Effects of functionalization on the nanofiltration performance of PIM-1: Molecular simulation investigation

Highly Thermally Stable and Gas Selective Hexaphenylbenzene Tröger's Base Microporous Polymers

This study shows the multistep synthesis of a series of Tröger's base polymers of intrinsic microporosity (TB-PIMs) based on a hexaphenylbenzene (HPB) core, with a focus on evaluating their thermal stability, porosity, and CO2 capture performance. Both ladder and linear structures were prepared, designed to feature tunable nitrogen content and porosity. Our findings demonstrate that polymers with higher nitrogen content, such as tetra-TB-HPB, exhibit superior CO2 affinity and selectivity, attributed to enhanced interactions with CO2 and optimized micropore sizes. Linear TB-polymers 1 and 2 are also made for comparison and show competitive performance in carbon capture, suggesting that cost-effective, simpler-to-synthesize materials can achieve efficient gas separation. The study reveals that increased porosity significantly enhances CO2 capacity and selectivity, particularly in networked TB-HPB-PIMs with high surface areas and narrow micropores, achieving values up to 544 m2 g-1, CO2 uptake of 2.00 mmol g-1, and CO2/N2 selectivity of 45.6. The thermal properties of these materials, assessed via thermogravimetric analysis (TGA), show that TB-HPB-PIMs maintain robust thermal stability in nitrogen atmosphere, with tetra- and hexa-TB-HPBs leading the series. However, in oxidative environments, denser polymers such as TB-HPB and linear TB-polymer 1 demonstrate higher performance, likely due to restricted air diffusion. Overall, our findings highlight the critical need to balance porosity and thermal stability in TB-HPB-PIMs for applications in gas separation, carbon capture, and the potential for these polymers as flame retardant materials. Tetra-TB-HPB stands out as the most promising material for CO2 capture and thermal stability under inert conditions, while denser polymers like TB-HPB offer superior performance in oxidative environments.

Dual-phase microporous polymer nanofilms by interfacial polymerization for ultrafast molecular separation

Fine-tuning microporosity in polymers with a scalable method has great potential for energy-efficient molecular separations. Here, we report a dual-phase molecular engineering approach to prepare microporous polymer nanofilms through interfacial polymerization. By integrating two micropore-generating units such as a water-soluble Tröger's base diamine (TBD) and a contorted spirobifluorene (SBF) motif, the resultant TBD-SBF polyamide shows an unprecedentedly high surface area. An ultrathin TBD-SBF membrane (~20 nm) exhibits up to 220 times improved solvent permeance with a moderate molecular weight cutoff (~640 g mol-1) compared to the control membrane prepared by conventional chemistry, which outperforms currently reported polymeric membranes. We also highlight the great potential of the SBF-based microporous polyamides for hydrocarbon separations by exploring the isomeric effects of aqueous phase monomers to manipulate microporosity.

Molecular Dynamics Simulation Study of Organic Solvents Confined in PIM-1 and P84 Polyimide Membranes

Organic solvent nanofiltration (OSN) has recently proved to be a promising separation process thanks to the development of membrane materials with suitable resistance toward organic solvents. Among those materials, P84 polyimide membranes are currently the most used in OSN while PIM-1 membranes have recently attracted attention due to their high permeance in apolar solvents and alcohols. Both P84 and PIM-1 membranes have nanosized free volumes, and their separation performance is finely connected to polymer/solvent interactions. Consequently, modeling OSN membranes at the molecular scale is highly desirable in order to rationalize experimental observations and gain a deeper insight into the molecular mechanisms ruling solvent and solute permeation. A prerequisite for understanding solvent transport through OSN membranes is therefore to characterize the membrane/solvent interactions at the molecular level. For that purpose, we carried out molecular simulations of three different solvents, acetone, methanol, and toluene in contact with P84 and PIM-1 membranes. The solvent uptake by both membranes was found to be correlated to the degree of confinement of the solvent, the polymer swelling ability and polymer/solvent interactions. The translational dynamics of the solvent molecules in the PIM-1 membrane was found to be correlated with the solvent viscosity due to the relatively large pores of this membrane. That was not the case with the P84 membrane, which has a much denser structure than the PIM-1 membrane and for which it was observed that the translational dynamics of the confined solvent molecules was directly correlated to the affinity between the P84 polymer and the solvent.

Accelerating Discovery of High Fractional Free Volume Polymers from a Data-Driven Approach

As a fundamental structure characteristic in polymers, fractional free volume (FFV) plays an indispensable role in governing polymer properties and performance. However, the design of new high-FFV polymers is challenging. In this study, we report a data-driven approach and aim to accelerate the discovery of high-FFV polymers. First, a computational method is proposed to calculate FFV, and a two-step fragmentation method is developed to construct a fragment library for digital representation of polymer structures. Data mining is employed to identify promising fragments for high FFV. Subsequently, machine learning (ML) models are trained using a data set with 1683 polymers and their excellent transferability is demonstrated by out-of-sample predictions in another data set with 11,479 polymers. Finally, the ML models are used to screen ∼1 million hypothetical polymers, and 29,482 polymers with FFV > 0.2 are shortlisted; representative high-FFV polymers are validated by molecular simulations, and design strategies are highlighted. To further facilitate the discovery of new high-FFV polymers, we develop an online interactive platform https://ffv-prediction.herokuapp.com, which allows for rapid FFV predictions, given polymer structures. The data-driven approach in this study might advance the development of new high-FFV polymers and further explore quantitative structure-property relationships for polymers.