▲ 作者:Simon Divilov, Hagen Eckert, David Hicks, Corey Oses, Cormac Toher, Rico Friedrich, Marco Esters, Michael J. Mehl, Adam C. Zettel, Yoav Lederer, Eva Zurek, Jon-Paul Maria, Donald W. Brenner, Xiomara Campilongo, Suzana Filipovi, William G. Fahrenholtz, Caillin J. Ryan, Christopher M. DeSalle, Ryan J. Crealese, Douglas E. Wolfe, Arrigo Calzolari & Stefano Curtarolo
▲ 链接:
https://www.nature.com/articles/s41586-023-06786-y
▲ 摘要:
对在极端环境下改进功能的需求正在激发人们对高熵陶瓷的兴趣。除了利用熵形成能力描述符(熵-形成能力描述符)计算发现高熵碳化物,大多数创新都是通过实验手段缓慢推动的。
因此,该领域的进步需要更多的理论贡献。新研究引入无序焓熵描述符(DEED),一个描述符捕获熵增益和焓成本之间的平衡,允许正确分类多组分陶瓷的功能合成能力,而不考虑化学和结构。为了使相关计算成为可能,研究者开发了一种卷积算法,它大大减少了计算资源。
此外,DEED还指导了新的单相高熵碳氮化物和硼化物的实验发现。这项工作被集成到AFLOW计算生态系统,提供了一系列潜在的实验发现。
▲ Abstract:
The need for improved functionalities in extreme environments is fuelling interest in high-entropy ceramics. Except for the computational discovery of high-entropy carbides, performed with the entropy-forming-ability descriptor, most innovation has been slowly driven by experimental means. Hence, advancement in the field needs more theoretical contributions. Here we introduce disordered enthalpy–entropy descriptor (DEED), a descriptor that captures the balance between entropy gains and enthalpy costs, allowing the correct classification of functional synthesizability of multicomponent ceramics, regardless of chemistry and structure. To make our calculations possible, we have developed a convolutional algorithm that drastically reduces computational resources. Moreover, DEED guides the experimental discovery of new single-phase high-entropy carbonitrides and borides. This work, integrated into the AFLOW computational ecosystem, provides an array of potential new candidates, ripe for experimental discoveries.