Development of Zinc Oxide-Sawdust Composite Adsorbent for Methylene Blue Removal: Synthesis, Characterization and Adsorption Mechanism

The natural world provides sawdust, also known as wood shavings, which is a reasonably abundant and affordable lignocellulosic compound. It is a waste product of agriculture and industry that is abundant and has disposal issues. A zinc oxide nanocomposite based on sawdust (ZnO@SD) was synthesized to efficiently remove the dye methylene blue (MB) from aqueous solutions. FTIR, SEM, TEM, and XRD analyses were used to characterize the freshly made sawdust material. Batch optimization of adsorption experimental parameters, including initial dye concentration, contact time, solution pH, temperature, and adsorbent dosage used, to achieve the maximum removal of MB dye from wastewater. For an initial MB dye concentration of 50 mg/L, the ideal parameters for the maximum removal of MB dye from aqueous solution were determined to be: 40 mg of adsorbent, 80 minutes of contact time, a pH of 6.0, and 25°C. The models that best fit the examined experimental data were the Freundlich and pseudo-second order. For the removal of MB dye, the experimental adsorption capacity of ZnO@SD was found to be 372.5 mg/g. According to the obtained results, the sawdust composite was thought to be a low-cost and efficient adsorbent for dye removal.

Authors

Institutions

Publication Details

Journal
Nature Environment and Pollution Technology
Published
2026-02-04
DOI
https://doi.org/10.46488/nept.2026.v25i01.b4331
Primary Topic
Adsorption and biosorption for pollutant removal
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of Zinc Oxide-Sawdust Composite Adsorbent for Methylene Blue Removal: Synthesis, Characterization and Adsorption Mechanism

Anil K. Berwal, Romit Antil
Nature Environment and Pollution Technology
Adsorption and biosorption for pollutant removal
article

Development of Zinc Oxide-Sawdust Composite Adsorbent for Methylene Blue Removal: Synthesis, Characterization and Adsorption Mechanism

Anil K. Berwal, Romit Antil
article en

Abstract

The natural world provides sawdust, also known as wood shavings, which is a reasonably abundant and affordable lignocellulosic compound. It is a waste product of agriculture and industry that is abundant and has disposal issues. A zinc oxide nanocomposite based on sawdust (ZnO@SD) was synthesized to efficiently remove the dye methylene blue (MB) from aqueous solutions. FTIR, SEM, TEM, and XRD analyses were used to characterize the freshly made sawdust material. Batch optimization of adsorption experimental parameters, including initial dye concentration, contact time, solution pH, temperature, and adsorbent dosage used, to achieve the maximum removal of MB dye from wastewater. For an initial MB dye concentration of 50 mg/L, the ideal parameters for the maximum removal of MB dye from aqueous solution were determined to be: 40 mg of adsorbent, 80 minutes of contact time, a pH of 6.0, and 25°C. The models that best fit the examined experimental data were the Freundlich and pseudo-second order. For the removal of MB dye, the experimental adsorption capacity of ZnO@SD was found to be 372.5 mg/g. According to the obtained results, the sawdust composite was thought to be a low-cost and efficient adsorbent for dye removal.

Nature Environment and Pollution TechnologyVol. 25(1)
Deenbandhu Chhotu Ram University of Science and Technology (IN)
Deenbandhu Chhotu Ram University of Science and Technology
Zero hunger
Openalex Percentile: Top 62%
Adsorption and biosorption for pollutant removal
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.