Onsite and intersite electronic correlations in the Hubbard model for halide perovskites

密度泛函理论 赫巴德模型 卤化物 带隙 电子结构 凝聚态物理 混合功能 强相关材料 电子相关 局部密度近似 电子 化学 材料科学 物理 量子力学 无机化学 超导电性
作者
Jiyuan Yang,Tianyuan Zhu,Shi Liu
出处
期刊:Physical review [American Physical Society]
卷期号:106 (19) 被引量:12
标识
DOI:10.1103/physrevb.106.195159
摘要

Halide perovskites (HPs) are widely viewed as promising photovoltaic and light-emitting materials for their suitable band gaps in the visible spectrum. Density functional theory (DFT) calculations employing (semi)local exchange-correlation functionals usually underestimate the band gaps for these systems. Accurate descriptions of the electronic structures of HPs often demand higher-order levels of theory such as the Heyd-Scuseria-Ernzerhof (HSE) hybrid density functional and $GW$ approximations that are much more computationally expensive than standard DFT. Here, we investigate three representative types of HPs, $AB{X}_{3}$ halide perovskites, vacancy-ordered double perovskites, and bond disproportionated halide perovskites (BDHPs), using $\mathrm{DFT}+U+V$ with onsite $U$ and intersite $V$ Hubbard parameters computed self-consistently without a priori assumption. The inclusion of Hubbard corrections improves the band gap prediction accuracy for all three types of HPs to a similar level of advanced methods. Moreover, the self-consistent Hubbard $U$ is a meaningful indicator of the true local charge state of multivalence metal atoms in HPs. The inclusion of the intersite Hubbard $V$ is crucial to properly capture the hybridization between valence electrons on neighboring atoms in BDHPs that have breathing-mode distortions of halide octahedra. In particular, the simultaneous convergence of both Hubbard parameters and crystal geometry enables a band gap prediction accuracy superior to HSE for BDHPs but at a fraction of the cost. Our work highlights the importance of using self-consistent Hubbard parameters when dealing with HPs that often possess intricate competitions between onsite localization and intersite hybridization.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
南风知我意完成签到,获得积分10
1秒前
大仙发布了新的文献求助10
1秒前
所所应助霸气棉花糖采纳,获得10
1秒前
清脆画板发布了新的文献求助10
1秒前
马大帅发布了新的文献求助10
2秒前
姀姀发布了新的文献求助10
2秒前
wudan完成签到,获得积分10
3秒前
Orange完成签到,获得积分10
3秒前
3秒前
3秒前
深情安青应助氯化铝采纳,获得10
3秒前
4秒前
5秒前
逍遥猪皮完成签到,获得积分10
5秒前
马大帅完成签到,获得积分10
7秒前
jiaxingwei发布了新的文献求助10
8秒前
研友_VZG7GZ应助阔达的无心采纳,获得10
8秒前
handsomeboy发布了新的文献求助10
8秒前
11秒前
八九寺完成签到,获得积分10
12秒前
wanci应助jie采纳,获得10
13秒前
搜集达人应助mookie采纳,获得10
14秒前
16秒前
甜茶发布了新的文献求助30
16秒前
henryoy完成签到 ,获得积分10
17秒前
斯文的傲珊完成签到,获得积分10
18秒前
科研通AI2S应助Sarina采纳,获得10
20秒前
在水一方应助阔达的无心采纳,获得10
20秒前
22秒前
23秒前
ly应助vicky采纳,获得10
23秒前
24秒前
慕青应助丽丽吖采纳,获得30
24秒前
24秒前
25秒前
深情安青应助济尔采纳,获得10
26秒前
27秒前
27秒前
caicai发布了新的文献求助10
27秒前
标致书本发布了新的文献求助10
28秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Kinesiophobia : a new view of chronic pain behavior 3000
Les Mantodea de guyane 2500
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 2000
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Brittle Fracture in Welded Ships 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5945010
求助须知:如何正确求助?哪些是违规求助? 7096306
关于积分的说明 15898001
捐赠科研通 5076912
什么是DOI,文献DOI怎么找? 2730242
邀请新用户注册赠送积分活动 1690084
关于科研通互助平台的介绍 1614512