在材料科学领域，基于密度泛函理论的高通量筛选技术可以有效解析复杂的化学结构，加速光电子学、储能等前沿技术中新材料的研发。 虽然材料表面在能量转换过程中起着至关重要的作用，但由于技术的复杂性，表面性质的研究相对落后，目前缺乏一套全面的高通量解决方案来应对这一挑战。
fig. 1 | schematic overview of the workflow.
由德国奥尔登堡大学物理系的Caterina Cocchi教授，德国Karl von Osiecki领导的团队提出了一个自动计算程序。 该过程基于密度泛函理论 （DFT） 自动计算和处理表面面的结构和电子特性。 作者提出了一个专门设计的工作流程，用于处理由无机块状晶体生成的准二维薄层模型。 该工作流基于内部实现的 Python 库，并与 AIIDA 基础结构以及已建立的 ASE 和 SPGLIB 库有效交互。
fig. 2 | bulk crystals.
作者以碲化铯（CS2TE）为例描述了该工具的特性。 CS2TE是一种著名的半导体材料，用于粒子加速器的光电阴极。 与大多数计算**材料一样，CS2TE不以单晶形式存在，而是通过蒸发沉积生长，形成具有共存相和复杂表面形貌的多晶样品。 这些样本很难系统地复制和表征。 正是由于缺乏关于CS2TE基本表面特性的实验信息，它成为证明作者在这项工作中引入的计算工作流程有效性的理想案例。
fig. 3 | surface types. schematic view of a a stoichiometric surface, b a nonstoichiometric surface with excess cs atoms, and c a non-stoichiometric surface with an excess of te atoms. white and black dots indicate cs and te atoms, respectively, and dashed lines highlight the unit cell boundaries.
通过这项工作，作者分析了这种化合物的特性，以形成具有低米勒指数的薄层，考虑了所有可能的终止表面，并重点关注了表面稳定性、带隙和电离能等关键特性。 作者将这些可观察到的测量结果与薄层的结构特征相关联，特别是松弛最外层的原子层，这对表面特性有最关键的影响。
fig. 4 | surface stability and under-coordination.
通过这些计算分析，作者揭示了表面结构与其功能性能之间的联系。 这些发现不仅增强了对材料表面电子特性的理解，而且还提供了可靠的数据支持，有助于在实验中观察到的结果，从而为未来的材料设计和应用开辟了新的途径。 本文最近发表在NPJ Computational Materials上
fig. 5 | electronic band structures and pdos of selected facets.
editorial summary
materials interface science: automated high-throughput surface screening
in the field of material science, high-throughput screening techniques based on density functional theory can effectively decipher complex chemical structures, accelerating the development of new materials in cutting-edge technologies such as optoelectronics and energy storage. despite the critical role that material surfaces play in energy conversion processes, research on surface properties has lagged due to technical complexities, and a comprehensive high-throughput approach to address these challenges is currently lacking.
fig. 6 | electronic properties of all facets.
a team led by prof. caterina cocchi from carl von ossietzky universität oldenburg, physics department, germany, filled the gap by presenting an automated computational procedure to calculate and post-process structural and electronic properties of surface facets from dft in an automated fashion. the authors present a workflow specifically aimed to deal with slabs generated from inorganic bulk crystals and based on an in-house implementedpython library interfaced with the aiida infrastructure as well as with the established libraries ase and spglib. the authors describe the features of the implemented tool with the example of cs2te, a known semiconductor for photocathodes in particle accelerators. like most computationally predicted materials, cs2te is not **ailable in single-crystalline form: it is grown via vapor deposition and gives rise to polycrystalline samples with coexisting phases and complex surface morphologies that are hard to be systematically reproduced and characterized. this lack of experimental information about the fundamental surface properties of cs2te makes it the ideal case study for the computational workflow introduced in this work. the characteristics of the low-miller-index slabs of this compound are analyzed, taking into account all possible terminations and focusing on key properties such as surface stability, band gap, and ionization potential. the authors relate these observables with the structural fingerprints of the slabs posing particular emphasis on the relaxation of the outermost atomic layers, which are known to most critically impact the characteristics of the surfaces. correlations identified among computed quantities represent an added value for insight and predictions of measurable output. this article was recently published in npj computational materials
原文摘要及其译文
表面刻面的自动分析：碲化铯的例子
holger-dietrich saßnick & caterina cocchi
abstract
high-throughput screening combined with ab initio calculations is a powerful tool to explore technologically relevant materials characterized by complex configurational spaces. despite the impressive developments achieved in this field in the last few years, most studies still focus on bulk materials, although the relevant processes for energy conversion, production, and storage occur on surfaces. herein, we present an automatized computational scheme that is capable of calculating surface properties in inorganic crystals from first principles in a high-throughput fashion. after introducing the method and its implementation, we showcase its applicability, focusing on four polymorphs of cs2te, an established photocathode material for particle accelerators, considering slabs with low miller indices and different terminations. this analysis gives insight into how the surface composition, accessible through the proposed high-throughput screening method, impacts the electronic properties and, ultimately, the photoemission performance. the developed scheme offers new opportunities for automated computational studies beyond bulk materials.
总结：
高通量筛选技术与从头计算相结合，已成为研究复杂构型技术材料的有力工具。 尽管在过去几年中，该领域取得了重大进展，但大多数研究仍然集中在散装材料上。 然而，能量转换、产生和存储等重要过程实际上发生在材料表面。 在本文中，我们提出了一种自动化计算框架，该框架能够从第一性原理以高通量方式准确计算无机晶体的表面性质。 在详细介绍了这种方法及其实现之后，我们通过几个例子展示了其实际应用能力，特别关注四种不同形式的碲化铯（CS2TE），这是一种广泛用于粒子加速器的光电阴极材料。 我们考虑了一个薄晶体层模型，具有不同的端接表面和低米勒指数。 该分析提供了对表面成分如何影响电子特性的见解，并最终影响光发射性能，这可以通过我们提出的高通量筛选方法实现。 我们开发的计算解决方案不仅为材料科学研究人员提供了新的视角，也拓宽了自动化计算研究的路径，使他们能够超越传统的散装材料分析，走向更广泛的应用。