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Surface measurement data of polished LTCC: Characterization of pores in polished low temperature co-fired glass-ceramic composites for optimization of their micromachining

Cite this dataset

Lubov, Maksim et al. (2022). Surface measurement data of polished LTCC: Characterization of pores in polished low temperature co-fired glass-ceramic composites for optimization of their micromachining [Dataset]. Dryad. https://doi.org/10.5061/dryad.kwh70rz5w

Abstract

Pores are intrinsic defects of ceramic composites and influence their functional properties significantly. Their characterization is therefore a pivotal task in material and process optimization. It is demonstrated that polished section analysis allows for obtaining precise information on pore size, shape, area fraction, and homogeneous distribution. It is proven that laser scanning microscopy provides accurate height maps and is thus an appropriate technique for assessing surface features. Such data is used to compare areas with good and poor polishing results, and various surface parameters are evaluated in terms of their informative value and data processing effort. The material under investigation is a low-temperature co-fired ceramic composite. Through statistical analysis of the data, the inclination angle was identified as an appropriate parameter to describe the polishing result. By using masked data, direct conclusions can be drawn about the leveling of load-bearing surface areas, which are crucial in photolithographic processing steps and bonding technology. A broad discussion of different defects based on the results contributes to a critical analysis of the potentials and obstacles of micromachining of low-temperature cofired ceramic substrates.

Methods

The data set contains raw data of the polished surface of LTCC substrates and compares good and bad polishing conditions. The data set is obtained by laser scanning microscopy. 

Usage notes

You will find the assignment of the measurements in the README file. Related scripts are provided on GitHub and linked in this document too.

Funding

Carl Zeiss Foundation, Award: MemWerk (P2018-01-002)

German Academic Exchange Service, Award: 57435564

University of Cádiz, Award: fpuUCA, reference 2016-060/PU/EPIF-FPU-CT/CP

IMEYMAT, Award: Líneas Prioritarias

Deutsche Forschungsgemeinschaft, Award: HO 2284/4-1 + 12-1