Abstract
During the past decade there have seen substantial progress being made on materials genome related research. However, coupling mechanisms across multi-scale microstructure and resulting consequences on property and performance of materials remain unsolved problems. Structural hierarchy, which was a concept developed but not quantitatively fulfilled in 1970s, is referred to as microstructure genome here and pinpoints the key enabler for materials genome engineering. Latest progress in deep learning for image recognition and understanding the underlying mathematical mechanisms have revealed the pivotal roles that directional wavelets and invariants play. Hierarchical invariants constructed by a wavelet system can provide an inherent descriptor for microstructure genome.
Highlights
The questions regarding possible coupling mechanisms across multiscale microstructure and resulting consequences on property and performance of materials remain still an openly challenging problem
Studies seeking quantitative formulations of the structure of materials and trying to understand the ways in which the structure change with composition and with processing, and the way in which structure relates to useful properties, i.e., the core idea of materials genome engineering (MGE), were full of the history and defined the core tenet of materials science and engineering (MSE)
The recent Materials Genome Initiative (MGI) in US [4] and MGE platform in China [5] have achieved substantial progress, Smith’s expectation on a new model that can help to understand the rich and necessary interactions between different levels of structural hierarchy remains yet to be solved. It is worth noting the recent progress made in the field of mechanics where a concept of structure genome (SG) was proposed by Yu in 2016 and defined as the smallest mathematical building block of the structure, to emphasize the fact that it contains all the constitutive information needed for a structure in the same fashion that the genome contains all the genetic information for an organism’s growth and development [6]
Summary
The questions regarding possible coupling mechanisms across multiscale microstructure and resulting consequences on property and performance of materials remain still an openly challenging problem. The recent Materials Genome Initiative (MGI) in US [4] and MGE platform in China [5] have achieved substantial progress, Smith’s expectation on a new model that can help to understand the rich and necessary interactions between different levels of structural hierarchy remains yet to be solved It is worth noting the recent progress made in the field of mechanics where a concept of structure genome (SG) was proposed by Yu in 2016 and defined as the smallest mathematical building block of the structure, to emphasize the fact that it contains all the constitutive information needed for a structure in the same fashion that the genome contains all the genetic information for an organism’s growth and development [6]. Recognizing a complex system like material microstructure works in the same way as recognizing a person This process requires a large set of training data, or many encountering occasions, and recognition starts first with an overall impression and progressively towards finer and finer details. Microstructure recognition and classification should be based on invariants, which means that the microstructure can be successfully identified even if its features are subjected to small deformations or symmetry operations such as translation and rotation
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