The excessive use of antibiotics in medicine, agriculture, and aquaculture has led to widespread environmental contamination and public health concerns, underscoring the urgent need for rapid, sensitive, and cost-effective detection methods. Here, we report a scalable surface-enhanced Raman scattering (SERS) platform based on silver-coated cross-scanned laser-induced periodic surface structures (CS-LIPSS) fabricated via femtosecond laser processing. By employing cylindrical lens-assisted beam shaping followed by orthogonal double-pass scanning, we generated periodic nanostructures enriched with dense nanoparticles. Subsequent Ag deposition produce a dense distribution of plasmonic hotspots, enabling strong electromagnetic enhancement. Compared with conventional mesh and single-scanned LIPSS substrates, the CS-LIPSS demonstrate superior SERS activity, with an enhancement factor of 6.4×107 and a detection limit down to 10-11 M for crystal violet. More importantly, the platform enable reliable identification of representative antibiotics including amoxicillin, tetracycline, and neomycin sulfate at concentrations as low as 1 ppm, highlighting its sensitivity and molecular specificity. The fabrication process is chemical-free, template-free, and compatible with wafer-scale production, offering a cost-effective route to reproducible, high-performance SERS substrates.
Jian-Jun Cao, Haoyue Yang, Tao-Hua Zhou et al.· Spectrochimica Acta Part A -...· 0 citations
Non-uniform illumination in tunnel environments severely degrades image quality, posing substantial challenges to visual monitoring and intelligent transportation systems. While histogram equalization (HE) remains prevalent due to its computational simplicity, its non-linear pixel transformations frequently induce over-enhancement, artifacts, and structural distortions. This paper proposes Prior-Guided Histogram Equalization (PGHE), a lightweight enhancement framework that integrates conventional HE with Retinex-based illumination priors. Within the Retinex decomposition paradigm, PGHE constructs a contrast illumination map from the ratio between the HE-enhanced image and the original input. A Prior Correction Module (PCM) subsequently refines this map via relative total variation regularization, thereby restoring spatial coherence and alleviating local discontinuities introduced by HE. The corrected map is then applied to the original image to obtain the final enhanced result. Extensive evaluation on the LOL low-light benchmarks and a proprietary tunnel dataset comprising 247 real-world frames shows that PGHE offers favorable trade-offs among contrast enhancement, structural fidelity, and brightness preservation: it is particularly strong in brightness preservation and Entropy, while its PSNR/SSIM on LOL and its NIQE on the tunnel dataset are comparable to, but not always the best among, the compared methods. Furthermore, the proposed PCM functions as a plug-in module that improves existing HE variants with measurable gains in Structural Similarity and perceived naturalness at a modest cost in Absolute Mean Brightness Error.
