Issue 5, 2022

The compositional characterization and coloring mechanism of Tianqing porcelain from the Huangpu kiln based on EDXRF, SEM, and XAFS analyses

Abstract

The Huangpu kiln in northern China plays an important role in studying the origination and development of Tianqing porcelain that was initially produced in the Five Dynasties. In this paper we study the glaze formulae and coloring mechanism of Tianqing porcelain from the Huangpu kiln by analyzing the chemical composition and Fe valence of the samples using EDXRF, SEM and XAFS. We also discuss the formula adjustment and technological innovation in the development from celadon to Tianqing porcelain of the Huangpu kiln during the Five Dynasties. The results indicate that the Tianqing glaze formula promoted the conversion of calcium glaze to calcium-alkali glaze and was conducive to the crystallization of anorthite by changing the fluxing agent components, such as increasing the Ca and K contents and reducing the Si/Al ratios. In the meantime, controlling the reducing atmosphere and gradient cooling technique resulted in the appropriate size of the separated phase to satisfy the Rayleigh scattering and the size of anorthite crystallite to meet the Mie scattering, promoting the appearance of Tianqing color and jade-like texture. The proportion of Fe2+ in the glaze accounts for about 1/3 of the total amount of Fe. In Tianqing glaze, 1/3–2/3 Fe is four coordinated with low symmetry of the near neighbor coordination structure of Fe atoms, and Fe atoms are basically in a disordered local environment.

Graphical abstract: The compositional characterization and coloring mechanism of Tianqing porcelain from the Huangpu kiln based on EDXRF, SEM, and XAFS analyses

Article information

Article type
Paper
Submitted
26 Oct 2021
Accepted
22 Dec 2021
First published
19 Jan 2022

Anal. Methods, 2022,14, 541-548

The compositional characterization and coloring mechanism of Tianqing porcelain from the Huangpu kiln based on EDXRF, SEM, and XAFS analyses

Y. Chen, R. Wen, L. Wang and M. Zhang, Anal. Methods, 2022, 14, 541 DOI: 10.1039/D1AY01819A

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