244 resultados para Rilassometro Rilassometria NMR Magnete Caratterizzazione Risonanza


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Quantum ensembles form easily accessible architectures for studying various phenomena in quantum physics, quantum information science and spectroscopy. Here we review some recent protocols for measurements in quantum ensembles by utilizing ancillary systems. We also illustrate these protocols experimentally via nuclear magnetic resonance techniques. In particular, we shall review noninvasive measurements, extracting expectation values of various operators, characterizations of quantum states and quantum processes, and finally quantum noise engineering.

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Identifying cellular processes in terms of metabolic pathways is one of the avowed goals of metabolomics studies. Currently, this is done after relevant metabolites are identified to allow their mapping onto specific pathways. This task is daunting due to the complex nature of cellular processes and the difficulty in establishing the identity of individual metabolites. We propose here a new method: ChemSMP (Chemical Shifts to Metabolic Pathways), which facilitates rapid analysis by identifying the active metabolic pathways directly from chemical shifts obtained from a single two-dimensional (2D) C-13-H-1] correlation NMR spectrum without the need for identification and assignment of individual metabolites. ChemSMP uses a novel indexing and scoring system comprised of a ``uniqueness score'' and a ``coverage score''. Our method is demonstrated on metabolic pathways data from the Small Molecule Pathway Database (SMPDB) and chemical shifts from the Human Metabolome Database (HMDB). Benchmarks show that ChemSMP has a positive prediction rate of >90% in the presence of deduttered data and can sustain the same at 60-70% even in the presence of noise, such as deletions of peaks and chemical shift deviations. The method tested on NMR data acquired for a mixture of 20 amino acids shows a success rate of 93% in correct recovery of pathways. When used on data obtained from the cell lysate of an unexplored oncogenic cell line, it revealed active metabolic pathways responsible for regulating energy homeostasis of cancer cells. Our unique tool is thus expected to significantly enhance analysis of NMIR-based metabolomics data by reducing existing impediments.

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A new approach for rapid resonance assignments in proteins based on amino acid selective unlabeling is presented. The method involves choosing a set of multiple amino acid types for selective unlabeling and identifying specific tripeptides surrounding the labeled residues from specific 2D NMR spectra in a combinatorial manner. The methodology directly yields sequence specific assignments, without requiring a contiguously stretch of amino acid residues to be linked, and is applicable to deuterated proteins. We show that a 2D N-15,H-1]HSQC spectrum with two 2D spectra can result in approximate to 50% assignments. The methodology was applied to two proteins: an intrinsically disordered protein (12kDa) and the 29kDa (268 residue) -subunit of Escherichia coli tryptophan synthase, which presents a challenging case with spectral overlaps and missing peaks. The method can augment existing approaches and will be useful for applications such as identifying active-site residues involved in ligand binding, phosphorylation, or protein-protein interactions, even prior to complete resonance assignments.

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This study reports a multinuclei in situ (real-time) NMR spectroscopic characterization of the electrochemical reactions of a negative Cu3P electrode toward lithium. Taking advantage of the different nuclear spin characteristics, we have obtained real-time P-31 and Li-7 NMR data for a comprehensive understanding of the electrochemical mechanism during the discharge and charge processes of a lithium battery. The large NMR chemical shift span of P-31 facilitates the observation of the chemical evolutions of different lithiated and delithiated LixCu3-xP phases, whereas the quadrupolar line features in Li-7 enable identification of asymmetric Li sites. These combined NMR data offer an unambiguous identification of four distinct LixCu3-xP phases, Cu3P, Li0.2Cu2.8P, Li2CuP, and. Li3P, and the characterization of their involvement in the electrochemical reactions. The NMR data led us to propose a delithiation process involving the intercalation of metallic Cu-0 atomic aggregates into the Li2CuP structure to form a Cu-0-Li2-xCu1-xP phase. This process might be responsible for the poor capacity retention in Cu3P lithium batteries when cycled to a low voltage.