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556 results on '"Dong, Huafeng"'

1. Predicting Miscibility in Binary Compounds: A Machine Learning and Genetic Algorithm Study

Author

Feng, Chiwen, Liang, Yanwei, Sun, Jiaying, Wang, Renhai, Sun, Huaijun, and Dong, Huafeng

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

The combination of data science and materials informatics has significantly propelled the advancement of multi-component compound synthesis research. This study employs atomic-level data to predict miscibility in binary compounds using machine learning, demonstrating the feasibility of such predictions. We have integrated experimental data from the Materials Project (MP) database and the Inorganic Crystal Structure Database (ICSD), covering 2,346 binary systems. We applied a random forest classification model to train the constructed dataset and analyze the key factors affecting the miscibility of binary systems and their significance while predicting binary systems with high synthetic potential. By employing advanced genetic algorithms on the Co-Eu system, we discovered three novel thermodynamically stable phases, CoEu8, Co3Eu2, and CoEu. This research offers valuable theoretical insights to guide experimental synthesis endeavors in binary and complex material systems.

Published
2024

3. High-throughput screening of strong electron-phonon couplings in ternary metal diborides

Author

Wang, Renhai, Sun, Yang, Zhang, Feng, Zheng, Feng, Fang, Yimei, Wu, Shunqing, Dong, Huafeng, Wang, Cai-Zhuang, Antropov, Vladimir, and Ho, Kai-Ming

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Materials Science
Abstract

We perform a high-throughput screening on phonon-mediated superconductivity in ternary metal diboride structure with alkali, alkaline earth, and transition metals. We find 17 ground states and 78 low-energy metastable phases. From fast calculations of zone-center electron-phonon coupling, 43 compounds are revealed to show electron-phonon coupling strength higher than that of MgB2. An anti-correlation between energetic stability and electron-phonon coupling strength is identified. We suggest two phases, i.e., Li3ZrB8 and Ca3YB8, to be synthesized, which show reasonable energetic stability and superconducting critical temperature., Comment: 8 pages, 5 figures

Published
2022

5. Stability of xenon-sodium compounds at moderately low pressures

Author

Wang, Shaoxiong, Dong, Huafeng, Peng, Junhao, Wen, Minru, Zhang, Xin, Wu, Fugen, Goncharov, Alexander F., and Oganov, Artem R.

Subjects
Condensed Matter - Materials Science
Abstract

A growing body of theoretical and experimental evidence suggests that inert gases (He, Ne, Ar, Kr, Xe, Rn) become less and less inert under increasing pressure. Here we use the ab initio evolutionary algorithm to predict stable compounds of Xe and Na at pressures below 100 GPa, and find three stable compounds, NaXe, NaXe$_3$ and NaXe$_4$. The NaXe belongs to a well-known cubic CsCl structure type. The NaXe$_4$'s structure is common in amphiboles, whereas the NaXe$_3$ has a unique structure, analogous to the "post-perovskite" orthorhombic CaIrO$_3$-type structure with Ir atoms removed. This is the first time that a cation-vacant version of the CaIrO$_3$ is found in any compound. NaXe, NaXe$_3$ and NaXe$_4$ are found to be metallic.

Published
2022

18. Theoretical study of the pressure-induced structure, phase transition, mechanical and electronic properties in the V-N system

Author

Zhang, Jin, Li, Xinfeng, Dong, Xiao, Dong, Huafeng, and Oganov, Artem R.

Subjects
Condensed Matter - Materials Science
Abstract

Stable compounds in the V-N system are systematically searched and four new high-pressure phases are found, including C2/m-V$_9$N, Pbam-V$_5$N$_2$, Pnma-V$_2$N and I4/mcm-VN$_2$. V$_2$N undergoes a phase transition from $\varepsilon$-Fe$_2$N-type V$_2$N (P$\bar{3}$1m) to $\zeta$-Fe$_2$N-type V$_2$N (Pbcn) at 10 GPa and to Fe$_2$C-type V$_2$N (Pnnm) at 59 GPa, then to Pnma-V$_2$N at 96 GPa. Low-temperature tetragonal VN is theoretically proved to belong to space group P$\bar{4}$2m. The estimated Vickers hardnesses and fracture toughness of WC-type VN are around 37 GPa and 4.3-6.1 MPa m$^{1/2}$, respectively. Al$_2$Cu-type VN$_2$ (I4/mcm) with a Vickers hardness of 25-27 GPa and fracture toughness of 3.6-6.6 MPa m$^{1/2}$ also shows excellent mechanical properties. Elastic properties of WC-type mononitrides of transition metals from IVB group (Ti, Zr and Hf), VB group (V, Nb and Ta) and VIB (Cr, Mo and W) are calculated and compared. Both the bond strength and structural configuration determine the mechanical properties of a material.

Published
2020

23. High-Temperature Superconductivity in the Ti--H System at High Pressures

Author

Zhang, Jin, McMahon, Jeffrey M., Oganov, Artem R., Li, Xinfeng, Dong, Xiao, Dong, Huafeng, and Wang, Shengnan

Subjects
Condensed Matter - Materials Science, Condensed Matter - Superconductivity
Abstract

Search for stable high-pressure compounds in the Ti--H system reveals the existence of titanium hydrides with new stoichiometries, including Ibam-Ti$_2$H$_5$, I4/m-Ti$_5$H$_{13}$, I$\bar{4}$-Ti$_5$H$_{14}$, Fddd-TiH$_4$, Immm-Ti$_2$H$_{13}$, P$\bar{1}$-TiH$_{12}$, and C2/m-TiH$_{22}$. Our calculations predict I4/mmm $\rightarrow$ R$\bar{3}$m and I4/mmm $\rightarrow$ Cmma transitions in TiH and TiH$_2$, respectively. Phonons and the electron--phonon coupling of all searched titanium hydrides are analyzed at high pressure. It is found that Immm-Ti$_2$H$_{13}$ rather than the highest hydrogen content C2/m-TiH$_{22}$, exhibits the highest superconducting critical temperature T$_{c}$. The estimated T$_{c}$ of Immm-Ti$_2$H$_{13}$ and C2/m-TiH$_{22}$ are respectively 127.4--149.4 K ($\mu^{*}$=0.1-0.15) at 350 GPa and 91.3--110.2 K at 250 GPa by numerically solving the Eliashberg equations. One of the effects of pressure on T$_{c}$ can be attributed to the softening and hardening of phonons with increasing pressure.

Published
2019
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48. Predicting miscibility in binary compounds: a machine learning and genetic algorithm study.

Author

Feng, Chiwen, Liang, Yanwei, Sun, Jiaying, Wang, Renhai, Sun, Huaijun, and Dong, Huafeng

Abstract

The combination of data science and materials informatics has significantly propelled the advancement of multi-component compound synthesis research. This study employs atomic-level data to predict miscibility in binary compounds using machine learning, demonstrating the feasibility of such predictions. We have integrated experimental data from the Materials Project (MP) database and the Inorganic Crystal Structure Database (ICSD), covering 2346 binary systems. We applied a random forest classification model to train the constructed dataset and analyze the key factors affecting the miscibility of binary systems and their significance while predicting binary systems with high synthetic potential. By employing advanced genetic algorithms on the Co–Eu system, we discovered three novel thermodynamically stable phases, CoEu8, Co3Eu2, and CoEu. This research offers valuable theoretical insights to guide experimental synthesis endeavors in binary and complex material systems. [ABSTRACT FROM AUTHOR]

Published
2025
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