Bond Breaking Kinetics in Mechanically Controlled Break Junction Experiments: A Bayesian Approach.

Break junction experiments allow investigating electronic and spintronic properties at the atomic and molecular scale. These experiments generate by their very nature broad and asymmetric distributions of the observables of interest, and thus, a full statistical interpretation is warranted. We show here that understanding the complete lifetime distribution is essential for obtaining reliable estimates. We demonstrate this for Au atomic point contacts by adopting Bayesian reasoning to make maximal use of all measured data to reliably estimate the distance to the transition state, x‡, the associated free energy barrier, ΔG‡, and the curvature, v, of the free energy surface. Obtaining robust estimates requires less experimental effort than with previous methods and fewer assumptions and thus leads to a significant reassessment of the kinetic parameters in this paradigmatic atomic-scale structure. Our proposed Bayesian reasoning offers a powerful and general approach when interpreting inherently stochastic data that yield broad, asymmetric distributions for which analytical models of the distribution may be developed.

Correlated Energy-Level Alignment Effects Determine Substituent-Tuned Single-Molecule Conductance.

The rational design of single-molecule electrical components requires a deep and predictive understanding of structure-function relationships. Here, we explore the relationship between chemical substituents and the conductance of metal-single-molecule-metal junctions, using functionalized oligophenylenevinylenes as a model system. Using a combination of mechanically controlled break-junction experiments and various levels of theory including non-equilibrium Green's functions, we demonstrate that the connection between gas-phase molecular electronic structure and in-junction molecular conductance is complicated by the involvement of multiple mutually correlated and opposing effects that contribute to energy-level alignment in the junction. We propose that these opposing correlations represent powerful new "design principles" because their physical origins make them broadly applicable, and they are capable of predicting the direction and relative magnitude of observed conductance trends. In particular, we show that they are consistent with the observed conductance variability not just within our own experimental results but also within disparate molecular series reported in the literature and, crucially, with the trend in variability across these molecular series, which previous simple models fail to explain. The design principles introduced here can therefore aid in both screening and suggesting novel design strategies for maximizing conductance tunability in single-molecule systems.