Deep learning analysis on transmission electron microscope imaging of atomic defects in two-dimensional materials

Gui, Chen; Zhang, Zhihao; Li, Zongyi; Luo, Chen; Xia, Jiang; Wu, Xing; Chu, Junhao

doi:10.1016/j.isci.2023.107982

Cited by 8 publications

(1 citation statement)

References 91 publications

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“…However, STEM images of 2D materials acquired at low voltage always have a low signal-to-noise ratio (SNR), and subsequently image analysis based on human subjective judgments may be subject to inaccuracy of structural information. Numerous studies have been conducted to develop automated analysis algorithms based on machine learning for structural identification with high accuracy [162][163][164][165][166]. The emerging 4D STEM technique is especially applicable to 2D materials, which enables the examination of electric, magnetic, and strain field structures at the atomic scale [167][168][169][170][171][172].…”

Section: Transmission Electron Microscopymentioning

confidence: 99%

Two-dimensional materials for future information technology: status and prospects

Qiu,

Yu,

Zhao

et al. 2024

Sci. China Inf. Sci.

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Over the past 70 years, the semiconductor industry has undergone transformative changes, largely driven by the miniaturization of devices and the integration of innovative structures and materials. Two-dimensional (2D) materials like transition metal dichalcogenides (TMDs) and graphene are pivotal in overcoming the limitations of silicon-based technologies, offering innovative approaches in transistor design and functionality, enabling atomic-thin channel transistors and monolithic 3D integration. We review the important progress in the application of 2D materials in future information technology, focusing in particular on microelectronics and optoelectronics. We comprehensively summarize the key advancements across material production, characterization metrology, electronic devices, optoelectronic devices, and heterogeneous integration on silicon. A strategic roadmap and key challenges for the transition of 2D materials from basic research to industrial development are outlined. To facilitate such a transition, key technologies and tools dedicated to 2D materials must be developed to meet industrial standards, and the employment of AI in material growth, characterizations, and circuit design will be essential. It is time for academia to actively engage with industry to drive the next 10 years of 2D material research.

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Section: Transmission Electron Microscopymentioning

confidence: 99%

Two-dimensional materials for future information technology: status and prospects

Qiu,

Yu,

Zhao

et al. 2024

Sci. China Inf. Sci.

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Regulation of High‐Index Crystal Facets with Laser‐Induced Periodic Surface Structures on CoFe₂O₄ Epitaxial Films for Ethanol Gas Sensing

Fan,

Xue,

et al. 2024

Adv Materials Inter

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Control of exposed crystal facets in nanostructures is scientifically important, but technically challenging due to the inherent difficulty in manipulating surface energy of crystals. Here, laser‐induced periodic surface structures (LIPSS) induced by femtosecond laser is applied to produce periodic subwavelength 1D nanostructures with high index crystal facets on epitaxial CoFe2O4 surfaces, providing an efficient, maskless, cost‐effective “top‐down” method for nanostructure fabrication. Homogenous 1D LIPSSs (1D‐LIPSSs) with a period of 131 ± 15 nm and a depth of 90 ± 5 nm are obtained. The orientation of LIPSS nanostructures is finely controlled by tuning the polarization of fs laser beam, therefore flexibly producing 1D‐LIPSSs along various crystallographic orientations. Gas sensing performance evaluation shows that the fabrication of 1D‐LIPSSs on CoFe2O4 enlarges its surface area and contributes to enhanced gas sensing response. Compared to CoFe2O4 with LIPSSs faceted along {100} orientation, CoFe2O4 with LIPSSs faceted along high‐index {110} facets exhibits further improved gas sensing performance, suggesting the critical role of high‐index crystal facets in promoting surface reactivity and sensing sensitivity. The development of a laser‐based nanostructure fabrication route with high controllability of exposed crystal facets provides a novel solution for high‐density film‐based gas sensing applications.

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Intelligent Nanomaterial Image Characterizations – A Comprehensive Review on AI Techniques that Power the Present and Drive the Future of Nanoscience

Krishnamoorthy,

Balasubramani

2024

Advcd Theory and Sims

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Artificial Intelligence (AI) is pivotal in advancing science, including nanomaterial studies. This review explores AI‐based image processing in nanoscience, focusing on algorithms to enhance characterization results from instruments like scanning electron microscopy, transmission electron microscopy, X‐ray diffraction, atomic force microscopy etc. It addresses the significance of AI in nanoscience, challenges in advancing AI‐based image processing for nano material characterization, and AI's role in structural analysis, property prediction, deriving structure‐property relations, dataset augmentation, and improving model robustness. Key AI techniques such as Graph Neural Networks, adversarial training, transfer learning, generative models, attention mechanisms, and federated learning are highlighted for their contributions to nano science studies. The review concludes by outlining persisting challenges and thrust areas for future research, aiming to propel nanoscience with AI. This comprehensive analysis underscores the importance of AI‐powered image processing in nanomaterial characterization, offering valuable insights for researchers.

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Deep learning analysis on transmission electron microscope imaging of atomic defects in two-dimensional materials

Cited by 8 publications

References 91 publications

Two-dimensional materials for future information technology: status and prospects

Two-dimensional materials for future information technology: status and prospects

Regulation of High‐Index Crystal Facets with Laser‐Induced Periodic Surface Structures on CoFe₂O₄ Epitaxial Films for Ethanol Gas Sensing

Intelligent Nanomaterial Image Characterizations – A Comprehensive Review on AI Techniques that Power the Present and Drive the Future of Nanoscience

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Deep learning analysis on transmission electron microscope imaging of atomic defects in two-dimensional materials

Cited by 8 publications

References 91 publications

Two-dimensional materials for future information technology: status and prospects

Two-dimensional materials for future information technology: status and prospects

Regulation of High‐Index Crystal Facets with Laser‐Induced Periodic Surface Structures on CoFe2O4 Epitaxial Films for Ethanol Gas Sensing

Intelligent Nanomaterial Image Characterizations – A Comprehensive Review on AI Techniques that Power the Present and Drive the Future of Nanoscience

Contact Info

Product

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Regulation of High‐Index Crystal Facets with Laser‐Induced Periodic Surface Structures on CoFe₂O₄ Epitaxial Films for Ethanol Gas Sensing