite RMs. Our optimized protocol, combined with these new RMs, enables high-precision in-situ Li isotope analysis of natural lepidolites, yielding results consistent with bulk-rock data and providing a robust tool for deciphering the genesis of pegmatite-type Li deposits.
Laser-induced breakdown spectroscopy (LIBS) is a powerful in-situ diagnostic technique for real-time, multi-element analysis in extreme environments. In this work, copper (Cu) pellets were fabricated by compressing metallic powders under different compaction pressures (198 MPa – 1164 MPa), resulting in samples with varying densities (6.22–8.47 g/cm3). The influence of compaction pressure on laser-induced plasma characteristics was systematically investigated under vacuum conditions (6 × 10−5 mbar). The results show that the intensity of Cu I emission lines increases with increasing compaction pressure (corresponding to higher density) and approaches a saturation regime at high pressure levels. Meanwhile, the relative standard deviation decreases significantly from ∼20% to below 6%, indicating a substantial improvement in signal reproducibility. Plasma diagnostics based on Boltzmann plot and Stark broadening analyses reveal that the electron temperature remains nearly unchanged, whereas the electron density increases markedly (up to ∼3×) with increasing compaction pressure, with a more pronounced effect observed at lower laser fluence. Plasma imaging at a fixed delay shows enhanced plume expansion with increasing compaction pressure. In contrast, ablation crater analysis reveals a decreasing trend in crater depth for highly compacted samples. This behavior is likely associated with enhanced plasma shielding effects, which may reduce effective laser energy coupling to the target. These results indicate that compaction pressure plays a critical role in governing LIBS signal characteristics under vacuum conditions. Overall, this study provides a clearer understanding of matrix effects associated with compacted powder materials and offers useful guidance for improving LIBS diagnostics of porous and compacted materials in environments relevant to fusion applications.
A novel adjustable signal smoother device for laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was developed and tested. The smoother consists of a cube-shaped device with an internal cylindrical cavity containing a rotating disc, whose inclination can be tuned to modify the aerosol transport path and laminar flow. The disc has an inner conduit allowing the aerosol to travel unperturbed when aligned with the entrance and exit of the smoother device, or can be rotated to different degrees, making the aerosol collide with the disc to change its path; thus, increasing washout time. The performance of the device was evaluated, for different inclinations of the rotating disc, and for different spot sizes, using NIST 610 as a testing sample. Moreover, this study was carried out using an ultraviolet femtosecond laser ablation system (UV-fs-LA) coupled to an ICP-Time-of-Flight (TOF)MS that provides high mass spectra acquisition rates to monitor the variation of multielemental signals in order to characterize the device (without the adverse effects (e.g., spectral skew) that the smoother is designed to mitigate in sequential spectrometers). The results demonstrate that the smoother device is able to flatten the transient signal, increasing the single pulse response (SPR, measured as the full width at 10% of the maximum intensity, FW0.1M) by a factor of up to 10-fold. This device is therefore considered of high utility when coupled to sequential mass spectrometers to adapt the SPR in order to avoid aliasing or other spectral skew related issues.
Laser-induced breakdown spectroscopy assisted by an acoustic levitation system (LIBS-AL) is a technique that has shown promising results for analyzing liquid in a droplet sample. However, previous publications have reported a strong dependency on a preconcentration process by heating the droplet using an IR laser to increase the signal of the spectral lines. This approach has shown successful results but involves additional equipment, sample pre-treatment, and time analysis. Hence, to improve the performance of the technique for liquid analysis, a deeper study of the laser-matter samples has been made. To achieve this objective, the shadowgraph and fast photo-detection techniques were employed to record the dynamics of plasma formation and expansion over time. The experiments were performed on different droplet sizes and ablation locations within the droplet. The results indicate variations in the amount of material ablated from the droplet. The amount of ablated material was found to be dependent on experimental parameters such as observation time (delay time), focal distance, and droplet size. Since the shadowgraph and fast-photo detection provide 2D information (area), the ablated material was evaluated with the intersection area of these images. The intersection area resulting is referred to as the effective ablated area. Therefore, in order to characterize the plasma plume expansion, the ablation efficiency (mass of the droplet ablated) was determined using the temporal evolution of the effective ablated area. The results show that the effective ablated area can reach up to 27% of the sample area across the different droplet sizes studied. Additionally, plasma expansion at the gas–liquid interface was studied using the Drag model to account for expansion against external pressure.
Accurate determination of total dissolved inorganic carbon (DIC) in seawater is essential for quantifying anthropogenic CO2 uptake and evaluating changes in the marine carbonate system; however, existing reference techniques such as coulometric titration require complex gas-extraction procedures and are difficult to deploy outside specialized laboratories. Here, we introduce a spectrometric method based on ICP-OES determination of Sr depletion in which dissolved CO2 is quantitatively converted to solid SrCO3 using strontium hydroxide under alkaline conditions, and the decrease in dissolved Sr2+ is measured by inductively coupled plasma optical emission spectrometry (ICP-OES). Because SrCO3 has an extremely low solubility product (Ksp = 5.6 × 10−10), the reaction proceeds with near-complete stoichiometry, enabling direct gravimetrically traceable quantification of DIC without the need for inert-gas bubbling or specialized gas-handling systems. Both liquid–liquid and gas–liquid modes showed highly linear correlations (R2 = 0.9997), and recovery tests using certified seawater reference material yielded a recovery of 99.99%. Although the analytical precision is lower than that of reference coulometric methods, the proposed approach provides a simple and reliable workflow suitable for routine analysis and field-oriented sample pretreatment followed by laboratory-based ICP-OES measurement. The estimated theoretical detection limit was 0.009 mmol kg−1 as CO2 in the sample solution. This method offers a practical complementary approach for DIC measurement in environmental samples.
The inherent paradox of laser-induced breakdown spectroscopy (LIBS) lies in its robustness for qualitative identification despite its historically limited quantitative precision. This discrepancy is rooted in the matrix effect, a complex coupling of physical and chemical interferences that disrupts the proportionality between emission intensity and analyte concentration. Critically examining the more than fifty-year evolution of the community’s response to this challenge, we trace a trajectory from early empirical recognition and physical modeling through calibration-free LIBS to multivariate chemometrics and the current rise of deep learning. We argue that progress toward more transferable and matrix-robust calibration may require a shift in modeling philosophy: from a paradigm of strictly controlling the physics to one of intelligent, physically constrained adaptation. To bridge this gap, we propose a physical state-space model as the organizing framework of this review: a latent-state formulation in which the LIBS spectrum is generated by an ordered chain of coarse-grained physical operators acting on a hidden sample state, with stage-resolved stochasticity entering throughout the chain and residual detector-level measurement noise. The operator chain comprises M for material removal, A for ablated-material transfer and initial speciation, P for plasma-state, R for radiation generation and transport to the acquisition-system entrance, and F for instrumental transfer and detection. By mapping specific interferences, such as surface hardness, moisture content, and easily ionizable elements (EIEs), to the operator or operators they primarily perturb, the review recasts matrix effects as structured physical perturbations rather than as undifferentiated black-box error. Building on this framework, we organize the emerging hybrid physics–artificial intelligence (AI) approaches – which constrain data-driven models with physical structure – into a graded taxonomy, ranging from light correction of physically derived estimates to architectures that embed physical laws directly into the model. We further address the largely neglected problem of uncertainty quantification for LIBS predictions, outlining a tiered protocol for producing calibrated and validated uncertainty estimates. We conclude that this state-space framework can provide a formal computational backbone for the development of autonomous LIBS sensors with calibrated uncertainty and more transferable, matrix-robust calibration for in situ applications.
Cancer diagnostic methods based on Raman spectroscopy are being actively investigated, and there is a strong need for simple approaches to amplify the intensity of Raman scattered light from biological fluids such as serum and urine, which contain only trace amounts of nucleic acids, proteins, amino acids, and other analytes together with highly autofluorescent background components. We evaluated two measurement methods. One was the needle method (NM), in which a laser irradiates a droplet of liquid sample held at the tip of a fine-diameter stainless-steel needle. The other was the quartz glass fiber sheet method (QSM), in which a quartz glass fiber sheet is imbued with a liquid sample, allowed to dry, and then irradiated at the sheet surface. Raman spectra of sodium benzoate, sodium sulfate, human serum, and human urine were recorded. For the model compounds, spectra obtained by QSM reproduced the Raman shifts of the solid state, whereas spectra of aqueous solutions measured by NM showed clear peak shifts, and the scattered-light intensity increased monotonically with the number of drops on the sheet. Based on these findings, we infer that the samples crystallize and become concentrated within the quartz glass fiber sheet, enabling acquisition of spectra with high scattered-light intensity even from low-concentration solutions. For human serum and urine, QSM increased the intensity of characteristic bands by up to about seven-fold compared with NM while preserving the spectral fingerprints. Our results indicate that a quartz glass fiber sheet is a practical low-background substrate for obtaining FT-Raman spectra of liquid biological samples whose components are present at low concentrations.
Systematic studies were conducted to elucidate the mechanism of splitting and polarization of the Pb Fraunhofer-type absorption (FTA) lines at 363.95 nm and 283.3 nm. These two lines share the same upper absorption level. It was found that the line splittings ΔUobs, expressed in wavenumber units, are proportional to the square root of the second laser pulse intensity.The two lines show similar splittings in wavenumber units, approximately 26.4 and 24.9 cm−1, and the wavelength separation Δλ differs, as expected, proportionally to the square of the central wavelength of the line (Δλ ∝ λ₀2). These results are characteristic of the Autler–Townes (AT) dressed-state mechanism, indicating that this mechanism is responsible for the FTA line splitting and polarization. A simplified AT model is presented. Based on this model, the effective dipole moment of the dressing transition, deff, was estimated. The polarization of the split lines is explained by considering magnetic sublevels m, selection rules, and pump-induced alignment of these sublevels. A strongly polarized absorption line at 285.57 nm, proportional to the second-laser intensity, was also observed. The 285.57 nm line is not listed in spectral databases. We propose that this line may appear due to the resonantly enhanced two-photon absorption (TPA) in Pb I atoms. This transition may be driven coherently by one UV continuum photon and one 1064-nm pump photon in DP LIP. Transitions are driven coherently by one continuum UV photon and one 1064 nm pump photon in Double-Pulse Laser–Induced Plasma (DP LIP). This hypothesis needs additional experimental and theoretical investigations.
