Molecular Systems Design & Engineering最新文献

Ice formation on solid surfaces presents major engineering challenges. Although zwitterionic polymer coatings show promising anti-icing performance, the fundamental role of the side-chain carbon spacer in governing polymer–water and polymer–ice interactions remains insufficiently understood. Here, density functional theory (DFT) calculations were used to investigate how the spacer length between zwitterionic groups affects these interactions, focusing on poly(2-methacryloyloxyethyl phosphorylcholine) (pMPC), a known anti-icing and anti-fouling polymer model system. To guide molecular design, the –CH₂– spacer length was systematically varied to generate five representative polymers: pMPC-1, pMPC, pMPC+1, pMPC+2, and pMPC+3, with one, two, three, four, and five –CH₂– units between the zwitterionic moieties, respectively. A comprehensive evaluation of polymer–water interactions, spanning the electronic structure, side-chain conformations governing water accessibility, the number and strength of bound water molecules, adsorption energetics, and charge transfer, was performed to elucidate how spacer-length-dependent molecular features control hydration. These analyses show that pMPC+1 and pMPC+2, containing three- and four-carbon spacers, respectively, exhibit the most favorable hydration behavior by achieving an optimal balance between side-chain flexibility and crumpling, which enables both strong and sufficiently abundant water binding. Interaction analysis with ice clusters further indicates that pMPC+1 provides the best anti-icing performance, displaying the greatest resistance to ice formation and thereby promoting the retention of water in the liquid state. Overall, these molecular-level insights underscore the critical role of carbon spacer architecture in dictating polymer–water/ice interactions, offering valuable guidance for designing zwitterionic polymeric materials via side-chain engineering.

A primary objective in supramolecular chemistry is the development of molecular host systems capable of specific ion-pair recognition. The current emphasis of this research is the strategic molecular design of receptors to achieve superior binding affinities and enhanced selectivity for a specific ion-pair. The concept of ion-pair recognition has evolved from the basic understanding of cation and anion recognition chemistry and has gradually developed into a dynamic sub-discipline of supramolecular chemistry. Among the various classes of synthetic receptor systems, tripodal receptors are particularly noteworthy for ion-pair recognition due to their inherent symmetry and the ease with which their structures can be tuned for host–guest interactions through the strategic incorporation of cation and anion binding groups. This review focuses on ion-pair receptors built upon tripodal scaffolds, examining their binding behaviour primarily towards inorganic salts and the intricate structure–function relationships that govern their cooperative cation and anion binding performances. Specifically, we provide a comprehensive analysis of the solid-state structures of ion-pair complexes and the solution-phase binding affinities of a diverse range of C₃-symmetrical and asymmetrical tripodal receptors, offering insights into their capabilities for selective ion-pair binding and their potential applications in inorganic salt extraction from competitive aqueous media.

This comprehensive study investigates the interplay between hydrogen atoms and structural defects, including vacancies and self-interstitial atom defects (SIAs), and their combined impact on hydrogen diffusion and mechanical properties in nickel through molecular dynamics simulations. The results indicate that the diffusion coefficient of hydrogen in nickel in the temperature range of 400 K to 1000 K follows the Arrhenius law, yielding an activation energy of 0.424 eV and a diffusion coefficient pre-exponential factor of 8.185 × 10⁻⁸ m² s⁻¹, aligning well with experimental values. The findings also highlight the intricate link between hydrogen diffusion in nickel, defect concentrations, and temperature. Therefore, selecting an appropriate temperature range for studying the system is crucial to minimize quantum effects on hydrogen diffusion and obtain more accurate diffusion coefficient estimates. Our outcomes indicate that despite promoting hydrogen diffusion by SIAs, the existence of vacancies in the system impedes the migration of hydrogen atoms in nickel, thereby reducing diffusivity. The impact of varying concentrations of vacancies, SIAs, and hydrogen in Ni–H–defect systems was examined. It can be inferred that the diffusion coefficient of hydrogen in nickel is strongly influenced not only by the temperature range studied, but also by the type and concentration of structural defects, the concentration of hydrogen atoms, and even the ratio of the hydrogen concentration to the defect concentration (H/defect) in the system. The study also explored how nickel behaves mechanically when exposed to both hydrogen atoms and vacancies or SIAs, revealing a significant influence on its mechanical properties.

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Electrolyte development for next-generation batteries has largely relied on knowledge-driven trial-and-error. A significant reason for this approach is due to the vast, high-dimensional molecular design space for solvents and molecular mixtures. Popular dimensionality reduction techniques such as principal component analysis (PCA), t-distributed stochastic neighbor embeddings (t-SNE), and uniform manifold approximation and projection (UMAP) can facilitate chemical exploration by projecting this space into low dimensions, yet their applicability in electrolyte discovery remains underexplored. Here, we present a framework to assess the faithfulness of various dimensionality reduction methods in preserving chemically meaningful relationships. Then, we apply this framework to guide electrolyte solvent discovery by searching for electrolyte solvents with high and low cosine similarities to state-of-the-art systems, followed by formulation refinement using domain knowledge. We then performed experimental validation which revealed different failure modes for different electrolyte selections. We specifically focus on next generation lithium metal batteries (LMBs), and identified a non-fluorinated ether electrolyte solvent that exhibited high coulombic efficiency (CE). Our findings demonstrate that rational navigation of the electrolyte chemical space, enabled by dimensionality reduction and guided by data, can complement traditional approaches and accelerate the discovery of advanced battery materials.

Although polymer brushes reduce friction by suppressing solid contact, performance degradation can occur under high shear and load. To address this, polymer-grafted nanoparticles (PGNPs) have been proposed as nanoscale spacers between wall brushes to stabilize the lubricating film and modulate the frictional response. In this study, dissipative particle dynamics were used to study PGNP solutions confined between polymer-brushed walls and relate self-assembly to the friction coefficient, μ, and shear viscosity, η. AB and BA diblock PGNPs (A: hydrophilic and B: hydrophobic) are compared with Janus architectures while varying the wall brush affinity from hydrophilic to hydrophobic. For hydrophilic wall brushes, AB-type PGNPs dimerized at equilibrium, whereas BA- and Janus-type PGNPs remained dispersed. Under shear, the viscosity exhibited shear-thinning, and architectural differences were minimal due to the dominance of wall brush alignment. Consequently, the tribological properties were similar across all PGNPs. For hydrophobic wall brushes, the PGNP architecture more strongly influenced self-assembly. At rest, AB-type PGNPs formed network-like aggregates, while BA-type and Janus PGNPs remained dispersed. Janus-type PGNPs preserved a solvent-rich core, yielding the lowest μ and η. At intermediate shear, BA-type PGNPs became less viscous than the Janus-type due to their low abundance in the channel center, reopening a low-resistance core pathway. The Janus-type PGNPs appeared in the channel center, which narrowed the solvent-rich core. At high shear, both architectures reconcentrated toward the center, and the differences in μ and η diminished. This work reveals how nanoscale self-assembly governs macroscopic tribological responses, offering design principles for next-generation PGNP-based lubricants.

The occurrence state of shale oil in a nanoscale confined matrix of a shale reservoir significantly impacts reserve evaluation and exploitation. As an endogenous gas, associated gas markedly affects the distribution of adsorbed shale oil and the mobility of free phase oil, yet a clear quantitative analysis of its effect has not been carried out, and the underlying control mechanism remains unclear. In this work, employing a molecular dynamics simulation method, the occurrence characteristics of multiple-component shale oil with different ratios of associated gas were investigated. Simulation results demonstrate that shale oil can be classified into free and adsorbed states in shale nanoslits based on its adsorption density profile. Upon increasing the associated gas ratio, the proportion of adsorbed oil decreases remarkably, which is an effect originating from the competitive adsorption between associated gas and oil, and the different oil components exhibit distinct response performances. As for the free states of the shale oil, the dissolved associated gas decreases their viscosity, leading to higher mobility. In addition, the impact of the mineral type on the occurrence characteristics of shale oil was investigated. The proportions of the adsorption states for the three typical minerals follow the order quartz ≈ kaolinite > calcite, while their sensitivities to associated gas follow the order quartz > calcite > kaolinite. The interactions between shale oil, associated gas, and mineral surfaces were analyzed to reveal the underlying mechanisms behind these response patterns. Insights gained from this study may contribute to a better theoretical understanding of the micro-scale behaviors of associated gas in influencing shale oil occurrence in reservoir nanopores, providing foundational data and theoretical guidance for shale oil reserve evaluation and development.

The global spread of New Delhi metallo-β-lactamase-1 (NDM-1) poses a significant challenge for β-lactam antibiotics, driving the search for effective molecular inhibitors. In this study, we used a suite of computational techniques—including long-timescale molecular dynamics, principal component analysis, free-energy landscape mapping, binding free-energy calculations (MM/GBSA and SIE), and interaction fingerprint profiling—to investigate how heteroaryl phosphonate scaffolds affect NDM-1's structure and dynamics. Analysis of nine inhibitors revealed that noncovalent phosphonate binding alters the dynamics of the L3 and L10 loops at the Zn(II) active site. Higher-affinity compounds within the series, such as C06 and C09, preferentially stabilize more localized conformational states of NDM-1. In contrast, lower-affinity analogs permit greater loop flexibility and access to multiple metastable conformation. Free-energy decomposition showed that van der Waals interactions, rather than electrostatics, are the main drivers of inhibitor binding. Interaction fingerprint analysis identified key hotspot residues—His122, Phe70, Met67, and Asn220—that are consistently involved in ligand binding. These findings establish clear design principles linking scaffold features to conformational control, providing a framework for developing next-generation noncovalent NDM-1 inhibitors.

To better study the mechanism of hierarchical porous polymers towards target substrates at a molecular level, we fabricated glucose/fructose-based crosslinked porous polymers with boric acid as the covalent bridge to in situ generate flexible macrocyclic skeletons including BA–G and BA–F. The thus obtained BA–G/BA–F polymers were fully characterized by SEM, FT-IR, XRD, TGA, DTG, BET, zeta potential and XPS, indicating the formation of porous structures with a good specific surface area. We also demonstrate the successful application of those polymers to efficient adsorption of diverse cationic dyes. The adsorption properties of BA–G/BA–F polymeric materials were studied by analyzing the adsorption effect towards a single category of dyes. Interestingly, as revealed by the adsorption kinetic studies and adsorption isotherm, chemical adsorption played a dominant role in molecular recognition of BA–G/BA–F towards cationic dyes, exhibiting a maximum adsorption capacity of 756.91 mg g⁻¹ (q_max of BA–G) towards MG. Thermal kinetic studies also show related trends in parameters, indicating in situ generated porous structures spontaneously adsorbing dyes driven by electrostatic and hydrogen bonding interactions. Furthermore, the mimicking behavior of macrocyclic skeletons by in situ fabrication was then proved by the analysis of elemental composition via EDS, molecular weight of materials via MALDI test, as well as proposed in situ generated macrocyclic structures towards target substrates via DFT calculations.

Low molecular-weight organogels are particularly attractive soft materials for drug delivery, tissue engineering, environmental remediation and the food industry. In this study, we describe a molecular approach to develop nucleolipid (NL) as a novel low molecular weight oleogelator (LMWO). NL 5 demonstrated self-assembling properties, forming a three-dimensional solid-like network that traps a substantial amount of the carrier oil solvent and enables the creation of an oleogel. As a bio-inspired, low molecular-weight oleogelator, NL 5 was able to stabilize thixotropic medium chain triglyceride (MCT)-based oleogels at low concentrations (1.5% w/w). Furthermore, this NL also induced the gelation of an oil-in-water nanoemulsion, resulting in a novel oleogel-based nanoemulsion through supramolecular interactions. Unlike common strategies that rely on trapping the dispersed phase by gelation of the continuous phase, we report an innovative oil-in-water nanoemulsion obtained via gelation of dispersed oil droplets. These oil droplets form an oleogel through LMWO based on NL, which is used at a remarkably low final concentration (1% w/w). The bio-inspired and biocompatible nature of this oleogelator, along with its efficiency at low concentrations and its ability to gel a nanoemulsion, makes it particularly appealing for further cosmetic and pharmaceutical developments.