SEARCH · Engineering Papers
Results for “Molecular solids”
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.
Overcoming Fundamental Limitations in Adsorbent Design: Alkene Adsorption by Non-porous Copper(I) Complexes
Purifying alkenes from alkanes requires cryogenic distillation. This consumes energy equivalent to countries of ca. 5 million people. Replacing distillation with adsorption processes would significantly increase energy efficiency. Trade-offs between kinetics, selectivity, capacity, and heat of adsorption have prevented production of an optimal adsorbent. Here, we report adsorbents that overcome these trade-offs. [Cu-Br] 3 and [Cu-H] 3 are air-stable trinuclear complexes that undergo reversible solid-state inter-molecular rearrangements to produce dinuclear [Cu-Br∙(alkene)] 2 and [Cu-H∙(alkene)] 2 . The reversible solid-state rearrangement, confirmed in situ using powder X-ray diffraction, allows adsorbent design trade-offs to be overcome, coupling low heat of adsorption (-10 to -17 kJ mol -1 alkene ), high alkene:alkane selectivity (47; 29), and uptake capacity (>2.5 molalkene mol -1 Cu3 ). Most remarkably, [Cu-H] 3 displays fast uptake and regenerates capacity within 10 minutes.
Extrapolation of thermal conductivity in non-equilibrium molecular dynamics simulations to bulk scale
Predictions of the bulk scale thermal conductivity of solids using non-equilibrium molecular dynamics (MD) simulations have relied on the linear extrapolation of the thermal resistivity versus the reciprocal of the system length in the simulations. Several studies have reported deviation of the extrapolation from linearity near the micro-scale, raising a concern of its applicability to large systems. To investigate this issue, present work conducted extensive MD simulations of silicon with two different potentials (EDIP and Tersoff-II) for unprecedented length scales up to 10.3 μm and simulation times up to 530 ns. For large systems ≥0.35 μm in size the non-linearity of the extrapolation of the reciprocal of the thermal conductivity is mostly due to ignoring the dependence of the thermal conductivity on temperature. To account for such dependence, the present analysis fixes the temperature range for determining the gradient for calculating the thermal conductivity values. However, short systems ≤0.23 μm in size show significant non-linearity in the calculated thermal conductivity values using a temperature window of 500 ± 10 K from the simulations results with the EDIP potential. Since these system sizes are shorter than the mean phonon free path in EDIP (~0.22 μm), the nonlinearity may be attributed to phonon transport. For the MD simulations with the Tersoff-II potential there is no significant non-linearity in the calculated thermal conductivity values for systems ranging in size from 0.05 to 5.4 μm.
Structural insights into Lewis acid- and F4TCNQ-doped conjugated polymers by solid-state magnetic resonance spectroscopy
Molecular doping strategies facilitate orders of magnitude enhancement in the charge carrier mobility of organic semiconductors (OSCs). Understanding the different doping mechanisms and molecular-level constraints on doping efficiency related to the material energy levels is crucial to develop versatile dopants for OSCs. Given the compositional and structural heterogeneities associated with OSC thin films, insight into dopant–polymer interactions by long-range techniques such as X-ray scattering and electron microscopy is exceedingly challenging to obtain. This study employs short-range probes, solid-state (ss)NMR and EPR spectroscopy, to resolve local structures and intermolecular interactions between dopants such as F4TCNQ (2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane), Lewis acid BCF (tris[pentafluorophenyl] borane) and Lewis base conjugated polymer, PCPDTBT (P4) (poly[2,6-(4,4-bis(2-hexadecyl)-4H-cyclopenta[2,1-b;3,4-b']dithiophene)-alt-4,7(2,1,3-benzothiadiazole)]). Analysis of 1 H and 13 C ssNMR spectra of P4, P4 : F4TCNQ and P4 : BCF blends indicates that the addition of dopants induces local structural changes in the P4 polymer, and causes paramagnetism-induced signal broadening and intensity losses. The hyperfine interactions in P4 : BCF and P4 : F4TCNQ are characterized by two-dimensional pulsed EPR spectroscopy. For P4 : F4TCNQ, 19 F ssNMR analysis indicates that the F4TCNQ molecules are distributed and aggregated into different local chemical environments. By comparison, BCF molecules are intermixed with the P4 polymer and interact with traces of water molecules to form BCF–water complexes that serve as Brønsted acid sites, as revealed by 11 B ssNMR spectroscopy. These results indicate that the P4–dopant blends exhibit complex morphology with different distributions of dopants, whereby the combined use of ssNMR and EPR provides essential insights into how higher doping efficiency is observed with BCF and a mediocre efficiency is associated with F4TCNQ molecules.
Enriched Molecular-Level View of Saline Wetland Soil Carbon by Sensitivity-Enhanced Solid-State NMR
Soil organic matter (SOM) plays a major role in mitigating greenhouse gas emission and regulating earth’s climate, carbon cycle, and biodiversity. Wetland soils account for one-third of all SOM; however, globally, coastal wetland soils are eroding faster due to increasing sea-level rise. Our understanding of carbon sequestration dynamics in wetlands lags behind that of upland soils. Here, we employ solid-state nuclear magnetic resonance (ssNMR) to investigate the molecular-level structure of biopolymers in wetland soils spanning 11 centuries. High-resolution multidimensional spectra, enabled by dynamic nuclear polarization (DNP), demonstrate enduring preservation of molecular structures within herbaceous plant cores, notably condensing aromatic motifs and carbohydrates, even over a millennium, with the preserved cores constituting a decreasing minority among molecules from decomposition and repolymerization with depth and age. Such preserved cores occur alongside molecules from the decomposition of loosely packed parent biopolymers. These findings emphasize the relative vulnerability of coastal wetland SOM when exposed to oxygenated water due to geological and anthropogenic changes.
Water-enhanced CO 2 capture with molecular salt sodium guanidinate
Solid-state amine absorbent materials, including those containing guanidine derivatives, have received tremendous attention as the world combats the challenges of climate change.
Understanding ionic transport in perovskite lithium-ion conductor Li 3/8 Sr 7/16 Ta 3/4 Hf 1/4 O 3 : a neutron diffraction and molecular dynamics simulation study
Solid-state Li-ion electrolytes (SSEs) are essential for the development of next-generation solid-state Li-metal batteries and new Li-extraction electrochemical cells.
Role of Local Structure in the Enhanced Dynamics of Deformed Glasses
External stress can accelerate molecular mobility of amorphous solids by several orders of magnitude. The changes in mobility are commonly interpreted through the Eyring model, which invokes an empirical activation volume. Here, we analyze constant-stress molecular dynamics simulations and propose a structure-dependent Eyring model, connecting activation volume to a machine-learned field, softness. We show that stress has a heterogeneous effect on the mobility that depends on local structure through softness. The barrier impeding relaxation reduces more for well-packed particles, which explains the narrower distribution of relaxation time observed under stress.
Modes of Disorder in Poly(carbon monofluoride)
Poly(carbon monofluoride), or (CF) n , is a layered fluorinated graphite material consisting of nanosized platelets. In this work, we present experimental multidimensional solid-state NMR spectra of (CF)n, supported by density functional theory (DFT) calculations of NMR parameters, which overhauls our understanding of structure and bonding in the material by elucidating many ways in which disorder manifests. We observe strong 19 F NMR signals conventionally assigned to elongated or “semi-ionic” C–F bonds and find that these signals are in fact due to domains where the framework locally adopts boat-like cyclohexane conformations. We calculate that C–F bonds are weakened but are not elongated by this conformational disorder. Exchange NMR suggests that conformational disorder avoids platelet edges. We also use a new J-resolved NMR method for disordered solids which provides molecular-level resolution of highly fluorinated edge states. Strings of consecutive difluoromethylene groups at edges are relatively mobile. Topologically distinct edge features, including zigzag edges, crenellated edges, and coves are resolved in our samples by solid-state NMR. Disorder should be controllable in a manner dependent on synthesis, affording new opportunities for tuning the properties of graphite fluorides.
Discrete Orientations of Interfacial Waters Direct Crystallization of Mica-Binding Proteins
Understanding the basis of templated molecular assembly on a solid surface requires a fundamental comprehension of both short- and long-range aqueous response to the surface under a variety of solution conditions. Herein we provide a detailed picture of how the molecular-scale response to different mica surfaces yields distinct solvent orientations that produce quasi-static directional potentials onto which macromolecules can adsorb. We connect this directionality to observed (a)symmetric epitaxial alignment of designed proteins onto these surfaces, corroborate our findings with 3D atomic force microscopy experiments, and identify slight differences in surface structure as the origin of this effect. Furthermore, our work provides a detailed picture of the intrinsic electrolyte response in the vicinity of mineral interfaces, with clear predictions for experiment, and highlights the role of solvent on the predictive assembly of hierarchical materials on mineral surfaces.
Molecular Details of Polyester Decrystallization via Molecular Simulation
Not Available
Mechanism of Solid Electrolyte Interphase Formation on Lithium Anodes Studied by Molecular Dynamics Simulations
We investigated the initial formation of the SEI on lithium-metal anodes in presence of several electrolyte compositions using ReaxFF, in absence of a bias potential. We observed the formation of well-defined regions with different density and oxidation states of Li. Dissolution of Li metal atoms results in an uneven distribution of Li in the liquid phase. The electrolyte decomposition mechanism was studied for various electrolyte mixtures. Overall, the reaction mechanisms observed with ReaxFF are in good agreement with previous reports using DFT. However, we found some discrepancies in specific predictions by the ReaxFF that should be addressed in future work.
Identifying the Molecular Edge Termination of Exfoliated Hexagonal Boron Nitride Nanosheets with Solid-State NMR Spectroscopy and Plane-Wave DFT Calculations
Hexagonal boron nitride nanosheets (h-BNNS), the isoelectronic analog to graphene, have received interest over the past decade due to their high thermal oxidative resistance, high bandgap, catalytic activity, and low cost. The functional groups that terminate boron and nitrogen zigzag and/or armchair edges directly affect their chemical, physical, and electronic properties. However, an understanding of the molecular edge termination present in h-BNNS is lacking. Here, high-resolution magic-angle spinning (MAS) solid-state NMR (SSNMR) spectroscopy, and plane-wave density-functional theory (DFT) calculations are used to determine the molecular edge termination in exfoliated h-BNNS. 1 H → 11 B cross-polarization MAS (CPMAS) SSNMR spectra of h-BNNS revealed multiple hydroxyl/oxygen coordinated boron edge sites that were not detectable in direct excitation experiments. A dynamic nuclear polarization (DNP)-enhanced 1 H → 15 N CPMAS spectrum of h-BNNS displayed four distinct 15 N resonances while a 2D 1 H{ 14 N} dipolar-HMQC spectrum acquired with fast MAS revealed three distinct 14 N environments. Plane-wave DFT calculations were used to construct model edge structures and predict the corresponding 11 B, 14 N and 15 N SSNMR spectra. Comparison of the experimental and predicted SSNMR spectra confirms that zigzag and armchair edges with both amine and boron hydroxide/oxide termination are present. The detailed characterization of h-BNNS molecular edge termination will prove useful for many material science applications. The techniques outlined here should also be applicable to understand the molecular edge terminations in other 2D materials
Molecular Properties and Chemical Transformations Near Interfaces
The properties of bulk water and aqueous solutions are known to change in the vicinity of an interface and/or in a confined environment, including the thermodynamics of ion selectivity at interfaces, transition states and pathways of chemical reactions, and nucleation events and phase growth. Here we describe joint progress in identifying unifying concepts about how air, liquid, and solid interfaces can alter molecular properties and chemical reactivity compared to bulk water and multicomponent solutions. Furthermore, we also discuss progress made in interfacial chemistry through advancements in new theory, molecular simulation, and experiments.
Revisiting the pseudo-supercritical path method: An improved formulation for the alchemical calculation of solid–liquid coexistence
Alchemical free energy calculations via molecular dynamics have been applied to obtain thermodynamic properties related to solid–liquid equilibrium conditions, such as melting points. In recent years, the pseudo-supercritical path (PSCP) method has proved to be an important approach to melting point prediction due to its flexibility and applicability. In the present work, we propose improvements to the PSCP alchemical cycle to make it more compact and efficient through a concerted evaluation of different potential energies. The multistate Bennett acceptance ratio (MBAR) estimator was applied at all stages of the new cycle to provide greater accuracy and uniformity, which is essential concerning uncertainty calculations. In particular, for the multistate expansion stage from solid to liquid, we employed the MBAR estimator with a reduced energy function that allows affine transformations of coordinates. Free energy and mean derivative profiles were calculated at different cycle stages for argon, triazole, propenal, and the ionic liquid 1-ethyl-3-methyl-imidazolium hexafluorophosphate. Comparisons showed a better performance of the proposed method than the original PSCP cycle for systems with higher complexity, especially the ionic liquid. Furthermore, a detailed study of the expansion stage revealed that remapping the centers of mass of the molecules or ions is preferable to remapping the coordinates of each atom, yielding better overlap between adjacent states and improving the accuracy of the methodology.
Statistical analysis of HAADF-STEM images to determine the surface coverage and distribution of immobilized molecular complexes
The surface immobilization of molecular catalysts is attractive because it combines the benefits of homogeneous and heterogeneous catalysis. However, determining the surface coverage and distribution of a molecular catalyst on a solid support is often challenging, inhibiting our ability to design improved catalytic systems. Here, in this work, we demonstrate that the combination of scanning transmission electron microscopy (STEM) and image analysis of the individual positions of heavy atoms in transition metal complexes via a convolutional neural network (CNN) allows statistically robust determination of the surface coverage and distribution of immobilized molecular catalysts. These observations provide information about how changes in the functionalization conditions, attachment group, and structure of the molecular catalyst affect the surface coverage and distribution, providing insight into the chemical mechanism of surface immobilization. The method could be generally valuable for correlating the surface coverage and distribution to the activity, selectivity, and stability of a catalytic system.
Phonon-Induced Localization of Excitons in Molecular Crystals from First Principles
The spatial extent of excitons in molecular systems underpins their photophysics and utility for optoelectronic applications. Phonons are reported to lead to both exciton localization and delocalization. However, a microscopic understanding of phonon-induced (de)localization is lacking, in particular, how localized states form, the role of specific vibrations, and the relative importance of quantum and thermal nuclear fluctuations. Here, we present a first-principles study of these phenomena in solid pentacene, a prototypical molecular crystal, capturing the formation of bound excitons, exciton-phonon coupling to all orders, and phonon anharmonicity, using density functional theory, the ab initio GW-Bethe-Salpeter equation approach, finite-difference, and path integral techniques. In this study, we find that for pentacene zero-point nuclear motion causes uniformly strong localization, with thermal motion providing additional localization only for Wannier-Mott-like excitons. Anharmonic effects drive temperature-dependent localization, and, while such effects prevent the emergence of highly delocalized excitons, we explore the conditions under which these might be realized
Genarris 2.0: A Random Structure Generator for Molecular Crystals
Genarris is an open source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and training machine learning models. Here we present a new version of the code, containing several major improvements. A MPI-based parallelization scheme has been implemented, which facilitates the seamless sequential execution of user-defined workflows. A new method for estimating the unit cell volume based on the single molecule structure has been developed using a machine-learned model trained on experimental structures. A new algorithm has been implemented for generating crystal structures with molecules occupying special Wyckoff positions. A new hierarchical structure check procedure has been developed to detect unphysical close contacts efficiently and accurately. New intermolecular distance settings have been implemented for strong hydrogen bonds. To demonstrate these new features, we study two specific cases: benzene and glycine. Genarris finds the experimental structures of the two polymorphs of benzene and the three polymorphs of glycine. Program summary Program Title: Genarris 2.0 Program Files doi: http://dx.doi.org/10.17632/grx6mz4pjn.1 Licensing provisions: BSD-3 Clause Programming language: Python, C External routines/libraries: Spglib, ASE, pymatgen, SciPy, mpi4py, scikit-learn, PyTorch, FHI-aims. Nature of problem: Molecular crystal structure prediction. Solution method: Genarris 2.0 generates molecular crystal structures over the 230 space groups, on general and special Wyckoff positions, using physical constraints. Down-sampling of the generated structures may be performed subsequently, based on molecular crystal packing descriptors and an unsupervised machine learning algorithm. Lastly, ab initio structure relaxation may be performed for the final pool. Depending on the user-defined workflow implemented, Genarris may be used to generate diverse molecular crystal datasets to seed evolutionary algorithms or to train machine learning algorithms or as a standalone crystal structure prediction method. Restrictions: For crystal structure generation, the molecule of interest must be semi-rigid with no bond rotational degrees of freedom. Unusual features: Genarris 2.0 is a highly distributed program, making use of MPI for Python parallelization. The user has the ability to design and implement workflows by executing a user-defined list of procedures. Genarris 2.0 offers new features including a machine learning model for estimating the molecular volume in the solid state from the single molecule structure, structure generation in special Wyckoff positions of space groups, hierarchical structure checks including rigorous treatment of non-orthogonal structures, and clustering and down-selection workflows combining first principles simulations with machine learning. (C) 2020 Elsevier B.V. All rights reserved.