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We demonstrate the use of a regressive upscaling generative adversarial network (RUGAN) as an effective way to sample state space for hexagonal porous graphene sheets. The RUGAN can, after being trained on a set of small-scale examples, generate new, energetically relevant microstates (atomic configurations). The RUGAN can generate configurations across a continuum of total energy values and produce configurations at requested energy values. The microstates produced respect periodic boundary conditions, and importantly, the fully convolutional nature of the generator allows the generation of arbitrarily large microstates, after being trained on only a small-scale data set.

The structure and interactions of proteins play a critical role in determining the quality attributes of many foods, beverages, and pharmaceutical products. Incorporating a multiscale understanding of the structure–function relationships of proteins can provide greater insight into, and control of, the relevant processes at play. Combining data from experimental measurements, human sensory panels, and computer simulations through machine learning allows the construction of statistical models relating nanoscale properties of proteins to the physicochemical properties, physiological outcomes, and tastes of foods. This review highlights several examples of advanced computer simulations at molecular, mesoscale, and multiscale levels that shed light on the mechanisms at play in foods, thereby facilitating their control. It includes a practical simulation toolbox for those new to in silico modeling.

Exploring and controlling chemical reactions in compartments opens new platforms for designing bioinspired catalysts and energy-autonomous systems. Aqueous polymer networks or hydrogels serve as a perfect model for biological tissues, allowing systematic investigations of chemical transformations in compartments. Herein, we report the synthesis of a versatile, colloidal microgel catalyst containing covalently bound L-proline as an organocatalyst. The key finding of our work is that the catalytic activity can be tuned by adjusting the distribution of the organocatalyst in the microgel network as well as the properties of the solvent. We demonstrate that L-proline groups integrated into microgels enable the reaction of 4-nitrobenzaldehyde and cyclohexanone in a heterogeneous reaction mixture in which free L-proline is not active. By controlling the localization of the L-proline groups within the microgel network (core or corona), the rate of the aldol reaction in homogenous and heterogeneous reaction mixtures can be modulated. Furthermore, microgels with covalently attached catalysts can be recycled and reused in sequential catalytic runs without deterioration of the catalyst performance in terms of activity and selectivity. The internal structure of the microgel in heterogeneous reaction mixtures was studied by computer simulations. (C) 2019 Elsevier Inc. All rights reserved.

Here we report on the non-hydrothermal aqueous synthesis and characterization of nanocrystalline lithium aluminum iodate, LiAl(IO3)4. Morphological and compositional analyses were carried out by using scanning electron microscopy (SEM) and energy-dispersive X-ray measurements (EDX). The optical and vibrational properties of LiAl(IO3)4 have been studied by UV-Vis and IR spectroscopy. LiAl(IO3)4 is found to crystallize in the non-centrosymmetric, monoclinic P21 space group, contrary to what was reported previously. Theoretical simulations and Rietveld refinements of crystal structure support this finding, together with the relatively high Second Harmonic Generation (SGH) response that was observed. Electronic band structure calculations show that LiAl(IO3)4 crystal has an indirect band gap Egap=3.68 eV, in agreement with the experimental optical band gap Egap=3.433 eV. The complex relative permittivity and the refraction index of LiAl(IO3)4 have also been calculated as a function of energy, as well as its elastic constants and mechanical parameters. LiAl(IO3)4 is found to be a very compressible and ductile material. Our findings imply that LiAl(IO3)4 is a promising material for optoelectronic and non -linear optical applications.

This paper addresses the path planning and control of multiple colonies/clusters that have unmanned aerial vehicles (UAV) which make a network in a hazardous environment. To solve the aforementioned issue, we design a new and novel hybrid algorithm. As seen in the mission requirement, to combine the Maximum-Minimum ant colony optimization (ACO) with Vicsek based multi-agent system (MAS) to make an Artificially Intelligent (AI) scheme. In order to control and manage the different colonies, UAVs make a form of a network. The designed method overcomes the deficiencies of existing algorithms related to controlling and synchronizing the information globally. Furthermore, our designed architecture bounds, lemmatizes the pheromone, and finds the best ants which then make the most optimized path. The key contribution of this study is to merge two unique algorithms into a hybrid algorithm that has superior performance than both algorithms operating separately. Another contribution of the designed method is the ability to increase the number of individual agents inside the colony or the number of colonies with a good convergence rate. Lastly, we also compared the simulation results with the non-dominated sorting genetic algorithm II (NSGA-II) in order to prove the designed algorithm has a better convergence rate.

Research shows that individuals benefit from setting up their personal networks strategically. There are two fundamental networking approaches: structural change, which involves the addition and deletion of communication ties, and frequency change, which means an increase or decrease of communication on existing ties. Existing literature has focused predominantly on structural change, leaving the potential of frequency change understudied. To investigate the differential effects of structural and frequency change on the efficiency of information flow through a network, we conduct simulations of networking approaches on a diverse set of real-world directed weighted communication networks. Our results indicate that, overall, frequency change is associated with higher efficiency than structural change in all but one of the studied cases. Structural change has a strong direct effect on individuals who actively modify their personal network. Surprisingly, our simulations also show that the indirect effects of frequency change (i.e., an individual’s ties are reshaped due to others’ actions) can exceed direct ones. Our results highlight the value of the so far less studied frequency change and suggest that using targeted network alterations can result in gains for information flow at the scale of the entire network.

This article deals with computer analyses of output quantities of a railway vehicle depending on changing of parameters of suspension system. A passenger car was chosen for dynamic analyses. An analysed passenger railway vehicle uses two stage suspension system composed of coil springs and hydraulic dampers. Stiffness of coil springs of primary and secondary suspensions were defined for two states and its influence on output values in terms of quality and quantity was evaluated. As output variables, values of forces in a wheel/rail contact and accelerations in several locations on a wagon body floor were chosen. Values of forces in a wheel/rail contact indicate dynamic response of a railway vehicle running in terms of running safety and values of accelerations serve as important input for evaluation of passenger ride comfort.

The efficiency of heat emitters plays an important role in the improvement of building energy performance, especially in the context of system and product comparison. In particular, it can be directly related to thermal comfort via the operative temperature that is effectively sensed by the users. For the first time in the literature, in this paper we develop a combined analytical model for room and radiator that computes directly the heat output required to maintain a specific operative temperature. The total heat balance of the enclosure is used to accurately quantify and compare the heat emission losses of different radiator types via an analytical calculation of the operative temperature. This determines the efficiency of a selection of panel radiators with different surface temperature, radiation fraction and number of panels, which were tested in a chamber conforming to the EN 442-2 standard. Additionally, we assess the related annual energy consumption in different climates by carrying out annual simulations in old (without heat recovery) and new (with heat recovery) building types located in Tallinn, Estonia and Strasbourg, France. In the new building we find a similar performance for all the radiators. In the old building however, one radiator outperforms the other two with up to 1.38% lower annual energy consumption, due to smaller rear losses and higher thermal comfort provided by the larger front panel surface.

Nowadays designing of selected areas of mines underground workings can be effectively improved by the application of computer techniques: 3D scanning, computer simulations and Virtual Reality. This, in fact, would result in the more reliable design process, significantly reduced designing costs and efforts, and improvement of the mines staff’s safety. This scientific paper presents a method developed for redesigning of selected areas of mines underground workings in which auxiliary transport is carried out. The method combines 3D laser scanning technique with computer simulations carried out in a CAD/MBS system, in order to determine the location of potential collisions of the transported loads with the arch yielding support and the equipment. The obtained results, visualized using Virtual Reality, will form input data in the process of designing the selected area of the mines underground workings. Finally, an example of the application of the described method during transportation of big-size load is given.

Computer simulations of vehicle dynamics become more complex when a vehicle movement takes place on the uneven road surface. In such a case two problems must be solved. The first one concerns a way of road surface modeling, and the second one a way of precisely determining a place of interaction of reaction forces of the road on the vehicle wheels. In this paper triangular irregular networks (TIN) surface was used for modeling surface unevenness, and the author’s algorithm based on the efficient kd-tree data structure was developed for determining a place of an application road surface reaction forces. For calculating the reaction forces including rolling resistance force the Pacejka Magic Formula tire model was used. The solution presented in the paper is computing efficient and for this reason it can be used in the in real-time simulations not only for a vehicle dynamics but for any objects moving over an uneven surface road.

Colloidal suspensions of two species have the ability to form binary crystals under certain conditions. The hunt for these functional materials and the countless investigations on their formation process are justified by the plethora of synergetic and collective properties these binary superlattices show. Among the many crystal structures observed over the past decades, the highly exotic colloidal icosahedral AB13 crystal was predicted to be stable in binary hard-sphere mixtures nearly 30 years ago, yet the kinetic pathway of how homogeneous nucleation occurs in this system is still unknown. Here we investigate binary nucleation of the AB13 crystal from a binary fluid phase of nearly hard spheres. We calculate the nucleation barrier and nucleation rate as a function of supersaturation and draw a comparison with nucleation of single-component and other binary crystals. To follow the nucleation process, we employ a neural network to identify the AB13 phase from the binary fluid phase and the competing fcc crystal with single-particle resolution and significant accuracy in the case of bulk phases. We show that AB13 crystal nucleation proceeds via a coassembly process where large spheres and icosahedral small-sphere clusters simultaneously attach to the nucleus. Our results lend strong support for a classical pathway that is well-described by classical nucleation theory, even though the binary fluid phase is highly structured and exhibits local regions of high bond orientational order.

Electric cargo bicycles have become a popular mode of transport for last-mile goods deliveries under conditions of restricted traffic in urban areas. The indispensable elements of the cargo bike delivery systems are loading hubs: they serve as intermediate points between vans and bikes ensuring loading, storage, and e-vehicle charging operations. The choice of the loading hub location is one of the basic problems to be solved when designing city logistics systems that presume the use of electric bicycles. The paper proposes an approach to justifying the location of a loading hub based on computer simulations of the delivery process in the closed urban area under the condition of stochastic demand for transport services. The developed mathematical model considers consignees and loading hubs as vertices in the graph representing the transport network. A single request for transport services is described based on the set of numeric parameters, among which the most significant are the size of the consignment, its dimensions, and the time interval between the current and the previous requests for deliveries. The software implementation of the developed model in Python programming language was used to simulate the process of goods delivery by e-bikes for two cases—the synthetically generated rectangular network and the real-world case of the Old Town district in Krakow, Poland. The loading hub location was substantiated based on the simulation results from a set of alternative locations by using the minimum of the total transport work as the efficiency criterion. The obtained results differ from the loading hub locations chosen with the use of classical rectilinear and center-of-gravity methods to solve a simple facility location problem.

The vector borne diseases share a high percentage of the annual deaths reported by the world health organization. Due to the involvement of multiple factors and resistance of the vector to the treatment strategies, it is highly desired to design a safe, efficient and harmless control strategy. A state of the art computational framework for the Wolbachia induced “genetic-control-strategy” has been documented during this research. The process of mating and molecular identification is complex and expensive and different labs around the world are devoted to format a smooth implementation strategy of this approach. During this research, as a first step, data was collected, secondly, dynamic artificial neural networks, with the “tapped delay” lines are used for nonlinear filtering of the data and for the prediction of the parametric values of the novel mathematical model. To study parametric reliance of stable solutions and unstable solution we analyze stability and the corresponding thresholds desired for this study are documented. The study conducted during this research can prove to be useful in future experimental and theoretical studies, aimed to control the vector borne diseases.

In the present study, a nonlinear delayed coronavirus pandemic model is investigated in the human population. For study, we find the equilibria of susceptible-exposed-infected-quarantine-recovered model with delay term. The stability of the model is investigated using well-posedness, Routh Hurwitz criterion, Volterra Lyapunov function, and Lasalle invariance principle. The effect of the reproduction number on dynamics of disease is analyzed. If the reproduction number is less than one then the disease has been controlled. On the other hand, if the reproduction number is greater than one then the disease has become endemic in the population. The effect of the quarantine component on the reproduction number is also investigated. In the delayed analysis of the model, we investigated that transmission dynamics of the disease is dependent on delay terms which is also reflected in basic reproduction number. At the end, to depict the strength of the theoretical analysis of the model, computer simulations are presented.

The challenge of optimizing the pore size distribution of porous electrodes for different electrolytes is encountered in supercapacitors, lithium-ion capacitors and hybridized battery-supercapacitor devices. A volume-averaged continuum model of ion transport, taking into account the pore size distribution, is employed for the design of porous electrodes for electrochemical double-layer capacitors (EDLCs) in this study. After validation against experimental data, computer simulations investigate two types of porous electrodes, an activated carbon coating and an activated carbon fabric, and three electrolytes: 1.5 M TEABF4 in acetonitrile (AN), 1.5 M TEABF4 in propylene carbonate (PC), and 1 M LiPF6 in ethylene carbonate:ethyl methyl carbonate (EC:EMC) 1:1 v/v. The design exercise concluded that it is important that the porous electrode has a large specific area in terms of micropores larger than the largest desolvated ion, to achieve high specific capacity, and a good proportion of mesopores larger than the largest solvated ion to ensure fast ion transport and accessibility of the micropores.

The paper focuses on thermal and mechanical analysis of Periodic Surface Structure (PSS). PSS is a continuous surface with a specific topology that is mathematically formulated by geometric factors. Cubic P-surface (&ldquo, primitive&rdquo, ), D-surface (&ldquo, diamond&rdquo, ), and G-surface (&ldquo, gyroid&rdquo, ) structures were simulated under load and heat transport using a numerical approach. We conducted our study by solving the stress and heat equations using the Finite Element Method (FEM). We achieved results using our software module, which generates PSS and simulates stress and temperature distribution. The stress model defined by dependence between stress and strain, gained from an experiment, and correlation of strain and displacement, gained from geometric conditions, was used in numerical experiments. The influence of geometric factors on the thermal and mechanical behavior of PSS was qualitatively determined. We showed decreasing effective stress values with an increased number of cells in the cubic domain for concerned PSS. It is important, because the increase in the number of cells does not increase the structure&rsquo, s volume.

Disordered systems like liquids, gels, glasses, or granular materials are not only ubiquitous in daily life and in industrial applications but they are also crucial for the mechanical stability of cells or the transport of chemical and biological agents in living organisms. Despite the importance of these systems, their microscopic structure is understood only on a rudimentary level, thus in stark contrast to the case of gases and crystals. Since scattering experiments and analytical calculations usually give only structural information that is spherically averaged, the three dimensional (3D) structure of disordered systems is basically unknown. Here we introduce a simple method that allows to probe the 3D structure of such systems. Using computer simulations we find that hard-sphere-like liquids have on intermediate and large scales an intricate structural order given by alternating layers with icosahedral and dodecahedral symmetries, while open network liquids like silica have a structural order with tetrahedral symmetry. These results show that liquids have a highly non-trivial 3D structure and that this structural information is encoded in non-standard correlation functions., Comment: arXiv admin note: substantial text overlap with arXiv:1904.12447

Inorganic phosphors based on monoclinic Y2WO6 doped with Sm3+ ions were prepared via conventional solid-state reactions at high temperature. A total of six samples were obtained with different Sm3+ concentrations (0–9%). The purity of the as-prepared phases was checked by powder X-ray diffraction (PXRD). The excitation, emission, and time-resolved emission spectra were examined in detail. The experimental decay curves were fitted to the Inokuti–Hirayama model, showing that the Sm3+ ions form clusters at all compositions. Periodic hybrid density functional theory calculations were also carried out on the undoped material and on 144-atom supercells of stoichiometry Y1.9375Sm0.0625WO6 and Y1.875Sm0.125WO6. The different coordination environments at the Y1, Y2 and Y3 sites are analysed in detail. The calculated structure and band gap of Y2WO6 are in good agreement with experiment with one potentially important discrepancy in a Y3-O bond length. The thermodynamically favoured substitution sites for Sm, Y2 and Y3, in the supercell are not those observed under the preparation conditions used here, since the experimental Rietveld analysis suggests occupation of Y1 at all concentrations. Analogous calculations for the Eu-doped system highlight marked differences between Eu and Sm despite their similar ionic sizes. The calculateddensities of states show the position of the 4f levels in the band gap depend on thesites occupied by the dopants and thus we expect marked differences in the luminescencespectra, opening up possibilities for tuning device performance.

International audience; This article focuses on Group Target Tracking (GTT) to counter swarms of drones using Random Finite Sets (RFSs) and Random Matrix (RM) approaches. Tracking swarms of drones is analog to tracking extended targets that are characterized by their continuously evolving shape and composition. Extended target tracking for groups of targets finds various applications in the literature because detecting and tracking each individual target of a group is computationally demanding and unnecessary if the group itself can be modeled. Elliptic shapes offers a suitable representation for most groups, and their inference is quite inexpensive with the random matrix approach. Indeed, they are efficient when coupled with random finite sets based filters, which represents the current state of the art for Bayesian multi-target tracking. In this work, a practical implementation of a labeled Poisson/Multi-Bernoulli filter using random matrices for group target tracking is proposed. This study compares several random matrix prediction and update algorithms with and without random finite sets based filters on several dataset.

The study presents the results of an experimental and computational study of the high-velocity impact of low-density aluminum foam into a rigid wall. It is shown that the aluminum foam samples deformed before hitting the rigid wall because of the high inertial forces during the acceleration. During the impact, the samples deformed only in the region contacting the rigid wall due to the high impact velocity, the inertial effects dominated the deformation process. However, the engineering stress&ndash, strain relationship retains its typical plateau shape until the densification strain. The experimental tests were successfully reproduced with parametric computer simulations using the LS-DYNA explicit finite element code. A unique computational lattice-type model was used, which can reproduce the randomness of the irregular, open-cell structure of aluminum foams. Parametric computer simulations of twenty different aluminum foam sample models with randomly generated irregular lattice structures were carried out at different acceleration levels to obtain representative statistical results. The high strain-rate sensitivity of low-density aluminum foam was also observed. A comparison of experimental and computational results during aluminum foam sample impact shows very similar deformation behavior. The computational model correctly represents the real impact conditions of low-density aluminum foam and can be recommended for use in similar high-velocity impact investigations.

Defects in an aircraft can be caused by design flaw, manufacturer flaw or wear and tear from use. Although inspections are performed on the airplane before and after flights, accidents still result from faulty equipment and malfunctioning components. Determining the causes of an aircraft accident is an outcome of a very laborious and often very long investigation process. According to the statistics, currently the human factor has the biggest share within the causal groups. Along with the development of aviation technology came a decline in the number of accidents caused by failures or malfunctions, though such still happen, especially considering aging aircraft. Discovering causes and factors behind an aircraft accident is of crucial significance from the perspective of improving aircraft operational safety. Effective prevention is the basic measure of raising the aircraft reliability level, and the safety-related guidelines must be developed based on verified facts, reliable analysis and logical conclusions. This article presents simulation tests carried out by finite element method and constitutive laboratory tests leading to the explanation of the direct cause of a military aircraft accident. Computer-based simulation methods are particularly useful when it comes to analysing the kinematics of mechanisms and potential stress concentration points. Using computer models enables analysing an individual element failure process, identifying their sequence and locating their primary failure source.

Today’s society is served by modern technology, accompanied by effects of insecurity and uncertainty, which are important and inevitable. Engineering analysis must include methods of assessing these impacts on the design, implementation and operation of technical systems. Mathematical statistics and probability theory provide the mathematical basis for modeling unreliability and analysis as well as their impact on already built technical systems. The aim of the paper is to introduce quantitative methods that enable systematic development of planned and constructed criteria, problem modeling and evaluation of economically technical optimum.

Passenger ride comfort of road vehicles is one of the most important performances of vehicle. The research of automotive passenger ride comfort is getting more and more important. In this contribution, the multibody model of a three-wheeled vehicle and analyses of passenger ride comfort is presented. The vehicle model and dynamic analyses were performed using the Simpack software package. The dynamic analyses of the vehicle driving were carried out on the road model with different surface quality. Analyses were focused on assessment of the passenger ride comfort on a driver seat.

International audience; Diffusion of interstitial carbon atoms in iron is the rate-limiting phenomenon of a number of phase transitions in body-centered (bcc) and body-centered tetragonal (bct) phases such as ferrite and martensite. These phases being rarely stress-free and undeformed, the influence of stress/strain on the diffusivity of carbon is essential, although scarcely documented. We developed a model of carbon elastodiffusion in bct-iron. We combined anisotropic linear elasticity theory of point defects, the dilute approximation of regular solutions and the multisite model of random walk into a coherent mean-field theory. The model allows predicting the effects of composition, temperature and mechanical loading on the anisotropy of carbon diffusion. Density functional theory calculations have provided most of the materials parameters. The predictions were successfully tested against kinetic Monte Carlo simulations. Our results show that compression of the crystal increases carbon diffusivity, while tension has the opposite effect. Axial straining is accompanied by a large anisotropy of diffusion. This effect could be exploited to produce stress-controlled diffusion channeling for the engineering of anisotropic microstructures during thermal ageing of martensitic Fe-C alloys.

A combined experimental and novel theoretical ab initio structural and electronic study was performed in order to characterize ZnO semiconductor nanopowders doped with Al atoms. For this, powder mixtures of ZnO and metallic Al in adequate proportions yielding different contents of Al (5, 10, and 30 at. %) were prepared by mechanical milling. The systems were characterized by X-ray diffraction and positron annihilation lifetime spectroscopy measurements. Additionally, combining two first-principles methods based on the Density Functional Theory (DFT) we calculated the final equilibrium structures for different concentrations of Al dopants and Zn vacancies in ZnO, predicting afterwards the characteristic positron annihilation lifetimes at these equilibrium structures. In addition to the structural relaxations, the ab initio predictions of the electronic properties in the studied systems help us to understand deeper the origin and characteristics of different positrons traps. This experimental and ab initio/DFT combined study allows to verify the dopant incorporation into the ZnO wurtzite structure and to extract the maximum information from the experimental data, giving an insight into the different defect complexes and their influence in the structural and electrical properties. Fil: Damonte, Laura Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina Fil: Darriba, German Nicolas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina Fil: Rentería, Mario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina

To solve matrix-type linear time-varying equation more efficiently, a novel exponential-type varying gain recurrent neural network (EVG-RNN) is proposed in this paper. Being distinguished from the traditional fixed-parameter gain recurrent neural network (FG-RNN), the proposed EVG-RNN is derived from a vector- or matrix-based unbounded error function by a varying-parameter neural dynamic approach. With four different kinds of activation functions, the super-exponential convergence performance of EVG-RNN is proved theoretically in details, of which the error convergence rate is much faster than that of FG-RNN. In addition, mathematics proves that the computation errors of EVG-RNN can converge to zero, and it possesses the capability of restraining external interference. Finally, series of computer simulations verify and illustrate the better performance of convergence and robustness of EVG-RNN than that of FG-RNN and FTZNN when solving the identical linear time-varying equation.

The recent widespread application of optical coherence tomography (OCT) in interventional cardiology has improved patient-specific modeling of stented coronary arteries for the investigation of local hemodynamics. In this review, the workflow for the creation of fluid dynamics models of stented coronary arteries from OCT images is presented. The algorithms for lumen contours and stent strut detection from OCT as well as the reconstruction methods of stented geometries are discussed. Furthermore, the state of the art of studies that investigate the hemodynamics of OCT-based stented coronary artery geometries is reported. Although those studies analyzed few patient-specific cases, the application of the current reconstruction methods of stented geometries to large populations is possible. However, the improvement of these methods and the reduction of the time needed for the entire modeling process are crucial for a widespread clinical use of the OCT-based models and future in silico clinical trials.

Monte Carlo and molecular dynamics computer simulations using the rigid TIP4P and the flexible BJH intermolecular H 2 O potentials were carried out for 50 states of supercritical water characterizing a very wide range of thermodynamic conditions, 573 ≤ T ≤ 1273 K; 0.02 ≤ ρ ≤ 1.67 g/cm 3 ; 10 ≤ P ≤ 10,000 MPa. Good agreement with available experimental data of the simulated thermodynamic and structural properties give confidence to the quantitative statistical analysis of intermolecular hydrogen bonding under the conditions studied. Energetic, geometric, and angular characteristics of supercritical H-bonds and their distributions at a given temperature remain almost invariant over the entire density range studied from dilute gas-like (~ 0.03 g·cm − 3 ) to highly compressed liquid-like (~ 1.5 g·cm − 3 ) states. The increase of temperature from ambient to supercritical affects the characteristics of H-bonding in water much more dramatically than the changes in density along any supercritical isotherm. Compared to H-bonds in liquid water under ambient conditions, the H-bonds at 773 K are, on average, 10% weaker, 5% longer, and less linear. Both above and below the H-bonding percolation threshold the fractions of H 2 O molecules involved in a certain number of H-bonds in liquid and supercritical water closely follow the universal binomial distribution as a function of the average number of H-bonds per one water molecule in the system, as predicted by the independent bond theory. This universal distribution remains intact even when dynamic criteria of H-bonding lifetimes are additionally applied.

Tight-binding models provide a conceptually transparent and computationally efficient method to represent the electronic properties of materials. With AFLOW$��$ we introduce a framework for high-throughput first principles calculations that automatically generates tight-binding hamiltonians without any additional input. Several additional features are included in AFLOW$��$ with the intent to simplify the self-consistent calculation of Hubbard U corrections, the calculations of phonon dispersions, elastic properties, complex dielectric constants, and electronic transport coefficients. As examples we show how to compute the optical properties of layered nitrides in the $AM$N$_2$ family, and the elastic and vibrational properties of binary halides with CsCl and NaCl structure., 13 pages, 8 figures

International audience; We study groups of interacting agents who are trying to discover probabilistic truths on the basis of sequentially provided evidence and information about the belief states of other group members. The main research question is which combination of epistemic principles-combinations of an evidential update rule, a rule for determining peerhood, and a rule for aggregating probability functions-such groups should adopt to strike the best balance between being fast and being accurate, where the former is understood by reference to how long it takes before a majority of the group assigns a high probability to the true hypothesis, and the latter by reference to the average Brier penalty incurred by the group. The main methodology to be used is that of agent-based optimization , which is a specific form of evolutionary computing. We implement this methodology in a generalization of the Hegselmann-Krause model. In the end, we are able to identify optimal procedures for taking into account both direct evidence and information about one's peers' beliefs. At the same time, we note that optimality for such procedures is dependent on context.

Inter-radar interference will be a crucial problem when a number of frequency modulated continuous wave (FMCW) radars are densely deployed in future, since it can cause miss detection and false detection of the target due to wideband interference and narrowband interference. One of the approaches to solve this problem is to introduce a multiple access technique for automotive radars, e.g. carrier sense multiple access used in wireless LAN to avoid packet collision. This study proposes multiple access FMCW radar which can avoid both narrow-band and wideband interference assuming all of the FMCW radars have the same design parameters. It also, proposes a carrier sense technique as a key technique for multiple access FMCW radar and evaluates the carrier sense performance by computer simulations.

Solvation effects play a key role in chemical and biological processes. The microscopic properties of water near molecular surfaces are radically different from those in the bulk. Furthermore, the behavior of water in confined volumes of a nanometer scale, including transmembrane pores of ion channels, is especially nontrivial. Knowledge at the molecular level of structural and dynamic parameters of water in such systems is necessary to understand the mechanisms of ion channels functioning. In this work, the results of molecular dynamics (MD) simulations of water in the pore and selectivity filter domains of TRPV1 (Transient Receptor Potential Vanilloid type 1) membrane channel are considered. These domains represent nanoscale volumes with strongly amphiphilic walls, where physical behavior of water radically differs from that of free hydration (e.g., at protein interfaces) or in the bulk. Inside the pore and filter domains, water reveals a very heterogeneous spatial distribution and unusual dynamics: It forms compact areas localized near polar groups of particular residues. Residence time of water molecules in such areas is at least 1.5 to 3 times larger than that observed for similar groups at the protein surface. Presumably, these water &ldquo, blobs&rdquo, play an important role in the functional activity of TRPV1. In particular, they take part in hydration of the hydrophobic TRPV1 pore by localizing up to six waters near the so-called &ldquo, lower gate&rdquo, of the channel and reducing by this way the free energy barrier for ion and water transport. Although the channel is formed by four identical protein subunits, which are symmetrically packed in the initial experimental 3D structure, in the course of MD simulations, hydration of the same amino acid residues of individual subunits may differ significantly. This greatly affects the microscopic picture of the distribution of water in the channel and, potentially, the mechanism of its functioning. Therefore, reconstruction of the full picture of TRPV1 channel solvation requires thorough atomistic simulations and analysis. It is important that the naturally occurring porous volumes, like ion-conducting protein domains, reveal much more sophisticated and fine-tuned regulation of solvation than, e.g., artificially designed carbon nanotubes.

New skeletal chemical kinetic models have been obtained by reducing a detailed model for the gas-phase combustion of Douglas Fir pyrolysis products. The skeletal models are intended to reduce the cost of high-resolution wildland fire simulations, without substantially affecting accuracy. The reduction begins from a 137 species, 4533 reaction detailed model for combustion of gas-phase biomass pyrolysis products, and is performed using the directed relation graph with error propagation and sensitivity analysis method, followed by further reaction elimination. The reduction process tracks errors in the ignition delay time and peak temperature for combustion of gas-phase products resulting from the pyrolysis of Douglas Fir. Three skeletal models are produced as a result of this process, corresponding to a larger 71 species, 1179 reaction model with less than 1\% error in ignition delay time compared to the detailed model, an intermediate 54 species, 637 reaction model with 24\% error, and a smaller 54 species, 204 reaction model with 80\% error. Using the skeletal models, peak temperature, volumetric heat release rate, premixed laminar flame speed, and diffusion flame extinction temperatures are compared with the detailed model, revealing an average maximum error in these metrics across all conditions considered of less than 1\% for the larger skeletal model, 10\% for the intermediate model, and 24\% for the smaller model. All three skeletal models are thus sufficiently accurate and computationally efficient for implementation in high-resolution wildland fire simulations, where other model errors and parametric uncertainties are likely to be greater than the errors introduced by the reduced kinetic models presented here.

Progress in computational methods has been stimulated by the widespread availability of cheap computational power leading to the improved precision and efficiency of simulation software. Simulation tools become indispensable tools for engineers who are interested in attacking increasingly larger problems or are interested in searching larger phase space of process and system variables to find the optimal design. In this paper, we show and introduce a new approach to a computational method that involves mixed time stepping scheme and allows to decrease computational cost. Implementation of our algorithm does not require a parallel computing environment. Our strategy splits domains of a dynamically changing physical phenomena and allows to adjust the numerical model to various sub-domains. We are the first (to our best knowledge) to show that it is possible to use a mixed time partitioning method with various combination of schemes during binary alloys solidification. In particular, we use a fixed time step in one domain, and look for much larger time steps in other domains, while maintaining high accuracy. Our method is independent of a number of domains considered, comparing to traditional methods where only two domains were considered. Mixed time partitioning methods are of high importance here, because of natural separation of domain types. Typically all important physical phenomena occur in the casting and are of high computational cost, while in the mold domains less dynamic processes are observed and consequently larger time step can be chosen. Finally, we performed series of numerical experiments and demonstrate that our approach allows reducing computational time by more than three times without losing the significant precision of results and without parallel computing.

Surrogate models are often used as alternatives to considerably reduce the computational burden of the expensive computer simulations that are required for engineering designs. The development of surrogate models for complex relationships between the parameters often requires the modeling of high-dimensional functions with limited information, and it is challenging to choose an effective surrogate model over the unknown design space. To this end, the ensemble models&mdash, combined with different surrogate models&mdash, offer effective solutions. This paper presents a new ensemble model based on the least squares method, which is a regularization strategy and an augmentation strategy, we call the model the regularized least squares ensemble model (RLS-EM). Three individual surrogate models&mdash, Kriging, radial basis function, and support vector regression&mdash, are used to compose the RLS-EM. Further, the weight factors are estimated by the least squares method without using the global or local error metrics, which are used in most existing methods. To solve the collinearity in the least squares calculation process, a regularization strategy and an augmentation strategy are developed. The two strategies help explore the unknown regions and improve the accuracy on one hand, on the other hand, the collinearity can be reduced, and the overfitting phenomenon that may occur can be avoided. Six numerical functions, from two-dimensional to 12-dimensional, and a computer numerical control (CNC) milling machine bed design problem are used to verify the proposed method. The results of the numerical examples show that RLS-EM saves a considerable amount of computation time while ensuring the same level of robustness and accuracy compared with other ensemble models. The RLS-EM used for the CNC milling machine bed design problem also shows good accuracy characteristics compared with other ensemble methods.

Thermoresponsive copolymer microgels based on the biocompatible monomer N-vinylcaprolactam (VCL) and the hydrophobic comonomer 4-tert-butylcyclohexylacrylate (TBCHA) with highly tunable comonomers ratio were for the first time synthesized by miniemulsion polymerization. Their physical properties in aqueous solution and at the solid interface were characterized using dynamic light scattering (DLS), atomic force microscopy (AFM) and dissipative particle dynamics (DPD) simulations. The results show a significant decrease of the swelling rate of the obtained microgels with an increase of the amount of the hydrophobic comonomer. In the case when the fraction of TBCHA is equal or higher than the fraction of VCL, the microgels become almost insensitive to the temperature changes, and the amount of water inside the microgels appeared to be diminishingly small. In the opposite case, if the VCL fraction is major, the copolymer microgels preserve their softness and deformability while being adsorbed onto a solid surface. At the same time, all samples have shown a good colloidal stability and a low polydispersity in size. Thus, the presented polymerization technique is applicable for the fabrication of microgels using hydrophobic monomers, which are not accessible by conventional precipitation polymerization. We demonstrate that the mechanical properties and the temperature-responsiveness of the copolymer microgels can be precisely adjusted by the content of the hydrophobic comonomer. (C) 2020 Elsevier Inc. All rights reserved.

© 2019 Le, Houri, Balage, Smith and Mechler. In studies of the transfer, distribution and biochemical activity of metal ions it is typically assumed that the phospholipid bilayer acts as an inert barrier. Yet, there is mounting evidence that metal ions can influence the physical properties of membranes. Little is known of the basis of this effect. In this work the location and distribution of common metal ions: Na + , Mg 2+ , and Ca 2+ in phospholipid membranes were studied. Computer simulations of lipid membrane segments in aqueous environment showed that the ions penetrate the membrane headgroup zone and co-localize with the phosphate and the ester moieties. Analysis of the chemical environment of the ions in the simulations suggested that the co-localization is facilitated by coordination to the polar oxygen atoms of the phosphate and ester groups in typical coordination geometries of each ionic species, where the coordination shells are completed by water molecules. In contrast, the counterions do not penetrate the headgroup zone but form a layer over the membrane instead; this layer is also an effective metal exclusion zone. Importantly, the choline groups appear to be distributed almost exactly in the same plane as the phosphate, suggesting that the zwitterion dipole is preferentially horizontally aligned: this suggests that the distribution of the Cl − over the membrane surface is not a direct result of interaction with the choline groups, but rather an effect of the field emanating from the metal ion content of the membrane. Such a well defined ion distribution is expected to have a strong influence on membrane properties, in particular phase transition temperatures via increased in-plane cohesion; this was proven by calorimetry measurements using differential scanning calorimetry of suspended liposomes and quartz crystal microbalance-based measurements on supported single bilayer membranes. These findings shed a new light on the role metal ions play in stabilizing biological membranes.

As the energy efficiency demands for future buildings become increasingly stringent, preliminary assessments of energy consumption are mandatory. These are possible only through numerical simulations, whose reliability crucially depends on boundary conditions. We therefore investigate their role in numerical estimates for the usage of geothermal energy, performing annual simulations of transient heat transfer for a building employing a geothermal heat pump plant and energy piles. Starting from actual measurements, we solve the heat equations in 2D and 3D using COMSOL Multiphysics and IDA-ICE, and discover a negligible impact of the multiregional ground surface boundary conditions. Moreover, we verify that the thermal mass of the soil medium induces a small vertical temperature gradient on the piles surface. We also find a roughly constant temperature on each horizontal cross-section, with nearly identical values if the average temperature is integrated over the full plane or evaluated at one single point. Calculating the yearly heating need for an entire building we then show that the chosen upper boundary condition affects the energy balance dramatically. Using directly the pipes’ outlet temperature induces a 54% overestimation of the heat flux, while the exact ground surface temperature above the piles reduces the error to 0.03%.

The authors thank Eugene Kotomin and V. Kuzovkov for fruitful discussions and valuable suggestions. A.I.P thanks A.Moskina for the technical assistance in preparation of the manuscript. A.I.P also gratefully acknowledges a project LZP-2018/1-0214 from the Latvian Council of Science for partial support., The paper presents the results of first-principles computer simulations of the band structure, the density of states, and the total energy of NaCl (NaCl, Na2Cl2, Na3Cl3, Na4Cl4, Na6Cl6) linear chains of atoms. Modelling of the specified characteristics is realised in the computer code Atomistix ToolKit combined with Virtual NanoLab. The total energy depends on the number of ions in the nanoobject under study, but practically does not depend on the geometric arrangement of ions., Latvian Council of Science LZP-2018/1-0214; Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART²

Dynamic self-assembly is an emerging area of research where properly designed self-assembly elements can be used reversibly to trigger and control some tasks at the molecular level. The interactions between decorated nanoparticles, NPs, are experimentally modifiable by a variety of stimuli that can also vary in time periodically or randomly. In coarse-grained simulations, we activate a switch, either periodically or randomly, which assembles-disassembles clusters of NPs. We then introduce a single catalytic NP(C) covered with catalytic moieties, C, and leave all remaining NP(R)s decorated with reactive moieties, R. The catalytic reaction that converts R into products P depends on the encounter of C and R. Particle-based simulations are here used to study the catalytic activity and reaction yields of decorated nanoparticles that aggregate/disaggregate with the application of time-varying perturbations. Static aggregation is not catalytically efficient because it traps the catalyst. The application of random perturbations that vary in time in the form of colored noises improves the reaction yields and can provide opportunities for more efficient catalytic activity. The work can also allow us to understand how in Nature many biological processes are affected or driven by random/noisy fluctuations of the environment.

International audience; Computers have transformed science and help to extend the boundaries of human knowledge. However, does the validation and diffusion of results of computational inquiries and computer simulations call for a novel epistemological analysis? I discuss how the notion of novelty should be cashed out to investigate this issue meaningfully and argue that a consequentialist framework similar to the one used by Goldman to develop social epistemology can be helpful at this point. I highlight computational, mathematical, representational, and social stages on which the validity of simulation-based belief-generating processes hinges, and emphasize that their epistemic impact depends on the scientific practices that scientists adopt at these different stages. I further argue that epistemologists cannot ignore these partially novel issues and conclude that the epistemology of computational inquiries needs to go beyond that of models and scientific representations and has cognitive, social, and in the present case computational, dimensions.

Monolayers of a cytosine-based nucleolipid (1,2-dipalmitoyl-sn-glycero-3-(cytidine diphosphate) (ammonium salt), CDP-DG) at basic subphase have been prepared at the air-water interface both in absence and presence of guanine. The formation of the complementary base pairing is demonstrated by combining surface experimental techniques, i.e., surface pressure (π)–area (A), Brewster angle microscopy (BAM), infrared spectroscopy (PM-IRRAS) and computer simulations. A folding of the cytosine-based nucleolipid molecules forming monolayer at the air-water interface occurs during the guanine recognition as absorbate host and is kept during several compression-expansion processes under set experimental conditions. The specificity between nitrogenous bases has been also registered. Finally, mixed monolayers of CDP-DG and a phospholipid (1,2-dimyristoyl-sn-glycero-3-phosphate (sodium salt), DMPA) has been studied and a molecular segregation of the DMPA molecules has been inferred by the additivity rule.

Molecular imprinting technology (MIT) offers an effective technique for efficient separation and enrichment of specific analytes from complicated matrices and has been used for illicit veterinary drug detectionin recent years due to its high selectivity, good chemical stability, and simple preparation. The development of in silico-based approaches has enabled the simulation of molecularly imprinted polymers (MIPs) to facilitate the selection of imprinting conditions such as template, functional monomer, and the best suitable solvent. In this work, using density functional theory (DFT), the molecularly imprinted polymers of clenbuterol and its metabolites were designed by computer-aided at B3LYP/6-31 + G (d, p) level. Screening molecular imprinting components such as functional monomers, cross-linkers, and solvents has been achieved in the computational simulation considerations. The simulation results showed that methacrylic acid (MAA) is the best functional monomer, the optimal imprinting ratio for both clenbuterol (CLB) and its dummy template molecule of phenylephrine (PE) to functional monomer is 1:3, while the optimal imprinting ratio for the two dummy template molecules of CLB&rsquo, s metabolites is 1:5. Choosin gethyleneglycol dimethacrylate (EDGMA) as a crosslinker and aprotic solvents could increase the selectivity of the molecularly imprinted system. Atoms in Molecules (AIM) topology analysis was applied to investigate the template-monomer complexes bonding situation and helped to explain the nature of the reaction in the imprinting process. These theoretical predictions were also verified by the experimental results and found to be in good agreement with the computational results. The computer-simulated imprinting process compensates for the lack of clarity in the mechanism of the molecular imprinting process, and provides an important reference and direction for developing better recognition pattern towards CLB and its metabolite analytes in swine urine samples at the same time.

Water displays a vast array of unique properties, known as water's anomalies, whose origin remains subject to hot debate. Our aim in this article is to provide a unified microscopic physical picture of water's anomalies in terms of locally favored structures, encompassing both thermodynamic and dynamic anomalies, which are often attributed to different origins. We first identify locally favored structures via a microscopic structural descriptor that measures local translational order and provide direct evidence that they have a hierarchical impact on the anomalies. At each state point, the strength of thermodynamic anomalies is directly proportional to the amount of locally favored structures, while the dynamic properties of each molecule depend on the local structure surrounding both itself and its nearest neighbors. To incorporate this, we develop a novel hierarchical two-state model. We show by extensive simulations of two popular water models that both thermodynamic and kinetic anomalies can be almost perfectly explained by the temperature and pressure dependence of these local and non-local versions of the same structural descriptor, respectively. Moreover, our scenario makes three unique predictions in supercooled water, setting it apart from other scenarios: (1) Presence of an "Arrhenius-to-Arrhenius" crossover upon cooling, as the origin of the apparent "fragile-to-strong" transition; (2) maximum of dynamic heterogeneity around 20 K below the Widom line and far above the glass transition; (3) violation of the Stokes-Einstein-Debye relation at ∼2Tg, rather than 1.2Tg typical of normal glass-formers. These predictions are verified by recent measurement of water's diffusion at very low temperatures (point 1) and discoveries from our extensive simulations (points 2-3). We suggest that the same scenario may generally apply to water-like anomalies in liquids tending to form locally favored structures, including not only other important tetrahedral liquids such as silicon, germanium, and silica, but also metallic and chalcogenide liquids.

Heat emitters, as the primary devices used in space heating, cover a fundamental role in the energy efficient use of buildings. In the search for an optimized design, heating devices should be compared with a benchmark emitter with maximum heat emission efficiency. However, such an ideal heater still needs to be defined. In this paper we perform an analysis of heat transfer in a European reference room, considering surface effects of thermal radiation and computing the induced operative temperature (op.t.) both analytically and numerically. Our ideal heater is the one determining the highest op.t. By means of functional optimization, we analyse trends such as the variation of operative temperature with radiator panel dimensions, finding optimal configurations. To make our definitions as general as possible, we address panel radiators, convectors, underfloor (UFH) and ceiling heater. We obtain analytical formulas for the operative temperature induced by panel radiators and identify the 10-type as our ideal radiator, while the UFH provides the best performance overall. Regarding specifically UFH and ceiling heaters, we find optimal sizes providing maximum op.t. The analytical method and qualitative results reported in this paper can be generalized and adopted in most studies concerning the efficiency of different heat emitter types in building enclosures.

We discuss two procedures to obtain empirical potentials from ab initio trajectories. The first method consists in adjusting the parameters of an empirical pair potential so that the radial distribution functions extracted from classical simulations using this potential match the ones extracted from the ab initio simulations. As a case study, we consider the example of amorphous silica, a material that is highly relevant in the field of glass science as well as in geology. With our approach we are able to obtain an empirical potential that gives a better description with respect to structural and thermodynamic properties than the potential proposed by van Beest, Kramer, and van Santen, and that has been very frequently used as a model for amorphous silica. The second method is the so-called “force matching” approach proposed by Ercolessi and Adams to obtain an empirical potential. We demonstrate that for the case of silica this method does not yield a reliable potential and discuss the likely origin for this failure.

In order to estimate theoretical stability of the perovskite structure for synthesized Ca 1− x Gd x MnO 3 ( x = 0.05, 0.1, 0.15, 0.2) nanopowders, the Goldschmidt tolerance factor G t and global instability index GII were calculated. Furthermore, we have performed structure prediction of Ca 1− x Gd x MnO 3 perovskites and found several possible perovskite-related phases. The influence of gadolinium amount on Mn─O bond angles and distances, tilting of MnO 6 octahedra around all three axes and deformation due to the presence of the Jahn–Teller distortion around Mn 3+ cation, as well as the influence of the amount of Mn 3+ cation on Ca 1− x Gd x MnO 3 compound, was examined. Ion Mn valence states were determined by bond valence calculations (BVC). Infrared active phonon modes in Ca 1− x Gd x MnO 3 were studied by infrared reflection spectroscopy and magnetic properties were studied by using EPR (electron paramagnetic resonance) measurements.

We investigated the phenomenon of carbon supersaturation and carbon clustering in bainitic ferrite with atom probe tomography (APT) and ab-initio density functional theory (DFT) calculations. The experimental results show a homogeneous distribution of silicon in the microstructure, which contains both ferrite and retained austenite. This distribution is mimicked well by the computational approach. In addition, an accumulation of C in certain regions of the bainitic ferrite with C concentrations up to 13 at % is observed. Based on the DFT results, these clusters are explained as strained, tetragonal regions in the ferritic bainite, in which the solution enthalpy of C can reach large, negative values. It seems that Si itself only has a minor influence on this phenomenon., APT measurements and analyses were conducted at ORNL's Center for Nanophase Materials Sciences (CNMS), which is a U.S. Department of Energy, Office of Science User Facility. The authors gratefully acknowledge the support of the Research Fund for Coal and Steel for funding this research under the Contract RFSR-CT- 2012-00017.

In perovskite-type strontium titanate (SrTiO 3 ) 〈110〉 dislocations, which are the main carriers of plastic flow at low temperature, lose their mobility as temperature increases, leading to brittle failure above 1050 K. We present theoretical evidence for a change in their core structure into a sessile, climb-dissociated configuration at high temperature. This mechanism is shown to operate in both SrTiO 3 and MgSiO 3 , indicating that it may be a general feature of perovskite-type materials. It follows that the activity of the 〈110〉 slip system depends critically on the strain rate-temperature couple, e T .

Experiments showed that multiwalled carbon nanotubes (MWCNT) can be used as masks gainst irradiation to create metallic nanowires in a substrate. In order to understand the limitations of this application, it is interesting to know the energy and number of carbon atoms emerging from the MWCNT after the irradiation and how the structure of the MWCNT is modified. Using a molecular dynamics code that we have previously developed, we have simulated the continuous irradiation of MWCNT with carbon and argon projectiles. We have obtained that the use of carbon instead of argon to irradiate the MWCNT increases de effectiveness of the MWCNTs as masks, due to the ability of the carbon projectiles to be part of the MWCNT structure and partially mend the damage produced during irradiation. We have analyzed the number, energy, and spatial distribution of the recoils generated during irradiation and the change of the MWCNT structure as a function of the incident energy (100 and 500 eV), fluence (up to 4:5 · 1015 ions=cm2), and number of shells (up to 5-shells) of the MWCNT. These results determine the effectiveness of MWCNT as a mask, being useful to understand whether the atoms emerging from the MWCNT produce damage in the substrate or not. We find that for carbon projectiles the efficiency of MWCNT as masks does not depend much on the fluence, but on the number of nanotube shells and projectile incident energy. On the other hand, for a given nanotube and fluence, we observe a threshold incident energy below which the nanotube acts as a perfect mask. This work has been financially supported by the Spanish Ministerio de Economía y Competitividad and the European Regional Development Fund (Project FIS2010-17225).