Understanding the Antifouling Mechanism of Zwitterionic Monomer-Grafted Polyvinylidene Difluoride Membranes: A Comparative Experimental and Molecular Dynamics Simulation Study

Multiscale Modeling and Simulation of Zwitterionic Anti-fouling Materials

Zwitterionic materials with cationic and anionic moieties in the same chain, being electrically neutral, have excellent hydrophilicity, stability, biocompatibility, and outstanding anti-biofouling performance. Because of their unique properties, zwitterionic materials are widely applied to membrane separation, drug delivery, surface coating, etc. However, what is the root of their unique properties? It is necessary to study the structure-property relationships of zwitterionic compounds to guide the design and development of zwitterionic materials. Modeling and simulation methods are considered to be efficient technologies for understanding advanced materials in principle. This Review systematically summarizes the computational exploration of zwitterionic materials in recent years. First, the classes of zwitterionic materials are summarized. Second, the different scale simulation methods are introduced briefly. To reveal the structure-property relationships of zwitterionic materials, multiscale modeling and simulation studies at different spatial and temporal scales are summarized. The study results indicated that the strong electrostatic interaction between zwitterions with water molecules promotes formation of a stable hydration layer, namely, superhydrophilicity, leading to the excellent anti-fouling properties. Finally, we offer our viewpoint on the development and application of simulation techniques on zwitterionic materials exploration in the future. This work establishes a bridge from atomic and molecular scales to mesoscopic and macroscopic scales and helps to provide an in-depth understanding of the structure-property relationships of zwitterionic materials.

Experimental and computational techniques to investigate the protein resistance of zwitterionic polymers

Most surfaces undergo non-specific protein adsorption upon direct contact with protein-containing environments, resulting in the formation of a protein corona, and the nature and composition of the corona affect the properties of the material. Zwitterionic polymers have oppositely charged groups in their repeating units, which facilitate the formation of a hydration layer on the surface through electrostatic interactions. The hydration layer possesses a strong water-binding ability and can prevent protein adsorption. Therefore, the hydration effect of zwitterionic polymers has become a research focus, and many researchers have investigated this mechanism using experimental and computational methods. This paper reviews the experimental techniques and simulation methods to study the hydration effect of zwitterionic polymers and the advantages and disadvantages of different techniques are discussed.

Machine Learning Aided Design and Optimization of Antifouling Surfaces

Antifouling surfaces, renowned for their strong surface resistance to proteins, cells, or tissues in various biological and environmental conditions, have broad applications in implanted devices, antibacterial coatings, biosensors, responsive materials, water treatment, and lab-on-a-chip. While extensive experimental research exists on antifouling surfaces, machine learning studies on this topic are relatively few. This perspective specifically focuses on exploring the complex relationships between the composition, structure, and properties of antifouling surfaces, examining how these factors correlate with surface hydration and protein adsorption. Different machine learning models have been developed to analyze and predict single and multiple protein adsorptions on various types of surfaces, ranging from structureless surfaces to well-ordered and rigid self-assembled monolayers, dynamically ordered polymer brushes, and complex filtration membranes. These models not only identify key descriptors or functional groups critical for antifouling performance (surface hydration, protein adsorption) but also predict the antifouling properties for a specific surface. Recognizing current challenges, this perspective delineates future research directions in the antifouling field. By leveraging and comparing current machine learning approaches, it aims to advance both the design and fundamental understanding of antifouling surfaces, thereby pushing the boundaries of innovation in this critical field.

Molecular Dynamics Study on Adsorption and Desorption of the Model Oligosaccharide above Polymer Antifouling Membranes

Polysaccharide foulants play a key role in the adhesion of many fouling organisms, which may cause severe marine biofouling. However, the detailed interaction mechanism between polysaccharides and antifouling membranes is still indistinct compared with that between the fouling protein and antifouling surfaces. In this paper, a model oligosaccharide built based on the monosaccharide composition found in diatom extracellular polymeric substances (EPS) was used as a model foulant to investigate its adsorption and desorption above three T4 antifouling membranes. It was found that the anionic poly(3-(methacryloyloxy)propane-1-sulfonate) (T4-SP) antifouling membrane had excellent antifouling ability with respect to the model oligosaccharide, while the oligosaccharide can be easily adsorbed on the poly(2-(dimethylamino)ethyl methacrylate) (T4-DM) membrane with vdW attraction and on the zwitterionic poly(sulfobetaine methacrylate) (T4-SB) membrane with electrostatic attraction. As little is known about the details of polysaccharides' adsorption above antifouling membranes at the molecular level, we hope this work will serve as a theoretical basis for finding more effective materials to prevent or control marine biofouling.

Impact of SiO2 doping on the structure and oil-water separation properties of a PVDF membrane: insights from molecular dynamics simulation

Hybrid inorganic particles combined with polymers are widely used to modify the properties of polymer membranes. However, the mechanism by which particles affect membranes remains unclear. This study investigates SiO2-hybridized PVDF membranes through molecular dynamic simulation, focusing on the interaction between SiO2 clusters and PVDF chains. It examines the impact of varying SiO2 concentrations (3.5 wt%, 6.8 wt%, 9.9 wt%, 12.8 wt%, and 15.5 wt%) on membrane stability and structure. The results indicate that adding SiO2 can inhibit PVDF chain mobility in the membrane with minimal effect on fractional free volume (FFV), except for altering interactions between PVDF-PVDF, PVDF-SiO2, and SiO2-SiO2, thereby affecting the structure of hybrid membranes. The adsorption and diffusion behavior of water and oil molecules on these membranes were also studied. It was observed that the adsorption energy and diffusion coefficient initially increase and then decrease with increasing SiO2 concentration, reaching an optimum between 6.8 wt% and 12.8 wt%. This phenomenon is attributed to the ability of optimal SiO2 concentrations to create hydrophilic channels in PVDF membranes, enhancing water affinity and reducing oil affinity. Consequently, water permeation through the hybrid membrane is promoted, improving the efficiency of oil/water separation compared to pure PVDF membranes. This research contributes to understanding the function of adding inorganic particles to polymer membranes and provides insights for designing advanced functional hybrid membranes.

Perspectives on Theoretical Models and Molecular Simulations of Polymer Brushes

Polymer brushes have witnessed extensive utilization and progress, driven by their distinct attributes in surface modification, tethered group functionality, and tailored interactions at the nanoscale, enabling them for various scientific and industrial applications of coatings, sensors, switchable/responsive materials, nanolithography, and lab-on-a-chips. Despite the wealth of experimental investigations into polymer brushes, this review primarily focuses on computational studies of antifouling polymer brushes with a strong emphasis on achieving a molecular-level understanding and structurally designing antifouling polymer brushes. Computational exploration covers three realms of thermotical models, molecular simulations, and machine-learning approaches to elucidate the intricate relationship between composition, structure, and properties concerning polymer brushes in the context of nanotribology, surface hydration, and packing conformation. Upon acknowledging the challenges currently faced, we extend our perspectives toward future research directions by delineating potential avenues and unexplored territories. Our overarching objective is to advance our foundational comprehension and practical utilization of polymer brushes for antifouling applications, leveraging the synergy between computational methods and materials design to drive innovation in this crucial field.

Zwitterionic Biomaterials

The term "zwitterionic polymers" refers to polymers that bear a pair of oppositely charged groups in their repeating units. When these oppositely charged groups are equally distributed at the molecular level, the molecules exhibit an overall neutral charge with a strong hydration effect via ionic solvation. The strong hydration effect constitutes the foundation of a series of exceptional properties of zwitterionic materials, including resistance to protein adsorption, lubrication at interfaces, promotion of protein stabilities, antifreezing in solutions, etc. As a result, zwitterionic materials have drawn great attention in biomedical and engineering applications in recent years. In this review, we give a comprehensive and panoramic overview of zwitterionic materials, covering the fundamentals of hydration and nonfouling behaviors, different types of zwitterionic surfaces and polymers, and their biomedical applications.

Impeding the Medical Protective Clothing Contamination by a Spray Coating of Trifunctional Polymers

The risk of fomite-mediated transmission in the clinic is substantially increasing amid the recent COVID-19 pandemic as personal protective equipment (PPE) of hospital workers is easily contaminated by direct contact with infected patients. In this context, it is crucial to devise a means to reduce such transmission. Herein, we report an antimicrobial, antiviral, and antibiofouling trifunctional polymer that can be easily coated onto the surface of medical protective clothing to effectively prevent pathogen contamination on the PPE. The coating layer is formed on the surfaces of PPE by the simple spray coating of an aqueous solution of the trifunctional polymer, poly(dodecyl methacrylate (DMA)-poly(ethylene glycol) methacrylate (PEGMA)-quaternary ammonium (QA)). To establish an optimal ratio of antifouling and antimicrobial functional groups, we performed antifouling, antibacterial, and antiviral tests using four different ratios of the polymers. Antifouling and bactericidal results were assessed using Staphylococcus aureus, a typical pathogenic bacterium that induces an upper respiratory infection. Regardless of the molar ratio, polymer-coated PPE surfaces showed considerable antiadhesion (∼65-75%) and antibacterial (∼75-87%) efficacies soon after being in contact with pathogens and maintained their capability for at least 24 h, which is sufficient for disposable PPEs. Further antiviral tests using coronaviruses showed favorable results with PPE coated at two specific ratios (3.5:6:0.5 and 3.5:5.5:1) of poly(DMA-PEGMA-QA). Moreover, biocompatibility assessments using the two most effective polymer ratios showed no recognizable local or systemic inflammatory responses in mice, suggesting the potential of this polymer for immediate use in the field.

Pyrite-embedded porous carbon nanocatalysts assembled in polyvinylidene difluoride membrane for organic pollutant oxidation

FeS₂-embedded in porous carbon (FeS₂/C) was prepared by simultaneous sulfidation and carbonization of an iron-based metal-organic framework precursor, and subsequently immobilized in polyvinylidene fluoride membranes (FeS₂/C@PVDF) for organics removal via peroxymonosulfate (PMS) activation. The composition, structure, and morphology of the FeS₂/C@PVDF membrane were extensively characterized. Scanning electron microscopy images manifest that the FeS₂/C nanoparticles with an average diameter of 40 nm are assembled on the external and internal membrane surface. The as-prepared FeS₂/C@PVDF membrane exhibits excellent performances over a wide pH range of 1.53-9.50, exceeding carbon-free syn-FeS₂@PVDF. The effective degradation could be improved by inner pyrite FeS₂ cores and thus enhanced the electron transfer between carbon shell and PMS. Electron paramagnetic resonance and quenching experiments elucidated that radical (HO^∙, SO₄^∙-) and nonradical (¹O₂) species were the predominant reactive oxidants. In addition, FeS₂/C@PVDF exhibited high stability with low Fe leaching (0.377 mg/L) owing to the effective protection of the outer carbon skeleton. Plentiful porosity of PVDF membranes not only affords a controlled size and confined uniform distribution of the immobilized FeS₂/C nanoparticles, but also enables a persistent exposure of active sites and enhanced mass transfer efficiency. Our findings demonstrate a promise for utilizing the novel FeS₂/C@PVDF membrane as an efficient catalyst for the environmental cleanup.

Molecular dynamics simulation for membrane separation and porous materials: A current state of art review

Computational frameworks have been under specific attention within the last two decades. Molecular Dynamics (MD) simulations, identical to the other computational approaches, try to address the unknown question, lighten the dark areas of unanswered questions, to achieve probable explanations and solutions. Owing to their complex microporous structure on one side and the intricate biochemical nature of various materials used in the structure, separative membrane materials possess peculiar degrees of complications. More notably, as nanocomposite materials are often integrated into separative membranes, thin-film nanocomposites and porous separative nanocomposite materials could possess an additional level of complexity with regard to the nanoscale interactions brought to the structure. This critical review intends to cover the recent methods used to assess membranes and membrane materials. Incorporation of MD in membrane technology-related fields such as desalination, fuel cell-based energy production, blood purification through hemodialysis, etc., were briefly covered. Accordingly, this review could be used to understand the current extent of MD applications for separative membranes. The review could also be used as a guideline to use the proper MD implementation within the related fields.

Molecular simulations and understanding of antifouling zwitterionic polymer brushes

Zwitterionic materials are an important class of antifouling biomaterials for various applications. Despite such desirable antifouling properties, molecular-level understanding of the structure-property relationship associated with surface chemistry/topology/hydration and antifouling performance still remains to be elucidated. In this work, we computationally studied the packing structure, surface hydration, and antifouling property of three zwitterionic polymer brushes of poly(carboxybetaine methacrylate) (pCBMA), poly(sulfobetaine methacrylate) (pSBMA), and poly((2-(methacryloyloxy)ethyl)phosporylcoline) (pMPC) brushes and a hydrophilic PEG brush using a combination of molecular mechanics (MM), Monte Carlo (MC), molecular dynamics (MD), and steered MD (SMD) simulations. We for the first time determined the optimal packing structures of all polymer brushes from a wide variety of unit cells and chain orientations in a complex energy landscape. Under the optimal packing structures, MD simulations were further conducted to study the structure, dynamics, and orientation of water molecules and protein adsorption on the four polymer brushes, while SMD simulations to study the surface resistance of the polymer brushes to a protein. The collective results consistently revealed that the three zwitterionic brushes exhibited stronger interactions with water molecules and higher surface resistance to a protein than the PEG brush. It was concluded that both the carbon space length between zwitterionic groups and the nature of the anionic groups have a distinct effect on the antifouling performance, leading to the following antifouling ranking of pCBMA > pMPC > pSBMA. This work hopefully provides some structural insights into the design of new antifouling materials beyond traditional PEG-based antifouling materials.

Analysis of zwitterionic membrane fouling mechanism caused by HPAM in the presence of electrolytes

Membrane fouling has always been a tough issue that is urgent to solve. Electrolytes which are prevalent in wastewater have a major influence on membrane fouling. Therefore, it is of great significance to understand the role and fouling mechanism of electrolytes in the membrane fouling process. In this work, the zwitterionic membrane is used to process hydrolyzed poly(acrylamide) (HPAM) with the addition of electrolytes (CaCl2, NaCl). Meanwhile, the effect of different electrolytes on the zwitterionic membrane fouling process by hydrolyzed poly(acrylamide) (HPAM) is systematically investigated. It was found that the flux recovery ratio (FRR) of the zwitterionic membrane is nearly 100% after treating HPAM with the addition of electrolytes. Therefore, molecular dynamics (MD) simulations were applied to illustrate the impact of electrolytes on the change of foulant structures and confirm the consequent effect of electrolytes on membrane fouling. According to the experiment and MD simulation results, it is found that the positive ion layer which exists between the HPAM and zwitterionic surface results in the excellent fouling resistance performance of the zwitterionic membrane. The zwitterionic membrane fouling mechanism is analyzed, which is helpful to the understanding of zwitterionic membrane fouling in high salinity wastewater.

Antibiotic Zwitterionic Nanogel Membrane: from Molecular Dynamics Simulation to Structure Manipulation

Membrane separation has been considered as one of the most revolutionary technologies for the removal of oils, dyes, or other pollutants from wastewater. However, most membranes still face great challenges in water permeability, antifouling property, and even antibiotic ability. Possessing a pathogen-repellent surface is of great significance as it can enable membranes to minimize the presence of active viral pathogens. Herein, we demonstrate a distinct design with a molecular dynamics simulation-guided experiment for the surface domination of antibiotic zwitterionic nanogel membranes. The zwitterionic nanoparticle gel (ZNG)/Cu²⁺/glutaraldehyde (GA) synergy system is first simulated by introducing a ZNG into a preset CuCl₂ brine solution and into a GA ethanol solution, in which the nanogel is observed to initially swell and subsequently shrink with the increase of GA concentration, leading to the membrane surface structure transition. Then, the corresponding experiments are performed under strict conditions, and the results suggest the surface structure transition from nanoparticles to network nanoflowers, which are consistent with the simulated results. The obtained network structure membrane with superhydrophilic and underwater superoleophobic abilities can significantly enhance the water permeability as high as almost 40% with its original rejection rate in comparison with unoptimizable ZNG-PVDF (polyvinylidene difluoride) membranes. Moreover, the obtained membrane achieves additional excellent antibiofouling capacity with the antibiotic efficiency exceeding 99.3%, manifesting remarkable potential for disinfection applications. By comparison, the conventional antibiotic methods generally improve the membrane's antibiotic property solely but can hardly improve the other properties of the membrane. That is to say, our simulation combined with the experimental strategy significantly improved the zwitterionic membrane property in this work, which provides a new perspective on the design of high-performance functional materials.

Machine Learning-Enabled Design and Prediction of Protein Resistance on Self-Assembled Monolayers and Beyond

The rational design of highly antifouling materials is crucial for a wide range of fundamental research and practical applications. The immense variety and complexity of the intrinsic physicochemical properties of materials (i.e., chemical structure, hydrophobicity, charge distribution, and molecular weight) and their surface coating properties (i.e., packing density, film thickness and roughness, and chain conformation) make it challenging to rationally design antifouling materials and reveal their fundamental structure-property relationships. In this work, we developed a data-driven machine learning model, a combination of factor analysis of functional group (FAFG), Pearson analysis, random forest (RF) and artificial neural network (ANN) algorithms, and Bayesian statistics, to computationally extract structure/chemical/surface features in correlation with the antifouling activity of self-assembled monolayers (SAMs) from a self-construction data set. The resultant model demonstrates the robustness of Q_CV² = 0.90 and RMSE_CV = 0.21 and the predictive ability of Q_ext² = 0.84 and RMSE_ext = 0.28, determines key descriptors and functional groups important for the antifouling activity, and enables to design original antifouling SAMs using the predicted antifouling functional groups. Three computationally designed molecules were further coated onto the surfaces in different forms of SAMs and polymer brushes. The resultant coatings with negative fouling indexes exhibited strong surface resistance to protein adsorption from undiluted blood serum and plasma, validating the model predictions. The data-driven machine learning model demonstrates their design and predictive capacity for next-generation antifouling materials and surfaces, which hopefully help to accelerate the discovery and understanding of functional materials.

Computational Investigation of Antifouling Property of Polyacrylamide Brushes

Antifouling materials and coatings have broad fundamental and practical applications. Strong hydration at polymer surfaces has been proven to be responsible for their antifouling property, but molecular details of interfacial water behaviors and their functional roles in protein resistance remain elusive. Here, we computationally studied the packing structure, surface hydration, and protein resistance of four poly(N-hydroxyalkyl acrylamide) (PAMs) brushes with different carbon spacer lengths (CSLs) using a combination of molecular mechanics (MM), Monte Carlo (MC), and molecular dynamics (MD) simulations. The packing structure of different PAM brushes were first determined and served as a structural basis for further exploring the CSL-dependent dynamics and structure of water molecules on PAM brushes and their surface resistance ability to lysozyme protein. Upon determining an optimal packing structure of PAMs by MM and optimal protein orientation on PAMs by MC, MD simulations further revealed that poly(N-hydroxymethyl acrylamide) (pHMAA), poly(N-(2-hydroxyethyl)acrylamide) (pHEAA), and poly(N-(3-hydroxypropyl)acrylamide) (pHPAA) brushes with shorter CSLs = 1-3 possessed a much stronger binding ability to more water molecules than a poly(N-(5-hydroxypentyl)acrylamide) (pHPenAA) brush with CSL = 5. Consequently, CSL-induced strong surface hydration on pHMAA, pHEAA, and pHPAA brushes led to high surface resistance to lysozyme adsorption, in sharp contrast to lysozyme adsorption on the pHPenAA brush. Computational studies confirmed the experimental results of surface wettability and protein adsorption from surface plasmon resonance, contact angle, and sum frequency generation vibrational spectroscopy, highlighting that small structural variation of CSLs can greatly impact surface hydration and antifouling characteristics of antifouling surfaces, which may provide structural-based design guidelines for new and effective antifouling materials and surfaces.