Nutation versus angular dependent NQR spectroscopy and the impact of underdoping on charge inhomogeneities in YBa2_2Cu3_3Oy_y

We describe two different nuclear quadrupole resonance (NQR) based techniques, designed to measure the local asymmetry of the internal electric field gradient, and the tilt angle of the main NQR principal axis z from the crystallographic axis c. These techniques use the dependence of the NQR signal on the duration of the radio frequency (rf) pulse and on the direction of the rf field H1 with respect to the crystal axis. The techniques are applied to oriented powder of YBa$_{2}$Cu$$O$_{y}$ fully enriched with 63Cu. Measurements were performed at different frequencies, corresponding to different in-plane copper sites with respect to the dopant. Combining the results from both techniques, we conclude that oxygen deficiency in the chain layer lead to a rotation of the NQR main principal axis at the nearby Cu on the CuO2 planes by 20+-degrees. This occurs with no change to the asymmetry. The axis rotation associated with oxygen deficiency means that there must be electric field inhomogeneities in the CuO2 planes only in the vicinity of the missing oxygen.Comment: 9 pages, 10 figure

Two-dimensional nuclear magnetic resonance correlation spectroscopy at zero field

Three methods for two-dimensional correlation nuclear magnetic resonance spectroscopy at zero field are discussed. All three involve coherence transfer via longitudinal polarization, double quantum coherence, or both in parallel. The double quantum pulse sequences exploit the spinor property of spin states. These sequences have been applied to connected Δm=1 transitions, as well as for the indirect detection of forbidden or nearly forbidden Δm.1 transitions

Methylene-Only Subspectra in \u3csup\u3e13\u3c/sup\u3eC CPMAS Using a New Double Quantum Filtering Sequence

Methodology for the assignment of 13C CPMAS spectra is still in its infancy. Previous methods of CPMAS spectral editing have utilized differences in the strength of the 13C–1H dipolar interaction or the rate and spin thermodynamics of crosspolarization from protons to carbon, to differentiate between quaternary, tertiary, and methylene carbons. We introduce a different approach, which is based on the fact that double-quantum coherence develops between the protons of a methylene group considerably faster than between most other proton spin pairs in an organic solid. We generate this coherence, filter it, convert it back to single quantum, and then crosspolarize selectively to carbon, followed by a short period of reversed crosspolarization to null out unwanted coherence generated from longer distance spin pairs. The sequence has been named DQCP. While the signal-to-noise of this method is poorer than ordinary CP, it is comparable to previous methods for generating methylene-only spectra, and the technique is straightforward and easy to implement

Low-Threshold Electrically Pumps Vertical-Cavity Surface-Emitting Microlasers

Vertical-cavity electrically driven lasers with three GaInAs quantum wells and diameters of several μm exhibit room-temperature pulsed current thresholds as low as 1.3mA with 958 nm output wavelength

Room-Temperature Continuous-Wave Vertical-Cavity Single-Quantum-Well Microlaser Diodes

Room-temperature continuous and pulsed lasing of vertical-cavity, single-quantum-well, surface-emitting microlasers is achieved at ~983nm. The active Ga[sub][0-8]In[sub][0-2]As single quantum well is 100 [angstroms] thick. These microlasers have the smallest gain medium volumes among lasers ever built. The entire laser structure is grown by molecular beam epitaxy and the microlasers are formed by chemically assisted ion-beam etching. The microlasers are 3-50-μm across. The minimum threshold currents are 1.1 mA (pulsed) and 1.5 mA (CW)

Estimating Protein-Ligand Binding Affinity using High- Throughput Screening by NMR

Many of today’s drug discovery programs utilize high-throughput screening methods that rely on quick evaluations of protein activity to rank potential chemical leads. By monitoring biologically relevant protein-ligand interactions, NMR can provide a means to validate these discovery leads and to optimize the drug discovery process. NMR-based screens typically use a change in chemical shift or linewidth to detect a protein-ligand interaction. However, the relatively low throughput of current NMR screens and their high demand on sample requirements generally makes it impractical to collect complete binding curves to measure the affinity for each compound in a large and diverse chemical library. As a result, NMR ligand screens are typically limited to identifying candidates that bind to a protein and do not give any estimate of the binding affinity. To address this issue, a methodology has been developed to rank binding affinities for ligands based on NMR-based screens that use 1D 1H NMR line-broadening experiments. This method was demonstrated by using it to estimate the dissociation equilibrium constants for twelve ligands with the protein human serum albumin (HSA). The results were found to give good agreement with previous affinities that have been reported for these same ligands with HSA

Estimating Protein-Ligand Binding Affinity using High- Throughput Screening by NMR

Many of today’s drug discovery programs utilize high-throughput screening methods that rely on quick evaluations of protein activity to rank potential chemical leads. By monitoring biologically relevant protein-ligand interactions, NMR can provide a means to validate these discovery leads and to optimize the drug discovery process. NMR-based screens typically use a change in chemical shift or linewidth to detect a protein-ligand interaction. However, the relatively low throughput of current NMR screens and their high demand on sample requirements generally makes it impractical to collect complete binding curves to measure the affinity for each compound in a large and diverse chemical library. As a result, NMR ligand screens are typically limited to identifying candidates that bind to a protein and do not give any estimate of the binding affinity. To address this issue, a methodology has been developed to rank binding affinities for ligands based on NMR-based screens that use 1D 1H NMR line-broadening experiments. This method was demonstrated by using it to estimate the dissociation equilibrium constants for twelve ligands with the protein human serum albumin (HSA). The results were found to give good agreement with previous affinities that have been reported for these same ligands with HSA

Epitaxial-tau(Mn,Ni)Al/(Al,Ga)As heterostructures: Magnetic and magneto-optic properties

Ferromagnetic Perpendicularly magnetized epitaxial thin films of tau (Mn,Ni)AI have been successfully grown on AlAs/GaAs heterostructures by molecular beam epitaxy. We have investigated the polar Kerr rotation and magnetization of tau MnAl and (Mn,Ni) Al as a function of Mn and Ni concentration. The largest polar Kerr rotation and remnant magnetization were obtained for Mn0.5Al0.5 thin films with values of 0.16-degrees and 224 emu/cm3, respectively. We observed that the Kerr rotation and magnetization remained constant with Ni additions up to about 12 at. % and subsequently decreased with further Ni additions. We discuss these results and one possible method of enhancing the Kerr rotation

Causal role of a neural system for separating and selecting multidimensional social cognitive information

People are multi-faceted, typically good at some things but bad at others, and a critical aspect of social judgement is the ability to focus on those traits relevant for the task at hand. However, it remains unknown how the brain supports such context-dependent social judgement. Here, we examine how people represent multidimensional individuals, and how the brain extracts relevant information and filters out irrelevant information when comparing individuals within a specific dimension. Using human fMRI, we identify distinct neural representations in dorsomedial prefrontal cortex (dmPFC) and anterior insula (AI) supporting separation and selection of information for context-dependent social judgement. Causal evaluation using non-invasive brain stimulation shows that AI disruption alters the impact of relevant information on social comparison, whereas dmPFC disruption only affects the impact of irrelevant information. This neural circuit is distinct from the one supporting integration across, as opposed to separation of, different features of a multidimensional cognitive space