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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Examining Bioethanol-Producing Ultrastructures with Electron Microscopy and Molecular Dynamics

A longstanding goal in the biofuel sector is to increase the efficiency of the circularization of the use of materials (1). One such instance is the degradation of plant material, such as cellulose, and converting it to biofuel via bacterial digestion (2). The bifunctional aldehyde-alcohol dehydrogenase (AdhE) from the anaerobic thermophile C. thermocellum seems to be vital for the production and cellular tolerance of bioethanol; however, it lacks the efficiency to produce ethanol at industry standards (3). Therefore, to understand how C. thermocellum AdhE functions, we used cryo-electron microscopy (cryo-EM) to obtain a 3.2 A structure of the AdhE complex. When compared to previously published structures from E. coli (4-6), we identified potential regions that control the native conformation of the ultrastructure, as well as located channels that isolate the intermediate aldehyde from the cellular milieu. This high-resolution structure, in combination with molecular dynamics simulations, provides insight into one example of substrate channeling and establishes a basis for future mutagenesis studies.

AdhE↗
DOE OSTI2023

PLAT domain protein 1 (PLAT1/PLAFP) binds to the Arabidopsis thaliana plasma membrane and inserts a lipid

Robust agricultural yields depend on the plant's ability to fix carbon amid variable environmental conditions. Over seasonal and diurnal cycles, the plant must constantly adjust its metabolism according to available resources or external stressors. The metabolic changes that a plant undergoes in response to stress are well understood, but the long-distance signaling mechanisms that facilitate communication throughout the plant are less studied. The phloem is considered the predominant conduit for the bidirectional transport of these signals in the form of metabolites, nucleic acids, proteins, and lipids. Lipid trafficking through the phloem in particular attracted our attention due to its reliance on soluble lipid-binding proteins (LBP) that generate and solubilize otherwise membrane-associated lipids. The Phloem Lipid-Associated Family Protein (PLAFP) from Arabidopsis thaliana is generated in response to abiotic stress as is its lipid-ligand phosphatidic acid (PA). PLAFP is proposed to transport PA through the phloem in response to drought stress. To understand the interactions between PLAFP and PA, nearly 100 independent systems comprised of the protein and one PA, or a plasma membrane containing varying amounts of PA, were simulated using atomistic classical molecular dynamics methods. In these simulations, PLAFP is found to bind to plant plasma membrane models independent of the PA concentration. When bound to the membrane, PLAFP adopts a binding pose where W41 and R82 penetrate the membrane surface and anchor PLAFP. This triggers a separation of the two loop regions containing W41 and R82. Subsequent simulations indicate that PA insert into the β -sandwich of PLAFP, driven by interactions with multiple amino acids besides the W41 and R82 identified during the insertion process. Finally, fine-tuning the protein-membrane and protein-PA interface by mutating a selection of these amino acids may facilitate engineering plant signaling processes by modulating the binding response.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Addition of Chloroform in a Solvent-in-Salt Electrolyte: Outcomes in the Microscopic Dynamics in Bulk and Confinement

Solvent-in-salt electrolytes (SISEs) are a promising alternative to the electrolytes currently used in commercial devices. Despite the SISEs’ advantages, their utilization is not yet realized due to the poor mobility of their chemical species. Here, we explore this problem by adding chloroform to a SISE formed by acetonitrile and a Li-salt. First, we performed illustrative cycling experiments to highlight the potential of this approach. Then, we focused on the description of the microscopic dynamics of the electrolytes and exposed the relevant aspects to be considered for their optimal performance. While the conductivity at low temperatures may be enhanced by the addition of chloroform, only subtle changes occur at room temperature. As revealed by molecular dynamics simulations and quasielastic neutron scattering (QENS) experiments, this effect is related to the preservation of the structure expected for a highly concentrated solution and promotion of the formation of ionic aggregates. These outcomes occur despite the increase in the overall mobility of the chemical species. The dynamics of the electrolytes in porous carbon was also investigated using QENS. In these circumstances, low concentrations of chloroform lead to diffusivities of the molecular species higher than those observed for the bulk electrolytes. As chloroform’s concentration increases, no further changes in the diffusivities are observed. Nonetheless, chloroform is mostly immobilized on the carbon surfaces and this behavior may be intensified at compositions closer to the eutectic mixture.

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

Fluctuating hydrodynamics of chiral active fluids

Active materials are characterized by continuous injection of energy at the microscopic level and typically cannot be adequately described by equilibrium thermodynamics. Here we study a class of active fluids in which equilibrium-like properties emerge when fluctuating and activated degrees of freedom are statistically decoupled, such that their mutual information is negligible. We analyse three paradigmatic systems: chiral active fluids composed of spinning frictional particles that are free to translate, oscillating granular gases and active Brownian rollers. In all of these systems, a single effective temperature generated by activity parameterizes both the equation of state and the emergent Boltzmann statistics. The same effective temperature, renormalized by velocity correlations, relates viscosities to steady-state stress fluctuations via a Green–Kubo relation. To rationalize these observations, we develop a theory for the fluctuating hydrodynamics of these non-equilibrium fluids and validate it through large-scale molecular dynamics simulations. Our work sheds light on the microscopic origin of odd viscosities and stress fluctuations characteristic of parity-violating fluids, in which mirror symmetry and detailed balance are broken.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Functional enzyme–polymer complexes

Significance The use of biological enzyme catalysts could have huge ramifications for chemical industries. However, these enzymes are often inactive in nonbiological conditions, such as high temperatures, present in industrial settings. Here, we show that the enzyme PETase (polyethylene terephthalate [PET]), with potential application in plastic recycling, is stabilized at elevated temperature through complexation with random copolymers. We demonstrate this through simulations and experiments on different types of substrates. Our simulations also provide strategies for designing more enzymatically active complexes by altering polymer composition and enzyme charge distribution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Solvation Energy of Ions in a Stockmayer Fluid

We calculate the solvation energy of monovalent and divalent ions in various liquids with coarse-grained molecular dynamics simulations. Our theory treats the solvent as a Stockmayer fluid, which accounts for the intrinsic dipole moment of molecules and the rotational dynamics of the dipoles. Despite the simplicity of the model, we obtain qualitative agreement between the simulations and experimental data for the free energy and enthalpy of ion solvation, which indicates that the primary contribution to the solvation energy arises mainly from the first and possibly second solvation shells near the ions. Our results suggest that a Stockmayer fluid can serve as a reference model that enables direct comparison between theory and experiment and may be invoked to scale up electrostatic interactions from the atomic to the molecular length scale.

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

Enzyme kinetics by GH7 cellobiohydrolases on chromogenic substrates is dictated by non‐productive binding: insights from crystal structures and MD simulation

Cellobiohydrolases (CBHs) in the glycoside hydrolase family 7 (GH7) ( EC3.2.1.176 ) are the major cellulose degrading enzymes both in industrial settings and in the context of carbon cycling in nature. Small carbohydrate conjugates such as p‐ nitrophenyl‐β‐ d ‐cellobioside (pNPC), p‐ nitrophenyl‐β‐ d ‐lactoside (pNPL) and methylumbelliferyl‐β‐ d ‐cellobioside have commonly been used in colorimetric and fluorometric assays for analysing activity of these enzymes. Despite the similar nature of these compounds the kinetics of their enzymatic hydrolysis vary greatly between the different compounds as well as among different enzymes within the GH7 family. Through enzyme kinetics, crystallographic structure determination, molecular dynamics simulations, and fluorometric binding studies using the closely related compound o‐nitrophenyl‐β‐ d ‐cellobioside (oNPC), in this work we examine the different hydrolysis characteristics of these compounds on two model enzymes of this class, TrCel7A from Trichoderma reesei and PcCel7D from Phanerochaete chrysosporium . Protein crystal structures of the E212Q mutant of TrCel7A with pNPC and pNPL, and the wildtype TrCel7A with oNPC, reveal that non‐productive binding at the product site is the dominating binding mode for these compounds. Enzyme kinetics results suggest the strength of non‐productive binding is a key determinant for the activity characteristics on these substrates, with PcCel7D consistently showing higher turnover rates ( k cat ) than TrCel7A, but higher Michaelis–Menten ( K M ) constants as well. Furthermore, oNPC turned out to be useful as an active‐site probe for fluorometric determination of the dissociation constant for cellobiose on TrCel7A but could not be utilized for the same purpose on PcCel7D, likely due to strong binding to an unknown site outside the active site.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to Experiment

Methodologies for training machine learning potentials (MLPs) with quantum-mechanical simulation data have recently seen tremendous progress. Experimental data have a very different character than simulated data, and most MLP training procedures cannot be easily adapted to incorporate both types of data into the training process. Here, we investigate a training procedure based on iterative Boltzmann inversion that produces a pair potential correction to an existing MLP using equilibrium radial distribution function data. By applying these corrections to an MLP for pure aluminum based on density functional theory, we observe that the resulting model largely addresses previous overstructuring in the melt phase. Interestingly, the corrected MLP also exhibits improved performance in predicting experimental diffusion constants, which are not included in the training procedure. The presented method does not require autodifferentiating through a molecular dynamics solver and does not make assumptions about the MLP architecture. Our results suggest a practical framework for incorporating experimental data into machine learning models to improve the accuracy of molecular dynamics simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analyzing the effect of pressure on the properties of point defects in $\gamma\mathrm{U–Mo}$ through atomistic simulations

Uranium–molybdenum (U–Mo) alloys in monolithic fuel foil are the primary candidate for the conversion of high-performance research reactors in the USA. Monolithic fuel is utilized in a plate-type design with a zirconium diffusion barrier and aluminum cladding. These fuel types are unique in that they contain no plenum for the release of fission gases, which, in conjunction with the aluminum cladding, can lead to large stress states within the fuel. The nature of how fundamental processes of radiation damage, including the evolution of point defects, under such stresses occur is unknown. In this work, we present molecular dynamics simulations of the formation energy of point defects under applied stress. We report this work will allow for the implementation of stress-dependent microstructural evolution models of nuclear fuels, including those for both fission gas bubble growth and creep, which are critical to ensure the stable and predictable behavior of research reactor fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Scaling Theory of Neutral Sequence-Specific Polyampholytes

The primary sequence of charged monomers in a polyampholyte has a profound effect on its conformational properties. In this work, theory and simulations are used to predict how the sequence influences the single-chain behavior of globally neutral polyampholytes (PAs) under salt-free conditions. We consider PAs with Markov statistics of charges, where charge “blockiness” is defined by the correlation λ along the chain. These PAs cover a wide spectrum of primary sequences ranging from alternating (λ = –1) to ideally random (λ = 0) to diblock (λ → 1). In a theta solvent, sufficiently long PAs of any primary sequence form globules, but their internal structure, as well as the position and sharpness of the coil–globule transition, crucially depends on λ. Further, using scaling arguments, we demonstrate that the excess charge of the globule correlation volume (blob) increases with increasing λ, thereby inducing stronger Coulomb attractions between neighboring blobs of opposite charge and leading to higher density PA globules. Scaling predictions are supported by the results of the random phase approximation (RPA) and coarse-grained molecular dynamics simulations. A generalization to good and poor solvents is presented that enables the construction of the resulting scaling diagram of PA conformations in terms of solvent quality and charge blockiness, thereby providing a comprehensive molecular understanding of the role of the PA primary sequence in the chain structure.

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

Predicting Outcomes of Nanoparticle Attachment by Connecting Atomistic, Interfacial, Particle, and Aggregate Scales

Predicting nanoparticle aggregation and attachment phenomena requires a rigorous understanding of the interplay among crystal structure, particle morphology, surface chemistry, solution conditions, and interparticle forces, yet no comprehensive picture exists. We used an integrated suite of experimental, theoretical, and simulation methods to resolve the effect of solution pH on the aggregation of boehmite nanoplatelets, a case study with important implications for the environmental management of legacy nuclear waste. Real-time observations showed that the particles attach preferentially along the (010) planes at pH 8.5 and the (101) planes at pH 11. To rationalize these results, we established the connection between key physicochemical phenomena across the relevant length scales. Starting from molecular-scale simulations of surface hydroxyl reactivity, we developed an interfacial-scale model of the corresponding electrostatic potentials, with subsequent particle-scale calculations of the resulting driving forces allowing successful prediction of the attachment modes. Finally, we scaled these phenomena to understand the collective structure at the aggregate-scale . Here, our results indicate that facet-specific differences in surface chemistry produce heterogeneous surface charge distributions that are coupled to particle anisotropy and shape-dependent hydrodynamic forces, to play a key role in controlling aggregation behavior.

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

Biomolecular condensates form spatially inhomogeneous network fluids

The functions of biomolecular condensates are thought to be influenced by their material properties, and these will be determined by the internal organization of molecules within condensates. However, structural characterizations of condensates are challenging, and rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that are formed by macromolecules from nucleolar granular components (GCs). We show that these minimal facsimiles of GCs form condensates that are network fluids featuring spatial inhomogeneities across different length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights suggest that condensates formed by multivalent proteins share features with network fluids formed by systems such as patchy or hairy colloids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Dynamic Control of Photocatalytic Proton Reduction through the Mechanical Actuation of a Hydrogel Host Matrix

This paper describes a photocatalytic hydrogen evolution system that is dynamically and reversibly responsive to the pH of the surrounding solution through actuation of a micro-hydrogel (microgel) matrix that hosts the photocatalysts (CdSe/CdS nanorods). Here, the reversible actuation occurs within 0.7 s (swelling) and 1.7 s (contraction). A ΔpH of 0.01 relative to the pK a of the tertiary amine on the microgel polymer (7.27) results in a reversible change in the average diameter of the microgel hosts by a factor of 2.5 and a change in the photocatalytic turnover frequency (TOF) by a factor of five. Kinetic isotope effect and photoluminescence quenching experiments reveal that the scavenging of the photoexcited hole by sulfite ions is the rate-limiting step and leads to the observed response of the TOF to pH through actuation of the microgel. Molecular dynamics simulations quantify a greater local concentration of sulfite hole scavengers for pH < pK a .

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

Atomistic, macromolecular model of the Populus secondary cell wall informed by solid-state NMR

Plant secondary cell walls (SCWs) are composed of a heterogeneous interplay of three major biopolymers: cellulose, hemicelluloses, and lignin. Details regarding specific intermolecular interactions and higher-order architecture of the SCW superstructure remain ambiguous. Here, we use solid-state nuclear magnetic resonance (ssNMR) measurements to infer refined details about the structural configuration, intermolecular interactions, and relative proximity of all three major biopolymers within air-dried Populus wood. To enhance the utility of these findings and enable evaluation of hypotheses in a physics-based environment in silico, the NMR observables are articulated into an atomistic, macromolecular model for biopolymer assemblies within the plant SCW. Through molecular dynamics simulation, we quantitatively evaluate several variations of atomistic models to determine structural details that are corroborated by ssNMR measurements.

09 BIOMASS FUELS↗
DOE OSTI2021

Persistent Homology Metrics Reveal Quantum Fluctuations and Reactive Atoms in Path Integral Dynamics

Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, given the significant interest in methods such as centroid molecular dynamics and ring polymer molecular dynamics that link the molecular dynamics of these ring polymers to real time properties, there exists significant opportunity to exploit metrics that also allow for the study of the fluctuations of the atom delocalization in time. Here we consider the ring polymer delocalization from the perspective of computational topology, specifically persistent homology, which describes the 3-dimensional arrangement of point cloud data, (i.e. atomic positions). We employ the Betti sequence probability distribution to define the ensemble of shapes adopted by the ring polymer. The Wasserstein distances of Betti sequences adjacent in time are used to characterize fluctuations in shape, where the Fourier transform and associated principal components provides added information differentiating atoms with different NQEs based on their dynamic properties. We demonstrate this methodology on two representative systems, a glassy system consisting of two atom types with dramatically different de Broglie thermal wavelengths, and ab initio molecular dynamics simulation of an aqueous 4 M HCl solution where the H-atoms are differentiated based on their participation in proton transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Molecular Dynamics Investigation of Oil Wetting on Synthetic Polymer Substrates

Understanding the interaction of polymer surfaces with nonpolar, low surface tension liquids, or whether a substrate is oleophobic versus oleophilic, is critical for applications ranging from antifingerprint coatings to oil–water separation membranes and oil spill remediation. Despite its technological importance, the molecular mechanisms underpinning polymer–oil wetting are not well characterized. Here, we employ molecular dynamics simulations to investigate the behavior of n-hexadecane in contact with chemically distinct polymer surfaces, spanning eight constitutional unit chemistries as well as amorphous and crystalline morphologies. This permits a critical examination of both thermodynamic and dynamic descriptors of oleophobicity, including oil contact angle, dewetting free energy, interfacial diffusivity, and a proposed “ghost probe energy,” which does not require explicit simulation of oil–polymer interactions. We find that the oil contact angle does not reliably distinguish oleophobic behavior across polymer chemistries, whereas other metrics provide clearer and more consistent differentiation. Analysis of the results reveals that polymer–oil wetting behavior is primarily governed by interfacial van der Waals interactions and modulated by surface flexibility and morphology. Collectively, this work establishes a computational framework for characterizing oil wetting and provides additional insight into what molecular-level factors dictate trends in oleophobicity.

lipids↗
DOE OSTI2021

Spatiotemporal mapping of mesoscopic liquid dynamics

The study of liquid dynamics at mesoscopic scales is still strewn with difficulty due to limitations in theory and experiment. Historically, significant attention has been given to the analysis of space-time correlation functions and their frequency-Fourier transforms at a few discrete wave numbers. The massive computing power afforded by modern high performance computing clusters and the advent of a wide-angle neutron spin-echo spectrometer, however, have unlocked a more intuitive and fruitful approach to this problem. Using molecular dynamics simulations, here we demonstrate the benefits of spatiotemporally mapping intermediate scattering functions on a dense grid of correlation times and wave numbers. Four model systems are investigated: a Lennard-Jones liquid, a coarse-grained bead-spring polymer, a molten sodium chloride, and a poly(ethylene oxide) melt. We show that the spatiotemporal mapping approach is particularly useful for elucidating the mesoscopic dynamics in these liquids, where several underlying mechanisms, such as molecular relaxations, hydrodynamic modes, and nonhydrodynamic excitations, are potentially at play. Therefore, compared to the traditional method, direct visualization of density space-time correlation functions on two-dimensional color maps permits appraisals of complicated dynamical behavior at mesoscales in a global manner. For example, the scaling relations between space and time for different types of molecular motions can be straightforwardly identified on these plots, without any model-dependent analysis. Additionally, we show how theoretical ideas regarding collective mesoscopic dynamics, such as the classical hydrodynamic theory, the convolution approximation, and a recently proposed phenomenological model, can be discussed in terms of the global features of spatiotemporal maps of intermediate scattering functions. The new perspective offered by the spatiotemporal mapping method should prove useful for the study of liquid dynamics in general.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗