Green Synthesis of Copper Oxide Nanoparticles Using Rauvolfia serpentina Root Extract and its Characterization

The development of sustainable and environmentally benign methods for nanoparticle synthesis is of growing importance in nanotechnology. In this study, copper oxide (CuO) nanoparticles were synthesized using Rauvolfia serpentina root extract, a dark brown coloured solution acts as a natural reducing and stabilizing agent. The color change of the reaction mixture (dark brown to dark maroon red) and the biosynthesized plant extract show a characteristic absorption peak at 334 nm in UV?Vis spectroscopy, confirming nanoparticle formation. The sharp peaks in the FTIR analysis at 1083 cm?? and 1045 cm?? indicated the involvement of phytochemicals such as phenolics, alkaloids, and flavonoids in the reduction and capping processes. X-ray diffraction (XRD) analysis revealed that the nanoparticles exhibited a monoclinic CuO crystal structure (JCPDS 48-1548) with crystallite sizes in the 20?30 nm range, as estimated by the Scherrer equation. Scanning electron microscopy (SEM) revealed predominantly spherical nanoparticles with average particle sizes ranging from 40 to 80 nm, consistent with XRD findings. These findings highlight the potential applications of biogenic CuO nanoparticles in catalysis, antimicrobial activity, sensors, environmental remediation, and energy storage, while aligning with the principles of green chemistry.

Authors

Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2025-09-30
DOI
https://doi.org/10.21275/sr25923151727
Primary Topic
Copper-based nanomaterials and applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Green Synthesis of Copper Oxide Nanoparticles Using Rauvolfia serpentina Root Extract and its Characterization

Malika Rani, Z T Anitha Krupanidhi
International Journal of Science and Research (IJSR)
Copper-based nanomaterials and applications
article

Green Synthesis of Copper Oxide Nanoparticles Using Rauvolfia serpentina Root Extract and its Characterization

Malika Rani, Z T Anitha Krupanidhi
article en

Abstract

The development of sustainable and environmentally benign methods for nanoparticle synthesis is of growing importance in nanotechnology. In this study, copper oxide (CuO) nanoparticles were synthesized using Rauvolfia serpentina root extract, a dark brown coloured solution acts as a natural reducing and stabilizing agent. The color change of the reaction mixture (dark brown to dark maroon red) and the biosynthesized plant extract show a characteristic absorption peak at 334 nm in UV?Vis spectroscopy, confirming nanoparticle formation. The sharp peaks in the FTIR analysis at 1083 cm?? and 1045 cm?? indicated the involvement of phytochemicals such as phenolics, alkaloids, and flavonoids in the reduction and capping processes. X-ray diffraction (XRD) analysis revealed that the nanoparticles exhibited a monoclinic CuO crystal structure (JCPDS 48-1548) with crystallite sizes in the 20?30 nm range, as estimated by the Scherrer equation. Scanning electron microscopy (SEM) revealed predominantly spherical nanoparticles with average particle sizes ranging from 40 to 80 nm, consistent with XRD findings. These findings highlight the potential applications of biogenic CuO nanoparticles in catalysis, antimicrobial activity, sensors, environmental remediation, and energy storage, while aligning with the principles of green chemistry.

International Journal of Science and Research (IJSR)
Openalex Percentile: Top 79%
Copper-based nanomaterials and applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.