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University of Guelph

Graphene Oxide Assisted Hydrothermal Carbonization of Corn Fibre for High-Quality Activated Carbon and its Application for Water Purification using Rapid Small-Scale Column Testing

Abstract

dc:description.abstract

Research in adsorbent applications continue to grow in importance to match an increasing demand for water/air treatment, hydrogen/energy storage, supercapacitor applications, etc. It is becoming apparent that the most cost-effective, environmentally friendly, and reliable solutions for these applications are often in the form of physisorption with porous carbon materials. This is further supported by the emergence of hydrothermal technologies as an effective thermochemical conversion method to process low-value biomass waste streams and produce high-value biocarbons. Studies are needed which elucidate the influence of different process variables to enhance bio-carbon properties and further improve their performance. In this sense, this work first provided a thorough characterization of novel activated carbons (ACs) derived from corn fibre (CF) that were pre-treated using HTC with the addition of graphene oxide (GO) in different amounts. Afterwards, the produced samples were tested for their adsorption capacity in water treatment applications using the rapid small-scale column testing (RSSCT) approach.

Degree

thesis:*
Grantor dc:publisher
University of Guelph

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ubene, Mitchell
Advisor dc:contributor.advisor
  • Dutta, Animesh

Subjects

dc:subject × 4

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10214/27788

Chain of custody

source
Harvested from
University of Guelph
Base URL
atrium.lib.uoguelph.ca/server/oai/request
Last updated
2026-08-21
Source record
OAI-PMH GetRecord
citation

Ubene, Mitchell. Graphene Oxide Assisted Hydrothermal Carbonization of Corn Fibre for High-Quality Activated Carbon and its Application for Water Purification using Rapid Small-Scale Column Testing. University of Guelph, https://hdl.handle.net/10214/27788