4.6 Article

Unraveling the Multi-Enzyme-Like Activities of Iron Oxide Nanozyme via a First-Principles Microkinetic Study

期刊

JOURNAL OF PHYSICAL CHEMISTRY C
卷 123, 期 50, 页码 30318-30334

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jpcc.9b07802

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资金

  1. 1331 Project of Shanxi Province
  2. Undergraduate Training Programs for Innovation and Entrepreneurship of Shanxi Province
  3. Graduate Technology Innovation Project of Shanxi Province
  4. Shanxi Normal University [01053017]
  5. High School 131 Leading Talent Project of Shanxi

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The design and construction of efficient artificial enzyme-mimicking nanomaterials, nanozymes, is highly desirable because of their high stability and low cost. Recent studies have demonstrated iron oxide nanomaterials as multifunctional nanozymes. However, the catalytic mechanism remains unclear. Herein we have combined density functional theory calculations with microkinetic modeling to demonstrate (Fe3O4)(n) (n = 1 to 2) exhibiting the intrinsic activity of mimicking enzymes of catalases (CATs), superoxide dismutases (SODs), and peroxidases (PODS). Their catalytic activities are facilitated by the close proximity of undercoordinated, tunable Fe/O pairs on the (Fe3O4) surfaces. The (Fe3O4)(n) (n = 1 to 2) with different morphologies and sizes exhibited different catalytic activities on the order of Fe3O4 > (Fe3O4)(2). Three possible reaction mechanisms of CAT-like activity (i.e., base-like dissociative mechanism, acid-like dissociative mechanism, and bihydrogen peroxide associative mechanism) and two possible reaction mechanisms of SOD-like activity (i.e., Langmuir-Hinshelwood mechanism and Eley-Rideal mechanism) are systematically explored based on minimum energy path calculations. It is identified that the acid -like dissociative mechanism and the Langmuir-Hinshelwood mechanism are the energetically most favorable pathways, which is proved by the analysis of the rate determining step, the energetic span model, and the rate constant. The degree of turnover frequency control (X-TOF) of the species in the mechanism is calculated and identifies the rate-controlling intermediates and transition states (i.e., those with the highest X-TOF), which are used as descriptors to modify and improve the (Fe3O4)(n) catalysts. This study should not only aid our understanding of Fe3O4 artificial enzymes from atomic level but also facilitate the design and construction of other types of target-specific artificial enzymes.

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