Dataset Information

Electrical Mobility as an Indicator for Flexibly Deducing the Kinetics of Nanoparticle Evaporation.

ABSTRACT: Condensation and evaporation of vapor species on nanoparticle surfaces drive the aerosol evolution in various industrial/atmospheric systems, but probing these transient processes is challenging due to related time and length scales. Herein, we present a novel methodology for deducing nanoparticle evaporation kinetics using electrical mobility as a natural size indicator. Monodispersed nanoparticles are fed to a differential mobility analyzer which serves simultaneously as an evaporation flowtube and an instrument for measuring the electrical mobility, realizing measurements of evaporation processes with time scales comparable to the instrument response time. A theoretical framework is derived for deducing the evaporation kinetics from instrument responses through analyzing the nanoparticle trajectory and size-mobility relationship, which considers the coupled mass and heat transfer effect and is applicable to the whole Knudsen number range. The methodology is demonstrated against evaporation but can potentially be extended to condensation and other industrial/atmospheric processes involving rapid size change of nanoparticles.

SUBMITTER: Yang H

PROVIDER: S-EPMC9150095 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Electrical Mobility as an Indicator for Flexibly Deducing the Kinetics of Nanoparticle Evaporation.

Yang Huan H Ding Dian D Skyttä Aurora A Cai Runlong R Kulmala Markku M Kangasluoma Juha J

The journal of physical chemistry. C, Nanomaterials and interfaces 20220511 20

Condensation and evaporation of vapor species on nanoparticle surfaces drive the aerosol evolution in various industrial/atmospheric systems, but probing these transient processes is challenging due to related time and length scales. Herein, we present a novel methodology for deducing nanoparticle evaporation kinetics using electrical mobility as a natural size indicator. Monodispersed nanoparticles are fed to a differential mobility analyzer which serves simultaneously as an evaporation flowtub ...[more]

PMID: 35655937

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Project description:The molecular machinery of life relies on complex multistep processes that involve numerous individual transitions, such as molecular association and dissociation steps, chemical reactions, and mechanical movements. The corresponding transition rates can be typically measured in vitro but not in vivo. Here, we develop a general method to deduce the in-vivo rates from their in-vitro values. The method has two basic components. First, we introduce the kinetic distance, a new concept by which we can quantitatively compare the kinetics of a multistep process in different environments. The kinetic distance depends logarithmically on the transition rates and can be interpreted in terms of the underlying free energy barriers. Second, we minimize the kinetic distance between the in-vitro and the in-vivo process, imposing the constraint that the deduced rates reproduce a known global property such as the overall in-vivo speed. In order to demonstrate the predictive power of our method, we apply it to protein synthesis by ribosomes, a key process of gene expression. We describe the latter process by a codon-specific Markov model with three reaction pathways, corresponding to the initial binding of cognate, near-cognate, and non-cognate tRNA, for which we determine all individual transition rates in vitro. We then predict the in-vivo rates by the constrained minimization procedure and validate these rates by three independent sets of in-vivo data, obtained for codon-dependent translation speeds, codon-specific translation dynamics, and missense error frequencies. In all cases, we find good agreement between theory and experiment without adjusting any fit parameter. The deduced in-vivo rates lead to smaller error frequencies than the known in-vitro rates, primarily by an improved initial selection of tRNA. The method introduced here is relatively simple from a computational point of view and can be applied to any biomolecular process, for which we have detailed information about the in-vitro kinetics.

Project description:PurposeThe aim of the present study was to develop a novel index using fuzzy logic procedures conflating cardiorespiratory and pulmonary kinetics during dynamic exercise as a representative indicator for exercise tolerance.MethodsOverall 69 data sets were re-analyzed: (age: 29 ± 1.2 y [mean ± SEM], height: 179 ± 1.0 cm; body mass: 78 ± 1.4 kg; peak oxygen uptake ([Formula: see text]̇O2peak): 48 ± 1.1 ml·min-1·kg-1), that comprised pseudo random binary sequence work rate (WR) changes between 30 and 80 W on a cycle ergometer, with additional voluntary exhaustion to estimate [Formula: see text]O2peak. Heart rate (HR), stroke volume (SV) and gas exchange (pulmonary oxygen uptake ([Formula: see text]O2pulm)) were measured beat-to-beat and breath-by-breath, respectively. For estimation of muscle oxygen uptake ([Formula: see text]O2musc) kinetics and for the analysis of kinetic responses of the parameters of interest (perfusion ([Formula: see text] = HR·SV), [Formula: see text]O2pulm, [Formula: see text]O2musc) the approach of Hoffmann et al. (2013) was applied. For calculation of the Fuzzy Kinetics Index [Formula: see text], [Formula: see text]O2pulm, and [Formula: see text]O2musc were used as input variables for the subsequent fuzzy- and defuzzyfication procedures.ResultsFor both absolute and relative [Formula: see text]O2peak a significant correlation has been observed with FKI, whereas the correlation coefficient is higher for relative (r = 0.430; p < 0.001; n = 69) compared to absolute [Formula: see text]O2peak (r = 0.358; p < 0.01; n = 69). No significant correlations have been found between FKI and age, height or body mass (p > 0.05 each).ConclusionsThe significant correlations between FKI and [Formula: see text]O2peak represent a physiological connection between the regulatory and the capacitive system and its exercise performance. In turn, the application of FKI can serve as an indicator for healthy participants to assess exercise tolerance and sport performance.

Dataset Information

Electrical Mobility as an Indicator for Flexibly Deducing the Kinetics of Nanoparticle Evaporation.

Publications

Electrical Mobility as an Indicator for Flexibly Deducing the Kinetics of Nanoparticle Evaporation.

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