Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein Diffusion in the Membrane

Protein Diffusion in the Membrane

Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...

Dialysis

Dialysis

Dialysis is a diffusion-based purification process that separates analyte molecules from a complex matrix. This is accomplished by allowing molecules in the solution to pass through a semipermeable membrane into a liquid on the other side. The membrane is usually made of cellulose acetate or cellulose nitrate, and the second liquid must be miscible with the solution. Ions (e.g., chloride or sodium) or organic molecules (e.g., glucose) can pass through the membrane pores, which generally have...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

ForestSAR-YOLO: real-time detection of small human targets in UAV imagery.

Scientific reports·2026

Same author

Assessing the onset of spring water-level rise in snowmelt-dominated rivers of northeastern Russia using machine learning.

Scientific reports·2026

Same author

Multi-objective optimization of a regional biogas supply chain using organic waste.

Scientific reports·2026

Same author

A review of applications of machine learning in quantum dots research.

Discover nano·2026

Same author

Dual-loop proportional control for high-precision induction brazing of thin-walled aluminum waveguides.

Scientific reports·2026

Same author

Data-Driven Optimization of Discontinuous and Continuous Fiber Composite Processes Using Machine Learning: A Review.

Polymers·2025

Search research articles

Related Experiment Video

Updated: Jun 26, 2025

Hydrophobic Salt-modified Nafion for Enzyme Immobilization and Stabilization

Hydrophobic Salt-modified Nafion for Enzyme Immobilization and Stabilization

Published on: July 11, 2012

Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach.

Ivan Malashin¹, Daniil Daibagya^1,2, Vadim Tynchenko¹

¹Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia.

|May 11, 2024

Summary

This summary is machine-generated.

This study models Nafion membrane behavior in salt solutions using machine learning. It accurately predicts diffusion coefficients during soaking and drying, crucial for electrochemical applications.

Keywords:

IR spectroscopy Nafion diffusion fine-tuning optimization genetic algorithm machine learning neural networks

More Related Videos

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

Published on: February 23, 2018

Controlled Synthesis and Fluorescence Tracking of Highly Uniform PolyN-isopropylacrylamide Microgels

Controlled Synthesis and Fluorescence Tracking of Highly Uniform PolyN-isopropylacrylamide Microgels

Published on: September 8, 2016

Related Experiment Videos

Last Updated: Jun 26, 2025

Hydrophobic Salt-modified Nafion for Enzyme Immobilization and Stabilization

Hydrophobic Salt-modified Nafion for Enzyme Immobilization and Stabilization

Published on: July 11, 2012

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

Published on: February 23, 2018

Controlled Synthesis and Fluorescence Tracking of Highly Uniform PolyN-isopropylacrylamide Microgels

Controlled Synthesis and Fluorescence Tracking of Highly Uniform PolyN-isopropylacrylamide Microgels

Published on: September 8, 2016

Area of Science:

Polymer science and electrochemistry
Materials science and engineering

Background:

Nafion membranes are vital in electrochemical devices but behave complexly in saline environments.
Understanding ion and water transport in Nafion is critical for optimizing membrane performance.

Purpose of the Study:

To investigate Nafion membrane's infrared (IR) spectra during hydration and dehydration in salt solutions.
To determine diffusion coefficients for Nafion in saline conditions using Fick's second law.
To develop a machine learning model for predicting these diffusion coefficients.

Main Methods:

Analysis of Nafion membrane IR spectra during soaking and drying in salt solutions of varying concentrations.
Application of Fick's second law and exponential approximation to derive diffusion coefficients.
Machine learning, including genetic algorithm (GA) optimization of neural network hyperparameters, for predictive modeling.

Main Results:

Accurate prediction of diffusion coefficients for Nafion membranes in saline solutions.
Identification of optimal neural network architectures and activation functions (ReLU, ELU, sigmoid) for predicting soaking and drying coefficients.
Quantification of Nafion's complex behavior in different salt concentrations.

Conclusions:

Machine learning models, particularly optimized neural networks, can effectively predict Nafion diffusion coefficients in saline environments.
The study provides valuable insights into Nafion membrane transport properties, essential for advanced electrochemical applications.
This research enhances the understanding of Nafion's performance in diverse electrochemical systems.