Intrinsic Thermal Shock Behavior of Common Rutile Oxides

Abstract

Rutile TiO2, VO2, CrO2, MnO2, NbO2, RuO2, RhO2, TaO2, OsO2, IrO2, SnO2, PbO2, SiO2, and GeO2 (space group P42/mnm) were explored for thermal shock resistance applications using density functional theory in conjunction with acoustic phonon models. Four relevant thermomechanical properties were calculated, namely thermal conductivity, Poisson’s ratio, the linear coefficient of thermal expansion, and elastic modulus. The thermal conductivity exhibited a parabolic relationship with the linear coefficient of thermal expansion and the extremes were delineated by SiO2 (the smallest linear coefficient of thermal expansion and the largest thermal conductivity) and PbO2 (vice versa). It is suggested that stronger bonding in SiO2 than PbO2 is responsible for such behavior. This also gave rise to the largest elastic modulus of SiO2 in this group of rutile oxides. Finally, the intrinsic thermal shock resistance was the largest for SiO2, exceeding some of the competitive phases such as Al2O3 and nanolaminated Ti3SiC2.

On the Microstructure and Isothermal Oxidation at 800 and 1200 °C of the Nb-24Ti-18Si-5Al-5Cr-5Ge-5Sn (at.%) Silicide-Based Alloy

“…The properties α, E, and κ are crucial for the response of oxides to rapid changes in temperature, which are described by the intrinsic thermal shock parameter (units W•m −1 •MPa −1 ). The ranking of MO 2 oxides and alumina in terms of decreasing intrinsic thermal shock parameter is SiO 2 , Al 2 O 3 , TiO 2 , GeO 2 , and SnO 2 [69]. The scale of ZF6 contained MO 2 oxides at the extremes of the aforementioned ranking for thermal shock, namely, SiO 2 and GeO 2 , compared with the scale of OHS1 where the presence of Al 2 O 3 , TiO 2 , and SnO 2 may have contributed to a more "measured" response to stresses.…”

“…The ranking of MO 2 oxides in the scales of the alloys OHS1 and ZF6 in decreasing order of thermal conductivity (κ) and Young's modulus (E) is SiO 2 , GeO 2 , TiO 2 , and SnO 2 , and the ranking in increasing order of linear coefficient of thermal expansion (α) is SiO 2 , TiO 2 , GeO 2 , and SnO 2 [69] (the SnO 2 oxide was not confirmed by GXRD, but the microanalysis suggested the presence of Sn in the scale; see Section 3.3 where the SnO 2 has the same crystal structure as TiO 2 ). A rapid temperature decrease is accompanied by temperature and stress gradients that could cause cracking and damage.…”

Closed porosity ceramics and glasses

“…Thermal shock resistance ( R TS ) is the ability to withstand the stresses caused because of sudden temperature changes, instead thermal (stress) fatigue is a failure due to cyclic thermal stresses/strains caused by temperature fluctuations. While the latter has not been investigated thoroughly for closed porosity C&Gs, the R TS of brittle materials has been well‐documented, and known to be affected by the elastic modulus, thermal conductivity, thermal expansion coefficient, strength, and the Poisson's ratio . Although the details can be found in related literature, the R TS increases by reduction in the foam density because the struts can accommodate the generated strain (thermal) by bending .…”

“…While the latter has not been investigated thoroughly for closed porosity C&Gs, 191 the R TS of brittle materials has been well-documented, 192 and known to be affected by the elastic modulus, thermal conductivity, thermal expansion coefficient, strength, and the Poisson's ratio. 193 Although the details can be found in related literature, 11,161,194 the R TS increases by reduction in the foam density because the struts can accommodate the generated strain (thermal) by bending. 161 Besides, it was shown that the introduction of small amount of porosity may enhance the R TS since the thermal stresses can be relaxed by the presence of pores, arresting the crack propagation.…”

Staged Training of Machine-Learning Potentials from Small to Large Surface Unit Cells: Efficient Global Structure Determination of the RuO2(100)-c(2 × 2) Reconstruction and (410) Vicinal

“…The MD simulations are carried out with the LAMMPS code, 38 using the velocity Verlet algorithm 39 and 1 fs time steps. Exploiting the small volumetric thermal expansion coefficients for RuO 2 , 40 we employ a canonical NVT ensemble, controlling the temperature with an efficient Berendsen thermostat. 41 In the actual SA protocol, the structures are heated from 200 to 1000 K and then quenched back to 200 K with a constant heating and cooling rate of 1.6 K/ps.…”