Thin layer chromatography coupled with surface enhanced Raman scattering for rapid separation and on-site detection of multi-components

The separation and detection of multi-component mixtures has always been a challenging task. Traditional detection methods often suffer from complex operation, high cost, and low sensitivity. Surface enhanced Raman scattering (SERS) technique is a high sensitivity, powerful and rapid detection tool, which can realize the specific detection of single substance components, but it must solve the problem that multi-component mixtures cannot be accurately determined. Thin layer chromatography (TLC) technology, as a high-throughput separation technology, uses chromatographic plate as the stationary phase, and could select different developing phases for separation experiments. The advantages of TLC technology in short distance and rapid separation are widely used in protein, dye and biomedical fields. However, TLC technology has limitations in detection ability and difficulty in obtaining ideal signal intensity. The combination of TLC technology and SERS technology made the operation procedure simple and the sample size small, which can achieve rapid on-site separation and quantitative detection of mixtures. Due to the rapid development of TLC-SERS technology, it has been widely used in the investigation of various complex systems. This paper reviews the application of TLC-SERS technology in food science, environmental pollution and biomedicine.

Functional cotton fabric-based TLC-SERS matrix for rapid and sensitive detection of mixed dyes

A facile cotton fabric with a built-in TLC-SERS structure was fabricated to demonstrate an integrated TLC separation and SERS identification of mixed dyes. The soft and flexible SERS fabric was firstly fabricated using a simple method in which gold nanoparticles were in-situ synthesized on cotton fabrics by heating. β-CD was then grafted onto cotton fabric through crosslinking with citric acid in presence of sodium hypophosphite monohydrate via esterification reaction. The adsorption and TLC development performance of β-CD grafted fabrics were comprehensively investigated with two organic dyes, one anionic dye and one nonionic dye. Besides, the recyclable adsorption and separation performance were tested to evaluate its sustainable application prospects. It displayed less adsorption capacity loss and reusable separation performance after several cycles than the pristine cotton fabrics. Finally, two sets of mixed dyes were successfully separated on the TLC fabrics and then identified via on-site SERS according to their different migration distance. The developed TLC-SERS fabric shows the advantage of quick, easy to handle, low-cost, sensitive, and could be exploited in on-site study of synthetic dyes in art objects, textile and packaging products or forensic applications.

Review of Thin-Layer Chromatography Tandem with Surface-Enhanced Raman Spectroscopy for Detection of Analytes in Mixture Samples

In the real world, analytes usually exist in complex systems, and this makes direct detection by surface-enhanced Raman spectroscopy (SERS) difficult. Thin layer chromatography tandem with SERS (TLC-SERS) has many advantages in analysis such as separation effect, instant speed, simple process, and low cost. Therefore, the TLC-SERS has great potential for detecting analytes in mixtures without sample pretreatment. The review demonstrates TLC-SERS applications in diverse analytical relevant topics such as environmental pollutants, illegal additives, pesticide residues, toxic ingredients, biological molecules, and chemical substances. Important properties such as stationary phase, separation efficiency, and sensitivity are discussed. In addition, future perspectives for improving the efficiency of TLC-SERS in real sample detecting are outlined.

Freeze Surface-Enhanced Raman Scattering Coupled with Thin-Layer Chromatography: Pesticide Detection and Quantification Case

Thin-layer chromatography (TLC) is widely used in various branches of chemical science to separate components in complex mixtures because of its simplicity. In most cases, analyte spots are visually detected by fluorescence, and the retention factor (R_f) is determined from the distance traveled by the analyte. Further characterizations are often necessary to identify separated chemicals because molecular information other than R_f is not available. Surface-enhanced Raman scattering (SERS) has been coupled with TLC to complement molecular information. In previously reported TLC-SERS, metal nanoparticle suspension was dropped onto analyte spots to obtain SERS spectra. This approach is simple and efficient for SERS measurements on the TLC plate but has limited sensitivity for several reasons, such as the low solubility of analytes in the dropped solution, difficult control of nanoparticle aggregation, and interference from the stationary phase. We recently showed that freezing enhances SERS sensitivity by a factor of ∼10³. Freezing simultaneously concentrates analytes and silver nanoparticles (AgNPs) in a freeze concentrated solution, where aggregation of AgNPs is facilitated, allowing sensitive freeze SERS (FSERS) measurements. Here, we discuss FSERS measurements on TLC plates to demonstrate the superiority of this combination, i.e. TLC-FSERS. Freezing enhances SERS sensitivity by freeze concentration and facilitated aggregation of AgNPs and, in addition, eliminates interference from the stationary phase. Under the optimized condition, TLC-FSERS enables the on-site detection of pesticides at the nM level. The use of the SERS signal from adenine added as the internal standard allows us to quantify pesticides. Applications to a commercial green tea beverage are also demonstrated.

Multiplex Sensing of Complex Mixtures by Machine Vision Analysis of TLC-SERS Images

Thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) has demonstrated tremendous potentials as a new analytical chemistry tool to detect a wide range of substances from real-world samples. However, it still faces significant challenges of multiplex sensing from complex mixtures due to the imperfect separation by TLC and the resulting interference of SERS detection. In this article, we propose a multiplex sensing method of complex mixtures by machine vision analysis of the scanning image of the TLC-SERS results. Briefly, various pure substances in solution and the complex mixture solution are separated by TLC followed by one-dimensional SERS scanning of the entire TLC plate, which generates TLC-SERS images of all target substances along the chromatography path. After that, a machine vision method is employed to extract the template images from the TLC-SERS images of pure substance solutions. Finally, we apply a feature point matching strategy based on the Winner-take-all principle, which matches the template image of each pure substance with the mixture image to confirm the existence and derive the position of each target substance in the TLC plate, respectively. Our experimental results based on the mixture solution of five different substances show that the proposed machine vision analysis is highly selective, sensitive and does not require artificial analysis of the SERS spectra. Therefore, we envision that the proposed machine vision analysis of the TLC-SERS imaging is an objective, accurate, and efficient method for multiplex sensing of trace level of target substances from complex mixtures.