Microbiological contamination of water and food remains a pressing concern in public health, the environment, and industry, largely due to the ability of bacteria to form biofilms that confer high resistance to antibiotics and disinfectants. One promising strategy to address this challenge involves the design of bioinspired surfaces combined with advanced analytical methods. This study investigated how the morphology and surface density of metal nanostructures influence bacterial adhesion and colonization by employing bioinspired patterns and micro-structured polydimethylsiloxane (PDMS) substrates. Model strains of Lactobacillus acidophilus , Lactobacillus casei , and Lactococcus lactis were characterized using surface-enhanced Raman spectroscopy (SERS) with complementary multivariate analysis. Results indicated that the Asian Lilium-inspired surface exhibited the strongest aseptic effect, significantly reducing bacterial adhesion and colonization compared with microstructured PDMS, which was more prone to microbial accumulation. Among the multivariate approaches, the support vector machine (SVM) model achieved superior predictive performance and sensitivity (R 2 Cal = 0.9999; R 2 CV = 0.958), with an estimated detection limit of approximately 3 × 10 1 CFU/mL; the partial least squares (PLS) model exhibited a practical detection of approximately 1.7 × 10 2 CFU/mL. Collectively, these findings demonstrate that integrating bioinspired substrates with SERS and advanced statistical models offers a robust, non-invasive approach to bacterial detection, with potential applications in microbiology, food safety, and environmental monitoring.
While handheld Raman spectroscopy is typically used for bulk material identification, it is rarely viewed as a tool for trace chemical analysis (nanogram to microgram) of powders due to the inherent challenges associated with the low interaction volume of the laser with dispersed particulate samples. Our study challenges this convention by demonstrating that with appropriate spatial confinement, commercial handheld systems can achieve detection limits in the single-nanogram range. We experimented with two approaches for sample confinement. One was to use inkjet-printed deposits on aluminum substrates. This produced a hemispherical deposit with micrometer dimensions, to simulate trace contraband particles, where we were able to successfully identify pure explosives and drugs with mass loadings as low as 2 ng to 17 ng, depending on the compound. Another was to physically confine the sample by preparing a novel testbed of laser-drilled silicon microwells with depths varying from 25 µm to 500 µm for packing pure contraband powders. In addition to achieving tens of nanograms in sensitivity, this allowed us to determine the effective sampling depth of the Raman probe at approximately 100 µm, beyond which any additional sample will not increase the signal. Also, the plot suggested that the minimum bulk film thickness for detection was in the order of tens of micrometers. These observations suggest that trace chemical screening for pure substances such as fine powders on a surface is feasible given appropriate sample collection and preconcentration methods to maximize the analytical thickness of the trace sample.
This study explores the electric field assisted laser induced breakdown spectroscopy (EF-LIBS) for rapid, sensitive and repeatable elemental characterization of industrial grade Al–Si alloy highlighting its potential in forensic applications. Laser-induced plasma was generated using a Q-switched Nd: YAG laser (532 nm, 300 mJ, 10 Hz) under an external electric field of 120 V/mm. The applied electric field significantly enhanced the emission intensity, improving both the qualitative and quantitative elemental detection. Plasma diagnostics revealed an increase in electron temperature from 7615 ± 800 K to 10857 ± 1100 K, while the electron number density increased from 8.81 × 10 17 cm −3 to 10.9 × 10 17 cm −3 under local thermodynamic equilibrium conditions. The plasma frequency and inverse Bremsstrahlung coefficient were calculated as 9.4 × 10 12 Hz and 9.58 × 10 6 cm −1 respectively, demonstrating enhanced laser–plasma energy coupling. EF-LIBS enabled detection of major (Al), minor (Si, Cu, Fe), and trace elements including Mg, Mn, Ni, Ti, Cr, Pb, and Ga with substantially enhanced sensitivity. A maximum thirteenfold signal enhancement factor (SEF) was observed in integrated intensity of Mg II (279.55 nm) line under EF-LIBS. The relative standard deviation (RSD) for Al (394.4 nm) emission line decreased from 10.97% to 3.02% and for Si (288.16 nm) emission line decreased from 14.55% to 3.48%, demonstrating remarkable improvement in signal repeatability and stability. Quantitative analysis using one-line calibration-free (OL-CF) LIBS showed strong agreement with SEM-EDS and industrial reference values. These trace elemental signatures possess substantial forensic importance because elemental impurity profiling can be used for source attribution, discrimination of metallic fragments, identification of counterfeit automotive and firearm components, optimization of serial number restoration reagents, and comparative analysis of gunshot residue (GSR), explosives, paint, and glass evidence. Detection of Pb, Cr, Ni, and Ga at trace levels further demonstrates the capability of EF-LIBS for forensic trace evidence analysis and material fingerprinting.
The aim of this study was to thoroughly investigate the physicochemical properties, including changes in antioxidant and biochemical properties, of ommochromes from insect eyes undergoing biological reversibility during their redox reactions. The biological function of ommochromes in the complex ocular structures of insects and other invertebrates may be related to their antioxidant properties due to reversible redox processes. In this study, we examined the reversible redox processes of ommochromes isolated from the eyes of the black soldier fly (Hermetia illucens) and the eyes of the tobacco hawk moth (Manduca sexta). Reversible changes in the spectral and fluorescent properties, as well as the composition of ommochromes during redox reactions, were investigated using IR spectroscopy, CARS spectroscopy, and fluorescence spectroscopy. Nearly complete reduction of oxidized ommochromes from fly eye was demonstrated using HPLC chromatography and mass spectrometry. Changes in the redox properties of ommochromes lead to structural changes that affect their ability to exhibit antioxidant properties—reduced ommochromes exhibited significantly higher antioxidant activity compared to oxidized ommochromes. The reversibility of redox transitions of ommochromes is important for regulating the spectral sensitivity and antioxidant status of the invertebrate eye.
Singular Value Decomposition (SVD) is a primary tool for exploratory analysis and for separating signal from noise and background in spectroscopic data, but it does not account for baseline variation. Standard SVD can assign to baseline features singular values comparable in magnitude to those of genuine chemical components, obscuring the boundary between signal and noise in the singular value spectrum and complicating determination of the chemical rank. This Note describes a preprocessing-enhanced SVD algorithm in which a Fourier-domain first-derivative transformation is combined with weights derived from the noise present in the data before the decomposition is performed, suppressing baseline contributions without loss of true signal components. The abstract spectra and time-traces are returned to the original spectral and temporal domains by inverse transformation, and a sign-ambiguity resolution procedure based on correlation coefficients is included. The algorithm is demonstrated on both synthetic and experimental time-dependent FTIR spectroscopic data. Relative to standard SVD, the enhanced decomposition yields a flat noise floor beyond the retained components, confining the baseline contribution to the discarded subspace rather than dispersing it through the low-rank subspace, and the recovered abstract spectral and temporal vectors carry less baseline contamination. Although demonstrated with time-dependent FTIR data, the algorithm applies to any variable-dependent spectroscopic measurement that can be organized as a two-way matrix. The implementation is released as open-source software.
