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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Predicting the preferred morphology of hexagonal boron nitride domain structure on nickel from ReaxFF-based molecular dynamics simulations

An understanding of the nucleation and growth of hexagonal boron nitride (hBN) on nickel substrates is essential to its development as a functional material. In particular, fundamental insights into the formation of the hexagonal lattices with alternating boron (B) and nitrogen (N) atoms could be exploited to control hBN lattice morphologies for targeted applications. Here, the preferred shapes and edge configurations of atomically smooth hBN on Ni(111) were investigated using molecular dynamics (MD) simulations, along with reactive force field (ReaxFF) developed to represent the Ni/B/N system and the lattice-building B–N bond formation. The obtained hBN lattices, from different B : N feed ratios, are able to confirm that hBN domain geometries can indeed be tuned by varying thermodynamic parameters (i.e., chemical potentials of N and B) – a finding that has only been predicted using quantum mechanical theories. Here, we also showed that the nitrogen fed to the system plays a more crucial role in dictating the size of hBN lattices. With an increase of the relative N content, the simulated hBN domain shapes also transition from equilateral triangles to hexagons, again, consistent with the anticipation based on Density Functional Theory (DFT) calculations. Hence, a plausible approach to acquire a desired hBN nanostructure depends on careful control over the synthesis conditions, which now can benefit from reliable molecular simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Parallel conjugate gradient algorithms for manipulator dynamic simulation

Parallel conjugate gradient algorithms for the computation of multibody dynamics are developed for the specialized case of a robot manipulator. For an n-dimensional positive-definite linear system, the Classical Conjugate Gradient (CCG) algorithms are guaranteed to converge in n iterations, each with a computation cost of O(n); this leads to a total computational cost of O(n sq) on a serial processor. A conjugate gradient algorithms is presented that provide greater efficiency using a preconditioner, which reduces the number of iterations required, and by exploiting parallelism, which reduces the cost of each iteration. Two Preconditioned Conjugate Gradient (PCG) algorithms are proposed which respectively use a diagonal and a tridiagonal matrix, composed of the diagonal and tridiagonal elements of the mass matrix, as preconditioners. Parallel algorithms are developed to compute the preconditioners and their inversions in O(log sub 2 n) steps using n processors. A parallel algorithm is also presented which, on the same architecture, achieves the computational time of O(log sub 2 n) for each iteration. Simulation results for a seven degree-of-freedom manipulator are presented. Variants of the proposed algorithms are also developed which can be efficiently implemented on the Robot Mathematics Processor (RMP).

Fijany, Amir↗
DOE OSTI2016

Molecular dynamics simulations of dislocations in TlBr crystals under an electrical field

TlBr crystals have superior radiation detection properties; however, their properties degrade in the range of hours to weeks when an operating electrical field is applied. To account for this rapid degradation using the widely-accepted vacancy migration mechanism, the vacancy concentration must be orders of magnitude higher than any conventional estimates. The present work has incorporated a new analytical variable charge model in molecular dynamics (MD) simulations to examine the structural changes of materials under electrical fields. Our simulations indicate that dislocations in TlBr move under electrical fields. As a result, this discovery can lead to new understanding of TlBr aging mechanisms under external fields.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Probing the limits of metal plasticity with molecular dynamics simulations

Ordinarily, the strength and plasticity properties of a metal are defined by dislocations—line defects in the crystal lattice whose motion results in material slippage along lattice planes. Dislocation dynamics models are usually used as mesoscale proxies for true atomistic dynamics, which are computationally expensive to perform routinely. However, atomistic simulations accurately capture every possible mechanism of material response, resolving every “jiggle and wiggle” of atomic motion, whereas dislocation dynamics models do not. We present fully dynamic atomistic simulations of bulk single-crystal plasticity in the body-centred-cubic metal tantalum. Our goal is to quantify the conditions under which the limits of dislocation-mediated plasticity are reached and to understand what happens to the metal beyond any such limit. In our simulations, the metal is compressed at ultrahigh strain rates along its [001] crystal axis under conditions of constant pressure, temperature and strain rate. To address the complexity of crystal plasticity processes on the length scales (85–340 nm) and timescales (1 ns–1μs) that we examine, we use recently developed methods of in situ computational microscopy to recast the enormous amount of transient trajectory data generated in our simulations into a form that can be analysed by a human. Our simulations predict that, on reaching certain limiting conditions of strain, dislocations alone can no longer relieve mechanical loads; instead, another mechanism, known as deformation twinning (the sudden re-orientation of the crystal lattice), takes over as the dominant mode of dynamic response. Below this limit, the metal assumes a strain-path-independent steady state of plastic flow in which the flow stress and the dislocation density remain constant as long as the conditions of straining thereafter remain unchanged. In this distinct state, tantalum flows like a viscous fluid while retaining its crystal lattice and remaining a strong and stiff metal.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Stress effects on the initial lithiation of crystalline silicon nanowires: Reactive molecular dynamics simulations using ReaxFF

Silicon (Si) has been recognized as a promising anode material for the next-generation high-capacity lithium (Li)-ion batteries because of its high theoretical energy density. Recent in situ transmission electron microscopy (TEM) revealed that the electrochemical lithiation of crystalline Si nanowires (c-SiNWs) proceeds by the migration of the interface between the lithiated Si (LixSi) shell and the pristine unlithiated core, accompanied by solid-state amorphization. The underlying atomic mechanisms of Li insertion into c-Si remain poorly understood. In this research, we perform molecular dynamics (MD) simulations using the reactive force field (ReaxFF) to characterize the lithiation process of c-SiNWs. Our calculations show that ReaxFF can accurately reproduce the energy barriers of Li migration from DFT calculations in both crystalline (c-Si) and amorphous Si (a-Si). The ReaxFF-based MD simulations reveal that Li insertion into interlayer spacing between two adjacent (111) planes results in the peeling-off of the (111) facets and subsequent amorphization, in agreement with experimental observations. We find that breaking of the Si–Si bonds between (111)-bilayers requires a rather high local Li concentration, which explains the atomically sharp amorphous–crystalline interface (ACI). Our stress analysis shows that lithiation induces compressive stress at the ACI layer, causing retardation or even the stagnation of the reaction front, also in good agreement with TEM observations. Lithiation at high temperatures (e.g. 1200 K) shows that Li insertion into c-SiNW results in an amorphous to crystalline phase transformation at Li : Si composition of ~4.2:1. In conclusion, our modeling results provide a comprehensive picture of the effects of reaction and diffusion-induced stress on the interfacial dynamics and mechanical degradation of SiNW anodes under chemo-mechanical lithiation.

25 ENERGY STORAGE↗
DOE OSTI2020

Large-Scale Molecular Dynamics Simulation of the Dehydration of a Suspension of Smectite Clay Nanoparticles

Fine-grained sediments and sedimentary rocks play important roles in a variety of modern energy technologies from petroleum geology to geological carbon sequestration and radioactive waste management. However, despite their utility and ubiquity, many of their properties remain poorly understood. In particular, the ability to predict the permeability and mechanics of these media remains a persistent fundamental challenge in the geosciences. In the present work, we show how large-scale classical molecular dynamics (MD) simulations can help interpret the properties of fine-grained sedimentary material. All-atom simulations containing 30 discrete clay particles are utilized to understand the evolution of a clay nanoparticle suspension during its progressive dehydration. Microstructural (pore size distribution, tortuosity, anisotropy), thermodynamic (enthalpy and free energy of hydration, anion exclusion), mechanical (total suction), and transport properties (diffusion coefficient tensors of water and sodium) are calculated and compared to the experiment. Overall, our results provide new insight into the coupled chemistry, mechanics, and transport properties of disordered nanoparticle assemblages and shed light upon the important role of water films in controlling these properties.

02 PETROLEUM↗
DOE OSTI2018

Manipulating molecular order in nematic liquid crystal capillary bridges via surfactant adsorption: guiding principles from dissipative particle dynamics simulations

The ability of liquid crystals (LCs) to change orientational order is used in applications, ranging from sensors to displays. The aim of this work is to computationally investigate how surfactant adsorption on cylindrical LC bridges can be used to control such orientational order. Building from classical fundamental lessons, understanding the ordering of mesogens along a preferred axis with the help of molecular modelling contributes to investigations of systems that could be a platform for LC-based sensing applications. The coarse-grained dissipative particle dynamics (DPD) simulation method is implemented here, because it allows us to quantify the effect of molecular features on the properties of meso-scopic systems containing LC bridges, an aqueous solvent, and surfactants at various concentrations. Three surfactant types are modelled with short, medium, and long tail lengths, respectively. All surfactants adsorb at the LC–water interface. It is found that the length of the surfactant hydrophobic tail determines the effectiveness by which the LC order is affected. Short tails are not as effective as long ones. Surfactants with long tails affect the LC order, but, in agreement with experiments, predominantly only within a short distance from the LC–water interface. For these surfactants, the surface density at the LC–water interface is an important knob that can be used to control the order of the LCs. As the effective LC–surfactant interactions change, so does the distribution of the surfactants at the interface. Consistent with theoretical expectations, the results presented here elucidate the effect of molecular features on the anchoring mechanism between surfactants and mesogens within cylindrical bridges dispersed in aqueous systems and could be helpful for designing novel surface-active compounds in the development of advanced sensing devices based on LCs.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2024

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

Formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗
NASA NTRSDate not supplied

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

Formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗
DOE OSTI2019

Ab Initio Molecular Dynamics Simulation of Divalent Metal Cation Incorporation in Calcite: Implications for Interpreting X-ray Absorption Spectroscopy Data

Calcite (CaCO 3 ) is a ubiquitous mineral with the ability to accommodate a wide range of impurities. Determination of the coordination environment and incorporation modes of impurities in calcite has historically relied primarily on the interpretation of extended X-ray absorption fine structure (EXAFS) spectroscopy. However, lack of standards combined with the large number of degrees of freedom involved in shell-by-shell fits have made the interpretation of EXAFS spectra challenging. As such, in this work, ab initio molecular dynamics (AIMD) simulations were performed to investigate the incorporation of seven divalent metal cation impurities, namely, Ba 2+ , Pb 2+ , Sr 2+ , Cd 2+ , Mn 2+ , Co 2+ , and Zn 2+ , in calcite. These cations span a wide range of sizes: 30.7 to –22.8% change in ionic radius with respect to Ca 2+ . The atomic trajectories were then used to compute EXAFS spectra for direct comparison with published experimental spectra. The simulations confirmed that all seven metal cations incorporate in calcite via substitution in the calcium site. The AIMD–EXAFS approach allowed for overcoming limitations of the shell-by-shell fitting approach, such as the difficulties in resolving weak backscatterers beyond the first coordination shell. As a result, the AIMD–EXAFS approach was able to provide a detailed and comprehensive characterization of the structural relaxation around divalent metal cation impurities in calcite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

The formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗
DOE OSTI2020

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and biodegradable polyesters that exhibit considerable potential to replace petroleum-based plastics towards a sustainable future. Despite the promise, general structure–property mappings within this class of polymers remain largely unexplored. An efficient exploration of this vast chemical space calls for the development and validation of predictive methods for accurate estimation of a diverse range of properties for PHA-based polymers. Towards this aim, we present and validate in this work the results of our molecular dynamics (MD) simulation based approach aimed at predicting glass transition temperatures (T g ) of PHA-based polymers. Since generally available and widely used polymer forcefields exhibit a relatively poor performance for T g predictions, we have developed a new forcefield by modifying the polymer consistent force field (PCFF) via refining a selected set of torsion potentials of the polymer backbone using accurate density functional theory (DFT) computations. After carefully assessing the dependence of critical simulation parameters, such as, polymer chain length, number of polymer chains, supercell size, and thermal quenching rate used in the simulation, the applicability and transferability of the modified PCFF (mPCFF) is demonstrated by directly comparing the computed T g predictions of various polymers with different chemistries, polymer side chain lengths and functional groups forming the polymer side chains against the respective experimentally measured values. Furthermore, the transport properties such as self-diffusion coefficient and viscosity are computationally determined and their well-known correlation with the target properties is demonstrated. Lastly, we have employed the developed approach to predict T g values for a number of yet-to-be-synthesized PHA-based polymers with a diverse set of functional groups in the polymer side chains. The results are further rationalized by correlating the predicted T g values with the inter-chain H-bond formation tendencies of the different side chain functional groups. This work represents an important first step towards computationally guided design of PHA-based functional polymers and opens up new directions for a systematic investigation of composition- and configuration-dependent structure–property relationships in more complex binary and ternary copolymer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Molecular dynamics simulations of the first charge of a Li-ion—Si-anode nanobattery

Rechargeable lithium-ion batteries are the most popular devices for energy storage but still a lot of research needs to be done to improve their cycling and storage capacity. Silicon has been proposed as an anode material because of its large theoretical capacity of ~3600 mAh/g. Therefore, focus is needed on the lithiation process of silicon anodes where it is known that the anode increases its volume more than 300%, producing cracking and other damages. In this study, we performed molecular dynamics atomistic simulations to study the swelling, alloying, and amorphization of a silicon nanocrystal anode in a full nanobattery model during the first charging cycle. A dissolved salt of lithium hexafluorophosphate in ethylene carbonate was chosen as the electrolyte solution and lithium cobalt oxide as cathode. External electric fields are applied to emulate the charging, causing the migration of the Li-ions from the cathode to the anode, by drifting through the electrolyte solution, thus converting pristine Si gradually into Li 14 Si 5 when fully lithiated. When the electric field is applied to the nanobattery, the temperature never exceeds 360 K due to a temperature control imposed resembling a cooling mechanism. The volume of the anode increases with the amorphization of the silicon as the external field is applied by creating a layer of LiSi alloy between the electrolyte and the silicon nanocrystal and then, at the arrival of more Li-ions changing to an alloy, where the drift velocity of Li-ions is greater than the velocity in the initial nanocrystal structure. Charge neutrality is maintained by concerted complementary reduction-oxidation reactions at the anode and cathode, respectively. Also, the nanobattery model developed here can be used to study charge mobility, current density, conductance and resistivity, among several other properties of several candidate materials for rechargeable batteries and constitutes the initial point for further studies on the formation of the solid electrolyte interphase in the anode.

25 ENERGY STORAGE↗
DOE OSTI2024

Accelerated Sequence Design of Star Block Copolymers: An Unbiased Exploration Strategy via Fusion of Molecular Dynamics Simulations and Machine Learning

Star block copolymers (s-BCPs) have potential applications as novel surfactants or amphiphiles for emulsification, compatibilization, chemical transformations, and separations. s-BCPs have chain architectures where three or more linear diblock copolymer arms comprised of two chemically distinct linear polymers, e.g., solvophobic and solvophilic chains, are covalently joined at one point. The chemical composition of each of the subunit polymer chains comprising the arms, their molecular weights, and the number of arms can be varied to tailor the surface and interfacial activity of these architecturally unique molecules. Further, this makes identification of the optimal s-BCP design nontrivial as the total number of plausible s-BCP architectures is experimentally or computationally intractable. In this work, we use molecular dynamics (MD) simulations coupled with a reinforcement learning-based Monte Carlo tree search (MCTS) to identify s-BCP designs that minimize the interfacial tension between polar and nonpolar solvents. We first validate the MCTS approach for the design of small- and medium-sized s-BCPs and then use it to efficiently identify sequences of copolymer blocks for large-sized s-BCPs. The structural origins of interfacial tension in these systems are also identified by using the configurations obtained from MD simulations. Chemical insights into the arrangement of copolymer blocks that promote lower interfacial tension were mined using machine learning (ML) techniques. Overall, this work provides an efficient approach to solve design problems via fusion of simulations and ML and provides important groundwork for future experimental investigation of s-BCPs for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Quantum chemical replica-exchange umbrella sampling molecular dynamics simulations reveal the formation mechanism of iron phthalocyanine from iron and phthalonitrile

Phthalocyanine (Pc) and its metal complexes (MPcs) have been used industrially since their discovery in the early 20th century. The phthalonitrile (PN) method is a well-known synthesis method in which Pc or MPc can be afforded by heating a mixture of PN and metal powders over 280 °C with only moderate yield. However, the formation mechanism of the phthalocyanines and the intermediate stages of this seemingly simple reaction have yet to be fully understood. To study this mechanism computationally, we carried out quantum chemical molecular dynamics (MD) simulations based on the density-functional tight-binding (DFTB) method, applying the replica-exchange umbrella sampling (REUS) method, starting from four PN molecules and one iron atom. The DFTB-REUS-MD simulations successfully yielded FePc, and a metastable structure very similar to FePc but with a reactive nitrene unit was also identified that might explain the incomplete conversion of the reactants into FePc. Furthermore, analysis of the MD trajectories reveals a three-step FePc formation mechanism for the PN method.

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

Isothermal Compressor Computational Fluid Dynamics Simulations (Final Report)

Carnot Compression is a startup company developing an innovative technology for air and gas compression. This technology is inherently oil-free and isothermal due to the use of water to simultaneously compress and cool the gas throughout the process. Isothermal gas compression eliminates the need to cool the compressed gas so it may lead to significant energy savings. The development of Carnot’s isothermal compressor is limited by the lack of insight into the flow and detailed behavior of the fluids (water and air/gas) inside the air end. Previous and current attempts at Computational Fluid Dynamics (CFD) simulations by Carnot have been unable to provide the level of accuracy required to use simulations for technology development. In this Cooperative Research and Development Agreement (CRADA) project, Oak Ridge National Laboratory (ORNL) used the CFD package Star-CCM+ to successfully develop a CFD simulation, providing the much-needed insight required to speed up the development. The work is intended to enable Carnot Compression to unlock its technology potential to a level sufficient for commercialization of the intended first product. The work will also prepare Carnot to scale the technology to much larger and more energy intensive applications, positioning it to broaden the product applications. Successful development of the technology has the potential to result in 20% or more efficiency gains for compression processes, or about $3 billion in annual energy savings potential for the U.S. alone.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗