Skip to content
#diffusion models Open access

Interconnected pore networks as a unifying framework for transport in dense polymer membranes

Sep 2026 · Frontiers in Membrane Science and Technology · 1 citation · 78 references
Membrane Separation and Gas Transport

Abstract

Transport in many dense polymer membranes used for reverse osmosis, organic solvent nanofiltration, pervaporation, and gas separation has traditionally been interpreted through the solution–diffusion model, which treats the membrane as a dense, nonporous polymer phase where molecules dissolve and diffuse under concentration gradients. Although this framework has been useful for correlating membrane performance, its mechanistic foundation for water and solvent transport is contradicted by current experimental and molecular simulation evidence. Observations from positron annihilation lifetime spectroscopy, scattering methods, spectroscopic probes, and molecular dynamics simulations demonstrate that polymer membranes, long considered dense and nonporous, contain interconnected (sub)nanometer free-volume networks rather than isolated transient cavities. These molecular pathways provide a more physically grounded basis for interpreting transport across diverse membrane processes. Here, we synthesize recent experimental and molecular simulation evidence to establish interconnected pore networks as a unifying mechanistic framework for transport across major classes of dense polymer membranes. In pressure-driven liquid separations, solvent transport is governed by pressure-driven viscous flow through interconnected, solvent-filled pore networks. In pervaporation, liquid-like and vapor-like domains coexist within the membrane, indicating an internal phase transition rather than evaporation only at the downstream surface. In glassy gas-separation polymer membranes, permeability and selectivity are governed by pore connectivity, molecular sieving, and gas–wall interactions. Together, these insights shift membrane design from optimizing empirical solubility and diffusivity parameters toward engineering pore size, connectivity, tortuosity, and pore-wall chemistry.

Read PDF

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Conference Sep 2010

Exploring the Sources of Waste in Kanban Software Development Projects

The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...

Marko Ikonen, Petri Kettunen, Nilay V. Oza et al. · 67 citations · ⚡9

Related blog posts

MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.