Experimental and Theoretical Investigation on Phase Formation and Mechanical Properties in Cr–Co–Ni Alloys Processed Using a Novel Thin-Film Quenching Technique

Abstract

The Cr−Co−Ni system was studied by combining experimental and computational methods to investigate phase stability and mechanical properties. Thin-film materials libraries were prepared and quenched from high temperatures up to 700 °C using a novel quenching technique. It could be shown that a wide A1 solid solution region exists in the Cr−Co−Ni system. To validate the results obtained using thin-film materials libraries, bulk samples of selected compositions were prepared by arc melting, and the experimental data were additionally compared to results from DFT calculations. The computational results are in good agreement with the measured lattice parameters and elastic moduli. The lattice parameters increase with the addition of Co and Cr, with a more pronounced effect for the latter. The addition of ∼20 atom % Cr results in a similar hardening effect to that of the addition of ∼40 atom % Co.

Effect of signal‐to‐noise ratio on the automatic clustering of X‐ray diffraction patterns from combinatorial libraries

“…Therefore, as a case study, the CMC‐XRD patterns range in 2θ of 40°–50° containing fcc‐(111) peak and bcc‐(110) peak are enough to be used in auto‐clustering analysis (Figure 1b). Considering the measurement time value of high‐throughput automated XRD are set to be 40 s in recent CMC studies, [10] here measurement time values of 4, 15, 30, 35, 40 and 50 s were set for the investigations of SNR effects on the clustering accuracies (one typical pattern is illustrated in Figure 1c). The SNR of each pattern was computed using the MATLAB code based on the formula SNR(dB) = 10log 10 (signal power/noise power), [11] as measurement time may be different for a same SNR from different μ‐XRD diffractometer.…”

“…More information about CMC preparation and characterization methods can be found in ref. [ 1,3,10,13 ] Hierarchical clustering and metric multidimensional data scaling transforming were performed by using the scikit‐learn package [14]…”

Experimental Methods to Enable High-Throughput Characterization of New Structural Materials

“…2 High throughput methods for structural materials are usually based on graded materials. Thin-film methods [3][4][5][6] allow the rapid generation of entire ternary or quaternary phase diagrams on a substrate, which can quickly be scanned with specific test methods given knowledge of the local composition. A disadvantage of the extremely thin-film thickness of a few micrometers 4,7,8 is that the characteristic microstructures of structural materials with all their constituents, such as phases, precipitates, grains, or grain boundaries, cannot be represented in all three spatial dimensions.…”

“…3,9 The mechanical characterization is limited to nano-indentation. 5,6 For this reason, thin-film methods have been established for functional materials 10,11 whose properties are mainly determined by their composition. Typical examples are searching for materials with specific magnetic 6,11 or corrosion properties.…”