General Force Research Articles

Thermophysical properties of polyethylene glycol oligomers via molecular dynamics simulations.

Polyethylene glycol (PEG) is a versatile chemical with numerous applications in various fields, including biomedical research, pharmaceutical development, and industrial manufacturing. Molecular dynamics (MD) is a powerful tool for investigating the thermophysical properties of PEG molecules. In this study, we employ the General AMBER force field (GAFF) to perform MD simulations on various PEG oligomers, focusing on the calculation of density, self-diffusion coefficients, shear viscosity, and thermal conductivity. The results demonstrate excellent agreement with experimental data, where GAFF outperforms other force fields in reproducing thermophysical properties. For a PEG tetramer, the GAFF force field reproduces experimental data within 5% for the density, 5% for the diffusion coefficient, and 10% for the viscosity. In comparison, the OPLS force field displays significant deviations exceeding 80% for the diffusion coefficient and 400% for the viscosity. A detailed analysis of partial charge distributions and dihedral angles reveals that they significantly impact the structural behavior of PEG oligomers. The findings highlight the GAFF force field as one of the most accurate and reliable options for simulating systems with PEGs.

Hangolható asztal optimális hangolásának kísérleti ellenőrzése és kompatibilis munkadarab tervezése

The tuneable clamping table was designed to attenuate chatter vibrations in the finishing operations of thin walled machining. This is achieved by the tuning of the frequency and damping parameters of the table’s dominant mode. The frequency is actively tuned by a rotary spring, while the damping can be changed passively, using eddy current modules. This study aims to develop a compatible dummy workpiece for the table and experimentally validate the corresponding optimal tuning parameters both for general harmonic forcing and in the case of a milling operation.

Computational predictions of interfacial tension, surface tension, and surfactant adsorption isotherms.

All-atom (AA) molecular dynamics (MD) simulations are employed to predict interfacial tensions (IFT) and surface tensions (ST) of both ionic and non-ionic surfactants. The general AMBER force field (GAFF) and variants are examined in terms of their performance in predicting accurate IFT/ST, γ, values for chosen water models, together with the hydration free energy, ΔGhyd, and density, ρ, predictions for organic bulk phases. A strong correlation is observed between the quality of ρ and γ predictions. Based on the results, the GAFF-LIPID force field, which provides improved ρ predictions is selected for simulating surfactant tail groups. Good γ predictions are obtained with GAFF/GAFF-LIPID parameters and the TIP3P water model for IFT simulations at a water-triolein interface, and for GAFF/GAFF-LIPID parameters together with the OPC4 water model for ST simulations at a water-vacuum interface. Using a combined molecular dynamics-molecular thermodynamics theory (MD-MTT) framework, a mole fraction of C12E6 molecule of 1.477 × 10-6 (from the experimental critical micelle concentration, CMC) gives a simulated surface excess concentration, ΓMAX, of 76 C12E6 molecules at a 36 nm2 water-vacuum surface (3.5 × 10-10 mol cm-2), which corresponds to a simulated ST of 35 mN m-1. The results compare favourably with an experimental ΓMAX of C12E6 of 3.7 × 10-10 mol cm-2 (80 surfactants for a 36 nm2 surface) and experimental ST of C12E6 of 32 mN m-1 at the CMC.

Contribution of FDI, fiscal policy, and labor force on inequality and economic growth: A case study in South Sulawesi, Indonesia

South Sulawesi Province faces a significant problem: economic growth that has not been inclusive. This study analyzes the relationship between foreign investment contribution, fiscal policy, and labor force to inclusive economic growth in South Sulawesi, Indonesia. The results of this study show two relationships, namely direct and indirect relationships. Judging from the direct influence. First, FDI and local native income positively affect the level of inequality. However, in contrast to general allocation funds and labor force variables, each negatively affects inequality. Meanwhile, FDI, general allocation funds, and local original revenues positively affect economic growth. However, in contrast to the variables labor force and inequality, each negatively affects the inequality level. When viewed from its indirect influence, FDI, general allocation funds, labor force, and local native income each positively impact economic growth through levels of inequality. The implication of this study is the importance of governments allocating FDI investments for infrastructure development that supports inclusive growth.

Study on VIV Behavior of Two 5:1 Rectangular Cylinders in Tandem Based on Correlation Analysis

To investigate the vortex-induced vibration (VIV) characteristics of two rectangular cylinders with a width-to-depth ratio of 5:1 in a tandem arrangement, sectional model wind tunnel tests that measure vibration responses and pressure distributions simultaneously were adopted. The ratio of the spacing between the cylinders to its width is 1.2. The analyses were performed considering VIV responses as well as the distribution characteristics of mean and rms pressure coefficients. Additionally, the time-frequency domain statistical parameters like correlation and contribution coefficients, phase lags between distributed and general vortex excited forces (VEFs), and amplitudes of VEF coefficients at predominant frequencies were calculated to analyze the physical VIV mechanism of two 5:1 rectangular cylinders in tandem. This study indicates that the influence of incidence angles on the dynamic responses is notable; the contribution of the distributed VEFs acting on the trailing surface of the upstream cylinder and the leading surface of the downstream one is significant to VIVs of the cylinders from wind pressure distribution characteristics and correlation analyses.

Rigid flexible coupling contact mechanism for oral and maxillofacial skin and soft tissues

Background and Objectives:The existing medical clinical treatment institutions mostly use rigid structures to come into contact with flexible skin. The rigid flexible coupled contact biomechanical model for the skin is the first step that urgently needs to be considered in the process of medical clinical operations. However, there has been currently no effective biomechanical contact model available. Methods:Based on the principle of elastic interface deformation, the basic biomechanical characteristics of oral and maxillofacial skin and soft tissues were analyzed to address the unknown mechanism of rigid body and maxillofacial contact in oral imaging operations. A nonlinear characterization method for the mechanical properties of oral and maxillofacial skin soft tissues was proposed by deriving a general contact force model that takes into account energy dissipation. However, the problem of the inability to obtain analytical solutions for the parameters of the dynamic model exists. It is necessary to perform particle swarm parameter identification on different nonlinear contact models and verify the accuracy of the algorithm through numerical simulation. A maxillofacial contact experiment was conducted to verify the operation process of an oral imaging robot. Results:After experimental analysis, it was found that the comprehensive average error between the model and the actual contact force was 0.13325 N. The absolute error of the maximum deformation displacement was below 0.18 N, which verified the effectiveness and safety of the contact model in the contact process of the oral imaging robot system. Conclusions:The results indicate that the output force of the model has been in good agreement with the actual contact force.

Intermolecular Non-Bonded Interactions from Machine Learning Datasets

Accurate determination of intermolecular non-covalent-bonded or non-bonded interactions is the key to potentially useful molecular dynamics simulations of polymer systems. However, it is challenging to balance both the accuracy and computational cost in force field modelling. One of the main difficulties is properly representing the calculated energy data as a continuous force function. In this paper, we employ well-developed machine learning techniques to construct a general purpose intermolecular non-bonded interaction force field for organic polymers. The original ab initio dataset SOFG-31 was calculated by us and has been well documented, and here we use it as our training set. The CLIFF kernel type machine learning scheme is used for predicting the interaction energies of heterodimers selected from the SOFG-31 dataset. Our test results show that the overall errors are well below the chemical accuracy of about 1 kcal/mol, thus demonstrating the promising feasibility of machine learning techniques in force field modelling.

Minimal Peptoid Dynamics Inform Self-Assembly Propensity.

Peptoids are structural isomers of natural peptides, with side chain attachment at the amide nitrogen, conferring this class of compounds with the ability to access both cis and trans ω torsions as well as an increased diversity of ψ/φ states with respect to peptides. Sampling within these dimensions is controlled through side chain selection, and an expansive set of viable peptoid residues exists. It has been shown recently that "minimal" di- and tripeptoids with aromatic side chains can self-assemble into highly ordered structures, with size and morphological definition varying as a function of sequence pattern (e.g., XFF and FXF, where X = a nonaromatic peptoid monomer). Aromatic groups, such as phenylalanine, are regularly used in the design of minimal peptide assemblers. In recognition of this, and to draw parallels between these compounds classes, we have developed a series of descriptors for intramolecular dynamics of aromatic side chains to discern whether these dynamics, in a preassembly condition, can be related to experimentally observed nanoscale assemblies. To do this, we have built on the atomistic peptoid force field reported by Weiser and Santiso (CGenFF-WS) through the rigorous fitting of partial charges and the collation of Charmm General Force Field (CGenFF) parameters relevant to these systems. Our study finds that the intramolecular dynamics of side chains, for a given sequence, is dependent on the specific combination of backbone ω torsions and that homogeneity of sampling across these states correlates well with the experimentally observed ability to assemble into nanomorphologies with long-range order. Sequence patterning is also shown to affect sampling, in a manner consistent for both tripeptoids and tripeptides. Additionally, sampling similarities between the nanofiber forming tripeptoid, Nf-Nke-Nf in the cc state, and the nanotube forming dipeptide FF, highlight a structural motif which may be relevant to the emergence of extended linear assemblies. To assess these properties, a variety of computational approaches have been employed.

Fiber-Integrated Force Sensor using 3D Printed Spring-Composed Fabry-Perot Cavities with a High Precision Down to Tens of Piconewton.

Developing microscale sensors capable of force measurements down to the scale of piconewtons is of fundamental importance for a wide range of applications. To date, advanced instrumentations such as atomic force microscopes and other specifically developed micro/nano-electromechanical systems face challenges such as high cost, complex detection systems and poor electromagnetic compatibility. Here, it presents the unprecedented design and 3D printing of general fiber-integrated force sensors using spring-composed Fabry-Perot cavities. It calibrates these microscale devices employing varied-diameter m-scale silica particles as standard weights. The force sensitivity and resolution reach values of (0.436 ± 0.007) nmnN-1 and (40.0 ± 0.7) pN, respectively, which are the best resolutions among all fiber-based nanomechanical probes so far. It also measured the non-linear airflow force distributions produced from a nozzle with an orifice of 2 m, which matches well with the full-sized simulations. With further customization of their geometries and materials, it anticipates the easy-to-use force probe can well extend to many other applications such as air/fluidic turbulences sensing, micro-manipulations, and biological sensing.

Development of CHARMM compatible force field parameters and molecular dynamics simulations for the pesticide flupyradifurone.

Flupyradifurone (FLU) is a novel butenolide insecticide with partial agonist activity for insect nicotinic acetylcholine receptors. Its safety for non-target organisms has been questioned in the literature, despite initial claims of its harmlessness. Detailed understanding of its toxicity and related molecular mechanisms remain under discussion. Thus, in this work, an optimized set of CHARMM compatible parameters for FLU is presented. CHARMM General Force Field program was used as a starting point while the non-bonded and bonded parameters were adjusted and optimized to reproduce MP2/6-31G(d) accuracy level results. For the validity assessment of these parameters, infrared spectrum, water-octanol partition coefficient, and normal modes were computed and compared to experimental values found in the literature. Several MD simulations of FLU in water and FLU in complex with an acetylcholine-binding protein were performed to estimate the ability of the optimized parameters to correctly describe its torsional space and reproduce observed crystallographic trends respectively.

Viewing second-order phase transitions as a metaphor for river bifurcations

The Earth's landscape hosts a variety of patterns resulting from the interaction between a sediment-carrying fluid and an erodible boundary. Here, the morphodynamics of river bifurcations is interpreted as a second-order phase transition. A consolidated one-dimensional bifurcation model is re-examined in the light of classical Landau theory of critical phenomena. The transition from a balanced to an unbalanced flux partition is described in terms of an order parameter. The equilibrium states of the system are shown to be minima of a morphodynamic potential function. Finally, the role of a generic external forcing is investigated. A threshold value of the forcing is shown to set bounds separating two different morphodynamic responses to allogenic and autogenic dynamics.

Concealed Carry, Agency, and Attention in a Technocratic Context

Standard discussions about guns as technologies focus on whether guns influence free choices or mediate sociocultural dynamics related to race, class, or gender. This article resituates these questions in a broader context by approaching guns from the perspective of Pope Francis’s critique of the “technocratic paradigm” as a general sociocultural force in its own right. Specifically, the article examines how concealed-carry armed citizenship participates in or resists the technocratic construal of the world as raw material to be freely manipulated for the utility and security of an unsituated autonomous subject. While armed citizenship clearly participates in the technocratic paradigm in its consistent depiction of potential assailants as irrational outsiders to be controlled through technical force, it also appears to resist that paradigm in its active search for meaningful skilled agency and in its potentially world-disclosing practice of “situational awareness.” Closer reflection reveals that in both latter cases concealed carry is caught in a cycle of failed resistance. Its search for skilled agency is thwarted by a myth of unsituated responsibility that undercuts the sociocultural conditions for such agency. Meanwhile, situational awareness fails to disclose the world (and resist distorting influences) because it anticipates for actions one cannot regularly practice.

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions.

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

SwissParam 2023: A Modern Web-Based Tool for Efficient Small Molecule Parametrization.

Most steps of drug discovery are now routinely supported and accelerated by computer-aided drug design tools. Among them, structure-based approaches use the three-dimensional structure of the targeted biomacromolecule as a major source of information. When it comes to calculating the interactions of small molecules with proteins using the equations of molecular mechanics, topologies, atom typing, and force field parameters are required. However, generating parameters for small molecules remains challenging due to the large number of existing chemical groups. The SwissParam web tool was first released in 2011 with the aim of generating parameters and topologies for small molecules based on the Merck molecular force field (MMFF) while being compatible with the CHARMM22/27 force field. Here, we present an updated version of SwissParam, providing various new features, including the possibility to setup covalent ligands. Molecules can now be imported from different file formats or via a molecular sketcher. The MMFF-based approach has been updated to provide parameters and topologies compatible with the CHARMM36 force field. An option was added to generate small molecule parametrizations following the CHARMM General Force Field via the multipurpose atom-typer for CHARMM (MATCH) approach. Additionally, SwissParam now generates information on probable alternative tautomers and protonation states of the query molecule so that the user can consider all microspecies relevant to its compound. The new version of SwissParam is freely available at www.swissparam.ch and can also be accessed through a newly implemented command-line interface.

Mechanism Analysis and Property Prediction of Extended Surfactants Based on the Respectively Optimized Force Field.

Extended surfactants represent a novel class of anionic-nonionic surfactants with exceptional performance and unique application value in chemically enhanced oil recovery. Although molecular dynamics (MD) simulations can efficiently screen these surfactants, the current research is limited. Here, it is proven for the first time that existing generic force fields (GAFF and CHARMM) cannot accurately describe extended surfactants, and traditional approaches are insufficient for obtaining precise charge parameters. The concept of the respectively optimized force field (ROFF) with the purports of specialization and accuracy is proposed to construct high-accuracy models for MD simulations, and a new approach is developed to simulate the interface model. By combining the newly specialized alkane model, ROFF-based surfactant models, and the innovative simulation protocol, high accuracy and reliability can be obtained in predicting hydration free energies, minimum of area per molecule, and critical micelle concentration of extended surfactants. Key properties of the newly designed extended surfactants in conventional oil-water interfaces and oil reservoir environments are comprehensively predicted by using advanced analytical and characterization methods. Furthermore, the more rigorous mechanism underlying the special amphiphilicity of the extended surfactant is revealed, potentially offering significant improvements over previous empirical perspectives.

Bacterial bioconvection confers context-dependent growth benefits and is robust under varying metabolic and genetic conditions.

Microbes often respond to environmental cues by adopting collective behaviors-like biofilms or swarming-that benefit the population. During "bioconvection," microbes gather in dense groups and plume downward through fluid environments, driving flow and mixing on the scale of millions of cells. Though bioconvection was observed a century ago, the effects of differing physical and chemical inputs and its potential selective advantages for different species of microbes remain largely unexplored. In Bacillus subtilis, vertical oxygen gradients that originate from air-liquid interfaces create cell-density inversions that drive bioconvection. Here, we develop Escherichia coli as a complementary model for the study of bioconvection. In the context of a still fluid, we found that motile and chemotactic genotypes of both E. coli and B. subtilis bioconvect and show increased growth compared to immotile or non-chemotactic genotypes, whereas in a well-mixed fluid, there is no growth advantage to motility or chemotaxis. We found that fluid depth, cell concentration, and carbon availability affect the emergence and timing of bioconvective patterns. Also, whereas B. subtilis requires oxygen gradients to bioconvect, E. coli deficient in aerotaxis (Δaer) or energy-taxis (Δtsr) still bioconvects, as do cultures that lack an air-liquid interface. Thus, in two distantly related microbes, bioconvection may confer context-dependent growth benefits, and E. coli bioconvection is robustly elicited by multiple types of chemotaxis. These results greatly expand the set of physical and metabolic conditions in which this striking collective behavior can be expected and demonstrate its potential to be a generic force for behavioral selection across ecological contexts. IMPORTANCE Individual microorganisms frequently move in response to gradients in their fluid environment, with corresponding metabolic benefits. At a population level, such movements can create density variations in a fluid that couple to gravity and drive large-scale convection and mixing called bioconvection. In this work, we provide evidence that this collective behavior confers a selective benefit on two distantly related species of bacteria. We develop new methods for quantifying this behavior and show that bioconvection in Escherichia coli is surprisingly robust to changes in cell concentration, fluid depth, interface conditions, metabolic sensing, and carbon availability. These results greatly expand the set of conditions known to elicit this collective behavior and indicate its potential to be a selective pressure across ecological contexts.

Symmetry and scaling in one-dimensional compressible two-phase flow

Investigations of shock compression of heterogeneous materials often focus on the shock front width and overall profile. The number of experiments required to fully characterize the dynamic response of a material often belie the structure–property relationships governing these aspects of a shock wave. Recent observations measured a pronounced shock-front width on the order of 10 s of ns in particulate composites. Here, we focus on particulate composites with disparate densities and investigate whether the mechanical interactions between the phases are adequate to describe this emergent behavior. The analysis proceeds with a general Mie–Grüneisen equation of state for the matrix material, a general drag force law with general power-law scaling for the particle-matrix coupling of the phases, and a volume fraction-dependent viscosity. Lie group analysis is applied to one-dimensional hydrodynamic flow equations for the self-consistent interaction of particles embedded in a matrix material. The particle phase is characterized by a particle size and volume fraction. The Lie group analysis results in self-similar solutions reflecting the symmetries of the flow. The symmetries lead to well-defined scaling laws, which may be used to characterize the propagation of shock waves in particle composites. An example of the derived scaling laws for shock attenuation and rise time is shown for experimental data on shock-driven tungsten-loaded polymers. A key result of the Lie analysis is that there is a relationship between the exponents characterizing the form of the drag force and the exponent characterizing the shock velocity and its attenuation in a particulate composite. Comparison to recent experiments results in a single exponent that corresponds to a conventional drag force.

Upgrading of the general AMBER force field 2 for fluorinated alcohol biosolvents: A validation for water solutions and melittin solvation.

The standard GAFF2 force field parameterization has been refined for the fluorinated alcohols 2,2,2-trifluoroethanol (TFE), 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP), and 1,1,1,3,3,3-hexafluoropropan-2-one (HFA), which are commonly used to study proteins and peptides in biomimetic media. The structural and dynamic properties of both proteins and peptides are significantly influenced by the biomimetic environment created by the presence of these cosolvents in aqueous solutions. Quantum mechanical calculations on stable conformers were used to parameterize the atomic charges. Different systems, such as pure liquids, aqueous solutions, and systems formed by melittin protein and cosolvent/water solutions, have been used to validate the new models. The calculated macroscopic and structural properties are in agreement with experimental findings, supporting the validity of the newly proposed models.

Tailored nonlinear stiffness and geometric damping: Applied to a bistable vibration absorber

A novel device is proposed to obtain arbitrary restoring force characteristics and nonlinear geometric damping. It consists of linear springs and dampers that are compressed along a track. The obtained nonlinear damping and stiffness law depend on the track’s shape. The device is then applied to obtain a nonlinear energy sink (NES) to damp the vibrations of a host system. Both the case of transient vibrations, induced by shock loads, and sustained vibrations, induced by harmonic loads, are studied. For arbitrary stiffness and damping, slow flow dynamics and slow invariant manifolds (SIMs) are derived by applying harmonic balancing and multiple timescales techniques. Under transient vibrations, two performance measures are derived from the SIM, the relative residual energy and the pumping time, and are found for generic nonlinear spring force and nonlinear geometric damping. For sustained vibrations, a load-dependent frequency response (FR) is derived from the SIMs. This FR predicts the occurrence of the efficient strongly modulated responses but also the occurrence of the unfavorable detached responses called isolas, where the NES fails to mitigate and even amplifies vibrations.This research investigates the performance of a conventional cubic NES and a bistable NES (BNES) with nonlinear damping obtained from the proposed device. Especially the BNES with nonlinear damping shows attractive properties, with a high degree of robustness over a wide energy range and a low vibration threshold under transient loading. Under harmonic loads, the nonlinear damping helps reduce the effect of isolas. A novel tuning methodology is proposed to avoid isolas for a range of load magnitudes. The new device opens up a whole range of possibilities regarding energy dissipation through nonlinear damping.

Effects of species and moisture content on the behaviour of solid wood under impact

The article's main aim is to assess the effects of species and moisture content (MC) on the behaviour of solid wood material under the low velocity of impact and present a pattern for predicting loading vs time curves for these species in different moisture levels. Three groups of samples (300 × 20 × 20 mm) were made from beech, oak, and spruce wood. Each group was subdivided into two groups with low moisture content (LMC) level (10–12%) and high moisture content (HMC) level (40–60%). A drop-weight impact machine did the tests, and high-speed cameras recorded the lateral specimens' surface during the impact. The digital image correlation technique (DIC) determined the strain pattern and the deflection. The timing of the crack initiation was also observed. Also, the force–time charts, the maximum force required for crack initiation, the work needed for crack initiation, and the total work required for the breakage of every specimen were gathered. A general force–time pattern with five identifiable steps was determined for each group. It turned out that the maximum deflection and longitudinal tensile strain of the beams up to crack initiation increase with increased moisture content while maximum force decreases. Unlike beech, the required work for rupture of HMC samples of oak and spruce is higher than LMC group.