132
Views
2
CrossRef citations to date
0
Altmetric
Articles

Evaluation of catalytic and adsorption activity of iron nanoparticles greenly prepared under different conditions: Box–Behnken design

, &
Pages 8-18 | Received 09 Nov 2018, Accepted 12 Jun 2020, Published online: 02 Jul 2020
 

ABSTRACT

Box–Behnken design methodology was used to study the effect of iron nanoparticles (FeNP) synthesis conditions on its oxidative catalytic degradation and adsorption of methyl orange (MO). The FeNP was synthesised using Acacia nilotica pods extract under different conditions. Models were built at the 95% confidence level using Minitab-18 software based on five responses, namely: production yield (Y), adsorption capacity (q), pH of zero charge (pHzc), gap energy (Egap), and degradation percentage after 60 min (R60). Results showed 100% degradation by 14/15 samples after 3 h, while more than 90% degradation was achieved after 1 h by 10/15 samples. On the other hand, more than 50% adsorption removal of MO was achieved by 8/15 samples. The minimum yield achieved was 13.09% and the maximum was 99.20%. More than 90% yield was achieved in 4/15 samples.

Acknowledgements

The authors acknowledge the Department of Chemistry at King Faisal University for the support of this research, project number 186097.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Deanship of Scientific Research, King Faisal University [grant number 186097].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 827.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.