Dataset Information

Detection of sub-atomic movement in nanostructures.

ABSTRACT: Nanoscale objects move fast and oscillate billions of times per second. Such movements occur naturally in the form of thermal (Brownian) motion while stimulated movements underpin the functionality of nano-mechanical sensors and active nano-(electro/opto) mechanical devices. Here we introduce a methodology for detecting such movements, based on the spectral analysis of secondary electron emission from moving nanostructures, that is sensitive to displacements of sub-atomic amplitude. We demonstrate the detection of nanowire Brownian oscillations of ∼10 pm amplitude and hyperspectral mapping of stimulated oscillations of setae on the body of a common flea. The technique opens a range of opportunities for the study of dynamic processes in materials science, nanotechnology and biology.

SUBMITTER: Liu T

PROVIDER: S-EPMC9419005 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Detection of sub-atomic movement in nanostructures.

Liu Tongjun T Ou Jun-Yu JY MacDonald Kevin F KF Zheludev Nikolay I NI

Nanoscale advances 20210225 8

Nanoscale objects move fast and oscillate billions of times per second. Such movements occur naturally in the form of thermal (Brownian) motion while stimulated movements underpin the functionality of nano-mechanical sensors and active nano-(electro/opto) mechanical devices. Here we introduce a methodology for detecting such movements, based on the spectral analysis of secondary electron emission from moving nanostructures, that is sensitive to displacements of sub-atomic amplitude. We demonstra ...[more]

PMID: 36133771

Similar Datasets

Project description:Magnetic nanoparticles of iron oxide (γ-Fe2O3) have been prepared using bio-assisted method and their application in the field of biosensors is demonstrated. Particularly in this work, different nanostructures of γ-Fe2O3 namely nanospheres (NS), nanograsses (NG) and nanowires (NW) are prepared using a bio-surfactant namely Furostanol Saponin (FS) present in Fenugreek seeds extract through co-precipitation method by following "green" route. Three distinct morphologies of iron oxide nanostructures possessing the same crystal structure, magnetic properties, and varied size distribution are prepared and characterized. The resultant materials are analyzed using field emission scanning electron microscopy, transmission electron microscopy, powder X-ray diffraction, X-ray photoelectron spectroscopy, vibrating sample magnetometer and Fourier transform infrared spectroscopy. Moreover, the effect of reaction time and concentration of FS on the resultant morphologies of γ-Fe2O3 nanostructures are systematically investigated. Among different shapes, NWs and NSs of γ-Fe2O3 are found to exhibit better sensing behaviour for both the individual and simultaneous electrochemical detection of most popular biomarkers namely dopamine (DA) and uric acid (UA). Electrochemical studies reveal that γ-Fe2O3 NWs showed better sensing characteristics than γ-Fe2O3 NSs and NGs in terms of distinguishable voltammetric signals for DA and UA with enhanced oxidation current values. Differential pulse voltammetric studies exhibit linear dependence on DA and UA concentrations in the range of 0.15-75 µM and 5 μM - 0.15 mM respectively. The detection limit values for DA and UA are determined to be 150 nM and 5 µM. In addition γ-Fe2O3 NWs modified electrode showed higher sensitivity, reduced overpotential along with good selectivity towards the determination of DA and UA even in the presence of other common interferents. Thus the proposed biosensor electrode is very easy to fabricate, eco-friendly, cheaper and possesses higher surface area suggesting the unique structural patterns of γ-Fe2O3 nanostructures to be a promising candidate for electrochemical bio-sensing and biomedical applications.

Dataset Information

Detection of sub-atomic movement in nanostructures.

Publications

Detection of sub-atomic movement in nanostructures.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets