Metal oxide semiconductors have attracted much attention due to their versatility in different applications, ranging from biosensing to green energy-harvesting technologies. Among these metal oxides, oxide-based diluted magnetic semiconductors have also been proposed for fuel cell applications, especially for the oxygen reduction reaction (ORR) and the oxygen evolution reaction. However, the catalytic mechanism has been proposed to follow a two-electron pathway, forming hydrogen peroxide, instead of the four-electron pathway. Herein, we report cobalt-doped zinc oxide (CoxZn1–xO, 0 < x < 0.018) materials prepared using a co-precipitation method suitable for the electrocatalytic production of hydrogen peroxide. The electrocatalytic performance of CoxZn1–xOmore »
Nanozymes—Hitting the Biosensing “Target”
Nanozymes are a class of artificial enzymes that have dimensions in the nanometer range and can be composed of simple metal and metal oxide nanoparticles, metal nanoclusters, dots (both quantum and carbon), nanotubes, nanowires, or multiple metal-organic frameworks (MOFs). They exhibit excellent catalytic activities with low cost, high operational robustness, and a stable shelf-life. More importantly, they are amenable to modifications that can change their surface structures and increase the range of their applications. There are three main classes of nanozymes including the peroxidase-like, the oxidase-like, and the antioxidant nanozymes. Each of these classes catalyzes a specific group of reactions. With the development of nanoscience and nanotechnology, the variety of applications for nanozymes in diverse fields has expanded dramatically, with the most popular applications in biosensing. Nanozyme-based novel biosensors have been designed to detect ions, small molecules, nucleic acids, proteins, and cancer cells. The current review focuses on the catalytic mechanism of nanozymes, their application in biosensing, and the identification of future directions for the field.
- Award ID(s):
- 1946202
- Publication Date:
- NSF-PAR ID:
- 10318360
- Journal Name:
- Sensors
- Volume:
- 21
- Issue:
- 15
- ISSN:
- 1424-8220
- Sponsoring Org:
- National Science Foundation
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