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扩散缔合速率方程的量纲分析。

Dimensional analysis of diffusive association rate equations.

作者信息

Chen Jixin

机构信息

Department of Chemistry and Biochemistry, Nanoscale and Quantum Phenomena Institute, Ohio University, Athens, Ohio 45701, USA.

出版信息

AIP Adv. 2024 Nov 14;14(11):115218. doi: 10.1063/5.0238119. eCollection 2024 Nov.

DOI:10.1063/5.0238119
PMID:39555209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11567696/
Abstract

Diffusive adsorption/association is a fundamental step in almost all chemical reactions in diluted solutions, such as organic synthesis, polymerization, self-assembly, biomolecular interactions, electrode dynamics, catalysis, chromatography, air and water environmental dynamics, and social and market dynamics. However, predicting the rate of such a reaction is challenging using the equations established over 100 years ago. Several orders of magnitude differences between the theoretical predictions and experimental measurements for various systems, from self-assembled monolayers to protein-protein aggregations, make such calculations meaningless in many situations. I believe the major problem is that the time-dependent evolution curve of Fick's gradient is an ideal assumption in most cases, and its slope is significantly overestimated. This paper digs into Fick's gradient problem for 3D cases and provides a solution using the single-molecule diffusion probability density function discretely.

摘要

扩散吸附/缔合是稀溶液中几乎所有化学反应的基本步骤,如有机合成、聚合反应、自组装、生物分子相互作用、电极动力学、催化、色谱分析、空气和水环境动力学以及社会和市场动力学。然而,使用100多年前建立的方程来预测此类反应的速率具有挑战性。从自组装单分子层到蛋白质-蛋白质聚集,各种系统的理论预测和实验测量之间存在几个数量级的差异,这使得在许多情况下这种计算毫无意义。我认为主要问题在于,菲克梯度的时间演化曲线在大多数情况下是一个理想假设,其斜率被显著高估。本文深入研究了三维情况下的菲克梯度问题,并使用单分子扩散概率密度函数离散地给出了一个解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/53f311b73414/AAIDBI-000014-115218_1-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/6124813cf64a/AAIDBI-000014-115218_1-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/64ccac531b5e/AAIDBI-000014-115218_1-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/290d83bccefc/AAIDBI-000014-115218_1-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/4e96b4b4c353/AAIDBI-000014-115218_1-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/9ecd92e5c70a/AAIDBI-000014-115218_1-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/acdbae1a506b/AAIDBI-000014-115218_1-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/53f311b73414/AAIDBI-000014-115218_1-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/6124813cf64a/AAIDBI-000014-115218_1-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/64ccac531b5e/AAIDBI-000014-115218_1-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/290d83bccefc/AAIDBI-000014-115218_1-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/4e96b4b4c353/AAIDBI-000014-115218_1-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/9ecd92e5c70a/AAIDBI-000014-115218_1-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/acdbae1a506b/AAIDBI-000014-115218_1-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fc5/11567696/53f311b73414/AAIDBI-000014-115218_1-g007.jpg

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