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Redox-controlled conductance of polyoxometalate molecular junctions.

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We demonstrate the reversible in situ photoreduction of molecular junctions of a phosphomolybdate [PMo12O40]3- monolayer self-assembled on flat gold electrodes, connected by the tip of a conductive atomic force microscope.… Click to show full abstract

We demonstrate the reversible in situ photoreduction of molecular junctions of a phosphomolybdate [PMo12O40]3- monolayer self-assembled on flat gold electrodes, connected by the tip of a conductive atomic force microscope. The conductance of the one electron reduced [PMo12O40]4- molecular junction is increased by ∼10, and this open-shell state is stable in the junction in air at room temperature. The analysis of a large current-voltage dataset by unsupervised machine learning and clustering algorithms reveals that the electron transport in the pristine phosphomolybdate junctions leads to symmetric current-voltage curves, controlled by the lowest unoccupied molecular orbital (LUMO) at 0.6-0.7 eV above the Fermi energy with ∼25% of the junctions having a better electronic coupling to the electrodes than the main part of the dataset. This analysis also shows that a small fraction (∼18% of the dataset) of the molecules is already reduced. The UV light in situ photoreduced phosphomolybdate junctions systematically feature slightly asymmetric current-voltage behaviors, which is ascribed to the electron transport mediated by the single occupied molecular orbital (SOMO) nearly at resonance with the Fermi energy of the electrodes and by a closely located single unoccupied molecular orbital (SUMO) at ∼0.3 eV above the SOMO with a weak electronic coupling to the electrodes (∼50% of the dataset) or at ∼0.4 eV but with a better electrode coupling (∼50% of the dataset). These results shed light on the electronic properties of reversible switchable redox polyoxometalates, a key point for potential applications in nanoelectronic devices.

Keywords: conductance; current voltage; redox controlled; molecular orbital; dataset; molecular junctions

Journal Title: Nanoscale
Year Published: 2022

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