The break-junction technique is widely used to measure electronic properties of nanoscale junctions including metal point-contacts and single-molecule junctions. In these measurements, conductance is measured as a function of electrode displacement yielding data that is analyzed by constructing conductance histograms to determine the most frequently observed conductance values in the nanoscale junctions. However much of the rich physics in these measurements is lost in this simple analysis technique. Conductance histograms cannot be used to study the statistical relation of distinct junction configurations, to distinguish structurally different configurations that have similar conductance values, or to obtain information on the relation between conductance and junction elongation. Here, we give a detailed introduction to a novel statistical analysis method based on the two-dimensional cross-correlation histogram (2DCH) analysis of conductance traces and show that this method provides new information about the relation of different junction configurations that occur during the formation and evolution of metal and single-molecule junctions. We first illustrate the different types of correlation effects by using simulated conductance traces. We then apply this analysis method to several different experimental examples. We show from break-junction measurements of different metal point-contacts that in aluminum, the first conductance histogram peak corresponds to two different junction structures. In tantalum, we identify the frequent absence of adhesive instability. We show that conductance plateaus shift in a correlated manner in iron and vanadium junctions. Finally, we highlight the applicability of the correlation analysis to single-molecule platinum-CO-platinum and gold-4,4'-bipyridine-gold junctions.

Break-junction measurements are typically aimed at characterizing electronic properties of single molecules bound between two metal electrodes. Although these measurements have provided structure-function relationships for such devices, there is little work that studies the impact of molecule-molecule interactions on junction characteristics. Here, we use a scanning tunneling microscope based break-junction technique to study pi-stacked dimer junctions formed with two amine-terminated conjugated molecules. We show that the conductance, force and flicker noise of such dimers differ dramatically when compared with the corresponding monomer junctions and discuss the implications of these results on intra- and inter-molecular charge transport.

Herein we demonstrate the controlled and reproducible fabrication of sub-5 nm wide gaps in single-layer graphene electrodes. The process is implemented for graphene grown via chemical vapor deposition using an electroburning process at room temperature and in vacuum. A yield of over 95% for the gap formation is obtained. This approach allows producing single-layer graphene electrodes for molecular electronics at a large scale. Additionally, from Raman spectroscopy and electroburning carried out simultaneously, we can follow the heating process and infer the temperature at which the gap formation happens.

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We measure simultaneously force and conductance of Ag metal point-contacts under ambient conditions at room temperature. We observe the formation of contacts with a conductance close to 1 G0, the quantum of conductance, which can be attributed to a single-atom contact, similar to those formed by Au. We also find two additional conductance features at ∼0.4 G0 and ∼1.3 G0, which have been previously ascribed to contacts with oxygen contaminations. Here, using a conductance cross-correlation technique, we distinguish three different atomic-scale structural motifs and analyze their rupture forces and stiffness. Our results allow us to assign the ∼0.4 G0 conductance feature to an Ag-O-Ag contact and the ∼1.3 G0 feature to an Ag-Ag single-atom contact with an oxygen atom in parallel. Utilizing complementary information from force and conductance, we thus demonstrate the correlation of conductance with the structural evolution at the atomic scale.

Single-molecule break junction measurements deliver a huge number of conductance vs. electrode separation traces. Along such measurements the target molecules may bind to the electrodes in different geometries, and the evolution and rupture of the single-molecule junction may also follow distinct trajectories. The unraveling of the various typical trace classes is a prerequisite of the proper physical interpretation of the data. Here we exploit the efficient feature recognition properties of neural networks to automatically find the relevant trace classes. To eliminate the need for manually labeled training data we apply a combined method, which automatically selects training traces according to the extreme values of principal component projections or some auxiliary measured quantities, and then the network captures the features of these characteristic traces, and generalizes its inference to the entire dataset. The use of a simple neural network structure also enables a direct insight to the decision making mechanism. We demonstrate that this combined machine learning method is efficient in the unsupervised recognition of unobvious, but highly relevant trace classes within low and room temperature gold-4,4' bipyridine-gold single molecule break junction data. arXiv:2001.03006v1 [cond-mat.mes-hall] 9 Jan 2020

Results of an experimental study of palladium nanojunctions in hydrogen environment are presented. Two new hydrogen-related atomic configurations are found, which have a conductances of ∼ 0.5 and ∼ 1 quantum unit (2e 2 /h). Phonon spectrum measurements demonstrate that these configurations are situated between electrodes containing dissolved hydrogen. The crucial differences compared to the previously studied Pt-H2 junctions, and the possible microscopic realizations of the new configurations in palladium-hydrogen atomic-sized contacts are discussed.

We present a novel statistical method for the study of stable atomic configurations in breaking nanowires based on the 2D cross-correlation analysis of conductance versus electrode separation traces. Applying this method, we can clearly resolve the typical evolutions of the conductance staircase in some transition metal nanojunctions (Ni, Fe, V) up to high conductance values. In these metals our analysis demonstrates a very well ordered atomic narrowing of the nanowire, indicating a very regular, stepwise decrease of the number of atoms in the minimal cross section of the junction, in contrast to the majority of the metals. All these features are hidden in traditional conductance histograms.