High-Throughput Screening and Design Guidelines for Single-Phase Refractory High Entropy Alloys from the Nb-Ti-Zr System
Bibliographic record
Abstract
Refractory high entropy alloys (RHEAs) hold promise as a candidate, next-generation material for high-temperature applications challenging widely used nickel-based superalloys [1-4]. Both single- and dual-phase RHEAs demonstrated the ability to deliver sufficient mechanical properties at temperatures exceeding superalloy applications. However, RHEAs are currently limited by insufficient oxidation resistance leading to fast structural degradation from their surface. Partially, it is caused by the low structure and phase stability of multicomponent alloys, especially in the presence of oxygen. Exploration of large refractory compositional space with a limited amount of elements offers a bottom-up approach to establishing fundamental guidelines for the design of stable refractory high entropy alloys. One of the ways to accelerate alloy design is combinatorial material libraries screening obtained by thin-film magnetron sputtering [5]. A large number of compositional variants combined with high-throughput materials characterization allows for the identification of relationships and patterns significantly faster than conventional alloy design. In this study, thin-film combinatorial libraries from ternary Nb-Ti-Zr were obtained by magnetron cosputtering a continuous spread from the elemental targets. The libraries were deposited onto a Si wafer coated with a Si3N4 layer as a diffusion barrier. Applied cosputtering resulted in a compositional gradient across the wafer surface. The chemical composition and thickness of the sputtered films were measured using scanning X-ray fluorescence microscopy (XRF), followed by X-ray diffraction (XRD) to investigate the structure. Further, a detailed structural analysis was performed using scanning electron microscopy (SEM) combined with focused ion beam (FIB) and transmission electron microscopy (TEM). The TEM studies were carried out on lift-outs prepared from down-selected areas by the FIB technique. The phase identification and analysis were done using a combination of selected area electron diffraction (SAED), energy-dispersive X-ray spectroscopy (EDXS), and electron energy-loss spectroscopy (EELS). To examine the compositional changes in the Nb-Ti-Zr system on phase formation, the calculation of phase diagrams (CALPHAD) method was utilized using Thermo-Calc software. Figure 1 shows the XRF analysis performed on the magnetron-sputtered thin film. The sputtering process resulted in the compositional gradient of elements ranging from 15 to 40 at% for Nb, 25 to 60 at% for Ti, and 15 to 55 at% for Zr. A ternary phase diagram with the investigated compositional area is presented in Fig. 1a, while compositional gradients obtained for each element are shown in Figs 1b-d. The investigated compositional space was located in the center of the phase diagram, with a slight shift towards Ti and Zr. Within the compositional space, roughly 60% of investigated compositions displayed a single-phase body-centered cubic structure, while the other 40% were multiphase. The detailed analysis of down-selected compositions revealed distinct changes in films. FIB lift-outs were prepared from compositional variants ranging from single-phase bcc through transitional range to multiphase regions. Despite no significant segregation of elements between the top and the bottom of the film, distinct changes in electronic structure were revealed using EELS (Fig. 2). In this case transition from single-maxima peaks of Ti-L2 and Ti-L3 edges to sharper ones, as well as notable energy shift towards higher energies, indicating change of oxidation states [6]. Overall, the described work establishes compositional rules for the design of single-phase bcc high-entropy refractory alloys with an in-depth explanation of the mechanisms behind them. These results and discussed concepts can be transitioned to bulk alloy development and unlock the potential of next-generation materials for high-temperature applications [7]. XRF analysis of magnetron sputtered Nb-Ti-Zr thin-film; A) ternary Nb-Ti-Zr phase diagram showing explored compositional space; XRF elemental distribution maps (at.%) of B) Nb; C) Zr; D) Ti. TEM analysis of Ti in a selected variant of Nb-Ti-Zr cosputtered film. From left to right: TEM-BF image of the sample; STEM-EDXS elemental distribution map of Ti; EELS spectra of Ti-L2,3 edges acquired at the top and the bottom of the selected variant.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".