Optimization of Nanoparticle-Based SERS Substrates through Large-Scale Realistic Simulations

Surface-enhanced Raman scattering (SERS) has become a widely used spectroscopic technique for chemical identification, providing unbeaten sensitivity down to the singlemolecule level. The amplification of the optical near field produced by collective electron excitations plasmons in nanostructured metal surfaces gives rise to a dramatic increase by many orders of magnitude in the Raman scattering intensities from neighboring molecules. This effect strongly depends on the detailed geometry and composition of the plasmonsupporting metallic structures. However, the search for optimized SERS substrates has largely relied on empirical data, due in part to the complexity of the structures, whose simulation becomes prohibitively demanding. In this work, we use state-of-the-art electromagnetic computation techniques to produce predictive simulations for a wide range of nanoparticle-based SERS substrates, including realistic configurations consisting of random arrangements of hundreds of nanoparticles with various morphologies. This allows us to derive rules of thumb for the influence of particle anisotropy and substrate coverage on the obtained SERS enhancement and optimum spectral ranges of operation. Our results provide a solid background to understand and design optimized SERS substrates.Peer ReviewedPostprint (published version

Preparation and biological investigation of luminescent water soluble CdTe nanoparticles

In this study CdTe quantum dots have been successfully prepared in aqueous medium using several different thiol stabilizers. The resulting nanocrystals were purified and the photoluminescence efficiency was subsequently enhanced through post preparative procedures such as photochemical etching and ageing. An optical study was carried out on the resulting CdTe nanocrystals as proof as their improvement. Preliminary tests of the thiol stabilised QDs as potential biolabels have been performed. It has been shown that L-cysteine stabilised QDs localising to the outer cell membrane in living cells. TGA stabilised CdTe QDs can potentially serve as live cell imaging tools as they exhibit strong luminescence and excellent photostability. In addition, the ability of TGA stabilised CdTe QDs to traverse the cell membrane of macrophages is a formidable quality that may potentially be harnessed for imaging and therapeutics. Modulating the delivery of QDs to subcellular locations in living cells opens a myriad of potential applications ranging from drug delivery to examination of intracellular processes

Rehaussement du signal de parole par EMD et opérateur de Teager-Kaiser

The authors would like to thank Professor Mohamed Bahoura from Universite de Quebec a Rimouski for fruitful discussions on time adaptive thresholdingIn this paper a speech denoising strategy based on time adaptive thresholding of intrinsic modes functions (IMFs) of the signal, extracted by empirical mode decomposition (EMD), is introduced. The denoised signal is reconstructed by the superposition of its adaptive thresholded IMFs. Adaptive thresholds are estimated using the Teager–Kaiser energy operator (TKEO) of signal IMFs. More precisely, TKEO identifies the type of frame by expanding differences between speech and non-speech frames in each IMF. Based on the EMD, the proposed speech denoising scheme is a fully data-driven approach. The method is tested on speech signals with different noise levels and the results are compared to EMD-shrinkage and wavelet transform (WT) coupled with TKEO. Speech enhancement performance is evaluated using output signal to noise ratio (SNR) and perceptual evaluation of speech quality (PESQ) measure. Based on the analyzed speech signals, the proposed enhancement scheme performs better than WT-TKEO and EMD-shrinkage approaches in terms of output SNR and PESQ. The noise is greatly reduced using time-adaptive thresholding than universal thresholding. The study is limited to signals corrupted by additive white Gaussian noise