Break-junction techniques provide the possibility to study electric and thermoelectric properties of single-molecule junctions in great detail. These techniques rely on the same principle of controllably breaking metallic contacts in order to create single-molecule junctions, whilst keeping track of the junction's conductance. Here, we compare results from mechanically controllable break junction (MCBJ) and scanning tunneling microscope (STM) methods, while characterizing conductance properties of the same novel mechanosensitive para- and meta-connected naphtalenophane compounds. In addition, thermopower measurements are carried out for both compounds using the STM break junction (STM-BJ) technique. For the conductance experiments, the same data processing using a clustering analysis is performed. We obtain to a large extent similar results for both methods, although values of conductance and stretching lengths for the STM-BJ technique are slightly larger in comparison with the MCBJ. STM-BJ thermopower experiments show similar Seebeck coefficients for both compounds. An increase in the Seebeck coefficient is revealed, whilst the conductance decreases, after which it saturates at around 10 μV K−1. This phenomenon is studied theoretically using a tight binding model. It shows that changes of molecule-electrode electronic couplings combined with shifts of the resonance energies explain the correlated behavior of conductance and Seebeck coefficient.
Single molecules can be used as miniaturized functional electronic components, when contacted by macroscopic electrodes. Mechanosensitivity describes a change in conductance for a certain change in electrode separation and is a desirable feature for applications such as ultrasensitive stress sensors. We combine methods of artificial intelligence with high-level simulations based on electronic structure theory to construct optimized mechanosensitive molecules from predefined, modular molecular building blocks. In this way, we overcome time-consuming, inefficient trial-and-error cycles in molecular design. We unveil the black box machinery usually connected to methods of artificial intelligence by presenting all-important evolutionary processes. We identify the general features that characterize well-performing molecules and point out the crucial role of spacer groups for increased mechanosensitivity. Our genetic algorithm provides a powerful way to search chemical space and to identify the most promising molecular candidates.
Mechanoelectric sensitivity reveals destructive quantum interference in single-molecule junctions
(2024)
Quantum interference plays an important role in charge transport through single-molecule junctions, even at room temperature. Of special interest is the measurement of the destructive quantum interference dip itself. Such measurements are especially demanding when performed in a continuous mode of operation. Here, we use mechanical modulation experiments at ambient conditions to reconstruct the destructive quantum interference dip of conductance versus displacement. Simultaneous measurements of the Seebeck coefficient show a sinusoidal response across the dip without sign change. Calculations that include electrode distance and energy alignment variations explain both observations quantitatively, emphasizing the crucial role of thermal fluctuations for measurements under ambient conditions. Our results open the way for establishing a closer link between break-junction experiments and theory in explaining single-molecule transport phenomena, especially when describing sharp features in the transmission.
