Bolaform Surfactant‐Induced Au Nanoparticle Assemblies for Reliable Solution‐Based Surface‐Enhanced Raman Scattering Detection

Abstract

The SERS enhancement is related to a combination of electromagnetic and chemical effects, being 10 10 a reasonable maximum value for the enhancement factor of the Raman signal. [4] Considering that the electromagnetic effect is the dominant one, the ability to achieve high SERS enhancements, and therefore high sensing capabilities, often relies on the plasmonic efficiency of the metal surface. In this regard, although discrete plasmonic nano particles can obtain reasonable SERS enhancements, their assembly gives rise to higher enhancement factors due to the amplification of the electromagnetic field confined in the gap between closely coupled nanoparticles (known as hot spots). [5] Therefore great effort has been devoted to designing and fabricating different substrates based on the assembly of nanoparticles for direct SERS sensing. Significantly, it is still challenging to synthesize/fabricate substrates with outstanding sensing capabilities in terms of efficiency, uniformity, and reliability. [1,6,7] The simplest approach to induce the assembly/aggregation of the nanoparticles is to produce its destabilization. For instance, the destabilization of charged nanoparticles dispersions, where the interparticle forces are dominated by the van der Waals attraction and the electrostatic double-layer repulsion, occurs by screening the electrostatic Solution-based surface-enhanced Raman scattering (SERS) detection typically involves the aggregation of citrate-stabilized Au nanoparticles into colloidal assemblies. Although this sensing methodology offers excellent prospects for sensitivity, portability, and speed, it is still challenging to control the assembly process by a salting-out effect, which affects the reproducibility of the assemblies and, therefore, the reliability of the analysis. This work presents an alternative approach that uses a bolaform surfactant, B 20 , to induce the plasmonic assembly. The decrease of the surface charge and the bridging effect, both promoted by the adsorption of B 20 , are hypothesized as the key points governing the assembly. Furthermore, molecular dynamic simulations supported the bridging effect of the B 20 by showing the preferential bridging of surfactant monomers between two adjacent Au(111) slabs. The colloidal assemblies showed excellent SERS capabilities towards the rapid, on-site detection and quantification of beta-blockers and analgesic drugs in the nanomolar regime, with a portable Raman device. Interestingly, the application of state-of-the-art convolutional neural networks, such as ResNet, allows a 100% accuracy in classifying the concentration of different binary mixtures. Finally, the colloidal approach was successfully implemented in a millifluidic chip allowing the automation of the whole process, as well as improving the performance of the sensor in terms of speed, reliability, and reusability without affecting its sensitivity.

SERS sensing for cancer biomarker: Approaches and directions

“…For instance, another disadvantage to applying this methodology to real-life samples is the presence of other non-interest molecules that can interfere with the SERS measurement and result in complex data. Fortunately, some classical statistical methods such as principal components analysis (PCA) [ [46] , [47] , [48] ], multivariate analysis [ 49 ], and, more recently, machine learning too [ [50] , [51] , [52] , [53] , [54] , [55] ] allow for separating and differentiating the information from the target analyte considering the full spectral fingerprint. These statistical tools will be of significant relevance when transitioning to the detection of real samples, enabling accurate identification of target analytes even in complex media as well as multiplex detection and quantification of target analytes.…”