Modeling of Adsorption of Copper on Activated Leaf-Based Biomass using Response Surface Methodology (RSM)

Yudi Sukmono, Wei Jie Ngu, Tony Hadibarata, Muhammad Syafrudin

Research output: Contribution to journalArticlepeer-review


Due to rapid development, heavy metal pollution has resulted in water pollution, causing a reduction in water sources. Hence, remediation actions should be taken to remove heavy metals. Adsorption is a physical remediation that is cost-effective and efficient in heavy metal removal. Developing adsorbents from low-cost materials, including leaves, could reduce the remediation cost. In this research, four types of leaves were collected and activated chemically into the adsorbents. The adsorbent with the highest adsorption capacity was determined through adsorbent screening, and the selected adsorbent was used in the following equilibrium study, batch study, and Fourier-Transform Infrared Spectroscopy analysis. Central composite design in Design Expert was used to design the batch study. Mango leaves adsorbent was found to have the highest adsorption capacity. The equilibrium time for copper and lead adsorptions was found to be 20 minutes and 30 minutes, respectively. The functional groups on adsorbents were identified by FTIR analysis. The fittest adsorption isotherm and adsorption kinetics were found to be Langmuir isotherm and Pseudo-second-order kinetic model. The Langmuir adsorption capacity constant was found as 12.7139 mg/g for copper adsorption. This leaf powder is valuable since they are green, economical, and easy to prepare with a simple design biosorption technique.

Original languageEnglish
Article number490
JournalBiointerface Research in Applied Chemistry
Issue number5
StatePublished - 15 Oct 2023


  • adsorption
  • chemical activation
  • heavy metal remediation
  • low-cost adsorbents


Dive into the research topics of 'Modeling of Adsorption of Copper on Activated Leaf-Based Biomass using Response Surface Methodology (RSM)'. Together they form a unique fingerprint.

Cite this