High-Throughput Automatic Integrated Material Calculations and Data Management Intelligent Platform and the Application in Novel Alloys

doi:10.11900/0412.1961.2021.00041

Acta Metall Sin

2022, Vol. 58

Issue (1): 75-88 DOI: 10.11900/0412.1961.2021.00041

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High-Throughput Automatic Integrated Material Calculations and Data Management Intelligent Platform and the Application in Novel Alloys

WANG Guanjie¹^,², LI Kaiqi¹^,², PENG Liyu¹^,², ZHANG Yiming¹^,², ZHOU Jian¹^,², SUN Zhimei¹^,²(

)

^1. School of Materials Science and Engineering, Beihang University, Beijing 100191, China
^2. Center for Integrated Computational Materials Engineering, International Research Institute for Multidisciplinary Science, Beihang University, Beijing 100191, China

Cite this article:

WANG Guanjie, LI Kaiqi, PENG Liyu, ZHANG Yiming, ZHOU Jian, SUN Zhimei. High-Throughput Automatic Integrated Material Calculations and Data Management Intelligent Platform and the Application in Novel Alloys. Acta Metall Sin, 2022, 58(1): 75-88.

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Abstract

The development of novel materials has experienced three paradigms: purely empirical, theoretical models, and computational materials science. Currently, the huge amount of data generated by experiments and simulations has facilitated a shift in materials science to a data-driven fourth paradigm. Therefore, the development of high-throughput automatic integrated computations and data mining algorithms based on material databases and artificial intelligence algorithms is critical for accelerating the design of novel materials. This paper presents an open-source distributed computational platform called Artificial Learning and Knowledge Enhanced Materials Informatics Engineering 2.0 (ALKEMIE2.0) based on the AMDIV (automation-modular-database-intelligence-visualization) design concepts. The ALKEMIE2.0 platform includes five core components of automation, modular, materials database, artificial intelligence, and visualization, which are suitable for the computational design of novel materials. The overall characteristics of ALKEMIE2.0 are divided into five pillars. ALKEMIE-Core integrates multiscale calculations and simulation software using the ALKEMIE-Plugin application programming interface. Its high-throughput calculation workflows that support 104 magnitude concurrencies are implemented by integrating the automatic frameworks of model constructions, calculation workflows, and data analyses. Furthermore, the platform is based on the ALKEMIE-Server, which can easily and automatically open daemon services and realize information interactions in distributed supercomputers. With its strong portability and scalability, ALKEMIE has been deployed in the National Supercomputing Tianjin Center. In addition, the multitype materials database called the ALKEMIE-Data Vault contains structure, task, workflow, and material property databases, which combined with the power of supercomputing, enables the rapid application of artificial intelligence algorithms in the design of new materials. In particular, the many user-friendly interfaces, which were elaborately designed using the ALKEMIE-GUI and are suitable for scientists with broad backgrounds, make structural building, work flowcharts, data analysis, and machine learning models more transparent and maneuverable. Finally, the main features of ALKEMIE2.0 are demonstrated using two examples of multiplatform deployment and high-throughput screening of binary aluminum alloys.

Key words: materials genome engineering high-throughput calculation materials database artificial intelligence multi-scale integrated simulation high-throughput screening of binary aluminum alloy

Received: 21 January 2021

ZTFLH:

TB30

Fund: National Key Research and Development Program of China(2017YFB0701700);National Natural Science Foundation of China(51872017);the High-Performance Computing (HPC) Resources at Beihang University

About author: SUN Zhimei, professor, Tel: (010)82317747, E-mail: zmsun@buaa.edu.cn

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	Guanjie WANG
	Kaiqi LI
	Liyu PENG
	Yiming ZHANG
	Jian ZHOU
	Zhimei SUN

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https://www.ams.org.cn/EN/10.11900/0412.1961.2021.00041 OR https://www.ams.org.cn/EN/Y2022/V58/I1/75

Fig.1 The AMDIV design philosophy of ALKEMIE2.0 platform (ALKEMIE—Artificial Learning and Knowledge Enhanced Materials Informatics Engineering, DB—database, ML—machine learning)

Fig.2 The architecture of ALKEMIE2.0 (GUI—graphical user interface, SSH—secure shell, AI—artificial intelligence, DOS—density of state, DFT—discrete Fourier transform, I/O—imput and output)

Fig.3 The outline of ALKEMIE2.0 platform (AIMD—ab initio molecular dynamics, HT—high-throughput, TC WF—Curie temperature workflow)

Fig.4 The flowchart of high-throughput automatic calculation and error correction

Fig.5 The types of databases in ALKEMIE2.0-Data Vault

Fig.6 High-throughput screening of the thermodynamic stability of aluminum alloys
(a) illustration of the not calculated elements (gray), the energetically unstable (red), and stable elements (white) in Al, respectively
(b) the formation energy of the 81 alloying element
(c, d) the average bond length (c) and lattice constant (d) of the alloyed compounds (The dashed lines indicate the value of the pure Al)

Fig.7 High-throughput screening of mechanical properties and electrical conductivities of aluminum alloys (The dotted line represents the reference value corresponding to pure aluminum calculated by DFT)
(a) bulk modulus (b) shear modulus
(c) Young's modulus (d) conductivity of different alloying elements

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