Software design for a highly parallel molecular dynamics simulation framework in chemical engineering

Source rocks contain significant volumes of hydrocarbon fluids trapped in kerogen, however their effective recovery is challenged due to amplified fluid-wall interactions and the nanopore confinement impact on fluid composition. Enhanced oil production can be achieved by modifying the existing molecular forces in kerogen pore-network by using custom-designed targeted chemistry technologies. Our objective is to show how the transport of hydrocarbons in kerogen and its recovery can be altered with the delivery of microemulsion nanodroplets into the pore network. This is done by using computational chemistry and molecular dynamics (MD) simulations. Molecular dynamics simulation is used to generate a 3D model replica of a Type II kerogen representative of source rocks located in Delaware and Midland basins in the United States. Oil phase saturated kerogen is modeled as consisting of nine different types of molecules: dimethyl naphthalene, toluene, tetradecane, decane, octane, butane, propane, ethane and methane. The delivered microemulsion is an aqueous dispersion of solvent-swollen surfactant micelles. The solvent and nonionic surfactant present in the microemulsion are modeled as d-limonene and dodecanol heptaethyl ether (C12E7), respectively. Molecular dynamics simulation experiments include two steps: (i) the injection of microemulsion treatment fluid into the oil-saturated kerogen pore-network, and (ii) transient flow-back of the oil-chemical mixture in the pore network. The utilized 3D kerogen models were developed based on a representative oil sample composition (H, C, O, S, N) from the region. Simulation results show that microemulsions can affect the reservoir via two different mechanisms. During the injection, microemulsion nanodroplets that enter the nano-capillaries of pore network disperse in the liquid present in the pore space under the influence of pore walls. The solvent dissolves in the oil phase and alters the physical and transport properties of the phase, while the surfactant molecules modify the wettability of the solid kerogen surfaces. The recovery effectiveness of heavier oil fractions is improved compared to the recovery effectiveness achieved with surfactant micelles without the solubilized solvent. New 3D kerogen models are presented using atomistic modeling and molecular simulations. These models possess important chemical and physical characteristics of the organic matter of the source rock. Molecular dynamic experiments indicate that solubilized solvent and surfactant are delivered as part of a microemulsion droplet and are expected to aid the mobilization of oil present within kerogen.

In recent years, short peptide self-assembled materials, prepared under the control of the thermolysin catalyst, have been investigated extensively and shown to acquire various morphologies and fun...

Food industry and engineering—Quo vadis?

Our recent studies revealed that none of the selected widely used force field parameters and molecular dynamics simulation techniques yield structural properties for the intrinsically disordered α-synuclein that are in agreement with various experiments via testing different force field parameters. Here, we extend our studies on the secondary structure properties of the disordered amyloid-β(1-40) peptide in aqueous solution. For these purposes, we conducted extensive replica exchange molecular dynamics simulations and obtained extensive molecular dynamics simulation trajectories from David E. Shaw group. Specifically, these molecular dynamics simulations were conducted using various force field parameters and obtained results are compared to our replica exchange molecular dynamics simulations and experiments. In this study, we calculated the secondary structure abundances and radius of gyration values for amyloid-β(1-40) that were simulated using varying force field parameter sets and different simulation techniques. In addition, the intrinsic disorder propensity, as well as sequence-based secondary structure predisposition of amyloid-β(1-40) and compared the findings with the results obtained from molecular simulations using various force field parameters and different simulation techniques. Our studies clearly show that the epitope region identification of amyloid-β(1-40) depends on the chosen simulation technique and chosen force field parameters. Based on comparison with experiments, we find that best computational results in agreement with experiments are obtained using the a99sb*-ildn, charmm36m, and a99sb-disp parameters for the amyloid-β(1-40) peptide in molecular dynamics simulations without parallel tempering or via replica exchange molecular dynamics simulations.

FOR THE PAST 100 YEARS, THE FUNdamental definition of chemical engineering has remained the same: engineers take chemistry out of the laboratory and into the factory and the world around us, according to the American Institute of Chemical Engineers (AIChE), the primary professional society for chemical engineers. But over the course of a century, things are bound to change. During the past few decades, an increasing amount of the basic research in chemical engineering, like chemistry, has been done with an eye toward developing useful end products, especially in materials science and in biomedical areas. An affirmation of this shift was a daylong symposium in late April at Tufts University titled and Biological Engineering: The Paradigm Evolves. The symposium was held to celebrate the centennial of the university's program in chemical engineering and to mark the department's change in name to the department of chemical and biological engineering. The latter served as a ...

Molecular dynamics simulation as a tool for prediction of the properties of TiO2 and TiO2:MoO3 based chemical gas sensors

Hydrophobic charge-induction chromatography (HCIC) with 4-mercaptoethyl-pyridine (MEP) as the ligand is a novel technology for antibody purification. In the present work, the molecular simulation methods were used to investigate the interactions between MEP ligand and Fc fragment of IgG (Fc-A). Six ligands with different structures of spacer arm were studied with molecular docking and dynamics simulation at neutral and acidic pH. The binding modes and the interaction energies were analyzed. The results indicated that all ligands tested could bind into the selected pocket on the C(H2) domain of Fc-A at neutral pH. The pyridine ring on the top of MEP ligands acts as a major role to provide the hydrophobic association and hydrogen bond for the ligand-IgG binding; meanwhile, the sulfone group on the spacer arm might form the additional hydrogen bond and enhance the binding of ligand onto the surface of IgG. The replacements of thioether sulfur atom on the spacer arm with either nitrogen or oxygen atom seem to have little influence on the binding. The influences of pH on the ligand-IgG interactions were also studied with the molecular dynamics simulation. It was found that MEP ligands would departed from the surface of Fc-A at low pH due to the electrostatic repulsion. The ligands with a sulfone group on the spacer arm would weaken the electrostatic repulsion and need more acidic conditions for the departing of ligand. The molecular simulation results were in agreement with some experimental observations, which would be useful to elucidate the molecular mechanism of HCIC and design a novel ligand to improve the efficiency of antibody separation.

Molecular dynamics (MD) simulations employing classical force fields constitute the cornerstone of contemporary atomistic modeling in chemistry, biology, and materials science. However, the predictive power of these simulations is only as good as the underlying interatomic potential. Classical potentials often fail to faithfully capture key quantum effects in molecules and materials. Here we enable the direct construction of flexible molecular force fields from high-level ab initio calculations by incorporating spatial and temporal physical symmetries into a gradient-domain machine learning (sGDML) model in an automatic data-driven way. The developed sGDML approach faithfully reproduces global force fields at quantum-chemical CCSD(T) level of accuracy and allows converged molecular dynamics simulations with fully quantized electrons and nuclei. We present MD simulations, for flexible molecules with up to a few dozen atoms and provide insights into the dynamical behavior of these molecules. Our approach provides the key missing ingredient for achieving spectroscopic accuracy in molecular simulations.

A bachelor's degree in chemical engineering enhances one's capacity to adapt both hard and soft skills in the classroom and at work to the quick changes in technology and increasing competitiveness in the professional world. This motivates an individual who has graduated from chemical engineering to enhance the caliber of their work. Technology for simulation programming is one of the hard skills he needs to possess. In the realm of chemical engineering, these abilities encompass not only using Microsoft Office but also making objects work with other software. Through theoretical research on cases in the process industry, the simulation program is used. Prioritizing the operational foundation of an application is essential for work in the chemical sector. It is recommended that a graduate of chemical engineering possess software capabilities in order to facilitate their employment in the workforce. Basic requirements and increased proficiency can be supported by theoretical and data processing techniques. This article discusses the need for software skills in the field of chemical engineering, such as Aspen HYSYS, Matlab, AutoCAD P&ID, and Scilab, using a literature study methodology. This endeavor is a method of looking through library data for pertinent articles and then delving deeper into an article's content. The purpose of this article review is to balance hard and soft skills in order to determine how software is used in the field of chemical engineering and what is required in the chemical industry.

New Developments in the Collective Variables Module: More Flexible, More Interactive

Intrinsic hydrophobicity of smectite basal surfaces quantitatively probed by molecular dynamics simulations

This work provides an immersive visualization of oil & gas relevant systems and enhanced oil recovery (EOR) processes at the nanoscale by coupling molecular dynamics (MD) simulations with gamming virtual reality (VR) technologies. The main objective is to understand oil/brine/rock interfaces at molecular level and identify the underlying EOR mechanisms at the atomic scale. Within this immersive experience, the user can directly interact and enhance its perception of atomic environment for EOR applications. The experiences cover nano-EOR, nano-IOR and low-salt processes at nanoscale based on MD calculations of nanoparticles at oil-brine interfaces, oil-brine at silica nanopores and calcite-brine-oil interfaces, respectively. The MD simulations are performed with the Lammps package. The visualizations were done with an HTC Vive and Oculus Rift virtual reality headsets with the Nomad VR and Unitymol software. For the Nomad VR, the trajectories are previously saved from a Lammps molecular dynamics simulation, whereas, for the Unitymol, the simulation with Lammps is performed on-the-fly through the iMD (interactive MD) plugin. The user can visualize and navigate through the trajectories using the Nomad VR. Furthermore, the Unitymol also allows the user apply forces on selected molecules on real time during the VR experience. As means of comparison, the visualization was also performed with cell-phone based VR headsets with the Nomad VR application. Our demonstrations show that VR combined with molecular simulations can be an interesting and attractive way to improve the perception of the nanoscale for the general public. Additionally, it is an emergent tool to characterize, improve the understanding and provide molecular insights about nanosystems and the EOR methods, and also to be integrated with on-going digitalization processes within the oil & gas industry.

Introduction: Milk kefir, a fermenting milk made with kefir grains, has shown potential in promoting apoptosis, regulating the cell cycle, and reducing tumor growth in breast cancer cells. This study aimed to investigate the stability and potential of milk kefir metabolites as inhibitors of breast cancer growth by interacting with the estrogen receptor alpha (ER-α), a key protein involved in breast cancer cell proliferation. We used computational methods, specifically molecular docking simulations with AutoDock and molecular dynamics (MD) simulations with Gromacs, to analyze how these metabolites bind to ER-α. Methods: A combination of molecular docking and MD simulations was used to explore how metabolites derived from milk kefir interact with ER-α, a crucial target in breast cancer therapy. The methodology included multiple stages: preparation of target proteins, preparation and screening of the metabolites, geometry optimization, molecular docking, and MD simulations. Results: The molecular docking simulations of 43 metabolites revealed three promising candidates: 2-Methyl (S35), benzeneethanol (S42), and 2,6-dimethyl-4-heptanone (S54), with binding affinities (ΔG) of -5.08, -5.06, and -4.90 kcal/mol, respectively. MD simulations further showed that the selected metabolites stabilized the ER-α-metabolite complex, with the 2,6-dimethyl-4-heptanone (S54) metabolite demonstrating the most negative total MM-GBSA energy value (ΔG = -22.98 kcal/mol), indicating a strong and stable binding interaction. Conclusion: 2,6-Dimethyl-4-heptanone, a metabolite from milk kefir, showed promising potential as a candidate for further development as a breast cancer treatment, offering a novel alternative to conventional therapies.

Molecular dynamics simulations of compressive yielding in cross-linked epoxies in the context of Argon theory

MMP1 (matrix metallopeptidase 1) plays a significant role in the degradation of collagen fibres within the extracellular matrix, and has been linked to a multitude of biological processes, including rheumatoid arthritis, osteoarthritis, periodontal disease, and tumor invasion. In order to discover inhibitors of MMP1 that originate from the phytochemicals of the dandelion (Taraxacum mongolicum Hand.-Mazz.). The herbal constituents of the dandelion were retrieved from the HERB database. A multifaceted approach including molecular docking, MMP1 enzyme assays, and molecular dynamics simulations was used to identify potential MMP1 inhibitors among the chemical compounds present in the dandelion. A total of 61 chemical constituents of the dandelion were collated from the HERB database. A potential MMP1 inhibitor was identified through a combination of molecular docking and an MMP1 enzyme bioactivity assay. Cichoric acid demonstrated pronounced inhibitory activity against MMP1, with an IC50 value of 7.81 ± 2.60 μM. Molecular dynamics simulations and binding free energy calculations indicated that the nonpolar interaction energies of LEU181, ARG214, VAL215, HIS218, GLU219, HIS228, PRO238, and SER239 played a primary role in the binding of cichoric acid to MMP1. The integration of molecular modeling and bioactivity testing proved an effective method for the rapid discovery of targeted small molecule inhibitors. Cichoric acid demonstrated potent MMP1 inhibitory activity and thus represented a promising candidate for further development.