Towards nanotube-based sensors for discrimination of drug molecules.

The proper detection of drug molecules is key for applications that have an impact in several fields, ranging from medical treatments to industrial applications. In case of illegal drugs, their correct and fast detection has important implications that affect different parts of society such as security or public health. Here we present a method based on nanoscale sensors made of carbon nanotubes modified with dopants that can detect three types of drug molecules: mephedrone, methamphetamine and heroin.

Influence of Environmental Fluctuations on Quantum Interference in Naphthalene and Azulene.

Both naphthalene and azulene have the same number of carbon and hydrogen atoms, but the former is an alternant hydrocarbon and the latter is a nonalternant hydrocarbon. This leads to a large difference in their electronic and transport properties. Herein, quantum transport is investigated through these two molecules and it is shown how quantum interference (QI) affects their electrical conductance.

2,7- and 4,9-Dialkynyldihydropyrene Molecular Switches: Syntheses, Properties, and Charge Transport in Single-Molecule Junctions.

This paper describes the syntheses of several functionalized dihydropyrene (DHP) molecular switches with different substitution patterns. Regioselective nucleophilic alkylation of a 5-substituted dimethyl isophthalate allowed the development of a workable synthetic protocol for the preparation of 2,7-alkyne-functionalized DHPs. Synthesis of DHPs with surface-anchoring groups in the 2,7- and 4,9-positions is described.

Breakdown of Curly Arrow Rules in Anthraquinone.

Understanding and controlling quantum interference (QI) in single molecules is fundamental to the development of QI-based single-molecule electronics. Simple rules such as counting rules, curly arrow rules (CARs), circuit rules, and more recently magic ratio rules have been developed to predict QI patterns in polycyclic aromatic hydrocarbons. CARs are widely used to predict destructive QI.