Journal Article10.1038/s41597-023-02004-6
Deep learning based atomic defect detection framework for two-dimensional materials
Fu-Xiang Rikudo Chen,Chia-Yu Lin,Hui-Ying Siao,C. Jian,Yong-Cheng Yang,Chun-Liang Lin +5 more
12
TL;DR: A deep learning-based atomic defect detection framework (DL-ADD) to efficiently detect atomic defects in molybdenum disulfide (MoS_2) and generalize the model for defect detection in other TMD materials is proposed.
read more
About: This article is published in Scientific Data. The article was published on 14 Feb 2023. The article focuses on the topics: Medicine.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Studying the Defects in Spinel Compounds: Discovery, Formation Mechanisms, Classification, and Influence on Catalytic Properties
Тетяна Татарчук
TL;DR: This review examines the influence of defects on the physical and chemical properties of spinel compounds, including their classification, formation mechanisms, and impact on catalytic properties, highlighting defect-engineering strategies for optimizing material properties.
7
Probe conditioning via convolution neural network for scanning probe microscopy automation
TL;DR: An automation system for conditioning a scanning probe microscopy (SPM) probe into different states on a Si(111)–(7 × 7) surface at room temperature is presented and the responsiveness of the method is demonstrated by experimentally reforming a Probe into different conditions defined by preset categories.
3
Advancements in defect engineering of two-dimensional nanomaterial-based membranes for enhanced gas separation.
Wenjia Luo,Changzheng Wang,Xueguo Li,Jian Liu,Duo Hou,Xi Zhang,Guoxian Huang,Xingwu Lu,Yanlong Li +8 more
TL;DR: Defect engineering of 2D nanomaterial-based membranes enhances gas separation performance. The technique involves manipulating defects in 2D nanomaterials to create highly efficient membranes for gas capture applications.
3
A Deep Learning Framework for COVID-19 Detection in X-Ray Images with Global Thresholding
05 May 2023
TL;DR: In this paper , a deep learning approach for COVID-19 identification in X-ray pictures utilizing global thresholding is presented. But the method is limited to the detection of lung opacity.
Design and Adaptive Control Method for STM Separating Nano Positioner
Yu-Liang Zhi,Hanqing Pan,Xin Wang,Xianguang Fan +3 more
- 04 Aug 2023
TL;DR: Design and adaptive control method for STM separating nano positioner improve the scanning speed and accuracy by addressing structure complexity, susceptibility to interference and nonlinearity issues.
References
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger,Philipp Fischer,Thomas Brox +2 more
- 05 Oct 2015
TL;DR: Neber et al. as discussed by the authors proposed a network and training strategy that relies on the strong use of data augmentation to use the available annotated samples more efficiently, which can be trained end-to-end from very few images and outperforms the prior best method (a sliding-window convolutional network) on the ISBI challenge for segmentation of neuronal structures in electron microscopic stacks.
A Review of Yolo Algorithm Developments
TL;DR: In this article , a brief overview of the You Only Look Once (YOLO) algorithm and its subsequent advanced versions is given, and the results show the differences and similarities among the YOLO versions and between CNNs.
1.2K
Defect engineering of two-dimensional transition metal dichalcogenides
Zhong Lin,Bruno R. Carvalho,Bruno R. Carvalho,Ethan Kahn,Ruitao Lv,Rahul Rao,Humberto Terrones,Marcos A. Pimenta,Mauricio Terrones +8 more
- 13 Apr 2016
TL;DR: In this article, structural defects in two-dimensional transition metal dichalcogenides (TMDs) have been studied and the authors provide a comprehensive understanding of structural defects and the pathways to generating structural defects during and after synthesis.
Defect-Dominated Doping and Contact Resistance in MoS2
TL;DR: It is found that intrinsic defects in MoS2 dominate the metal/MoS2 contact resistance and provide a low Schottky barrier independent of metal contact work function.
779
Effect of disorder on Raman scattering of single-layer Mo S 2
Sandro Mignuzzi,Sandro Mignuzzi,Andrew J. Pollard,Nicola Bonini,Barry Brennan,Ian S. Gilmore,Marcos A. Pimenta,David Richards,Debdulal Roy +8 more
TL;DR: In this paper, the effect of defects induced by ion bombardment on the Raman spectrum of single-layer molybdenum disulfide was determined by using density functional theory to calculate the phonon dispersion curves.