A novel measurement of dynamic friction

A tribometer, based on a pin-on-disc machine, uses a PZT drive to produce small sinusoidal fluctuations of sliding speed. The frequency and amplitude of these fluctuations can be controlled, and the dynamic response measured. Preliminary test results show that the dynamic friction variation is influenced by the contact materials, normal force, oscillation frequency and steady sliding speed. The variation of friction force amplitude and phase with frequency gives clues about the underlying state variables determining the friction. Modelling studies illustrate the expected behaviour for idealized friction laws governed by, for example, sliding speed, contact temperature, and "rate-state" laws. © 2008 SAE International.

A novel measurement of dynamic friction

A tribometer, based on a pin-on-disc machine, uses a PZT drive to produce small sinusoidal fluctuations of sliding speed. The frequency and amplitude of these fluctuations can be controlled, and the dynamic response measured. Preliminary test results show that the dynamic friction variation is influenced by the contact materials, normal force, oscillation frequency and steady sliding speed. The variation of friction force amplitude and phase with frequency gives clues about the underlying state variables determining the friction. Modelling studies illustrate the expected behaviour for idealized friction laws governed by, for example, sliding speed, contact temperature, and "rate-state" laws. © 2008 SAE International.

Uniform stability of a particle approximation of the optimal filter derivative

Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.

Single-particle probing of edge-state formation in a graphene nanoribbon

We investigate the effect of a perpendicular magnetic field on the single-particle charging spectrum of a graphene quantum dot embedded inline with a nanoribbon. We observe uniform shifts in the single-particle spectrum which coincide with peaks in the magnetoconductance, implicating Landau level condensation and edge state formation as the mechanism underlying magnetic field-enhanced transmission through graphene nanostructures. The experimentally determined ratio of bulk to edge states is supported by single-particle band-structure simulations, while a fourfold beating of the Coulomb blockade transmission amplitude points to many-body interaction effects during Landau level condensation of the ν=0 state. © 2012 American Physical Society.

Oscillator models and collective motion: Splay state stabilization of self-propelled particles

This paper presents a Lyapunov design for the stabilization of collective motion in a planar kinematic model of N particles moving at constant speed. We derive a control law that achieves asymptotic stability of the splay state formation, characterized by uniform rotation of N evenly spaced particles on a circle. In designing the control law, the particle headings are treated as a system of coupled phase oscillators. The coupling function which exponentially stabilizes the splay state of particle phases is combined with a decentralized beacon control law that stabilizes circular motion of the particles. © 2005 IEEE.

Introducing carbon diffusion barriers for uniform, high-quality graphene growth from solid sources.

Carbon diffusion barriers are introduced as a general and simple method to prevent premature carbon dissolution and thereby to significantly improve graphene formation from the catalytic transformation of solid carbon sources. A thin Al2O3 barrier inserted into an amorphous-C/Ni bilayer stack is demonstrated to enable growth of uniform monolayer graphene at 600 °C with domain sizes exceeding 50 μm, and an average Raman D/G ratio of <0.07. A detailed growth rationale is established via in situ measurements, relevant to solid-state growth of a wide range of layered materials, as well as layer-by-layer control in these systems.