Eric P. Fahrenthold

Chemical doping has been studied extensively in attempts to produce high conductivity carbon nanotube wiring. In the case of KAuBr 4, which has shown excellent performance in experiments, ab initio modeling has shown that the disassociated molecule (potassium and AuBr 4 fragments) produces strong n-type (potassium) and p-type (AuBr 4 ) doping of the continuous nanotubes. However, dopant performance at the nanotube junctions, an essential feature of CNT based wiring, is not well understood. Recent ab initio modeling of current transmission at the CNT junctions indicates that the potassium atoms induce a moderate level of conventional doping at the junctions, but that AuBr 4 effects on junction current transmission are fundamentally different. As a conventional dopant the AuBr 4 fragments perform poorly, however in an interstitial configuration they produce near perfect current transmission, even at very small nanotube overlaps. Bond current models of the junctions suggest that their ‘perfect’ performance in an interstitial configuration is due to the formation of supramolecular wires, whose noncovalent assembly is assisted by extrusion processes used to fabricate CNT wiring.

Computational research on laser-metal interaction dynamics has focused heavily on molecular dynamics, continuum thermofluid dynamics, and particle dynamics methods. Research in progress is developing an extended hybrid particle-element method for the simulation of continuous and pulsed laser loading on powder beds and continuous solids. Initial research suggests that the extended formulation is well suited to simulate laser-metal interaction processes.

Chemiresistive oxygen sensing experiments on graphene have shown a wide range of sheet conductivities, with mean values that depend on the sensor substrate, and an order of magnitude variation between reported values for experiments conducted with the same substrate. Recent research by the authors has performed a new series of experiments investigating substrate effects on chemiresistive oxygen sensing with monolayer graphene. The testing included four different substrates, ranging from the most commonly used (silicon dioxide over silicon) to one almost never used (hexagonal boron nitride (hBN) over silicon). The experiments employed eddy current testing, eliminating variations in contact resistance included in the published database, and a single graphene supplier, eliminating variations in graphene quality included in the published database. The results show a strong dependence of the measured sheet conductance on the graphene substrate, including (in the most pronounced case) a sign reversal of the change in conductance induced by oxygen adsorption. This observed substrate dependence may be exploited, by introducing sensor arrays composed of monolayer graphene deposited on different types of substrates, to add selectivity to chemiresistive gas sensors.

Carbon nanotube (CNT) heterostructures have been developed to address a variety of electrical and electrochemical applications, including gas sensing. Examples include the CNT encapsulation of halogen or alkali metal dopants and the surface decoration of CNTs with ferromagnetic materials. Spin polarized chemiresistive sensing, recently proposed for graphene nanoribbon (GNR) based devices, offers a new opportunity for CNT heterostructures in gas sensing applications, one which exploits fundamental quantum physics. Ab initio computational research suggests that iron-filled CNT sensors subjected to a bias voltage and a transverse electric field offer both high sensitivity and excellent selectivity in the trace detection of explosive molecules. As compared to GNR sensors employing the same sensing mechanism, CNT heterostructures show an order of magnitude increase in sensitivity to trinitrotoluene (TNT) and the ability to discriminate between background gases, nitroaromatic explosives, and chemically similar nitramine explosives at a current threshold level a factor of 2 less stringent than that demanded by graphene sensors.

Abstract Experimental research has investigated the non-Newtonian fluid augmentation of fabric barrier materials, aimed at adding impact energy dissipation mechanisms and thereby improving ballistic performance. Published experimental results on the effectiveness of these augmentations are mixed, and numerical models supporting complimentary modeling research are lacking, primarily due to the multiple geometric and material nonlinearities present in the system. The combination of Hamiltonian mechanics with hybrid particle-element kinematics offers a very general modeling approach to impact simulation for these systems, one which includes interstitial fluid–structure interactions, the yarn level dynamics of projectile impacts, and yarn fracture without the introduction of slidelines and without mass or energy discard. Three-dimensional (3D) impact simulations show good agreement with published experiments for magnetorheological (MR) fluid-saturated Kevlar, including fabric tested under bulk field excitation of the target region and magnetomechanically edge-clamped fabric sliding in an excited air gap. The Hamiltonian method employed to develop the system-level model allows for computationally efficient partitioning of the modeled physics while maintaining a thermodynamically consistent formulation.

Energy averaged bond currents assist in the understanding of current transmission in molecular electronic devices and offer an intuitive, yet rigorous, approach to designing nanoscale conductors. Recent research has employed bond current visualization to investigate the changes in transmission pathways induced by boron and nitrogen substitutional doping in graphene nanoribbons. The results identify favored current pathways created by patterned substitutional dopants, especially at low bias voltages, and may be used to tailor the system performance. Selective trimming of the conductors may be used to modify the device geometry while preserving the principal current pathways of interest. Bond current analysis offers a holistic understanding of device performance and therefore serves as a valuable complement to conventional modeling tools, such as band structure analysis. The method maintains a focus on device level performance objectives, while offering intuitive insight into the current distribution patterns which underlie integrated performance metrics.

Simulation of laser-metal interaction dynamics is of interest in a wide range of engineering applications, including laser ablation, laser cutting, and powder bed fusion. Research in progress by the authors is extending Hybrid Particle-Element (HPE) methods to simulate laser-metal interaction dynamics. Simulations indicate that HPE methods are well suited to address the complex mixed energy domain dynamics, material failure processes, and process boundary conditions of interest in this problem. No mass or energy discard, mesh evolution, or particle-to-element mapping is required and common numerical complications such as tensile instabilities and Eulerian frame mass diffusion are avoided. Results of initial research suggest that numerical methods must accurately model laser-metal interaction in both solid structures and powder beds in order to represent the complete process dynamics.