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Engineering SERS Properties of Silicon Nanotrees at the Nanoscale (CROSBI ID 317747)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Gebavi, Hrvoje ; Pál, Petra ; Csarnovics, István ; Gašparić, Vlatko ; Ivanda, Mile ; Engineering SERS Properties of Silicon Nanotrees at the Nanoscale // Chemosensors, 10 (2022), 12; 534, 13. doi: 10.3390/chemosensors10120534

Podaci o odgovornosti

Gebavi, Hrvoje ; Pál, Petra ; Csarnovics, István ; Gašparić, Vlatko ; Ivanda, Mile ;

engleski

Engineering SERS Properties of Silicon Nanotrees at the Nanoscale

Large specific surface area nanostructures are desirable in a wide range of sensing applications due to their longer light-trapping path and increased absorption. Engineering of the specific nanotree structure which possesses a high branch density turned out to be challenging from the experimental point of view, and certainly not adequately explored. This paper shows how to design substrates with a silicon nanotree structure for surface-enhanced Raman spectroscopy (SERS) applications. Silicon nanotrees were synthesized by a Ag-Au nanocluster-catalyzed low- pressure chemical vapor deposition method (LPCVD). By the presented approaches, it is possible to manipulate branches’ number, length and thickness. The synthesized nanostructures are flexible after immersion in water which improves SERS performance. The amount of sputtered metal played a key role in preserving the flexibility of the nanotree structure. The obtained substrates with highly fractal nanostructure were tested on 4- mercaptophenylboronic acid (MPBA) to match the optimal SERS parameters. The silicon nanotrees fabrication, and particularly obtained SERS substrates plated with Ag and Au nanoparticles, demonstrated good features and a promising approach for further sensor development.

surface-enhanced Raman spectroscopy (SERS) ; Si nanotrees ; vapor–liquid–solid (VLS) method ; low-pressure chemical vapor deposition (LPCVD) ; Ag and Au nanoparticles ; 4-mercaptophenylboronic acid detection ; SERS substrates optimization

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Podaci o izdanju

10 (12)

2022.

534

13

objavljeno

2227-9040

10.3390/chemosensors10120534

Povezanost rada

Fizika, Kemija

Poveznice
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