高通量筛选极性材料:发现铁电材料新视界

铁电材料因其独特的极性和电场可切换性质,在微电子和能量转换等多个领域有着广泛的应用。然而,寻找新的铁电材料面临挑战,主要是因为准确预测材料的极化和电场可切换性质往往需要与其非极性相进行比较,而对于许多极性材料来说,这样的非极性相要么不存在,要么还未被发现。此外,尽管已有研究通过高通量第一性原理方法生成了大量潜在铁电材料的数据库,但这些工作往往没有区分材料的合成可能性和稳定性,也忽略了数据库中缺少非极性对应相的极性化合物。

高通量筛选极性材料:发现铁电材料新视界
Fig. 1 Schematic representation of the key properties of a ferroelectric.

来自美国劳伦斯伯克利国家实验室的Francesco Ricci等,提出了一种新的高通量筛选流程,旨在系统地发现新的铁电材料。作者通过自动为1978个极性结构生成非极性参考结构,计算了极性与非极性相之间的极化差和能量势垒,从而筛选出潜在的铁电材料。他们的研究聚焦于182个潜在的铁电材料,并基于极化程度和极性非极性能量差异,实施了一种系统的评级策略。此外,通过综合考虑材料的稳定性和合成可能性,以及与文献调研相结合的方式,揭示了约130种作为铁电材料未被研究的有潜力的材料。

高通量筛选极性材料:发现铁电材料新视界

Fig. 2 Summary of the screening process and number of structures in output at each step. 

这项工作不仅为新铁电材料的发现提供了新的途径,也为未来的实验和理论研究奠定了基础,展示了大量有前景的候选材料,对于扩展铁电材料的应用范围和深入理解其物理性质具有重要意义。该文近期发布于npj Computational Materials 10: 15 (2024)

高通量筛选极性材料:发现铁电材料新视界
Fig. 3 Main classification of the potential ferroelectrics in the dataset.

Editorial Summary

High-throughput screening of polar materials: Discovering ferroelectric materials

Ferroelectric materials, with their unique polar properties and switchable electric fields, find widespread applications across various domains, including microelectronics and energy conversion. However, the quest for new ferroelectric materials faces challenges, primarily due to the necessity of accurately predicting the materials’ polarization and electric field switchability, often requiring comparison with their non-polar counterparts. Unfortunately, such non-polar phases are either non-existent or undiscovered for many polar materials. Furthermore, although existing studies have generated extensive databases of potential ferroelectric materials using high-throughput first-principles methods, these efforts often fail to differentiate materials based on their synthesizability and stability, overlooking the absence of corresponding non-polar phases in the databases. In this work, Francesco Ricci et al. from the Lawrence Berkeley National Laboratory, introduced a novel high-throughput screening process aimed at systematically discovering new ferroelectric materials. By automatically generating non-polar reference structures for 1978 polar structures and calculating the polarization difference and energy barriers between polar and non-polar phases, the process identified potential ferroelectric materials. The study focused on 182 potential ferroelectric materials, employing a systematic ranking strategy based on polarization levels and energy differences between polar and non-polar phases. Moreover, by considering the materials’ stability and synthesizability, combined with literature research, the authors unveiled about 130 materials with potential ferroelectric properties that have not been researched previously. This work not only opens new avenues for the discovery of new ferroelectric materials, but also lays the foundation for future experimental and theoretical explorations, presenting a plethora of promising candidates. The study significantly contributes to expanding the application range of ferroelectric materials and deepening our understanding of their physical properties. This work was recently published in npj Computational Materials 10: 15 (2024).

原文Abstract及其翻译

Candidate ferroelectrics via ab initiohigh-throughput screening of polar materials (通过从头算高通量筛选极性材料发现候选铁电材料)

Francesco RicciSebastian E. Reyes-LilloStephanie A. Mack & Jeffrey B. Neaton

Abstract Ferroelectrics are a class of polar and switchable functional materials with diverse applications, from microelectronics to energy conversion. Computational searches for new ferroelectric materials have been constrained by accurate prediction of the polarization and switchability with electric field, properties that, in principle, require a comparison with a nonpolar phase whose atomic-scale unit cell is continuously deformable from the polar ground state. For most polar materials, such a higher-symmetry nonpolar phase does not exist or is unknown. Here, we introduce a general high-throughput workflow that screens polar materials as potential ferroelectrics. We demonstrate our workflow on 1978 polar structures in the Materials Project database, for which we automatically generate a nonpolar reference structure using pseudosymmetries, and then compute the polarization difference and energy barrier between polar and nonpolar phases, comparing the predicted values to known ferroelectrics. Focusing on a subset of 182 potential ferroelectrics, we implement a systematic ranking strategy that prioritizes candidates with large polarization and small polar-nonpolar energy differences. To assess stability and synthesizability, we combine information including the computed formation energy above the convex hull, the Inorganic Crystal Structure Database id number, a previously reported machine learning-based synthesizability score, and ab initio phonon band structures. To distinguish between previously reported ferroelectrics, materials known for alternative applications, and lesser-known materials, we combine this ranking with a survey of the existing literature on these candidates through Google Scholar and Scopus databases, revealing ~130 promising materials uninvestigated as ferroelectric. Our workflow and large-scale high-throughput screening lays the groundwork for the discovery of novel ferroelectrics, revealing numerous candidates materials for future experimental and theoretical endeavors.

摘要 铁电材料是一类具有极性和可切换特性的功能材料,在从微电子到能量转换等多个领域都有广泛的应用。目前,计算搜索新的铁电材料受到了一个限制,即准确预测极化和电场可切换性。这通常需要与一个高对称性的非极性相进行对比,而这种相对于许多极性材料来说要么不存在,要么尚未被发现。在本文中,我们介绍了一种全新的高通量筛选流程,专门针对作为潜在铁电材料的极性材料进行筛选。我们在Materials Project数据库中对1978个极性结构进行了演示,为它们自动生成了一个非极性参考结构,并计算了极性与非极性相之间的极化差及能量势垒,并将其与已知的铁电材料进行了比较。我们特别关注了182种潜在的铁电材料,并实施了一种系统化的评级策略,优先选择那些极化大且极性与非极性能量差异小的候选材料。为了评估这些材料的稳定性和合成可能性,我们综合考虑了包括计算出的形成能、无机晶体结构数据库中的ID编号、之前报道的基于机器学习的合成可能性评分以及从头算声子带结构等信息。我们通过与Google ScholarScopus数据库中已有文献的调研相结合的方式,对材料进行了进一步的分类,以区分之前报道的铁电材料、已知用于其他应用的材料以及较不为人知的材料,从而发现了约130种作为铁电材料尚未被研究的有潜力的材料。我们的工作流程和大规模高通量筛选方法为新铁电材料的发现奠定了基础,揭示了大量待进一步实验和理论研究的候选材料。

原创文章,作者:计算搬砖工程师,如若转载,请注明来源华算科技,注明出处:https://www.v-suan.com/index.php/2024/04/09/7cbc04e1f6/

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