We present the coupling of two frameworks -- pseudo-open boundary simulation method known as constant potential Molecular Dynamics simulations (C$\mu$MD), combined with QMMD calculations to describe properties graphene electrodes in contact electrolytes. The resulting C$\mu$QMMD model was then applied three ionic solutions (LiCl, NaCl and KCl water) at bulk solution concentrations ranging from 0.5 M up 6 a charged electrode. new approach we are describing here provides protocol control...

The wetting properties of a liquid in contact with solid are commonly described by Young’s equation, which defines the relationship between angle made fluid droplet onto surface and interfacial different interfaces involved. When modeling such systems, several assumptions usually to determine this contact, as completely rigid or use tension at interface instead free energy. In work, we perform molecular dynamics simulations Lennard-Jones crystal compare angles measured from simulation those...

Single-use bioreactors (SUBs) are revolutionizing biotechnology and biopharmaceutical manufacturing by offering cost-efficient, flexible, scalable alternatives to traditional reusable systems. These bioreactors, made from disposable pre-sterilized materials, streamline cell cultivation for biological production while minimizing the need complex cleaning sterilization. A critical aspect of SUB performance lies in optimizing hydrodynamic parameters flow field, power consumption, mixing time,...

One of the most common processes to produce polymer nanoparticles is solvent-displacement method, in which dissolved a "good" solvent and solution then mixed with an "anti-solvent". The processability therefore determined by its structural transport properties solutions pure solvents at intermediate compositions. In this work, we focus on poly-ε-caprolactone (PCL) biocompatible that finds widespread application pharmaceutical biomedical fields, performing full atomistic molecular dynamics...

The geometry optimization of a water molecule with novel type energy function called FFLUX is presented, which bypasses the traditional bonded potentials. Instead, topologically-partitioned atomic energies are trained by machine learning method kriging to predict their IQA for previously unseen molecular geometry. Proof-of-concept that FFLUX's architecture suitable rigorously demonstrated. It found accurate models can optimize 2000 distorted geometries within 0.28 kJ mol-1 corresponding ab...

We present a simple hybrid model for macromolecules where the single molecules are modelled with both atoms and coarse-grained beads. apply our approach to two different polymer melts, polystyrene polyethylene, which potential has been developed using iterative Boltzmann inversion procedure. Our results show that it is possible couple potentials without modifying them mixed preserves local global structure of melts in each case presented. The degree resolution molecule seems not affect...

The machine learning method kriging is an attractive tool to construct next-generation force fields. Kriging can accurately predict atomistic properties, which involves optimization of the so-called concentrated log-likelihood function (i.e., fitness function). difficulty this problem quickly escalates in response increase either number dimensions system considered or size training set. In article, we demonstrate and compare use two search algorithms, namely, particle swarm (PSO)...

FFLUX is a novel force field based on quantum topological atoms, combining multipolar electrostatics with IQA intraatomic and interatomic energy terms. The program FEREBUS calculates the hyperparameters of models produced by machine learning method kriging. Calculation kriging (θ p) requires optimization concentrated log-likelihood . uses Particle Swarm Optimization (PSO) Differential Evolution (DE) algorithms to find maximum PSO DE are two heuristic that each use set particles or vectors...

Even though the study of interfacial phenomena can be traced back to Laplace and was given a solid thermodynamic foundation by Gibbs, it appears that some concepts relations among them are still causing confusion debates in literature, particularly for interfaces involving solids. In particular, definitions tension, free energy, stress relationships between sometimes lack clarity, authors even question their validity. So far, about these relationships, particular Shuttleworth equation, have...

The numerical calculation of the properties interface between different materials or phases same material has always been an important problem due to insight it can bring into understanding mechanisms underlying various interfacial phenomena, but also because challenges measuring such experimentally.While free energy liquid-liquid and liquid-vapour interfaces is directly linked surface tension, which be calculated from anisotropy pressure tensor at interface, approach cannot used when a...

The determination of the free energy cost forming an interface between two phases, i.e. interfacial energy, is critical for characterizing a phase transition.In particular case liquid-to-solid transitions, it not straightforward to obtain this quantity through experiment or computation.Here, we present computational package Mold, which integrated in Molecular Dynamics open-source software LAMMPS (Thompson et al., 2022).Mold enables direct calculation arbitrarily complex crystal structures...

Machine learning algorithms have been demonstrated to predict atomistic properties approaching the accuracy of quantum chemical calculations at significantly less computational cost. Difficulties arise, however, when attempting apply these techniques large systems, or systems possessing excessive conformational freedom. In this article, machine method kriging is applied both intra‐atomic and interatomic energies, as well electrostatic multipole moments, atoms a water molecule center 10...

In hybrid particle models where coarse‐grained beads and atoms are used simultaneously, two clearly separate time scales mixed. If such in molecular dynamics simulations, a multiple step (MTS) scheme can therefore be used. this manuscript, we propose simple MTS algorithm which approximates for specific number of integration steps the slow bead–bead interactions with Taylor series approximation while atom–atom ones integrated every step. The procedure is applied to previously developed model...

Molecular dynamics represents a key enabling technology for applications ranging from biology to the development of new materials. However, many real-world remain inaccessible fully resolved simulations due their unsustainable computational costs and must therefore rely on semiempirical coarse-grained models. Significant efforts have been devoted in last decade towards improving predictivity these models providing rigorous justification use, through combination theoretical studies...

We present a general procedure to introduce electronic polarization into classical Molecular Dynamics (MD) force fields using Neural Network (NN) model. apply this framework the simulation of solid–liquid interface where surface is essential correctly capture main features system. By introducing multi-input, multi-output NN and treating as discrete classification problem, we are able obtain very good accuracy in terms quality predictions. Through definition custom loss function impose...

A new force field called FFLUX uses the machine learning technique kriging to capture link between properties (energies and multipole moments) of topological atoms (i.e., output) coordinates surrounding input). Here we present a novel, general method applying chemical systems that do not possess fixed number (geometrical) inputs. Unlike traditional methods, which require an input system be dimensionality, presented here can readily applied molecular simulation, where interaction cutoff...

We present a thorough analysis of the dynamic behaviour hybrid atomistic/coarse-grained (CG) models polymer melts. While structural properties are well preserved in dual-resolved model, we show how chains can be influenced by simultaneous presence atoms and beads. that although long enough to exhibit reptation, corresponding CG model is unable capture expected subdiffusive regimes seems still follow Rouse dynamics. The introduction chain restores correct regime, dynamics systems becomes...

Using the machine learning method kriging, we predict energies of atoms in ion-water clusters, consisting either Cl− or Na+ surrounded by a number water molecules (i.e., without Na+Cl− interaction). These atomic are calculated following topological energy partitioning called Interacting Quantum Atoms (IQAs). Kriging predicts properties (in this case IQA energies) model that has been trained over small set geometries with known property values. The results presented here part development an...