Density Functional Theory-Based Method to Predict the Activities of Nanomaterials as Peroxidase Mimics

Xiaomei Shen, Zhenzhen Wang, Xingfa Gao, Yuliang Zhao

Research output: Contribution to journalArticlepeer-review

130 Scopus citations

Abstract

A wide variety of nanomaterials possess peroxidase-like catalytic activities and show promise as cost-effective and versatile replacements for natural peroxidases. However, a universal tool for predicting the activities of these materials is still lacking, thus hindering the efficient discovery of nanomaterials as peroxidase mimics. Here, we use density functional theory calculations to reveal the peroxidase-mimetic mechanisms for a series of iron-oxide nanosurfaces, and we derive a volcano-shaped plot of catalytic activity as a function of simple energy-based descriptors. The activity curves and the descriptors can be used to predict peroxidase-like activities for not only iron oxides but also other nanomaterials that share similar catalytic mechanisms. The results demonstrate that the method developed herein can systematically predict the peroxidase-like activities of nanomaterials and thus is expected to be of use for computer-aided design of nanomaterial-based peroxidase mimics.

Original languageEnglish (US)
Pages (from-to)12657-12665
Number of pages9
JournalACS Catalysis
Volume10
Issue number21
DOIs
StatePublished - Nov 6 2020

Keywords

  • density functional theory calculations
  • iron oxides
  • nanomaterials
  • nanozymes
  • reaction mechanisms

ASJC Scopus subject areas

  • Catalysis
  • General Chemistry

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