Search Results (75)

Conventional cooperative control methods for multi-AUV systems typically rely on quasi-steady hydrodynamic assumptions and do not explicitly account for time-varying uncertainties in ocean dynamics. In addition, controller parameters are often tuned empirically. As a result, under complex disturbed flow fields and communication constraints, AUV swarms are prone to group fragmentation and reduced polarization, which undermines stable cooperative navigation. To address these limitations, we propose a double-gyre-flow-optimized autonomous underwater vehicle swarm (DGF-OAS) model for coordinated operations in time-varying flow fields. The proposed model incorporates a heading-aware graph attention mechanism to adaptively adjust adjacency weights among agents with different roles. It further integrates the Lennard–Jones potential to preserve safe inter-vehicle spacing and embeds a periodically varying double-gyre flow field to characterize ocean disturbances. Bayesian optimization is then employed to automatically identify suitable weights for the alignment and attraction–repulsion terms, thereby improving swarm cohesion and environmental adaptability. Simulation results demonstrate that, under flow-field disturbances, DGF-OAS achieves group polarization of up to 96%, reduces the average task completion time by 15.84% compared with the baseline model, and attains a task completion rate of 97%, significantly outperforming the compared methods. These findings indicate that the proposed approach exhibits strong adaptability and stability in complex environments and offers an effective solution for AUV swarm control. Full article

Ice adhesion on exposed structures remains a major operational challenge, motivating the search for passive, material-based anti-icing strategies. Molecular dynamics offers a controlled way to investigate ice–surface interactions beyond the limits of experimental setups. In this work, we develop a simulation framework to model the impact of solid hexagonal ice droplets on metallic substrates. Ice impacts are simulated across a range of velocities (10–120 m/s), temperatures (120–250 K), and face-centred cubic surface materials (gold, copper, silver, aluminum, and nickel). Using LAMMPS, mW water force-field, EAM/Alloy metal potentials, and Lennard-Jones water–surface interactions, we quantify phase evolution through angular order parameter and quasi-liquid layer measurements, complemented by the CHILL+ algorithm in OVITO. By isolating all external factors, we show that melting increases with velocity and temperature and correlates with substrate properties: metals with high thermal diffusivity and low Young’s modulus tend to decrease post-collision ice melting. The ratio of the former to the latter, a derived index of merit Υ, significantly correlates with melting percentage and identifies silver as the most effective anti-ice material examined. Statistical analyses strongly suggest that these surface properties influence interfacial melting, supporting the use of this modelling framework for screening and designing anti-icing materials. Full article

To investigate the structural characteristics of Ir_n clusters (n = 9–30) and their interaction with NH₃, the CALYPSO structure-prediction method was employed to identify the lowest-energy configurations. The Lennard–Jones potential was then used to compute the binding energy and average binding energy, thereby evaluating size-dependent stability. The results show that Ir_n clusters evolve from relatively open motifs to compact three-dimensional frameworks as n increases. Meanwhile, the average binding energy increases overall and exhibits several locally stable size regions, indicating a pronounced size effect. Based on slab and cluster models, NH₃ adsorption was further examined on the Ir₁₃ cluster as a representative system due to its high structural stability as a “magic-number” cluster. The calculated adsorption energies demonstrate that the Ir₁₃ cluster exhibits substantially stronger adsorption than the bulk Ir surface, with low-coordinated Ir atoms playing a key role in strengthening the interaction and enhancing adsorption activity. Adsorption-configuration analysis indicates that NH₃ preferentially binds to active surface sites via the N lone pair. These findings clarify the relationship between structural stability and adsorption performance of Ir clusters and provide theoretical support for Ir-based materials in NH₃ catalytic conversion and high-sensitivity gas detection, and offer insights relevant to improving NH₃ monitoring in underground coal mine environments. Full article

Handling dispersion of casein powders in water is widely encountered in the milk industry. However, in silico prediction of the apparent viscosity of these colloidal dispersions is not an easy task, especially when these micellar casein suspensions are highly concentrated, as in hyper-protein milk beverages, which are experiencing exponential market growth. In this work, Coarse-Grained (CG) models using Lennard-Jones potentials to model interactions were built for simulating rheological properties of colloidal micellar casein dispersions (native and demineralized). In a first approach, a polydisperse explicit CG model was developed. For this polydisperse CG model, the representation chain was composed of four large smooth spheres of different sizes mimicking the real distribution of casein colloids. The CG simulation results were validated by comparison with experimental rheological data for native colloidal casein dispersions. Both in-house experimental results and available data found in the literature were used for this purpose, covering a wide range of casein concentrations ([10 g/L–200 g/L], [8–20%] corresponding to casein concentration, colloid volume fraction and solid/liquid volume fraction, respectively). In a second approach, a simplified model using a monodisperse CG model was developed. This simplified model only included one type of soft sphere and was found to preserve the accuracy of the rheological prediction. Finally, a monodisperse CG model was set up to predict the behavior of demineralized micellar casein dispersions, for which a decrease in the average size of the micelle size distribution is observed when demineralization occurs. For all models, the comparison between the predicted and experimental rheological behavior is fully satisfactory, proving that the CG models proposed for casein-based micellar dispersions are physically well founded and that the proposed simplified representation chain, based on micelle size observation, makes sense. Full article

The interaction between water and metallic interfaces is crucial in many fields, and accurate modeling requires good parametrizations using reference data. In classical molecular dynamics (MD), an important part of this interaction is described using the Lennard–Jones (LJ) potential. However, previously reported LJ parameters are not always optimal for capturing the metal/water interactions observed in ab initio descriptions such as density functional theory (DFT). Therefore, well-tailored LJ parameters are necessary to improve the description of water structuring metals in classical MD. The usual route for obtaining LJ parameters involves energetic analysis, where the energies of various structures are obtained via DFT calculations and then matched with the energies obtained using the LJ potentials by varying the sigma/epsilon parameters. Here, we show a different approach to fit LJ parameters for metal/water interactions, based on structural analysis. We report several classical MD simulations for gold/water, varying the sigma/epsilon parameters, comparing the resulting water structuring with that obtained using DFT. Additionally, we test these parameters in quantum mechanics/molecular mechanics (QM/MM) MD simulations, where electrostatic interactions are enabled. Our results demonstrate that the proposed approach can improve the LJ parameters reported in the literature and potentially develop parameters for more complex systems where the water structure above metallic surfaces plays a significant role. Finally, within this proposed approach, the water density profile obtained in hybrid QM/MM calculations, where water is treated as MM at a substantially reduced cost, closely matches the description it would have if treated as QM. Full article

This study provides a comprehensive overview of research and advancements on carbon materials with regard to practical targets for hydrogen storage in terms of gravimetric and volumetric capacities. For the sake of clarity, only the most relevant references on hydrogen storage by adsorption are presented, although the study was conducted in the same exhaustive manner as the one initially carried out by Anne C. Dillon and Michael J. Heben in 2001 with a particular emphasis on emerging technologies and potential applications in various sectors. This study also focuses on the importance of carbon-based materials with high specific surface areas and porous structures optimised to maximise adsorption—including at high pressure—while primarily limiting references herein to experimentally validated results. It therefore offers insights into the porous materials, as well as the methodologies—including a fully comprehensive and so-far proven highly transferable intermolecular hydrogen model combining van der Waals’s and Coulomb’s forces—used to improve hydrogen solid storage efficiency. Full article

Detailed knowledge regarding the thermophysical properties and electrical conductivity of the combustion products derived from solid propellants is essential for the optimized design and operation of solid-fuel rocket engines employing magnetohydrodynamic drive technology. However, the high-temperature and high-pressure environment prevailing during rocket operation makes the experimental measurement of these characteristics extremely difficult, while the ionization reactions obtained by adding ionization seeds containing cesium to solid propellants for increasing the electrical conductivity of gaseous combustion products makes the theoretical calculation of these characteristics extremely problematic as well. The present work addresses these issues by constructing a minimum Gibbs free energy constraint function in conjunction with the Debye–Hückel correction under the condition of ionization to calculate the equilibrium components of combustion products. The obtained equilibrium components are then applied in conjunction with Lennard–Jones potential energy theory and the Champan–Enskog framework to approximately calculate the specific heat, viscosity coefficient, and thermal conductivity of propellant gases over a wide range of temperatures and pressures. The Kantrowitz model is proposed to solve the electrical conductivity of combustion products. Finally, the accuracy of the numerical calculations is validated through the Langmuir probe experiment. The discrepancy between calculated and measured electron density decreases with increasing temperature and remains within 5% when the combustion product temperature exceeds approximately 1800 K. The validity of the proposed framework is demonstrated by examining the effects of temperature, pressure, and ionization seed content on the thermophysical properties and electrical conductivity of the combustion products derived from tri-base solid propellant with cesium atoms employed as ionization seeds. Full article

We derive an explicit analytic expression for the first quantum correction to the second virial coefficient of a d-dimensional fluid whose particles interact via the generalized Lennard-Jones $(2n,n)$ potential. By introducing an appropriate change of variable, the correction term is reduced to a single integral that can be evaluated in closed form in terms of parabolic cylinder or generalized Hermite functions. The resulting expression compactly incorporates both dimensionality and stiffness, providing direct access to the low- and high-temperature asymptotic regimes. In the special case of the standard Lennard-Jones fluid ($d=3$, $n=6$), the formula obtained is considerably more compact than previously reported representations based on hypergeometric functions. The knowledge of this correction allows us to determine the first quantum contribution to the Boyle temperature, whose dependence on dimensionality and stiffness is explicitly analyzed, and enables quantitative assessment of quantum effects in noble gases such as helium, neon, and argon. Moreover, the same methodology can be systematically extended to obtain higher-order quantum corrections. Full article

Lennard-Jones clusters, while an easy system, have a significant number of non equivalent configurations that increases rapidly with the number of atoms in the cluster. Here, we aim at determining the cluster partition function; we use the nested sampling algorithm, which transforms the multidimensional integral into a one-dimensional one, to perform this task. In particular, we use the nested_fit program, which implements slice sampling as search algorithm. We study here the 7-atom and 36-atom clusters to benchmark nested_fit for the exploration of potential energy surfaces. We find that nested_fit is able to recover phase transitions and find different stable configurations of the cluster. Furthermore, the implementation of the slice sampling algorithm has a clear impact on the computational cost. Full article

The second virial coefficient (SVC) of the Lennard-Jones fluid is a cornerstone of molecular theory, yet its calculation has traditionally relied on the complex integration of the pair potential. This work introduces a fundamentally different approach by reformulating the problem in terms of ordinary differential equations (ODEs). For the classical component of the SVC, we generalize the confluent hypergeometric and Weber–Hermite equations. For the first quantum correction, we present entirely new ODEs and their corresponding exact-analytical solutions. The most striking result of this framework is the discovery that these ODEs can be transformed into Schrödinger-like equations. The classical term corresponds to a harmonic oscillator, while the quantum correction includes additional inverse-power potential terms. This formulation not only provides a versatile method for expressing the virial coefficient through a linear combination of functions (including Kummer, Weber, and Whittaker functions) but also reveals a profound and previously unknown mathematical structure underlying a classical thermodynamic property. Full article

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