Pressure-driven polymeric membrane performance prediction, new membrane dimensionless number, and considerations for effective membrane design, ...

Published on by

Pressure-driven polymeric membrane performance prediction, new membrane dimensionless number, and considerations for effective membrane design, ...
Pressure-driven polymeric membrane performance prediction, new membrane dimensionless number, and considerations for effective membrane design, selection, testing, and operation

Alexander R. Anim-Mensah1,2*
1African Membrane Society (AMSIC), a Ecole Nationale d’Ingénieurs du Mali Abderhamane Baba Touré, Bamako, Mali
2i2i Innovation MegaHub (i2iMegaHub), Accra, Ghana
The demand for polymeric membranes in industries such as fine chemicals, petroleum, and pharmaceuticals underscores the need to optimize organic separation systems. This involves enhancing performance, longevity, and cost-efficiency while tackling chemical and mechanical instabilities. A model is here developed which relates membrane performance, indicated by the permeate solute concentration (Cpi) of species i, to the real-time compressive Young’s modulus (E) during compaction with permeation under a transmembrane pressure (ΔP) or compressive stress. Lower Cpi values indicate better performance. The model integrates solvent densities (ρi), solubility parameters of the membrane (δM), solute (δSo), solvent (δSv), and the extent of membrane constraint (ϕ). It also considers membrane swelling (Ls) and compaction (Lc) with the associated Poisson ratio (γ), providing a comprehensive framework for predicting membrane performance. A key feature is the dimensionless parameter β, defined as ln (Ls/Lc), which describes different operational regimes (β < 1, β = 1, β > 1). This parameter connects membrane affinity characteristics with mechanical properties. The model’s capabilities were demonstrated using three organic separation systems (A, B, and C) which separated isoleucine from DMF, methanol, and hexane solutions, respectively, using nanofiltration (NF) membranes with low, medium, and high E values. The transmembrane pressure ranged from 0.069 to 5.52 MPa (10–800 psi) for β < 1. The performance results indicate that the trend of System B (medium E) > System A (low E) > System C (high E), correlating to decreasing solvent–solute interactions (ΔδSoSv) and compaction levels. Moderate compaction, resulting in moderate membrane resistance and densification, proved beneficial. Cpi–β plots revealed three distinct slopes, corresponding to elastic deformation, plastic deformation, and the densification of membrane polymers, thus guiding optimal ΔP ranges for operation. This model paves the way for advancing polymeric pressure-driven membrane research and offers new insights into membrane selection, testing, design, and operation.

1 Introduction
Polymeric membranes are critical for processes such as delivery, selective transport, discrimination, and separation (Anim-Mensah, et al., 2010). Of these processes, separation is gaining prominence across the chemical, petroleum, and pharmaceutical industries due to its effectiveness, compactness, and cost efficiency (Iulianelli and Drioli, 2020; Jhaveri and Murthy, 2016). Polymeric materials, valued for their flexibility and affordability, have found increasing industrial application, especially in organic solvent environments (Zahid et al., 2018).

However, membranes in such environments face challenges such as excessive swelling and, in extreme cases, dissolution, which compromises performance and longevity (Ebert et al., 2004; Wang et al., 2023). Addressing chemical and mechanical instabilities is crucial to improving operational cost-effectiveness and extending membrane lifespan (Oxley and Livingston, 2024).

Polymeric membranes, especially in pressure-driven systems like ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO), and gas separation, undergo varying degrees of compaction and densification due to applied transmembrane pressure ΔP (Ng et al., 2019).

Membranes swell upon initial contact with permeating fluids under no pressure, followed by compaction during permeation, leading to densification, reduced porosity, and altered performance (Hung et al., 2022; Sánchez-Arévalo et al., 2023). The compressive stress applied in these systems deforms the polymer structure, causing elastic or plastic deformation and increasing resistance as free volume reduces (Davenport et al., 2020).

Polymeric materials can be categorized based on their stress-strain behavior as soft, medium, or hard, reflecting their resistance to deformation (Rahimidehgolan and Altenhof, 2023). Soft materials, such as polydimethylsiloxane (PDMS) while compressed, exhibit low Young’s modulus and high flexibility, while medium materials like polyvinylidene fluoride (PVDF) and hard materials like polyimide (PI) demonstrate varying degrees of stiffness and strength (Ariati et al., 2021; Overview on PVDF Material, 2024; Overview on PI Material, 2024). Notably, these properties are often measured in the absence of fluids, thus neglecting changes induced by membrane–fluid interactions during operation (Anim-Mensah et al., 2005).

In membrane separation, the interaction between membrane and solvent (ΔδMSv) significantly influences mechanical stability (Anim-Mensah et al., 2005). Strong membrane–solvent affinity can cause excessive swelling, reducing stability, while weaker interactions minimize mechanical impacts (Sánchez-Arévalo et al., 2023). Long-term mechanical stability is essential for reliable performance, yet many existing models fail to incorporate real-time data reflective of actual separation conditions.

To address these limitations, real-time data-driven approaches are needed to better characterize separation systems and enhance membrane performance. Ultrasonic time-domain reflectometry (UTDR) has been identified as a valuable technology for the real-time detection and monitoring of swelling, compaction, and densification, offering flexibility for improving membrane systems (Aghajani et al., 2017). As the demand for advanced polymeric membranes grows, leveraging such technologies will be essential for driving innovation and ensuring sustainable improvements.

Swelling during preparation is inevitable for polymeric pressure-driven membranes due to their constraints and exposure to permeating fluids. During operation, these membranes experience varying degrees of densification caused by compaction under applied transmembrane pressure (ΔP), which significantly influences their performance and stability (Bilad et al., 2022; Chu et al., 2021; Ng et al., 2019).

This model integrates key chemical, mechanical, and thermodynamic parameters into a comprehensive framework for pressure-driven membrane systems. It highlights the relationships between these parameters, offering insights for optimizing membrane design, testing, selection, and operation. The model explains how factors such as membrane constraint, Poisson ratio, swelling, and compaction contribute to densification and membrane resistance, ultimately affecting transport and separation performance. Additionally, it addresses the real-time mechanical behavior of membranes during operation, including variations in Poisson ratio, axial and lateral strains, and Young’s modulus (E), while also accounting for interactions between membrane, solvent, and solution, as well as solvent density, to evaluate impacts on stability and performance.

A key feature of the model is the dimensionless parameter β, defined as β = ln (Ls/Lc), which relates membrane affinity characteristics to mechanical properties by comparing swelling (Ls) and compaction (Lc). This parameter allows the model to describe different swelling and compaction regimes: β > 1 (swelling dominant), β = 1 (swelling and compaction balanced), and β < 1 (compaction dominant).

The model also introduces a novel research direction by rigorously integrating mechanical, chemical, and thermodynamic parameters to improve separation system designs. It emphasizes the importance of incorporating real-time data for accurate membrane characterization and validation, which can help refine existing theories, challenge current models, and develop innovative approaches for better-performing and more reliable membrane systems.
https://doi.org/10.3389/frmst.2024.1454589

Taxonomy