Quasiparticle states in superconducting superlattices

The energy bands and the global density of states are computed for superconductor / normal-metal superlattices in the clean limit. Dispersion relations are derived for the general case of insulating interfaces, including the mismatch of Fermi velocities and effective band masses. We focus on the influence of finite interface transparency and compare our results with those for transparent superlattices and trilayers. Analogously to the rapid variation on the atomic scale of the energy dispersion with layer thicknesses in transparent superlattices, we find strong oscillations of the almost flat energy bands (transmission resonances) in the case of finite transparency. In small-period transparent superlattices the BCS coherence peak disappears and a similar subgap peak is formed due to the Andreev process. With decreasing interface transparency the characteristic double peak structure in the global density of states develops towards a gapless BCS-like result in the tunnel limit. This effect can be used as a reliable STM probe for interface transparency.     

NMR analysis of surfaces and interfaces in 2-nm CdSe

Solid-state NMR analysis on wurtzite 2-nm hexadecylamine-capped CdSe nanocrystals (CdSe-HDA) provides evidence of discrete nanoparticle reconstruction within the Se sublattice of the nanomaterial. The cadmium and selenium atoms are probed with (1)H-(113)Cd and (1)H-(77)Se cross-polarization magic angle spinning (MAS) experiments, which demonstrate five ordered selenium sites in the nanoparticle that can be assigned to contributions arising from different surface sites and a selenium site one layer down from the surface. Intriguingly, in these materials both HDA and thiophenol are observed to selectively bind to specific sites on the nanoparticle surface. 2D heteronuclear chemical shift correlation (HETCOR) experiments provide evidence for thiophenol selectively binding at surface vacancies. Analysis of the NMR provides a model of a 2-nm CdSe-HDA molecular surface.     

Detecting outlying samples in a parallel factor analysis model

To explore multi-way data, different methods have been proposed. Here, we study the popular PARAFAC (Parallel factor analysis) model, which expresses multi-way data in a more compact way, without ignoring the underlying complex structure. To estimate the score and loading matrices, an alternating least squares procedure is typically used. It is however well known that least squares techniques suffer from outlying observations, making the models useless when outliers are present in the data. In this paper, we present a robust PARAFAC method. Essentially, it searches for an outlier-free subset of the data, on which we can then perform the classical PARAFAC algorithm. An outlier map is constructed to identify outliers. Simulations and examples show the robustness of our approach.     

Solving chromatographic challenges in comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry using multivariate curve resolution–alternating least squares

Multivariate curve resolution–alternating least squares (MCR–ALS) analysis is proposed to solve chromatographic challenges during two-dimensional gas chromatography–time-of-flight mass spectrometry (GC?×?GC–TOFMS) analysis of complex samples, such as crude oil extract. In view of the fact that the MCR–ALS method is based on the fulfillment of the bilinear model assumption, three-way and four-way GC?×?GC–TOFMS data are preferably arranged in a column-wise superaugmented data matrix in which mass-to-charge ratios (m/z) are in its columns and the elution times in the second and first chromatographic columns are in its rows. Since m/z values are common for all measured spectra in all second-column modulations, unavoidable chromatographic challenges such as retention time shifts within and between GC?×?GC–TOFMS experiments are properly handled. In addition, baseline/background contributions can be modeled by adding extra components to the MCR–ALS model. Another outstanding aspect of MCR–ALS analysis is its extreme flexibility to consider all samples (standards, unknowns, and replicates) in a single superaugmented data matrix, allowing joint analysis. In this way, resolution, identification, and quantification results can be simultaneously obtained in a very fast and reliable way. The potential of MCR–ALS analysis is demonstrated in GC?×?GC–TOFMS analysis of a North Sea crude oil extract sample with relative errors in estimated concentrations of target compounds below 6.0 % and relative standard deviations lower than 7.0 %. The results obtained, along with reasonable values for the lack of fit of the MCR–ALS model and high values of the reversed match factor in mass spectra similarity searches, confirm the reliability of the proposed strategy for GC?×?GC–TOFMS data analysis.      

Isotope-labeling of the fibril binding compound FSB via a Pd-catalyzed double alkoxycarbonylation

We have synthesized two isotopically labeled variants of the β-amyloid binding compound FSB possessing (13)C-labels on the two terminal aryl carboxylic acid moieties. One of these was also fully deuterated on the olefinic spacers. The (13)C-isotope labeling was achieved applying a Pd-catalyzed methoxycarbonylation of the corresponding aryl chlorides with externally (ex situ) generated (13)C-labeled CO. Application of the Shirakawa-Hayashi protocol for the Pd-catalyzed reduction of a dialkyne intermediate using D(2)O allowed for the selective deuterium labeling of the two trans-C,C double bonds of FSB.     

Comparison of thermodynamic stabilities and mechanical properties of CO2, SiO2, and GeO2 polymorphs by first-principles calculations

The recent discovery that molecular CO(2) transforms under compression into carbon four-coordinated, 3-dimensional network solid phases has generated considerable interests on possible new phases in the fourth-main-group elemental oxides. Based on density-functional theory calculations, we have investigated the thermodynamic stability, mechanical properties and electronic structure of proposed guest-free clathrates, quartz and cristobalite phases for CO(2), SiO(2), and GeO(2), and the dry ice phase for CO(2). It was predicted that a GeO(2) clathrate, likely a semiconductor, could be synthesized presumably with some suitable guest molecules. The hypothetical CO(2) guest-free clathrate phase was found hardly to be formed due to the large energy difference with respect to the other polymorphs. This phase is unstable at all pressures, which is also implied by its different electronic structure in comparison with SiO(2) and GeO(2). Finally, the SiO(2) clathrate presents a uniquely high bulk modulus, which is higher than that of quartz and three times of the experimental data, might not be a weak point of ab-initio calculations such as pseudopotentials, correlation functional etc., instead it can be readily understood by the constraint as imposed by the high symmetry. Either temperature or an "exhausted" relaxation (without any symmetry constraint) can remedy this problem.     

Mimics of small ribozymes utilizing a supramolecular scaffold

For elucidating the mechanism of the general acid/base catalysis of the hydrolysis of RNA phosphodiester bonds, a number of cleaving agents having two cyclen moieties tethered to a 1,3,5-triazine core have been prepared and their ability to bind and cleave uridylyl-3',5'-uridine (UpU) studied over a wide pH range. Around neutral pH, the cleaving agents form a highly stable ternary complex with UpU and Zn(II) through coordination of the uracil N3 and the cyclen nitrogen atoms to the Zn(II) ions. Under conditions where the triazine core exists in the deprotonated neutral form, hydrolysis of UpU, but not of adenylyl-3',5'-adenosine (ApA), is accelerated by approximately two orders of magnitude in the presence of the cleaving agents, suggesting general base rather than metal ion catalysis. The probable mechanism of the observed catalysis and implications to understanding the general acid/base-catalyzed phosphodiester hydrolysis by ribozymes are discussed.     

A Deterministic Algorithm for Robust Location and Scatter

Most algorithms for highly robust estimators of multivariate location and scatter start by drawing a large number of random subsets. For instance, the FASTMCD algorithm of Rousseeuw and Van Driessen starts in this way, and then takes so-called concentration steps to obtain a more accurate approximation to the MCD. The FASTMCD algorithm is affine equivariant but not permutation invariant. In this article, we present a deterministic algorithm, denoted as DetMCD, which does not use random subsets and is even faster. It computes a small number of deterministic initial estimators, followed by concentration steps. DetMCD is permutation invariant and very close to affine equivariant. We compare it to FASTMCD and to the OGK estimator of Maronna and Zamar. We also illustrate it on real and simulated datasets, with applications involving principal component analysis, classification, and time series analysis. Supplemental material (Matlab code of the DetMCD algorithm and the datasets) is available online.     

N-Naphthyl peptoid foldamers exhibiting atropisomerism

We introduce peptoid oligomers incorporating N-(1)-naphthyl glycine monomers. Axial chirality was established due to restricted rotation about the C-N(aryl) bond. Atropisomerism of both linear and cyclic peptoids was investigated by computational analysis, dynamic HPLC, and X-ray crystallographic studies.     

Informatics methods to enable sharing of quantitative imaging research data

Introduction

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community.

Methods

We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN.

Results

There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network.

Conclusions

As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers.