Cybermaterials: materials by design and accelerated insertion of materials

Abstract

Cybermaterials innovation entails an integration of Materials by Design and accelerated insertion of materials (AIM), which transfers studio ideation into industrial manufacturing. By assembling a hierarchical architecture of integrated computational materials design (ICMD) based on materials genomic fundamental databases, the ICMD mechanistic design models accelerate innovation. We here review progress in the development of linkage models of the process-structure-property-performance paradigm, as well as related design accelerating tools. Extending the materials development capability based on phase-level structural control requires more fundamental investment at the level of the Materials Genome, with focus on improving applicable parametric design models and constructing high-quality databases. Future opportunities in materials genomic research serving both Materials by Design and AIM are addressed. BACKGROUND: ICMD BLUEPRINTThe far-reaching multi-agency enterprise, Materials Genome Initiative (MGI), 1,2 highlights computational materials design techniques grounded in fundamental databases, which can support an ambition of decreasing the full development cycle of new materials from the present 10-20 years to ⩽ 5 years. As a subfield of the broader field of integrated computational materials engineering (ICME), which includes modelling of existing materials, 3,4 the MGI centres on design of new materials and their accelerated qualification through the inherent predictability of designed systems. Creation of the infrastructure of this technology has been a global activity as summarised in a recent series of viewpoint papers on materials genomics. 5-10 Particularly notable has been the design work of Bhadeshia 8 at the University of Cambridge and his former students including Harada 11,12 and Reed. 13 The highest achievements of full cycle compression have been demonstrated in US research, which will be the focus of this paper.In the development of applied engineering materials design powered by fundamental thermodynamic and kinetic genomic databases, a hierarchical infrastructure called ICMD presents a proven scenario of materials genomic design for accelerated engineering innovation. As indicated in Figure 1, the backbone of the ICMD infrastructure is composed of Materials by Design and accelerated insertion of materials (AIM) techniques. The application of both techniques spans the entire course of materials innovation, which can be divided into three phases: concept implementation, materials and processing design, and material qualification. The quality of the materials innovation is determined by the mechanistic models applied in the ICMD framework, which follow the universal process-structure-property-performance paradigm in materials science. 14 In Materials by Design, both process-structure and structure-property models are evaluated and refined to maximise the model-predictability grounded in the Materials Genome, which is powered by fundamental research on

On the Rapid Assessment of Mechanical Behavior of a Prototype Nickel-Based Superalloy using Small-Scale Testing

“…The importance of accelerated material development cycles has led to large-scale enterprises like the Materials Genome Initiative (MGI), part of the broader field of Integrated Computational Materials Engineering (ICME). [2,63] Several promising approaches toward alloy design have been proposed and applied to the development of new grades of superalloys. [64][65][66][67][68] Furthermore, laboratory-scale process chains for rapid production of single-crystal superalloy trial castings have been successfully established.…”

“…Such so-called qualification activities can be difficult and costly; this explains why the time needed to insert them into new applications can be notoriously long. [1][2][3] Furthermore, processing costs for the production of pilot-scale material quantities can be excessively large-often too great to justify-thus leading to conservatism and undue emphasis on maintaining the status quo. Without a doubt, such challenges lead to a slackening in the pace of technological change.…”

A brief review of data-driven ICME for intelligently discovering advanced structural metal materials: Insight into atomic and electronic building blocks

“…It is recognized that recent advances in superpower computation [6], additive manufacturing [7,8], big data [9], data mining [10], machine learning [10,11,12], cloud computation [13], metallic materials ontology [14], graphic knowledge [15,16], and so on, provide an opportunity to create a designing and manufacturing paradigm shift. For instance, the high-throughput-type and the combinatorial approaches integrating both the bottom-up designing and the top-down engineering set up the digital twin feature of compositionprocessing-structure-property-performance (CPSPP) workflow process at multiscales [17,18,19,20,21,22,23], which is known as the data-driven ICME [2]. The advanced structural metal materials are developed/manufactured crossing multiscales, from Electronics to Phases [24,25], i.e., from Atom to Autos [26], from CALPHAD to Flight [27].…”

Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm

“…[1][2][3][4] The variability in the reactivity of nanoclusters hinders theoretical efforts to rapidly characterize them and screen for the ones with optimal catalytic properties, whereas similar efforts are already well under way for extended solid surfaces 12,13 and for bulk materials as part of the Materials Genome Initiative. [14][15][16] To characterize the catalytic properties of nanoclusters, the computational catalysis community typically performs manual guess-and-optimize calculations to systematically probe the reactivity of the unique site types on these clusters. Although the computational and human workload for manual exploration of small clusters is manageable, comprehensive investigations of larger, more complex nanoclusters (e.g., alloy nanoclusters) requires extensive and tedious human effort.…”