Nanopetal-Assembled SnS Flower-Based Vis-NIR Photodetector

被引：0

作者：

Gupta, Prashant Kumar ^{[1
]}

Goswami, Yashwant Puri ^{[1
]}

Pandey, Amritanshu ^{[1
]}

机构：

[1] Banaras Hindu Univ, Indian Inst Technol, Dept Elect Engn, Varanasi 221005, India

来源：

ACS APPLIED ELECTRONIC MATERIALS | 2024年 / 6卷 / 10期

关键词：

2D nanopetals; 3D SnS flowers; heterojunction; photodetector; vis-NIR; NANOFLOWERS;

D O I：

10.1021/acsaelm.4c01133

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper reports a simple, low-cost, and high-performance two-dimensional (2D) nanopetal-assembled three-dimensional (3D) SnS flowers/Si heterojunction-based visible-near-infrared (vis-NIR) photodetector (PD). A modified chemical bath deposition (CBD) method was used to grow a uniform and closely spaced array of SnS flowers on a Si substrate. This type of nanostructure offers a large photoactive area, thus generating a large number of carriers. The high-performance parameters of the fabricated PD (responsivity, 68.21 A/W; external quantum efficiency (EQE), 1.32 x 10(4)%; detectivity, 6.87 x 10(13) Jones; rise time, 193.91 ms; and fall time, 94.19 ms at 635 nm) are attributed to the heterojunction characteristics resulting from closely spaced nanopetal-assembled SnS flowers on silicon.

引用

页码：7215 / 7221

页数：7

共 50 条

[31] Non-invasive measurement of blood and tissue parameters based on VIS-NIR spectroscopy
Kraitl, Jens
Timm, Ulrich
Ewald, Hartmut
OPTICAL DIAGNOSTICS AND SENSING XIII: TOWARD POINT-OF-CARE DIAGNOSTICS, 2013, 8591
[32] VIS-NIR Hyperspectral Prediction of Soil Organic Matter Based on Stacking Generalization Model
Zhang Xiu-quan
Li Zhi-wei
Zheng De-cong
Song Hai-yan
Wang Guo-liang
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43 (03) : 903 - 910
[33] Soil Organic Matter Content Estimation Based on Soil Covariate and VIS-NIR Spectroscopy
Ma Guolin
Ding Jianli
Zhang Zipeng
LASER & OPTOELECTRONICS PROGRESS, 2020, 57 (19)
[34] Estimation Method of VIS-NIR Spectroscopy for Soil Organic Matter Based on Sparse Networks
Ran Si
Ding Jianli
Ge Xiangyu
Liu Bohua
Zhang Junyong
LASER & OPTOELECTRONICS PROGRESS, 2020, 57 (24)
[35] Computational aberration correction of VIS-NIR multispectral imaging microscopy based on Fourier ptychography
Shen, Cheng
Chan, Antony Chi Shing
Chung, Jaebum
Williams, D. Elliott
Hajimiri, Ali
Yang, Changhuei
OPTICS EXPRESS, 2019, 27 (18) : 24923 - 24937
[36] Using deep neural networks for evaluation of soil quality based on VIS-NIR spectroscopy
Safaie, Mehdi
Hosseinpour-Zarnaq, Mohammad
Omid, Mahmoud
Sarmadian, Fereydoon
Ghasemi-Mobtaker, Hassan
EARTH SCIENCE INFORMATICS, 2024, 17 (01) : 271 - 281
[37] Comparison of Soil Total Nitrogen Content Prediction Models Based on Vis-NIR Spectroscopy
Wang, Yueting
Li, Minzan
Ji, Ronghua
Wang, Minjuan
Zheng, Lihua
SENSORS, 2020, 20 (24) : 1 - 20
[38] Prediction System for Soluble Solid Content in Averrhoa Carambola Based on Vis-NIR Image
Rangkuti, Maisyarah Yuniar
Saputro, Adhi Harmoko
Imawan, Cuk
2017 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (ICELTICS), 2017, : 114 - 118
[39] Quantitative analysis of soil cadmium content based on the fusion of XRF and Vis-NIR data
Qingya, Wang
Li, Fusheng
Jiang, Xiaoyu
Hao, Jun
Zhao, Yanchun
Wu, Shuliang
Cai, Yaoyi
Huang, Wengang
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2022, 226
[40] Pixel based bruise region extraction of apple using Vis-NIR hyperspectral imaging
Che, Wenkai
Sun, Laijun
Zhang, Qian
Tan, Wenyi
Ye, Dandan
Zhang, Dan
Liu, Yangyang
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2018, 146 : 12 - 21

← 1 2 3 4 5 →