ArticleProceedings of the National Academy of Sciences of the United States of America2021
Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- From Static Structures to Molecular Dynamics: Emerging Directions in X-Ray and Electron Materials Characterization.Materials (Basel, Switzerland) · 2026Review
- An Inverse Transwell Assay for Airway Mucus Barrier Function Reveals both Virus- and Mucin-Specific Impacts on Infection.bioRxiv : the preprint server for biology · 2026Article
- Solution-Tunable Interfacial Interaction Landscape Governs Anomalous Nanoparticle Diffusion in Liquid-Phase Electron Microscopy.ACS nano · 2026Article
- A Lightweight Data-Augmented Deep Learning Framework for Real-Time Instance Segmentation in Liquid-Phase In Situ Transmission Electron Microscopy.ACS measurement science au · 2026Article
- Liquid Phase TEM of Diffusing Emulsion Droplets.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Learning the diffusion of nanoparticles in liquid phase TEM via physics-informed generative AI.Nature communications · 2025Article
- Mucus Physically Restricts Influenza A Viral Particle Access to the Epithelium.Advanced biology · 2025Article
- Nanopipette dynamic microscopy unveils nano coffee ring.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Inferring pointwise diffusion properties of single trajectories with deep learning.Biophysical journal · 2023Article
- Observing ion diffusion and reciprocating hopping motion in water.Science advances · 2023Article
- Near-atomic resolution reconstructions from in situ revitrified cryo samples.Acta crystallographica. Section D, Structural biology · 2023Article
- Ouzo Effect Examined at the Nanoscale via Direct Observation of Droplet Nucleation and Morphology.ACS central science · 2023Article
- Facet-selective etching trajectories of individual semiconductor nanocrystals.Science advances · 2022Article
- Machine learning-informed predictions of nanoparticle mobility and fate in the mucus barrier.APL bioengineering · 2022Article
- Article
- Real-space imaging of nanoparticle transport and interaction dynamics by graphene liquid cell TEM.Science advances · 2021Article
- Objective comparison of methods to decode anomalous diffusion.Nature communications · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The motion of nanoparticles near surfaces is of fundamental importance in physics, biology, and chemistry. Liquid cell transmission electron microscopy (LCTEM) is a promising technique for studying motion of nanoparticles with high spatial resolution. Yet, the lack of understanding of how the electron beam of the microscope affects the particle motion has held back advancement in using LCTEM for in situ single nanoparticle and macromolecule tracking at interfaces. Here, we experimentally studied the motion of a model system of gold nanoparticles dispersed in water and moving adjacent to the silicon nitride membrane of a commercial LC in a broad range of electron beam dose rates. We find that the nanoparticles exhibit anomalous diffusive behavior modulated by the electron beam dose rate. We characterized the anomalous diffusion of nanoparticles in LCTEM using a convolutional deep neural-network model and canonical statistical tests. The results demonstrate that the nanoparticle motion is governed by fractional Brownian motion at low dose rates, resembling diffusion in a viscoelastic medium, and continuous-time random walk at high dose rates, resembling diffusion on an energy landscape with pinning sites. Both behaviors can be explained by the presence of silanol molecular species on the surface of the silicon nitride membrane and the ionic species in solution formed by radiolysis of water in presence of the electron beam.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.