Ultra-Fast Electron Microscopic Imaging of Single Molecules With a Direct Electron Detection Camera and Noise Reduction

Stuckner, Joshua; Shimizu, Takayuki; Harano, Koji; Nakamura, Eiichi; Murayama, Mitsuhiro

doi:10.1017/s1431927620001750

Cited by 11 publications

(8 citation statements)

References 28 publications

(42 reference statements)

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“…Using the three binding sites, γ-CD can recognize NT apexes of a van der Waals (vdW) radius between 4 and 9 Å with a size-recognition precision of better than 1 Å. A 2.5 ms resolution video taken on a state-of-the-art electron microscopic camera combined with denoising software , provided direct information on how a CD molecule discovers the best-fitting curved surface after migrating on the NT surface (Figure h,i, Movies S1, S2). We believe that the findings account for molecular recognition in liquid chromatographic separation and provide new insights on the design of CD applications. − The data also illustrate the unique ability of dynamic molecular electron microscopy for deciphering the spatiotemporal details of supramolecular events.…”

Section: Introductionmentioning

confidence: 99%

Rim Binding of Cyclodextrins in Size-Sensitive Guest Recognition

et al. 2021

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Cyclodextrins (CDs) are doughnut-shaped cyclic oligosaccharides having a cavity and two rims. Inclusion binding in the cavity has long served as a classic model of molecular recognition, and rim binding has been neglected. We found that CDs recognize guests by size-sensitive binding using the two rims in addition to the cavity, using single-molecule electron microscopy and a library of graphitic cones as a solid-state substrate for complexation. For example, with its cavity and rim binding ability combined, γ-CD can recognize a guest of radius between 4 and 9 Å with a size-recognition precision of better than 1 Å, as shown by structural analysis of thousands of individual specimens and statistical analysis of the data thereof. A 2.5 ms resolution electron microscopic video provided direct evidence of the process of size recognition. The data suggest the occurrence of the rim binding mode for guests larger than the size of the CD cavity and illustrate a unique application of dynamic molecular electron microscopy for deciphering the spatiotemporal details of supramolecular events.

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Section: Introductionmentioning

confidence: 99%

Rim Binding of Cyclodextrins in Size-Sensitive Guest Recognition

et al. 2021

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“…In addition to the high chemical reactivity at their tip and sidewalls with pentagonal and heptagonal defects, computational analyses using density functional theory , and the reactive Monte Carlo method suggest that the functionalization of CNHs mainly occurs at the closed tip because of the pyramidal distortion of sp 2 carbon bonding. Transmission electron microscopy (TEM) has been employed to experimentally investigate functionalization. − Images of the CNH surface on the atomic scale confirmed the presence of chemical bonding onto their conical edge − and sidewall. , In addition, organic chains covalently grafted on the tip of CNHs have been identified in terms of conformational mobility and conformers’ structure by single-molecule and-real time TEM imaging at different accelerating voltages. − The same technique has also been employed to image prenucleation clusters of metal–organic frameworks attached on CNHs . However, the aforementioned theoretical and experimental studies only focus on the individual tubules.…”

Section: Introductionmentioning

confidence: 99%

Outer-Surface Covalent Functionalization of Carbon Nanohorn Spherical Aggregates Assessed by Highly Spatial-Resolved Energy-Dispersive X-ray Spectrometry in Scanning Electron Microscopy

et al. 2020

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Single-walled carbon nanohorns (CNHs) have great potential in diverse applications such as gas storage, catalyst support, and drug carriers. Although chemical functionalization of CNHs is critical for enhancing the dispersibility and handling in solution, they inherently form robust spherical "dahlia-like" aggregates, which may inhibit chemical reactivity. Theoretical and experimental studies have identified spatial information related to the functional groups on each tubule. However, the overall characteristics of dahlia-like aggregates remain unclear. Herein, highly spatial-resolved energy-dispersive X-ray spectrometry analysis in scanning electron microscopy is employed to elucidate the spatial distribution of functional groups on dahlia-like aggregates. The technique clearly visualizes the elemental distribution associated with the functional groups on the dahlia-like structure. Additionally, it is found that the outer surface of an individual CNH dahlia-like aggregate is functionalized while the inner core remains almost unreacted. Hence, the present findings provide fundamental information about the sites in CNHs that can be modified by chemical functionalization.

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“…Such a rapid scanning, however, brings about poor signal intensity and artifacts mainly coming from the hardware working principles, i.e., unidirectional blurring and image distortion in the scanning direction. The poor signal intensity causes a non-negligible statistical noise which is also well recognized in the rapid image acquisition by using the CTEM 14,15 . The unidirectional blurring and distortion, on the other hand, are unique in the STEM and originated from the delay of the detector response as well as the hysteresis effect of the scan device 16 .…”

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confidence: 99%

Deep learning-based noise filtering toward millisecond order imaging by using scanning transmission electron microscopy

Ihara

Saito

Yoshinaga

et al. 2022

Preprint

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Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM’s high affinity with various analytical options into account. As is well known, STEM’s image acquisition time needs to be further shortened to capture a targeted phenomenon in real time as STEM’s current temporal resolution is far below the conventional TEM’s. However, rapid image acquisition in the millisecond per frame or faster generally causes image distortion, poor electron signals, and unidirectional blurring, which are obstacles for realizing video-rate STEM observation. Here we show an image correction framework integrating deep learning (DL)-based denoising and image distortion correction schemes optimized for STEM rapid image acquisition. By comparing a series of distortion corrected rapid scan images with corresponding regular scan speed images, the trained DL network is proven to remove not only the statistical noise but also the unidirectional blurring. This result demonstrates that rapid as well as high-quality image acquisition by STEM without hardware modification can be established by the DL. The DL-based noise filter could be applied to in-situ observation, such as dislocation activities under external stimuli, with high spatio-temporal resolution.

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Ultra-Fast Electron Microscopic Imaging of Single Molecules With a Direct Electron Detection Camera and Noise Reduction

Cited by 11 publications

References 28 publications

Rim Binding of Cyclodextrins in Size-Sensitive Guest Recognition

Rim Binding of Cyclodextrins in Size-Sensitive Guest Recognition

Outer-Surface Covalent Functionalization of Carbon Nanohorn Spherical Aggregates Assessed by Highly Spatial-Resolved Energy-Dispersive X-ray Spectrometry in Scanning Electron Microscopy

Deep learning-based noise filtering toward millisecond order imaging by using scanning transmission electron microscopy

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