Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:


A new paradigm of material identification based on graph theory


Materials Genome Initiative (MGI) and National Materials Genome Project have been launched by American and Chinese government in the past decade. One of the major goals of these missions is to facilitate the identification of materials data to speed material discovery and development. 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 error lead to variation of bond length and bond angle.

Feng Pan and his colleagues, from Peking Univerisy Shenzhen Graduate School, propose a new paradigm based on graph theory (GT scheme) 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.

The simplified graph and the actual crystal structure (upper right) of spinel Co3O4.

Credit: Science China Press

The GT scheme can distinguish 2H phase SiC from 4H phase SiC which has strong similarity.

Credit: Science China Press

In GT scheme, the researchers first simplify crystal structures into a graph, which only consists of vertices and edges, in which atoms are simplified as vertices and adjacent atoms with the actual chemical bonds are "connected" with edges.

If the topological connections in the simplified graphs between two structures are the isomorphic, the GT scheme will consider them as one structure. 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 GT 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.

Compared with the traditional structure chemistry methods, the GT scheme can address these iusses much more easily, which enhances the efficiency and reliability of material identification.

By using this artificial intelligent technique, the researchers are trying to achieve high-throughput calculation, preparation and detection for the materials database. The GT scheme subverts the traditional material research methods and accelerates the development in material research field.


This work "Identify crystal structures by a new paradigm based on graph theory for building materials big data" has been published in SCIENCE CHINA Chemistry, and the paper is available online at:

The authors thank Dr. Lin-Wang Wang from Lawrence Berkeley National Laboratory and Dr. Wenfei Fan from the University of Edinburgh for their helpful discussions. This work was supported by the National Key R&D Program of China (2016YFB0700600), the National Natural Science Foundation of China (21603007, 51672012), Soft Science Research Project of Guangdong Province (2017B030301013), and New Energy Materials Genome Preparation & Test Key-Laboratory Project of Shenzhen (ZDSYS201707281026184).

See the article: Mouyi Weng, Zhi Wang, Guoyu Qian, Yaokun Ye, Zhefeng Chen, Xin Chen, Shisheng Zheng, Feng Pan. Identify crystal structures by a new paradigm based on graph theory for building materials big data. Sci. China Chem., 2019, doi: 10.1007/s11426-019-9502-5

Feng Pan | EurekAlert!
Further information:

More articles from Materials Sciences:

nachricht Research shows black plastics could create renewable energy
17.07.2019 | Swansea University

nachricht A new material for the battery of the future, made in UCLouvain
17.07.2019 | Université catholique de Louvain

All articles from Materials Sciences >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Better thermal conductivity by adjusting the arrangement of atoms

Adjusting the thermal conductivity of materials is one of the challenges nanoscience is currently facing. Together with colleagues from the Netherlands and Spain, researchers from the University of Basel have shown that the atomic vibrations that determine heat generation in nanowires can be controlled through the arrangement of atoms alone. The scientists will publish the results shortly in the journal Nano Letters.

In the electronics and computer industry, components are becoming ever smaller and more powerful. However, there are problems with the heat generation. It is...

Im Focus: First-ever visualizations of electrical gating effects on electronic structure

Scientists have visualised the electronic structure in a microelectronic device for the first time, opening up opportunities for finely-tuned high performance electronic devices.

Physicists from the University of Warwick and the University of Washington have developed a technique to measure the energy and momentum of electrons in...

Im Focus: Megakaryocytes act as „bouncers“ restraining cell migration in the bone marrow

Scientists at the University Würzburg and University Hospital of Würzburg found that megakaryocytes act as “bouncers” and thus modulate bone marrow niche properties and cell migration dynamics. The study was published in July in the Journal “Haematologica”.

Hematopoiesis is the process of forming blood cells, which occurs predominantly in the bone marrow. The bone marrow produces all types of blood cells: red...

Im Focus: Artificial neural network resolves puzzles from condensed matter physics: Which is the perfect quantum theory?

For some phenomena in quantum many-body physics several competing theories exist. But which of them describes a quantum phenomenon best? A team of researchers from the Technical University of Munich (TUM) and Harvard University in the United States has now successfully deployed artificial neural networks for image analysis of quantum systems.

Is that a dog or a cat? Such a classification is a prime example of machine learning: artificial neural networks can be trained to analyze images by looking...

Im Focus: Extremely hard yet metallically conductive: Bayreuth researchers develop novel material with high-tech prospects

An international research group led by scientists from the University of Bayreuth has produced a previously unknown material: Rhenium nitride pernitride. Thanks to combining properties that were previously considered incompatible, it looks set to become highly attractive for technological applications. Indeed, it is a super-hard metallic conductor that can withstand extremely high pressures like a diamond. A process now developed in Bayreuth opens up the possibility of producing rhenium nitride pernitride and other technologically interesting materials in sufficiently large quantity for their properties characterisation. The new findings are presented in "Nature Communications".

The possibility of finding a compound that was metallically conductive, super-hard, and ultra-incompressible was long considered unlikely in science. It was...

All Focus news of the innovation-report >>>



Industry & Economy
Event News

2nd International Conference on UV LED Technologies & Applications – ICULTA 2020 | Call for Abstracts

24.06.2019 | Event News

SEMANTiCS 2019 brings together industry leaders and data scientists in Karlsruhe

29.04.2019 | Event News

Revered mathematicians and computer scientists converge with 200 young researchers in Heidelberg!

17.04.2019 | Event News

Latest News

Heat flow through single molecules detected

19.07.2019 | Physics and Astronomy

Heat transport through single molecules

19.07.2019 | Physics and Astronomy

Welcome Committee for Comets

19.07.2019 | Earth Sciences

Science & Research
Overview of more VideoLinks >>>