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A scalable multidimensional fully implicit solver for Hall magnetohydrodynamics
We propose an optimally performant fully implicit algorithm for the Hall magnetohydrodynamics (HMHD) equations based on multigrid-preconditioned Jacobian-free Newton-Krylov methods. HMHD is a challenging system to solve numerically because it supports stiff fast dispersive waves. The preconditioner is formulated using an operator-split approximate block factorization (Schur complement), informed by physics insight. We use a vector-potential formulation (instead of a magnetic field one) to allow a clean segregation of the problematic $\nabla$ x $\nabla$ x operator in the electron Ohm's law subsystem. This segregation allows the formulation of an effective damped block-Jacobi smoother for multigrid. We demonstrate by analysis that our proposed block-Jacobi iteration is convergent and has the smoothing property. The resulting HMHD solver is verified linearly with wave propagation examples, and nonlinearly with the GEM challenge reconnection problem by comparison against another HMHD code. We demonstrate the excellent algorithmic and parallel performance of the algorithm up to 16384 MPI tasks in two dimensions.
A deterministic verification strategy for multidimensional gyrokinetic particle-in-cell algorithms using the method of manufactured solutions
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Analysis of cicada wing surface constituents by comprehensive multidimensional gas chromatography for species differentiation
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SNAPRed: Reduction of multidimensional neutron time-of-flight diffraction data
SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.
Multidimensional solid-state NMR spectroscopy of plant cell walls
Plant biomass has become an important source of bio-renewable energy in modern society. The molecular structure of plant cell walls is difficult to characterize by most atomic-resolution techniques due to the insoluble and disordered nature of the cell wall. Solid-state NMR (SSNMR) spectroscopy is uniquely suited for studying native hydrated plant cell walls at the molecular level with chemical resolution. Significant progress has been made in the last five years to elucidate the molecular structures and interactions of cellulose and matrix polysaccharides in plant cell walls. These studies have focused on primary cell walls of growing plants in both the dicotyledonous and grass families, as represented by the model plants Arabidopsis thaliana, Brachypodium distachyon, and Zea mays. To date, these SSNMR results have shown that 1) cellulose, hemicellulose, and pectins form a single network in the primary cell wall; 2) in dicot cell walls, the protein expansin targets the hemicellulose-enriched region of the cellulose microfibril for its wall-loosening function; and 3) primary wall cellulose has polymorphic structures that are distinct from the microbial cellulose structures. This article summarizes these key findings, and points out future directions of investigation to advance our fundamental understanding of plant cell wall structure and function.
Rapid noninvasive monitoring of freshness variation in frozen shrimp using multidimensional fluorescence imaging coupled with chemometrics
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Removal of Homogeneous Broadening from 1 H-Detected Multidimensional Solid-State NMR Spectra
1 H-detected magic-angle spinning (MAS) NMR experiments have revolutionized the NMR studies of biological and inorganic solids by providing unparalleled sensitivity and resolution. Despite these gains, homogeneous broadening, originating from the incomplete removal of homonuclear dipolar interactions under fast MAS, remains highly prevalent and limits the achievable resolution. In direct analogy to super-resolution microscopy methods, we show that resolution beyond that currently achievable by fast MAS alone can be obtained by experiment-driven deconvolution. Following the acquisition of a single 2D NMR spectrum to measure the frequency-dependent homogeneous lineshapes, any number of 1 H-detected spectra can be enhanced in resolution, yielding comparable spectra as obtained with twice the MAS frequency. In conclusion, the versatility of this approach is demonstrated in the enhancement of single- and double-quantum homonuclear correlation spectra, in addition to heteronuclear correlation spectra acquired on a surface organometallic complex and the protein GB1.
Characterization of Silicon Nanocrystal Surfaces by Multidimensional Solid-State NMR Spectroscopy
The chemical and photophysical properties of silicon nanocrystals (Si NCs) are strongly dependent on the chemical composition and structure of their surfaces. Here we use fast magic angle spinning (MAS) and proton detection to enable the rapid acquisition of dipolar and scalar 2D 1 H– 29 Si heteronuclear correlation (HETCOR) solid-state NMR spectra and reveal a molecular picture of hydride-terminated and alkyl-functionalized surfaces of Si NCs produced in a nonthermal plasma. 2D 1 H– 29 Si HETCOR and dipolar 2D 1 H– 1 H multiple-quantum correlation spectra illustrate that resonances from surface mono-, di-, and trihydride groups cannot be resolved, contrary to previous literature assignments. Instead the 2D NMR spectra illustrate that there is large distribution of 1 H and 29 Si chemical shifts for the surface hydride species in both the as-synthesized and functionalized Si NCs. However, proton-detected 1 H– 29 Si refocused INEPT experiments can be used to unambiguously differentiate NMR signals from the different surface hydrides. Varying the 29 Si evolution time in refocused INEPT experiments and fitting the oscillation of the NMR signals allows for the relative populations of the different surface hydrides to be estimated. This analysis confirms that monohydride species are the predominant surface species on the as-synthesized Si NCs. A reduction in the populations of the di- and trihydrides is observed upon functionalization with alkyl groups, consistent with our previous hypothesis that the trihydride, or silyl (*SiH 3 ), group is primarily responsible for initiating surface functionalization reactions. Density functional theory (DFT) calculations were used to obtain quantum chemical structural models of the Si NC surface and reproduce the observed 1 H and 29 Si chemical shifts. Furthermore, the approaches outlined here will be useful to obtain a more detailed picture of surface structures for Si NCs and other hydride-passivated nanomaterials.
Coarse-Graining Conformational Dynamics with Multidimensional Generalized Langevin Equation: How, When, and Why
A data-driven ab initio generalized Langevin equation (AIGLE) approach is developed to learn and simulate high-dimensional, heterogeneous, coarse-grained (CG) conformational dynamics. Constrained by the fluctuation–dissipation theorem, the approach can build CG models in dynamical consistency (DC) with all-atom molecular dynamics. Here, we also propose practical criteria for AIGLE to enforce long-term DC. Case studies of a toy polymer, with 20 CG sites, and the alanine dipeptide, with two dihedral angles, elucidate why one should adopt AIGLE or its Markovian limit for modeling CG conformational dynamics in practice.
Cryogenic Vibrationally Resolved Photoelectron Spectroscopy of OH–(H2O): Confirmation of Multidimensional Franck-Condon Simulation Results for the Transition State of the OH + H2O Reaction
We present a transition state spectroscopic study of the OH + H2O reaction using the experimental technique of cryogenic Negative Ion Photoelectron Spectroscopy (NIPES). The recorded NIPE spectrum at 193 nm exhibits multiple vibrational progressions that include excitations to the shared H atom antisymmetric stretching mode with an interval of 0.32 eV as well as other progressions, mainly involving the H bending and O…O symmetric stretching modes. The Vertical Detachment Energy (VDE) was measured at 3.53 eV, whereas an upper limit for the Adiabatic Detachment Energy (ADE) was estimated at 2.90 eV. These values are in excellent agreement with the theoretically computed values of 3.51 eV and 2.83 eV respectively, obtained at the CCSD(T)/aug-cc-pV5Z level of theory. The recorded NIPE spectrum is in very good agreement when compared to the one recently reported from four-dimensional Franck-Condon simulations, in which a similar spectral profile was predicted. Besides observing the ground state, a charge-transfer excited state in the form of [OH–(H2O)+] is identified with a relative energy of 1.39 eV, well matching the previous prediction of 1.36 eV. This work was supported by U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, and performed using EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the DOE. The theoretical calculations were conducted on EMSL’s “Cascade” Supercomputer. This research also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
Probing surface hydrogen bonding and dynamics by natural abundance, multidimensional, 17 O DNP-NMR spectroscopy
Dynamic nuclear polarization (DNP)-enhanced solid-state nuclear magnetic resonance (SSNMR) spectroscopy is increasingly being used as a tool for the atomic-level characterization of surface sites. DNP surface-enhanced SSNMR spectroscopy of materials has, however, been limited to studying relatively receptive nuclei, and the particularly rare 17 O nuclide, which is of great interest for materials science, has not been utilized. We demonstrate that advanced 17 O SSNMR experiments can be performed on surface species at natural isotopic abundance using DNP. We use 17 O DNP surface-enhanced 2D SSNMR to measure 17 O{ 1 H} HETCOR spectra as well as dipolar oscillations on a series of thermally treated mesoporous silica nanoparticle samples having different pore diameters. These experiments allow for a nonintrusive and unambiguous characterization of hydrogen bonding and dynamics at the surface of the material; no other single experiment can give such details about the interactions at the surface. Lastly, our data show that, upon drying, strongly hydrogen-bonded surface silanols, whose motions are greatly restricted by the interaction when compared to lone silanols, are selectively dehydroxylated.