2026-09-22T09:51:47Z https://archive.materialscloud.org/oai2d

oai:materialscloud.org:ftqw5-kr204 2026-08-18T09:06:06Z community-mcarchive openaire_data

Yixiu, Luo Yixiu, Luo Xinyu, Gao Ziyu, Wang Cui, Zhou Jiemin, Wang Tiefeng, Du Luchao, Sun Jingyang, Wang Ying, Xiong 2026-08-18 <p><span lang="EN-US">The targeted design of multi-RE-principal-component RE<sub>2</sub>Si<sub>2</sub>O<sub>7</sub> disilicates ((<em>n</em>RE<em><sub>xi</sub></em>)<sub>2</sub>Si<sub>2</sub>O<sub>7</sub>) for environmental barrier coatings (EBCs) applications requires customizing the multi-RE compositions to achieve maximal optimization on the target properties, with a prerequisite to control their high-temperature stabilized phase as β or γ polymorphs. This is challenged by their rich polymorphic phases varied with the elemental properties on the RE cationic sites. In this study, a random forest (RF) model is developed with high accuracy to classify the four types of high-temperature stabilized phase composition </span><span lang="EN-US">−</span><span lang="EN-US"> single-</span><span>β</span><span lang="EN-US">, single-</span><span>γ</span><span lang="EN-US">, single-</span><span>δ</span><span lang="EN-US">/mixed </span><span>δ</span><span lang="EN-US">+</span><span>γ</span><span lang="EN-US">, and phase separation </span><span>–</span><span lang="EN-US"> identifying the average RE<sup>3+</sup> cationic radius ( ) and the deviation of RE<sup>3+</sup> cationic radius ( ) as the most influential factors. The well-trained model is validated on the prediction of (Gd<sub>x1</sub>Ho<sub>x2</sub>Yb<sub>x3</sub>Lu<sub>x4</sub>)<sub>2</sub>Si<sub>2</sub>O<sub>7</sub> and (Nd<sub>x1</sub>Ho<sub>x2</sub>Yb<sub>x3</sub>Lu<sub>x4</sub>)<sub>2</sub>Si<sub>2</sub>O<sub>7</sub> systems, supported by experimental characterization of six representative compositions. High-throughput DFT calculations reveal that the formation of their high-temperature stabilized phases correlates with the the low energy costs to accommodate configurational randomness into the multicomponent system, characterized by rapid convergence of the configurational entropy of mixing with increased excitation energy. The design criteria for single-phase β-(<em>n</em>RE<em><sub>xi</sub></em>)<sub>2</sub>Si<sub>2</sub>O<sub>7</sub> and γ-(<em>n</em>RE<em><sub>xi</sub></em>)<sub>2</sub>Si<sub>2</sub>O<sub>7</sub> disilicates are established. This work provides an investigation paradigm enabling the targeted design of (<em>n</em>RE<em><sub>xi</sub></em>)<sub>2</sub>Si<sub>2</sub>O<sub>7</sub> EBCs materials. </span></p> application/zip text/plain https://doi.org/10.24435/materialscloud:p8-ge oai:materialscloud.org:ftqw5-kr204 mcid:2026.163 eng Materials Cloud https://archive.materialscloud.org/communities/mcarchive https://doi.org/10.24435/materialscloud:k7-wn info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode High-entropy rare-earth disilicates Phase composition Machine learning Environmental barrier coatings Machine learning empowered compositional design of multiple rare-earth principal component disilicates for environmental barrier coatings applications info:eu-repo/semantics/other