Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “conformation dynamics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

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

Probing Hydrogen-Bond Anharmonicity in Cocrystals with Colossal Thermal Expansion

Organic cocrystals with sizable anisotropic thermal expansion (TE) are attractive building blocks for thermally responsive soft actuators. Such materials often display intermolecular H-bonding, whose thermal strength fluctuations are frequently overlooked if displacements and/or conformational changes are visible during TE. In this work, we employed variable-temperature single-crystal synchrotron diffraction to investigate the linear expansion coefficients of two organic cocrystals, 1 and 2, which exhibit colossal thermal expansivity exceeding 140 MK –1 . Despite such pronounced TE, solid-state 2 H and 13 C NMR experiments show no evidence of fast internal reorientations or large-amplitude molecular displacement during expansion. Although nondirectional π–π stacking dominates the colossal TE, our results indicate that hydrogen bonds play a non-negligible role in the anisotropic response. Molecular dynamics simulations reveal a temperature-dependent broadening of H-bond length distributions, which arises from the increased thermal sampling of an anharmonic potential energy surface. Our data support an expansion mechanism based on cooperativity in π-π interactions, accompanied by thermal softening and fluctuation-driven stretching of directional hydrogen bonds in these molecular solids. This mechanism underscores the significance of directional interactions in organic cocrystals, which is a key factor in the design of organic thermoresponsive crystalline materials.

Hernández-Morales, Ernesto A. [Univ. Nacional Auto↗
DOE OSTI2020

Thermodynamics and Structure of Poly[n]catenane Melts.

Motivated by recent achievements in the synthesis of interlocking polymers, the structural features of poly[n]catenanes, polymers composed entirely of interlocking rings (or macrocycles), are studied by extensive molecular dynamics simulations in the melt state. The degree of polymerization (number of links) is varied from n = 1 25 and the number of beads per macrocycle is varied from m = 15-50; the results are compared to linear chains of degrees of polymerization N = 15-175. The mechanical bonds in the system cause significant topological contributions to the pressure and potential energy density not seen in other polymer systems. The polymers themselves possess many unusual structural features at short and intermediate length scales, which can be attributed to density inhomogeneities along the polymer contour. Furthermore, the conformations of the individual macrocycles within poly[n]catenanes are quite different from those of ordinary ring polymers and depend on the topology of the macrocycle, that is, whether it is threaded by one ring (chain end) or two (chain center). At larger length scales, the poly[n]catenanes are conformationally similar to ideal linear chains, but unlike traditional (covalent) polymers, they are highly globular at low degrees of polymerization and are extremely flexible relative to their size, which inhibits interchain entanglement. Implications for poly[n]catenane material properties and synthesis are discussed.

Rauscher, Phillip M.↗
DOE OSTI2024

Capturing the generation and structural transformations of molecular ions

Molecular ions are ubiquitous and play pivotal roles in many reactions, particularly in the context of atmospheric and interstellar chemistry. However, their structures and conformational transitions, particularly in the gas phase, are less explored than those of neutral molecules owing to experimental difficulties. A case in point is the halonium ions, whose highly reactive nature and ring strain make them short-lived intermediates that are readily attacked even by weak nucleophiles and thus challenging to isolate or capture before they undergo further reaction. Here we show that mega-electronvolt ultrafast electron diffraction (MeV-UED), used in conjunction with resonance-enhanced multiphoton ionization, can monitor the formation of 1,3-dibromopropane (DBP) cations and their subsequent structural dynamics forming a halonium ion. We find that the DBP + cation remains for a substantial duration of 3.6 ps in aptly named ‘dark states’ that are structurally indistinguishable from the DBP electronic ground state. The structural data, supported by surface-hopping simulations and ab initio calculations, reveal that the cation subsequently decays to iso-DBP + , an unusual intermediate with a four-membered ring containing a loosely bound bromine atom, and eventually loses the bromine atom and forms a bromonium ion with a three-membered-ring structure. We anticipate that the approach used here can also be applied to examine the structural dynamics of other molecular ions and thereby deepen our understanding of ion chemistry.

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

Fast GPU-Based Generation of Large Graph Networks From Degree Distributions

Synthetically generated, large graph networks serve as useful proxies to real-world networks for many graph-based applications. The ability to generate such networks helps overcome several limitations of real-world networks regarding their number, availability, and access. Here, we present the design, implementation, and performance study of a novel network generator that can produce very large graph networks conforming to any desired degree distribution. The generator is designed and implemented for efficient execution on modern graphics processing units (GPUs). Given an array of desired vertex degrees and number of vertices for each desired degree, our algorithm generates the edges of a random graph that satisfies the input degree distribution. Multiple runtime variants are implemented and tested: 1) a uniform static work assignment using a fixed thread launch scheme, 2) a load-balanced static work assignment also with fixed thread launch but with cost-aware task-to-thread mapping, and 3) a dynamic scheme with multiple GPU kernels asynchronously launched from the CPU. The generation is tested on a range of popular networks such as Twitter and Facebook, representing different scales and skews in degree distributions. Results show that, using our algorithm on a single modern GPU (NVIDIA Volta V100), it is possible to generate large-scale graph networks at rates exceeding 50 billion edges per second for a 69 billion-edge network. GPU profiling confirms high utilization and low branching divergence of our implementation from small to large network sizes. For networks with scattered distributions, we provide a coarsening method that further increases the GPU-based generation speed by up to a factor of 4 on tested input networks with over 45 billion edges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

HIV Env assembling is tightly modulated by lipid composition and cytoplasmic tail integrity

HIV envelope glycoprotein (Env) is a homotrimeric transmembrane protein which binds to receptors CD4, CCR5- CXCR4, leading to a cascade of conformational changes ultimately resulting in the entrance of the virus into the host cell. Its whole structure comprises an extracellular region, a transmembrane domain and a cytoplasmic region. While many efforts are carried in order to develop an effective vaccine specifically targeting the extracellular domain, less efforts are focus into regions close to the transmembrane region; mostly limited by the lack of structural knowledge within this domain. Thus, it is desirable to have a molecular description of the trimeric association of the transmembrane domain, as well as the membrane properties affecting their structure. We have carried molecular dynamic (MD) simulations of HIV transmembrane region in different lipid environments, mimicking the complex viral membrane. Our results indicate that the lipid environment heavily affects the dynamics and association of the transmembrane helices, modulating its structure. In addition, we have investigated the effect of the cytoplasmic tail (CT). Unexpectedly, this region has a tremendous effect on the lateral organization of the transmembrane. These results clearly highlights the importance of this region in the overall structure of the Env protein and point towards its key role for the in-silico design of effective vaccines towards this domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Modulating Microphase Separation of Lamellae-Forming Diblock Copolymers via Ionic Junctions

In this work, we present a molecular dynamics simulation study investigating the phase behavior of lamellae-forming diblock copolymers with a single ionic junction on the backbone. Our results show qualitative agreement with experimental findings regarding enhanced microphase separation with the introduction of an ionic junction at the conjunction point, while further revealing nonmonotonic changes in domain spacing and order–disorder transition as a function of the electrostatic interaction strength. This highlights the dominant roles of entropic and binding effects of counterions under weak and strong ionic correlations, respectively. The location of the ionic junction is found to effectively modulate the charge distribution and chain conformation in the ordered domains; its presence in the middle of a block promotes folding of the block, leading to a smaller domain size. These findings demonstrate the interplay of ionic coupling with steric hindrance and chain end effects, which enhances our understanding of the delicate control over the microphase domain features.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Understanding Metal–Organic Framework Nucleation from a Solution with Evolving Graphs

A mechanistic understanding of metal–organic framework (MOF) synthesis and scale-up remains underexplored due to the complex nature of the interactions of their building blocks. In this work, we investigate the collective assembly of building units at the early stages of MOF nucleation, using MIL-101(Cr) as a prototypical example. Using large-scale molecular dynamics simulations, we observe that the choice of solvent (water and N,N-dimethylformamide), the introduction of ions (Na+ and F–) and the relative populations of MIL-101(Cr) half-secondary building unit (half-SBU) isomers have a strong influence on the cluster formation process. Additionally, the shape, size, nucleation and growth rates, crystallinity, and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting the self-assembly of MOF nuclei as the time evolution of an undirected graph. Solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly. While pure solvents lead to the rapid formation of a small number of large clusters, the presence of ions in aqueous solutions results in smaller clusters and slower nucleation. This diversity is captured by the key features of the graph representation. Principle component analysis on graph properties reveals that only a small number of molecular descriptors is needed to deconvolute MOF self-assembly. Furthermore, descriptors such as the average coordination number between half-SBUs and fractal dimension are of particular interest as they can be can be followed experimentally by techniques like by time-resolved spectroscopy. Ultimately, graph theory emerges as an approach that can be used to understand complex processes revealing molecular descriptors accessible by both simulation and experiment.

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

An Evolve-Then-Correct Reduced Order Model for Hidden Fluid Dynamics

In this paper, we put forth an evolve-then-correct reduced order modeling approach that combines intrusive and nonintrusive models to take hidden physical processes into account. Specifically, we split the underlying dynamics into known and unknown components. In the known part, we first utilize an intrusive Galerkin method projected on a set of basis functions obtained by proper orthogonal decomposition. We then present two variants of correction formula based on the assumption that the observed data are a manifestation of all relevant processes. The first method uses a standard least-squares regression with a quadratic approximation and requires solving a rank-deficient linear system, while the second approach employs a recurrent neural network emulator to account for the correction term. We further enhance our approach by using an orthonormality conforming basis interpolation approach on a Grassmannian manifold to address off-design conditions. The proposed framework is illustrated here with the application of two-dimensional co-rotating vortex simulations under modeling uncertainty. The results demonstrate highly accurate predictions underlining the effectiveness of the evolve-then-correct approach toward real-time simulations, where the full process model is not known a priori.

long short-term memory↗
DOE OSTI2019

Initial Simulations of Empty Room Collapse and Reconsolidation at the Waste Isolation Pilot Plant

The Waste Isolation Pilot Plant (WIPP) is a geologic repository for defense-related nuclear waste. If left undisturbed, the virtually impermeable rock salt surrounding the repository will isolate the nuclear waste from the biosphere. If humans accidentally intrude into the repository in the future, then the likelihood of a radionuclide release to the biosphere will depend significantly on the porosity and permeability of the repository itself. Room ceilings and walls at the WIPP tend to collapse over time, causing rubble piles to form on floors of empty rooms. The surrounding rock formation will gradually compact these rubble piles until they eventually become solid salt, but the length of time for a rubble pile to reach a certain porosity and permeability is unknown. This report details the first efforts to build models to predict the porosity and permeability evolution of an empty room as it closes. Conventional geomechanical numerical methods would struggle to model empty room collapse and rubble pile consolidation, so three different meshless methods, the Immersed Isogeometric Analysis Meshfree, Reproducing Kernel Particle Method (RKPM), and the Conformal Reproducing Kernel method, were assessed. First, the meshless methods and the finite element method each simulated gradual room closure, without ceiling or wall collapse. All three methods produced equivalent room closure predictions with comparable computational speed. Second, the Immersed Isogeometric Analysis Meshfree method and RKPM simulated two-dimensional empty room collapse and rubble pile consolidation. Both methods successfully simulated large viscoplastic deformations, fracture, and rubble pile rearrangement to produce qualitatively realistic results. In addition to geomechanical simulations, the flow channels in damaged salt and crushed salt were measured using micro-computed tomography, and input into a computational fluid dynamics simulation to predict the salt's permeability. Although room for improvement exists, the current simulation approaches appear promising.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Toward Automated Sampling of Polymorph Nucleation and Free Energies with the SGOOP and Metadynamics

Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process and correctly calculating the relative free energies of different polymorphs. Here, we demonstrate, for the prototypical case of urea nucleation from the melt, how one can learn such a one-dimensional reaction coordinate as a function of prespecified order parameters and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of the generic thermodynamic and structural order parameters using the “spectral gap optimization of order parameters (SGOOP)” approach [Tiwary, P. and Berne, B. J. Proc. Natl. Acad. Sci. U.S.A. (2016)] and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insights into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes an accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. Here, we believe the ideas demonstrated in this work will facilitate efficient sampling of nucleation in complex, generic systems.

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

Sensitive Detection of Structural Differences using a Statistical Framework for Comparative Crystallography

Chemical and conformational changes underlie the functional cycles of proteins. Comparative crystallography can reveal these changes over time, over ligands, and over chemical and physical perturbations in atomic detail. A key difficulty, however, is that the resulting observations must be placed on the same scale by correcting for experimental factors. We recently introduced a Bayesian framework for correcting (scaling) X-ray diffraction data by combining deep learning with statistical priors informed by crystallographic theory. To scale comparative crystallography data, we here combine this framework with a multivariate statistical theory of comparative crystallography. By doing so, we find strong improvements in the detection of protein dynamics, element-specific anomalous signal, and the binding of drug fragments.

Hekstra, Doeke R. [Harvard Univ., Cambridge, MA (U↗
DOE OSTI2025

Editorial: Structure and mechanism of microbial membrane active transporters

Membrane active transporters play essential roles in microbial physiology. They couple energy transduction to conformational changes that drive translocation of nutrients, substrates and ions, as well as molecular communication. The structure and function of microbial membrane active transporters are highly diverse. Typical examples include the primary active transporters in the ATP-binding cassette (ABC) superfamily (Thomas and Tampé, 2020; Davidson et al., 2008; Locher et al., 2002), the secondary active transporters in the Major Facilitator Superfamily (MFS) (Drew et al., 2021; Kaback and Guan, 2019), and the ligand-gated porins in the TonB-dependent transporter (TBDT) family (Klebba et al., 2021). As structural, proteogenomic, and computational methods advance, active transporters are increasingly recognized as dynamic molecular machines whose mechanisms can now be visualized and modeled with remarkable precision, building on decades of biochemical and biophysical discovery that established the foundations of this field. The transporter studies recruited in this Research Topic provide us with new insights into the field including structure-function of sugar transporters in yeast, structural prediction and classification of ABC complexes in Bacillus subtilis, Type VI Secretion System (T6SS) in Bacteroides fragilis, amino acids uptake in Escherichia coli and bacterial spore germination.

mechanism↗
DOE OSTI2023

A reactive wetting strategy improves lithium metal reversibility

The cycling of lithium metal (Li 0 ) anode is often accompanied by irregular lithium plating/stripping, leading to poor Li 0 reversibility, and posing a grand challenge to constructing reliable Li 0 batteries. Hereby, we report a reactive wetting strategy to enable conformal and highly reversible Li 0 plating/stripping through a lithium-reactive substrate. In this study, the reactive wetting, smooth nucleation, and conformal growth behaviors of Li 0 are visualized through in-situ transmission electron microscopy, ex-situ scanning electron microscope, and in-situ optical microscope characterizations. Based on the reactive wetting substrate, high average Coulombic efficiencies (99.0% at 0.5 mA cm -2 for 400 cycles) are realized for Li 0 anodes. By pre-plating Li 0 into the reactive wetting substrate as anodes and leveraging LiFePO 4 as cathodes, high capacity retention (76.0% after 200 cycles in low N/P ratio conditions) is also achieved in the as-constructed Li 0 full cells. This work establishes a fundamental understanding of reactive wetting dynamics of Li 0 and provides a drop-in solution to improving Li 0 reversibility.

25 ENERGY STORAGE↗
DOE OSTI2020

Nanobody-enabled monitoring of kappa opioid receptor states

Recent studies show that GPCRs rapidly interconvert between multiple states although our ability to interrogate, monitor and visualize them is limited by a relative lack of suitable tools. We previously reported two nanobodies (Nb39 and Nb6) that stabilize distinct ligand- and efficacy-delimited conformations of the kappa opioid receptor. Here, we demonstrate via X-ray crystallography a nanobody-targeted allosteric binding site by which Nb6 stabilizes a ligand-dependent inactive state. As Nb39 stabilizes an active-like state, we show how these two state-dependent nanobodies can provide real-time reporting of ligand stabilized states in cells in situ. Significantly, we demonstrate that chimeric GPCRs can be created with engineered nanobody binding sites to report ligand-stabilized states. Our results provide both insights regarding potential mechanisms for allosterically modulating KOR with nanobodies and a tool for reporting the real-time, in situ dynamic range of GPCR activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Conformational space exploration of cryo-EM structures by variability refinement

Cryo-EM observation of biological samples enables visualization of sample heterogeneity, in the form of discrete states that are separable, or continuous heterogeneity as a result of local protein motion before flash freezing. Variability analysis of this continuous heterogeneity describes the variance between a particle stack and a volume, and results in a map series describing the various steps undertaken by the sample in the particle stack. While this observation is absolutely stunning, it is very hard to pinpoint structural details to elements of the maps. Here, in order to bridge the gap between observation and explanation, we designed a tool that refines an ensemble of structures into all the maps from variability analysis. Using this bundle of structures, it is easy to spot variable parts of the structure, as well as the parts that are not moving. Comparison with molecular dynamics simulations highlights the fact that the movements follow the same directions, albeit with different amplitudes. Ligand can also be investigated using this method. Variability refinement is available in the Phenix software suite, accessible under the program name phenix.varref.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Polymer Tacticity Effects in Polymer–Lanthanide Chelation Thermodynamics

Metal-chelating polymers are critical components in numerous applications. However, despite the known influence of polymer tacticity on both bulk and solution properties, most materials used in metal-chelation applications are atactic. Here, we investigate the relationship between polymer tacticity and polymer–lanthanide interactions in aqueous solution. We synthesized a series of five poly(methacrylic acid)s with systematic variations in tacticity (20–99% m diads) and used isothermal titration calorimetry to measure the thermodynamics of lanthanide binding to each material (ΔH, ΔG, ΔS, K a , and stoichiometry). We observed enthalpy–entropy compensation across this tacticity series, finding that both |ΔH| and |ΔS| decreased with decreasing m diad content while ΔG remained similar. Molecular dynamics simulations of the polymer–metal interactions revealed that the observed differences in binding thermodynamics may be largely ascribed to differences in polymer flexibility. Furthermore, these combined experimental and computational results demonstrate that metal binding can be influenced by altering the polymer stereochemistry, ultimately influencing the design of more efficient metal-chelating materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗