Advancing DFT predictions in Cu-chalcogenides with full-yet-shallow 3d-orbitals: Meta-GGA plus Hubbard-like U correction

原子轨道 混合功能 密度泛函理论 局部密度近似 带隙 赫巴德模型 电子结构 离域电子 近似误差 物理 统计物理学 计算物理学 材料科学 凝聚态物理 量子力学 数学 算法 超导电性 电子
作者
Yubo Zhang
出处
期刊:Journal of Chemical Physics [American Institute of Physics]
卷期号:161 (17) 被引量:1
标识
DOI:10.1063/5.0232711
摘要

The technologically important Cu-chalcogenides, such as Cu2Se and CuInSe2, usually have relatively small band gaps. Achieving a reliable yet efficient description of the electronic properties has proven to be quite challenging for the popular exchange-correlation functionals of density functional theory, primarily due to the involvement of full-yet-shallow Cu-3d orbitals. In this study, we evaluate the applicability of several meta-generalized gradient approximation (GGA) functionals that have been recently developed. We find that the r2SCAN (regularized-restored strongly constrained and appropriately normed) functional significantly improves upon conventional local density approximation and GGA in terms of geometry and electronic band structure; however, there is still a notable discrepancy with experimental results due to the remaining delocalization error. This error is mitigated by combining r2SCAN with a Hubbard-like U correction applied to the Cu-3d orbitals. For predicting band gaps, both the TASK functional and the mBJ potential, when combined with the U correction, demonstrate similar accuracies with a mean absolute error of 0.17–0.19 eV. This accuracy is lower than that achieved with the many-body Hedin’s GW approximation method but more accurate than that of hybrid functionals. Moreover, the r2SCAN+U approach well reproduces the phonon dispersion in CuInSe2, revealing a neglected computational problem in previous reports. We conclude that the meta-GGA+U approach represents a significant advancement by striking a balance between reliability and computational effort, and further efforts are still required to describe the Cu-3d orbitals more accurately.
最长约 10秒,即可获得该文献文件

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
red发布了新的文献求助10
刚刚
dd完成签到,获得积分20
1秒前
1秒前
1秒前
CodeCraft应助开心最重要采纳,获得10
1秒前
云溪完成签到,获得积分10
1秒前
喵喵描白完成签到,获得积分10
2秒前
2秒前
雷家完成签到,获得积分10
2秒前
菠萝冰完成签到,获得积分10
2秒前
阿ccc发布了新的文献求助10
2秒前
科研通AI6.2应助jusss采纳,获得30
3秒前
烟花应助YU采纳,获得10
3秒前
科研通AI6.2应助少年梦采纳,获得10
3秒前
dyk完成签到,获得积分10
3秒前
Aimee完成签到,获得积分10
3秒前
周灿灿完成签到,获得积分10
4秒前
zj发布了新的文献求助10
4秒前
阿南完成签到 ,获得积分10
5秒前
Dd发布了新的文献求助50
5秒前
杨蒙博发布了新的文献求助10
5秒前
liu完成签到,获得积分10
5秒前
小二郎应助horsam采纳,获得10
5秒前
Donby完成签到,获得积分0
5秒前
realtimes完成签到,获得积分10
5秒前
Kevin完成签到,获得积分10
5秒前
lei完成签到,获得积分10
6秒前
cl完成签到,获得积分10
6秒前
6秒前
6秒前
Owen应助白纸采纳,获得10
7秒前
ZAy4gG发布了新的文献求助10
7秒前
独特的哈密瓜数据线完成签到,获得积分10
7秒前
7秒前
汉堡包应助英俊的依凝采纳,获得10
7秒前
科研通AI2S应助高强采纳,获得10
7秒前
7秒前
yuyuyu完成签到,获得积分10
7秒前
芳芳完成签到,获得积分10
7秒前
fqk完成签到,获得积分10
8秒前
高分求助中
Malcolm Fraser : a biography 680
Signals, Systems, and Signal Processing 610
天津市智库成果选编 600
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Organic Reactions Volume 118 400
A Foreign Missionary on the Long March: The Unpublished Memoirs of Arnolis Hayman of the China Inland Mission 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6459612
求助须知:如何正确求助?哪些是违规求助? 8268626
关于积分的说明 17623451
捐赠科研通 5528990
什么是DOI,文献DOI怎么找? 2905996
邀请新用户注册赠送积分活动 1882711
关于科研通互助平台的介绍 1727971