Au Nanoparticles on Superhydrophobic Scaffolds for Large-Area Surface-Enhanced Raman Scattering Substrates

The efficient development of reliable surface -enhanced Raman scattering (SERS)-active plasmonic substrates containing hot spots via an extremely facile, simple, cost-effective method remains challenging in terms of batch-to-batch reprodu-cibility and large-scale homogeneity. Herein, a universal, single-step strategy to transform superhydrophobic (SH) surfaces to large, label-free SERS substrates using Au nanoparticles (NPs) is developed. The transformed superhydrophobic (TSH) substrate with SERS characteristics was named as TSH-SERS platform. Three-dimensional (3D) stacked Au NPs with double-nanoareole structures are mounted on the 3D quasi-network with micro-/ nanostructures, which serves as a skeleton. The SH surface with typical 3D quasi-network with micro-/nanostructures serves as a skeleton to tailor complex hierarchical structures for Au NP deposition. As the 3D stacked Au NPs with double-nanoareole structures did not alter the overall morphology of the SH surface at the micrometer level, the TSH-SERS substrates not only provided uniform, dense hot spots but also enabled the homogenized concentration of the diluted analytes with the aid of surface hydrophobility. In this work, only 5 mu L of pure analyte is used in label -free SERS assay, and the final spot is uniformly distributed on the 3D plasmonic film without a "coffee-ring" effect during evaporative enrichment. TSH-SERS is evaluated through the quantitative SERS detection of Raman probes, bioanalytes, and pesticides in a serial concentration gradient to the picomolar level. Our strategy provides versatile routes for the facile transformation of various SH substrates into large, efficient 3D plasmonic films with double-nanoareole structures as cost-effective SERS platforms. The reliable detection also demonstrates the applicability of the TSH-SERS platform for the emerging demands for sensitive and high-throughput detection in practical applications, including biological sensing and environmental pollution monitoring.