Search Results (65)

In this purely analytical analysis, we have investigated the effects of a point-like defect in a continuous medium on a diatomic molecule under the influence of small oscillations arising from the Lennard-Jones potential. In the search for bound-state solutions, we have shown that the allowed values for the lowest energy state of the molecule are influenced by the presence of the defect. Furthermore, another quantum effect was observed: the stability radial point of the diatomic molecule depends on the system’s quantum numbers; it is quantized. Full article

BioHealing Optimization (BHO) is a bio-inspired metaheuristic that operationalizes the injury–recovery paradigm through an iterative loop of recombination, stochastic injury, and guided healing. The algorithm is further enhanced by adaptive mechanisms, including scar map, hot-dimension focusing, RAGE/hyper-RAGE bursts (Rapid Aggressive Global Exploration), and healing-rate modulation, enabling a dynamic balance between exploration and exploitation. Across 17 benchmark problems with 30 runs, each under a fixed budget of $1.5·{10}^5$ function evaluations, BHO achieves the lowest overall rank in both the “best-of-runs” (47) and the “mean-of-runs” (48), giving an overall rank sum of 95 and an average rank of 2.794. Representative first-place results include Frequency-Modulated Sound Waves, the Lennard–Jones potential, and Electricity Transmission Pricing. In contrast to prior healing-inspired optimizers such as Wound Healing Optimization (WHO) and Synergistic Fibroblast Optimization (SFO), BHO uniquely integrates (i) an explicit tri-phasic architecture (DE/best/1/bin recombination → Gaussian/Lévy injury → guided healing), (ii) per-dimension stateful adaptation (scar map, hot-dims), and (iii) stagnation-triggered bursts (RAGE/hyper-RAGE). These features provide a principled exploration–exploitation separation that is absent in WHO/SFO. Full article

In the field of unmanned aerial vehicle (UAV) swarm control, achieving efficient consensus is paramount. This paper proposes a molecular dynamics-based UAV swarm consensus control strategy. The strategy emulates the random motion of molecules in a vacuum, establishing a framework for UAV swarm behavior that aligns with principles from molecular dynamics. The framework is built upon the Vicsek model, a cornerstone in swarm dynamics, and employs the Lennard-Jones and Morse potential functions to model the attractive and repulsive forces between UAVs. Through simulation, this paper explores how different potential functions and swarm sizes affect consensus control, finding the Morse potential particularly advantageous. Theoretical analysis and experimental results demonstrate that these potential functions not only prevent UAV collisions but also facilitate the emergence of swarming behaviors, thereby enhancing the collaborative efficiency and stability of UAV swarms. This advancement significantly boosts the overall performance of swarm control, paving the way for the deployment of UAV swarms in complex environments. Full article

Resorting to microcanonical ensemble Monte Carlo simulations, we study the geometric and topological properties of the state space of a model of a network glass-former. This model, a Lennard-Jones binary mixture, does not crystallize due to frustration. We have found two peaks in specific heat at equilibrium and at low energy, corresponding to important changes in local ordering. These singularities were accompanied by inflection points in geometrical markers of the potential energy level sets—namely, the mean curvature, the dispersion of the principal curvatures, and the variance of the scalar curvature. Pinkall’s and Overholt’s theorems closely relate these quantities to the topological properties of the accessible state-space manifold. Thus, our analysis provides strong indications that the glass transition is associated with major changes in the topology of the energy level sets. This important result suggests that this phase transition can be understood through the topological theory of phase transitions. Full article

Silver(I) ions and organometallic complexes thereof are well-established antimicrobial agents. They have been employed in medical applications for centuries. It is also known that some bacteria can resist silver(I) treatments through an efflux mechanism. However, the exact mechanism of action remains unclear. All-atom force-field simulations can provide valuable structural and thermodynamic insights into the molecular processes of the underlying mechanism. Lennard-Jones parameters of silver(I) have been available for quite some time; their applicability to properly describing the binding properties (affinity, binding distance) between silver(I) and peptide-based binding motifs is, however, still an open question. Here, we demonstrate that the standard 12-6 Lennard-Jones parameters (previously developed to describe the hydration free energy with the TIP3P water model) significantly underestimate the interaction strength between silver(I) and both methionine and histidine. These are two key amino-acid residues in silver(I)-binding motifs of proteins involved in the efflux process. Using free-energy calculations, we calibrated non-bonded fix (NBFIX) parameters for the CHARMM36m force field to reproduce the experimental binding constant between amino acid sidechain fragments and silver(I) ions. We then successfully validated the new parameters on a set of small silver-binding peptides with experimentally known binding constants. In addition, we monitored how silver(I) ions increased the α-helical content of the LP1 oligopeptide, in agreement with previously reported Circular Dichroism (CD) experiments. Future improvements are outlined. The implementation of these new parameters is straightforward in all simulation packages that can use the CHARMM36m force field. It sets the stage for the modeling community to study more complex silver(I)-binding processes such as the interaction with silver(I)-binding-transporter proteins. Full article

Interfacial adhesion is one of the key factors affecting the reliability of micro–nano systems. The adhesion contact mechanism is still unclear as the time-dependent viscoelasticity of soft materials. To clarify the adhesion interaction, the pull-off detachment between the rigid flat punch and viscoelastic substrate is explored considering the viscoelasticity of soft materials and rate-dependent adhesion. Taking the Lennard-Jones (L-J) potential characterizing interfacial adhesion and the Prony series defining the viscoelasticity of materials as references, the bilinear cohesion zone model (CZM) and standard Maxwell model are employed, and an adhesion analysis framework is established by combining finite element technology. The influence laws of the loading and unloading rates, material relaxation coefficients and size effect on adhesion pull-off behavior are revealed. The results show that the pull-off force is independent of the material relaxation effect and related to the unloading rate. When $\widehat{v}$ ≥ 50 or $\widehat{v}$ < 0.01, the pull-off force has nothing to do with the unloading rate, but when 0.01 < $\widehat{v}$ < 50, the pull-off force increases with the increasing unloading rate. Also, it is controlled by the size effect, and the changing trend conforms to the MD-n model proposed by Jiang. The energy required for interfacial separation (i.e., effective adhesion work) is a result of the comprehensive influence of unloading rates, material properties and the relaxation effect, which is consistent with Papangelo1’s research results. In addition, we derive the critical contact radius of the transition from the Kendall solution to the strength control solution. This work not only provides a detailed solution for the interfacial adhesion behavior but also provides guidance for the application of adhesion in Micro-Electro-Mechanical Systems (MEMSs). Full article

The speed of sound depends on the structure and material properties of the crystal, such as density and Young’s modulus. On the other hand, from atomistic arguments it is possible to associate Young’s modulus with other material properties. These observations lead to a relationship between binding energy of atoms in a crystal (which is one of the parameters appearing in Mie-Lennard-Jones potential), speed of sound in the longitudinal direction and mass of one atom in the lattice. This subject was addressed by several authors, providing different implementations of this relation. A literature review on this topic is made and the mathematical derivation of the relation is carried out. Applications of this relationship to rare gases, some metals and some rare earths are presented and the results compared to others taken from literature. Full article

An accurate description of short-range interactions among atoms is crucial for simulating irradiation effects in applications related to ion modification techniques. A smooth integration of the Ziegler–Biersack–Littmark (ZBL) potential with the adaptive intermolecular reactive empirical bond-order (AIREBO) potential was achieved to accurately describe the short-range interactions for carbon-based materials. The influence of the ZBL connection on potential energy, force, and various AIREBO components, including reactive empirical bond-order (REBO), Lennard–Jones (LJ), and the torsional component, was examined with configurations of the dimer structure, tetrahedron structure, and monolayer graphene. The REBO component is primarily responsible for the repulsive force, while the LJ component is mainly active in long-range interactions. It is shown that under certain conditions, the torsional energy can lead to a strong repulsive force at short range. Molecular dynamics simulations were performed to study the collision process in configurations of the C-C dimer and bulk graphite. Cascade collisions in graphite with kinetic energies of 1 keV and 10 keV for primary knock-on atoms showed that the short-range description can greatly impact the number of generated defects and their morphology. Full article

Carbon nanotubes filled with organic molecules can serve as chemical nanoreactors. Recent experimental results show that, by introducing cyclic hydrocarbon molecules inside carbon nanotubes, they can be transformed into nanoribbons or inner tubes, depending on the experimental conditions. In this paper, we present our results obtained as a continuation of our previous molecular dynamics simulation work. In our previous work, the initial geometry consisted of independent carbon atoms. Now, as an initial condition, we have placed different molecules inside a carbon nanotube (18,0): C₅H₅ (fragment of ferrocene), C₅, C₅+H₂; C₆H₆ (benzene), C₆, C₆+H₂; C₂₀H₁₂ (perylene); and C₂₄H₁₂ (coronene). The simulations were performed using the REBO-II potential of the LAMMPS software package, supplemented with a Lennard-Jones potential between the nanotube wall atoms and the inner atoms. The simulation proved difficult due to the slow dynamics of the H abstraction. However, with a slight modification of the parameterization, it was possible to model the formation of carbon nanoribbons inside the carbon nanotube. Full article

The adsorption of nitrogen molecules on a (100) tungsten surface has been studied using a new potential energy surface in which long-range interactions are suitably characterized and represented by the Improved Lennard–Jones function. The new potential energy surface is used to carry out molecular dynamics simulations by adopting a semiclassical collisional method that explicitly includes the interaction with the surface phonons. The results of the sticking probability, evaluated as a function of the collision energy, are in good agreement with those obtained in the experiments and improve the already good comparison recently obtained with calculations performed using interactions from the Density Functional Theory method and corrected for long-range van der Waals contributions. The dependence of trapping probability on the surface temperature for a well-defined collision energy has also been investigated. Full article

Complex networks is a growing discipline aimed at understanding large interacting systems. One of its goals is to establish a relation between the interactions of a system and the networks structure that emerges. Taking a Lennard-Jones particle system as an example, we show that when interactions are governed by a potential, the notion of structure given by the physical arrangement of the interacting particles can be interpreted as a binary approximation to the interaction potential. This approximation simplifies the calculation of the partition function of the system and allows to study the stability of the interaction structure. We compare simulated results with those from the approximated partition function and show how the network and system perspective complement each other. With this, we draw a direct connection between the interactions of a molecular system and the network structure it forms and assess the degree to which it describes the system. We conclude by discussing the advantages and limitations of this method for weighted networks, as well as how this concept might be extended to more general systems. Full article

The effectiveness of all antibiotics in the β-lactam group to cure bacterial infections has been impaired by the introduction of the New Delhi Metallo-β-lactamase (NDM-1) enzyme. Attempts have been made to discover a potent chemical as an inhibitor to this enzyme in order to restore the efficacy of antibiotics. However, it has been a challenging task to develop broad-spectrum inhibitors of metallo-β-lactamases. Lack of sequence homology across metallo-β-lactamases (MBLs), the rapidly evolving active site of the enzyme, and structural similarities between human enzymes and metallo-β-lactamases, are the primary causes for the difficulty in the development of these inhibitors. Therefore, it is imperative to concentrate on the discovery of an effective NDM-1 inhibitor. This study used various in silico approaches, including molecular docking and molecular dynamics simulations, to investigate the potential of phytochemicals to inhibit the NDM-1 enzyme. For this purpose, a library of about 59,000 phytochemicals was created from the literature and other databases, including FoodB, IMPPAT, and Phenol-Explorer. A physiochemical and pharmacokinetics analysis was performed to determine possible toxicity and mutagenicity of the ligands. Following the virtual screening, phytochemicals were assessed for their binding with NDM-1using docking scores, RMSD values, and other critical parameters. The docking score was determined by selecting the best conformation of the protein–ligand complex. Three phytochemicals, i.e., butein (polyphenol), monodemethylcurcumin (polyphenol), and rosmarinic acid (polyphenol) were identified as result of pharmacokinetics and molecular docking studies. Furthermore, molecular dynamics simulations were performed to determine structural stabilities of the protein–ligand complexes. Monodemethylcurcumin, butein, and rosmarinic acid were identified as potential inhibitors of NDM-1 based on their low RMSD, RMSF, hydrogen bond count, average Coulomb–Schrödinger interaction energy, and Lennard–Jones–Schrödinger interaction energy. The present investigation suggested that these phytochemicals might be promising candidates for future NDM-1 medication development to respond to antibiotic resistance. Full article

The effect of oscillatory shear deformation on the fatigue life, yielding transition, and flow localization in metallic glasses is investigated using molecular dynamics simulations. We study a well-annealed Cu-Zr amorphous alloy subjected to periodic shear at room temperature. We find that upon loading for hundreds of cycles at strain amplitudes just below a critical value, the potential energy at zero strain remains nearly constant and plastic events are highly localized. By contrast, at strain amplitudes above the critical point, the plastic deformation is gradually accumulated upon continued loading until the yielding transition and the formation of a shear band across the entire system. Interestingly, when the strain amplitude approaches the critical value from above, the number of cycles to failure increases as a power-law function, which is consistent with the previous results on binary Lennard-Jones glasses. Full article

Random walks (RWs) have been important in statistical physics and can describe the statistical properties of various processes in physical, chemical, and biological systems. In this study, we have proposed a self-interacting random walk model in a continuous three-dimensional space, where the walker and its previous visits interact according to a realistic Lennard-Jones (LJ) potential $u_{LJ}\left(r\right)=\epsilon \left[{\left(r_0/r\right)}^{12}-2{\left(r_0/r\right)}^6\right]$. It is revealed that the model shows a novel globule-to-helix transition in addition to the well-known coil-to-globule collapse in its trajectory when the temperature decreases. The dependence of the structural transitions on the equilibrium distance $r_0$ of the LJ potential and the temperature T were extensively investigated. The system showed many different structural properties, including globule–coil, helix–globule–coil, and line–coil transitions depending on the equilibrium distance $r_0$ when the temperature T increases from low to high. We also obtained a correlation form of k_BT_c = λε for the relationship between the transition temperature T_c and the well depth $\epsilon$, which is consistent with our numerical simulations. The implications of the random walk model on protein folding are also discussed. The present model provides a new way towards understanding the mechanism of helix formation in polymers like proteins. Full article

In this paper, the authors present the results of modeling the movement of three methane molecules into a closed carbon nanotube. The main approach in this work is to model the interaction between methane molecules and the structure of a nanocapsule, which is a single-walled closed carbon nanotube. Descriptively, the interaction is represented using molecular dynamics approaches and the Lennard-Jones potential. Methane molecules in this model are material points corresponding to the centers of mass of the molecules. To solve the resulting equations of motion of molecules inside the nanotube, the classical Runge–Kutta method is used. Full article