Influence of Functional Groups on Charge Transport in Molecular Junctions

Using density functional theory (DFT), we analyze the influence of five classes of functional groups, as exemplified by NO2, OCH3, CH3, CCl3, and I, on the transport properties of a 1,4-benzenedithiolate (BDT) and 1,4-benzenediamine (BDA) molecular junction with gold electrodes. Our analysis demonstrates how ideas from functional group chemistry may be used to engineer a molecule's transport properties, as was shown experimentally and using a semiempirical model for BDA [Nano Lett. 7, 502 (2007)]. In particular, we show that the qualitative change in conductance due to a given functional group can be predicted from its known electronic effect (whether it is pi/sigma donating/withdrawing). However, the influence of functional groups on a molecule's conductance is very weak, as was also found in the BDA experiments. The calculated DFT conductances for the BDA species are five times larger than the experimental values, but good agreement is obtained after correcting for self-interaction and image charge effects.Comment: 6 pages, 3 figures, J. Chem. Phys (in press

Tilt-angle landscapes and temperature dependence of the conductance in biphenyl-dithiol single-molecule junctions

Using a density-functional-based transport method we study the conduction properties of several biphenyl-derived dithiol (BPDDT) molecules wired to gold electrodes. The BPDDT molecules differ in their side groups, which control the degree of conjugation of the pi-electron system. We have analyzed the dependence of the low-bias zero-temperature conductance on the tilt angle phi between the two phenyl ring units, and find that it follows closely a cos^2(phi) law, as expected from an effective pi-orbital coupling model. We show that the tilting of the phenyl rings results in a decrease of the zero-temperature conductance by roughly two orders of magnitude, when going from a planar conformation to a configuration in which the rings are perpendicular. In addition we demonstrate that the side groups, apart from determining phi, have no influence on the conductance. All this is in agreement with the recent experiment by Venkataraman et al. [Nature 442, 904 (2006)]. Finally, we study the temperature dependence of both the conductance and its fluctuations and find qualitative differences between the examined molecules. In this analysis we consider two contributions to the temperature behavior, one coming from the Fermi functions and the other one from a thermal average over different contact configurations. We illustrate that the fluctuations of the conductance due to temperature-induced changes in the geometric structure of the molecule can be reduced by an appropriate design.Comment: 9 pages, 6 figures; submitted to Phys. Rev.

TractoR: Magnetic Resonance Imaging and Tractography with R

Statistical techniques play a major role in contemporary methods for analyzing magnetic resonance imaging (MRI) data. In addition to the central role that classical statistical methods play in research using MRI, statistical modeling and machine learning techniques are key to many modern data analysis pipelines. Applications for these techniques cover a broad spectrum of research, including many preclinical and clinical studies, and in some cases these methods are working their way into widespread routine use.In this manuscript we describe a software tool called TractoR (for “Tractography with R”), a collection of packages for the R language and environment, along with additional infrastructure for straightforwardly performing common image processing tasks. TractoR provides general purpose functions for reading, writing and manipulating MR images, as well as more specific code for fitting signal models to diffusion MRI data and performing tractography, a technique for visualizing neural connectivity

Image analysis and statistical inference in neuroimaging with R

R is a language and environment for statistical computing and graphics. It can be considered an alternative implementation of the S language developed in the 1970s and 1980s for data analysis and graphics (Becker and Chambers, 1984; Becker et al., 1988). The R language is part of the GNU project and offers versions that compile and run on almost every major operating system currently available. We highlight several R packages built specifically for the analysis of neuroimaging data in the context of functional MRI, diffusion tensor imaging, and dynamic contrast-enhanced MRI. We review their methodology and give an overview of their capabilities for neuroimaging. In addition we summarize some of the current activities in the area of neuroimaging software development in R

Palladium-Mediated Catalysis Leads to Intramolecular Narcissistic Self-Sorting on a Cavitand Platform

Palladium-catalyzed aminocarbonylation reactions have been used to directly convert a tetraiodocavitand intermediate into the corresponding carboxamides and 2-ketocarboxamides. When complex mixtures of the amine reactants are employed in competition experiments, no ‘mixed’ products possessing structurally different amide fragments are detected either by 1H or 13C NMR. Only highly symmetrical cavitands are sorted out of a large number of potentially feasible products, which represents a rare example of intramolecular, narcissistic self-sorting. The reactivity order of the amine reactants and the changes in the Gibbs energies calculated using the semiempirical PM6 model suggest that this self-sorting process is kinetically controlled

A Robust Cross-Linking Strategy for Block Copolymer Worms Prepared via Polymerization-Induced Self-Assembly

A poly(glycerol monomethacrylate) (PGMA) chain transfer agent is chain-extended by reversible addition-fragmentation chain transfer (RAFT) statistical copolymerization of 2-hydroxypropyl methacrylate (HPMA) with glycidyl methacrylate (GlyMA) in concentrated aqueous solution via polymerization-induced self-assembly (PISA). A series of five free-standing worm gels is prepared by fixing the overall degree of polymerization of the core-forming block at 144 while varying its GlyMA content from 0 to 20 mol %. 1H NMR kinetics indicated that GlyMA is consumed much faster than HPMA, producing a GlyMA-rich sequence close to the PGMA stabilizer block. Temperature-dependent oscillatory rheological studies indicate that increasing the GlyMA content leads to progressively less thermoresponsive worm gels, with no degelation on cooling being observed for worms containing 20 mol % GlyMA. The epoxy groups in the GlyMA residues can be ring-opened using 3-aminopropyltriethoxysilane (APTES) in order to prepare core cross-linked worms via hydrolysis-condensation with the siloxane groups and/or hydroxyl groups on the HPMA residues. Perhaps surprisingly, 1H NMR analysis indicates that the epoxy-amine reaction and the intermolecular cross-linking occur on similar time scales. Cross-linking leads to stiffer worm gels that do not undergo degelation upon cooling. Dynamic light scattering studies and TEM analyses conducted on linear worms exposed to either methanol (a good solvent for both blocks) or anionic surfactant result in immediate worm dissociation. In contrast, cross-linked worms remain intact under such conditions, provided that the worm cores comprise at least 10 mol % GlyMA

White Matter Integrity and Processing Speed in Sickle Cell Anemia

Objective The purpose of this retrospective cross-sectional study was to investigate whether changes in white matter integrity are related to slower processing speed in sickle cell anemia. Methods Thirty-seven patients with silent cerebral infarction, 46 patients with normal MRI, and 32 sibling controls (age range 8–37 years) underwent cognitive assessment using the Wechsler scales and 3-tesla MRI. Tract-based spatial statistics analyses of diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters were performed. Results Processing speed index (PSI) was lower in patients than controls by 9.34 points (95% confi- dence interval: 4.635–14.855, p = 0.0003). Full Scale IQ was lower by 4.14 scaled points (95% confidence interval: −1.066 to 9.551, p = 0.1), but this difference was abolished when PSI was included as a covariate (p = 0.18). There were no differences in cognition between patients with and without silent cerebral infarction, and both groups had lower PSI than controls (both p < 0.001). In patients, arterial oxygen content, socioeconomic status, age, and male sex were identified as predictors of PSI, and correlations were found between PSI and DTI scalars (fractional anisotropy r = 0.614, p < 0.00001; r = −0.457, p < 0.00001; mean diffusivity r = −0.341, p = 0.0016; radial diffusivity r = −0.457, p < 0.00001) and NODDI parameters (intracellular volume fraction r = 0.364, p = 0.0007) in widespread regions. Conclusion Our results extend previous reports of impairment that is independent of presence of infarction and may worsen with age. We identify processing speed as a vulnerable domain, with deficits potentially mediating difficulties across other domains, and provide evidence that reduced processing speed is related to the integrity of normal-appearing white matter using microstructure parameters from DTI and NODDI