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?材料界面的突破:自動化高通量篩選

在材料科學領域,基于密度泛函理論的高通量篩選技術可有效解析復雜的化學結構,加速了光電子、能量存儲等前沿技術中新材料研發(fā)進程。盡管材料表面在能源轉(zhuǎn)換過程中扮演著至關重要的角色,但由于技術上的復雜性,表面屬性的研究相對落后,且目前還缺乏一套全面的高通量方案來應對這一挑戰(zhàn)。

?材料界面的突破:自動化高通量篩選
Fig. 1 | Schematic overview of the workflow.

由德國卡爾·馮·奧西茨基奧爾登堡大學大學物理系Caterina Cocchi教授領導的團隊,提出了一種自動化計算程序。這一流程能夠自動計算并處理基于密度泛函理論(DFT)得到的表面刻面的結構和電子性質(zhì)。作者呈現(xiàn)了一個專門設計的工作流程,用于處理從無機塊體晶體生成的準二維薄層模型。該工作流基于內(nèi)部實現(xiàn)的python庫,并與AiiDA基礎設施以及已建立的asespglib庫進行了高效接口對接。

?材料界面的突破:自動化高通量篩選
Fig. 2 | Bulk crystals.

作者以銫碲化物(Cs2Te)為例描述了該工具的特點。Cs2Te是一種在粒子加速器光陰極中使用的知名半導體材料。與大多數(shù)計算預測的材料一樣,Cs2Te并不以單晶形式存在,而是通過蒸發(fā)沉積生長,形成具有共存相和復雜表面形貌的多晶樣品。這些樣品難以被系統(tǒng)地再現(xiàn)和表征。正因為缺乏有關Cs2Te基本表面性質(zhì)的實驗信息,它成為了一個理想的案例,以展示作者在這項工作中引入的計算工作流程的有效性。

?材料界面的突破:自動化高通量篩選
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.
通過這項工作,作者分析了這種化合物形成低米勒指數(shù)薄層的特性,考慮了所有可能的終止面,并集中研究了表面穩(wěn)定性、帶隙和電離能等關鍵性質(zhì)。作者將這些可觀測量與薄層的結構特征聯(lián)系起來,并特別弛豫了最外層的原子層,因為這些層對表面特性影響最為關鍵。
?材料界面的突破:自動化高通量篩選

Fig. 4 | Surface stability and under-coordination.

通過這些計算分析,作者揭示了表面結構與其功能性能之間的聯(lián)系。這些發(fā)現(xiàn)不僅增強了對材料表面電子性質(zhì)的理解,還提供了可靠的數(shù)據(jù)支持,有助于預測實驗中可能觀察到的結果,從而為未來的材料設計和應用開辟了新的道路。該文近期發(fā)表于npj Computational Materials?10:?38 (2024).

?材料界面的突破:自動化高通量篩選
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.?

?材料界面的突破:自動化高通量篩選
Fig. 6 | Electronic properties of all facets.?
A team led by Prof. Caterina Cocchi from Carl von Ossietzky Universit?t 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 available 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 10: 38 (2024).

原文Abstract及其翻譯

Automated analysis of surface facets: the example of cesium telluride(表面刻面的自動化分析:以銫碲化物為例)

Holger-Dietrich Sa?nick?&?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.

摘要?高通量篩選技術結合從頭算(ab initio)計算,已成為研究那些構型空間復雜的技術材料的有力工具。盡管這一領域在過去幾年已經(jīng)取得了顯著進展,但大部分研究依舊主要關注于體材料。然而能量轉(zhuǎn)換、產(chǎn)生以及儲存等重要過程實際卻發(fā)生在材料表面。在本文中,我們提出了一個自動化的計算框架,它能夠從第一性原理出發(fā),以高通量方式精確計算無機晶體的表面性質(zhì)。在詳細說明了這種方法及其實現(xiàn)之后,我們通過幾個實例來展示它的實際應用能力,特別是聚焦于四種不同形態(tài)的銫碲化物(Cs2Te)——這是一種在粒子加速器中被廣泛使用的光陰極材料。我們考慮了具有不同終止面和低米勒指數(shù)的晶體薄層模型。這種分析深入探討了表面組成如何影響電子性質(zhì),以及最終的光電發(fā)射性能,而這些組成是可以通過我們提出的高通量篩選方法來實現(xiàn)的。我們所開發(fā)的計算方案不僅為材料科學的研究人員提供了新的視角,還為自動化計算研究拓寬了路徑,使其能夠超越傳統(tǒng)的體材料分析,邁向更加廣闊的應用前景。

原創(chuàng)文章,作者:計算搬磚工程師,如若轉(zhuǎn)載,請注明來源華算科技,注明出處:http://www.xiubac.cn/index.php/2024/03/06/72575de482/

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