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Thermodynamic Aspects of Phase Stability
Published in Mary Anne White, Physical Properties of Materials, 2018
The element boron has recently been studied experimentally at high pressure. There are three main solid phases (allotropes) of boron: α, β, and γ. The phase densities are in the order γ > α > β. The triple point (α–β–γ coexistence) is at 8 GPa and 1850 K. The phases α and β are in equilibrium at 4 GPa and 1400 K; the phases α and γ are in equilibrium at 11 GPa and 1420 K; and the phases β and γ are in equilibrium at 10 GPa and 2300 K.
Unveiling the principle descriptor for predicting the electron inelastic mean free path based on a machine learning framework
Published in Science and Technology of Advanced Materials, 2019
Xun Liu, Zhufeng Hou, Dabao Lu, Bo Da, Hideki Yoshikawa, Shigeo Tanuma, Yang Sun, Zejun Ding
Although there are many formulae for predicting the IMFP, there are still problems to be solved, mainly relating to the artificial selection of the combination of terms. The combination space of terms is nearly infinite. The descriptions of several materials, such as carbon allotropes and boron nitride (BN), are very poor, because manually chosen terms can capture only relatively obvious physics of most materials, lacking both an overall and comprehensive understanding. Furthermore, Tanuma and co-workers have spent more than 20 years to build a database of IMFPs for elemental solids, inorganic and organic compounds, and to validate the applicability of the TPP-2M formula to many materials (see their initial work [17] to their most recent work [22]). Beyond the fitting work itself, however, one cannot ensure the applicability of the formula to materials not in the fitting database; that is, one cannot ensure generalization ability in machine learning (ML) terminology. Generally speaking, the manual selection of features is no longer efficient or even reliable.