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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Technical Note: Development of a 3D printed subresolution sandwich phantom for validation of brain SPECT analysis

Purpose: To make an adaptable, head shaped radionuclide phantom to simulate molecular imaging of the brain using clinical acquisition and reconstruction protocols. This will allow the characterization and correction of scanner characteristics, and improve the accuracy of clinical image analysis, including the application of databases of normal subjects. Methods: A fused deposition modeling 3D printer was used to create a head shaped phantom made up of transaxial slabs, derived from a simulated MRI dataset. The attenuation of the printed polylactide (PLA), measured by means of the Hounsfield unit on CT scanning, was set to match that of the brain by adjusting the proportion of plastic filament and air (fill ratio). Transmission measurements were made to verify the attenuation of the printed slabs. The radionuclide distribution within the phantom was created by adding {sup 99m}Tc pertechnetate to the ink cartridge of a paper printer and printing images of gray and white matter anatomy, segmented from the same MRI data. The complete subresolution sandwich phantom was assembled from alternate 3D printed slabs and radioactive paper sheets, and then imaged on a dual headed gamma camera to simulate an HMPAO SPECT scan. Results: Reconstructions of phantom scans successfully used automated ellipse fitting to apply attenuation correction. This removed the variability inherent in manual application of attenuation correction and registration inherent in existing cylindrical phantom designs. The resulting images were assessed visually and by count profiles and found to be similar to those from an existing elliptical PMMA phantom. Conclusions: The authors have demonstrated the ability to create physically realistic HMPAO SPECT simulations using a novel head-shaped 3D printed subresolution sandwich method phantom. The phantom can be used to validate all neurological SPECT imaging applications. A simple modification of the phantom design to use thinner slabs would make it suitable for use in PET.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Learning local equivariant representations for large-scale atomistic dynamics

Abstract A simultaneously accurate and computationally efficient parametrization of the potential energy surface of molecules and materials is a long-standing goal in the natural sciences. While atom-centered message passing neural networks (MPNNs) have shown remarkable accuracy, their information propagation has limited the accessible length-scales. Local methods, conversely, scale to large simulations but have suffered from inferior accuracy. This work introduces Allegro, a strictly local equivariant deep neural network interatomic potential architecture that simultaneously exhibits excellent accuracy and scalability. Allegro represents a many-body potential using iterated tensor products of learned equivariant representations without atom-centered message passing. Allegro obtains improvements over state-of-the-art methods on QM9 and revMD17. A single tensor product layer outperforms existing deep MPNNs and transformers on QM9. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular simulations using Allegro recover structural and kinetic properties of an amorphous electrolyte in excellent agreement with ab-initio simulations. Finally, we demonstrate parallelization with a simulation of 100 million atoms.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Exploring the impacts of conformer selection methods on ion mobility collision cross section predictions

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection of the correct population of molecular conformers. Here, we report an in-depth evaluation of multiple conformation selection techniques, including simple averaging, Boltzmann weighting, lowest energy selection, low energy threshold reductions, and similarity reduction. Generating 50,000 conformers each for 18 molecules, we used the In Silico Chemical Library Engine (ISiCLE) to calculate the collision cross sections for the entire dataset. First, we employed Monte Carlo simulations to understand the variability between conformer structures as generated using simulated annealing. Then we employed Monte Carlo simulations to the aforementioned conformer selection techniques applied on the simulated molecular property—the ion mobility collision cross section. Based on our analyses, we found Boltzmann weighting to be a good tradeoff between precision and theoretical accuracy. Combining multiple techniques revealed that energy thresholds and root-mean-squared deviation-based similarity reductions can save considerable computational expense while maintaining property prediction accuracy. Molecular dynamic conformer generation tools like AMBER can continue to generate new lowest energy conformers even after tens of thousands of generations, decreasing precision between runs. This reduced precision can be ameliorated and theoretical accuracy increased by running density functional theory geometry optimization on carefully selected conformers.

Nielson, Felicity F.↗
DOE OSTI2016

Highly stable and self-repairing membrane-mimetic 2D nanomaterials assembled from lipid-like peptoids

Two-dimensional (2D) materials with molecular-scale thickness have attracted increasing interest for separation, electronic, catalytic, optical, energy and biomedical applications. Although extensive research on 2D materials, such as graphene and graphene oxide, has been performed in recent years, progress is limited on self-assembly of 2D materials from sequence-specific macromolecules, especially from synthetic sequences that could exhibit lipid-like self-assembly of bilayer sheets and mimic membrane proteins for functions. The creation of such new class of materials could enable development of highly stable biomimetic membranes that exhibit cell-membrane-like molecular transport with exceptional selectively and high transport rates. Here we demonstrate self-assembly of lipid-like 12-mer peptoids into extremely stable, crystalline, flexible and free-standing 2D membrane materials. As with cell membranes, upon exposure to external stimuli, these materials exhibit changes in thickness, varying from 3.5 nm to 5.6 nm. We find that self-assembly occurs through a facile crystallization process, in which inter-peptoid hydrogen bonds and enhanced hydrophobic interactions drive the formation of a highly-ordered structure. Molecular simulation confirms this is the energetically favored structure. Displaying functional groups at arbitrary locations of membrane-forming peptoids produces membranes with similar structures. This research further shows that single-layer membranes can be coated onto substrate surfaces. Moreover, membranes with mechanically-induced defects can self-repair. Given that peptoids are sequence-specific and exhibit protein-like molecular recognition with enhanced stability, we anticipate our membranes to be a robust platform tailored to specific applications.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Hydrogen adsorption and desorption with 3D silicon nanotube-network and film-network structures: Monte Carlo simulations

Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Carbon mineralization pathways in interfacial adsorbed water nanofilms

Carbon mineralization in humidified carbon dioxide offers a promising route to mitigate anthropogenic emissions in a world stressed by water security. Despite its technological importance, our understanding of carbonation in water-poor environments lags, as traditional dissolution-precipitation pathways struggle to explain the adsorbed water nanofilm-mediated reactivity. Here, we utilize in operando X-ray diffraction (XRD) and advanced molecular simulations to investigate nanoconfined reactions driving forsterite carbonation, the magnesium-rich olivine. By examining magnesium ion dissolution and transport in atomistic simulations of the forsterite-water-carbon dioxide interface and comparing these with the in operando XRD activation energies, we identify both processes as rate-limiting at saturation. Our simulations reveal a mechanistic view of interfacial carbonation, where dissolution and precipitation are mediated by anomalous quasi two-dimensional diffusion. The transport process involves intermittent diffusive hopping in the desorbed state, separated by crawling events that are spatially short but temporally long. This understanding transcends carbon mineralization, with implications for understanding the transport of contaminants in geosystems, the design of multifunctional materials, water desalination, and molecular recognition systems.

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

Understanding the Unusual Adsorption Behavior in Hierarchical Zeolite Nanosheets

Hierarchical zeolites are advanced materials possessing the catalytic and adsorption properties of conventional zeolites while eliminating their transport limitations through the introduction of mesopores. Recent experiments comparing the adsorption in hierarchical self-pillared pentasils (SPP) and silicalite-1 (MFI) revealed an interesting crossover in sorbate loading for branched or long-chain alkanes but not for shorter linear alkanes, but an explanation for this behavior is not readily available through experimental probes due to the complications arising from the presence of multiple adsorption sites. We present a molecular simulation study on the adsorption of alkane isomers and show that a multi-step mechanism, found here for all molecules, is responsible for the observed phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Nuclear quantum effects enter the mainstream

Atomistic simulations of chemical, biological and materials systems have become increasingly precise and predictive owing to the development of accurate and efficient techniques that describe the quantum mechanical behaviour of electrons. Nevertheless, the overwhelming majority of such simulations still assumes that the nuclei behave as classical particles. Historically, this approximation could sometimes be justified owing to the complexity and computational overhead. However, neglecting nuclear quantum effects has become one of the largest sources of error, especially when systems containing light atoms are treated using current state-of-the-art descriptions of chemical interactions. Over the past decade, this realization has spurred a series of methodological advances that have dramatically reduced the cost of including these important physical effects in the structure and dynamics of chemical systems. We discuss how these developments are now allowing nuclear quantum effects to become a mainstream feature of molecular simulations. These advances have led to new insights into phenomena that are relevant to different areas of science — from biochemistry to condensed matter — and open the door to many exciting future opportunities.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2013

Optimizing nanoporous materials for gas storage

In this work, we address the question of which thermodynamic factors determine the deliverable capacity of methane in nanoporous materials. The deliverable capacity is one of the key factors that determines the performance of a material for methane storage in automotive fuel tanks. To obtain insights in how the molecular characteristics of a material are related to this deliverable capacity, we developed several statistical thermodynamic models. The predictions of these models are compared with the classical thermodynamics approach of Bhatia and Myers [Bhatia and Myers Langmuir, 2005, 22, 1688] and with the results of molecular simulations in which we screen the IZA zeolite structures and a hypothetical zeolite database of over 100,000 structures. Both the simulations and our models do not support the rule of thumb that, for methane storage, one should aim for an optimal heat of adsorption of 18.8 kJ/mol -1 . Instead, our models show that one can identify an optimal heat of adsorption, but that this optimal heat of adsorption depends on the structure of the material. The different models we have developed are aimed to provide guidelines on how this optimal heat of adsorption is related to the molecular structure of the material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Generalized ensemble method applied to study systems with strong first order transitions

At strong first-order phase transitions, the entropy versus energy or, at constant pressure, enthalpy, exhibits convex behavior, and the statistical temperature curve correspondingly exhibits an S-loop or back-bending. In the canonical and isothermal-isobaric ensembles, with temperature as the control variable, the probability density functions become bimodal with peaks localized outside of the S-loop region. Inside, states are unstable, and as a result simulation of equilibrium phase coexistence becomes impossible. To overcome this problem, a method was proposed by Kim, Keyes and Straub, where optimally designed generalized ensemble sampling was combined with replica exchange, and denoted generalized replica exchange method (gREM). This new technique uses parametrized effective sampling weights that lead to a unimodal energy distribution, transforming unstable states into stable ones. In the present study, the gREM, originally developed as a Monte Carlo algorithm, was implemented to work with molecular dynamics in an isobaric ensemble and coded into LAMMPS, a highly optimized open source molecular simulation package. Lastly, the method is illustrated in a study of the very strong solid/liquid transition in water.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Effects of Lytic Polysaccharide Monooxygenase Oxidation on Cellulose Structure and Binding of Oxidized Cellulose Oligomers to Cellulases

In nature, polysaccharide glycosidic bonds are cleaved by hydrolytic enzymes for a vast array of biological functions. Recently, a new class of enzymes that utilize an oxidative mechanism to cleave glycosidic linkages was discovered; these enzymes are called lytic polysaccharide monooxygenases (LPMO). These oxidative enzymes are synergistic with cocktails of hydrolytic enzymes and are thought to act primarily on crystalline regions, in turn providing new sites of productive attachment and detachment for processive hydrolytic enzymes. In the case of cellulose, the homopolymer of ..beta..-1,4-d-glucose, enzymatic oxidation occurs at either the reducing end or the nonreducing end of glucose, depending on enzymatic specificity, and results in the generation of oxidized chemical substituents at polymer chain ends. LPMO oxidation of cellulose is thought to produce either a lactone at the reducing end of glucose that can spontaneously or enzymatically convert to aldonic acid or 4-keto-aldose at the nonreducing end that may further oxidize to a geminal diol. Here, we use molecular simulation to examine the effect of oxidation on the structure of crystalline cellulose. The simulations highlight variations in behaviors depending on the chemical identity of the oxidized species and its location within the cellulose fibril, as different oxidized species introduce steric effects that disrupt local crystallinity and in some cases reduce the work needed for polymer decrystallization. Reducing-end oxidations are easiest to decrystallize when located at the end of the fibril, whereas nonreducing end oxidations readily decrystallize from internal cleavage sites despite their lower solvent accessibility. The differential in decrystallization free energy suggests a molecular mechanism consistent with experimentally observed LPMO/cellobiohydrolase synergy. Additionally, the soluble oxidized cellobiose products released by hydrolytic cellulases may bind to the active sites of cellulases with different affinities relative to cellobiose itself, which potentially affects hydrolytic turnover through product inhibition. To examine the effect of oxidation on cello-oligomer binding, we use thermodynamic integration to compute the relative change in binding free energy between the hydrolyzed and oxidized products in the active site of Family 7 and Family 6 processive glycoside hydrolases, Trichoderma reesei Cel7A and Cel6A, which are key industrial cellulases and commonly used model systems for fungal cellulases. Our results suggest that the equilibrium between the two reducing end oxidized products, favoring the linear aldonic acid, may increase product inhibition, which would in turn reduce processive substrate turnover. In the case of LMPO action at the nonreducing end, oxidation appears to lower affinity with the nonreducing end specific cellulase, reducing product inhibition and potentially promoting processive cellulose turnover. Overall, this suggests that oxidation of recalcitrant polysaccharides by LPMOs accelerates degradation not only by increasing the concentration of chain termini but also by reducing decrystallization work, and that product inhibition may be somewhat reduced as a result.

09 BIOMASS FUELS↗
DOE OSTI2018

Studies of lysine cyclodeaminase from Streptomyces pristinaespiralis: Insights into the complex transition NAD+ state

Highlights: • LCD and its three structure complexes are determined for the first time. • A NAD{sup +} gate function was revealed in LCD by combining molecular simulation methods. • A substrate tunnel towards NAD{sup +} was observed in LCD via alignment of structures. • This study expands our understanding of catalytic NAD{sup +} usage in various enzymes. Lysine cyclodeaminase (LCD) catalyzes the piperidine ring formation in macrolide-pipecolate natural products metabolic pathways from a lysine substrate through a combination of cyclization and deamination. This enzyme belongs to a unique enzyme class, which uses NAD{sup +} as the catalytic prosthetic group instead of as the co-substrate. To understand the molecular details of NAD{sup +} functions in lysine cyclodeaminase, we have determined four ternary crystal structure complexes of LCD-NAD{sup +} with pipecolic acid (LCD-PA), lysine (LCD-LYS), and an intermediate (LCD-INT) as ligands at 2.26-, 2.00-, 2.17- and 1.80 Å resolutions, respectively. By combining computational studies, a NAD{sup +}-mediated “gate keeper” function involving NAD{sup +}/NADH and Arg49 that control the binding and entry of the ligand lysine was revealed, confirming the critical roles of NAD{sup +} in the substrate access process. Further, in the gate opening form, a substrate delivery tunnel between ε-carboxyl moiety of Glu264 and the α-carboxyl moiety of Asp236 was observed through a comparison of four structure complexes. The LCD structure details including NAD{sup +}-mediated “gate keeper” and substrate tunnel may assist in the exploration the NAD{sup +} function in this unique enzyme class, and in regulation of macrolide-pipecolate natural product synthesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

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

Controlling Structure and Properties of Vapor-Deposited Glasses of Organic Semiconductors: Recent Advances and Challenges

The past decade has seen great progress in manipulating the structure of vapor-deposited glasses of organic semiconductors. Upon varying the substrate temperature during deposition, glasses with a wide range of density and molecular orientation can be prepared from a given molecule. Here, we review recent studies that show the structure of vapor-deposited glasses can be tuned to significantly improve the external quantum efficiency and lifetime of organic light-emitting diodes (OLEDs). We highlight the ability of molecular simulations to reproduce experimentally observed structures, setting the stage for in silico design of vapor-deposited glasses in the coming decade. Finally, we identify research opportunities for improving the properties of organic semiconductors by controlling the structure of vapor-deposited glasses.

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

Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic–inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. Here, to understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31–calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ∼2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31–calcite interactions. While this work provides the first experimental confirmation that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31–calcite interface has advanced our fundamental understanding of the atomic interactions at the organic–inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Close, Emily G. S. [Pacific Northwest National Lab↗
DOE OSTI2021

Adsorption space for microporous polymers with diverse adsorbate species

Abstract The enormous number of combinations of adsorbing molecules and porous materials that exist is known as adsorption space. The adsorption space for microporous polymers has not yet been systematically explored, especially when compared with efforts for crystalline adsorbents. We report molecular simulation data for the adsorptive and structural properties of polymers of intrinsic microporosity with a diverse set of adsorbate species with 345 distinct adsorption isotherms and over 240,000 fresh and swollen structures. These structures and isotherms were obtained using a sorption-relaxation technique that accounts for the critical role of flexibility of the polymeric adsorbents. This enables us to introduce a set of correlations that can estimate adsorbent swelling and fractional free volume dilation as a function of adsorbate uptake based on readily characterized properties. The separation selectivity of the 276 distinct binary molecular pairs in our data is reported and high-performing adsorbent systems are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Visualizing group II intron dynamics between the first and second steps of splicing

Group II introns are ubiquitous self-splicing ribozymes and retrotransposable elements evolutionarily and chemically related to the eukaryotic spliceosome, with potential applications as gene-editing tools. Recent biochemical and structural data have captured the intron in multiple conformations at different stages of catalysis. Here, we employ enzymatic assays, X-ray crystallography, and molecular simulations to resolve the spatiotemporal location and function of conformational changes occurring between the first and the second step of splicing. We show that the first residue of the highly-conserved catalytic triad is protonated upon 5’-splice-site scission, promoting a reversible structural rearrangement of the active site (toggling). Protonation and active site dynamics induced by the first step of splicing facilitate the progression to the second step. Our insights into the mechanism of group II intron splicing parallels functional data on the spliceosome, thus reinforcing the notion that these evolutionarily-related molecular machines share the same enzymatic strategy.

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

DataSet for Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic-inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. To understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31-calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ~2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31-calcite interactions. These studies provide the first experimental evidence to confirm that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template. However, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31-calcite interface has advanced our fundamental understanding of the atomic interactions at the organic-inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Saccuzzo Close, Emily Grace [Pacific Northwest Nat↗