Atomistic Simulations of Biofouling and Molecular Transfer of a Cross-linked Aromatic Polyamide Membrane for Desalination

Synergistic effects of hydrophilic function group and micropores on water evaporation in a novel carbon hydrogels for efficient solar steam generation

Solar steam generation (SSG) using hydrogels is emerging as a promising technology for clean water production. Herein, a novel oxygen-doped microporous carbon hydrogel (OPCH), rich in hydrophilic groups and micropores, has been synthesized from microalgae to optimize SSG. OPCH outperforms hydrogels with hydrophobic porous carbon or nonporous hydrophilic biochar, significantly reducing water's evaporation enthalpy from 2216.06 to 1107.88 J g-1 and activating 42.3 g of water per 100 g for evaporation, resulting in an impressive evaporation rate of 2.44 kg m-2 h-1 under one sun. A detailed investigation into the synergistic effects of hydrophilic groups and micropores on evaporation via a second derivative thermogravimetry method revealed two types of bonded water contributing to enthalpy reduction. Molecular dynamics simulations provided further insights, revealing that the hydrophilic micropores considerably decrease both the number and the lifetime of hydrogen bonds among water molecules. This dual effect not only reduces the energy barrier for evaporation but also enhances the kinetic energy needed for the phase transition, significantly boosting the water evaporation process. The sustained high evaporation rates of OPCH, observed across multiple cycles and under varying salinity conditions, underscore its potential as a highly efficient and sustainable solution for SSG applications.

New insight into the mechanism of biofouling-resistant thiazole-linked covalent organic frameworks for selective uranium capture from seawater

The extraction of uranium from seawater is crucial for the sustainable production of nuclear fuel. Traditional amidoxime-functionalized adsorbents suffer from competitive adsorption of vanadium ion and biofouling. These challenges motivate the development of novel adsorbents for selective uranium extraction from seawater. Herein, four kinds of thiazole-linked covalent organic frameworks (COFs) were investigated to harvest uranium from seawater. The selectivity and anti-biofouling performance were systematically investigated through the molecular dynamics (MD) simulations. Driven by the pore size sieving effect and electrostatic interaction, the Ca2UO2(CO3)3 complex and vanadate anions were selectively separated by different COFs in special areas. On one hand, benefits from the small steric partition factor, the Ca2UO2(CO3)3 complex can stick on the surface of COFs. On the other hand, the dispersive negatively and positively charged areas of studied COFs work as potential binding sites for the Ca2UO2(CO3)3 complex and vanadate anions, respectively. Moreover, an analysis of pulling force and desorption time between uranium and vanadium ions further confirmed the selectivity of various thiazole-linked COFs. The anti-biofouling property was comparatively investigated by dynamic trajectory and solvent accessible surface area. Our outcomes illustrate that the hydroxyl and zwitterionic groups in the thiazole-linked COFs endow their strong surface hydrations to resist marine biofouling. In particular, the TpBdsaPa is identified as a promising candidate due to charge dispersed zwitterionic group as well as remarkable anti-biofouling ability. The present study sheds an atomic-level understanding of the thiazole-linked COFs for selective uranium uptaking from seawater, which will provide aid to design novel adsorbent with highly selective uranium extraction capacity and strong anti-biofouling property.

Determination of protein conformation and orientation at buried solid/liquid interfaces

Protein structures at solid/liquid interfaces mediate interfacial protein functions, which are important for many applications. It is difficult to probe interfacial protein structures at buried solid/liquid interfaces in situ at the molecular level. Here, a systematic methodology to determine protein molecular structures (orientation and conformation) at buried solid/liquid interfaces in situ was successfully developed with a combined approach using a nonlinear optical spectroscopic technique - sum frequency generation (SFG) vibrational spectroscopy, isotope labeling, spectra calculation, and computer simulation. With this approach, molecular structures of protein GB1 and its mutant (with two amino acids mutated) were investigated at the polymer/solution interface. Markedly different orientations and similar (but not identical) conformations of the wild-type protein GB1 and its mutant at the interface were detected, due to the varied molecular interfacial interactions. This systematic strategy is general and can be widely used to elucidate protein structures at buried interfaces in situ.

Wrinkles, Ridges, Miura-Ori, and Moiré Patterns in MoSe2 Using Neural Networks

Effects of lateral compression on out-of-plane deformation of two-dimensional MoSe₂ layers are investigated. A MoSe₂ monolayer develops periodic wrinkles under uniaxial compression and Miura-Ori patterns under biaxial compression. When a flat MoSe₂ monolayer is placed on top of a wrinkled MoSe₂ layer, the van der Waals (vdW) interaction transforms wrinkles into ridges and generates mixed 2H and 1T phases and chain-like defects. Under a biaxial strain, the vdW interaction induces regions of Miura-Ori patterns in bilayers. Strained systems analyzed using a convolutional neural network show that the compressed system consists of semiconducting 2H and metallic 1T phases. The energetics, mechanical response, defect structure, and dynamics are analyzed as bilayers undergo wrinkle-ridge transformations under uniaxial compression and moiré transformations under biaxial compression. Our results indicate that in-plane compression can induce self-assembly of out-of-plane metasurfaces with controllable semiconducting and metallic phases and moiré patterns with unique optoelectronic properties.

Graph Clustering Analyses of Discontinuous Molecular Dynamics Simulations: Study of Lysozyme Adsorption on a Graphene Surface

Understanding the interfacial behaviors of biomolecules is crucial to applications in biomaterials and nanoparticle-based biosensing technologies. In this work, we utilized autoencoder-based graph clustering to analyze discontinuous molecular dynamics (DMD) simulations of lysozyme adsorption on a graphene surface. Our high-throughput DMD simulations integrated with a Go̅-like protein-surface interaction model makes it possible to explore protein adsorption at a large temporal scale with sufficient accuracy. The graph autoencoder extracts a low-dimensional feature vector from a contact map. The sequence of the extracted feature vectors is then clustered, and thus the evolution of the protein molecule structure in the absorption process is segmented into stages. Our study demonstrated that the residue-surface hydrophobic interactions and the π-π stacking interactions play key roles in the five-stage adsorption. Upon adsorption, the tertiary structure of lysozyme collapsed, and the secondary structure was also affected. The folding stages obtained by autoencoder-based graph clustering were consistent with detailed analyses of the protein structure. The combination of machine learning analysis and efficient DMD simulations developed in this work could be an important tool to study biomolecules' interfacial behaviors.

Molecular Dynamics Study on Properties of Hydration Layers above Polymer Antifouling Membranes

Zwitterionic polymers as crucial antifouling materials exhibit excellent antifouling performance due to their strong hydration ability. The structure−property relationship at the molecular level still remains to be elucidated. In this work, the surface hydration ability of three antifouling polymer membranes grafting on polysiloxane membranes Poly(sulfobetaine methacrylate) (T4-SB), poly(3-(methacryloyloxy)propane-1-sulfonate) (T4-SP), and poly(2-(dimethylamino)ethyl methacrylate) (T4-DM) was investigated. An orderly packed, and tightly bound surface hydration layer above T4-SP and T4-SB antifouling membranes was found by means of analyzing the dipole orientation distribution, diffusion coefficient, and average residence time. To further understand the surface hydration ability of three antifouling membranes, the surface structure, density profile, roughness, and area percentage of hydrophilic surface combining electrostatic potential, RDFs, SDFs, and noncovalent interactions of three polymers’ monomers were studied. It was concluded that the broadest distribution of electrostatic potential on the surface and the nature of anionic SO3- groups led to the following antifouling order of T4-SB > T4-SP > T4-DM. We hope that this work will gain some insight for the rational design and optimization of ecofriendly antifouling materials.

Multiscale Simulation of Protein Corona Formation on Silver Nanoparticles: Study of Ovispirin-1 Peptide Adsorption

The exposure of nanoparticles (NPs) to biofluids leads to the rapid coverage of proteins, named protein corona, which alters the NPs' chemicophysical and biological properties. Fundamental studies of the protein corona are thus critical to the increasing applications of NPs in nanotechnology and nanomedicines. The present work utilizes multiscale simulations of a model biological system, small ovispirin-1 peptides, and bare silver nanoparticles (AgNPs) to examine the NPs' size and surface hydrophilicity effects on formation dynamics and the structure of the peptide corona. Our simulations revealed the different adsorption dynamics of ovispirin-1 peptides on the NPs, including the direct adsorption of a single peptide and peptide aggregates and multistep adsorption, as well as an intermediate cycle of desorption and readsorption. Notably, the whole process of peptide adsorption on hydrophilic AgNP surfaces can be generalized as three stages: diffusion to the surface, initial landing via hydrophilic residues, and the final attachment. The decrease in AgNP's size leads to faster adsorption with more heterogeneous peptide interfacial dynamics, a denser and inhomogeneous peptide packing structure, and a wider distribution of adsorption orientations. Subsequent atomistic molecular dynamics simulations demonstrated that on the hydrophilic AgNP surfaces, adsorbed peptides display moderate changes in their secondary structure, resulting in further changes of corona composition, i.e., amino acid residue distribution on the surface.

Discontinuous Molecular Dynamics Simulations of Biomolecule Interfacial Behavior: Study of Ovispirin-1 Adsorption on a Graphene Surface

Fundamental understanding of biomolecular interfacial behavior, such as protein adsorption at the microscopic scale, is critical to broad applications in biomaterials, nanomedicine, and nanoparticle-based biosensing techniques. The goal of achieving both computational efficiency and accuracy presents a major challenge for simulation studies at both atomistic and molecular scales. In this work, we developed a unique, accurate, high-throughput simulation method which, by integrating discontinuous molecular dynamics (DMD) simulations with the Go-like protein-surface interaction model, not only solves the dynamics efficiently, but also describes precisely the protein intramolecular and intermolecular interactions at the atomistic scale and the protein-surface interactions at the coarse-grained scale. Using our simulation method and in-house developed software, we performed a systematic study of α-helical ovispirin-1 peptide adsorption on a graphene surface, and our study focused on the effect of surface hydrophobic interactions and π-π stacking on protein adsorption. Our DMD simulations were consistent with full-atom molecular dynamics simulations and showed that a single ovispirin-1 peptide lay down on the flat graphene surface with randomized secondary structure due to strong protein-surface interactions. Peptide aggregates were formed with an internal hydrophobic core driven by strong interactions of hydrophobic residues in the bulk environment. However, upon adsorption, the hydrophobic graphene surface can break the hydrophobic core by denaturing individual peptide structures, leading to disassembling the aggregate structure and further randomizing the ovispirin-1 peptide's secondary structures.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Machine Learning Analysis of the Thermodynamic Responses of In Situ Dielectric Spectroscopy Data in Amino Acids and Inorganic Electrolytes

Dielectric spectroscopy (DS) can be a robust in situ technique for geochemical applications. In this study, we applied deep-learning techniques to DS measurement data to enable rapid science interrogation and identification of electrolyte solutions containing salts and amino acids over a wide temperature range (20 to -60 °C). For the purpose of searching for signs of life, detecting amino acids is a fundamental high priority for field and planetary instruments as amino acids are one of the building blocks for life as we know it. A convolutional neural network (CNN) with channel-wise one-dimensional filters is proposed to fulfill the task, using the DS data of amino acid and inorganic salt solutions. Experimental results show that the CNN with two convolutional layers and one fully connected layer can effectively differentiate solutions containing amino acids from those containing salts in both the liquid and solid (water ice) states. To complement the experimental measurements and CNN analysis, the diffusive behaviors of ions (K⁺, Cl^-, and OH^-) were further discussed with atomistic molecular dynamics simulations performed in this work as well as the quantum simulation published in the literature. Combining DS with machine-learning techniques and simulations will greatly facilitate more real-time decision-making of mobility systems for future exploratory endeavors in other worlds beyond Earth.

One-Step and Low-Cost Designing of Two-Layered Active-Layer Superhydrophobic Silicalite-1/PDMS Membrane for Simultaneously Achieving Superior Bioethanol Pervaporation and Fouling/Biofouling Resistance

Recently, the coupling of biofuel fermentation broths and pervaporation has been receiving increasing attention. Some challenges, such as the destructive effects of constituents of the real fermentation broth on the membrane performances, the lethal effects of the membrane surface chemical modifiers on the microorganisms, and being expensive, are against this concept. For the first time, a continuous study on the one-step and low-cost preparation of superhydrophobic membranes for bioethanol separation is made to address these challenges. In our previous work, spraying as a fast, scalable, and low-cost procedure was applied to fabricate the one-layered active-layer hydrophobic (OALH) silicalite-1/polydimethylsiloxane (PDMS) membrane on the low-cost mullite support. In this work, the spraying method was adopted to fabricate a two-layered active-layer superhydrophobic (TALS) silicalite-1/PDMS membrane, where the novel active layer consisted of two layers with different hydrophobicities and densities. Contact-angle measurements, surface charge determination, scanning electron microscopy, atomic force microscopy, and pervaporation separation using a 5 wt % ethanol solution were used to statically evaluate the fouling/biofouling resistance and pervaporation performances of OALH and TALS membranes in this study. The TALS membrane presented a better resistance and performance. For dynamic experiments, the Box-Behnken design was used to identify the effects of substrates, microorganisms, and nutrient contents as the leading indicators of fermentation broth on the TALS membrane performances for the long-term utilization. The maximum performances of 1.88 kg/m²·h, 32.34, and 59.04 kg/m²·h concerning the permeation flux, separation factor, and pervaporation separation index were obtained, respectively. The dynamic fouling/biofouling resistance of the TALS membrane was also characterized using energy-dispersive X-ray spectroscopy of all the tested membranes. The TALS membrane demonstrated the synergistic resistance of membrane fouling and biofouling. Eventually, the novel TALS membrane was found to have potential for biofuel recovery, especially bioethanol.

Protein Corona on Gold Nanoparticles Studied with Coarse-Grained Simulations

Understanding protein corona formation in an aqueous environment at the molecular and atomistic levels is critical to applications such as biomolecule-detection and drug delivery. In this work, we employed mesoscopic coarse-grained simulations to study ovispirin-1 and lysozyme protein coronas on bare gold nanoparticles. Our study showed that protein corona formation is governed by protein-surface and protein-protein interactions, as well as the surface hydrophobic effect. The corona structure was found to be dependent on protein types and the size of nanoparticles. Ovispirin proteins form homogeneous single-layered adsorption in comparison with the lysozyme's inhomogeneous multilayered aggregates on gold NP surfaces. The decrease in nanoparticle size leads to more angular degrees of freedom for protein adsorption orientation. Subsequent atomistic molecular dynamics simulations further demonstrate the loss of secondary structure of ovispirin upon adsorption and the heterogeneity of its local structure.