Quantitative cw Overhauser DNP Analysis of Hydration Dynamics

Liquid state Overhauser Effect Dynamic Nuclear Polarization (ODNP) has experienced a recent resurgence of interest. In particular, a new manifestation of the ODNP measurement measures the translational mobility of water within 5-10 \AA\ of an ESR-active spin probe (i.e. the local translational diffusivity D_{local} near an electron spin resonance active molecule). Such spin probes, typically stable nitroxide radicals, have been attached to the surface or interior of macromolecules, including proteins, polymers, and membrane vesicles. Despite the unique specificity of this measurement, it requires only a standard X-band (~10 GHz) continuous wave (cw) electron spin resonance (ESR) spectrometer, coupled with a standard nuclear magnetic resonance (NMR) spectrometer. Here, we present a set of developments and corrections that allow us to improve the accuracy of quantitative ODNP and apply it to samples more than two orders of magnitude lower than were previously feasible.Comment: 25 page manuscript submitted to PNMR

Carbon and proton overhauser DNP from MD simulations and ab initio calculations: TEMPOL in acetone

A computational analysis of the Overhauser effect is reported for the proton, methyl carbon, and carbonyl carbon nuclei of liquid acetone doped with the nitroxide radical TEMPOL. A practical methodology for calculating the dynamic nuclear polarization (DNP) coupling factors by accounting for both dipole–dipole and Fermi-contact interactions is presented. The contribution to the dipolar spectral density function of nuclear spins that are not too far from TEMPOL is computed through classical molecular dynamics (MD) simulations, whereas the contribution of distant spins is included analytically. Fermi contacts are obtained by subjecting a few molecules from every MD snapshot to ab initio quantum mechanical calculations. Scalar interaction is found to be an essential part of the 13C Overhauser DNP. While mostly detrimental to the carbonyl carbon of acetone it is predicted to result in large enhancements of the methyl carbon signal at magnetic fields of 9 T and beyond. In contrast, scalar coupling is shown to be negligible for the protons of acetone. The additional influence of proton polarization on the carbon DNP (three-spin effect) is also analyzed computationally. Its effect, however, is concluded to be practically insignificant for liquid acetone

Comment on new physics contributions to Gamma_{12}^s

A recent measurement by the D0 collaboration finds a like-sign di-muon charge asymmetry in the B system that is roughly 3 sigma larger than the value predicated by the Standard Model. This suggests new physics contributing to B-Bbar mixing. For the current central value of the CP asymmetry, the required size of Gamma_{12}^s is larger than Standard Model estimates of this quantity. In this paper, we will explore the constraints on new physics contributions to Gamma_{12}^s. We show that there are two dimension six operators of Standard Model fields in the electroweak Hamiltonian whose coefficients are not constrained enough to rule out possible contributions from new physics. We argue that a more precise measurement of tau(B_s)/tau(B_d), which is possible with currently available data, could either support or strongly constrain the existence of new physics in Gamma_{12}^s.Comment: 6 pages, 1 figure. Minor revisions and references adde

Graph transformations for the vehicle routing and job shop scheduling problems

The vehicle routing problem (VRP) and job shop scheduling problem (JSP) are two common combinatorial problems that can be naturally represented as graphs. A core component of solving each problem can be modeled as finding a minimum cost Hamiltonian path in a complete weighted graph. The graphs extracted from VRPs and JSPs have different characteristics however, notably in the ratio of edge weight to node weight. Our long term research question is to determine the extent to which such graph characteristics impact the performance of algorithms commonly applied to VRPs and JSPs. As a preliminary step, in this paper we investigate five transformations for complete weighted graphs that preserve the cost of Hamiltonian paths. These transformations are based on increasing node weights while reducing edge weights or the inverse. We demonstrate how the transformations affect the ratio of edge to node weight and how they change the relative weights of edges at a node. Finally, we conjecture how the different transformations will impact the performance of existing VRP and JSP solving techniques

Spatially Heterogeneous Surface Water Diffusivity around Structured Protein Surfaces at Equilibrium

Hydration water on the surface of a protein is thought to mediate the thermodynamics of protein-ligand interactions. For hydration water to play a role beyond modulating global protein solubility or stability, the thermodynamic properties of hydration water must reflect on the properties of the heterogeneous protein surface and thus spatially vary over the protein surface. A potent read-out of local variations in thermodynamic properties of hydration water is its equilibrium dynamics spanning picosecond to nanosecond time scales. In this study, we employ Overhauser dynamic nuclear polarization (ODNP) to probe the equilibrium hydration water dynamics at select sites on the surface of Chemotaxis Y (CheY) in dilute solution. ODNP reports on site-specific hydration water dynamics within 5-10 Å of a label tethered to the biomolecular surface on two separate time scales of motion, corresponding to diffusive water (DW) and protein-water coupled motions, referred to as bound water (BW). We find DW dynamics to be highly heterogeneous across the surface of CheY. We identify a significant correlation between DW dynamics and the local hydropathy of the CheY protein surface, empirically determined by molecular dynamics (MD) simulations, and find the more hydrophobic sites to be hydrated with slower diffusing water. Furthermore, we compare the hydration water dynamics on different polypeptides and liposome surfaces and find the DW dynamics on globular proteins to be significantly more heterogeneous than on intrinsically disordered proteins (IDPs), peptides, and liposomes. The heterogeneity in the hydration water dynamics suggests that structured proteins have the capacity to encode information into the surrounding hydration shell

A Modernized View of Coherence Pathways Applied to Magnetic Resonance Experiments in Unstable, Inhomogeneous Fields

Over recent decades, the value of conducting experiments at lower frequencies and in inhomogeneous and/or time-variable fields has grown. For example, an interest in the nanoscale heterogeneities of hydration dynamics demands increasingly sophisticated and automated measurements deploying Overhauser Dynamic Nuclear Polarization (ODNP) at low field. The development of these methods poses various challenges that drove us to develop a standardized alternative to the traditional schema for acquiring and analyzing coherence pathway information employed by the overwhelming majority of contemporary Nuclear Magnetic Resonance (NMR) research. Specifically, on well-tested, stable NMR systems running well-tested pulse sequences in highly optimized, homogeneous magnetic fields, traditional hardware and software quickly isolate a meaningful subset of data by averaging and discarding between 3/4 and 127/128 of the digitized data. In contrast, spurred by recent advances in the capabilities of open-source libraries, the domain colored coherence transfer (DCCT) schema implemented here builds on the long-extant concept of Fourier transformation along the pulse phase cycle domain to enable data visualization that more fully reflects the rich physics underlying these NMR experiments. In addition to discussing the outline and implementation of the general DCCT schema and associated plotting methods, this manuscript presents a collection of algorithms that provide robust phasing, avoidance of baseline distortion, and the ability to realize relatively weak signals amidst background noise through signal-averaged correlation alignment. The methods for visualizing the raw data, together with the processing routines whose development they guide should apply directly to or extend easily to other techniques facing similar challenges.Comment: 32 pages, 18 figure

The Oregon Digital Newspaper Program’s Commitment to Open Access

The Oregon Digital Newspaper Program (ODNP) at the University of Oregon Libraries is an initiative to digitize historic and current Oregon newspapers, making them freely available to the public through a keyword-searchable online database. The ODNP is committed to open access and has included collaboration and data sharing with larger programs like the Library of Congress’ Chronicling America historic newspaper website. Since 2015, the ODNP has increased its open access mission by archiving and hosting born-digital newspaper content, as well as continuing digitization of historic newspapers from microfilm and print. This article outlines the ODNP’s past and current open access efforts, inclusion of diverse content, and open source, sustainable applications, websites, and workflows

Benchtop NMR Spectroscopy in Process Engineering

Nuclear magnetic resonance (NMR) is a highly attractive powerful method that enables non-invasive analysis of complex mixtures without requiring tedious calibration procedures. Benchtop NMR spectrometers are small, robust, and inexpensive, which makes them especially suited for process and reaction monitoring. However, the low magnetic field strength and the small premagnetization volume of these spectrometers are major drawbacks, resulting in low spectral resolution, peak overlap, low signal intensities, and insufficient magnetization build-up in flowing liquids. As a consequence, the quantitative analysis of complex mixtures is not always possible by benchtop NMR spectroscopy. This thesis tackles these challenges and introduces methods that extend the applications of benchtop NMR spectroscopy in process engineering. The first method is a model-based approach for resolving overlapping peaks in 1H NMR spectra of complex multi-component mixtures. This method has been successfully tested by online monitoring of a wine fermentation. The second method uses dedicated NMR pulse sequences for 1H-13C polarization transfer and enables an improved quantitative analysis of mixtures in particular in flow experiments based on 13C NMR spectroscopy. 13C NMR spectroscopy is advantageous as the high chemical shift dispersion prevents peak overlap, albeit at the expense of low signal-to-noise ratio (SNR) and extended experimental time. The NMR pulse sequences provide an elegant solution to achieve 13C signal enhancement and to shorten the experimental time by exploiting the higher polarization and favorable spin-lattice relaxation of protons. The method was also successfully applied for measuring diffusion coefficients by NMR. The third method uses the hyperpolarization technique Overhauser Dynamic Nuclear Polarization (ODNP) to significantly enhance 1H and 13C NMR signals. This enables the detection and quantification of components at low concentrations or at high flow velocities with just a single scan. These methods can also be applied together and significantly extend the NMR toolbox for process engineering and other applications.Die Kernspinresonanz (NMR) ist eine äußerst attraktive und leistungsstarke Methode, die eine nicht-invasive Analyse komplexer Mischungen ermöglicht, ohne dass langwierige Kalibrierungsverfahren erforderlich sind. Benchtop NMR Spektrometer sind klein, robust und kostengünstig, was sie besonders für die Prozess- und Reaktionsüberwachung geeignet macht. Die geringe Magnetfeldstärke und das kleine Vormagnetisierungsvolumen dieser Spektrometer sind jedoch ein großer Nachteil, der zu geringer spektraler Auflösung, Peaküberlappung, geringen Signalintensitäten und unzureichendem Magnetisierungsaufbau in fließenden Proben führt. Infolgedessen ist die quantitative Analyse komplexer Mischungen mit der Benchtop NMR Spektroskopie nicht immer möglich. In dieser Arbeit werden diese Probleme angegangen und Methoden vorgestellt, die die Anwendungsmöglichkeiten der Benchtop NMR Spektroskopie in der Verfahrenstechnik erweitern. Die erste Methode ist ein modellbasierter Ansatz zur Auflösung überlappender Peaks in 1H NMR-Spektren komplexer Mehrkomponentenmischungen. Diese Methode wurde bei der Online-Überwachung einer Weinfermentation erfolgreich getestet. Die zweite Methode verwendet spezielle NMR-Pulssequenzen für den 1H-13CPolarisationstransfer und ermöglicht eine verbesserte quantitative Analyse von Mischungen, insbesondere in Strömungsexperimenten auf der Grundlage der 13C NMR Spektroskopie. Die 13C NMR Spektroskopie ist vorteilhaft, da die hohe Dispersion der chemischen Verschiebung eine Überlappung der Peaks verhindert, wenn auch auf Kosten eines geringen Signal-Rausch-Verhältnisses (SNR) und verlängerte Versuchsdauer. Die NMR-Pulssequenzen bieten eine elegante Lösung, um das 13C-Signal zu verstärken und die Versuchszeit zu verkürzen, indem die höhere Polarisation und die kurze Spin-Gitter-Relaxation der Protonen ausgenutzt werden. Die Methode wurde auch erfolgreich für die Messung von Diffusionskoeffizienten mittels NMR eingesetzt. Die dritte Methode nutzt die Hyperpolarisationstechnik Overhauser Dynamic Nuclear Polarization (ODNP), um die 1H und 13C NMR-Signale deutlich zu verstärken. Dies ermöglicht den Nachweis und die Quantifizierung von Komponenten in niedrigen Konzentrationen oder bei hohen Flussgeschwindigkeiten mit nur einem einzigen Scan. Diese Methoden können auch gemeinsam angewendet werden und erweitern den NMR-Werkzeugkasten für die Verfahrenstechnik und andere Anwendungen erheblich

Estimation of Photovoltaic Generation Forecasting Models using Limited Information

This work deals with the problem of estimating a photovoltaic generation forecasting model in scenarios where measurements of meteorological variables (i.e. solar irradiance and temperature) at the plant site are not available. A novel algorithm for the estimation of the parameters of the well-known PVUSA model of a photovoltaic plant is proposed. Such a method is characterized by a low computational complexity, and efficiently exploits only power generation measurements, a theoretical clear-sky irradiance model, and temperature forecasts provided by a meteorological service. An extensive experimental validation of the proposed method on real data is also presented