Learning Conductance: Gaussian Process Regression for Molecular Electronics

Methods for the analysis, interpretation, and prediction of single-molecule junction conductance behaviour

This article offers a broad overview of measurement methods in the field of molecular electronics, with a particular focus on the most common single-molecule junction fabrication techniques, the challenges in data analysis and interpretation of single-molecule junction current-distance traces, and a summary of simulations and predictive models aimed at establishing robust structure-property relationships of use in the further development of molecular electronics.

Quantitative Structure-Reactivity Relationships for Synthesis Planning: The Benzhydrylium Case

Selective and feasible reactions are among the top targets in synthesis planning. Mayr's approach to quantifying chemical reactivity has greatly facilitated the planning process, but reactivity parameters for new compounds require time-consuming experiments. In the past decade, data-driven modeling has been gaining momentum in the field, as it shows promise in terms of efficient reactivity prediction. However, state-of-the-art models use quantum chemical data as input, which prevent access to real-time planning in organic synthesis. Here, we present a novel data-driven workflow for predicting reactivity parameters of molecules that takes only structural information as input, enabling de facto real-time reactivity predictions. We use the well-understood chemical space of benzhydrylium ions as an example to demonstrate the functionality of our approach and the performance of the resulting quantitative structure-reactivity relationships (QSRRs). Our results suggest that it is straightforward to build low-cost QSRR models that are accurate, interpretable, and transferable to unexplored systems within a given scope of application. Moreover, our QSRR approach suggests that Hammett σ parameters are only approximately additive.

Unraveling the Interplay between Quantum Transport and Geometrical Conformations in Monocyclic Hydrocarbons' Molecular Junctions

In the field of molecular electronics, especially in quantum transport experiments, determining the geometrical configurations of a single molecule trapped between two electrodes can be challenging. To address this challenge, we employed a combination of molecular dynamics (MD) simulations and electronic transport calculations based on density functional theory to determine the molecular orientation in our break-junction experiments under ambient conditions. The molecules used in this study are common solvents used in molecular electronics, such as benzene, toluene (aromatic), and cyclohexane (aliphatic). Furthermore, we introduced a novel criterion based on the normal vector of the surface formed by the cavity of these ring-shaped monocyclic hydrocarbon molecules to clearly define the orientation of the molecules with respect to the electrodes. By comparing the results obtained through MD simulations and density functional theory with experimental data, we observed that both are in good agreement. This agreement helps us to uncover the different geometrical configurations that these molecules adopt in break-junction experiments. This approach can significantly improve our understanding of molecular electronics, especially when using more complex cyclic hydrocarbons.

Microscopic theory, analysis, and interpretation of conductance histograms in molecular junctions

Molecular electronics break-junction experiments are widely used to investigate fundamental physics and chemistry at the nanoscale. Reproducibility in these experiments relies on measuring conductance on thousands of freshly formed molecular junctions, yielding a broad histogram of conductance events. Experiments typically focus on the most probable conductance, while the information content of the conductance histogram has remained unclear. Here we develop a microscopic theory for the conductance histogram by merging the theory of force-spectroscopy with molecular conductance. The procedure yields analytical equations that accurately fit the conductance histogram of a wide range of molecular junctions and augments the information content that can be extracted from them. Our formulation captures contributions to the conductance dispersion due to conductance changes during the mechanical elongation inherent to the experiments. In turn, the histogram shape is determined by the non-equilibrium stochastic features of junction rupture and formation. The microscopic parameters in the theory capture the junction's electromechanical properties and can be isolated from separate conductance and rupture force (or junction-lifetime) measurements. The predicted behavior can be used to test the range of validity of the theory, understand the conductance histograms, design molecular junction experiments with enhanced resolution and molecular devices with more reproducible conductance properties.