Dataset Information

Diffusion and reactivity in ultraviscous aerosol and the correlation with particle viscosity.

ABSTRACT: The slow transport of water, organic species and oxidants in viscous aerosol can lead to aerosol existing in transient states that are not solely governed by thermodynamic principles but by the kinetics of gas-particle partitioning. The relationship between molecular diffusion constants and particle viscosity (for example, as reflected in the Stokes-Einstein equation) is frequently considered to provide an approximate guide to relate the kinetics of aerosol transformation with a material property of the aerosol. We report direct studies of both molecular diffusion and viscosity in the aerosol phase for the ternary system water/maleic acid/sucrose, considering the relationship between the hygroscopic response associated with the change in water partitioning, the volatilisation of maleic acid, the ozonolysis kinetics of maleic acid and the particle viscosity. Although water clearly acts as a plasticiser, the addition of minor fractions of other organic moieties can similarly lead to significant changes in the viscosity from that expected for the dominant component forming the organic matrix (sucrose). Here we highlight that the Stokes-Einstein relationship between the diffusion constant of water and the viscosity of the particle may be more than an order of magnitude in error, even at viscosities as low as 1 Pa s. We show that the thermodynamic relationships of hygroscopic response that underpin such kinetic determinations must be accurately known to retrieve accurate values for diffusion constants; such data are often not available. Further, we show that scaling of the diffusion constants of organic molecules of similar size to those forming the matrix with particle viscosity may be well represented by the Stokes-Einstein equation, suppressing the apparent volatility of semi-volatile components. Finally, the variation in uptake coefficients and diffusion constants for oxidants and small weakly interacting molecules may be much less dependent on viscosity than the diffusion constants of more strongly interacting molecules such as water.

SUBMITTER: Marshall FH

PROVIDER: S-EPMC5975831 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Diffusion and reactivity in ultraviscous aerosol and the correlation with particle viscosity.

Marshall Frances H FH Miles Rachael E H REH Song Young-Chul YC Ohm Peter B PB Power Rory M RM Reid Jonathan P JP Dutcher Cari S CS

Chemical science 20151110 2

The slow transport of water, organic species and oxidants in viscous aerosol can lead to aerosol existing in transient states that are not solely governed by thermodynamic principles but by the kinetics of gas-particle partitioning. The relationship between molecular diffusion constants and particle viscosity (for example, as reflected in the Stokes-Einstein equation) is frequently considered to provide an approximate guide to relate the kinetics of aerosol transformation with a material propert ...[more]

PMID: 29910887

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Project description:Diffusion plays a crucial role in many biological processes including signaling, cellular organization, transport mechanisms, and more. Direct observation of molecular movement by single-particle-tracking experiments has contributed to a growing body of evidence that many cellular systems do not exhibit classical Brownian motion but rather anomalous diffusion. Despite this evidence, characterization of the physical process underlying anomalous diffusion remains a challenging problem for several reasons. First, different physical processes can exist simultaneously in a system. Second, commonly used tools for distinguishing between these processes are based on asymptotic behavior, which is experimentally inaccessible in most cases. Finally, an accurate analysis of the diffusion model requires the calculation of many observables because different transport modes can result in the same diffusion power-law α, which is typically obtained from the mean-square displacements (MSDs). The outstanding challenge in the field is to develop a method to extract an accurate assessment of the diffusion process using many short trajectories with a simple scheme that is applicable at the nonexpert level. Here, we use deep learning to infer the underlying process resulting in anomalous diffusion. We implement a neural network to classify single-particle trajectories by diffusion type: Brownian motion, fractional Brownian motion and continuous time random walk. Further, we demonstrate the applicability of our network architecture for estimating the Hurst exponent for fractional Brownian motion and the diffusion coefficient for Brownian motion on both simulated and experimental data. These networks achieve greater accuracy than time-averaged MSD analysis on simulated trajectories while only requiring as few as 25 steps. When tested on experimental data, both net and ensemble MSD analysis converge to similar values; however, the net needs only half the number of trajectories required for ensemble MSD to achieve the same confidence interval. Finally, we extract diffusion parameters from multiple extremely short trajectories (10 steps) using our approach.

Dataset Information

Diffusion and reactivity in ultraviscous aerosol and the correlation with particle viscosity.

Publications

Diffusion and reactivity in ultraviscous aerosol and the correlation with particle viscosity.

Similar Datasets

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