Controlled synthesis of Cu nanoparticle arrays with surface enhanced Raman scattering effect performance

DFT Study of the Adsorption and SERS of Pyridine on M10N10 (M, N = Cu, Ag) Tetrahedral Clusters

This work presents a theoretical detailed analysis of the surface-enhanced Raman spectroscopy (SERS) of the pyridine-M10N10 (M, N = Ag, Cu) tetrahedral (Td) clusters considering two binding positions: vertex (V) and surface (S). In addition to the well-known monometallic Td structure, we added two different bimetallic Ag-Cu compositions, named Td1 and Td2 geometries. Density functional methodology with the use of BP86 and CAM-B3LYP exchange-correlation functionals (XCs) and LANL2DZ pseudopotential has been employed for analyzing the electronic structure and geometries, the chemical static (CHEM), and resonant Raman mechanisms (RR): charge transfer RR-CT and intracluster excitation RR-CR. The static CHEM mechanism shows an increase in the enhancement factors (EFs) of Py-V concerning Py-S positions, which can also be distinguished by the averaged adsorption energies and bond polarizabilities. The static SERS response for Cu-Py-V junction is from 5 to 10 times greater than Ag-Py-V EFs and up to 28 times greater than Py-S complexes. For the static Raman, we found that the analyses of ν8a and ν1 normal modes are related to the EF changes and allow us to distinguish V from S complexes. The TDDFT calculations show striking differences between BP86 and CAM-B3LYP XCs analyzed spectra, and CAM-B3LYP granted a clear distinction between V and S for the location of CT-type transitions. In addition, important differences were obtained from the analysis of the charge transfer excitations between both XCs. Resonant Raman calculations evidenced significant enhancements for RR-CT and RR-CR as compared to the static enhancements, and RR-CT can be distinguished from the RR-CR mechanism, while specific normal modes help to differentiate the vertex from the surface Py-junction. Bimetallic Ag-Cu nanostructures represent promising choices for SERS substrates, showing EFs higher than those of monometallic Ag.

Lattice Mismatch-Induced Formation of Copper Nanoplates with Embedded Ultrasmall Platinum or Palladium Cores for Tunable Optical Properties

Although noble metal nanocrystals have been studied extensively in the past decades, the shape-controlled synthesis of non-noble metal nanocrystals has remained challenging with limited success, which is a grand obstacle to their wide applications. Herein, a novel lattice mismatch-involved shape-control mechanism of Cu nanocrystals in a seed-mediated synthesis is reported, which can produce Cu nanoplates in high yield with tailored sizes (28-130 nm), holding great potential in optical and catalytic applications. The lattice mismatch between Cu and the seed is found effective in inducing crystallographic defects for symmetry breaking toward anisotropic nanocrystals. While a too-large lattice mismatch (11.7% for Au seeds) leads to multiple twin defects to form quasi-spherical Cu nanocrystals, an appropriately large lattice mismatch (7.7% for Pt and 6.9% for Pd seeds) successfully induces planar defects for the formation of Cu nanoplates. The size of the Cu nanoplates is customizable by controlling the concentration of the seeds, leading to tunable optical properties. A prototype of a colorimetric indicator with Cu nanoplates, potentially applicable to the safety control of foods and drugs is demonstrated. This mechanism paves a new way for the shape-controlled synthesis of Cu and other metal nanocrystals for a broad range of applications.

Highly Sensitive and Stable Copper-Based SERS Chips Prepared by a Chemical Reduction Method

Cu chips are cheaper than Ag and Au chips for practical SERS applications. However, copper substrates generally have weak SERS enhancement effects and poor stability. In the present work, Cu-based SERS chips with high sensitivity and stability were developed by a chemical reduction method. In the preparation process, Cu NPs were densely deposited onto fabric supports. The as-prepared Cu-coated fabric was hydrophobic with fairly good SERS performance. The Cu-coated fabric was able to be used as a SERS chip to detect crystal violet, and it exhibited an enhancement factor of 2.0 × 106 and gave a limit of detection (LOD) as low as 10-8 M. The hydrophobicity of the Cu membrane on the fabric is favorable to cleaning background interference signals and promoting the stability of Cu NPs to environment oxidation. However, this Cu SERS chip was still poor in its long-term stability. The SERS intensity on the chip was decreased to 18% of the original one after it was stored in air for 60 days. A simple introduction of Ag onto the clean Cu surface was achieved by a replacement reaction to further enhance the SERS performances of the Cu chips. The Ag-modified Cu chips showed an increase of the enhancement factor to 7.6 × 106 due to the plasmonic coupling between Cu and Ag in nanoscale, and decreased the LOD of CV to 10-11 M by three orders of magnitude. Owing to the additional protection of Ag shell, the SERS intensity of the Cu-Ag chip after a two-month storing maintained 80% of the original intensity. The Cu-Ag SERS chips were also applied to detect other organics, and showing wide linearity range and low LOD values for the quantitative detection.

SERS-Active Cu Nanoparticles on Carbon Nitride Support Fabricated Using Pulsed Laser Ablation

We report a single-step route to co-deposit Cu nanoparticles with a graphitic carbon nitride (gCN) support using nanosecond Ce:Nd:YAG pulsed laser ablation from a Cu metal target coated using acetonitrile (CH3CN). The resulting Cu/gCN hybrids showed strong optical absorption in the visible to near-IR range and exhibited surface-enhanced Raman or resonance Raman scattering (SERS or SERRS) enhancement for crystal violet (CV), methylene blue (MB), and rhodamine 6G (R6G) used as probe analyte molecules adsorbed on the surface. We have characterized the Cu nanoparticles and the nature of the gCN support materials using a range of spectroscopic, structural, and compositional analysis techniques.