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An ion diffusion method for visualising a solid-like water nanofilm.

ABSTRACT: A nano-thick solid-like water film on solid surfaces plays an important role in various fields, including biology, materials science, atmospheric chemistry, catalysis and astrophysics. Visualising the water nanofilm has been a challenge due to its dynamic nature and nanoscale thickness. Here we report an ion diffusion method to address this problem using a membrane formed with a BSA-Na2CO3 (BSA, bovine serum albumin) mixture. After a solid-like water nanofilm deposits onto the membrane, Na(+) and CO3(2-) ions diffuse into the film to form a solid Na2CO3 phase in its place. Consequently, the morphology of the nanofilm can be visualised by the space filled by the Na2CO3. Using this method, we successfully observed polygon-like, ribbon-like and spot-like nanofilms at 193?K, 253?K and room temperature, respectively. Our method may provide a tool for characterising confined water films ranging from a few nanometres to hundreds of nanometres in thickness.

SUBMITTER: Wang Y

PROVIDER: S-EPMC3863810 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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An ion diffusion method for visualising a solid-like water nanofilm.

Wang Ya Y Duan Zhiguang Z Fan Daidi D

Scientific reports 20131216

A nano-thick solid-like water film on solid surfaces plays an important role in various fields, including biology, materials science, atmospheric chemistry, catalysis and astrophysics. Visualising the water nanofilm has been a challenge due to its dynamic nature and nanoscale thickness. Here we report an ion diffusion method to address this problem using a membrane formed with a BSA-Na2CO3 (BSA, bovine serum albumin) mixture. After a solid-like water nanofilm deposits onto the membrane, Na(+) an ...[more]

PMID: 24336341

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Project description:The diffusion-weighted magnetic resonance imaging (dMRI) signal measured in vivo arises from multiple diffusion domains, including hindered and restricted water pools, free water and blood pseudo-diffusion. Not accounting for the correct number of components can bias metrics obtained from model fitting because of partial volume effects that are present in, for instance, diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Approaches that aim to overcome this shortcoming generally make assumptions about the number of considered components, which are not likely to hold for all voxels. The spectral analysis of the dMRI signal has been proposed to relax assumptions on the number of components. However, it currently requires a clinically challenging signal-to-noise ratio (SNR) and accounts only for two diffusion processes defined by hard thresholds. In this work, we developed a method to automatically identify the number of components in the spectral analysis, and enforced its robustness to noise, including outlier rejection and a data-driven regularization term. Furthermore, we showed how this method can be used to take into account partial volume effects in DTI and DKI fitting. The proof of concept and performance of the method were evaluated through numerical simulations and in vivo MRI data acquired at 3 T. With simulations our method reliably decomposed three diffusion components from SNR = 30. Biases in metrics derived from DTI and DKI were considerably reduced when components beyond hindered diffusion were taken into account. With the in vivo data our method determined three macro-compartments, which were consistent with hindered diffusion, free water and pseudo-diffusion. Taking free water and pseudo-diffusion into account in DKI resulted in lower mean diffusivity and higher fractional anisotropy values in both gray and white matter. In conclusion, the proposed method allows one to determine co-existing diffusion compartments without prior assumptions on their number, and to account for undesired signal contaminations within clinically achievable SNR levels.

Dataset Information

An ion diffusion method for visualising a solid-like water nanofilm.

Publications

An ion diffusion method for visualising a solid-like water nanofilm.

Similar Datasets

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