Mathematical modelling of the influence of physico-chemical properties on heavy metal adsorption by biosorbents.

Clicks: 275
ID: 106995
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #184 of 409 articles by views in Chemosphere

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 409 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Adsorption rate is a critical parameter in the design of effective biosorbent treatment systems for heavy metals removal. Though numerous studies have identified the physico-chemical properties of biosorbents that exert influence on the adsorption rate, such influence has not been mathematically defined, limiting the effective design of adsorption systems. This study quantifies the influence of biosorbent physico-chemical properties including, specific surface area, surface functional groups, pore size, pore volume and zeta potential on the adsorption rate in relation to three divalent metal cations. Mathematical equations were developed to predict the influence of physico-chemical properties on pseudo second order kinetic constant and thereby predict the adsorption rate. Tea factory waste and coconut shell biochar were mixed in different weight percentages to vary the physico-chemical properties under consideration. Four different initial metal ion concentrations were used. Relationship between pseudo second order kinetic constant at each concentration with physico-chemical properties was quantified using regression analysis. The experimental analysis revealed that among the physico-chemical properties, acidic surface functional groups had the most profound influence on sorption mechanisms. Reliability and accuracy of the predictive models were significantly improved when separate models were developed for two ranges of initial metal ion concentrations. The outcomes of this study will contribute to the effective design and optimization of biosorbent mixtures with the capacity to remove Pb, Cu and Cd in wastewater.
Reference Key
pathirana2020mathematicalchemosphere Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Pathirana, Chaamila;Ziyath, Abdul M;Jinadasa, K B S N;Egodawatta, Prasanna;Goonetilleke, Ashantha;
Journal Chemosphere
Year 2020
DOI
S0045-6535(20)31158-9
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.