Investigation of phosphonic acid surface modifications on zinc oxide nanoparticles under ambient conditions
Source abstract
Abstract
Abstract Zinc oxide (ZnO) nanoparticles have emerged as a fascinating metal oxide semiconductor nanomaterial due largely to their wide array of properties that can be altered by surface modification. For example electrical and photonic properties include a range of conductivity from metallic to insulating (n-type and p- type conductivity), wide-band gap semiconductivity, room-temperature ferromagnetism, and chemical-sensing. Recently there has been much interest in the electronic and photonic properties of ZnO nanostructures as foreseeable applications include solar cells and laser diodes. For such purposes, controlling the surface functionalization is important and can be tailored by the chemical attachment of organic acids to the surface. The oxide surface readily reacts with organics forming self-assembled alkylphosphonate films. In this study, ZnO nanoparticles were modified using self-assembly thin films with phosphonic functional head groups. The amount of organic acid used in preparation of the thin film was shown to be important to the nanoparticle surface coverage. The modified ZnO nanoparticles were then characterized using infrared spectroscopy, powder X-ray diffraction, solid-state nuclear magnetic resonance, and scanning electron microscopy-energy dispersive X-ray spectroscopy. The interfacial bonding was identified by spectroscopy analysis to be the bidentate and tridentate motifs between the phosphonic head group and the oxide surface. Work function modification was measured using Ultraviolet photoelectron spectroscopy. The influences of temperature, humidity, and solvent rinse on the stability of the surface modifications were performed.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: ZnO doping and properties · Quantum Dots Synthesis And Properties · Nanowire Synthesis and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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