Search NASA⌕ Search

SEARCH · Search NASA

Results for “molecular ordering”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Orientational Order in Spin-Cast Lead-Iodide Perovskite Nanocrystal Solids

Combined synthetic control over size and composition renders colloidal lead-halide perovskite nanocrystals a tunable platform for high-efficiency optoelectronic applications. However, the properties and operational stability of devices based on nanocrystal solids are often dictated by the method of the evaporation-induced assembly. Ubiquitous slow evaporation techniques can produce highly ordered nanocrystal domains but limit the prospects for scalable fabrication of continuous device layers, calling for investigation of approaches to more rapidly form ordered perovskite nanocrystal solids. Here, we study orientationally ordered lead-iodide perovskite nanocrystal solids prepared by conventional spin coating with molecular additives (excess ligand) to enhance ordering within the arrays. In situ X-ray scattering measurements reveal that orientational ordering occurs rapidly upon solvent removal during spin coating and can be further enhanced by manipulating the spin speed. We vary the additive ligand length and explore trade-offs between ordering and layered perovskite impurity formation. Arrays treated with the intermediate-length octylamine ligand exhibit increased in-plane electronic conductivity, suggesting orientational ordering and internanocrystal electronic coupling can be enhanced by the treatment. In conclusion, these results highlight the prospects of establishing long-range order in lead-halide perovskite nanocrystal solids by using simple and fast coating methods.

14 SOLAR ENERGY↗
DOE OSTI2021

Scalable ab initio fragmentation methods based on a truncated expansion of the non-orthogonal molecular orbital model

An alternative formulation of the non-orthogonal molecular orbital model of electronic structure theory is developed based on the expansion of the inverse molecular orbital overlap matrix. From this model, a hierarchy of ab initio fragment-based quantum chemistry methods, referred to as the nth-order expanded non-orthogonal molecular orbital methods, are developed using a minimal number of approximations, each of which is frequently employed in intermolecular interaction theory. These novel methods are compared to existing fragment-based quantum chemistry methods, and the implications of those significant differences, where they exist, between the methods developed herein and those already existing methods are examined in detail. Computational complexities and theoretical scaling are also analyzed and discussed. Future extensions for the hierarchy of methods, to account for additional intrafragment and interfragment interactions, are outlined.

Westheimer, Bryce M. (ORCID:0000000267645714)↗
DOE OSTI2023

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations

Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds due to advances in combinatorial chemistry. Traditional methods for identifying "hit" molecules from a large collection of potential drug-like candidates have relied on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have the major drawback that they require exceptional computing capabilities for even relatively small collections of molecules. Hyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with high-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas. We consider existing HDC approaches for molecular property classification and introduce two novel encodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP). We show that HDC-based inference methods are as much as 91 times more efficient than traditional machine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to molecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a number of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and bind/no-bind activity classification using the DUD-E and LIT-PCBA datasets. Our work thus motivates further investigation into molecular representation learning to develop ultraefficient pre-screening tools.

Jones, William↗
DOE OSTI2022

Computational Engineering of Human Apolipoprotein for Enhanced Interaction with Bacterial Toxins

Sepsis is caused by an over-activation of the immune system in response to the presence of bacterial endotoxins in the bloodstream. LPS exemplifies a potent immune stimulator which can lead to an excessive activation leading to an overly pro-inflammatory reaction and if left untreated results in multi-organ failure and death. Human lipoproteins (HLP) have been shown to neutralize LPS and facilitate its clearance from circulation via the liver. However, host-derived lipoproteins are inhomogeneous in content and size, presenting a challenge for therapeutic applications. In this work, we have used IC facilities in order to computationally engineer HLP for an enhanced interaction with LPS. This work is a continuation of our previous efforts to derive an optimal Nanodisc (ND) lipid mixture for enhanced association with the endotoxin. We have performed fully atomistic Molecular dynamic (MD) simulations in order to carefully identify the most optimal residues in HLP, which can potentially lead to a stronger association to LPS.

42 ENGINEERING↗
DOE OSTI2024

Large-scale atomistic model construction of subbituminous and bituminous coals for solvent extraction simulations with reactive molecular dynamics

Large-scale atomistic models for complex polycyclic aromatic hydrocarbon systems help understand the chemical properties and behaviors of complex feedstocks such as coal or petroleum. However, the development and utilization of large-scale models remain limited due to the difficulty in achieving the varied structural characteristics necessary to capture stochastic nature of these feedstocks. Here we demonstrate a systematic workflow to construct stochastic molecular systems from a broad analytical suite: high-resolution transmission electron microscopy (HRTEM), carbon-13 nuclear magnetic resonance spectroscopy ( 13 C NMR), laser desorption ionization mass spectroscopy (LDI-MS), and elemental analysis. We present a model construction and analysis utility of a new Python-based module. We selected one subbituminous and three high-volatile bituminous coals to construct large-scale models (~40,000 atoms). The constructed models were utilized to examine the affinity for solvent extraction (naphthalene or tetralin) and the effect of structural properties (e.g., aromatic cluster size, functional groups, and cross-linking) in reactive molecular dynamics simulations. Complex chemical reactions were monitored with bond order transitions, intermediates formation, and mass distributions. Reactive molecular dynamics simulations suggest a plausible chemical extraction process and products for the complex fossil feedstocks. The results indicated that radical formations with bond breaking of bridging oxygens and carbons were required at high temperatures to facilitate hydrogeneration and extraction of gas molecules from radical-free molecules. We observed that aliphatic chains of tetralin were easily decomposed and combined with radicals to form small size of molecules with aryl bonding, mainly increasing molecules in the 500–1000 Da, while naphthalene had little impact on chemical extraction process.

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

Charge transport and antiferromagnetic ordering in nitroxide radical crystals

Nonconjugated radical polymers and small molecules are employed as functional materials in organic electronic devices. Furthermore, the unpaired electrons on these materials have permanent magnetic moments, making these materials promising candidates for organic magnets. Through molecular design, strong antiferromagnetic and ferromagnetic ordering have been achieved in conjugated materials. However, the magnetic properties of nonconjugated radical polymers have only shown weak magnetic interactions among the open-shell sites due to the large mean separation between radicals in typical materials. Here, we have designed, synthesized, and crystalized two open-shell molecules that used molecular engineering to control the assembly of the open-shell sites into a strong antiferromagnetically ordered network. The strong antiferromagnetic interaction is evidenced by a high paramagnetic-to-antiferromagnetic transition temperature of ~40 K. This high transition temperature was a result of a high spin exchange coupling constant J of about –20 cm –1 , which was suggested by both experimental and computed coupling parameters given by the energy difference between high-spin and low-spin broken-symmetry structures. In addition, a single-crystal electrical conductivity of ~10 –3 S m –1 was achieved, which indicated the potential of this material in electronic applications. As a result, this work provides an insight into a design strategy for radical-based electronic and magnetic materials through proper molecular structure modifications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lipid vesicles induced ordered nanoassemblies of Janus nanoparticles

Since many advanced applications require specific assemblies of nanoparticles (NPs), considerable efforts have been made to fabricate nanoassemblies with specific geometries. Although nanoassemblies can be fabricated through top-down approaches, recent advances show that intricate nanoassemblies can also be obtained through self-assembly, mediated for example by DNA strands. Here, we show, through extensive molecular dynamics simulations, that highly ordered self-assemblies of NPs can be mediated by their adhesion to lipid vesicles (LVs). Specifically, Janus NPs are considered so that the amount by which they are wrapped by the LV is controlled. The specific geometry of the nanoassembly is the result of effective curvature-mediated repulsion between the NPs and the number of NPs adhering to the LV. Further, the NPs are arranged on the LV into polyhedra which satisfy the upper limit of Euler's polyhedral formula, including several deltahedra and three Platonic solids, corresponding to the tetrahedron, octahedron, and icosahedron.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Leveraging peptide–cellulose interactions to tailor the hierarchy and mechanics of peptide–polymer hybrids

Inspired by spider silk's hierarchical diversity, we leveraged peptide motifs with the capability to tune structural arrangement for controlling the mechanical properties of a conventional polymer framework. The addition of nanofiller with hydrogen bonding sites was used as another pathway towards hierarchical tuning via matrix–filler interactions. Specifically, peptide–polyurea hybrids (PPUs) were combined with cellulose nanocrystals (CNCs) to develop mechanically-tunable nanocomposites via tailored matrix–filler interactions (or peptide–cellulose interactions). In this material platform, we explored the effect of these matrix–filler interactions on the secondary structure, hierarchical ordering, and mechanical properties of the peptide hybrid nanocomposites. Interactions between the peptide matrix and CNCs occur in all of the PPU/CNC nanocomposites, preventing α-helical ordering, but promoting inter-molecular hydrogen bonded β-sheet formation. Depending on peptide and CNC content, the Young's modulus varies from 10 to 150 MPa. Unlike conventional cellulose-reinforced polymer nanocomposites, the mechanical properties of these composite materials are dictated by a balance of CNC reinforcement, peptidic ordering, and microphase-separated morphology. This research highlights that leveraging peptide–cellulose interactions is a strategy to create materials with targeted mechanical properties for a specific application using a limited selection of building blocks.

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

Trends in Siting of Metals in Heterometallic Nd–Yb Metal–Organic Frameworks and Molecular Crystals

Several studies suggest that metal ordering within metal–organic frameworks (MOFs) is important for understanding how MOFs behave in relevant applications; however, these siting trends can be difficult to determine experimentally. To garner insight into the energetic driving forces that may lead to nonrandom ordering within heterometallic MOFs, we employ density functional theory (DFT) calculations on several bimetallic metal–organic crystals composed of Nd and Yb metal atoms. We also investigate the metal siting trends for a newly synthesized MOF. Our DFT-based energy of mixing results suggest that Nd will likely occupy sites with greater access to electronegative atoms and that local homometallic domains within a mixed-metal Nd–Yb system are favored. We also explore the use of less computationally extensive methods such as classical force fields and cluster expansion models to understand their feasibility for large system sizes. Here, this study highlights the impact of metal ordering on the energetic stability of heterometallic MOFs and crystal structures.

energy of mixing↗
DOE OSTI2022

Chemical and Reactive Transport Processes Associated with Hydraulic Fracturing of Unconventional Oil/Gas Shales

Hydraulic fracturing of unconventional oil/gas shales has changed the energy landscape of the U.S.. Recovery of hydrocarbons from tight, hydraulically fractured shales is a highly inefficient process, with estimated recoveries of < 25% for natural gas and < 5% for oil. This review focuses on the complex chemical interactions of additives in hydraulic fracturing fluid (HFF) with minerals and organic matter in oil/gas shales. These interactions are intended to increase hydrocarbon recovery by increasing porosities and permeabilities of tight shales. However, fluid-shale interactions result in the dissolution of shale minerals and the release and transport of chemical components. They also result in mineral precipitation in the shale matrix, which can reduce permeability, porosity, and hydrocarbon recovery. Competition between mineral dissolution and mineral precipitation processes influences the amounts of oil and gas recovered. We review the temporal/spatial origins and distribution of unconventional oil/gas shales from mudstones and shales, followed by discussion of their global and U.S. distributions and compositional differences from different U.S. sedimentary basins. We discuss the major types of chemical additives in HFF with their intended purposes, including drilling muds. Fracture distribution, porosity, permeability, and the identity and molecular-level speciation of minerals and organic matter in oil/gas shales throughout the hydraulic fracturing process are discussed. Also discussed are analysis methods used in characterizing oil/gas shales before and after hydraulic fracturing, including permeametry and porosimetry measurements, X-ray diffraction/Rietveld refinement, X-ray computed tomography, scanning/transmission electron microscopy, and laboratory- and synchrotron-based imaging/spectroscopic methods. Reactive transport and spatial scaling are discussed in some detail in order to relate fundamental molecular-scale processes to fluid transport. Furthermore, our review concludes with a discussion of potential environmental impacts of hydraulic fracturing and important knowledge gaps that must be bridged to achieve improved mechanistic understanding of fluid transport in oil/gas shales.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

Influence of functional groups on low-temperature combustion chemistry of biofuels

Ongoing progress in synthetic biology, metabolic engineering, and catalysis continues to produce a diverse array of advanced biofuels with complex molecular structure and functional groups. In order to integrate biofuels into existing combustion systems, and to optimize the design of next-generation combustion systems, understanding connections between molecular structure and ignition at low-temperature conditions (< 1000 K) remains a priority that is addressed in part using chemical kinetics modeling. The development of predictive models relies on detailed information, derived from experimental and theoretical studies, on molecular structure and chemical reactivity, both of which influence the balance of chain reactions that occur during combustion – propagation, termination, and branching. In broad context, three main categories of reactions affect ignition behavior: (i) initiation reactions that generate a distribution of organic radicals, ; (ii) competing unimolecular decomposition of and bimolecular reaction of with O2; (iii) decomposition mechanisms of peroxy radical adducts (RO), including isomerization via RO ⇌ OOH. Furthermore, all three categories are influenced by functional groups in different ways, which causes a shift in the balance of chain reactions that unfold over complex temperature- and pressure-dependent mechanisms.

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

Preferential interactions of primary amine-terminated quantum dots with membrane domain boundaries and lipid rafts revealed with nanometer resolution

The initial interactions of engineered nanoparticles (NPs) with living cells are governed by physicochemical properties of the NP and the molecular composition and structure of the cell membrane. Eukaryotic cell membranes contain lipid rafts – liquid-ordered nanodomains involved in membrane trafficking and molecular signaling. However, the impact of these membrane structures on cellular interactions of NPs remains unclear. Here we investigate the role of membrane domains in the interactions of primary amine-terminated quantum dots (Qdots) with liquid-ordered domains or lipid rafts in model membranes and intact cells, respectively. Using correlative atomic force and fluorescence microscopy, we found that the Qdots preferentially localized to boundaries between liquid-ordered and liquid-disordered phases in supported bilayers. The Qdots also induced holes at these phase boundaries. Using super resolution fluorescence microscopy (STORM), we found that the Qdots preferentially co-localized with lipid rafts in the membrane of intact trout gill epithelial cells – a model cell type for environmental exposures. Our observations uncovered preferential interactions of amine-terminated Qdots with liquid-ordered domains and their boundaries, possibly due to membrane curvature at phase boundaries creating energetically favorable sites for NP interactions. The preferential interaction of the Qdots with lipid rafts supports their potential internalization via lipid raft-mediated endocytosis and interactions with raft-resident signaling molecules.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

A coarse-grain force field based on quantum mechanics (CGq FF) for molecular dynamics simulation of poly(ethylene glycol)- block -poly(ε-caprolactone) (PEG- b -PCL) micelles

In order to provide the means to predict from molecular dynamics (MD) simulations the structures of copolymer-based micelles in solution, we developed coarse grain force field (CGq FF) parameters for poly(ethylene glycol) (PEG) and for poly(ε-caprolactone) (PCL). A key advance here is the use of quantum mechanics to train the parameters describing the non-bonded (NB) interactions between the CG beads. The functional forms are the same as the MARTINI CG FF so standard MD codes can be used. Our CGq FF describes well the experimentally observed properties for the polymer–air and polymer–water interfaces, indicating the accuracy of the NB interactions. Additionally, the structural properties (density, radius of gyration ( R g ), and end-to-end distance ( h )) match both experiment and all atom (AA) simulations. We illustrate the application of this CGq FF by following the formation of a spherical micelle from 250 chains of PEG 23 - b -PCL 9 diblock copolymer, each block with molecular weight of 1000 Daltons (10 500 beads, corresponding to 123 250 atoms), in a water box with 119 139 water beads (426 553 water molecules).

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

Probing the effect of magnetic field on charge order in the quasi-two-dimensional Mott insulator κ - (ET) 2 Hg(SCN) 2 Cl

Molecular-based quasi-two-dimensional charge-ordered Mott insulators can possess both spin S = 1/2 and an electric dipole degree of freedom residing on each (BEDT - TTF) 2 lattice site. There exists a theoretical proposal for a magnetoelectric effect in such a material, which can manifest itself as a sensitivity of charge distribution on (BEDT - TTF) 2 dimers to the magnetic field. Here in this work, we used Raman scattering spectroscopy in the magnetic field up to 31 T applied perpendicular to the two-dimensional triangular lattice planes to probe a magnetoelectric effect in $\kappa$ - (ET) 2 H g (SCN) 2 Cl. This is a model compound, which shows charge order and antiferromagnetic correlations at temperatures below 30 K. We discuss possible reasons for the absence of an observable magnetoelectric effect in the probed temperature and magnetic field ranges.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Origin of short- and medium-range order in supercooled liquid Ge 3 Sb 2 Te 6 from ab initio molecular dynamics simulations

Phase-change materials such as Ge–Sb–Te compounds have attracted much attention due to their potential value in electrical data storage. In contrast to the amorphous and crystalline phases, supercooled liquids are far from being deeply understood despite their inevitable role in both amorphization and crystallization processes. To this end, we have studied the dynamics properties and structural characteristics of liquid and supercooled liquid Ge 3 Sb 2 Te 6 during the fast cooling process. As the temperature decreases, chemical bonds become more homogeneous, but coordination numbers of Ge, Sb and Te atoms change very little. Meanwhile, the structural order of short-range configuration is obviously enhanced. Further studies suggest that Ge-centered, Sb-centered and Te-centered configurations change to the more ordered defective octahedrons mainly by adjusting the bond-angle relationship and bond length, rather than just by changing the coordination environment. It is the more ordered octahedrons that promote the formation of medium-range order. Our findings provide a deep insight into the origin of local structural order in supercooled liquid Ge 3 Sb 2 Te 6 , which is of great importance for the comprehensive understanding of amorphization and crystallization processes.

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

Chain Redistribution Stabilizes Coexistence Phases in Block Copolymer Blends

The nanoscale morphologies of block copolymer (BCP) thin films are determined by chain architecture. Experimental studies of thin film blends of different BCP chain types have demonstrated that blending can stabilize new motifs, such as coexistence phases. Here, we deploy coarsegrained molecular dynamics (MD) simulations in order to better understand the self-assembly behavior of BCP blend thin films. Here, we consider blends of lamella- and cylinder-forming BCP chains, studying their morphological makeup, the chain distribution within the morphology, and the underlying polymer chain conformations. Our simulations show that there are local concentration deviations at the scale of the morphological objects that dictate the local structure, and that BCP chains redistribute within the morphology so as to stabilize the structure. Underlying these effects are measurable distortions in the BCP chain conformations. The conformational freedom afforded by BCP blending stabilizes defects and allows coexistence phases to appear, while also leading to kinetic trapping effects. These results highlight the power of blending in designing the morphology that forms.

36 MATERIALS SCIENCE↗