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- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
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Received May 24, 2022
Revised December 6, 2022
Accepted December 16, 2022
- Acknowledgements
- Authors acknowledged the Deputy for Strengthening Research and Development, National Research and Innovation Agency, Indonesia for the financial support No: 187-08/UN7.6.1/PP/2021.
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Synthesis of graphene-like material derived from biomass from agricultural waste and its application in Cu (II) removal
1Department of Chemical Engineering, Faculty of Engineering, Universitas Diponegoro, Tembalang, Semarang, Indonesia 2SDGs Center, Universitas Diponegoro, Tembalang, Semarang, Indonesia 3Departemen of Chemistry, Faculty of Science and Mathematics, Universitas Diponegoro, Tembalang, Semarang, Indonesia
Korean Journal of Chemical Engineering, April 2023, 40(4), 964-974(11), 10.1007/s11814-023-1380-8
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Abstract
The conversion of biomass from agricultural waste into valuable chemicals and materials is in the need,
considering the growing demand for chemicals and materials originating from renewable resources. In this paper the
feasibility of graphene-like materials preparation from biomass namely sugarcane bagasse, rice husk, coconut shell, and
sawdust using modified Hummers methods was investigated. The application of the graphene-like materials resulting
from the process in the Cu (II) removal via adsorption route was also studied. The characterization of samples shows
the materials produced from sugarcane bagasse and coconut shells depict the pattern of reduced graphene oxide (rGO),
while the materials derived from rise husk and sawdust follow the pattern of graphene. The synthesized graphene-like
materials later were used as an adsorbent for Cu (II) removal. The results shows that graphene-like materials from sugarcane bagasse and coconut shells give the highest adsorption reaction kinetics with 19.76 and 19.34 mg/g, respectively,
by following the second-order-pseudo model and the adsorption isotherm fitted the Langmuir model.
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