Graphene based sensors have shown excellent potential in the trace detection of specific gases which are hazardous to humans or environmentally toxic. Sensor designs incorporating pristine graphene, graphene oxide, and nanopatterned graphene have been the focus of much recent experimental and computational research. The application of graphene based sensors in the trace detection of explosives has seen relatively limited study, due in part to the difficulties of conducting experiments using the nitramine and aromatic explosives of central interest. Computational studies of explosive sensors are not subject to hazardous materials handling constraints, and may be used to complement experimental research on the development of low weight, low power, graphene-based sensors. Ab initio models of five different graphene nanoribbon sensor configurations have been developed, and their chemiresistive response to three widely used explosives and four background gases has been investigated. The results indicate that the sensitivity and selectivity of nanoribbon devices exposed to mixtures of explosives and background gases will vary significantly with explosive type and sensor configuration.

Oblique view of a sensing nanoribbon in equilibrium with an analyte molecule.

The electrical properties of deformed graphene nanoribbons (GNRs) are of considerable current research interest since GNRs have wide potential application in electronic and nanoelectromechanical devices. Examples include flexible carbon-based electrical conductors, soft actuators, and chemiresistive sensors. Although considerable experimental and computational research has investigated both zigzag and armchair GNR performance, general analytical descriptions of electromechanical coupling in GNRs are needed. Motivated by questions raised in published experimental research, the new modeling research presented here provides a general description of the combined effects of length and curvature on the current−voltage characteristics of 3M − 1 aGNRs. Consistent with experiment, the modeling results show that the total length and total rotation (along a circular arc) are orthogonal coordinates which determine the GNR resistance. The ratio of curved GNR current to flat GNR current, at the same length and voltage bias, is a linear function of the rotation over a wide operating range. The proposed model generalizes the well-known exponential decay law for the resistance of flat semiconducting nanowires and has direct application in the design of experiments and the conceptual design of new devices, including high-resolution displacement transducers, strain gauges, and nanoresonators.

Spin current based sensing methods offer a new approach to the development of selective detection devices for explosive molecules. Employing a combination of bias voltages and transverse electric fields to vary the chemiresistive properties of a zigzag graphene nanoribbon, dual-input dual-output sensors of this kind offer major advantages: tuning the electrical properties of a single nanoribbon is equivalent to deploying a sensor array, and measuring two outputs (spin-up and spin-down currents, total current and spin current difference, etc.) offers improved selectivity. Ab initio modeling suggests that the magnetic properties of the analyte, charge transfer effects, current transmission pathways, and analyte molecule size all influence sensor signatures. Analysis of the sensing cause–effect physics relies upon the calculation of energy averaged bond currents, which visualize the global spin current transport. Principal component analysis of the proposed sensing scheme suggests that it can distinguish between common background gases, nitroaromatic explosives, and nitramine explosives and will offer far better selectivity than carbon nanotube based explosive sensing devices.

Carbon-based conductors and metal−carbon composites have attracted much recent research interest as candidates for the future replacement of copper wiring in a variety of applications. The development of nanocarbon-based electrical wiring with high mass specific conductivity is of particular interest in weight sensitive applications such as aerospace vehicle design. Although recent experimental research suggests that doped graphene may offer fundamental improvements in specific conductivity, some important properties of interest cannot be measured directly, including the effects of dopants on the conductance of interfaces (junctions) in multilayer graphene. Recent computational research has developed the first general ab initio model of doped graphene nanoribbon (GNR)-based electrical conductors, including the combined effects of doping density, doping distribution, GNR overlap, junction conductance, junction cascades, and electron mean free path on the specific conductivity of doped graphene nanowires. The general modeling approach has been applied to potassium-doped graphene; the results are consistent with published experimental data and identify nanoscale features which limit macroscale conductor performance.