Liang Jiang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012946

Abstract The Materials Genome Engineering (MGE) spurs the developments and applications of methods and tools in high-throughput experiments, integrated computation materials engineering and big data. Due to the unique importance and characteristics of structural alloys, there are great needs for MGE high throughput experimental methods and tools to enable efficient establishment of the complex alloy composition-microstructures-property relationships. To explore the alloy composition-phase relationships, several high-throughput experimental concepts are discussed. The diffusion-based high-throughput experimental concepts and approaches are highlighted from generating composition spread, automating characterization, and to illustrating systematic analysis. In particular, the evolution of diffusion multiple More >

Yabin Xu^1,*, Lulu Cui¹, Xiaowei Xu²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 121-132, 2022, DOI:10.32604/csse.2022.022758 - 02 December 2021

Abstract Fracture toughness plays a vital role in damage tolerance design of materials and assessment of structural integrity. To solve these problems of complexity, time-consuming, and low accuracy in obtaining the fracture toughness value of nickel-based superalloys through experiments. A combination prediction model is proposed based on the principle of materials genome engineering, the fracture toughness values of nickel-based superalloys at different temperatures, and different compositions can be predicted based on the existing experimental data. First, to solve the problem of insufficient feature extraction based on manual experience, the Deep Belief Network (DBN) is used to… More >