Michael McMurtrey

The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces¹. Whereas traditional combinatorial deposition methods can generate material libraries^2,3, these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid–liquid or solid–solid phases^4–6. We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.

UNS S17400 steel is used in turbines for the aerospace and utility industries. While it is generally corrosion resistant, it is susceptible to pitting when exposed to aqueous chloride environments. Effects of pitting characteristics, such as depth, width, and local density on fatigue life, have been studied in this work to better inform criteria for component replacement or repair. While pit depth correlates well with cracking, the deepest pit never initiated the crack that ultimately led to failure. The clustering of pits, or local pitting density, also correlated well with crack initiation location; however, the densest region of pitting was not always the location where cracking occurred. There is likely no single metric that directly correlates pitting with fatigue cracking, rather there is a combination of pitting characteristics that ultimately lead to cracking. The results from this work suggest that pit depth and local pitting density are among the more important metrics.

For ageing airframe structures, a critical challenge for next generation linear elastic fracture mechanics (LEFM) modelling is to predict the effect of corrosion damage on the remaining fatigue life and structural integrity of components. This effort aims to extend a previously developed LEFM modelling approach to field corroded specimens and variable amplitude loading. Iterations of LEFM modelling were performed with different initial flaw sizes and crack growth rate laws and compared to detailed experimental measurements of crack formation and small crack growth. Conservative LEFM‐based lifetime predictions of corroded components were achieved using a corrosion modified‐equivalent initial flaw size along with crack growth rates from a constant K_max‐decreasing ΔK protocol. The source of the error in each of the LEFM iterations is critiqued to identify the bounds for engineering application.