Built-up AFM tips by metal nanoclusters engineering

Jiménez-Sánchez, Mariano D.; Brihuega, I.; Nicoara, Nicoleta; Gómez-Herrero, Júlio; Gómez‐Rodríguez, José M.

doi:10.1016/j.apsusc.2021.149325

Cited by 3 publications

(5 citation statements)

References 41 publications

(48 reference statements)

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“…Jiménez-Sánchez et al [ 25 ] studied the extraction of Ir clusters from graphene (by indentation) on the surface of Rh(111) to fabricate AFM sharp nano-tips, i.e., with weak van der Waals interactions. Experiments were performed under ultrahigh pressure and low temperature (5 K) conditions using a homemade cantilevered non-contact atomic force microscopy (NC-AFM) system.…”

Section: Reviewmentioning

confidence: 99%

“…Imaging parameters: A =14.5 nm; V CPD = +0.18 V; Δ f = −5.5 Hz. Figure 1 was reproduced from [ 25 ] (© 2021 M. D. Jiménez-Sánchez et al, published by Elsevier, distributed under the terms of the Creative Commons Attribution NonCommercial-NoDerivatives 4.0 International License, https://creativecommons.org/licenses/by-nc-nd/4.0/). This content is not subject to CC BY 4.0.…”

Section: Reviewmentioning

confidence: 99%

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Studies of probe tip materials by atomic force microscopy: a review

Xu¹,

Liu²

2022

Beilstein J. Nanotechnol.

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As a tool that can test insulators' surface morphology and properties, the performance index of atomic force microscope (AFM) probes is the most critical factor in determining the resolution of microscopy, and the performance of probes varies in various modes and application requirements. This paper reviews the latest research results in metal, carbon nanotube, and colloidal probes and reviews their related methods and techniques, analyses the advantages and disadvantages of the improved probes compared with ordinary probes by comparing the differences in spatial resolution, sensitivity, imaging, and other performance aspects, and finally provides an outlook on the future development of AFM probes. This paper promotes the development of AFM probes in the direction of new probes and further promotes the broader and deeper application of scanning probe microscope (SPM).

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Section: Reviewmentioning

confidence: 99%

Section: Reviewmentioning

confidence: 99%

Studies of probe tip materials by atomic force microscopy: a review

Xu¹,

Liu²

2022

Beilstein J. Nanotechnol.

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“…These can even distort the nanostructure on the sample surface. Figure 1(A) [20] shows an example of the differences in spatial resolution of the experimental topography images of Ir nanoclusters formed on a graphene on Rh (111) surface using sharp and blunt tips in STM and AFM modes. Both STM and AFM images obtained using blunted tips exhibit a clear loss of resolution as compared with these observed using sharp tips.…”

Section: Current Challenges In Data Acquisitionmentioning

confidence: 99%

“…For example, figure 1(B) presents that the surface topography can contain incorrect information about the height of the sidewall in the case that the actual depth of the (A) Illustration of differences in spatial resolution between sharp and blunt tips in STM and AFM modes. Reprinted from [20], Copyright (2021), with permission from Elsevier. (B) Schematic of the differences in SPM cross-sectional profile observed using a conventional SPM tip to scan across different sidewall slopes.…”

Section: Current Challenges In Data Acquisitionmentioning

confidence: 99%

Emerging machine learning strategies for diminishing measurement uncertainty in SPM nanometrology

Nguyen¹,

Liu²

2022

Surf. Topogr.: Metrol. Prop.

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Scanning probe microscopy (SPM) is an outstanding nanometrology tool for characterizing the structural, electrical, thermal, and mechanical properties of materials at the nanoscale. However, many challenges remain in the use of SPM. Broadly speaking, these challenges are associated with the acquisition of the SPM data and the subsequent analysis of this data, respectively. Both problems are related to the inherent uncertainty of the data obtained in SPM-based measurements due to the nanoscale geometry of the SPM probe tip, the state of the sample imaging region, the data analysis methods themselves, and the experience of the users. Machine learning (ML) approaches have been increasingly applied to address these problems in recent years. In general, ML approaches involve constructing a well-organized and representative SPM dataset from experimental and theoretical trials, and then using the data features of this dataset for ML models to learn and produce appropriate predictions. Herein, this review examines the development of recent ML strategies for reducing measurement uncertainty in SPM-based measurements. The review commences by introducing the ML models and algorithms commonly used in SPM-related applications. Recent approaches for collecting and preprocessing the SPM data to extract significant data features for further ML processing are then introduced. A review of recent proposals for the applications of ML to the improvement of SPM instrumentation and the enhancement of data processing and overall understanding of the material phenomena is then presented. The review concludes by presenting brief perspectives on future opportunities and open challenges in the related research field.

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“…Through continuous refraction and reflection, the surface electromagnetic wave field resonates and condenses at the tip, achieving enhanced resonance beyond the diffraction limit of the tip optical field, with a maximum intensity jump of over five orders of magnitude [12]. At the same time, when the profile and structural parameters of micro/nano structures are determined, their optical characteristics and functions are generally also determined, making it hard to meet the dynamic adjustable requirements of micro/nano device functions in complex usage scenarios [13,14]. The optical properties of the nanotips metasurface are greatly influenced by its structural parameters and the refractive index of the environmental medium.…”

Section: Introductionmentioning

confidence: 99%

Application of nanotips metasurface in extending image depth of field

Liu,

Duan,

et al. 2024

MIPPR 2023: Multispectral Image Acquisition, Processing, and Analysis

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Metasurfaces, enabling effective optical modulation of incident lightwave, can be employed as a promising candidate to implement different functions, thus significantly improving the lightwave controllability, validity and system integration. In this paper, the phase and intensity modulation, firstly, of the incident lightwave based on a single nanotip was researched. Then, the metasurface consist of nanotips with different structural parameters was designed according to the grayscale image obtained via diffractive network encoding, so as to realize the extending image depth of field. We demonstrate that the metasurface based on the nanotips antenna can achieve a large image depth range of field exceeding 50μm. Moreover, the maximum focal length can reach ~200μm after passing through the arrayed nanotips.

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Built-up AFM tips by metal nanoclusters engineering

Cited by 3 publications

References 41 publications

Studies of probe tip materials by atomic force microscopy: a review

Studies of probe tip materials by atomic force microscopy: a review

Emerging machine learning strategies for diminishing measurement uncertainty in SPM nanometrology

Application of nanotips metasurface in extending image depth of field

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