pyAPEP: An all-in-one software package for the automated preparation of adsorption process simulations

Ga, Seongbin; An, Nahyeon; Joo, Chonghyo; Kim, Junghwan

doi:10.1016/j.cpc.2023.108830

Cited by 1 publication

(1 citation statement)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, the oil agent was absorbed into biochar microspheres efficiently. In this process, the introduced alkyl chains from lauric acid, pore structures, and a high degree of graphitization improved its adsorption efficiency [ 28 ].…”

Section: Resultsmentioning

confidence: 99%

Preparation of Biochar Composite Microspheres and Their Ability for Removal with Oil Agents in Dyed Wastewater

Shen,

Jin,

Chen

et al. 2023

Materials

View full text Add to dashboard Cite

Oil agents produced from the degreasing treatment of synthetic fibers are typical pollutants in wastewater from printing and dyeing, which may cause large-scale environmental pollution without proper treatment. Purifying oily dye wastewater (DTY) at a low cost is a key problem at present. In this study, biochar microspheres with oil removal ability were prepared and derived from waste bamboo chips using the hydrothermal method. The structure of the biochar microsphere was regulated by activation and modification processes. Biochar microspheres were characterized, and their adsorption behaviors for oily dye wastewater were explored. The results show that the adsorption efficiency of biochar microspheres for oily dye wastewater (DTY) was improved significantly after secondary pyrolysis and the lauric acid grafting reaction. The maximum COD removal quantity of biochar microspheres for DTY was 889 mg/g with a removal rate of 86.06% in 30 min. In addition, the kinetics showed that chemisorption was the main adsorption manner. Considering the low cost of raw materials, the application of biochar microspheres could decrease the cost of oily wastewater treatment and avoid environmental pollution.

show abstract

Section: Resultsmentioning

confidence: 99%