Search Results (42)

The dangerous potential of chemical warfare requires immediate development of new materials capable of detecting and efficiently adsorbing the toxic nerve agents VX and Novichok (A-234). The current adsorbents fail to achieve sufficient detection efficiency and specific binding capabilities. Our research, conducted through advanced computational modeling, predicts that carbon nanocones (CNCs) could function as effective molecular traps for these toxic substances. The research combines density functional theory (DFT) with molecular dynamics (MD) and Monte Carlo (MC) simulations to explain the basic principles of molecular trapping by these agents. The nanocone shape produces two distinct and selective binding areas. MC shows preferential trapping VX molecules within the internal concave surface (P1), while A-234 molecules are strongly adsorbed on the external convex surface (P2). Docking results complement this by showing that A-234 exhibits stronger single-molecule binding on the more open surface, consistent with its preference for P2. The nanocone captures molecules through van der Waals forces, which produce measurable electronic changes that modify its electronic signature. The research demonstrates that carbon nanocones represent a promising candidate material for the future development of chemical defense systems, potentially including sensitive detection systems and advanced filtration technologies. Full article

Materials capable of withstanding extreme environments open promising opportunities for nuclear fusion reactors. In this study, equiatomic CrFeTaVW and CrFeTiVW high-entropy alloys are investigated as interlayer materials between W and CuCrZr. Monte Carlo and Molecular Dynamics simulations predicted a bcc-type structure for both systems. Additionally, the Monte Carlo simulation predicts lower potential energy and a more stable structure for both systems than Molecular Dynamics. For CrFeTaVW, the chemical segregation values are lower in MC than in the MD simulation, whereas for CrFeTiVW, the opposite trend is observed, with MC indicating stronger segregation values. After simulation, the high-entropy alloys were prepared by planetary ball milling, consolidated by spark plasma sintering, and analyzed using X-ray diffraction, scanning electron microscopy, and thermal diffusivity. The experimental results for the milled powders confirmed the formation of a bcc structure in both alloys. The consolidated material revealed a bcc-type structure and an Fe₂Ta Laves phase for the CrFeTaVW HEA, while the CrFeTiVW HEA exhibits two different bcc-type structures. The values of CrFeTaVW and CrFeTiVW thermal diffusivity are between 3.5 and 7 mm²/s, which is consistent with the expected values for high-entropy alloys. Overall, the findings indicate that these HEAs have promising properties that can be used in extreme environments. Full article

Background: Melanin protects skin and hair from the effects of ultraviolet (UV) radiation damage, which contributes to all forms of skin cancer, including melanoma. Human melanocytes produce two main types of melanin: eumelanin provides effective photoprotection, and pheomelanin offers less protection against UV-induced skin damage. The agouti signaling protein (ASIP) antagonizes the melanocortin-1 receptor (MC1R), hinders melanocyte signaling, and shifts pigmentation toward pheomelanin, promoting UV vulnerability. In this study, we aim to discover compounds that inhibit ASIP–MC1R interaction and effectively preserve eumelanogenic signaling. Methods: The ASIP–MC1R interface-based pharmacophore model from ASIP is implicated in MC1R receptor protein engagement. We performed virtual screening with a validated pharmacophore model for ~4000 compounds curated from ZINCPharmer and applied drug-likeness filters, viz. ADMET and toxicity profiling tests. Further, the screened candidates were targeted for docking to the ASIP C-terminal domain corresponding to the MC1R-binding moiety. Top compounds underwent a 100-nanosecond (ns) run of molecular dynamics (MD) simulations to assess complex stability and persistence of key contacted residues. Results: Sequential triage, including pharmacophore, ADME–toxicity (ADMET), and docking/ΔG, yielded a focused group of candidates against ASIP antagonists with a favorable fit value. The MD run for 100 ns supported pose stability at the targeted pocket. Based on these predictions and analyses, compound ZINC14539068 was screened as a new potent inhibitor of ASIP to preserve α-MSH-mediated signaling of MC1R. Conclusions: Our in silico pipeline identifies ZINC14539068 as a potent inhibitor of ASIP at its C-terminal interface. This compound is predicted to disrupt ASIP–MC1R binding, thereby maintaining eumelanin-biased signaling. These findings motivate experimental validation in melanocytic models and in vivo studies to confirm pathway modulation and anti-melanoma potential. Full article

This review highlights the growing relevance of ion-exchange nanofibrous membranes (IEX-NFMs) in membrane chromatography (MC) for protein purification, emphasising their structural advantages such as high porosity, tunable surface functionality, and low-pressure drops. While the adsorption of IEX-NFMs in MC is expanding due to their potential for high throughput and rapid mass transfer, a critical limitation remains: the precise binding capacity of these membranes is not well understood. Traditional experimental methods to evaluate protein–membrane interactions and optimise binding capacities are labour-intensive, time-consuming, and costly. Therefore, this review underscores the importance of computational modelling as a viable predictive approach to guide membrane design and performance prediction. Yet major obstacles persist, including the challenge of accurate representation of the complex and often irregular pore structures, as well as limited and/or oversimplified adsorption models. Along with molecular-scale simulations such as molecular dynamics (MD) simulations and quantum simulations, meso-scale simulations can provide insight into protein–fibre and protein–protein interactions under varying physicochemical conditions for larger time scales and lower computational burden. These tools can help identify key parameters such as binding accessibility, ionic strength effects, and surface charge density, which are essential for the rational design and performance prediction of IEX-NFMs. Moreover, integrating simulations with experimental validation can accelerate optimisation process while reducing cost. This technical review sets the foundation for a computationally driven design framework for multifunctional IEX-NFMs, supporting their use in next-generation chromatographic separations and broadening their applications in bioprocessing and analytical biotechnology. Full article

Lipid nanoparticles (LNPs) have received significant attention as effective RNA carriers in RNA-based therapeutics and vaccines. Particularly, ionizable lipids (ILs) of LNPs play a crucial role in endosomal escape and lipid-mediated RNA delivery owing to their pH-dependent molecular characteristics. Therefore, it is essential to enhance the endosomal escape efficiency of ILs, which is primary bottleneck in the successful cytoplasmic delivery of RNA. However, the molecular-level understanding of the roles and dynamics of ILs during the endosomal escape stage remains unclear. To elucidate this, we utilized coarse-grained (CG) molecular dynamics (MD) simulations. In this simulation, we designed lipid nanodroplets (LNDs) containing D-Lin-MC3-DMA (MC3) and ALC-0315, which have proven effective as LNPs in RNA-based therapeutics and vaccines, respectively, while accounting for the pH environments of early and late endosomes. Also, we formulated lipid bilayers reflecting the composition of early and late endosomal membranes to investigate the fusion process between LNDs and endosomal membranes. Our findings reveal that, irrespective of endosomal membrane composition and LNP types, ILs are the first lipids to enter the endosomal membrane during the fusion, and the flip-flop process of ILs from the inner leaflet to the outer leaflet of the endosomal membrane is a critical step for LNP endosomal escape. More specifically, we observed that protonated ILs predominantly participate in the flip-flop process, while many deprotonated ILs remain clustered and disordered within the intermediate layer of the endosomal membrane. Furthermore, we found that the extent of IL flip-flop varies with the cholesterol content of the endosomal membrane. Additionally, under identical pH conditions, MC3-containing LNDs exhibited a more active IL flip-flop process toward the outer leaflet than ALC-0315-containing LNDs. This observation supports experimental findings that MC3-containing LNPs manifest higher endosomal escape efficiency than ALC-0315-containing LNPs in mRNA delivery studies. The mechanistic insights into the endosomal escape mechanism demonstrated by our simulations could aid in the development of effective ILs. Full article

This work investigates the influence of chemical composition, grain boundary (GB) type, and atomic distribution on the thermal conductivity of Hf–Nb–Ta–Zr refractory high-entropy alloys (RHEAs) via atomistic simulations. Three compositions—equiatomic HfNbTaZr (M1), Hf₁₀Nb₄₀Ta₁₀Zr₄₀ (M2), and Hf₄₀Nb₁₀Ta₄₀Zr₁₀ (M3)—were studied in single-crystalline and bicrystalline models containing Σ3 or Σ5 GBs. The effect of chemical short-range order (SRO) and GB segregation was probed by comparing results for non-relaxed structures with those obtained for corresponding materials relaxed using combined Monte Carlo/molecular dynamics (MC/MD) simulation. Material relaxation is accompanied by the formation of coherent nanoclusters (NbTa in M1, Nb or Zr in M2, Hf or Ta in M3) and Hf/Zr segregation to GBs. In single crystals, SRO reduces thermal conductivity by up to ~2.7% (e.g., from 3.66 to 3.56 W/m·K in M1), which is explained by the phonon scattering effect from matrix–cluster interfaces, densely distributed in the structures. In contrast, in certain bicrystals, the combined effects of GB healing and intragranular cluster coarsening lead to a 6.9% increase in thermal conductivity (from 4.59 to 4.93 W/m·K), despite the presence of high-energy Σ5 GBs. These results demonstrate that the interplay between SRO, GB segregation, and microstructural evolution governs phonon transport in RHEAs, revealing a counterintuitive pathway to enhance thermal conductivity through controlled atomic redistribution. Full article

Geosynchronous satellite maneuver detection is critical for enhancing space situational awareness and inferring satellite intent. However, traditional methods often require high-quality orbital sequence data and heavily rely on hand-crafted features, limiting their effectiveness in complex real-world environments. While recent neural network-based approaches have shown promise, they are typically trained in scene or task-specific settings, resulting in limited generalization and adaptability. To address these challenges, we propose MC-MD, a pre-training framework that integrates Masked and Clustered learning strategies to improve the robustness and transferability of geosynchronous satellite Maneuver Detection. Specifically, we introduce a masked prediction module that applies both time- and frequency-domain masking to help the model capture temporal dynamics more effectively. Meanwhile, a cluster-based module guides the model to learn discriminative representations of different maneuver patterns through unsupervised clustering, mitigating the negative impact of distribution shifts across scenarios. By combining these two strategies, MC-MD captures diverse maneuver behaviors and enhances cross-scenario detection performance. Extensive experiments on both simulated and real-world datasets demonstrate that MCMD achieves significant performance gains over the strongest baseline, with improvements of 8.54% in Precision and 7.8% in F1-Score. Furthermore, reconstructed trajectories analysis shows that MC-MD more accurately aligns with the ground-truth maneuver sequence, highlighting its effectiveness in satellite maneuver detection tasks. Full article

The intelligently thermosensitive 2-methacryloyloxyethyl phosphorylcholine (MPC) groups-conjugated methylcellulose (MC) hydrogel, abbreviated as MPC-g-MC, exhibits good potential for prevention of postoperative adhesions. However, its thermosensitive gelation mechanism and why the MPC-g-MC hydrogel shows a lower gelation temperature than that of MC hydrogel are still unclear. Molecular dynamics (MD) simulation was thus used to investigate these mechanisms in this work. After a fully atomistic MPC-g-MC molecular model was constructed, MD simulations during the thermal simulation process and at constant temperatures were performed using GROMACS 2022.3 software. The results indicated that the hydrophobic interactions between the MPC-g-MC molecular chains increased, the interactions between the MPC-g-MC molecular chains and H₂O molecules decreased with the rise in temperature, and the hydrogen bonding structures were changed during the thermal simulation process. As a result, the MPC-g-MC molecular chains began to aggregate at about 33 °C (close to the gelation temperature of 33 °C determined by the rheological measurement), bringing about the formation of the MPC-g-MC hydrogel in the macroscopic state. The mechanism of MPC-g-MC hydrogel formation showed that its lower gelation temperature than that of the MC hydrogel is attributed to the increase in the interactions (including hydrophobic interactions, hydrogen bonding interactions, Van der Waals and Coulomb forces) induced by the side MPC groups of MPC-g-MC molecules. The thermosensitive gelation mechanism revealed in this study provides an important reference for the development of novel thermosensitive MC-derived hydrogels with gelation temperatures close to human body temperature. Full article

Chemiresistive gas sensors have gained significant attention and have been widely applied in various fields. However, the gap between experimental observations and fundamental sensing mechanisms hinders systematic optimization. Despite the critical role of modeling in explaining atomic-scale interactions and offering predictive insights beyond experiments, existing reviews on chemiresistive gas sensors remain predominantly experimental-centric, with a limited systematic exploration of the modeling approaches. Herein, we present a comprehensive overview of the modeling approaches for chemiresistive gas sensors, focusing on two critical processes: the reception and transduction stages. For the reception process, density functional theory (DFT), molecular dynamics (MD), ab initio molecular dynamics (AIMD), and Monte Carlo (MC) methods were analyzed. DFT quantifies atomic-scale charge transfer, and orbital hybridization, MD/AIMD captures dynamic adsorption kinetics, and MC simulates equilibrium/non-equilibrium behaviors based on statistical mechanics principles. For the transduction process, band-bending-based theoretical models and power-law models elucidate the resistance modulation mechanisms, although their generalizability remains limited. Notably, the finite element method (FEM) has emerged as a powerful tool for full-process modeling by integrating gas diffusion, adsorption, and electronic responses into a unified framework. Future directions highlight the use of multiscale models to bridge microscopic interactions with macroscopic behaviors and the integration of machine learning, accelerating the iterative design of next-generation sensors with superior performance. Full article

To tackle the degradation of sealing performance in nitrile butadiene rubber (NBR) seals due to material aging during long-term service, this study integrates experimental and molecular simulation methods to elucidate the aging mechanism. Experimental results reveal that the contents of C=C and C=O functional groups significantly decrease during aging, accompanied by enhanced hydrophobicity and increased crosslink density of NBR, indicating that crosslinking reactions dominate the aging process with the participation of C=C and C=O groups. Quantum mechanics (QM) and molecular dynamics (MD) simulations further demonstrate that α-H, C=C, and C≡N groups are preferentially oxidized due to their low bond energies. The oxidation of NBR generates unstable epoxy intermediates, which undergo chain scission to form ketones, aldehydes, and ultimately crosslinked structures. Using a multi-dimensional evaluation system based on bond dissociation energy (BDE), solubility parameter (Δδ), and migration coefficient (MSD), four antioxidants (4010NA, 4010, MC, and BHT) were screened. BHT emerges as the optimal choice, exhibiting superior free radical scavenging ability (BDE = 346.3 kJ/mol), good matrix compatibility (Δδ = 2.95), and anti-migration properties. The MD-based screening method established herein provides a theoretical basis for designing antioxidant systems in high-performance rubber materials, facilitating the development of advanced rubber products. Full article

Epoxy resins are critical materials in aerospace applications, yet their mechanical properties, specifically the tensile modulus, can be significantly compromised when exposed to electron irradiation in space environments. To thoroughly examine this degradation, we developed an integrated research approach combining vacuum electron irradiation experiments with multi-scale simulations. Coarse-grained (CG) and Monte Carlo (MC) methods were employed to generate the necessary models and primary knock-on atom (PKA) data, while molecular dynamics (MD) simulations were conducted to model the irradiation and tensile processes. Our findings reveal that the tensile modulus percentage loss of epoxy resin stabilizes as the irradiation dose approaches 1.0×10¹⁵ eV/cm². The strong agreement between experimental and simulation results validates the accuracy of this methodology. In the epoxy resin systems studied with different degrees of cross-linking, irradiation leads to an increase in the tensile modulus of the low cross-linked structures with a maximum increase of 21.46%, and it leads to a decrease in the tensile modulus of the high cross-linked structures with a maximum decrease of 8.03%. This multi-scale approach has been successfully applied to investigate the trends and causes of tensile modulus changes in epoxy resins after electron irradiation. It can be used to explore the changes in the properties of a wider range of polymers after irradiation. Full article

In the study, the combined molecular dynamics and Monte Carlo (MD/MC) simulation was used to investigate the short-range ordering effect on tensile deformation of bicrystals with grain boundaries (GBs) Σ3(1$\overline{1}$2)[110]. Three different equiatomic high-entropy alloys, namely, ZrTiNbV, ZrTiNbTa and ZrTiNbHf, were considered. The tensile loading at 300K was applied in the direction perpendicular to the GBs’ planes. The stress–strain response as well as the structure evolution of the alloys with initial random distribution of atoms were compared with results obtained for the corresponding materials relaxed during the MD/MC procedure. It was revealed that the distribution of atoms in the alloys significantly affects the deformation process. Ordered clusters of Nb atoms are able to suppress the dislocation sliding and twin formation increasing the yield strength of ZrTiNbV. On the contrary, in ZrTiNbTa, the twinning mechanism is dominant in the case of the ordered structure due to the absence of Nb clusters and the presence of areas enriched with Zr atoms, which ease nucleation of dislocations and twins. Since Hf decreases the stability of the body-centered cubic lattice, the main deformation mechanism of ZrTiNbHf is the stress-induced phase transition; however, Nb clusters inside grains of the relaxed alloy slightly delay this process. Full article

This study investigates the effects of natural inhibitors (pomegranate, algae, and tomato extracts) on the corrosion resistance of titanium (grade 2). To deepen understanding the inhibition mechanism, Molecular Dynamic (MD) and Monte Carlo (MC) simulations were employed to analyze adsorption behaviors and identify optimal adsorption sites on titanium oxide (TiO₂) surfaces for compounds within the inhibitors. Results indicate non-flat adsorption orientations, with pomegranate peel extract components showing superior inhibition capabilities, attributed to the formation of strong O-H chemical bonds with the TiO₂ surface. In the experimental part of the study Electrochemical Impedance Spectroscopy (EIS) and Potentiodynamic Polarization (PDP) were conducted. Two electrolytes were tested: a solution 3.5% NaCl and a solution 0.5 M NaOH. All the tests were performed with 5% of inhibitor and with the reference solution. Also, inhibition efficiency was calculated on the base of PDP tests. The study found that pomegranate extract can act as a good corrosion inhibitor for titanium alloy in aqueous solutions 0.5 M NaOH. This was demonstrated by the increase in the corrosion potential and impedance modulus and decrease in the corrosion current density after the addition of pomegranate extract to the solution. However, in a 3.5% NaCl solution, the efficacy of pomegranate extract was less pronounced, probably due to the high aggressivity of the electrolyte. Tomato and algae extract have instead shown very low inhibition effects in all the tested conditions. Full article

Using Molecular Dynamics (MD) and Monte Carlo (MC) simulations, we studied the grain boundary (GB) segregation under different temperatures and Cr concentrations in Ni-Cr alloys with two distinct grain-boundary structures, i.e., Σ5(310)[010] and Σ101(200)[100]. Temperature plays a minor influence on Cr segregation for Σ5(310)[010] GB, but Cr segregation rapidly diminishes with elevating temperatures for Σ101(200)[100] GB. We also used the synthetic driving force and corresponding identification methods to investigate the effect of Cr solute segregation on grain boundary stability. All Σ5(310)[010] models have multi-stage grain boundary migration at 800 K. In the first stage, the grain boundary’s slow acceleration time is related to solute concentration. The migration temperature can influence this phenomenon. As temperatures rise, the duration of this slow acceleration phase diminishes. No similar phenomenon was observed in the process of the grain boundary movement of Σ101(200)[100]. The influence of solute concentration on grain boundary migration is complicated. The segregation concentration at the grain boundary cannot be regarded as the only factor affecting the migration of the grain boundary because the Cr atom on the grain boundary does not move with the grain boundary. This work will also discuss the grain boundary migration‘s relationship with lattice distortion and grain boundary atom diffusion. The results and findings of this study provide further insights into the segregation-increase GB stabilization of NC Ni-Cr alloys. Full article

We present a novel approach to characterize and quantify microheterogeneity and microphase separation in computer simulations of complex liquid mixtures. Our post-processing method is based on local density fluctuations of the different constituents in sampling spheres of varying size. It can be easily applied to both molecular dynamics (MD) and Monte Carlo (MC) simulations, including periodic boundary conditions. Multidimensional correlation of the density distributions yields a clear picture of the domain formation due to the subtle balance of different interactions. We apply our approach to the example of force field molecular dynamics simulations of imidazolium-based ionic liquids with different side chain lengths at different temperatures, namely 1-ethyl-3-methylimidazolium chloride, 1-hexyl-3-methylimidazolium chloride, and 1-decyl-3-methylimidazolium chloride, which are known to form distinct liquid domains. We put the results into the context of existing microheterogeneity analyses and demonstrate the advantages and sensitivity of our novel method. Furthermore, we show how to estimate the configuration entropy from our analysis, and we investigate voids in the system. The analysis has been implemented into our program package TRAVIS and is thus available as free software. Full article