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At least 433 records · Page 24

Stratification of polymer mixtures in drying droplets: Hydrodynamics and diffusion

In this work, we study the evaporation-induced stratification of a mixture of short and long polymer chains in a drying droplet using molecular simulations. We systematically investigate the effects of hydrodynamic interactions (HI) on this process by comparing hybrid simulations accounting for HI between polymers through the multiparticle collision dynamics technique with free-draining Langevin dynamics simulations neglecting the same. We find that the dried supraparticle morphologies are homogeneous when HI are included but are stratified in core–shell structures (with the short polymers forming the shell) when HI are neglected. The simulation methodology unambiguously attributes this difference to the treatment of the solvent in the two models. We rationalize the presence (or absence) of stratification by measuring phenomenological multicomponent diffusion coefficients for the polymer mixtures. The diffusion coefficients show the importance of not only solvent backflow but also HI between polymers in controlling the dried supraparticle morphology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sorption-induced polymer rearrangement: approaches from molecular modeling

With the growing need for chemical separation and chemical storage solutions, polymeric adsorbents have emerged as a promising class of candidate materials because of their potentially tunable sorption properties, membrane structure and relatively cost consciousness. Moreover, the developing field of polymeric membrane materials has shown particular success at integrating both experimental and computational studies. However, these material systems are known to suffer from varying degrees of induced membrane structural rearrangement upon adsorbate uptake, and thus many polymeric membrane performance metrics are often considered to degrade with an increasing number of ‘guest’ species. In this mini–review, we highlight methodology tradeoffs and provide insights into atomistic molecular simulations used to study adsorption with flexible frameworks, which have the potential to predict separation, storage or catalytic capabilities a priori to experimental efforts. Specifically, molecular simulation methods that have been applied to provide predictions of polymeric membrane properties that have included consideration for sorbate–induced polymer chain rearrangement, swelling and/or plasticization are reviewed. Here, the examples and methodologies described provide demonstrations of the applicability of simulations as an approach to understand adsorption–based phenomena at an atomistic/molecular level, and as a tool to carry out screening studies aimed at efficiently providing analysis for a diversity of polymeric adsorbent–adsorbate systems.

36 MATERIALS SCIENCE↗

Atomistic origins of biomass recalcitrance in organosolv pretreatment

Separation of lignocellulosic biomass components for use in sustainable energy and biomaterials applications remains challenging, since biopolymers such as cellulose and hemicellulose carbohydrates and polyaromatic lignin are found in close proximity within the plant secondary cell wall. Organic solvents have been used to pretreat recalcitrant biomass and separate the interacting polymers, solubilizing the lignin fraction for lignin-first valorization approaches. However, no single organosolv pretreatment approach has proven superior for heterogeneous biomass samples. Here we present a complementary atomic view of interactions between biomass components using molecular simulations, specific to lignin and cellulose, resolving mechanistic hypotheses for how lignin-cellulose composition influences separation processes. Further, using lignin-cellulose binding free energy calculated using molecular simulations, we find polar protic solvents such as methanol and ethanol separate lignin from cellulose, irrespective of the charge on the lignin monomer. Aprotic organic solvents (DMSO, THF, 1,4-dioxane) separate uncharged lignin (phenols and monolignols) from cellulose, while charged lignin (cinnamates) prefer binding to cellulose.

09 BIOMASS FUELS↗

AladynPi – Adaptive Neural Network Molecular Dynamics Simulation Code with Physically Informed Potential: Computational Materials Mini-Application

This report provides an overview and description of commands used in the Computational Materials mini-application, AladynPi. AladynPi is an extension of a previously released mini-application, Aladyn (https://github.com/nasa/aladyn; Yamakov, V.I., and Glaessgen, E.H., NASA/TM-2018-220104). Aladyn and AladynPi are basic molecular dynamics codes written in FORTRAN 2003, which are designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory method. An input for the ANN is a set of structure coefficients, characterizing the local atomic environment of each atom, for which the atomic energy is obtained in the ANN inference process. In Aladyn, the ANN gives directly the energy of interatomic interactions. In AladynPi, the ANN gives optimized parameters for a predefined empirical function, known as bond-order-potential (BOP). The parameterized BOP function is then used to calculate the energy. AladynPi code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing manycore architectures based on graphic processing units (GPUs). The effort is supported by the High Performance Computing incubator (HPCi) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗

New Nonreactive Force Field for Accurate Molecular Dynamics Simulations of TATB at Extreme Conditions

Insensitive high explosives based on TATB (1,3,5-triamino-2,4,6-trinitrobenzene) are needed in applications when safety is of paramount importance, but the basic material properties that give rise to its insensitivity are not fully understood. Molecular dynamics modeling using empirical force fields (FFs) has been the main route to characterize many complicated dynamical properties of TATB single crystal, but these FFs have not been comprehensively tested at extreme conditions typical of detonation. We collect a benchmark data set of (quasi)static TATB physical properties as determined by experiments and electronic structure calculations and apply this data set to validate four existing TATB FFs along with a new TATB FF that we develop here and denote as the CEA-LLNL-Missouri (CLM) FF. Benchmark data include vibrational spectra, the TATB crystal temperature–pressure–volume equation of state and lattice parameters, properties of TATB crystal polymorphs and transitions to the gaseous and liquid states, dimer energy landscapes, the pressure-dependent elastic tensor, and the energy landscape for inelastic deformation via sliding of TATB crystal layers. As a general assessment, we find that the two existing nonreactive FFs are more accurate in describing TATB’s physical properties compared to the two variants of the ReaxFF reactive FF considered. The new CLM FF is found to consistently yield similar or better agreement with experiments and electronic structure theory than any of the existing FF models, and it presents a distinct improvement in accurately modeling TATB elasticity and equation of state. So this work is expected to help improve the accuracy of FF-based modeling of complicated dynamic responses that ultimately govern the safety and performance characteristics of this material.

36 MATERIALS SCIENCE↗

Simulation of Molecular Hydrogen Jets and Visualization of Associated Hydrodynamic Features [Slides]

A numerical method is presented for solving the Navier-Stokes equations to represent a steady-state hydrogen jet expanding into a vacuum chamber. This numerical method has been evaluated using three test problems with promising results. Simulations of the hydrogen jet indicate the presence of a low temperature region (less than 15 K) within the jet for the high flow rate case. The high flow rate case also gives rise to a large recirculation region within the jet. The conditions at the minimum temperature point within the jet approach the hydrogen sublimation line when the mass flow rate exceeds 2 g/s, which may allow for the formation of hydrogen ice crystals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗

Unfolding bovine α-lactalbumin with T-jump: Characterizing disordered intermediates via time-resolved x-ray solution scattering and molecular dynamics simulations

The protein folding process often proceeds through partially folded transient states. Therefore, a structural understanding of these disordered states is crucial for developing mechanistic models of the folding process. Characterization of unfolded states remains challenging due to their disordered nature, and incorporating multiple methods is necessary. Combining the time-resolved x-ray solution scattering (TRXSS) signal with molecular dynamics (MD), we are able to characterize transient partially folded states of bovine α-lactalbumin, a model system widely used for investigation of molten globule states, during its unfolding triggered by a temperature jump. We track the unfolding process between 20 μs and 70 ms and demonstrate that it passes through three distinct kinetic states. The scattering signals associated with these transient species are then analyzed with TRXSS constrained MD simulations to produce protein structures that are compatible with the input signals. Without utilizing any experimentally extracted kinetic information, the constrained MD simulation successfully drove the protein to an intermediate molten globule state; signals for two later disordered states are refined to terminal unfolded states. From our examination of the structural characteristics of these disordered states, we discuss the implications disordered states have on the folding process, especially on the folding pathway. Finally, we discuss the potential applications and limitations of this method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tasting nuclear pasta made with classical molecular dynamics simulations

Nuclear clusters or voids in the inner crust of neutron stars were predicted to have various shapes collectively nicknamed nuclear pasta. Furthermore, the recent review by López, Dorso and Frank summarized their systematic investigations into properties especially the morphological and thermodynamical phase transitions of the nuclear pasta within a Classical Molecular Dynamics model, providing further stimuli to find more observational evidences of the predicted nuclear pasta in neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Molecular dynamics simulations of radiation response of $\mathrm{LiAlO_2}$ and $\mathrm{LiAl_5O_8}$

Here, we report the findings of a computational investigation of defect production and migration in two lithium aluminate ceramics: LiAlO 2 and LiAl 5 O 8 . Although the first ceramic, LiAlO 2 has been widely investigated computationally, especially via molecular dynamics (MD), there have been no MD studies done on LiAl 5 O 8 up to date, due to the lack of interatomic potentials for this system. This work implemented an existing set of Li-Al-O coulombic and Buckingham potential parameters for the LiAl 5 O 8 system from the literature, followed by validating it based on experimental values of density, crystallinity, bond lengths and melting point. The Li + diffusion in the two ceramics was examined and was found to be one order of magnitude slower in LiAl 5 O 8 (D 0 = 3.17 x 10 -11 m 2 /s) as compared to that in LiAlO 2 (D 0 = 4.02 x 10 -10 m 2 /s) at 600 K. The lithium vacancy migration barrier of 4.15 eV in LiAl 5 O 8 was more than three times that in LiAlO 2 (1.31 eV) possibly due to stronger ordering in the Li-O 6 octahedra of LiAl 5 O 8 than in Li-O 4 tetrahedra of LiAlO 2 . The Li displacement threshold energy (E d ) in LiAl 5 O 8 was found to have a median value of 68 eV which is much higher than that in LiAlO 2 (40 eV). The greater E d for Li signifies a lower likelihood for defect formation and clustering and thus lower tendency for amorphization in LiAl 5 O 8 . The presented results show the difference in defect dynamics in the two ceramics that may help us understand the susceptibility of the two ceramics to amorphization caused by irradiation.

36 MATERIALS SCIENCE↗

Strong adsorption of guanidinium cations to the air–water interface

Combining Deep-UV second harmonic generation spectroscopy with molecular simulations, we confirm and quantify the specific adsorption of guanidinium cations to the air–water interface. Using a Langmuir analysis of measurements at multiple concentrations, we extract the Gibbs free energy of adsorption, finding it larger than typical thermal energies. Molecular simulations clarify the role of polarizability in tuning the thermodynamics of adsorption, and establish the preferential parallel alignment of guanidinium at the air–water interface. As a polyatomic cation, guanidinium represents one of the few examples of a positively charged species to exhibit a propensity for the air-water interface. As such, these results expand on the growing body of work on specific ion adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum-Based Molecular Dynamics Simulations Using Tensor Cores

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary computational speed and energy efficiency but with the caveat that they were designed for tensor contractions (matrix–matrix multiplications) using only low-precision floating-point operations. Despite this perceived limitation, we demonstrate how tensor cores can be applied with high efficiency to the challenging and numerically sensitive problem of quantum-based Born–Oppenheimer molecular dynamics, which requires highly accurate electronic structure optimizations and conservative force evaluations. The interatomic forces are calculated on-the-fly from an electronic structure that is obtained from a generalized deep neural network, where the computational structure naturally takes advantage of the exceptional processing power of the tensor cores and allows for high performance in excess of 100 Tflops on a single Nvidia A100 GPU. Stable molecular dynamics trajectories are generated using the framework of extended Lagrangian Born–Oppenheimer molecular dynamics, which combines computational efficiency with long-term stability, even when using approximate charge relaxations and force evaluations that are limited in accuracy by the numerically noisy conditions caused by the low-precision tensor core floating-point operations. A canonical ensemble simulation scheme is also presented, where the additional numerical noise in the calculated forces is absorbed into a Langevin-like dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗