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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Interfacial Reactivity and Speciation Emerging from Na-Montmorillonite Interactions with Water and Formic Acid at 200 °C: Insights from Reactive Molecular Dynamics Simulations, Infrared Spectroscopy, and X-ray Scattering Measurements

Reactive organic fluid - mineral interactions at elevated temperatures contribute to the evolution of planetary matter. One of the less studied but important transformations in this regard involves the reactions of formic acid with naturally occurring clays such as sodium montmorillonite. To advance a mechanistic understanding of these interactions, we use ReaxFF reactive molecular dynamics simulations in conjunction with infrared (IR) spectroscopy and X-ray scattering experiments to investigate the speciation behavior of water-formic acid mixtures on sodium montmorillonite interfaces at 473 K and 1 atm. Using a newly developed reactive forcefield, we show that the experimental IR spectra of unreacted and reacted mixture can be accurately reproduced by ReaxFF/MD. We further benchmark the simulation predictions of sodium carbonate and bicarbonate formation in the clay interlayers using Small and Wide-Angle X-ray Scattering measurements. Subsequently, leveraging the benchmarked forcefield, we interrogate the pathway of speciation reactions with emphasis on carbonate, formate, and hydroxide groups elucidating the energetics, transition states, intermediates, and preferred products. Further, we also delineate the differences in reactivities and catalytic effects of clay edges, facets, and interlayers owing to their local chemical environments, which have far reaching consequences in their speciation behavior. The experimental and simulation approaches described in this study and the transferable forcefields can be applied translationally to advance the science of clay-fluid interactions for several applications including subsurface fluid storage and recovery and clay-pollutant dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reactive Molecular Dynamics Simulations and Quantum Chemistry Calculations To Investigate Soot-Relevant Reaction Pathways for Hexylamine Isomers

Sooting tendencies of a series of nitrogen-containing hydrocarbons (NHCs) have been recently characterized experimentally using the yield sooting index (YSI) methodology. This work aims to identify soot-relevant reaction pathways for three selected C6H15N amines, namely, dipropylamine (DPA), diisopropylamine (DIPA), and 3,3-dimethylbutylamine (DMBA) using ReaxFF molecular dynamics (MD) simulations and quantum mechanical (QM) calculations and to interpret the experimentally observed trends. ReaxFF MD simulations are performed to determine the important intermediate species and radicals involved in the fuel decomposition and soot formation processes. QM calculations are employed to extensively search for chemical reactions involving these species and radicals based on the ReaxFF MD results and also to quantitatively characterize the potential energy surfaces. Specifically, ReaxFF simulations are carried out in the NVT ensemble at 1400, 1600, and 1800 K, where soot has been identified to form in the YSI experiment. These simulations account for the interactions among test fuel molecules and pre-existing radicals and intermediate species generated from rich methane combustion, using a recently proposed simulation framework. ReaxFF simulations predict that the reactivity of the amines decrease in the order DIPA > DPA > DMBA, independent of temperature. Both QM calculations and ReaxFF simulations predict that C2H4, C3H6, and C4H8 are the main nonaromatic soot precursors formed during the decomposition of DPA, DIPA, and DMBA, respectively, and the associated reaction pathways are identified for each amine. Both theoretical methods predict that sooting tendency increases in the order DPA, DIPA, and DMBA, consistent with the experimentally measured trend in YSI. This work demonstrates that sooting tendencies and soot-relevant reaction pathways of fuels with unknown chemical kinetics can be identified efficiently through combined ReaxFF and QM simulations. Overall, predictions from ReaxFF simulations and QM calculations are consistent, in terms of fuel reactivity, major intermediates, and major nonaromatic soot precursors.

fuel decomposition↗
DOE OSTI2022

Developing Reaction Chemistry Models from Reactive Molecular Dynamics: TATB

Reactive Molecular Dynamic (RMD) are used to simulate the cook-off chemistry of TATB at a variety of fixed density and fixed temperature conditions. The chemical transformations are monitored using a Coordination Geometry Analysis (CGA) approach which tracks which atom types are bonded to each specific atom. This particularly identifies oxidation state changes that occur during the transformations. Correlations between these different chemical changes are identified using a Non-negative Matrix Factorization (NMF) approach. These identify reduced order chemistry models for the TATB system which contains six components whose concentration profiles are a function of both the temperature and density/pressure. The time histories of these transformations appear to show exponential growth/decay properties that could be fit with Arrhenius rates. These components should form the basis of deflagration rate models for these materials which could then be used in mesoscale simulations to analyze accidental initiation, shock-to-detonation and detonation propagation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Physics-based, neural network force fields for reactive molecular dynamics: Investigation of carbene formation from [EMIM + ][OAc - ]

Reactive molecular dynamics simulations enable detailed understanding of solvent effects on chemical reaction mechanisms and reaction rates. While classical molecular dynamics using reactive force fields allows significantly longer simulation time scales and larger system sizes compared with ab initio molecular dynamics, constructing reactive force fields is a difficult and complex task. In this work, we describe a general approach following the Empirical Valence Bond (EVB) framework for constructing ab initio reactive force fields for condensed phase simulations by combining physics-based methods with neural networks (PB/NN). The physics-based terms ensure correct asymptotic behavior of electrostatic, polarization, and dispersion interactions, and are compatible with existing solvent force fields. Neural networks are utilized for versatile description of short-range orbital interactions within the transition state region, and accurate rendering of vibrational motion of the reacting complex. Herein, we demonstrate our methodology for a simple deprotonation reaction of the 1-ethyl-3-methylimidazolium (EMIM+) cation with acetate to form 1-ethyl- 3-methylimidazol-2-ylidene and acetic acid. Our PB/NN force field exhibits ~ 1 kJ/mol MAE accuracy within the transition state region for the gas-phase complex. To characterize solvent modulation of the reaction profile, we compute potentials of mean force (PMFs) for the gas-phase reaction as well as the reaction within a four ion cluster, and benchmark against ab initio molecular dynamics simulations. We find that the surrounding ionic environment significantly destabilizes formation of the carbene product, and we show that this effect is accurately captured by the reactive force field. By construction, the PB/NN potential may be directly employed for simulations of other solvents/chemical environments without additional parameterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Large-scale atomistic model construction of subbituminous and bituminous coals for solvent extraction simulations with reactive molecular dynamics

Large-scale atomistic models for complex polycyclic aromatic hydrocarbon systems help understand the chemical properties and behaviors of complex feedstocks such as coal or petroleum. However, the development and utilization of large-scale models remain limited due to the difficulty in achieving the varied structural characteristics necessary to capture stochastic nature of these feedstocks. Here we demonstrate a systematic workflow to construct stochastic molecular systems from a broad analytical suite: high-resolution transmission electron microscopy (HRTEM), carbon-13 nuclear magnetic resonance spectroscopy ( 13 C NMR), laser desorption ionization mass spectroscopy (LDI-MS), and elemental analysis. We present a model construction and analysis utility of a new Python-based module. We selected one subbituminous and three high-volatile bituminous coals to construct large-scale models (~40,000 atoms). The constructed models were utilized to examine the affinity for solvent extraction (naphthalene or tetralin) and the effect of structural properties (e.g., aromatic cluster size, functional groups, and cross-linking) in reactive molecular dynamics simulations. Complex chemical reactions were monitored with bond order transitions, intermediates formation, and mass distributions. Reactive molecular dynamics simulations suggest a plausible chemical extraction process and products for the complex fossil feedstocks. The results indicated that radical formations with bond breaking of bridging oxygens and carbons were required at high temperatures to facilitate hydrogeneration and extraction of gas molecules from radical-free molecules. We observed that aliphatic chains of tetralin were easily decomposed and combined with radicals to form small size of molecules with aryl bonding, mainly increasing molecules in the 500–1000 Da, while naphthalene had little impact on chemical extraction process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Assessment of the impact of reactor residence time distribution on non-equilibrium product selectivity of polypropylene pyrolysis using reactive molecular dynamics simulations

Mass residence time distribution (RTD) is considered to be an important factor controlling the product selectivity in the pyrolysis of biomass and plastic wastes along with the pyrolysis chemistry. However, due to the complex pyrolysis chemistry of biomass and plastic waste, the coupling between the reaction chemistry, RTD, and product selectivity is challenging to understand. Here, we introduce a reaction molecular dynamics-based method to examine pyrolysis chemistry and species timescales to assess the impact of RTD on product selectivity and yield. To validate this method, reactive molecular dynamics simulations were conducted for polypropylene pyrolysis and its non-equilibrium product selectivity using 6 different RTDs. We find that the RTD and the reaction chemistry control the peak non-equilibrium product concentrations. The peak monomer (C 3 H 6 ) concentration during pyrolysis can be increased by up to 25 % by using a narrow RTD in the case of polypropylene pyrolysis. We also find that product selectivity is strongly affected by the average residence time and RTD. This coupling between the reaction chemistry, RTD, and product selectivity highlights the need to understand detailed reaction chemistry to control RTD and optimize non-equilibrium product selectivity during polymer and biomass pyrolysis. The present method provides a new way to design RTD for reactors to reach maximized product selectivity of plastic waste and biomass.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Atomic-scale mechanism of carbon nucleation from a deep crustal fluid by replica exchange reactive molecular dynamics simulation

Here we present a mechanistic model of carbon nucleation and growth from a fluid at elevated temperature (T) and pressure conditions, typical of those found in the shallow Earth’s lithosphere. Our model uses a replica exchange reactive molecular dynamics framework in which molecular configurations are swapped between adjacent T replica at regular intervals according to underlying statistical mechanics. This framework allows predicting complex molecular structures and thermodynamics while remaining computationally efficient. Here we simulate the reactivity of an unstable mixture of CO 2 and CH 4 at 1000 K and 1 GPa. We find that the path to thermodynamic equilibrium is initially entropy-driven, producing a diversity of short-lived species, including various alcohols with intermediate carbon oxidation states. Cyclic and polycyclic radicals that are sometimes resonance-stabilized form next and set the stage for carbon nucleation. The carbon exsolution process releases abundant water, is exothermic and starts with the nucleation of a large aggregate of hydrogenated graphene flakes from covalently bonded polycyclic units. The carbon backbone of this nucleus subsequently grows into a hydrogen-depleted fullerene-like structure, before evolving toward a partially bilayered graphene layer. Overall, our results show that the mechanism of graphitic C formation is certainly not bimolecular, and that it may involve a combination of key condensation and radical chain reactions. This will help understand the isotopic, and reactive characteristics of carbon-bearing fluids during their upward transit through the Earth’s mantle and crust. Moreover, the mechanistic insights outlined here present intriguing similarities with the process of soot and interstellar dust formation, which suggests that the widespread distribution of abiotic polyaromatic and graphitic material on Earth and beyond may reflect the prevalence of a fundamental chemical pathway.

58 GEOSCIENCES↗
DOE OSTI2025

Growth of Hexagonal Boron Nitride from Molten Nickel Solutions: A Reactive Molecular Dynamics Study

Metal flux methods are excellent for synthesizing high-quality hexagonal boron nitride (hBN) crystals, but the atomic mechanisms of hBN nucleation and growth in these systems are poorly understood and difficult to probe experimentally. Here, we harness classical reactive molecular dynamics (ReaxFF) to unravel the mechanisms of hBN synthesis from liquid nickel solvent over time scales up to 30 ns. These simulations mimic experimental conditions by including relatively large liquid nickel slabs containing dissolved boron and a molecular nitrogen gas phase. Overall, the reaction takes place almost exclusively on the surface of the liquid nickel, owing to the low solubility of nitrogen in bulk nickel and the intermediate species’ preference for the metal–gas interface. The formation of hBN invariably begins by reaction of dinitrogen with nickel-solvated boron atoms at the surface, forming intermediate N–N–B species, which typically evolve into B–N–B units through a short-lived intermediate where a single nitrogen atom is coordinated by one nitrogen and two boron atoms. The resulting B–N–B units, in turn, coalesce with growing hBN nuclei and carry nitrogen between hBN nanocrystals in an Ostwald ripening process. The amount of hBN produced on the tens of nanosecond time scale depends critically on the boron concentration, while having a much weaker dependence on the N 2 pressure for the regime considered (N 2 pressures of 2.5–10 MPa, Ni–B solutions with 6–12% boron by atom fraction). The highest rate of hBN formation occurs at the lowest temperature considered (1750 K, just above the melting point of nickel), while no hBN sheets are formed at 2000 K or above. An analysis of the transition pathways for nitrogen atoms shows that the final step, incorporation of small B–N motifs into larger hBN sheets, is the rate-limiting step in the regimes considered. While raising the temperature from 1750 to 2000 K has little effect on the formation of intermediates (N–N–B, B–N–B, etc.), the lack of large hBN sheets at temperatures >1900 K is explained by decreased probability of the final step and increased probability of breakup of hBN into B–N motifs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Simulations of the Biodegradation of Citrate Based Polymers for Artificial Scaffolds Using Accelerated Reactive Molecular Dynamics

Here, we explore the reactivity and mechanical properties of poly(1,6-hexanediol-co-Citric acid) via ReaxFF molecular dynamics simulations. We implement an accelerated scheme within the ReaxFF framework to study the hydrolysis reaction of the polymer which is provided with sufficient amount of energy known as the restrain energy after a suitable pre-transition state configuration is obtained to overcome the activation energy barrier and the desired product is obtained. The validity of the ReaxFF force field is established by comparing the ReaxFF energy barriers of ester and ether hydrolysis with benchmark DFT values in literature. We perform chemical and mechanical degradation of polymer chain bundles at 300 K. We find that ester hydrolyzes faster than ether due to lower activation energy barrier of the reaction. The selectivity of the bond-boost scheme has been demonstrated by lowering the boost parameters of the accelerated simulation which almost stops the ether hydrolysis. Mechanical degradation of pre-hydrolyzed and intermittent hydrolyzed polymer bundles is performed along the longitudinal direction at two different strain rates. We find that the tensile modulus of the polymers are increases with increase in strain rates which shows that polymers show a strain dependent behavior. The tensile modulus of the Polyester-ether is higher than Polyester yet reaches yield-stress faster than Polyester. This makes Polyester more ductile than Polyester-ether.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Alkali triel chalcogenide nanocrystals: a molecular reactivity approach to ternary phase selectivity

Alkali-metal-based materials are promising building blocks for energy conversion and storage technologies. Here, we use a molecular reactivity-based solution-phase approach to selectively synthesize multiple phases and specific polymorphs of lithium- and sodium-containing triel chalcogenide nanocrystals, LiTrCh 2 , NaTrCh 2 , and NaTr 3 Ch 5 , where Tr = Ga and In and Ch = S, Se, and Te. Analogous to the case of binary II–VI and III–V tetrahedral semiconductors, where the two commonly isolated zinc blende and wurtzite polymorphs are separated by only 1–50 meV f.u. −1 , we find that LiTrCh 2 nanocrystals easily adopt tetragonal (chalcopyrite) and orthorhombic polymorphs separated by only 2.7–6.2 meV f.u. −1 Because of this small energy difference, soft colloidal synthesis succeeds in accessing either one of these polymorphs, depending on the specific dichalcogenide precursor used. Highly reactive diethyl diselenide favors the thermodynamically more stable tetragonal I$\bar{4}2$d phase, whereas mildly reactive diphenyl diselenide favors the kinetic, metastable orthorhombic Pna2 1 phase. Density functional theory calculations confirm the relative energies among multiple LiTrCh 2 polymorphs and also model the observed powder X-ray diffraction pattern of a new C2 NaIn 3 Te 5 phase. 7 Li, 69 Ga, and 77 Se solid-state NMR spectra are consistent with phase-pure ternary LiGaSe 2 nanocrystals. A majority of the nanocrystal compositions are visible-light emitters. This work opens the door to new Li/Na-based ternary triel chalcogenide nanostructures for energy storage and conversion applications.

Pavel, Md Riad Sarkar [Iowa State Univ., Ames, IA ↗
DOE OSTI2019

Effect of Domain Size, Boundary, and Loading Conditions on Mechanical Properties of Amorphous Silica: A Reactive Molecular Dynamics Study

Mechanical properties are very important when choosing a material for a specific application. They help to determine the range of usefulness of a material, establish the service life, and classify and identify materials. The size effect on mechanical properties has been well established numerically and experimentally. However, the role of the size effect combined with boundary and loading conditions on mechanical properties remains unknown. In this paper, by using molecular dynamics (MD) simulations with the state-of-the-art ReaxFF force field, we study mechanical properties of amorphous silica (e.g., Young’s modulus, Poisson’s ratio) as a function of domain size, full-/semi-periodic boundary condition, and tensile/compressive loading. We found that the domain-size effect on Young’s modulus and Poisson’s ratio is much more significant in semi-periodic domains compared to full-periodic domains. The results, for the first time, revealed the bimodular and anisotropic nature of amorphous silica at the atomic level. We also defined a “safe zone” regarding the domain size, where the bulk properties of amorphous silica can be reproducible, while the computational cost and accuracy are in balance.

bimodular materials↗
DOE OSTI2021

Predicting Hugoniot equation of state in erythritol with ab initio and reactive molecular dynamics

Erythritol has been proposed as an inert surrogate for developing theoretical and computational models to study aging in energetic materials. In this work, we present a comparison of mechanical and shock properties of erythritol computed using the ReaxFF reactive force field and from ab initio calculations employing density functional theory (DFT). We screened eight different ReaxFF parameterizations, of which the CHO parameters developed for hydrocarbon oxidation provide the most accurate predictions of mechanical properties and the crystal structure of erythritol. Further validation of the applicability of this ReaxFF parameterization for modeling erythritol is demonstrated by comparing predictions of the elastic constants, crystal structure, vibrational density of states, and Hugoniot curves against DFT calculations. The ReaxFF predictions are in close agreement with the DFT simulations for the elastic constants and shock Hugoniot when the crystal is loaded along its c axis but show as much as 30% disagreement in the elastic constants in the ab plane and 12% difference in shock pressures when shocked along the a or b crystal axes. Last, we compare thermomechanical properties predicted from classical molecular dynamics with those calculated using the quasi-harmonic approximation and show that quantum mechanical effects produce large discrepancies in the computed values of heat capacity and thermal expansion coefficients compared with classical assumptions. Combining classical molecular dynamics predictions of mechanical behavior with phonon-based calculations of thermal behaviors, we show that predicted shock-induced temperatures for pressures up to 6.5 GPa do not exceed the pressure-dependent melting point of erythritol.

Hu, Jing↗
DOE OSTI2023

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces

Here, this paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations include the use of symmetry function-based atomic energy vector constructions as feature vectors for representing structures across families of molecules and single-fidelity neural network training capabilities that learn the relationships needed to map feature vectors to potential energy predictions. These foundations are embedded within several multifidelity topologies that decompose the high-fidelity mapping into model-based components, including sequential formulations that admit a general nonlinear mapping across fidelities and discrepancy-based formulations that presume an additive decomposition. Methodologies are first explored and demonstrated on a pair of simple analytical test problems and then deployed for potential energy prediction for C 5 H 5 using B2PLYP-D3/6-311++G(d,p) for high-fidelity simulation data and Hartree–Fock 6-31G for low-fidelity data. For the common case of limited access to high-fidelity data, our computational results demonstrate that multifidelity neural network potential energy surface constructions achieve roughly an order of magnitude improvement, either in terms of test error reduction for equivalent total simulation cost or reduction in total cost for equivalent error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗