Year: 2023

Defective Graphene/Plasmonic Nanoparticle Hybrids for Surface-Enhanced Raman Scattering Sensors

Biroju Ravi K., Marepally Bhanu Chandra, Malik Pariksha, Dhara Soumen, Gengan Saravanan, Maity Dipak, Narayanan Tharangattu N., Giri Pravat K.

In: ACS Omega 2023, 8, 4, 4344–4356, (2023)

https://doi.org/10.1021/acsomega.2c07706

Abstract

Two-dimensional–zero-dimensional plasmonic hybrids involving defective graphene and transition metals (DGR-TM) have drawn significant interest due to their near-field plasmonic effects in the wide range of the UV–vis–NIR spectrum. In the present work, we carried out extensive investigations on resonance Raman spectroscopy (RRS) and localized surface plasmon resonance (LSPR) from the various DGR-TM hybrids (Au, Ag, and Cu) using micro-Raman, spatial Raman mapping analysis, high-resolution transmission electron microscopy (HRTEM), and LSPR absorption measurements on defective CVD graphene layers. Further, electric field (E) mappings of samples were calculated using the finite domain time difference (FDTD) method to support the experimental findings. The spatial distribution of various in-plane and edge defects and defect-mediated interaction of plasmonic nanoparticles (NPs) with graphene were investigated on the basis of the RRS and LSPR and correlated with the quantitative analysis from HRTEM, excitation wavelength-dependent micro-Raman, and E-field enhancement features of defective graphene and defective graphene-Au hybrids before and after rapid thermal annealing (RTA). Excitation wavelength-dependent surface-enhanced Raman scattering (SERS) and LSPR-induced broadband absorption from DGR-Au plasmonic hybrids reveal the electron and phonon interaction on the graphene surface, which leads to the charge transfer from TM NPs to graphene. This is believed to be responsible for the reduction in the SERS signal, which was observed from the wavelength-dependent Raman spectroscopy/mappings. We implemented defective graphene and DGR-Au plasmonic hybrids as efficient SERS sensors to detect the Fluorescein and Rhodamine 6G molecules with a detection limit down to 10–9 M. Defective graphene and Au plasmonic hybrids showed an impressive Raman enhancement in the order of 108, which is significant for its practical application.

Effect of surface roughness on laser surface alloying of additively manufactured 17-4PH stainless steel

A.S. Chaus, O.G. Devoino, M. Sahul, Ľ. Vančo, I. Buranský, M. Kusý

In: Surface & Coatings Technology. Vol. 454, (2023)

https://doi.org/10.1016/j.surfcoat.2022.129161

Abstract

In the present work, the evolution of the final microstructure in 17-4PH stainless steel additively manufactured and subjected to the laser surface alloying with boron and nitrogen is described with special emphasis on the influence of surface topography and roughness. It was shown that character of the surface topography, and hence the surface roughness of the additively manufactured samples plays a major role in the development of microstructure during laser surface alloying. Dendritic microstructure of a solid solution with a small amount of eutectic in the interdendritic space was observed in a laser-melted zone (LMZ) of so-called smooth samples. In contrast, fully eutectic microstructure was revealed in the LMZ of the rough samples. This resulted in significantly different microhardness of the LMZ of both samples, i.e. 317.0 ± 12.7 and 636.7 ± 18.5 HV0.1 for the smooth and rough samples. The microstructural features and varying microhardness were found to be attributed to the different degree of the steel alloying primarily with boron in the LMZ, significantly affected by the initial roughness of the sample surface. This mechanism can be used to enhance laser surface alloying of the additively manufactured products.