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| 1 | Discovering unusual structures from exception using big data and machine learning techniques显示文摘Recently, machine learning(ML) has become a widely used technique in materials science study. Most work focuses on predicting the rule and overall trend by building a machine learning model. However,new insights are often learnt from exceptions against the overall trend. In this work, we demonstrate that how unusual structures are discovered from exceptions when machine learning is used to get the relationship between atomic and electronic structures based on big data from high-throughput calculation database. For example, after training an ML model for the relationship between atomic and electronic structures of crystals, we find AgO2 F, an unusual structure with both Ag3+and O22à, from structures whose band gap deviates much from the prediction made by our model. A further investigation on this structure might shed light into the research on anionic redox in transition metal oxides of Li-ion batteries. | Jianshu Jie Zongxiang Hu Guoyu Qian Mouyi Weng Shunning Li Shucheng Li Mingyu Hu Dong Chen Weiji Xiao Jiaxin Zheng Lin-Wang Wang Feng Pan | 2019 | Science Bulletin2019，64，9： | 5 |
| 2 | A new MaterialGo database and its comparison with other high-throughput electronic structure databases for their predicted energy band gaps显示文摘Recently, many high-throughput calculation materials databases have been constructed and found wide applications. However, a database is only useful if its content is reliable and sufficiently accurate. It is thus of paramount importance to gauge the reliabilities and accuracies of these databases. Although many properties have been predicted accurately in these databases,electronic band gap is well known to be underestimated by traditional density functional theory(DFT) calculations under local density approximation(LDA), which becomes a challenging problem for materials database building. Here, we introduce MaterialGo(http://gffzz077c307637e74fb9hn5f5u5vub9bv60kf.ffgz.tsg.suse.edu.cn/data-base.html), a new database calculating the band structures of crystals using both Perdew-Burke-Ernzerhof(PBE) exchange-correlation functional and Heyd-Scuseria-Ernzerhof(HSE) hybrid functional.Comparing different PBE databases, it is found that their band gaps are consistent when no U parameter is used for transition metal d-state or heavy element f-state to correct their self-interaction error, but rather different when PBE+U are used, mostly because of the different values of U used in different database. HSE calculations under standard parameters will give larger band gaps that are closer to experiment. Based on the high-throughput HSE calculations over 10000 crystal structures, we might have a better understanding of the relationship between crystal structures and electronic structures, which will help us to further explore material genome science and engineering. | JIE JianShu WENG MouYi LI ShunNing CHEN Dong LI ShuCheng XIAO WeiJi ZHENG JiaXin PAN Feng Wang LinWang | 2019 | Science China(Technological Sciences)2019，62，8： | 4 |
| 3 | Identify crystal structures by a new paradigm based on graph theory for building materials big data显示文摘Material identification technique is crucial to the development of structure chemistry and materials genome project. Current methods are promising candidates to identify structures effectively, but have limited ability to deal with all structures accurately and automatically in the big materials database because different material resources and various measurement errors lead to variation of bond length and bond angle. To address this issue, we propose a new paradigm based on graph theory(GTscheme) to improve the efficiency and accuracy of material identification, which focuses on processing the 'topological relationship' rather than the value of bond length and bond angle among different structures. By using this method, automatic deduplication for big materials database is achieved for the first time, which identifies 626,772 unique structures from 865,458 original structures.Moreover, the graph theory scheme has been modified to solve some advanced problems such as identifying highly distorted structures, distinguishing structures with strong similarity and classifying complex crystal structures in materials big data. | Mouyi Weng Zhi Wang Guoyu Qian Yaokun Ye Zhefeng Chen Xin Chen Shisheng Zheng Feng Pan | 2019 | Science China Chemistry2019，62，8： | 3 |
| 4 | Wannier–Koopmans method calculations for transition metal oxide band gaps显示文摘The widely used density functional theory(DFT)has a major drawback of underestimating the band gaps of materials.Wannier–Koopmans method(WKM)was recently developed for band gap calculations with accuracy on a par with more complicated methods.WKM has been tested for main group covalent semiconductors,alkali halides,2D materials,and organic crystals.Here we apply the WKM to another interesting type of material system:the transition metal(TM)oxides. | Mouyi Weng Feng Pan Lin-Wang Wang | 2020 | npj Computational Materials2020，，1： | 1 |
| 5 | Calculating electron-phonon coupling matrix: Theory introduction,code development and preliminary application显示文摘Electron-phonon coupling(EPC) in bulk materials is an important effect in multifarious physical and chemical phenomena. It is the key to explaining the mechanisms for superconductivity, electronic transport, etc. The EPC matrix describes the coupling of the electronic eigenstates of the studied system under the perturbation of phonons. Although the EPC matrix is closely relevant to many fundamental physicochemical properties, it remains a challenge to calculate the EPC matrix precisely due to the high computational cost. In recent years, Giustino et al. developed the EPW method on open-source ab-initio software Quantum Espresso, which uses Wannier functions(WFs) to calculate EPC matrix. However, due to the limitation of their implementation,it is not possible yet to calculate the EPC matrix under some important computational conditions, e.g., for DFT+U and HSE calculation. Given the importance of these computational conditions(e.g., for transition metal oxides), we have developed our own implementation of EPC matrix calculation based on the domestic ab-initio software PWmat. Our code allows the DFT+U and HSE correction, so we can get a more accurate EPC matrix in the related problems. In this article, we will first review the formulae and elucidate how to calculate the EPC matrix by constructing WFs. Then we will introduce our code along with its workflow on PWmat and present our test results of two classical semiconductor systems Al As and Si, showing consistency with EPW. Next, the EPC matrix of Li Co O_(2), a classical cathode material for lithium-ion batteries, is calculated using different exchange correlation(XC) functionals including LDA, PBE, DFT+U and HSE. A comparison is provided for the related EPC matrix. It shows there could be a significant difference for the EPC matrix elements due to the use of different XC functionals.Our implementation thus opens the way for fast calculation of EPC for the important class of materials, like the transition metal oxides. | YE YaoKun WENG MouYi ZHANG WenTao LIN WeiCheng CHEN TaoWen PAN Feng ZHENG JiaXin WANG Lin-Wang | 2023 | Science China(Technological Sciences)2023，66，1： | 1 |
| 6 | Graph-based discovery and analysis of atomic-scale one-dimensional materials显示文摘Recent decades have witnessed an exponential growth in the discovery of low-dimensional materials(LDMs), benefiting from our unprecedented capabilities in characterizing their structure and chemistry with the aid of advanced computational techniques. Recently, the success of two-dimensional compounds has encouraged extensive research into one-dimensional(1 D) atomic chains. Here, we present a methodology for topological classification of structural blocks in bulk crystals based on graph theory,leading to the identification of exfoliable 1 D atomic chains and their categorization into a variety of chemical families. A subtle interplay is revealed between the prototypical 1 D structural motifs and their chemical space. Leveraging the structure graphs, we elucidate the self-passivation mechanism of 1 D compounds imparted by lone electron pairs, and reveal the dependence of the electronic band gap on the cationic percolation network formed by connections between structure units. This graph-theory-based formalism could serve as a source of stimuli for the future design of LDMs. | Shunning Li Zhefeng Chen Zhi Wang Mouyi Weng Jianyuan Li Mingzheng Zhang Jing Lu Kang Xu Feng Pan | 2022 | National Science Review2022，9，6： | 0 |
| 7 | A descriptor of “material genes”: Effective atomic size in structural unit of ionic crystals显示文摘The atomic size of each element, described by the ionic radius, is one category of 'material genes' and can facilitate our understanding of atomic arrangements in compounds. Most of the ionic radii currently used to measure the sizes of cations and anions in ionic crystals are derived from hard-sphere model based on the coordination numbers, or the soft-sphere model incorporating the effect of ionic polarization. Herein we take a first step towards a novel 'effective atomic size'(EAS) model,which takes into consideration the impact of the types and number of neighboring atoms on the relationship between ionic radii and interatomic distances. Taking the binary compounds between Group IA/IIA and VIA/VIIA elements gathered from the latest databases as an example, we show that the proposed EAS model can yield excellent agreement between the predicted and the DFT-calculated interatomic distances, with deviation of less than 0.1 ?. A set of EAS radii for ionic crystals has been compiled and the role of coordination numbers, geometric symmetry and distortion of structural units has been examined. Thanks to its superior predictability, the EAS model can serve as a foundation to analyze the structure of newly-discovered compounds and to accelerate materials screening processes in the future works. | CHEN Dong LI ShunNing JIE JianShu LI SiBai ZHENG ShiSheng WENG MouYi YU ChangCheng LI ShuCheng CHEN DaJun PAN Feng | 2019 | Science China(Technological Sciences)2019，62，5： | 0 |
| 8 | Co_(13)O_(8)—metalloxocubes:a new class of perovskite-like neutral clusters with cubic aromaticity显示文摘Exploring stable clusters to understand structural evolution from atoms to macroscopic matter and to construct new materials is interesting yet challenging in chemistry.Utilizing our newly developed deep-ultraviolet laser ionization mass spectrometry technique,here we observe the reactions of neutral cobalt clusters with oxygen and find a very stable cluster species of Co13O8 that dominates the mass distribution in the presence of a large flow rate of oxygen gas.The results of global-minimum structural search reveal a unique cubic structure and distinctive stability of the neutral Co13O8 cluster that forms a new class of metal oxides that we named as‘metalloxocubes’.Thermodynamics and kinetics calculations illustrate the structural evolution from icosahedral Co13 to the metalloxocube Co13O8 with decreased energy,enhanced stability and aromaticity.This class of neutral oxygen-passivated metal clusters may be an ideal candidate for genetic materials because of the cubic nature of the building blocks and the stability due to cubic aromaticity. | Lijun Geng Mouyi Weng Cong-Qiao Xu Hanyu Zhang Chaonan Cui Haiming Wu Xin Chen Mingyu Hu Hai Lin Zhen-Dong Sun Xi Wang Han-Shi Hu Jun Li Jiaxin Zheng Zhixun Luo Feng Pan Jiannian Yao | 2021 | National Science Review2021，8，1： | 0 |
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