We report transport measurements on tunable single-molecule junctions of the organic perchlorotrityl radical molecule, contacted with gold electrodes at low temperature. The current−voltage characteristics of a subset of junctions shows zerobias anomalies due to the Kondo effect and in addition elevated magnetoresistance (MR). Junctions without Kondo resonance reveal a much stronger MR. Furthermore, we show that the amplitude of the MR can be tuned by mechanically stretching the junction. On the basis of these findings, we attribute the high MR to an interference effect involving spin-dependent scattering at the metal−molecule interface and assign the Kondo effect to the unpaired spin located in the center of the molecule in asymmetric junctions.

SynopsisPolymerization of fibrin molecules results in the formation of a double-stranded protofibril. Although convincing data have not been presented, it is classically believed that 7-chain cross-linking of fibrin molecules occurs between the longitudinal end-to-end contacts (DD-long contacts) of the molecules within each of the two strands of a protofibril (intrastrand crosslinking). In this investigation the question addressed was whether y-chain cross-linking takes place across the two strands (interstrand cross-linking) between the transversal half-staggered contacts of the molecules. Demonstration of double-stranded protofibrils in the presence of urea would indicate an interstrand cross-linking, whereas in the case of intrastrand cross-linking, the chaotropic agent urea would dissociate the double-stranded structure to fofm single-stranded fibrils. Protofibrils were obtained by generating soluble cross-linked fibrin polymers (sXLFbP): After incubation of soluble fibrin polymers with Factor XIIIa at 37"C, the polymerization and cross-linking reaction was stopped by the addition of 6M urea and EDTA. Gel filtration of the reaction mixture in the presence of 3M urea was effect in separating sXLFbP from monomeric molecules. The sXLFbP-containing fractions were adsorbed onto mica in the presence of different concentrations of urea and investigated by electron micrwopy after rotary shadowing. In the presence of 3 M urea the sXLFbP appeared as double-stranded protofibrils. In the presence of 4 M urea some parts of the double-stranded structure were found to be unfolded whereas in the presence of 6M urea multiple-bended single-stranded fibrils were observed. SDS-polyacrylamide gel electrophoresis of the sXLFbP demonstrated no a-chain cross-linking within the protofibrils. Ultracentrifugation of the sXLFbP showed that in the presence of 3M urea noncross-linked fibrin polymers dissociated to monomeric molecules. When sXLFbP was centrifuged into 6 M urea on sucrose density gradients, no reduction of the polymer size could be observed. The data indicate that y-chain cross-linking occurs between the transversal contacts of the fibrin molecules within a protofibril, thus generating interstrand cross-linking. A model of the cross-linking of polymerized fibrin molecules is developed and the term DD-trans contact is proposed for this specific alignment of the D-domains.

Colloidal quantum dots assembled into quantum dot solids usually suffer from poor conductivity. The most common charge transport mechanism through the solid is hopping transport where the hopping probability depends on the barrier type (stabilizing/connecting ligand molecule) and the interparticle distance. It is demonstrated that the electronic structure of the ligand molecule strongly alters the transport behavior through CuInSe2 quantum dot solids. Transport measurements and optical‐pump terahertz‐probe experiments after a ligand exchange to fully conjugated molecules show an increase of the conductivity by orders of magnitude, as well as a change of the hopping transport mechanism. This change is not due to a reduced interparticle distance, but the electronic structure: the obtained frequency‐dependent complex conductivities point toward an efficient hole transport enabled by an alignment of the quantum dot valence bands and ligand states.

Experimental studies of charge transport through single molecules often rely on break junction setups, where molecular junctions are repeatedly formed and broken while measuring the conductance, leading to a statistical distribution of conductance values. Modeling this experimental situation and the resulting conductance histograms is challenging for theoretical methods, as computations need to capture structural changes in experiments, including the statistics of junction formation and rupture. This type of extensive structural sampling implies that even when evaluating conductance from computationally efficient electronic structure methods, which typically are of reduced accuracy, the evaluation of conductance histograms is too expensive to be a routine task. Highly accurate quantum transport computations are only computationally feasible for a few selected conformations and thus necessarily ignore the rich conformational space probed in experiments. To overcome these limitations, we investigate the potential of machine learning for modeling conductance histograms, in particular by Gaussian process regression. We show that by selecting specific structural parameters as features, Gaussian process regression can be used to efficiently predict the zero-bias conductance from molecular structures, reducing the computational cost of simulating conductance histograms by an order of magnitude. This enables the efficient calculation of conductance histograms even on the basis of computationally expensive first-principles approaches by effectively reducing the number of necessary charge transport calculations, paving the way toward their routine evaluation.