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Register a new userUnsupervised feature recognition in single molecule break junction data
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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.
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Controlling electronic transport through a single-molecule junction is crucial for molecular electronics or spintronics. In magnetic molecular devices, the spin degree-of-freedom can be used to this end since the magnetic properties of the magnetic ion centers fundamentally impact the transport through the molecules. Here we demonstrate that the electron pathway in a single-molecule device can be selected between two molecular orbitals by varying a magnetic field, giving rise to a tunable anisotropic magnetoresistance up to 93%. The unique tunability of the electron pathways is due to the magnetic reorientation of the transition metal center, resulting in a re-hybridization of molecular orbitals. We obtain the tunneling electron pathways by Kondo effect, which manifests either as a peak or a dip line shape. The energy changes of these spin-reorientations are remarkably low and less than one millielectronvolt. The large tunable anisotropic magnetoresistance could be used to control electronic transport in molecular spintronics.
It is known that the quantum-mechanical ground state of a nano-scale junction has a significant impact on its electrical transport properties. This becomes particularly important in transistors consisting of a single molecule. Due to strong electron-electron interactions and the possibility to access ground states with high spins, these systems are eligible hosts of a current-blockade phenomenon called ground-state spin blockade. This effect arises from the inability of a charge carrier to account for the spin difference required to enter the junction, as that process would violate the spin selection rules. Here, we present a direct experimental demonstration of ground-state spin blockade in a high-spin single-molecule transistor. The measured transport characteristics of this device exhibit a complete suppression of resonant transport due to a ground-state spin difference of 3/2 between subsequent charge states. Strikingly, the blockade can be reversibly lifted by driving the system through a magnetic ground-state transition in one charge state, using the tunability offered by both magnetic and electric fields.
Single molecules are nanoscale thermodynamic systems with few degrees of freedom. Thus, the knowledge of their entropy can reveal the presence of microscopic electron transfer dynamics, that are difficult to observe otherwise. Here, we apply thermocurrent spectroscopy to directly measure the entropy of a single free radical molecule in a magnetic field. Our results allow us to uncover the presence of a singlet to triplet transition in one of the redox states of the molecule, not detected by conventional charge transport measurements. This highlights the power of thermoelectric measurements which can be used to determine the difference in configurational entropy between the redox states of a nanoscale system involved in conductance without any prior assumptions about its structure or microscopic dynamics.
A simple and fast analysis method to sort large data sets into groups with shared distinguishing characteristics is described, and applied to single molecular break junction conductance versus electrode displacement data. The method, based on principal component analysis, successfully sorted data sets based on the projection of the data onto the first or second principal component of the correlation matrix without the need to assert any specific hypothesis about the expected features within the data. This was an improvement on the current correlation matrix analysis approach because it sorted data automatically, making it more objective and less time consuming, and our method is applicable to a wide range of multivariate data sets. Here the method was demonstrated on two systems. First, it was demonstrated on mixtures of two molecules with identical anchor groups, similar lengths, but either a $pi$ (high conductance) or $sigma$ (low conductance) bridge. The mixed data was automatically sorted into two groups containing one molecule or the other. Second, it was demonstrated on break junction data measured with the $pi$ bridged molecule alone. Again the method distinguished between two groups. These groups were tentatively assigned to different geometries of the molecule in the junction.
We have investigated electrical transport through the molecular model systems benzenedithiol, benzenediamine, hexanedithiol and hexanediamine. Conductance histograms under different experimental conditions indicate that measurements using mechanically controllable break junctions in vacuum are limited by the surface density of molecules at the contact. Hexanedithiol histograms typically exhibit a broad peak around 7 * 10^{-4} G_0. In contrast to recent results on STM-based break junctions in solution we find that the spread in single-molecule conductance is not reduced by amino anchoring groups. Histograms of hexanediamine exhibit a very wide peak around 4 * 10^{-4} G_0. For both benzenedithiol and benzenediamine we observe a large variability in low-bias conductance. We attribute these features to the slow breaking of the lithographic mechanically controllable break junctions and the absence of a solvent that may enable molecular readsorption after bond breaking. Nevertheless, we have been able to acquire reproducible current-voltage characteristics of benzenediamine and benzenedithiol using a statistical measurement approach. Benzenedithiol measurements yield a conductance gap of about 0.9 V at room temperature and 0.6 V at 77 K. In contrast, the current-voltage characteristics of benzenediamine-junctions typically display conductance gaps of about 0.9 V at both temperatures.
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