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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Investigating the Effect of Water on the Mechanical Properties of Cellulose from Multiscale Molecular Dynamics Simulations

Classical molecular dynamics (MD) simulations provide insight into the structure and physicochemical properties of materials with atomic resolution. However, the length and time scales accessible to atomistic MD are orders of magnitude smaller than many relevant processes such as the response of a bulk material to experimentally accessible strain rates, which presents challenges when comparing models to experimental measurements. Bottom-up coarse-graining provides a means for systematically mapping atomistic information to lower resolution models to increase the length and time scales achievable by simulation. Cellulose is an abundant carbohydrate biopolymer with applications to many fields of research, such as materials science and renewable energy, due to its desirable mechanical properties and viability for conversion into biofuel. The effect of moisture content on the Young's modulus of cellulose is of special interest due to its native environment often being in the hydrated secondary plant cell wall and the grinding energy requirements for biomass feedstock preprocessing. The current work investigates the effects of water solvent on the Young's modulus of cellulose calculated from coarse-grained MD mechanical stress simulations. The coarse-grained model was parametrized from atomistic MD calculations of cellulose-cellulose potentials of mean force using umbrella sampling techniques under vacuum and solvated conditions. The Young's moduli of the coarse-grained cellulose assemblies parametrized from cellulose in vacuum or solvated in water were computed via mechanical stress simulations to highlight the importance of capturing solvent interactions for modeling the mechanical behavior of cellulose.

BASIC BIOLOGICAL SCIENCES,RADIATION PROTECTION AND↗
DOE OSTI2023

Equation of state for He bubbles in W and model of He bubble growth and bursting near W{100} surfaces derived from molecular dynamics simulations

Abstract Molecular dynamics (MD) simulations are performed to derive an equation of state (EOS) for helium (He) bubbles in tungsten (W) and to study the growth of He bubbles under a W(100) surface until they burst. We study the growth as a function of the initial nucleation depth of the bubbles. During growth, successive loop-punching events are observed, accompanied by shifts in the depth of the bubble towards the surface. Subsequently, the MD data are used to derive models that describe the conditions that cause the loop punching and bursting events. Simulations have been performed at 500, 933, 1500, 2000, and 2500 K to fit the parameters in the models. To compute the pressure in the bubble at the loop punching and bursting events from the models, we derive an EOS for He bubbles in tungsten with an accompanying volume model to compute the bubble volume for a given number of vacancies ( $$N_\text {V}$$ N V ), He atoms ( $$N_\text {He}$$ N He ), and temperature ( T ). To derive the bubble EOS, we firstly derive the EOS for a free He gas. The derived free-gas EOS can accurately predict all MD data included in the analysis (which span up to 54 GPa at 2500 K). Subsequently, the bubble EOS is derived based on the free-gas EOS by correcting the gas density to account for the interaction between He and W atoms. The EOS for the bubbles is fitted to data from MD simulations of He bubbles in bulk W that span a wide range of gas density and sizes up to about 3 nm in diameter. The pressure of subsurface bubbles at the loop punching events as calculated using the bubble-EOS and the volume model agrees well with the pressure obtained directly from the MD simulations. In the loop punching model, for bubbles consisting of $$N_\text {V}$$ N V vacancies and $$N_\text {He}$$ N He helium atoms, the $$N_\text {He}/N_\text {V}$$ N He / N V ratio that causes the event, the resulting increase in $$N_\text {V}$$ N V , and the associated shift of the bubble depth are formulated as a function of $$N_\text {V}$$ N V and T . In the bursting model, a bubble must simultaneously reach a certain depth and $$N_\text {He}/N_\text {V}$$ N He / N V ratio in order to burst. The burst depth and $$N_\text {He}/N_\text {V}$$ N He / N V are also modeled as a function of $$N_\text {V}$$ N V and T . The majority of the loop punching events occur at bubble pressures between 20 and 60 GPa, depending on the bubble size and temperature. The larger the bubble and the higher the temperature, the lower the bubble pressure. Furthermore, our results indicate that at a higher temperature, a bubble can burst from a deeper region.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Full structural ensembles of intrinsically disordered proteins from unbiased molecular dynamics simulations

Abstract Molecular dynamics (MD) simulation is widely used to complement ensemble-averaged experiments of intrinsically disordered proteins (IDPs). However, MD often suffers from limitations of inaccuracy. Here, we show that enhancing the sampling using Hamiltonian replica-exchange MD (HREMD) led to unbiased and accurate ensembles, reproducing small-angle scattering and NMR chemical shift experiments, for three IDPs of varying sequence properties using two recently optimized force fields, indicating the general applicability of HREMD for IDPs. We further demonstrate that, unlike HREMD, standard MD can reproduce experimental NMR chemical shifts, but not small-angle scattering data, suggesting chemical shifts are insufficient for testing the validity of IDP ensembles. Surprisingly, we reveal that despite differences in their sequence, the inter-chain statistics of all three IDPs are similar for short contour lengths (< 10 residues). The results suggest that the major hurdle of generating an accurate unbiased ensemble for IDPs has now been largely overcome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Note: Local thermal conductivities from boundary driven non-equilibrium molecular dynamics simulations

We report non-equilibrium molecular dynamics simulations of heat transport in models of molecular fluids. We show that the “local” thermal conductivities obtained from non-equilibrium molecular dynamics simulations agree within numerical accuracy with equilibrium Green-Kubo computations. Our results support the local equilibrium hypothesis for transport properties. We show how to use the local dependence of the thermal gradients to quantify the thermal conductivity of molecular fluids for a wide range of thermodynamic states using a single simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Aspherical particle models for molecular dynamics simulation

In traditional molecular dynamics (MD) simulations, atoms and coarse-grained particles are modeled as point masses interacting via isotropic potentials. For studies where particle shape plays a vital role, more complex models are required. Here, we describe a spectrum of approaches for modeling aspherical particles, all of which are now available (some recently) as options within the LAMMPS MD package. Broadly these include two classes of models. In the first, individual particles are aspherical, either via a pairwise anisotropic potential which implicitly assigns a simple geometric shape to each particle, or in a more general way where particles store internal state which can explicitly define a complex geometric shape. In the second class of models, individual particles are simple points or spheres, but rigid body constraints are used to create composite aspherical particles in a variety of complex shapes. This work discusses parallel algorithms and associated data structures for both kinds of models, which enable dynamics simulations of aspherical particle systems across a wide range of length and time scales. We also highlight parallel performance and scalability and give a few illustrative examples of aspherical models in different contexts.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Parareal in Time for Dynamic Simulations of Power Systems

In recent years, there have been significant developments in parallel algorithms and high performance parallel computing platforms. Parareal in time algorithm has become popular for long transient simulations (e.g., molecular dynamics, fusion, reacting flows). Parareal is a parallel algorithm which divides the time interval into sub-intervals and solves them concurrently. This paper investigates the applicability of the parareal algorithm to power system dynamic simulations. Preliminary results on the application of parareal for multi-machine power systems are reported in this paper. Two widely used test systems, WECC 3-generator 9-bus system, New England 10-generator 39- bus system, is used to explore the effectiveness of the parareal. Severe 3 phase bus faults are simulated using both the classical and detailed models of multi-machine power systems. Actual Speedup of 5-7 times is observed assuming ideal parallelization. It has been observed that the speedup factors of the order of 20 can be achieved by using fast coarse approximations of power system models. Dependency of parareal convergence on fault duration and location has been observed.

Gurrala, Gurunath↗
DOE OSTI2015

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: i. reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements; ii. the conformational entropy of folding of β 2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state; iii. backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy); iv. the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β 2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

Science & Technology - Other Topics↗
DOE OSTI2011

SciDAC Advances in Beam Dynamics Simulation: From Light Sources to Colliders

In this paper, we report on progress that has been made in beam dynamics simulation, from light sources to colliders, during the first year of the SciDAC-2 accelerator project 'Community Petascale Project for Accelerator Science and Simulation (ComPASS).' Several parallel computational tools for beam dynamics simulation are described. Also presented are number of applications in current and future accelerator facilities (e.g., LCLS, RHIC, Tevatron, LHC, and ELIC). Particle accelerators are some of most important tools of scientific discovery. They are widely used in high-energy physics, nuclear physics, and other basic and applied sciences to study the interaction of elementary particles, to probe the internal structure of matter, and to generate high-brightness radiation for research in materials science, chemistry, biology, and other fields. Modern accelerators are complex and expensive devices that may be several kilometers long and may consist of thousands of beamline elements. An accelerator may transport trillions of charged particles that interact electromagnetically among themselves, that interact with fields produced by the accelerator components, and that interact with beam-induced fields. Large-scale beam dynamics simulations on massively parallel computers can help provide understanding of these complex physical phenomena, help minimize design cost, and help optimize machine operation. In this paper, we report on beam dynamics simulations in a variety of accelerators ranging from next generation light sources to high-energy ring colliders that have been studied during the first year of the SciDAC-2 accelerator project.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Molecular Dynamics Simulation and Theoretical Analysis of Structural Relaxation, Bond Exchange Dynamics, and Glass Transition in Vitrimers

Vitrimers are a class of polymer networks featuring dynamic covalent cross-links that can undergo associative bond exchange. There has been recent interest in these materials due to their promise as recyclable thermosets or self-healing polymers because of the ability of vitrimer networks to rearrange at the molecular level and undergo macroscopic flow. However, the practical use of these materials often occurs in the supercooled regime or glassy state, where the implications of dynamic bonds are complicated by the interplay between slow activated segmental dynamics, cross-link (i.e., bond-exchange) kinetics, and ultimately material properties. Here, in this paper, we combine coarse-grained molecular dynamics simulation and microscopic statistical mechanical theory to understand how cross-linking kinetics affect material dynamics and how this couples to segmental relaxation of the polymeric network strands across a spectrum of length and time scales, especially in the supercooled regime. We characterize the Kuhn segmental alpha relaxation time and bond exchange time for vitrimer systems across various cross-link densities, temperatures, and bond exchange rates. Simulation and theory both exhibit a bending-up behavior for bond exchange time upon cooling, suggesting a coupling between bond exchange dynamics and segmental relaxation that intensifies with faster bond exchange kinetics. We also found bond exchange dynamics have an impact on Kuhn segment alpha relaxation time, which is most significant at higher cross-link densities. Both these effects are most prominent when the bond exchange time is similar to the Kuhn segment alpha relaxation time, and the resulting coupling of these two relaxation processes is tied to both the probability of a free end to find a bonded pair and the time scale of the constraints imposed by the dynamic cross-links. This relationship is reflected by a cross-link dependence of a theoretical parameter which represents the quantitative degree of coupling between bond exchange and segmental dynamics. Overall, the combination of simulation and theory clarifies the intricate interaction between bond kinetics and segmental relaxation and demonstrates the ability to provide molecular-level insights into vitrimer dynamics over a wide temperature range.

dynamic relaxation↗
DOE OSTI2012

Direct dynamics simulation of dioxetane formation and decomposition via the singlet ·O–O–CH2–CH2 · biradical: Non-RRKM dynamics

Electronic structure calculations and direct chemical dynamics simulations are used to study the formation and decomposition of dioxetane on its ground state singlet potential energy surface. The stationary points for 1O2 + C2H4, the singlet {center_dot}O-O-CH2-CH2{center_dot} biradical, the transition state (TS) connecting this biradical with dioxetane, and the two transition states and gauche {center_dot}O-CH2-CH2-O{center_dot} biradical connecting dioxetane with the formaldehyde product molecules are investigated at different levels of electronic structure theory including UB3LYP, UMP2, MRMP2, and CASSCF and a range of basis sets. The UB3LYP/6-31G* method was found to give representative energies for the reactive system and was used as a model for the simulations. UB3LYP/6-31G* direct dynamics trajectories were initiated at the TS connecting the {center_dot}O-O-CH2-CH2{center_dot} biradical and dioxetane by sampling the TS's vibrational energy levels, and rotational and reaction coordinate energies, with Boltzmann distributions at 300, 1000, and 1500 K. This corresponds to the transition state theory model for trajectories that pass the TS. The trajectories were directed randomly towards both the biradical and dioxetane. A small fraction of the trajectories directed towards the biradical recrossed the TS and formed dioxetane. The remainder formed 1O2 + C2H4 and of these {approx} 40% went directly from the TS to 1O2 + C2H4 without getting trapped and forming an intermediate in the {center_dot}O-O- CH2-CH2{center_dot} biradical potential energy minimum, a non-statistical result. The dioxetane molecules which are formed dissociate to two formaldehyde molecules with a rate constant two orders of magnitude smaller than that predicted by Rice-Ramsperger-Kassel-Marcus theory. The reaction dynamics from dioxetane to the formaldehyde molecules do not follow the intrinsic reaction coordinate or involve trapping in the gauche {center_dot}O-CH2-CH2-O{center_dot} biradical potential energy minimum. Important non-statistical dynamics are exhibited for this reactive system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Applying Molecular Dynamics Simulations to Identify Rarely Sampled Ligand-bound Conformational States of Undecaprenyl Pyrophosphate Synthase, an Antibacterial Target

Undecaprenyl pyrophosphate synthase is a cis-prenyltransferase enzyme, which is required for cell wall biosynthesis in bacteria. Undecaprenyl pyrophosphate synthase is an attractive target for antimicrobial therapy. We performed long molecular dynamics simulations and docking studies on undecaprenyl pyrophosphate synthase to investigate its dynamic behavior and the influence of protein flexibility on the design of undecaprenyl pyrophosphate synthase inhibitors. We also describe the first X-ray crystallographic structure of Escherichia coli apo-undecaprenyl pyrophosphate synthase. The molecular dynamics simulations indicate that undecaprenyl pyrophosphate synthase is a highly flexible protein, with mobile binding pockets in the active site. By carrying out docking studies with experimentally validated undecaprenyl pyrophosphate synthase inhibitors using high- and low-populated conformational states extracted from the molecular dynamics simulations, we show that structurally dissimilar compounds can bind preferentially to different and rarely sampled conformational states. By performing structural analyses on the newly obtained apo-undecaprenyl pyrophosphate synthase and other crystal structures previously published, we show that the changes observed during the molecular dynamics simulation are very similar to those seen in the crystal structures obtained in the presence or absence of ligands. We believe that this is the first time that a rare 'expanded pocket' state, key to drug design and verified by crystallography, has been extracted from a molecular dynamics simulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Parallel Dynamics Simulation Using a Krylov-Schwarz Linear Solution Scheme

Fast dynamics simulation of large-scale power systems is a computational challenge because of the need to solve a large set of stiff, nonlinear differential-algebraic equations at every time step. The main bottleneck in dynamic simulations is the solution of a linear system during each nonlinear iteration of Newton’s method. In this paper, we present a parallel Krylov- Schwarz linear solution scheme that uses the Krylov subspacebased iterative linear solver GMRES with an overlapping restricted additive Schwarz preconditioner. As a result, performance tests of the proposed Krylov-Schwarz scheme for several large test cases ranging from 2,000 to 20,000 buses, including a real utility network, show good scalability on different computing architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

New insights into photodissociation dynamics of cyclobutanone from the AIMS dynamic simulation

In this work, the combined electronic structure calculations and non-adiabatic dynamics simulations were performed for understanding mechanistic photodissociation of cyclobutanone at ∼248 nm. Besides the stationary and intersection structures reported before, two new conical intersections between the ground (S{sub 0}) and the first excited singlet (S{sub 1}) states were determined in the present study, which were confirmed to be the new S{sub 1} → S{sub 0} funnels by the ab initio multiple spawning dynamic simulation, giving rise to products in the S{sub 0} state selectively. The time evolution of the S{sub 1} electronic population was fitted with the pure exponential formulae, from which the S{sub 1} lifetime was estimated to be 484.0 fs. The time constant for the S{sub 1} α-cleavage is calculated to be 176.6 fs, which is based on the present dynamics simulation. As a result of the ultrafast S{sub 1} processes, the statistical distribution of the excess energies is prevented in the S{sub 1} state. The S{sub 1} dynamic effect (the nonergodic behavior) was predicted to be an important factor that is responsible for the wavelength dependence of the branching ratio of photodissociation products, which will be discussed in detail.

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

Crystallization of the P 3 Sn 4 Phase upon Cooling P 2 Sn 5 Liquid by Molecular Dynamics Simulation Using a Machine Learning Interatomic Potential

We performed molecular dynamics simulations to study the crystallization of the P3Sn4 phase from P 2 Sn 5 liquid using a machine learning (ML) interatomic potential with desirable efficiency and accuracy. Our results capture the liquid properties of P 2 Sn 5 at 1300 K, which is well above the melting temperature. The phase separation and crystallization are observed when P 2 Sn 5 liquid is cooled down below 832 and 505 K, respectively. The simulation results are in good agreement with the experimentally observed phase transformation behaviors and provide useful insights into the complex nucleation and crystallization process at the details of atomistic scale. Our work also demonstrated that ML interatomic potentials based on neural network deep learning are robust and capable of accurately describing the energetics and kinetics of complex materials through molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Radiation damage in cubic ZrO 2 and yttria-stabilized zirconia from molecular dynamics simulations

Here, we perform molecular dynamics simulation on cubic ZrO 2 and yttria-stabilized zirconia (YSZ) to elucidate defect cluster formation resulting from radiation damage, and evaluate the impact of Y-dopants. Interstitial clusters composed of split-interstitial building blocks, i.e., Zr-Zr or Y-Zr are formed. Moreover, oxygen vacancies control cation defect migration; in their presence, Zr interstitials aggregate to form split-interstitials whereas in their absence Zr interstitials remain immobile, as isolated single-interstitials. Y-doping prevents interstitial cluster formation due to sequestration of oxygen vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Analysis of a Li-Ion Nanobattery with Graphite Anode Using Molecular Dynamics Simulations

In this work, molecular dynamics simulations were performed of the initial charging of a Li-ion nanobattery with a graphite anode and lithium hexaflourphosphate (LiPF 6 ) salt dissolved in ethylene carbonate (CO 3 C 2 H 4 ) solvent as the electrolyte solution. The charging was achieved through the application of external electric fields simulating voltage sources. A variety of force fields were combined to simulate the materials of the nanobattery, including the solid electrolyte interphase, metal collectors, and insulator cover. Some of the force field parameters were estimated using ab initio methods and others were taken from the literature. We studied the behavior of Li-ions traveling from cathode to anode through electrolyte solutions of concentrations 1.15 and 3.36 M. Time-dependent variables such as energy, temperature, volume, polarization, and mean square displacement are reported; a few of these variables, as well as others such as current, resistance, current density, conductivity, and resistivity are reported as a function of the external field and charging voltage. A solid electrolyte interphase (SEI) layer was also added to the model to study the mechanism behind the diffusion of the Li-ions through the SEI. As the battery is charged, the depletion of Li atoms in the cathode and their accumulation in the anode follow a linear increase of the polarizability in the solvent, until reaching a saturation point after which the charging of the battery stops, i.e., the energy provided by the external source decays to very low levels. Lastly, the nanobattery model containing the most common materials of a commercial lithium-ion battery is very useful to determine atomistic information that is difficult or too expensive to obtain experimentally; available data shows consistency with our results.

25 ENERGY STORAGE↗
DOE OSTI2015

Classical Molecular Dynamics Simulation of Nuclear Fuel

Molecular dynamics simulation is well suited to study primary damage production by irradiation, defect interactions with fission gas atoms, gas bubble nucleation, grain boundary effects on defect and gas bubble evolution in nuclear fuel, and the resulting changes in thermo-mechanical properties. In these simulations, the forces on the ions are dictated by interaction potentials generated by fitting properties of interest to experimental data. The results obtained from the present generation of potentials are qualitatively similar, but quantitatively different. There is a need to refine existing potentials to provide a better representation of the performance of polycrystalline fuel under a variety of operating conditions, and to develop models that are equipped to handle deviations from stoichiometry. In addition to providing insights into fundamental mechanisms governing the behaviour of nuclear fuel, MD simulations can also provide parameters that can be used as inputs for mesoscale models.

Devanathan, Ram↗
DOE OSTI2024

Dynamical simulation via quantum machine learning with provable generalization

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we develop a framework for using QML methods to simulate quantum dynamics on near-term quantum hardware. We use generalization bounds, which bound the error a machine learning model makes on unseen data, to rigorously analyze the training data requirements of an algorithm within this framework. Our algorithm is thus resource efficient in terms of qubit and data requirements. Furthermore, our preliminary numerics for the XY model exhibit efficient scaling with problem size, and we simulate 20 times longer than Trotterization on IBMQ-Bogota. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗