Year: 2024
Type: article
Abstract: We report the first conductance measurements of [ n ]staffane (bicyclopentane) oligomers in single‐molecule junctions. Our studies reveal two quantum transport characteristics unique to staffanes that emerge from their strained bicyclic structure. First, though staffanes are composed of weakly conjugated C−C σ ‐bonds, staffanes carry a shallower conductance decay value (β=0.84±0.02 n −1 ) than alkane chain analogs ( β =0.96±0.03 n −1 ) when measured with the scanning tunneling microscopy break junction (STM‐BJ) technique. Staffanes are thus more conductive than other σ ‐bonded organic backbones reported in the literature on a per atom basis. Density functional theory (DFT) calculations suggest staffane backbones are more effective conduits for charge transport because their significant bicyclic ring strain destabilizes the HOMO‐2 energy, aligning it more closely with the Fermi energy of gold electrodes as oligomer order increases. Second, the monostaffane is significantly lower conducting than expected. DFT calculations suggest that short monostaffanes sterically enforce insulating gauche interelectrode orientations over syn orientations; these steric effects are alleviated in longer staffanes. Moreover, we find that [2‐5]staffane wires may accommodate axial mechanical strain by “rod‐bending”. These findings show for the first time how bicyclic ring strain can enhance charge transmission in saturated molecular wires. These studies showcase the STM‐BJ technique as a valuable tool for uncovering the stereoelectronic proclivities of molecules at material interfaces.
Institution: University of California, Riverside
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $5,510
Awards: G1567405373, CAREER: Saturated and Unsaturated Silicon for Single-Molecule Electronics, Acquisition of a Scalable Storage Cluster for Data Intensive NIH Research, G2868574568, Research Infrastructure: MRI: Acquisition of a Big Data HPC Cluster for Interdisciplinary Research and Training, MRI: Acquisition of a Big Data Compute Cluster for Interdisciplinary Research, G5503543704, G6023280940, G742844383
OpenAlex ID: W4402971808