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Computation, Volume 6, Issue 4 (December 2018)

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Open AccessArticle Computational Assessment of the Hazardous Release Dispersion from a Diesel Pool Fire in a Complex Building’s Area
Computation 2018, 6(4), 65; https://doi.org/10.3390/computation6040065
Received: 10 November 2018 / Revised: 10 December 2018 / Accepted: 10 December 2018 / Published: 13 December 2018
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Abstract
A hazardous release accident taking place within the complex morphology of an urban setting could cause grave damage both to the population’s safety and to the environment. An unpredicted accident constitutes a complicated physical phenomenon with unanticipated outcomes. This is because, in the
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A hazardous release accident taking place within the complex morphology of an urban setting could cause grave damage both to the population’s safety and to the environment. An unpredicted accident constitutes a complicated physical phenomenon with unanticipated outcomes. This is because, in the event of an unforeseen accident, the dispersion of the hazardous materials exhausted in the environment is determined by unstable parameters such as the wind flow and the complex turbulent diffusion around urban blocks of buildings. Our case study focused on a diesel pool fire accident that occured between an array of nine cubical buildings. The accident was studied with a Large eddy Simulation model based on the Fire Dynamics Simulation method. This model was successfully compared against the nine cubes of the Silsoe experiment. The model’s results were used for the determination of the immediately dangerous to life or health smoke zones of the accident. It was found that the urban geometry defined the hazardous gasses dispersion, thus increasing the toxic mass concentration around the buildings. Full article
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Open AccessArticle Mode Pressure Coefficient Maps as an Alternative to Mean Pressure Coefficient Maps for Non-Gaussian Processes: Hyperbolic Paraboloid Roofs as Cases of Study
Computation 2018, 6(4), 64; https://doi.org/10.3390/computation6040064
Received: 9 November 2018 / Revised: 29 November 2018 / Accepted: 10 December 2018 / Published: 12 December 2018
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Abstract
Wind tunnel experiments are necessary for geometries that are not investigated by codes or that are not generally and parametrically investigated by literature. One example is the hyperbolic parabolic shape mostly used for cable net roofs, for which codes do not provide pressure
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Wind tunnel experiments are necessary for geometries that are not investigated by codes or that are not generally and parametrically investigated by literature. One example is the hyperbolic parabolic shape mostly used for cable net roofs, for which codes do not provide pressure coefficients and literature only gives mean, maxima, and minima pressure coefficient maps. However, most of pressure series acquired in wind tunnels on the roof are not Gaussian processes and, for this reason, the mean values are not precisely representative of the process. The paper investigates the ratio between mean and mode of pressure coefficient series acquired in wind tunnels on buildings covered with hyperbolic paraboloid roofs with square plans. Mode pressure coefficient maps are given as an addition to traditional pressure coefficient maps. Full article
(This article belongs to the Special Issue Computational Methods in Wind Engineering)
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Open AccessReview Unravelling the Potential of Density Functional Theory through Integrated Computational Environments: Recent Applications of the Vienna Ab Initio Simulation Package in the MedeA® Software
Computation 2018, 6(4), 63; https://doi.org/10.3390/computation6040063
Received: 16 October 2018 / Revised: 15 November 2018 / Accepted: 28 November 2018 / Published: 5 December 2018
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Abstract
The development of density functional theory and the tremendous increase of compute power in recent decades have created a framework for the incredible success of modern computational materials engineering (CME). CME has been widely adopted in the academic world and is now established
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The development of density functional theory and the tremendous increase of compute power in recent decades have created a framework for the incredible success of modern computational materials engineering (CME). CME has been widely adopted in the academic world and is now established as a standard tool for industrial applications. As theory and compute resources have developed, highly efficient computer codes to solve the basic equations have been implemented and successively integrated into comprehensive computational environments leading to unprecedented increases in productivity. The MedeA software of Materials Design combines a set of comprehensive productivity tools with leading computer codes such as the Vienna Ab initio Simulation Package (VASP), LAMMPS, GIBBS and the UNiversal CLuster Expansion code (UNCLE), provides interoperability at different length and time scales. In the present review, technological applications including microelectronic materials, Li-ion batteries, disordered systems, high-throughput applications and transition-metal oxides for electronics applications are described in the context of the development of CME and with reference to the MedeA environment. Full article
(This article belongs to the Special Issue Ab Initio Modelling in Solid State Chemistry)
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Open AccessArticle DeepFog: Fog Computing-Based Deep Neural Architecture for Prediction of Stress Types, Diabetes and Hypertension Attacks
Computation 2018, 6(4), 62; https://doi.org/10.3390/computation6040062
Received: 13 October 2018 / Revised: 13 November 2018 / Accepted: 26 November 2018 / Published: 4 December 2018
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Abstract
The use of wearable and Internet-of-Things (IoT) for smart and affordable healthcare is trending. In traditional setups, the cloud backend receives the healthcare data and performs monitoring and prediction for diseases, diagnosis, and wellness prediction. Fog computing (FC) is a distributed computing paradigm
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The use of wearable and Internet-of-Things (IoT) for smart and affordable healthcare is trending. In traditional setups, the cloud backend receives the healthcare data and performs monitoring and prediction for diseases, diagnosis, and wellness prediction. Fog computing (FC) is a distributed computing paradigm that leverages low-power embedded processors in an intermediary node between the client layer and cloud layer. The diagnosis for wellness and fitness monitoring could be transferred to the fog layer from the cloud layer. Such a paradigm leads to a reduction in latency at an increased throughput. This paper processes a fog-based deep learning model, DeepFog that collects the data from individuals and predicts the wellness stats using a deep neural network model that can handle heterogeneous and multidimensional data. The three important abnormalities in wellness namely, (i) diabetes; (ii) hypertension attacks and (iii) stress type classification were chosen for experimental studies. We performed a detailed analysis of proposed models’ accuracy on standard datasets. The results validated the efficacy of the proposed system and architecture for accurate monitoring of these critical wellness and fitness criteria. We used standard datasets and open source software tools for our experiments. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle Coefficient-of-Determination Fourier Transform
Computation 2018, 6(4), 61; https://doi.org/10.3390/computation6040061
Received: 1 August 2018 / Revised: 31 October 2018 / Accepted: 8 November 2018 / Published: 27 November 2018
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Abstract
This algorithm is designed to perform numerical transforms to convert data from the temporal domain into the spectral domain. This algorithm obtains the spectral magnitude and phase by studying the Coefficient of Determination of a series of artificial sinusoidal functions with the temporal
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This algorithm is designed to perform numerical transforms to convert data from the temporal domain into the spectral domain. This algorithm obtains the spectral magnitude and phase by studying the Coefficient of Determination of a series of artificial sinusoidal functions with the temporal data, and normalizing the variance data into a high-resolution spectral representation of the time-domain data with a finite sampling rate. What is especially beneficial about this algorithm is that it can produce spectral data at any user-defined resolution, and this highly resolved spectral data can be transformed back to the temporal domain. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle Finite Element Modellingand Simulations of Piezoelectric Actuators Responses with Uncertainty Quantification
Computation 2018, 6(4), 60; https://doi.org/10.3390/computation6040060
Received: 17 October 2018 / Revised: 13 November 2018 / Accepted: 15 November 2018 / Published: 20 November 2018
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Abstract
Piezoelectric structures are widely used in engineering designs including sensors, actuators, and energy-harvesting devices. In this paper, we present the development of a three-dimensional finite element model for simulations of piezoelectric actuators and quantification of their responses under uncertain parameter inputs. The implementation
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Piezoelectric structures are widely used in engineering designs including sensors, actuators, and energy-harvesting devices. In this paper, we present the development of a three-dimensional finite element model for simulations of piezoelectric actuators and quantification of their responses under uncertain parameter inputs. The implementation of the finite element model is based on standard nodal approach extended for piezoelectric materials using three-dimensional tetrahedral and hexahedral elements. To account for electrical-mechanical coupling in piezoelectric materials, an additional degree of freedom for electrical potential is added to each node in those elements together with their usual mechanical displacement unknowns. The development was validated with analytical and experimental data for a range of problems from a single-layer piezoelectric beam to multiple layer beams in unimorph and bimorph arrangement. A more detailed analysis is conducted for a unimorph composite plate actuator with different design parameters. Uncertainty quantification was also performed to evaluate the sensitivity of the responses of the piezoelectric composite plate with an uncertain input of material properties. This sheds light on understanding the variations in reported responses of the device; at the same time, providing extra confidence to the numerical model. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle Pattern Formation in a Model Oxygen-Plankton System
Computation 2018, 6(4), 59; https://doi.org/10.3390/computation6040059
Received: 22 August 2018 / Revised: 4 November 2018 / Accepted: 5 November 2018 / Published: 14 November 2018
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Abstract
Decreasing level of dissolved oxygen has recently been reported as a growing ecological problem in seas and oceans around the world. Concentration of oxygen is an important indicator of the marine ecosystem’s health as lack of oxygen (anoxia) can lead to mass mortality
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Decreasing level of dissolved oxygen has recently been reported as a growing ecological problem in seas and oceans around the world. Concentration of oxygen is an important indicator of the marine ecosystem’s health as lack of oxygen (anoxia) can lead to mass mortality of marine fauna. The oxygen decrease is thought to be a result of global warming as warmer water can contain less oxygen. Actual reasons for the observed oxygen decay remain controversial though. Recently, it has been shown that it may as well result from a disruption of phytoplankton photosynthesis. In this paper, we further explore this idea by considering the model of coupled plankton-oxygen dynamics in two spatial dimensions. By means of extensive numerical simulations performed for different initial conditions and in a broad range of parameter values, we show that the system’s dynamics normally lead to the formation of a rich variety of patterns. We reveal how these patterns evolve when the system approaches the tipping point, i.e., the boundary of the safe parameter range beyond which the depletion of oxygen is the only possibility. In particular, we show that close to the tipping point the spatial distribution of the dissolved oxygen tends to become more regular; arguably, this can be considered as an early warning of the approaching catastrophe. Full article
(This article belongs to the Special Issue Pattern Formation in Population Dynamics)
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Open AccessArticle The Role of Dimensionality in Understanding Granuloma Formation
Computation 2018, 6(4), 58; https://doi.org/10.3390/computation6040058
Received: 8 October 2018 / Revised: 4 November 2018 / Accepted: 9 November 2018 / Published: 14 November 2018
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Abstract
Within the first 2–3 months of a Mycobacterium tuberculosis (Mtb) infection, 2–4 mm spherical structures called granulomas develop in the lungs of the infected hosts. These are the hallmark of tuberculosis (TB) infection in humans and non-human primates. A cascade of immunological events
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Within the first 2–3 months of a Mycobacterium tuberculosis (Mtb) infection, 2–4 mm spherical structures called granulomas develop in the lungs of the infected hosts. These are the hallmark of tuberculosis (TB) infection in humans and non-human primates. A cascade of immunological events occurs in the first 3 months of granuloma formation that likely shapes the outcome of the infection. Understanding the main mechanisms driving granuloma development and function is key to generating treatments and vaccines. In vitro, in vivo, and in silico studies have been performed in the past decades to address the complexity of granuloma dynamics. This study builds on our previous 2D spatio-temporal hybrid computational model of granuloma formation in TB (GranSim) and presents for the first time a more realistic 3D implementation. We use uncertainty and sensitivity analysis techniques to calibrate the new 3D resolution to non-human primate (NHP) experimental data on bacterial levels per granuloma during the first 100 days post infection. Due to the large computational cost associated with running a 3D agent-based model, our major goal is to assess to what extent 2D and 3D simulations differ in predictions for TB granulomas and what can be learned in the context of 3D that is missed in 2D. Our findings suggest that in terms of major mechanisms driving bacterial burden, 2D and 3D models return very similar results. For example, Mtb growth rates and molecular regulation mechanisms are very important both in 2D and 3D, as are cellular movement and modulation of cell recruitment. The main difference we found was that the 3D model is less affected by crowding when cellular recruitment and movement of cells are increased. Overall, we conclude that the use of a 2D resolution in GranSim is warranted when large scale pilot runs are to be performed and if the goal is to determine major mechanisms driving infection outcome (e.g., bacterial load). To comprehensively compare the roles of model dimensionality, further tests and experimental data will be needed to expand our conclusions to molecular scale dynamics and multi-scale resolutions. Full article
(This article belongs to the Special Issue Computational Modeling in Inflammation and Regenerative Medicine)
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Open AccessArticle NaRIBaS—A Scripting Framework for Computational Modeling of Nanomaterials and Room Temperature Ionic Liquids in Bulk and Slab
Computation 2018, 6(4), 57; https://doi.org/10.3390/computation6040057
Received: 1 October 2018 / Revised: 4 November 2018 / Accepted: 6 November 2018 / Published: 13 November 2018
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Abstract
Computational modeling is more and more often used in studies of novel ionic liquids. The inevitable side-effect is the growing number of similar computations that require automation. This article introduces NaRIBaS (Nanomaterials and Room Temperature Ionic Liquids in Bulk and Slab)—a scripting framework
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Computational modeling is more and more often used in studies of novel ionic liquids. The inevitable side-effect is the growing number of similar computations that require automation. This article introduces NaRIBaS (Nanomaterials and Room Temperature Ionic Liquids in Bulk and Slab)—a scripting framework that combines bash scripts with computational codes to ease modeling of nanomaterials and ionic liquids in bulk and slab. NaRIBaS helps to organize and document all input and output data, thus, improving the reproducibility of computations. Three examples are given to illustrate the NaRIBaS workflows for density functional theory (DFT) calculations of ionic pairs, molecular dynamics (MD) simulations of bulk ionic liquids (ILs), and MD simulations of ILs at an interface. Full article
(This article belongs to the Section Computational Chemistry)
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Open AccessArticle Chelating Mechanisms of Transition Metals by Bacterial Metallophores “Pseudopaline and Staphylopine”: A Quantum Chemical Assessment
Computation 2018, 6(4), 56; https://doi.org/10.3390/computation6040056
Received: 6 September 2018 / Revised: 24 October 2018 / Accepted: 24 October 2018 / Published: 31 October 2018
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Abstract
In bacterial pathology, metallophores fabricated by bacteria such as Staphylococcus aureus and Pseudomonas aeruginosa are exported to surrounding physiological media via a specific process to sequester and import metals, resulting in enhanced virulence of the bacteria. While these mechanisms are understood at qualitative
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In bacterial pathology, metallophores fabricated by bacteria such as Staphylococcus aureus and Pseudomonas aeruginosa are exported to surrounding physiological media via a specific process to sequester and import metals, resulting in enhanced virulence of the bacteria. While these mechanisms are understood at qualitative levels, our investigation presents a complementary original view based on quantum chemical computations. Further understanding of the active centers in particular was provided for pseudopaline and staphylopine metallophores, which were described chemically and with vibration spectroscopy. Then, for complexes formed with a range of transition metal divalent ions (Ni, Cu, and Zn), description and analyses of the frontier molecular orbitals (FMOs) are provided, highlighting a mechanism of metal-to-ligand charge transfer (MLCT), based on excited-states calculations (time-dependent density functional theory (TD-DFT)) at the basis of the delivery of the metallic ionic species to the bacterial medium, leading eventually to its enhanced virulence. Such investigation gains importance especially in view of stepwise syntheses of metallophores in the laboratory, providing significant progress in the understanding of mechanisms underlying the enhancement of bacterial pathologies. Full article
(This article belongs to the Section Computational Chemistry)
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Open AccessArticle Spatial Diversity for CDMA RoFSO Links over M Turbulence Channels with Nonzero Boresight Pointing Errors
Computation 2018, 6(4), 55; https://doi.org/10.3390/computation6040055
Received: 9 September 2018 / Revised: 19 October 2018 / Accepted: 25 October 2018 / Published: 28 October 2018
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Abstract
A CDMA RoFSO link with receivers’ spatial diversity is studied. Turbulence-induced fading, modeled by the M(alaga) distribution, is considered that hamper the FSO link performance along with the nonzero boresight pointing errors effect. Novel, analytical closed-form expressions are extracted for the estimation
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A CDMA RoFSO link with receivers’ spatial diversity is studied. Turbulence-induced fading, modeled by the M(alaga) distribution, is considered that hamper the FSO link performance along with the nonzero boresight pointing errors effect. Novel, analytical closed-form expressions are extracted for the estimation of the average bit-error-rate and the outage probability of the CDMA RoFSO system for both directions of the forward and the reverse link. The numerical results show clearly the performance improvement of using spatial diversity, even in the most adverse atmospheric conditions with strong and saturated atmospheric turbulence with enhanced misalignment. Also, the effects of nonlinear distortion, multiple access interference and clipping noise aggravate the performance of the link, where cases with large number of users are taken into account. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle Computational Analysis of the Performance Characteristics of a Supercritical CO2 Centrifugal Compressor
Computation 2018, 6(4), 54; https://doi.org/10.3390/computation6040054
Received: 16 August 2018 / Revised: 15 October 2018 / Accepted: 17 October 2018 / Published: 19 October 2018
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Abstract
A centrifugal compressor working with supercritical CO2 (S-CO2) has several advantages over other supercritical and conventional compressors. S-CO2 is as dense as the liquid CO2 and becomes difficult to compress. Thus, during the operation, the S-CO2 centrifugal
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A centrifugal compressor working with supercritical CO 2 (S-CO 2 ) has several advantages over other supercritical and conventional compressors. S-CO 2 is as dense as the liquid CO 2 and becomes difficult to compress. Thus, during the operation, the S-CO 2 centrifugal compressor requires lesser compression work than the gaseous CO 2 . The performance of S-CO 2 compressors is highly varying with tip clearance and vanes in the diffuser. To improve the performance of the S-CO 2 centrifugal compressor, knowledge about the influence of individual components on the performance characteristics is necessary. This present study considers an S-CO 2 compressor designed with traditional engineering design tools based on ideal gas behaviour and tested by SANDIA national laboratory. Three-dimensional, steady, viscous flow through the S-CO 2 compressor was analysed with computational fluid dynamics solver based on the finite volume method. Navier-Stokes equations are solved with K- ω (SST) turbulence model at operating conditions in the supercritical regime. Performance of the impeller, the main component of the centrifugal compressor is compared with the impeller with vaneless diffuser and vaned diffuser configurations. The flow characteristics of the shrouded impeller are also studied to analyse the tip-leakage effect. Full article
(This article belongs to the Special Issue Computational Heat, Mass and Momentum Transfer)
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Open AccessArticle Numerical Study on Sloshing Characteristics with Reynolds Number Variation in a Rectangular Tank
Computation 2018, 6(4), 53; https://doi.org/10.3390/computation6040053
Received: 15 August 2018 / Revised: 8 October 2018 / Accepted: 9 October 2018 / Published: 12 October 2018
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Abstract
A study on sloshing characteristics in a rectangular tank, which is horizontally excited with a specific range of the Reynolds number, is approached numerically. The nonlinearity of sloshing flow is confirmed by comparing it with the linear solution based on the potential theory,
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A study on sloshing characteristics in a rectangular tank, which is horizontally excited with a specific range of the Reynolds number, is approached numerically. The nonlinearity of sloshing flow is confirmed by comparing it with the linear solution based on the potential theory, and the time series results of the sloshing pressure are analyzed by Fast Fourier Transform (FFT) algorithm. Then, the pressure fluctuation phenomena are mainly observed and the magnitude of the amplitude spectrum is compared. The results show that, when the impact pressure is generated, large pressure fluctuation in a pressure cycle is observed, and the effects of the frequencies of integral multiples when the fundamental frequency appears dominantly in the sloshing flow. Full article
(This article belongs to the Special Issue Computational Heat, Mass and Momentum Transfer)
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Open AccessArticle Numerical Simulation on Flow Dynamics and Pressure Variation in Porous Ceramic Filter
Computation 2018, 6(4), 52; https://doi.org/10.3390/computation6040052
Received: 6 September 2018 / Revised: 19 September 2018 / Accepted: 20 September 2018 / Published: 20 September 2018
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Abstract
Using five samples with different porous materials of Al2TiO5, SiC, and cordierite, we numerically realized the fluid dynamics in a diesel filter (diesel particulate filter, DPF). These inner structures were obtained by X-ray CT scanning to reproduce the flow
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Using five samples with different porous materials of Al2TiO5, SiC, and cordierite, we numerically realized the fluid dynamics in a diesel filter (diesel particulate filter, DPF). These inner structures were obtained by X-ray CT scanning to reproduce the flow field in the real product. The porosity as well as pore size was selected systematically. Inside the DPF, the complex flow pattern appears. The maximum filtration velocity is over ten times larger than the velocity at the inlet. When the flow forcibly needs to go through the consecutive small pores along the filter’s porous walls, the resultant pressure drop becomes large. The flow path length ratio to the filter wall thickness is almost the same for all samples, and its value is only 1.2. Then, the filter backpressure closely depends on the flow pattern inside the filter, which is due to the local substrate structure. In the modified filter substrate, by enlarging the pore and reducing the resistance for the net flow, the pressure drop is largely suppressed. Full article
(This article belongs to the Section Computational Engineering)
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Open AccessArticle Can Combined Electrostatic and Polarization Effects Alone Explain the F···F Negative-Negative Bonding in Simple Fluoro-Substituted Benzene Derivatives? A First-Principles Perspective
Computation 2018, 6(4), 51; https://doi.org/10.3390/computation6040051
Received: 31 July 2018 / Revised: 9 September 2018 / Accepted: 17 September 2018 / Published: 20 September 2018
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Abstract
The divergence of fluorine-based systems and significance of their nascent non-covalent chemistry in molecular assemblies are presented in a brief review of the field. Emphasis has been placed to show that type-I and -II halogen-centered F···F long-ranged intermolecular distances viable between the entirely
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The divergence of fluorine-based systems and significance of their nascent non-covalent chemistry in molecular assemblies are presented in a brief review of the field. Emphasis has been placed to show that type-I and -II halogen-centered F···F long-ranged intermolecular distances viable between the entirely negative fluorine atoms in some fluoro-substituted dimers of C6H6 can be regarded as the consequence of significant non-covalent attractive interactions. Such attractive interactions observed in the solid-state structures of C6F6 and other similar fluorine-substituted aromatic compounds have frequently been underappreciated. While these are often ascribed to crystal packing effects, we show using first-principles level calculations that these are much more fundamental in nature. The stability and reliability of these interactions are supported by their negative binding energies that emerge from a supermolecular procedure using MP2 (second-order Møller-Plesset perturbation theory), and from the Symmetry Adapted Perturbation Theory, in which the latter does not determine the interaction energy by computing the total energy of the monomers or dimer. Quantum Theory of Atoms in Molecules and Reduced Density Gradient Non-Covalent Index charge-density-based approaches confirm the F···F contacts are a consequence of attraction by their unified bond path (and bond critical point) and isosurface charge density topologies, respectively. These interactions can be explained neither by the so-called molecular electrostatic surface potential (MESP) model approach that often demonstrates attraction between sites of opposite electrostatic surface potential by means of Coulomb’s law of electrostatics, nor purely by the effect of electrostatic polarization. We provide evidence against the standalone use of this approach and the overlooking of other approaches, as the former does not allow for the calculation of the electrostatic potential on the surfaces of the overlapping atoms on the monomers as in the equilibrium geometry of a complex. This study thus provides unequivocal evidence of the limitation of the MESP approach for its use in gaining insight into the nature of reactivity of overlapped interacting atoms and the intermolecular interactions involved. Full article
(This article belongs to the Section Computational Chemistry)
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