Fabrication and application of porous materials made from coal gangue: A review

Coal gangue (CG), which is mainly generated during coal excavation, mining, and coal washing, is an industrial solid waste that is recognized as an environmental pollutant. The ever-increasing amount of CG produced is a serious threat to the ecological environment and property safety, especially in China, which is the largest coal producer and consumer in the world. Considerable studies have investigated means for utilizing CG worldwide. This review summarizes and discusses various porous inorganic materials made from CG, including cement-based porous materials, porous bricks, porous ceramics (cordierite and mullite) and glasses, porous geopolymers, zeolites, aerogels, and porous carbon materials. Different preparation processes and performances of each type of porous inorganic materials were reviewed. Porous CG-based materials can be used as promising adsorbents for the removal of various pollutants and have good potential for use in construction industry as well as catalyst material applications. Besides, porous materials obtained from CG have also been tested as slow-release fertilizers after the absorption of phosphate, as electrode materials, and as oil-in-water separation agents. The systematic summary of porous materials based on CG aims at promoting high-value-added applications for this waste. Future research directions for the use of CG as a raw material are also presented.     

Multi-scale models for cross-linked sulfonated poly (1, 3-cyclohexadiene) polymer

Atomistic and coarse-grained (CG) models of cross-linked sulfonated Poly (1, 3-cyclohexadiene) (xsPCHD) were developed and implemented in Molecular Dynamics (MD) simulations of PCHD chains with different architectures. In the atomistic model, PCHD chains are cross linked by a sulfur–sulfur bond. Sulfonic acid groups are evenly distributed along the chain. The architecture is specifically aimed for application as a proton exchange membrane used in fuel cells. An atomistic force field for this architecture was tested and applied in the atomistic MD simulation of xsPCHD for the first time. The atomistic simulations generate the density and cross-linker separation distribution. To further study the structural properties of longer chain systems, a CG model was proposed. The bonded structural probability distribution functions (PDFs) and non-bonded pair correlation function (PCF) of the CG beads were obtained from the atomistic simulation results. The bonded CG potentials are obtained by simple inversion of the corresponding PDFs. The CG non-bonded potential is parameterized to the PCF using the Iterative Boltzmann Inversion (IBI) method. The CGMD simulations of xsPCHD chains using potentials from above method satisfactorily reproduce the structural properties from atomistic MD simulation of the same system. The transferability of the CG potentials has been further tested through CGMD simulation of xsPCHD homopolymer with different architectures.     

Study of Materials Deformation in Nanometric Cutting by Large-scale Molecular Dynamics Simulations

Nanometric cutting involves materials removal and deformation evolution in the surface at nanometer scale. At this length scale, atomistic simulation is a very useful tool to study the cutting process. In this study, large-scale molecular dynamics (MD) simulations with the model size up to 10 millions atoms have been performed to study three-dimensional nanometric cutting of copper. The EAM potential and Morse potential are used, respectively, to compute the interaction between workpiece atoms and the interactions between workpiece atoms and tool atoms. The material behavior, surface and subsurface deformation, dislocation movement, and cutting forces during the cutting processes are studied. We show that the MD simulation model of nanometric cutting has to be large enough to eliminate the boundary effect. Moreover, the cutting speed and the cutting depth have to be considered in determining a suitable model size for the MD simulations. We have observed that the nanometric cutting process is accompanied with complex material deformation, dislocation formation, and movement. We find that as the cutting depth decreases, the tangential cutting force decreases faster than the normal cutting force. The simulation results reveal that as the cutting depth decreases, the specific cutting force increases, i.e., “size effect” exists in nanometric cutting.     

液氩沿纳米级微通道流动的模拟:外力的影响

Liquid argon flow along a nanochannel is studied using molecular dynamics (MD) simulation in this work. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is used as the MD simulator. The effects of reduced forces at 0.5, 1.0 and 2.0 on argon flow on system energy in the form of system potential energy, pressure and velocity profile are described. Output in the form of three-dimensional visualization of the system at steady-state condition using Visual Molecular Dynamics (VMD) is pro-vided to describe the dynamics of the argon atoms. The equilibrium state is reached after 16000 time steps. The effects on system energy, pressure and velocity profile due to reduced force of 2.0 (F2) are clearly distinguishable from the other two lower forces where sufficiently high net force along the direction of the nanochannel for F2 renders the attractive and repulsive forces between the argon atoms virtually non-existent. A reduced force of 0.5 (F0.5) provides liquid argon flow that approaches Poiseuille (laminar) flow as clearly shown by the n-shaped average velocity profile. The extension of the present MD model to a more practical application affords scientists and engineers a good option for simulation of other nanofluidic dynamics processes.     

Characterization and criteria of phase transformations and lattice slipping in potassium dihydrogen phosphate crystals

Being an important nonlinear optical material, potassium dihydrogen phosphate (KDP) has been widely used in many technological fields such as laser frequency conversion and high-speed Q-switching. Nevertheless, KDP is one of the most difficult-to-handle materials because it is prone to phase transformations under mechanical loading during component fabrication. This study investigated the mechanisms of phase transformations and microstructural lattice slipping in KDP with the aid of molecular dynamics (MD) analysis. A fundamental structural characterization method was established to identify the structural changes, enabling the determination of the corresponding trigger criteria. The results showed that various phase transformations can be initiated under a range of mechanical loading conditions. Microstructural lattice slipping can be nucleated via different mechanisms. These findings provide insights for developing damage-free manufacturing processes of ultraprecision KDP components.     

Multiscale Genome Modeling for Predicting the Thermal Conductivity of Silicon Carbide Ceramics

Silicon carbide (SiC) ceramics have been widely used in industry due to its high thermal conductivity. Understanding the relations between the microstructure and the thermal conductivity of SiC ceramics is critical for improving the efficiency of heat removal in heat sink applications. In this paper, a multiscale model is proposed to predict the thermal conductivity of SiC ceramics by bridging atomistic simulations and continuum model via a materials genome model. Interatomic potentials are developed using ab initio calculations to achieve more accurate molecular dynamics (MD) simulations. Interfacial thermal conductivities with various additive compositions are predicted by nonequilibrium MD simulations. A homogenized materials genome model with the calculated interfacial thermal properties is used in a continuum model to predict the effective thermal conductivity of SiC ceramics. The effects of grain size, additive compositions, and temperature are also studied. The good agreement found between prediction results and experimental measurements validates the capabilities of the proposed multiscale genome model in understanding and improving the thermal transport characteristics of SiC ceramics.     

Development and verification of coarse-grain CFD-DEM for nonspherical particles in a gas–solid fluidized bed

Computational fluid dynamics coupled with discrete element method (CFD-DEM) has been widely used to understand the complicated fundamentals inside gas–solid fluidized beds. To realize large-scale simulations, CFD-DEM integrated with coarse-grain model (CG CFD-DEM) provides a feasible solution, and has led to a recent upsurge of interest. However, when dealing with large-scale simulations involving irregular-shaped particles such as biomass particles featuring elongated shapes, current CG models cannot function as normal because they are all developed for spherical particles. To address this issue, a CG CFD-DEM for nonspherical particles is proposed in this study, and the morphology of particles is characterized by the super-ellipsoid model. The effectiveness and accuracy of CG CFD-DEM for nonspherical particles are comprehensively evaluated by comparing the hydrodynamic behaviors with the results predicted by traditional CFD-DEM in a gas–solid fluidized bed. It is demonstrated that the proposed model can accurately model gas–solid flow containing nonspherical particles, merely the particle dynamics are somewhat lost due to the scaleup of particle size. Finally, the calculation efficiency of CG CFD-DEM is assessed, and the results show that CG CFD-DEM can largely reduce computational costs mainly by improving the calculation efficiency of DEM. In general, the proposed CG CFD-DEM for nonspherical particles strikes a good balance between efficiency and accuracy, and has shown its prospect as a high-efficiency alternative to traditional CFD-DEM for engineering applications involving nonspherical particles.     

Understanding macroscopic diffusion of adsorbed molecules in crystalline nanoporous materials via atomistic simulations

The diffusion rates of molecules inside nanoporous materials lie at the heart of many large-scale industrial applications of these materials. Quantitatively describing this diffusion, particularly diffusion of chemical mixtures in situations leading to net mass transport, remains challenging. Molecular dynamics (MD) simulations can play an important complementary role to experiments in this area. This Account describes applications of MD to diffusion in nanoporous materials with a particular focus on macroscopic diffusion, that is, diffusion involving mass transport. These methods have made useful contributions to developing mixing theories for predicting multicomponent diffusion from single-component data and to screening new classes of materials for practical applications.     

MARTINI coarse-grained model for poly-ε-caprolactone in acetone-water mixtures

In this work we present the development of a MARTINI-type coarse-graining (CG) model for poly-ε-caprolactone (PCL) dissolved in a solvent binary mixture of acetone and water. A thermodynamic/conformational procedure is adopted to build up the CG model of the system, starting from the standard MARTINI force field. The single CG bead is parametrized upon solvation free energy calculations, whereas the conformation of the whole polymer chain is optimized using the radius of gyration values calculated at different chain lengths. The model is then able to reproduce the correct thermodynamics of the system, as well as the conformation of single PCL chains, especially in pure water and acetone. The results obtained here are then used to simulate the interactions between multiple longer PCL chains in solution. The model developed here can be used in the future to achieve deeper insight into the dynamics of the polymer self-assembly.     

A Generic Force Field for Protein Coarse-Grained Molecular Dynamics Simulation

Coarse-grained (CG) force fields have become promising tools for studies of protein behavior, but the balance of speed and accuracy is still a challenge in the research of protein coarse graining methodology. In this work, 20 CG beads have been designed based on the structures of amino acid residues, with which an amino acid can be represented by one or two beads, and a CG solvent model with five water molecules was adopted to ensure the consistence with the protein CG beads. The internal interactions in protein were classified according to the types of the interacting CG beads, and adequate potential functions were chosen and systematically parameterized to fit the energy distributions. The proposed CG force field has been tested on eight proteins, and each protein was simulated for 1000 ns. Even without any extra structure knowledge of the simulated proteins, the Cα root mean square deviations (RMSDs) with respect to their experimental structures are close to those of relatively short time all atom molecular dynamics simulations. However, our coarse grained force field will require further refinement to improve agreement with and persistence of native-like structures. In addition, the root mean square fluctuations (RMSFs) relative to the average structures derived from the simulations show that the conformational fluctuations of the proteins can be sampled.     

SCOPE AND LIMITS OF MOLECULAR SIMULATIONS

We briefly review the basic tenets of the two most popular methods of molecular simulation, molecular dynamics (MD) and Monte Carlo (MC), highlighting their strengths and limitations. As an illustration, two typical examples from the authors' work are presented: first, selected results from equilibrium molecular dynamics (MD) simulation studies of model liquid-liquid interfaces, then characteristic data obtained for bulk water and aqueous solutions at ambient conditions. We demonstrate the two basic types of thermodynamic averages that can be obtained from these simulations: time-independent, or “structural,” averages and averages involving the evolution of the system in time (often loosely called “dynamic”).     

Restrained Molecular Dynamics Procedure for Protein Tertiary Structure Determination from NMR Data: A Lac Repressor Headpiece Structure Based on Information on J-coupling and from Presence and Absence of NOE's

In recent years a procedure has been developed by which the three-dimensional (3D) structure of biomolecules can be derived from 2D NMR data. This procedure combines model building with restrained energy minimization (EM) and molecular dynamics (MD) techniques. Distance information from NOE's is incorporated in the form of an upper limit distance restraining term that is added to the interatomic potential function. Here, two improvements of the refinement procedure are introduced. First, the information that is contained in empty parts of 2D-NOE spectra is transformed into, so-called, non-NOE's which are modelled by adding a lower limit distance restraining term to the potential function for each non-NOE proton pair. Secondly, the information that is contained in the occurrence of large J-coupling constants for specific dihedrals is modelled by adding a sinusoidal dihedral angle restraining term to the potential function for each dihedral angle with a large J-value. The improved refinement procedure is tested by application of the lac repressor headpiece. Both the inclusion of non-NOE data and the inclusion of J-coupling information markedly improve the result of the restrained MD refinement of headpiece. In the refinement procedure MD simulation is used for searching configuration space. Energy barriers which are too high to be crossed by MD are surmounted by manually changing the model structures on a picture system. The resulting close non-bonded contacts are relaxed by EM. The final structure of headpiece satisfies essentially all 169 NOE and 9529 non-NOE distance constraints as well as the 6C_α – C_β dihedral angle values corresponding to the measured J-coupling values.     

Application of Molecular Dynamics Simulations in the Analysis of Cyclodextrin Complexes

Cyclodextrins (CDs) are highly respected for their ability to form inclusion complexes via host–guest noncovalent interactions and, thus, ensofance other molecular properties. Various molecular modeling methods have found their applications in the analysis of those complexes. However, as showed in this review, molecular dynamics (MD) simulations could provide the information unobtainable by any other means. It is therefore not surprising that published works on MD simulations used in this field have rapidly increased since the early 2010s. This review provides an overview of the successful applications of MD simulations in the studies on CD complexes. Information that is crucial for MD simulations, such as application of force fields, the length of the simulation, or solvent treatment method, are thoroughly discussed. Therefore, this work can serve as a guide to properly set up such calculations and analyze their results.     

Multiscale Modeling of Amyloid Fibrils Formed by Aggregating Peptides Derived from the Amyloidogenic Fragment of the A-Chain of Insulin

Computational prediction of molecular structures of amyloid fibrils remains an exceedingly challenging task. In this work, we propose a multi-scale modeling procedure for the structure prediction of amyloid fibrils formed by the association of ACC_1-13 aggregation-prone peptides derived from the N-terminal region of insulin’s A-chain. First, a large number of protofilament models composed of five copies of interacting ACC_1-13 peptides were predicted by application of CABS-dock coarse-grained (CG) docking simulations. Next, the models were reconstructed to all-atom (AA) representations and refined during molecular dynamics (MD) simulations in explicit solvent. The top-scored protofilament models, selected using symmetry criteria, were used for the assembly of long fibril structures. Finally, the amyloid fibril models resulting from the AA MD simulations were compared with atomic force microscopy (AFM) imaging experimental data. The obtained results indicate that the proposed multi-scale modeling procedure is capable of predicting protofilaments with high accuracy and may be applied for structure prediction and analysis of other amyloid fibrils.     

Behavior of Atoms at the Surface of a K2O · 3siO2 Glass—A Molecular Dynamics Simulation

Recent ion scattering spectroscopy (ISS) studies indicate that an excess of K ions occurs at the surface of a K₂O · 3SiO₂ glass. Molecular dynamics (MD) computer simulations were used to evaluate the short-time dynamic behavior of atoms at the surface of such a glass in order to determine a mechanism for the K ion enrichment. In the simulations, a bulk glass of several hundred atoms was melted using three-dimensional periodic boundary conditions, and subsequently quenched to lower temperatures. Periodic boundary conditions were removed in one dimension near room temperature so as to create free surfaces. The distribution of species perpendicular to the free surface was determined. The MD simulations show that K ions can build up at the outermost surface of the glass within several picoseconds after formation of the surface.     

Molecular dynamics simulations of the effect of the volume fraction on unidirectional polyimide–carbon nanotube nanocomposites

Molecular dynamics (MD) simulations were used to predict the effect of the reinforcement volume fraction on a unidirectional nanocomposite comprised of a polyimide and multi-walled carbon nanotubes (MWCNTs). We derived a modified volume fraction equation that takes the interface into account, and thus can precisely calculate the volume fraction of the reinforcement. From the MD simulations, both the stress and the modulus are predicted to increase with increasing number of MWCNTs as a function of a constantly applied strain, although some interesting observations were made in comparison to a pure polyimide system that is ordered, akin to the pre-nucleated crystalline system. In addition, we developed an approach to indirectly predict the change in the degree of order in the matrix with the addition of the CNT reinforcements. The results suggest that the degree of ordering increases with an increase in the volume fraction of MWCNTs, especially at the polymer–CNT interface according to number density plots of the polymer, which is consistent with the hypothesis that CNTs can act as nucleation sites for the crystallization of the polymer matrix.     

Atomistic Investigation on the Effects of Thermal Loading on Interfacial Adhesion of Dissimilar Materials

Heat transfer has a large effect on the adhesion and the corresponding failure at material interfaces. When a system becomes extremely small, the conventional finite element method is not capable of accurately capturing all the information, and precise modeling of interfacial properties is essential. In this paper, molecular dynamics (MD) simulations are used to investigate the effects of heat transfer on the adhesion properties of material interfaces. For Al–W and Cr–W interfaces, the interfacial strengths are calculated by MD simulations and are compared with the critical loads obtained from scratch tests. Both the results of MD simulations and experiments show that the interfacial strength of an Al–W interface is larger than that for a Cr–W interface; and furthermore, the Cr–W interface is more sensitive to thermal loading than the Al–W interface. In this work we concluded that the proposed MD model can be used to estimate interfacial adhesion under the effects of heat transfer.     

A pore network model for diffusion in nanoporous carbons: Validation by molecular dynamics simulation

A hybrid molecular dynamics simulation/pore network model (MD/PNM) approach is developed for predicting diffusion in nanoporous carbons. This approach is computationally fast, and related to the structure of the real material. The PNM takes into account both the geometrical (a distribution of pore sizes) and topological (the pore network connectivity) characteristics of nanoporous carbons, which are obtained by analysing adsorption data. The effective diffusion coefficient is calculated by taking the transport diffusion coefficients in single slit-shaped model pores from MD simulation and then computing the effective value over the PNM. The reliability of this approach is evaluated by comparing the results of the PNM analysis with a more rigorous, but much slower, simulation applied to a realistic model material, the virtual porous carbon (VPC). We obtain good agreement between the diffusion coefficients for the PNM and the VPC, indicating the reliability of the hybrid MD/PNM method and it can be used in industry for materials design.     

Molecular dynamics modeling of the structure, dynamics and energetics of mineral-water interfaces: Application to cement materials

This paper reviews molecular modeling studies of water structure in nano-confinement and at fluid-solid interfaces and presents new molecular dynamics (MD) modeling results for water on the surface of tobermorite. MD modeling provides detailed information about the structure, dynamics and energetics of water at solid surfaces and in confinement that can add significant additional molecular scale insight to experimental results. For the tobermorite (001) surface the results show strong structuring of water in the channels between the drietkette silicate chains and above the surface due to the development of an integrated H-bond network involving the water and the surface sites. Calculated diffusion coefficients for the surface-associated water are in good agreement with published experimental results.     

Investigation of hygroscopic properties in electronic packages using molecular dynamics simulation

Moisture-induced package failures such as interfacial delamination and pop-corn cracking are common failure phenomena that occur during the solder reflow process in the semiconductor industry. Therefore, the hygroscopic properties of the package materials are crucial factors in the reliability of electronic packaging products. In this work, molecular dynamics (MD) simulation was performed to study the hygroscopic properties, including diffusivity and swelling strain, of epoxy materials with respect to temperature and moisture concentration. Hygroscopic material properties predicted by MD are discussed and compared with the experimental data.