Modeling Nonequilibrium Reactive Systems with REACTER
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machine learning, polymer simulations, molecular d↗
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Predicting Char Yield of High-Temperature Resins
A simulation technique has been developed for predicting the char yield of organic resins during high-temperature processing. In silico methods can aid in the screening of new advanced materials for a number of important properties, but no chemistry-sensitive protocol currently exists for predicting the important experimental value of char yield. The proposed method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to pyrolysis temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small by-product molecules to mimic outgassing, and the application of high pressure to encourage the formation of a dense, glassy network. Six different resin chemistries were investigated: an ethynyl, a phenylethynyl, a cyanate ester, a phthalonitrile, acrylonitrile, and adamantane. These candidates represent a diverse group of precursors with respect to initial cyclic content, presence of heteroatoms, and types of reactive groups. The protocol developed accurately predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. Several simulated properties of the carbonized structures are compared with experimental results, including outgassing products, morphology of the final chemical configurations, cyclic content, and mechanical properties.
polymer simulations, molecular dynamics↗
Predicting Char Yield of High-Temperature Resins
A simulation protocol is developed to predict the char yield of organic resins during high-temperature processing. Simulation protocol in silico methods can help screen promising new formulations for advanced materials, but previously no chemistry-sensitive technique existed to predict the important experimental value of char yield. The method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to processing temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small byproduct molecules to mimic outgassing, and the application of high pressure to eliminate porosity and encourage graphitization. More than ten different resin chemistries are investigated, including arylacetylenes, cyanate esters, phthalonitriles, and polyimides, representing a diverse group of precursors with respect to initial cyclic content, heteroatoms and reactive groups. The protocol correctly predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. The properties of the resins during processing are compared, including outgassing products, morphology of the final chemical configurations, cyclic content and mechanical properties.
polymer simulations, molecular dynamics↗
Molecular Dynamics of ULTEM 9085 for 3D Manufacturing: Spectra, Thermodynamic Properties, and Shear Viscosity.
We present results of a molecular dynamic analysis of welding at the polymer-polymer interface. The analysis is performed for polyetherimide/ polycarbonate polymer blends. The work is motivated by the applications to 3D manufacturing in space. In the first part of the report, we discuss bulk and spectral characteristics of the amorphous polymer blends. The vibrational and infra-red spectra obtained using auto-correlation functions calculations in molecular dynamics are compared with the experimental spectra. The mechanical and thermal properties of the samples including heat capacity, bulk modulus, and thermal expansion coefficients are estimated and compared with experimental values. In the second part of the report, we discuss the result of molecular dynamical modeling of shear viscosity in a fully atomistic model of amorphous polymer blends with flat interface. The key result of the research is the demonstration of shear thinning behavior of the shear viscosity as a function of shear rate which is in good agreement with experimental data.
Luchinsky, Dmitry G.↗
Computational Materials Research
Computational Materials aims to model and predict thermodynamic, mechanical, and transport properties of polymer matrix composites. This workshop, the second coordinated by NASA Langley, reports progress in measurements and modeling at a number of length scales: atomic, molecular, nano, and continuum. Assembled here are presentations on quantum calculations for force field development, molecular mechanics of interfaces, molecular weight effects on mechanical properties, molecular dynamics applied to poling of polymers for electrets, Monte Carlo simulation of aromatic thermoplastics, thermal pressure coefficients of liquids, ultrasonic elastic constants, group additivity predictions, bulk constitutive models, and viscoplasticity characterization.
Hinkley, Jeffrey A.↗
Effect of molecular weight on polyphenylquinoxaline properties
A series of polyphenyl quinoxalines with different molecular weight and end-groups were prepared by varying monomer stoichiometry. Thus, 4,4'-oxydibenzil and 3,3'-diaminobenzidine were reacted in a 50/50 mixture of m-cresol and xylenes. Reaction concentration, temperature, and stir rate were studied and found to have an effect on polymer properties. Number and weight average molecular weights were determined and correlated well with viscosity data. Glass transition temperatures were determined and found to vary with molecular weight and end-groups. Mechanical properties of films from polymers with different molecular weights were essentially identical at room temperature but showed significant differences at 232 C. Diamine terminated polymers were found to be much less thermooxidatively stable than benzil terminated polymers when aged at 316 C even though dynamic thermogravimetric analysis revealed only slight differences. Lower molecular weight polymers exhibited better processability than higher molecular weight polymers.
Jensen, Brian J.↗
Building and Breaking Carbon Composites with REACTER
Carbon-based composites have become indispensable materials in aerospace and other high-performance applications, yet obtaining a detailed, nanoscale understanding of their morphology and failure mechanisms using only experimental methods remains a difficult challenge. REACTER is a versatile computational modeling tool for atomistic molecular dynamics simulations designed to model chemical reactions at the speed and length scales of classical force fields. In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites: carbon nanotube (CNT) composites and carbon fiber reinforced polymers (CFRP). A network of CNTs was grown dynamically using the new ‘create atoms’ feature of REACTER. The CNT filler was embedded into a polyarylacetylene (PAA) matrix by simulated in situ polymerization to obtain the final composite model. To generate the second class of carbon composite, fully carbonized (graphitic) carbon fiber morphologies were created by the method of Desai et al. [1], but using the advanced reaction constraints framework of REACTER. Two fiber models were created, representing a circular carbon fiber core and a flat surface, and similarly infiltrated with resin to obtain the final CFRP structure. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third order DFT-based tight-binding simulations, via a reaction constraint on the total potential energy of the involved atoms.
Polymer↗
Carbonization Under Confinement: Predicting Charring Behavior of Carbon Composite Resins
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polymer↗
Building and Breaking Carbon Composites with REACTER
Carbon composites have become indispensable for aerospace and other high-performance applications, and a detailed picture of their morphology and failure mechanisms remains difficult to obtain through experiment. REACTER is a versatile computational modeling tool for atomistic molecular dynamics designed to model chemical reactions at the speed and length scales of classical force fields.1 In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites, carbon-fiber reinforced polymers (CFRP) and carbon nanotube (CNT) composites. Carbon fiber core morphologies were created by the method of Desai et al.,2 but using the advanced reaction constraints framework of REACTER, their proposed multistep procedure was reduced to a single uninterrupted molecular dynamics simulation. The carbon fiber filler was embedded into a polymer matrix by simulated in situ polymerization of several thermosetting resins, including bismaleimide and polyarylacetylene, to obtain the final CFRP model. To generate the second class of carbon composite, CNT networks were grown dynamically using the new ‘create atoms’ feature of REACTER, and similarly infiltrated with resin to obtain CNT composites. The resulting models were compared directly to experiment using simulated high resolution transmission electron microscopy and x-ray diffraction. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third-order DFT-based tight-binding (DFTB3) simulations, via a reaction constraint on the total potential energy of the involved atoms.
Molecular Dynamics↗
Formation, Structure and Properties of Amorphous Carbon Char from Polymer Materials in Extreme Atmospheric Reentry Environments
Amorphous carbonaceous char produced from the pyrolysis of polymer solids has many desirable properties for ablative heat shields for space vehicles. Molecular dynamics simulations are presented to study the transformation of the local atomic structure from virgin polymer to a dense, disordered char [1]. Release of polymer hydrogen is found to be critical to allow the system to collapse into a highly coordinated char structure. Mechanisms of the char formation process and the morphology of the resulting structures are elucidated. Thermal conductivity and mechanical response of the resulting char are evaluated [2]. During reenty, the optical response and oxidative reactivity of char are also important properties. Results of ab initio computations of char optical functions [3] and char reactivity [4] are also presented.
Lawson, John W.↗
Development and Application of Tools to Characterize the Oxidative Degradation of AP/HTPB/Al Propellants in a Propellant Reliability Study
The oxidative thermal aging of a crosslinked hydroxyl-terminated polybutadiene (HTPB)/isophorone diisocyanate (IPDI) polyurethane rubber was studied at temperatures between 25 C and 125 C. Changes in tensile elongation, mechanical hardening, polymer network properties, density, O2 permeation, and molecular chain dynamics were investigated as a function of age. The techniques used include solvent swelling, detailed modulus profiling, and NMR relaxation measurements. The Arrhenius methodology, which normally assumes a linear extrapolation of high temperature aging data, is critically evaluated by using extensive data superposition and highly sensitive oxygen consumption measurements. Significant curvature in the Arrhenius diagram of these oxidation rates is observed to be similar to previous results found for other rubber materials that have been evaluated by this technique. Preliminary gel/network properties suggest that crosslinking is the dominant process at higher temperatures. The effect on the oxidation rate of the binder when other constituents found in propellants are present, such as ammonium perchlorate, plasticizer and aluminum powder, is presented.
Celina, Mathew↗
Prediction of Mechanical Properties of Polymers With Various Force Fields
The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.
Odegard, Gregory M.↗
MODELING FUNCTIONALLY GRADED INTERPHASE REGIONS IN CARBON NANOTUBE REINFORCED COMPOSITES
A combination of micromechanics methods and molecular dynamics simulations are used to obtain the effective properties of the carbon nanotube reinforced composites with functionally graded interphase regions. The multilayer composite cylinders method accounts for the effects of non-perfect load transfer in carbon nanotube reinforced polymer matrix composites using a piecewise functionally graded interphase. The functional form of the properties in the interphase region, as well as the interphase thickness, is derived from molecular dynamics simulations of carbon nanotubes in a polymer matrix. Results indicate that the functional form of the interphase can have a significant effect on all the effective elastic constants except for the effective axial modulus for which no noticeable effects are evident.
Seidel, G. D.↗
Modeling Ring-Opening Polymerization with Machine-Learned Committors
Many important industrial and biological processes depend on ring-opening polymerization (ROP), including large-scale production polymers, such as nylon 6, and a variety of biodegradable polymers and high-performance resins. Large-scale simulations (>200K atoms) of ROP were performed using a deep neural network-based method that captured the effect of the local chemical environment of the reactive sites using training data from quantum chemical methods. The utility of this method was demonstrated by modeling the cationic ROP of bis-benzoxazine, a promising resin for use in advanced high-temperature application composites (>200°C). Density functional theory calculations were used to map out the various ring opening and polymerization reaction paths that occur during the thermal processing of bis-benzoxazine. The probabilities of these reactions, as a function of local atomic configurations, were used to construct committor functions using a neural network approach. The learned committor functions were then used to determine when a particular reaction occurred within the REACTER framework for reactive molecular dynamics simulations. The experimentally observed exotherm that occurs during bis-benzoxazine ROP was captured in an effective manner in the simulations by imposing a local heating of the system that corresponds to the enthalpy of reaction for each reaction. The dependence of the final polymer morphology on the ROP reaction temperature was analyzed at the molecular scale. The results presented in this work indicate that machine-learned committor functions are a promising approach for incorporating high-fidelity reactivity criteria that capture the effect of local chemical environments into large-scale polymerization simulations.
machine learning, polymer simulations, molecular d↗
Molecular modeling of polymer composite-analyte interactions in electronic nose sensors
We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL electronic nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereoisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings with no hydrogens. The Dreiding 2.21 force field is used for the polymer, solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4-vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic and organic compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites. c2003 Elsevier Science B.V. All rights reserved.
NASA Center JPL↗
Molecular modeling of polymer composite interactions with analytes in electronic nose sensors for environmental monitoring in International Space Station
We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL Electronic Nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings (with no hydrogens). The Dreiding 2.21 force field is used for the polymer and solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4- vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic (ammonia) and organic (methanol, toluene, hydrazine) compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites.
electronic noise environmental monitoring polymer ↗
Computationally Guided Design of Polymer-Coated Microparticles as Reusable Materials
Long-duration space exploration missions and sustained lunar or Martian surface operations present greater demands for multifunctional and reusable materials. By scaling down the amount of material to be launched from Earth, both mission cost and risk can be reduced. In this regard, leveraging in-space manufacturing capabilities with reusable feedstock materials is an attractive option, as it will allow for articles to be generated on demand, utilized, and then recycled for additional use. NASA’s Enabling Sustained Presence Using Recyclables (ESPUR) project aims to develop reusable materials using polymer-coated microparticles that are bonded via reversible Diels-Alder reactions, where only modest heat is needed to trigger the reverse reaction and enable reuse. For proof-of-concept demonstration, research is currently focused on the fabrication of epoxy microparticles that contain a copoly(carbonate urethane) coating with maleimide and furan functionalities. Here, we discuss the integration of computational materials modeling approaches to help navigate the large design space in this development effort. We perform molecular dynamics (MD) simulations with atomistic and coarse-grained models of the copolymer, which allow us to evaluate the effects of design parameters like the molecular weight and composition on the molecular interactions and chain dynamics. We show how the properties change with the reversible bonds. We also leverage discrete element method (DEM) simulations to assess how microparticle design parameters like the size ratio and volume fraction can be tuned to increase the packing density and number of microparticle contacts to improve the mechanical properties. Our results demonstrate how computational tools can be used in close collaboration with experimental efforts to accelerate material design.
reusable materials↗
Molecular Dynamics Investigation of the Structural and Mechanical Properties of Off-Stoichiometric Epoxy Resins
We carried out molecular dynamics (MD) simulations to measure the mechanical properties of various off-stoichiometric polymers regarding amine to epoxy ratios (r) and to understand the stiffness of the polymers in terms of their structures. The aerospace-grade API-60 epoxy resin is used as an adhesive bond for assembling large-scale composite structures via the co-curing-ply bonding method. This method will produce a reliable and certifiable composite joint without additional fasteners. Calculated Young's modulus was measured from the uniaxial tension simulation with several high strain rates, and the experimental modulus was estimated by extrapolating the simulation results. We found that the stiffness was associated with molecular packing caused by chemical cross-linking. We also found that the number of network clusters gradually decreased as the ratio approached r = 1.0, which made the tighter cluster and the system much stiffer with an increase in the molecular weight and the degree of cross-linking. Structural properties such as Rg, MSD were measured to figure out the degree of stiffness with respect to the r.
Jang, Chang Woon↗