Au nanoparticles identifiction with the use of AFM Volta potential mapping - Open Research Data - Bridge of Knowledge

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Au nanoparticles identifiction with the use of AFM Volta potential mapping

Description

The specific physical, chemical and electrochemical electrical properties of gold nanoparticles have led to their extensive use as high-performance chemical and biochemical sensors. The described properties relate to surface plasmon resonance, fluorescence quenching or enhancement, high electrical conductivity and light scattering. The described nanoparticles provide an appropriate microenvironment for the immobilization of biomolecules, maintaining their biological activity. Chemical modification of the described species enables the creation of chemical sensors with increased selectivity and efficiency compared to traditional solutions. Due to the size of the examined objects, atomic force microscopy seems to be an ideal visualization tool, additionally allowing the study of chemical interactions using the so-called chemical force microscopy mode [1]. It should be noted that the different operating mode of the probe microscope allows the visualization of the surface distribution of chemical structure differences by measuring the local value of the surface potential. This operating mode of the device was used as part of the measurements, the results of which are included in this collection. They present images of the distribution of gold nanoparticles locations on a silicon substrate, allowing the estimation of their size and the potential changes between the molecules and the carrier. The set contains 13 maps, made in the topographic and the Kelvin probe mode, with the use of the CDT-NCHR probe.

[1]       T. Ito, S. Ibrahim, I. Grabowska, Chemical-force microscopy for materials characterization, TrAC - Trends Anal. Chem. 29 (2010) 225–233. doi:10.1016/j.trac.2009.12.008.

Dataset file

set07.mdt
1.7 MB, S3 ETag 9b6c6beef421dbdbdde363c76db07536-1, downloads: 56
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File details

License:
Creative Commons: by-nc 4.0 open in new tab
CC BY-NC
Non-commercial
Raw data:
Data contained in dataset was not processed.
Software:
Gwyddion

Details

Year of publication:
2021
Verification date:
2021-05-28
Dataset language:
English
Fields of science:
  • chemical sciences (Natural sciences)
DOI:
DOI ID 10.34808/tt24-vz53 open in new tab
Funding:
Series:
Verified by:
Gdańsk University of Technology

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