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Formation of Thick Dense Yttrium Iron Garnet Films Using Aerosol Deposition
Published on: May 15, 2015
On-line characterization of YBCO coated conductors using Raman spectroscopy methods
V A Maroni1, J L Reeves, G Schwab
1Argonne National Laboratory, Argonne, Illinois 60439, USA. maroni@cmt.anl.gov
Applied Spectroscopy
|April 26, 2007
Summary
Raman spectroscopy now monitors the production of Yttrium Barium Copper Oxide (YBCO) superconducting films on moving tapes. This method identifies film quality and impurities, enabling process control for improved superconductor manufacturing.
Area of Science:
- Materials Science
- Spectroscopy
- Superconductivity
Background:
- Superconducting Yttrium Barium Copper Oxide (YBCO) thin films are crucial for advanced applications.
- On-line monitoring during production is essential for quality control and process optimization.
Purpose of the Study:
- To report the first use of Raman spectroscopy for on-line monitoring of YBCO thin film production.
- To develop a methodology for acquiring Raman spectra from YBCO on moving tapes.
- To assess the feasibility of using Raman spectroscopy for real-time quality assessment and process feedback.
Main Methods:
- Utilized Raman spectroscopy to analyze YBCO thin films on moving metal tapes post-metal-organic-chemical-vapor-deposition (MOCVD).
- Developed a baseline correction method for spectra obtained from moving samples.
- Investigated the impact of laser focusing on spectral quality, identifying optimal out-of-focus conditions.
Main Results:
- Successfully obtained Raman spectra revealing YBCO phonons, impurities, and texture.
- Distinguished between properly textured films and those with misoriented grains.
- Identified optical speckle effects from reflective surfaces and optimized measurement by maintaining a slightly out-of-focus condition.
Conclusions:
- Raman spectroscopy is a viable technique for on-line monitoring of YBCO thin film production.
- The method can identify critical quality indicators, including texture and impurities.
- Potential exists for adapting data processing for automated defect tagging and feedback control to the MOCVD process.
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