Molecular Dynamics Simulation Package Research Articles

The effect of constant electric field on the crack growth process of aluminum nanosheet using molecular dynamics simulation

Aluminum nanosheets are a form of Al nanoparticle that have been recently manufactured on an industrial scale and have a variety of uses. Al nanoparticles are extensively used in a variety of sectors, including aerospace, construction, medical, chemistry, and marine industries. Crack propagation in various constructions must be investigated thoroughly for structural design purposes. Cracks in nanoparticles may occur during the production of nanosheets (NSs) or when different mechanical or thermal pressures were applied. In this work, the effect of a continuous electric field on the fracture formation process of aluminum nanosheets was investigated. For this study, molecular dynamics simulation and LAMMPS software were used. The effects of various electric fields on several parameters, including as stress, velocity (Velo), and fracture length, were explored, and numerical data were retrieved using software. The results show that the amplitude of the electric field parameter affected the atomic development of modeled Al nanosheets throughout the fracture operation. This effect resulted in atomic resonance (amplitude) fluctuations, which affected the mean interatomic forces and led the temporal evolution of atoms to converge to certain specified initial conditions. The crack length in our modeled samples ranged from 22.88 to 32.63 Å, depending on the electric field parameter (0.1–1 V/Å). Finally, it was determined that the crack growth of modeled Al nanosheets may be controlled using CEF parameters in real-world situations.

LUNAR: Automated Input Generation and Analysis for Reactive LAMMPS Simulations.

Generating simulation-ready molecular models for the LAMMPS molecular dynamics (MD) simulation software package is a difficult task and impedes the more widespread and efficient use of MD in materials design and development. Fixed-bond force fields generally require manual assignment of atom types, bonded interactions, charges, and simulation domain sizes. A new LAMMPS pre- and postprocessing toolkit (LUNAR) is presented that efficiently builds molecular systems for LAMMPS. LUNAR automatically assigns atom types, generates bonded interactions, assigns charges, and provides initial configuration methods to generate large molecular systems. LUNAR can also incorporate chemical reactivity into simulations by facilitating the use of the REACTER protocol. Additionally, LUNAR provides postprocessing for free volume calculations, cure characterization calculations, and property predictions from LAMMPS thermodynamic outputs. LUNAR has been validated via building and simulation of pure epoxy and cyanate ester polymer systems with a comparison of the corresponding predicted structures and properties to benchmark values, including experimental results from the literature. LUNAR provides the tools for the computationally driven development of next-generation composite materials in the Integrated Computational Materials Engineering (ICME) and Materials Genome Initiative (MGI) frameworks. LUNAR is written in Python with the usage of NumPy and can be used via a graphical user interface, a command line interface, or an integrated design environment. LUNAR is freely available via GitHub.

Investigating the effect of heat flux on tetracycline absorption by bio-MOF-11 nanostructure: A molecular dynamics approach

Tetracycline is a type of antibiotic that falls under the category of antibiotics. Studying the absorption process of Tetracycline by bio-MOF-11 carrier is important for enhancing drug delivery efficiency, optimizing dosage, and increasing bioavailability, ultimately improving treatment outcomes and potentially leading to the development of new therapies. The present study examined the effect of variable amplitude heat flux (HF) on the bio-MOF-11 carriers' ability to absorb tetracycline. Various parameters were assessed and documented using molecular dynamics simulation and LAMMPS software, including the mean square displacement, number of drug particles, diffusion coefficient, and interaction energy. The results show that by increasing heat flux to 0.04 W/m2, the interaction energy became more negative, decreasing from −1376.35 to −1549.35 kcal/mol. Both mean square displacement and diffusion coefficient increased from 72.906 Å2 and 75.69 28 nm2/ns to 79.745 Å2 and 83.28 nm2/ns, respectively. Also, the number of penetrated Tetracycline-Drug in bio-MOF-11 carriers increased to 606, but it decreased to 520 with a further increase in HF to 0.08 W/m2. The different ways that heat affected adsorption process within the MOF structure may be the cause of this change. The first improvement in penetration can be a sign of improved drug binding and mobility at a moderate HFA. In contrast, the subsequent decrease at higher HFA levels could suggest that excessive heat disrupts the adsorption mechanism, potentially affecting the stability and efficiency of drug delivery within the system.

Implementation of Girsanov Reweighting in OpenMM and Deeptime.

Classical molecular dynamics (MD) simulations provide invaluable insights into complex molecular systems but face limitations in capturing phenomena occurring on time scales beyond their reach. To bridge this gap, various enhanced sampling techniques have been developed, which are complemented by reweighting techniques to recover the unbiased dynamics. Girsanov reweighting is a reweighting technique that reweights simulation paths, generated by a stochastic MD integrator, without evoking an effective model of the dynamics. Instead, it calculates the relative path probability density at the time resolution of the MD integrator. Efficient implementation of Girsanov reweighting requires that the reweighting factors are calculated on-the-fly during the simulations and thus needs to be implemented within the MD integrator. Here, we present a comprehensive guide for implementing Girsanov reweighting into MD simulations. We demonstrate the implementation in the MD simulation package OpenMM by extending the library openmmtools. Additionally, we implemented a reweighted Markov state model estimator within the time series analysis package Deeptime.

Improving the Synthesis Efficiency of Amino Acids by Analyzing the Key Sites of Intracellular Self-Assembly of Artificial Cellulosome

To explore the key sites affecting the intracellular assembly of key components of cellulosomes and obtain DocA mutants independent of Ca2+, Swiss-model, GROMACS, PyMOL, and other molecular dynamics simulation software were used for modeling and static and dynamic combination analysis. Site-specific mutation technology was used to mutate DocA, and Biacore was used to test the dependence of Ca2+ on the binding ability of protein DocA mutants and protein Coh, and to analyze the interaction and binding effect of mutant proteins in vitro. Forward intracellular mutant screening was performed based on semi-rational design and high throughput screening techniques. The orientation of mutations suitable for intracellular assembly was determined, and three directional mutant proteins, DocA-S1, DocA-S2, and DocA-S3, were obtained. Ca2+ independent DocA mutants were obtained gradually and their potential interaction mechanisms were analyzed. In the present study, intracellular self-assembly of key components of cellulosomes independent of Ca2+ was achieved, and DocA-S3 was applied to the assembly of key enzymes of L-lysine biosynthesis, in which DapA and DapB intracellular assembly increased L-lysine accumulation by 29.8% when compared with the control strains, providing a new strategy for improving the intracellular self-assembly of cellulosomes and amino acid fermentation efficiency.

Enhancing piezoelectric performance of CNTs through B and N substitution under combined mechanical loads: insights from MD simulations

The piezoelectric properties of carbon nanotubes (CNTs) doped with boron (B) and nitrogen (N) were studied using the classical molecular dynamics (MD) simulation software package large scale atomic/molecular massively parallel simulator. The interactions among the nanotube atoms C, N, and B were calculated using the Tersoff potential. MD simulations were performed to observe the changes in the piezoelectric coefficient of the doped CNTs under loading conditions like tension, torsion, and a combination of both. We considered a wide range of chirality to determine the influence of structural variation on the piezoelectric effect. The study revealed that B-CNTs exhibit superior piezoelectric coefficients compared to N-CNTs, indicating the significant role of dopant type. Moreover, under tensile loading, zigzag-oriented B-CNTs showed higher piezoelectric coefficients with a maximum e33 = 0.2441 C m−2, whereas under torsional loading, armchair-oriented B-CNTs showed enhanced response with a maximum e36 = 0.0564 C m−2. A notable observation was that under combined loading conditions (tensile and torsional), the piezoelectric behavior of the B-CNTs was dependent on the nanotube’s chirality and did not yield a linear additive response. The polarization induced under combined loading in most of the doped CNTs is significantly higher than the sum of polarization generated under tensile and torsional loading conditions. This behavior suggests that the overall piezoelectric effect under combined loading can be enhanced, which emphasizes the need for an approach to optimize the mechanical loading condition. The results showcase the potential of B-/N-CNTs to be engineered for efficient performance by demonstrating that tailored mechanical loading can enhance the piezoelectric responses in doped CNTs, opening a pathway for highly functional and efficient nanoscale piezoelectric devices.

Investigating the effect of pH on the swelling process, mechanical and thermal attributes of polyacrylamide hydrogel structure: A molecular dynamics study

Stimuli-responsive hydrogels are a class of hydrogels that undergo reversible changes in their physical or chemical properties in response to specific external stimuli. The pH is a critical environmental stimulus for stimuli-responsive hydrogels. When the pH of the surrounding environment changes, it can lead to significant alterations in the properties of the hydrogel, such as swelling behavior, mechanical strength, etc. So, understanding how pH affects the swelling behavior and mechanical properties of these hydrogels is crucial to optimize their performance in biomedical applications. Therefore, in the present study, the effect of pH on the swelling process, mechanical and thermal attributes of polyacrylamide hydrogel structure were studied using molecular dynamics simulation and LAMMPS software. The results reveal that as the pH increased from 2 to 11, the structural volume increased from 342,583 to Å3. The increase in the volume of the structure was in terms of the increase in atomic fluctuations by increasing the pH, and consequently, it led to more swelling. The mechanical properties show that the ultimate strength and Young’s modulus of the sample increase from 0.0298 to 0.0007 to 0.0359 and 0.0012 MPa, respectively. The reason for the increase in these parameters was that by increasing the pH, the attraction force among different components of the PAM hydrogel structure increased. This issue led to an increase in the stability of the nanostructure. Finally, the thermal properties showed that thermal conductivity increased from 0.51 to 0.62 W/m K by increasing pH to 11. The findings may lead to the development of pH-responsive hydrogels with enhanced properties, offering more effective and tailored solutions for biomedical applications.

Multiscale modeling of unfolding and bond dissociation of rubredoxin metalloprotein

Mechanical properties of proteins that have a crucial effect on their operation. This study used a molecular dynamics simulation package to investigate rubredoxin unfolding on the atomic scale. Different simulation techniques were applied, and due to the dissociation of covalent/hydrogen bonds, this protein demonstrates several intermediate states in force-extension behavior. A conceptual model based on the cohesive finite element method was developed to consider the intermediate damages that occur during unfolding. This model is based on force-displacement curves derived from molecular dynamics results. The proposed conceptual model is designed to accurately identify bond rupture points and determine the associated forces. This is achieved by conducting a thorough comparison between molecular dynamics and cohesive finite element results. The utilization of a viscoelastic cohesive zone model allows for the consideration of loading rate effects. This rate-dependent model can be further developed and integrated into the multiscale modeling of large assemblies of metalloproteins, providing a comprehensive understanding of mechanical behavior while maintaining a reduced computational cost.

Preparation of Crust Type Dust Suppression Gel Based on Plant Extraction Technology for Ginkgo biloba Leaves: Characterization, Properties, and Function Mechanism

The coal industry plays an essential role in China’s economic development, and issues such as occupational health and environmental pollution caused by coal dust have attracted a great deal of attention. In accordance with the principles of environmental protection and waste management, this study used carboxymethyl ginkgo cellulose (CL) extracted and modified from Ginkgo biloba leaves as a matrix, and a graft copolymerized with sodium 3-allyloxy-1-hydroxy-1-propanesulfonate (AHPS) and N-isopropylacrylamide (NIPAM) monomers to prepare low-cost, environmentally friendly, and high-performance coal dust suppression (C-A-N). By optimizing fitting experimental data through three factors and two response surface analyses, the optimal dust suppression efficiency ratio was determined to be 4:8:5, and its swelling and water retention properties were analyzed. The microstructure, chemical reaction process, combustion performance and crusting property of the dust suppression gel were analyzed using Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetry (TG), scanning electron microscopy (SEM), cone calorimetry, and consolidation layer strength tests. Relevant experiments show that the dust suppression gel prepared in this study has the characteristics of a strong wettability and minor impacts on the calorific value of coal, as well as green and environmental protection. When the wind speed is 10 m/s, the dust suppression effect reaches 93%, and the hardness of the solidified layer reaches 39.6 KPa. This study analyzed the migration and combination of functional groups in the interaction system using molecular dynamics simulation software. The microscopic effect and mechanism between dust suppression gel and coal are revealed from a molecular point of view. The feasibility and accuracy of the molecular dynamics simulation were verified by the consistency between simulation results and experimental data. Therefore, combining the utilization of waste resources with dust suppression can have important economic and social benefits.

SpaiNN: equivariant message passing for excited-state nonadiabatic molecular dynamics.

Excited-state molecular dynamics simulations are crucial for understanding processes like photosynthesis, vision, and radiation damage. However, the computational complexity of quantum chemical calculations restricts their scope. Machine learning offers a solution by delivering high-accuracy properties at lower computational costs. We present SpaiNN, an open-source Python software for ML-driven surface hopping nonadiabatic molecular dynamics simulations. SpaiNN combines the invariant and equivariant neural network architectures of SchNetPack with SHARC for surface hopping dynamics. Its modular design allows users to implement and adapt modules easily. We compare rotationally-invariant and equivariant representations in fitting potential energy surfaces of multiple electronic states and properties arising from the interaction of two electronic states. Simulations of the methyleneimmonium cation and various alkenes demonstrate the superior performance of equivariant SpaiNN models, improving accuracy, generalization, and efficiency in both training and inference.

Study on the Effect of Nano Pour Point Depressant on Wax Oil Crystallization

The influence of nano pour point depressant (NPPD) on crude oil containing wax is primarily manifested through their interaction with the wax constituents. This study examines the depressant's effects using a polarizing microscope and an atomic force microscope (AFM) to assess morphological and structural changes in the wax crystals within the oil, both before and after the addtion of the NPPD. Additionally, a surface tensiometer measured surface tension, while a rheometer evaluated viscosity and modulus alterations. These methods facilitated insights into NPPD's mechanistic effects. The interaction process between crude oil wax crystal molecules and the main components of NPPD was simulated using JOCTA molecular dynamics simulation software, and the highest interaction strength between benzenesulfonic acid groups and crude oil wax crystal molecules was determined. The findings indicate that the addition of the NPPD alters the growth patterns and crystalline structure of the wax in the oil. Initially, the wax crystals present as flaky, predominantly single molecular layer lamellae with a thickness of approximately 100 nm. Post-treatment, the wax crystals adopt a flattened lamellar configuration, composed of multilayer lamellae, with a reduced thickness of within 10 nm and exhibiting short-range order. AFM height maps reveal an increase in the average roughness of the wax oil correlated with the addition of the NPPD across different sampling lengths. Surface tension measurements demonstrate that the wax oil doped with the NPPD exhibits lower surface tension than undoped oil, with the surface tension decreasing as the temperature increases.

Transplantation and optimization of molecular dynamics simulation on MT-3000

Molecular dynamics (MD) simulation is a research method to simulate the change of particle systems with the help of the powerful calculating power of computers. As the number of atoms increases and the duration of the simulation system extends, current mainstream software for MD simulations has become increasingly strained. This is largely due to a surge in computing time, attributed to the architecture characteristics of the central processing unit (CPU), which executes instructions serially and accesses shared memory randomly. These features have resulted in an enormous overhead that these software applications can no longer efficiently manage. Recently, National University of Defense Technology proposed the MT-3000 processor, a multi-zone heterogeneous architecture with a double-precision peak performance of 11.5 TFLOPS. In this paper, we implement the heterogeneous transplantation and optimization of the massively parallel program for MD simulation on Tianhe new-generation supercomputer based on MT-3000. By porting the key computing hotspot module to the acceleration zones of MT-3000, we have greatly improved the efficiency and performance of the simulation of billion-metal-atom cascade collision. The experimental results show that the heterogeneous MD program on a single node can achieve about 6 times faster than the original version executed in a general purpose zone of MT-3000. On the basis of 250 thousand cores, the strong-scalability parallel efficiency of heterogeneous MD program using 4 million cores can reach 89.89%, and the weak-scalability parallel efficiency can reach 91.98%. It can be predicted that the heterogeneous MD implementation has excellent scaling ability to simulate large-scale atomic cascade collisions on ten million of cores.

Preparation of barium sulfate chelating agent DTPA-5Na and molecular dynamics simulation of chelating mechanism.

Barium sulfate (BaSO4) scale is dense and hard, making it difficult to remove using conventional acid and alkali treatments. Diethylenetriaminepentaacetic acid (DTPA) and its complexes have been identified as important chelating agents for the removal of BaSO4 scale. However, DTPA has good solubility only under strong alkali conditions, which in turn exacerbate scaling. To improve the solubility and chelation effectiveness of DTPA, penta sodium diethylenetriamine-pentaacetate (DTPA-5Na) was synthesized using chloroacetic acid, diethylenetriamine, sodium carbonate, and sodium hydroxide as raw materials. The structure of DTPA-5Na was characterized by infrared spectroscopy and 1H-NMR, and its chelation effectiveness was evaluated. Experimentation demonstrated that under conditions of 50 °C and with a molar ratio of chloroacetic acid (ClCH2COOH), sodium carbonate (Na2CO3), sodium hydroxide (NaOH), and diethylenetriamine (DETA) of 5.00 : 2.50 : 5.25 : 1.00, the reaction for 6 hours resulted in the optimal chelation value of DTPA-5Na at 76.8 mg CaCO3·per g. Analysis of the chelation and dissolution of BaSO4 scale using DTPA-5Na and microstructural scanning electron microscopy of the BaSO4 crystal indicate that DTPA-5Na functions through solubilization, lattice distortion, and flaking dispersion to remove BaSO4. Molecular dynamics simulation software was used to simulate the chelation mechanism of DTPA-5Na, where the results indicated strong adsorption of DTPA-5Na to the surface of BaSO4. The adsorption energy follows the order of (120) surface > (001) surface > (100) surface > (210) surface. The adsorption is mainly a result of the interaction between the carboxylic "O" atom in DTPA-5Na and the (001), (100), and (120) surfaces of BaSO4 scale, while N atoms in DTPA-5Na structure primarily interact with the (210) surface. The adsorption of "O" atoms is stronger than that of "N" atoms in the DTPA-5Na structure.

Assign_v2: a novel bonded-force field parameterization software for square planar palladium molecular dynamics simulations

In the present study, a requisite bonded force field for conducting molecular dynamics simulations of palladium compounds was derived utilizing a novel technique termed the “numbering system,” implemented through a program named assign.py. A significant challenge in deriving a bonded force field for square-planar palladium compounds emanates from their cis-trans characteristics, whereby the bond angles of identical atoms diverge across different compounds due to the presence of cis and trans isomers. To navigate this challenge, atoms surrounding the palladium were assigned numerical identifiers; consecutively numbered neighboring atoms were designated as “cis,” while atoms alternately numbered were regarded as “trans” relative to each other. Through the employment of the newly developed assign.py program, atoms common to GAFF were automatically assigned, facilitating the seamless integration of GAFF with the newly derived force field for cis and trans configurations. The tested innovative force field demonstrated results in close proximity to experimental findings. This research introduced two novel elements: firstly, a comparatively extensive force field was derived for palladium compounds, enabling the simulation of the previously non-simulable square planar geometry of palladium. Secondly, new software, assign.py, was developed, capable of amalgamating “numbering system atom types” with GAFF atom types into a unified force field. Conclusive tests within the study affirmed that the innovative bonded force field and technique utilizing the assign.py program was successful, simulating the square-planar geometry of palladium in a manner highly congruent with the experimental geometry. The program, licensed under Apache2, can be accessed via the following link: https://github.com/bkurt00/palladiumFF2/blob/main/assign_v2/assign_v2.py Communicated by Ramaswamy H. Sarma

Study of Asphalt Behavior on Pre-Wet Aggregate Surface Based on Molecular Dynamics Simulation and Surface Energy Theory

The improvement of the performance of asphalt mixtures has been studied by scholars. This research proposes a new asphalt–mineral interface formation method, which is a pre-wet bitumen–mineral mixture. The formation process of the pre-wet asphalt–mineral interface was simulated by molecular dynamics simulation software. The diffusion coefficient, concentration distribution, and interfacial energy of the asphalt on the surface of the pre-wet mineral material and non-pre-wet mineral material were compared and analyzed. The simulation results show that the mineral surface diffusion rate of the asphalt after pre-wetting is increased by more than 50%, and the concentration in the X, Y, and Z directions is reduced by 0.8%, 4.6%, and 7.8%, respectively. At the same time, the interface energy between the bitumen and the pre-wet mineral was increased by more than 8%. The results of the molecular dynamics model are verified based on the surface energy theory and contact angle test. The experimental results show that the contact angle of the asphalt is smaller and the diffusion performance is better after pre-wetting. At the same time, the interface adhesion work between the asphalt and wet mineral surface increased by 4.3% in a dry environment, and the peeling work decreased by 41.1% in a water environment. Therefore, the author believes that the pre-wetting technology of the asphalt mixture has a certain feasibility and practicability.

Studying performance portability of LAMMPS across diverse GPU‐based platforms

SummaryThe molecular dynamics simulation software, LAMMPS, utilizes the Kokkos acceleration library to port computation to a diverse set of architectures including those based on GPU accelerators. In addition to Kokkos, LAMMPS contains a vast code base that leverages the CUDA application programming interface using library functions such as cuFFT, CUDA's fast‐fourier transform (FFT) library, and, more recently, also support for AMD's Heterogeneous Interface for Portability (HIP) that is rapidly growing. While preparing LAMMPS tests for the AMD GPU‐based test system precursors to Frontier, we investigated several strategies for accelerating LAMMPS on AMD GPUs, using the AMD Instinct MI100 and MI250X. In this work, we integrated the HIP FFT library, hipFFT, into the particle‐particle particle‐mesh (PPPM) long‐range solver, which allowed the porting of PPPM calculations to the GPUs. Kokkos behavior on the MI100 and MI250X was also investigated through the package kokkos command of LAMMPS, targeting communication, memory usage, and particle grid decomposition. The Tersoff, Reax, Lennard‐Jones (LJ), EAM, Granular, and PPPM potentials were investigated in this effort, and results from these experiments are provided. The selected potentials were run on Spock (AMD Instinct MI100), Crusher (AMD Instinct MI250X), AFW HPC11 (NVIDIA A100) and Summit (NVIDIA V100), for comparison. Operational roofline models were constructed and analyzed for the Tersoff, Reax, and Lennard–Jones potentials on Crusher and Summit.

Assembly of a Diphenylalanine Peptide Nanotube by Molecular Dynamics Methods

The paper develops an approach to modeling the processes of self-assembly of complex molecular nanostructures by molecular dynamics methods using a molecular dynamics manipulator. Previously, this approach was considered using the example of assembling a phenylalanine helical nanotube from a linear set of chains of phenylalanine (F) molecules of different chirality: left-handed L-F and right-handed D-F chirality L-FF and D-FF. The process of self-assembly of dipeptide chains into helical structures of nanotubes is an imitation of applying certain forces to the existing initial linear structure in order to obtain the final structure of the same chemical composition, but with a different helical geometry. The PUMA-CUDA molecular dynamics simulation software package was used as the main software. Using this tool, one can investigate the formation of helical structures from a linear sequence of any amino acids. A comparative analysis of the structures of nanotubes obtained by assembling by molecular dynamics methods and by their experimental self-assembly was performed using the method of visual differential analysis. It has been established that the obtained data correspond to the law of the sign change of chirality of molecular helical structures with the complication of their hierarchical level of organization.

Rational design of a self-assembly promoting fusion domain enhances high molecular weight levan synthesis by levansucrase SacB

The catalytic product of levansucrase from Bacillus subtilis (SacB) is mainly composed of 10 % high molecular weight levan (HMW, ~2000 kDa) and 90 % low molecular weight levan (LMW, ~7000 Da). In order to achieve efficient production of food hydrocolloid, high molecular weight levan (HMW), with the help of molecular dynamics simulation software, a protein self-assembly element, Dex-GBD, was found and fused with the C-terminus of SacB to construct a novel fusion enzyme, SacB-GBD. The product distribution of SacB-GBD was reversed compared with SacB, and the proportion of HMW in the total polysaccharide was significantly increased to >95 %. We then confirmed that the self-assembly was responsible for the reversal of the SacB-GBD product distribution by the simultaneous modulation of SacB-GBD particle size and product distribution by SDS. The hydrophobic effect may be the main driver of self-assembly as analyzed by molecular simulations and hydrophobicity determination. Our study provides an enzyme source for the industrial production of HMW and provides a new theoretical basis for guiding the molecular modification of levansucrase towards the size of the catalytic product.

Nano-microscopic analysis on the interaction of new and old asphalt mortar in recycled asphalt mixture

Asphalt and fillers form asphalt mortar, which plays the role of bonding and filling in the asphalt mixture, and has a significant impact on the performance of the asphalt mixture. However, it is very necessary to fully study the interaction between old and new asphalt mortar in recycled asphalt mixture. In this study, molecular dynamics simulation software (Material Studio 8.0) was used to study the interface action of old and new asphalt mortar and the mechanical properties of the mixed old and new asphalt mortar. Quantification and characterization of solubility parameters, interaction energy, and mechanical properties from a microscopic perspective. In order to better demonstrate the simulation results, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and atomic force microscopy (AFM) were used to conduct microstructural tests to clarify the interaction of old and new asphalt mortar in recycled asphalt mixtures. The results show that at 190 °C, the solubility parameter difference of the old and new asphalt mortar molecular models and the interaction energy are in the best mixing state. At this temperature, the SEM surface morphology characterization is relatively good; the quantitative characterization of the functional groups also shows that the two have a good relationship. the miscible state. The mechanical properties of new and old asphalt mortars are described at the nano and micro scales, and the mechanical properties recover after miscibility. The above results show that it is a comprehensive and reliable method to conduct multi-scale research on the interaction of old and new asphalt mortar in recycled mixtures, and provide new ideas for the research of polymer materials.

Combining experiments and molecular dynamics simulations to investigate the effects of water on the structure and mechanical properties of a coal gangue-based geopolymer

The effects of water on the structure and mechanical properties of a coal gangue-based geopolymer were investigated experimentally and compared with the results of molecular dynamics simulations. The chemical composition and crystalline phases of the raw materials were analyzed via X-ray fluorescence and X-ray diffraction (XRD) after 28 days of curing, and the mechanical properties were tested. Molecular structure models for H2O/Al ratios of 2.5, 3, and 3.5 were established using molecular dynamics simulation software, and structural optimization and molecular dynamics simulations were performed under the universal force field. Based on the obtained results, the energy and temperature change curves, simulated XRD spectrum, radial distribution function, hydrogen bonding, mean squared displacement, and mechanical properties of the amorphous geopolymer were analyzed. The rationality of the molecular model was verified through comparison with the results of the molecular dynamics simulations and experiments, and as the H2O/Al ratio increased within a given range, the energy and temperature stability time of the system are decreased, the area of the dispersion peak is decreased, the amorphous phase is increased, the diffusion degree of Si and Al in the system is decreased, the length of Si-O bond, Al-O bond, H-O bond and O-O bond is shortened, and the structure is more stable. The mechanical properties obtained from the experiment were also improved.