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In order to reveal the migration and evolution of gas molecules in the actual oil–paper insulation composite system of transformer from the molecular level, the diffusion behavior of seven gas molecules (H2, CO, CO2, CH4, C2H2, C2H4, C2H6) generated during the operation and aging of oil-immersed transformers in the oil–paper composite insulation system is studied by molecular dynamics. Firstly, based on the molecular dynamics software, the model of the oil–paper composite insulation system and the gas molecule model is constructed. In order to compare and analyze the diffusion properties of gas molecules in a single medium, a single model of insulating oil and cellulose is also constructed. Then, the diffusion coefficients of gas molecules in the insulating oil, cellulose, and oil–paper insulating composite system are simulated and calculated. And the differences in the diffusion properties of gas molecules in the three insulating mediums are discussed. Finally, the microscopic mechanism of diffusion of different gas molecules in the three mediums is analyzed. The simulation results show that among the three mediums, the diffusion coefficient of H2 is the largest, while the diffusion coefficients of the other gas molecules are not very different. The diffusion coefficients of the seven gas molecules are the smallest in the oil-immersed paper composite insulation system, followed by cellulose, while the diffusion coefficients are the largest in mineral oil. It indicates that the diffusion of gas molecules is inhibited in oil–paper insulation systems where the insulating paper is completely immersed in oil. This is mainly due to the fact that the insulating oil completely penetrates into the paper, filling the pores and voids between the fibers, resulting in a reduction in the transition vacancies of the intermediate gas molecules, which hinders the diffusion of the gas molecules. [ABSTRACT FROM AUTHOR]

The complex and demanding environments of high humidity, heat, altitude, and intricate electric fields necessitate higher standards for the mechanical, thermal stability, and electric insulation properties of insulating paper. However, a single nanomaterial alone struggles to enhance overall performance. Hence, we propose employing two-phase nanomaterials with distinct dimensions to synergistically enhance the performance of cellulose insulation paper. Accordingly, "simulation design directly guided experimental research" was utilized in constructing nano-BN/nanocellulose/cellulose (nano-BN/NFC/cellulose) models through molecular dynamics simulation, and its mechanical parameters, dielectric properties, thermal stability, and so on were simulated and calculated. Based on simulation results, suitable proportions of nano-BN/NFC/cellulose insulating paper were prepared. Nano-BN and NFC synergistically enhance the mechanical properties of insulating paper. The nano-BN, CNF, and cellulose are arranged layer by layer under the action of gravity, allowing the fillers to overlap diagonally along the plane, synergistically forming a thermally conductive network conducive to heat transfer. Additionally, a strong interfacial effect is formed between the three-phase materials, reducing the overall structure's polarization effect and charge accumulation, and synergistically enhancing electrical insulation performance. The 12%nano-BN/NFC/cellulose (P12) exhibits optimal overall performance and is expected to be used in power equipment operating in special environments with high humidity and heat. [Display omitted] • The results of MD simulations successfully guided the preparation of nano-BN/NFC/cellulose insulating paper. • Nano-BN and NFC synergistically enhance the mechanical, thermal, and electrical properties of cellulose insulating papers. • The P12 insulating paper possesses a high thermal conductivity of 0.286 W/(m·K) and a T g of 140.2 °C. • The P12 with high tensile stress (68.93 MPa), volume resistivity (4.79 × 1015 Ω m), and breakdown strength (67.48 kV mm−1). [ABSTRACT FROM AUTHOR]

Epoxy-impregnated aramid composites, notable for their excellent mechanical and insulation qualities, are pivotal in electrical engineering and electronics. However, their performance is severely restrained by interface issues. This research proposes an effective modification strategy for improving interface property by employing non-thermal atmospheric plasma to introduce active functional groups onto aramid paper. The modified composites demonstrated a 26 % increase in tensile strength and a 20 % enhancement in breakdown strength at best, alongside inhibited charge transport properties and reduced partial discharge under operational electric fields. Molecular simulation suggests that plasma treatment bolsters interface hydrogen bonding, restricting the chain mobility of the resin molecular, and thus augmenting inter-phase compatibility. This study offers a factual perspective on improving resin-impregnated composites, laying a theoretical foundation for advancing high-performance materials in power industries. [Display omitted] [ABSTRACT FROM AUTHOR]

This work constructed chiral nanozymes (Cys@Au/Fe Hops) with high enantioselectivity activity by cysteine-induced synthesis. The nanozymes, proficient in detecting DOPA enantiomers, have been transformed into a test paper sensor, offering enantioselective catalysis and enabling visual chiral detection via a smartphone platform. [Display omitted] • The Chiral Cys@Au/Fe Hops was synthesized using a one-pot method with cysteine as a chiral inducer. • Remarkable enantioselective catalytic activity for DOPA enantiomers by L/D -Cys@Au/Fe Hops. • Steric effects on DOPA enantiomers catalyzed by L/D -Cys@Au/Fe Hops revealed through molecular dynamics simulations. • Development of chiral nanozymes into stable test paper sensor for visual DOPA detection. The development of enantioselective nanozymes holds profound significance in synthesizing chiral compounds and elevating analytical precision. Herein, we have synthesized chiral gold/iron hierarchically organized particles (Cys@Au/Fe Hops) possessing peroxidase-like catalytic activity, through a one-pot method using cysteine as a chiral inducer. The nanozymes exhibited remarkable enantioselective catalytic activity to 3,4-dihydroxy-phenylalanine (DOPA) enantiomer. Notably, L -Cys@Au/Fe Hops, comprising right-handed helical nanopetals, exhibited elevated catalytic efficiency for L -DOPA over D -DOPA, whereas the reverse held for D -Cys@Au/Fe Hops. The molecular dynamics simulations demonstrated hydrogen bonding interactions between the active site and substrate, thereby revealing how steric effects affected the enantioselective catalysis of chiral DOPA by L/D -Cys@Au/Fe Hops. Moreover, the chiral nanozymes were developed into a test paper sensor due to their exceptional stability, which can achieve the visual detection of DOPA enantiomer combined with a smartphone platform. This work is significant in advancing the design and practical utility of highly selective enzyme mimics. [ABSTRACT FROM AUTHOR]

We report a novel OLED material discovery process and several applications based on AI technology. This process in which six AI modules that generate molecular structures with active learning algorithm, predict multiple properties, analyze novelty, predict synthetic scheme, predict relative synthesizability and predict device characteristics are linked one after another. Also, we introduce some cases in which materials designed by this process were actually synthesized and applied to devices for evaluation to confirm the improvement of characteristics. [ABSTRACT FROM AUTHOR]

Xylanases are used in several industrial applications, such as feed additives, the bleaching of pulp and paper, and the production of bread, food, and drinks. Xylanases are required to remain active after heat treatment at 80–90 °C for 30 s to several minutes due to the conditions of feed pelleting. Also, xylanases need to be active at 60–70 °C for several hours while bleaching of pulp and paper or manufacturing of bread, food, and drinks is performed. Xylanases of the glycoside hydrolase family GH10 are good candidates for application in such processes because of their high thermostability and, in particular, as feed additives because of their insensitivity to protein inhibitors in cereal feeds. In the study, the thermostability of GH10 xylanase E from Penicillium canescens was improved to reach a half-inactivation period of 2 min at 80 °C compared to 21 s for the wild-type enzyme (WT). Enzymatic activity was increased by 22–48 % at 40–70 °C, which improved the action of the enzyme as a feed additive in the gastric system of animals and during bleaching of pulp and paper. Molecular dynamics simulations demonstrated lower flexibility of the tertiary structure of the engineered enzyme at elevated temperatures compared to WT. The residues W113, Q116, W313, and W321 in the (−1) and (−2) subsites for the substrate binding were less flexible. In the simulations, the engineered enzyme had a comparable content of α-helixes, 3 10 -helixes, β-sheets, and β-bridges as WT, but a lower content of coils and a higher content of β-turns. [Display omitted] • Thermostability was improved by six times to reach t 1/2 of 2 min at 80 °C. • Enzymatic activity was increased by 22–48 % at 40–70 °C. • Stability of active center cleft and surface loops and α-helixes was increased. [ABSTRACT FROM AUTHOR]

The February 2024 issue of the Journal of Materials Science features a cover paper titled "Enhancing the impact property of high-entropy alloys with graphene layers: a molecular dynamics study" by Qing-Xiang Pei et al. The paper explores the use of molecular dynamics simulations to study the impact of a projectile on a high-entropy alloy (HEA) containing layers of graphene. The authors highlight the broad interest in their research, as it appeals not only to the modeling community but also to other communities interested in the materials being modeled. The paper provides valuable insights into the behavior of composite materials and includes figures illustrating the preparation of the model material and the interaction between a projectile and the HEA. The article is freely accessible through the SharedIt link provided, and the corresponding authors can be contacted for access to the data. The publisher, Springer Nature, maintains a neutral stance on jurisdictional claims and institutional affiliations. [Extracted from the article]

Thermal energy storage and utilization has been widely concerned due to the intermittency, renewability, and economy of renewable energy. In this paper, the potential energy function of binary Na2CO3–K2CO3 salt was first constructed using the Deep Potential GENerator (DPGEN) enhanced sampling method. Deep potential molecular dynamics simulations were performed to calculate the thermal properties and structural evolution of binary carbonates. The results show that as the temperature increases from 1073 to 1273 K, the viscosity and thermal conductivity decrease from 5.011 mPa s and 0.502 W/(m K) to 2.526 mPa s and 0.481 W/(m K), respectively. The decrease in viscosity is related to the distance and interaction between the molten salt ions. In addition, the diffusion coefficients, energy barriers, ionic radius, angular distribution function, and coordination number of molten salt were calculated and analyzed. The CO32− exhibits a stable planar triangular structure. The ionic radius of Na+ is smaller than that of K+, which makes Na+ suffer less spatial hindrance during motion and has a higher diffusion coefficient. The energy barriers that Na+ needs to overcome to escape the Coulomb force is greater than that of K+ ions, so molten salt containing Na+ may possess greater heat storage potential. We believe that the potential function constructed with DPGEN enhanced sampling strategy can provide more convincing results for predicting the thermal properties of molten salts. This paper aims to provide a technical route to develop the novel complex molten salt phase change material for thermal energy storage. [ABSTRACT FROM AUTHOR]

Computer-aided drug design and discovery methods have been essential in developing small molecules with therapeutic properties over the last decades. Application of computational resources includes drug target identification, hit discovery, and lead optimization. Accordingly, with tremendous research efforts and the availability of financial support from government agencies across the world, and multinational drug companies, the overall research level in this area will continue to advance. The methodology used in this review paper entailed a thorough examination of research studies on relevant literature on drug design and development using computational resources. Extensive searches using Scopus, International Pharmaceutical Abstracts (OvidSp, WHO Global Health Library, Cochrane, Google Scholar, Web of Science, Science Direct, ProQuest dissertation & theses, Worldwide Political Science Abstracts (CSA), and PubMed was carried out. A standardized template was used to ensure that the selected papers met the inclusion criteria, and relevant to the review. Ultimately, there are robust technologies developed to enhance the drug discovery process. Therefore, this review provides insights into computational resources in Silico and ab initio methods and algorithms, not restricted to drug metabolism predictions for drug design, and the practical applications of artificial intelligence (AI) in drug discovery. Computational tools and methods for drug design and development such as molecular dynamics (MD), molecular docking, quantum mechanics (QM), hybrid quantum mechanics/molecular mechanics (QM/MM), and Density functional theory (DFT) have been reviewed. Accordingly, the emerging technique of synergistically employing these techniques influences the fundamental challenges of conventional medicines for complex diseases. Herein, we discuss ligand-based and structure-based drug discoveries, force field models in MD simulations, docking algorithms, subtractive and additive QM/MM coupling. Nonetheless, as computer-aided drug (CADD) approaches continue to evolve with significant improvements, the focus areas will be on docking and virtual screening, scoring functions, optimization of hits, and assessment of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. With the current success, the present computational resources will aid in the future discovery of novel compounds with high therapeutic performance. The ongoing oncology research efforts will also significantly contribute to UN sustainable development goals – good health and well-being, sustainable innovation and industrialization. [ABSTRACT FROM AUTHOR]

Copyright of Oilfield Chemistry is the property of Sichuan University, Oilfield Chemistry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this article, the formation of laser-induced graphene on the two natural polymers, cellulose, and lignin, as precursors was investigated with molecular dynamics simulations and some experiments. These eco-friendly polymers provide significant industrial advantages due to their low cost, biodegradability, and recyclable aspects. It was discovered during the simulation that LIG has numerous defects and a porous structure. Carbon monoxide, H2, and water vapor are gases released by cellulose and lignin substrates. H2O and CO are released when the polymer transforms into an amorphous structure. Later on, as the amorphous structure changes into an ordered graphitic structure, H2 is released continuously. Since cellulose monomer has a higher mass proportion of oxygen (49%) than lignin monomer (29%), it emits more CO. The LIG structure contains many 5- and 7-carbon rings, which cause the structure to have bends and undulations that go out of the plane. In addition, to verify the molecular dynamics simulation results with experimental tests, we used a carbon dioxide laser to transform filter paper, as a cellulose material, and coconut shell, as a lignin material, into graphene. Surprisingly, empirical experiments confirmed the simulation results. [ABSTRACT FROM AUTHOR]

Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586–599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head–tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes. [ABSTRACT FROM AUTHOR]

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Diamond nano-imprint microhole forming technology is a new type of microhole forming method. However, there will always be some unqualified microholes and cracks in the manufacture of microholes. In order to obtain better microhole quality, it is crucial to study the mechanism of microhole formation. In this paper, the indentation process of single crystal copper by a conical indenter is simulated by molecular dynamics. After the indentation is completed, microholes and cracks will form on the surface of the copper sheet. Dislocation analysis will be conducted on the microholes and surrounding cracks, and then the microstructure and morphology will be demonstrated to explain the formation mechanism of microholes and cracks. The influence of different indentation speeds and temperatures on the energy change of the system is discussed. In addition, this article established an experimental device for diamond indentation of copper sheets, and conducted indentation microholes experiments to observe microholes and cracks through scanning electron microscopy. The results show that when the diamond indenter is pressed down, the number of atoms in contact between the diamond indenter particles and the copper surface gradually increases, causing local stress concentration and the formation of new dislocations. Among them, 1/6<112> shockley dislocation is the main dislocation type. When the strain energy stored in the lattice increases beyond a certain value, the lattice structure of the copper atoms in the contact area is broken, resulting in internal defects, gradually forming microholes and surrounding cracks. The increase in the imprinting speed will accelerate the plastic deformation of the copper sheet. This paper reveals the mechanism of the formation of microholes and cracks, laying the foundation for high-quality micropore manufacturing. [ABSTRACT FROM AUTHOR]

Periplasmic binding proteins (PBPs) are bacterial proteins commonly used as scaffolds for substrate-detecting biosensors. In these biosensors, effector proteins (for example fluorescent proteins) are inserted into a PBP such that the effector protein's output changes upon PBP-substate binding. The insertion site is often determined by comparison of PBP apo/holo crystal structures, but random insertion libraries have shown that this can miss the best sites. Here, we present a PBP biosensor design method based on residue contact analysis from molecular dynamics. This computational method identifies the best previously known insertion sites in the maltose binding PBP, and suggests further previously unknown sites. We experimentally characterise fluorescent protein insertions at these new sites, finding they too give functional biosensors. Furthermore, our method is sufficiently flexible to both suggest insertion sites compatible with a variety of effector proteins, and be applied to binding proteins beyond PBPs. Author summary: "Biosensors" are microscopic tools that can detect specific molecules of interest and are made of biological building blocks, such as proteins. Upon coming into contact with their target molecule, such as a marker of a specific disease, biosensors change shape and their properties are altered. For example, upon contact with a disease marker, a biosensor could glow brightly to work as a diagnostic, or perhaps it could produce a chemical signal that can be detected by the immune system. Understanding how biosensors change shape in response to their target is key to developing more biosensors with complex responses. In this paper, we use computer simulations of a biosensor component to understand what parameters are important for biosensor design. We use these parameters to generate new biosensors that respond to their target molecule by producing light, but put forward a case that the lesson learned are generalisable enough to inform more complex sensor outputs as well. [ABSTRACT FROM AUTHOR]

The thermomechanical behavior of materials is known to be sensitive to preexisting defects in their microstructure. In this paper, non-equilibrium molecular dynamics simulations have been used to investigate the effects of the microvoid size on the plastic deformation in single-crystal iron shock-compressed along the [ 001 ] crystallographic direction. The higher the microvoid radius, the faster the kinetics of dislocations. Thus, as the microvoid radius increases, the plastic activity evolves from a regime where the deformation is dominated by twin activities to a regime where both twin and dislocation activities play an essential role and then to a regime where the deformation is dominated by dislocation slip. Furthermore, in both defect-free and defective initial crystal states, the elastic precursor wave is observed to decay with propagation distance, resulting in a constitutive functional dependence of the yielding pressure, σ E , on the plastic deformation rate, ε ˙ p. In the regime where both deformation twinning and dislocation slip play important roles, the constitutive behavior is consistent with the original Swegle–Grady model and is in overall agreement with experimental data and thermomechanical simulations. [ABSTRACT FROM AUTHOR]

A central paradigm of polymer physics states that chains in melts behave like random walks as intra- and interchain interactions effectively cancel each other out. Likewise, θ-chains, i.e., chains at the transition from a swollen coil to a globular phase, are also thought to behave like ideal chains, as attractive forces are counterbalanced by repulsive entropic contributions. While the simple mapping to an equivalent Kuhn chain works rather well in most scenarios with corrections to scaling, random walks do not accurately capture the topology and knots, particularly for flexible chains. In this paper, we demonstrate with Monte Carlo and molecular dynamics simulations that chains in polymer melts and θ-chains not only agree on a structural level for a range of stiffnesses but also topologically. They exhibit similar knotting probabilities and knot sizes, both of which are not captured by ideal chain representations. This discrepancy comes from the suppression of small knots in real chains, which is strongest for very flexible chains because excluded volume effects are still active locally and become weaker with increasing semiflexibility. Our findings suggest that corrections to ideal behavior are indeed similar for the two scenarios of real chains and that the structure and topology of a chain in a melt can be approximately reproduced by a corresponding θ-chain. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic behavior of EthylChlorophyllide A (EChlideA) molecules in a methanol solution confined within a 4 nm silica nanoslit, using molecular dynamics simulations over a duration of 1 ms. Three systems, containing 1, 2, and 4 solutes, were studied at 298 K. The results demonstrate that EChlideA molecules predominantly adsorb onto the silica surfaces, driven by specific interactions between chlorin ring's methyl group and the hydroxyl groups of the silica. This adsorption leads to stable binding, particularly in less crowded environments, as indicated by the potential of mean force analysis. Higher molecular concentrations, such as those with four EChlideA molecules, introduce variation in binding strength due to molecular aggregation and complex interactions. The orientation analysis reveals that the chlorin ring tends to align parallel to the surface, requiring rotational adjustments during surface diffusion. In addition, solvent coordination around the Mg ion remains consistent under bulk conditions, although with some variation in higher concentrations. This study also highlights a decrease in linear diffusion and an increase in rotational relaxation times for EChlideA molecules within the confined nanoslit, reflecting the influence of molecular concentration and arrangement on their dynamics. These findings provide valuable insights into the role of surface interactions, molecular orientation, and solvent coordination in confined environments, offering implications for the design of nanoscale systems. [ABSTRACT FROM AUTHOR]

Cold spray is an effective method for surface coating, which has been applied in various engineering areas. However, it is difficult to directly observe the dynamic deformation process in experiments. This paper applies the molecular dynamics simulation to model the deposition of a monocrystalline Cu particle onto a Cu substrate and, subsequently, carries out a systematic study on the deposition mechanism and microstructure evolution. The results indicate that the deposition process consists of an impact stage and a relaxation stage. It is mainly the high speed collision and the friction following the collision that lead to particle deposition, which, under different circumstances, can be defined as surface deposition or penetration deposition. Two methods, namely, drastic shear deformation and cooling in the relaxation stage, can help form nanocrystallines. Jetting and melting are not the necessary factors for the deposition of nano-sized particles. The formation of dislocation lines is influenced by impact velocities. At lower impact velocities, the dislocation lines are mainly distributed near the contact surface. However, when the impact velocity is higher, dislocation lines are almost uniformly distributed in the particle. [ABSTRACT FROM AUTHOR]

Liquid–liquid phase transitions hold a unique and profound significance within condensed matter physics. These transitions, while conceptually intriguing, often pose formidable computational challenges. However, recent advances in neural network (NN) potentials offer a promising avenue to effectively address these challenges. In this paper, we delve into the structural transitions of liquid CdTe, CdS, and their alloy systems using molecular dynamics simulations, harnessing the power of an NN potential named LaspNN. Our investigations encompass both pressure and temperature effects. Through our simulations, we uncover three primary liquid structures around melting points that emerge as pressure increases: tetrahedral, rock salt, and close-packed structures, which greatly resemble those of solid states. In the high-temperature regime, we observe the formation of Te chains and S dimers, providing a deeper understanding of the liquid's atomic arrangements. When examining CdSxTe1−x alloys, our findings indicate that a small substitution of S by Te atoms for S-rich alloys (x > 0.5) exhibits a structural transition much different from CdS, while a large substitution of Te by S atoms for Te-rich alloys (x < 0.5) barely exhibits a structural transition similar to CdTe. We construct a schematic diagram for liquid alloys that considers both temperature and pressure, providing a comprehensive overview of the alloy system's behavior. The local aggregation of Te atoms demonstrates a linear relationship with alloy composition x, whereas that of S atoms exhibits a nonlinear one, shedding light on the composition-dependent structural changes. [ABSTRACT FROM AUTHOR]

Understanding how external electric fields (EFs) impact the properties of aqueous molecules is crucial for various applications in chemistry, biology, and engineering. In this paper, we present a study utilizing molecular dynamics simulation to explore how direct-current (DC) and alternative-current (AC) EFs affect hydrophobic (n-triacontane) and hydrophilic (PEG-10) oligomer chains. Through a machine learning approach, we extract a 2-dimensional free energy (FE) landscape of these molecules, revealing that electric fields modulate the FE landscape to favor stretched configurations and enhance the alignment of the chain with the electric field. Our observations indicate that DC EFs have a more prominent impact on modulation compared to AC EFs and that EFs have a stronger effect on hydrophobic chains than on hydrophilic oligomers. We analyze the orientation of water dipole moments and hydrogen bonds, finding that EFs align water molecules and induce more directional hydrogen bond networks, forming 1D water structures. This favors the stretched configuration and alignment of the studied oligomers simultaneously, as it minimizes the disruption of 1D structures. This research deepens our understanding of the mechanisms by which electric fields modulate molecular properties and could guide the broader application of EFs to control other aqueous molecules, such as proteins or biomolecules. [ABSTRACT FROM AUTHOR]

Single crystal 3C-SiC as a typical hard and brittle material. Due to its extremely high hardness and brittleness, diamond tools can have drastic wear problems in a short period of time when performing nano-machining processes. Single-crystal 3C-SiC has good anisotropy. In order to gain insight into the effect of crystal orientation on the tool wear behavior during nano-cutting, this paper investigated the tool wear for six cutting crystals downward using molecular dynamics simulation. The tool wear process was analyzed in terms of tool wear, cutting stress, cutting temperature, cutting force and subsurface damage. The results showed that the tool is subjected to large hydrostatic stress concentrations, radial forces and tool temperature concentrations during machining. Under these effects, abrasive wear, graphitic wear and amorphous phase change were produced. In addition, the clearance face of the tool is more severely worn than the rake face. By reasonably selecting the cutting crystal orientation, well control and improvement of tool wear and machined surface quality can be achieved. [ABSTRACT FROM AUTHOR]

The integration of abscisic acid (ABA) into a chitosan–alginate gel blend unveils crucial insights into the formation and stability of these two substances. ABA, a key phytohormone in plant growth and stress responses, is strategically targeted for controlled release within these complexes. This study investigates the design and characterization of this novel controlled-release system, showcasing the potential of alginate–chitosan gel blends in ABA delivery. Computational methods, including molecular dynamics simulations, are employed to analyze the structural effects of microencapsulation, offering valuable insights into complex behavior under varying conditions. This paper focuses on the controlled release of ABA from these complexes, highlighting its strategic importance in drug delivery systems and beyond. This controlled release enables targeted and regulated ABA delivery, with far-reaching implications for pharmaceuticals, agriculture, and plant stress response studies. While acknowledging context dependency, the paper suggests that the liberation or controlled release of ABA holds promise in applications, urging further research and experimentation to validate its utility across diverse fields. Overall, this work significantly contributes to understanding the characteristics and potential applications of chitosan–alginate complexes, marking a noteworthy advancement in the field of controlled-release systems. [ABSTRACT FROM AUTHOR]

In Parallel programming, a programmer needs to understand hardware environment, programming paradigm and primitives available in the programming language. Most of the time, parallel programmes are written for a specific architecture and cannot typically adapt to other architectures Particularly, programs written for shared memory architectures are unsuitable for distributed or hybrid architectures. This paper proposes Adaptive Design Pattern for Parallel Programming to improve adaptability, flexibility with achieving performance on different architectures. Molecular Dynamics (MD) simulation is required to scale to various architectures from simple machine to cluster of workstations. In this study, MD Simulation experimented using both pure benchmark code and code based on adaptive design patterns. Redesigned MD Simulation with Adaptive Design Pattern claims parallel efficiency from 56% to 90% for different number of processing elements used. The solution demonstrates adaptability to different architectures and scalability to use with large number of atoms and long duration simulation. [ABSTRACT FROM AUTHOR]

Bioresorbable magnesium-metal vascular stents are gaining popularity due to their biodegradable nature and good biological and mechanical properties. They are also suitable candidate materials for biodegradable stents. Due to the rapid degradation rate of Mg metal vascular scaffolds, a Mg/Zn bilayer composite was formed by a number of means, such as magnetron sputtering and physical vapor deposition, thus delaying the degradation time of the Mg metal vascular scaffolds while providing good radial support for the stenotic vessels. However, the interlaminar compounds at the metal interface have an essential impact on the mechanical properties of the bi-material interface, especially the cracking and delamination of the Mg matrix Zn coating vascular stent in the radially expanded process layer. Intermetallic compounds (IMCs) are commonly found in dual-layer composites, such as Mg/Zn composites and multi-layer structures. They are frequently overlooked in simulations aiming to predict mechanical properties. This paper analyses the interfacial failure processes and evolutionary mechanisms of interfacial fracture mechanics of a Mg/Zn interface with an intermetallic compound layer between coated Zn and Mg matrix metallic vascular stents. The simulation results show that the fracture mode in the Mg/Zn interface with an intermetallic compound involves typical ductile fracture under static tensile conditions. The dislocation line defects mainly occur on the side of the Mg, which induces the Mg/Zn interfacial crack to expand along the interface into the pure Mg. The stress intensity factor and the critical strain energy release rate decrease as the intermetallic compound layer's thickness gradually increases, indicating that the intensity of stress and the force of the crack extending and expanding along the crack tip are weakened. The presence of intermetallic compounds at the interface can significantly strengthen the mechanical properties of the material interface and alleviate the crack propagation between the interfaces. [ABSTRACT FROM AUTHOR]

The self-driven behavior of droplets on a functionalized surface, coupled with wetting gradient and wedge patterns, is systematically investigated using molecular dynamics (MD) simulations. The effects of key factors, including wedge angle, wettability, and wetting gradient, on the droplet self-driving effect is revealed from the nanoscale. Results indicate that the maximum velocity of droplets on hydrophobic wedge-shaped surfaces increases with the wedge angle, accompanied by a rapid attenuation of driving force; however, the average velocity decreases with the increased wedge angle. Conversely, droplet movement on hydrophilic wedge-shaped surfaces follows the opposite trend, particularly in terms of average velocity compared to the hydrophobic case. Both wedge-shaped and composite gradient wedge-shaped surfaces are found to induce droplet motion, with droplets exhibiting higher speeds and distances on hydrophobic surfaces compared to hydrophilic surfaces, regardless of surface type. Importantly, the inclusion of wettability gradients significantly influences droplet motion, with hydrophobic composite gradient wedge-shaped surfaces showing considerable improvements in droplet speed and distance compared to their hydrophilic counterparts. By combining suitable wettability gradients with wedge-shaped surfaces, the limitations inherent in the wettability gradient range and wedge-shaped configuration can be mitigated, thereby enhancing droplet speed and distance. The findings presented in this paper offer valuable insights for the design of advanced functional surfaces tailored for manipulating droplets in real-world applications. [ABSTRACT FROM AUTHOR]

AbstractCompared with conventional solders, nano-silver benefits low-temperature sintering and high-temperature service, perfectly matching the high-temperature operating environment for third-generation semiconductor devices. However, the synthetic cost, complexity of the sintering process and the low connection strength limit its development. This paper describes the physical, chemical reduction and biological methods of synthesizing and compares the advantages and disadvantages of these three methods. The process parameters affecting the sintering process of silver nanoparticles (Ag NPs) are presented in a comprehensive and in-depth manner. Present methods are also introduced to improve the quality of nano-silver joints, such as the adding enhancement, the silver nanostructured films, and a trimodal-Ag paste consisting of silver particles in three sizes: nano, submicron and micron, aiming to break the limitation of the poor quality of nano-silver joints. In addition, this paper provides the first comprehensive summary of the sintering process and sintering mechanism of nano-silver, and introduces the latest results of the study of the sintering mechanism of nano-silver by using the Molecular Dynamics Simulation (MDS) technique. At the end, the advanced applications of nano-silver are shown, thus pointing out the direction for the further development and applications of nano-silver. [ABSTRACT FROM AUTHOR]

Given that SOF materials have both inorganic and organic properties and are easy to prepare and structurally designable, this paper carries out the microbehavioral analysis and membrane design of SOF-8, SOF-9, and SOF-10 membranes for the hydrogen purification process of RMFCs. Since three materials have complementary performance characteristics for hydrogen purification, this paper focuses on the gas separation behavior of these three composite membranes using molecular dynamics simulations. Results showed that the SOF-9a+10a composite membranes could 100% block CO 2 and CO, and displayed an excellent H 2 permeability of 6.118 × 105 GPU during H 2 /CO 2 separation, which exceeded the industry standard by nearly 105 times. Additionally, the SOF-9a+8 and SOF-10a+8 composite membranes improved gas selectivity and maintained high H 2 permeability. Moreover, microdiffusion analyses revealed that the small pore sizes and irregular-shaped pore channels effectively hindered CO 2 and CO transport. Microscopic analysis shows the potential of SOF composite membranes for gas separation. [Display omitted] • SOF composite membranes can effectively improve gas selectivity. • Small pore sizes and irregular pore channels can effectively block CO 2 transport. • SOF-9a+10 can 100% intercept CO 2 and CO. • The interaction between gas and membrane affects the gas separation performance. [ABSTRACT FROM AUTHOR]

The study of nano-scratching under water lubrication is helpful to understand the role of lubrication mechanism in the machining of single crystal γ-TiAl alloy. In this paper, through the comparative analysis of nano-scratching under different thicknesses of water layers, it was found that under a water layer thickness of 1 nm, nano-scratching not only improves the surface quality but also achieves multiple reductions in scratch force, stress, temperature and subsurface structural damage. In order to deeply reveal the internal mechanism of workpiece temperature variation under different thicknesses of water layer lubrication, a fitting formula was innovatively adopted to conduct quantitative analysis. In addition, with the increase of the thickness of the water layer, it was observed that the water film effect was continuously enhanced, and this change caused the matrix stress to gradually increase, which hindered the forward motion of the nanoscratch, ultimately resulting in an increase in the friction coefficient. These findings provide valuable insights into the nanoscratching mechanism of monocrystalline γ-TiAl alloy in the presence of water film, and provide a new perspective for understanding the complex mechanism of nanoscratch behaviour under water lubrication, thus promoting the understanding of nanoscale lubrication effects. [ABSTRACT FROM AUTHOR]

Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws rely on phenomenological models of the underlying physics, whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress, temperature, and local environment, such as body-centered cubic crystals (BCC) metals and alloys. In this paper, we present a novel, uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations, using Graph Neural Networks (GNN) with a physics-informed architecture. We demonstrate that this Physics-informed Graph Neural Network (PI-GNN) framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals. [ABSTRACT FROM AUTHOR]

In this study, we use molecular dynamics (MD) simulation to predict the thermodynamics, structural, and transport characteristics of liquid para-hydrogen (para-H 2) over a wide temperature range. The Feynman–Hibbs (FH) technique employs Lennard-Jones pair potentials (LJ) which are enhanced by quantum modifications to describe molecular interactions. Results retain the FH's structural, thermodynamics and transport properties, and the classical LJ models (the radial distribution function, total energy, pressure, potential energy, enthalpy, diffusion coefficient, and shear viscosity). The datasets included in the paper were also considered, along with the experimental data collected, where possible. This work shows that for liquid para-H2, FH approach integrated to classical MD simulation, including quantum corrections yields an excellent accordance with the experimental findings. The FH potential improves concordance with the shear viscosity and diffusion coefficient values, as demonstrated by the results. With greater accuracy to experimental data, the FH Molecular Dynamics approach (FHMD) predicts such values. [ABSTRACT FROM AUTHOR]

Black phosphorene is a kind of two-dimensional layered material with special structure and excellent physical properties. It is a kind of middle temperature thermoelectric material with application prospect. In this paper, the advantages and disadvantages of the two methods are discussed by summarizing and comparing the experimental research and simulation calculation methods of the thermoelectric properties of black phosphorene. The characteristics and unique anisotropy of the thermoelectric transport performance of black phosphorene were studied, and the influence of different regulation methods on the thermoelectric transport performance of black phosphorene was analyzed. This paper can provide reference for the research methods of related thermoelectric materials. [ABSTRACT FROM AUTHOR]

Porous graphene membranes (PGMs) have nanopores with single atomic thickness, which enables the precise and stable supply of ultralow flow rate gas below 10−14 Pa·m3·s−1. Different from a conventional channel, the surface diffusion (SD) process in PGM has become increasingly important and unique. However, the physical process and mathematical model of gas molecule transport in nanopores with single atomic thickness remain unclear. These inadequacies constrained the application of PGM in ultrasensitive leak detection. In this paper, the SD process in PGM was investigated using molecular dynamics simulation. A test rig was constructed to verify the simulation results. The nanopores in PGM were quantitatively characterized using a transmission electron microscope. Results show that a transfer region encircling the nanopores was identified, which plays a crucial role in the SD process. Furthermore, the physical model of SD process is described with a two-step model. Finally, a mathematical model of the SD process is established and validated. This paper provides nanoscale insights for an in-depth understanding of the SD process in PGM and promotes ultrasensitive leak detection technology. [ABSTRACT FROM AUTHOR]

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Powder metallurgy is a process for compacting and sintering powders such as metals and ceramics, and has been attracting new attention in recent years. This paper presents research examples in which simulation methods such as molecular dynamics (MD) method, Monte Carlo (MC) method, finite element method (FEM), and discrete element method (DEM) are applied to powder metallurgy. The MD method is used to calculate physical property values such as interfacial energy and diffusion coefficient that change depending on the type of grain boundaries. The MC method is used to calculate the microstructural development due to the sintering and grain growth. The microstructure can be predicted when the sintering process is changed. The FEM is used to calculate deformation and strain. The sintering simulation combined with the MC method can calculate the microstructural changes and deformation simultaneously. In the compaction simulation, density distribution due to the friction with the mold can be analyzed. The DEM is used to calculate the compaction structure. The interaction of the friction and stiffness between particles and particle/mold can be analyzed. As powder metallurgy technology develops, process design that considers the whole process will be important. Supporting technology based on simulation will become increasingly important. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Bioinformatics is the property of Bioinformatics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nitrogen vacancy (NV) color centers in diamond have useful applications in quantum sensing and fluorescent marking. They can be generated experimentally by ion implantation, femtosecond lasers, and chemical vapor deposition. However, there is a lack of studies of the yield of NV color centers at the atomic scale. In the molecular dynamics simulations described in this paper, NV color centers are prepared by ion implantation in diamond with pre-doped nitrogen and subsequent annealing. The differences between the yields of NV color centers produced by implantation of carbon (C) and nitrogen (N) ions, respectively, are investigated. It is found that C-ion implantation gives a greater yield of NV color centers and superior location accuracy. The effects of different pre-doping concentrations (400–1500 ppm) and implantation energies (1.0–3.0 keV) on the NV color center yield are analyzed, and it is shown that a pre-doping concentration of 1000 ppm with 2 keV C-ion implantation can produce a 13% yield of NV color centers after 1600 K annealing for 7.4 ns. Finally, a brief comparison of the NV color center identification methods is presented, and it is found that the error rate of an analysis utilizing the identify diamond structure + coordination analysis method is reduced by about 7% compared with conventional identification methods. HIGHLIGHTS: • Homologous ion implantation can produce excellent nitrogen vacancy (NV) color centers. • Appropriate implantation parameters determine the quality of NV color centers. • A 13% yield of NV color centers can be realized at 2 keV C implantation. • Enhanced quality of NV color centers benefits quantum applications. [ABSTRACT FROM AUTHOR]

This paper conducts a computational investigation of the phase behaviour of $ \textrm{C}{\textrm{H}_4} $ C H 4 - $ \textrm{C}{\textrm{O}_2} $ C O 2 binary system, utilising the SAFT-VR Mie equation of state alongside molecular dynamics (MD) simulations. Molecular parameters for pure $ \textrm{C}{\textrm{H}_4} $ C H 4 and $ \textrm{C}{\textrm{O}_2} $ C O 2 compounds were obtained by fitting the SAFT-VR Mie EOS to vapour pressure and saturated liquid density experimental data. The research first validates the SAFT-VR Mie EOS on thermodynamic properties and vapour–liquid equilibria for different compositions, pressures, and temperatures of pure $ \textrm{C}{\textrm{H}_4} $ C H 4 , $ \textrm{C}{\textrm{O}_2} $ C O 2 , and $ \textrm{C}{\textrm{H}_4} $ C H 4 - $ \textrm{C}{\textrm{O}_2} $ C O 2 mixtures with the newly extracted parameters. The study confirms the EOS's accurate prediction of coexistence properties, including pressure, density, and phase-equilibrium curve. MD simulations were performed using the LAMMPS software package, with Mie force field parameters derived from this study for non-bonded interactions. Simulations were conducted using three other force fields (OPLS-UA, UFF, and GAFF) to compare their performance with our approach. The simulation results were compared to laboratory data, or REFPROP, in the absence of laboratory data. The results showed a relatively good agreement, indicating that combining SAFT-VR Mie EOS and MD simulations is a reliable predictive tool for designing gas processing and gas storage applications involving $ \textrm{C}{\textrm{H}_4} $ C H 4 - $ \textrm{C}{\textrm{O}_2} $ C O 2 mixtures. This approach also mitigates the need for expensive and hazardous high-pressure laboratory techniques. [ABSTRACT FROM AUTHOR]

Bisphenols are a group of endocrine-disrupting chemicals used worldwide for the production of plastics and resins. Bisphenol A (BPA), the main bisphenol, exhibits many unwanted effects. BPA has, currently, been replaced with bisphenol F (BPF) and bisphenol S (BPS) in many applications in the hope that these molecules have a lesser effect on metabolism than BPA. Since bisphenols tend to partition into the lipid phase, their place of choice would be the cellular membrane. In this paper, I carried out molecular dynamics simulations to compare the localization and interactions of BPA, BPF, and BPS in a complex membrane. This study suggests that bisphenols tend to be placed at the membrane interface, they have no preferred orientation inside the membrane, they can be in the monomer or aggregated state, and they affect the biophysical properties of the membrane lipids. The properties of bisphenols can be attributed, at least in part, to their membranotropic effects and to the modulation of the biophysical membrane properties. The data support that both BPF and BPS, behaving in the same way in the membrane as BPA and with the same capacity to accumulate in the biological membrane, are not safe alternatives to BPA. [ABSTRACT FROM AUTHOR]

In order to investigate the interphase mass transfer and component distribution characteristics of the CO2–water system under micro-scale and nano-scale transport conditions, a micro-scale kinetic model representing interphase mass transfer in the CO2–water/saline system is developed in this paper. The molecular dynamics method is employed to delineate the diffusion and mass transfer processes of the system's components, revealing the extent of the effects of variations in temperature, pressure, and salt ion concentration on interphase mass transfer and component distribution characteristics. The interphase mass transfer process in the CO2–water system under transport conditions can be categorized into three stages: approach, adsorption, and entrance. As the system temperature rises and pressure decreases, the peak density of CO2 molecules at the gas–liquid interface markedly drops, with their aggregation reducing and their diffusion capability enhancing. The specific hydration structures between salt ions and water molecules hinder the entry of CO2 into the aqueous phase. Additionally, as the salt concentration in water increases, the density peak of CO2 molecules at the gas–liquid interface slightly increases, while the density value in the water phase region significantly decreases. [ABSTRACT FROM AUTHOR]

In low-temperature environments, asphalt materials harden easily and become brittle, and the repeated action of traffic load further aggravates the cracking of and damage to the asphalt mixture. In order to explore high-performance asphalt pavement materials that are more suitable for cold climates, this paper selected four modifiers, namely SBS, rubber powder, SBR and TPS. With SBS as the main agent, combined with other modifiers, three types of base asphalts with grades of 70#, 90# and 110# were compositely modified to prepare 12 different combinations of composite-modified asphalt samples. The optimal dosage of the modifier was determined by the basic performance test of asphalt, and the compatibility, interaction energy and mechanical properties of the modifier and base asphalt at different temperatures were analyzed by molecular dynamics simulation. Subsequently, the high- and low-temperature rheological properties of various modified asphalts were systematically evaluated using a dynamic shear rheology test (DSR) and a bending beam rheology test (BBR), and the rheological properties and road performance indicators of each composite-modified asphalt were comprehensively compared so as to select the road materials most suitable for cold areas. The research results show that different grades of base asphalt and modifiers show good compatibility in the range of 160–175 °C. Among them, rubber powder and TPS modifier significantly improve the high-temperature mechanical properties of SBS-modified asphalt, while rubber powder and SBR modifier significantly improve its low-temperature mechanical properties. The DSR and BBR test results further show that SBS/rubber powder composite-modified asphalt exhibits excellent rheological properties under both high- and low-temperature conditions, and is the preferred solution for road materials in cold regions. [ABSTRACT FROM AUTHOR]

Sampling rare events in proteins is crucial for comprehending complex phenomena like cryptic pocket opening, where transient structural changes expose new binding sites. Understanding these rare events also sheds light on protein-ligand binding and allosteric communications, where distant site interactions influence protein function. Traditional unbiased molecular dynamics simulations often fail to sample such rare events, as the free energy barrier between metastable states is large relative to the thermal energy. This renders these events inaccessible on the timescales typically simulated by unbiased molecular dynamics, limiting our understanding of these critical processes. In this paper, we proposed a novel unsupervised learning approach termed as slow feature analysis (SFA) which aims to extract slowly varying features from high-dimensional temporal data. SFA trained on small unbiased molecular dynamics simulations launched from AlphaFold generated conformational ensembles manages to capture rare events governing cryptic pocket opening, protein-ligand binding, and allosteric communications in a kinase. Metadynamics simulations using SFA as collective variables manage to sample 'deep' cryptic pocket opening within a few hundreds of nanoseconds which was beyond the reach of microsecond long unbiased molecular dynamics simulations. SFA augmented metadynamics also managed to capture conformational plasticity of protein upon ligand binding/unbinding and provided novel insights into allosteric communication in receptor-interacting protein kinase 2 (RIPK2) which dictates protein-protein interaction. Taken together, our results show how SFA acts as a dimensionality reduction tool which bridges the gap between AlphaFold, molecular dynamics simulation and metadynamics in context of capturing rare events in biomolecules, extending the scope of structure-based drug discovery in the era of AlphaFold. [ABSTRACT FROM AUTHOR]

This study utilized ion implantation to modify the material properties of silicon carbide (SiC) to mitigate subsurface damage during SiC machining. The paper analyzed the mechanism of hydrogen ion implantation on the machining performance of SiC at the atomic scale. A molecular dynamics model of nanoscale cutting of an ion-implanted SiC workpiece using a non-rigid regular tetrakaidecahedral diamond abrasive grain was established. The study investigated the effects of ion implantation on crystal structure phase transformation, dislocation nucleation, and defect structure evolution. Results showed ion implantation modification decreased the extension depth of amorphous structures in the subsurface layer, thereby enhancing the surface and subsurface integrity of the SiC workpiece. Additionally, dislocation extension length and volume within the lattice structure were lower in the ion-implanted workpiece compared to non-implanted ones. Phase transformation, compressive pressure, and cutting stress of the lattice in the shear region per unit volume were lower in the ion-implanted workpiece than the non-implanted one. Taking the diamond abrasive grain as the research subject, the mechanism of grain wear under ion implantation was explored. Grain expansion, compression, and atomic volumetric strain wear rate were higher in the non-implanted workpiece versus implanted ones. Under shear extrusion of the SiC workpiece, dangling bonds of atoms in the diamond grain were unstable, resulting in graphitization of the diamond structure at elevated temperatures. This study established a solid theoretical and practical foundation for realizing non-destructive machining at the atomic scale, encompassing both theoretical principles and practical applications. [ABSTRACT FROM AUTHOR]

Checkpoint kinases 1 and 2 (CHK1 and CHK2) are enzymes that are involved in the control of DNA damage. At the present time, these enzymes are some of the most important targets in the fight against cancer since their inhibition produces cytotoxic effects in carcinogenic cells. This paper proposes the use of spirostans (Sp), natural compounds, as possible inhibitors of the enzymes CHK1 and CHK2 from an in silico analysis of a database of 155 molecules (S5). Bioinformatics studies of molecular docking were able to discriminate between 13 possible CHK1 inhibitors, 13 CHK2 inhibitors and 1 dual inhibitor for both enzymes. The administration, distribution, metabolism, excretion and toxicity (ADMETx) studies allowed a prediction of the distribution and metabolism of the potential inhibitors in the body, as well as determining the excretion routes and the appropriate administration route. The best inhibition candidates were discriminated by comparing the enzyme-substrate interactions from 2D diagrams and molecular docking. Specific inhibition candidates were obtained, in addition to studying the dual inhibitor candidate and observing their stability in dynamic molecular studies. In addition, Highest Occupied Molecular Orbital—Lowest Unoccupied Molecular Orbital (HOMO-LUMO) interactions were analyzed to study the stability of interactions between the selected enzymes and spirostans resulting in the predominant gaps from HOMOCHKs to LUMOSp (Highest Occupied Molecular Orbital of CHKs—Lowest Unoccupied Molecular Orbital of spirostan). In brief, this study presents the selection inhibitors of CHK1 and CHK2 as a potential treatment for cancer using a combination of molecular docking and dynamics, ADMETx predictons, and HOMO-LUMO calculation for selection. [ABSTRACT FROM AUTHOR]

The strategic importance of developing environmentally friendly PVC biomass plasticizers with excellent anti-migration and plasticizing effects cannot be overstated. This paper delves into the synthesis and application of bio-based isosorbide di-epoxidized oleate (IDEO) as a secondary biomass plasticizer in polyvinyl chloride (PVC) films. Explored were the synergistic effects between IDEO and dioctyl phthalate (DOP), alongside an assessment of the influence of the compound plasticizer on the properties of PVC products. The partial substitution of DOP resulted in PVC films with improved thermal stability, flexibility, and migration resistance. IDEO-10/PVC, in particular, exhibited a 64% increase in tensile strength compared to DOP/PVC and maintained thermal stabilization for over 280 min at 180 °C. With a glass transition temperature (Tg) of 33 °C, a plasticizing efficiency of 148%, and excellent cold resistance properties, IDEO-10/PVC outperformed DOP/PVC. IDEO-10/PVC migration resistance was significantly lower than in the original PVC resin with only DOP plasticizers under three different polar conditions. Transmittance remained above 87% after 10 days of UV irradiation. Molecular dynamics simulation further confirmed the synergistic plasticizing effect between IDEO and DOP at an IDEO addition of 10 phr. The environmentally friendly approach holds significant promise for the scaled-up application of PVC. [ABSTRACT FROM AUTHOR]

The design and optimization of antimicrobial materials (polymers, biomolecules, or nanocomposites) can be significantly advanced by computational methodologies like molecular dynamics (MD), which provide insights into the interactions and stability of the antimicrobial agents within the polymer matrix, and machine learning (ML) or design of experiment (DOE), which predicts and optimizes antimicrobial efficacy and material properties. These innovations not only enhance the efficiency of developing antimicrobial polymers but also enable the creation of materials with tailored properties to meet specific application needs, ensuring safety and longevity in their usage. Therefore, this paper will present the computational methodologies employed in the synthesis and application of antimicrobial polymers, biomolecules, and nanocomposites. By leveraging advanced computational techniques such as MD, ML, or DOE, significant advancements in the design and optimization of antimicrobial materials are achieved. A comprehensive review on recent progress, together with highlights of the most relevant methodologies' contributions to state-of-the-art materials science will be discussed, as well as future directions in the field will be foreseen. Finally, future possibilities and opportunities will be derived from the current state-of-the-art methodologies, providing perspectives on the potential evolution of polymer science and engineering of novel materials. [ABSTRACT FROM AUTHOR]

The commonly used aluminum–copper alloys in industry are mainly rolled plates and extruded or drawn bars. The aluminum–copper alloys' anisotropy generated in the manufacturing process is unfavorable for subsequent applications. Its underlying mechanism shall be interpreted from a microscopic perspective. This paper conducted the loading simulation on Al–4%Cu alloy crystals at the microscopic scale with molecular dynamics technology. Uniaxial tension and compression loading were carried out along three orientations: X-< 1 ¯ 12 >, Y-< 1 1 ¯ 1 >, and Z-<110>. It analyzes the micro-mechanisms that affect the performance changes of aluminum–copper alloys through the combination of stress–strain curves and different organizational analysis approaches. As shown by the results, the elastic modulus and yield strength are the highest under tension along the < 1 1 ¯ 1 > direction. Such is the case for the reasons below: The close-packed plane of atoms ensures large atomic binding forces. In addition, the Stair-rod dislocation forms a Lomer–Cottrell dislocation lock, which has a strengthening effect on the material. The elastic modulus and yield strength are the smallest under tension along the <110> direction, and the periodic arrangement of HCP atom stacking faults serves as the main deformation mechanism. This is because the atomic arrangement on the <110> plane is relatively loose, which tends to cause atomic misalignment. When compressed in different directions, the plastic deformation mechanism is mainly dominated by dislocations and stacking faults. When compressed along the <110> direction, it has a relatively high dislocation density and the maximum yield strength. That should be attributed to the facts below. As the atomic arrangement of the <110> plane itself was not dense originally, compression loading would cause an increasingly tighter arrangement. In such a case, the stress could only be released through dislocations. This research aims to provide a reference for optimizing the processing technology and preparation methods of aluminum–copper alloy materials. [ABSTRACT FROM AUTHOR]