17:15 〜 18:45
[SCG49-P02] Bonding properties of hydrated minerals with layered structure under compression : ab initio molecular-dynamics simulations

キーワード:トバモライト、第一原理分子動力学法、結合特性、水和鉱物
In the research field of earth and planetary science, clay minerals which are silicate minerals with layered structure are one of the key materials for elucidating the internal structure of the earth and other planets. In addition, due to their susceptibility for modifications and good absorption properties, applied technologies related to clay minerals are currently being developed. Recently, tobermorite minerals, the group of hydrated calcium silicates which most nearly resembles the clay minerals, have attracting attention in the research field of construction materials (civil engineering materials). The mechanical properties of concrete are considered to be determined by mechanical property of C-S-H (Calcium silicate hydrate), which are formed by hydration of cement and water. The C-S-H structure is reported to be similar to 11Å tobermorite[1]-[3]. For these circumstances, detailed properties of 11Å tobermorite under compressive simulation is required to understand the mechanical property of compression resistant concrete. For these reasons, in this study, we have investigated in variation of bonding property of 11Å tobermorite as a model of hydrated minerals with layered structure under compression deformation using ab initio molecular dynamics simulation.
[1] L. B. Skinner et al.: Nanostructure of Calcium Silicate Hydrates in Cements, Physical Review Letters, Vol. 104, p. 195502 (2010)
[2] K. Kobayashi et al.: Machine learning potentials for tobermorite minerals, Computational Materials Science, Vol. 188, p. 110173 (2021)
[3] D. Viehland et al.: Structural Studies of Jennite and 1.4 nm Tobermorite: Disordered Layering along the [100] of Jennite, Journal of the American Ceramic Society, Vol. 80, pp. 3021-3028 (1997)
[1] L. B. Skinner et al.: Nanostructure of Calcium Silicate Hydrates in Cements, Physical Review Letters, Vol. 104, p. 195502 (2010)
[2] K. Kobayashi et al.: Machine learning potentials for tobermorite minerals, Computational Materials Science, Vol. 188, p. 110173 (2021)
[3] D. Viehland et al.: Structural Studies of Jennite and 1.4 nm Tobermorite: Disordered Layering along the [100] of Jennite, Journal of the American Ceramic Society, Vol. 80, pp. 3021-3028 (1997)