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Description
Mapping surface electrical conductivity offers enormous cognitive possibilities regarding the structure and properties of modern materials. The technique invented for this purpose (Conductive AFM) by Murrel's team and colleagues allows independent monitoring of the local conductivity of materials in correlation with the topographic profile. The mentioned independence is due to the fact that the position and deformation of the probe levers are measured by the optical system, while the electric current is measured by a separate circuit. The measurements use probes with a curvature radius varying in the range of 2 to 200 nm, which results from the use of various materials as conductive layers. This diversity, combined with the parameters that are difficult to control of the experiment (water condensation on the surface, mechanical wear or oxidation, or melting of the conductive layer) contribute to low repeatability and reproducibility of the results. In order to standardize the conditions of the experiment, spectroscopic measurements are made to assess the degree of coating degradation based on current voltage relationships. This type of dependence has been summarized in this collection, showing how the resistance of the probe/metal contact (in this case, copper) changes with the number of microscopic scans performed. The collection contains 8 images and 3 spectroscopic curves illustrating the described process. Measurements were made using NSG30 probes with a self-sputtering gold layer.
Reference:
[1] L. Jiang, J. Weber, F. M. Puglisi, et al., Understanding Current Instabilities in Conductive Atomic Force Microscopy, Materials, 12 (2019) 459, DOI: 10.3390/ma12030459
Dataset file
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.Example script for calculation:
https://github.com/antespi/s3md5
File details
- License:
-
open in new tab
CC BYAttribution - Raw data:
- Data contained in dataset was not processed.
- Software:
- Gwyddion
Details
- Year of publication:
- 2021
- Verification date:
- 2021-08-06
- Dataset language:
- English
- Fields of science:
-
- chemical sciences (Natural sciences)
- DOI:
- DOI ID 10.34808/akak-8g51 open in new tab
- Series:
- Verified by:
- Gdańsk University of Technology
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