Deterministic Josephson vortex ratchet with a load. 2012

M Knufinke, and K Ilin, and M Siegel, and D Koelle, and R Kleiner, and E Goldobin
Physikalisches Institut-Experimentalphysik II and Center for Collective Quantum Phenomena in LISA+, Universität Tübingen, Auf der Morgenstelle 14, D-72076 Tübingen, Germany.

We investigate experimentally a deterministic underdamped Josephson vortex ratchet-a fluxon particle moving along a Josephson junction in an asymmetric periodic potential. By applying a sinusoidal driving current, one can compel the vortex to move in a certain direction, producing an average dc voltage across the junction. Being in such a rectification regime, we also load the ratchet, i.e., apply an additional dc bias current I(dc) (counterforce) which tilts the potential so that the fluxon climbs uphill due to the ratchet effect. The value of the bias current at which the fluxon stops climbing up defines the strength of the ratchet effect and is determined experimentally. This allows us to estimate the loading capability of the ratchet, the output power, and the efficiency. For the quasistatic regime we present a simple model which delivers straightforward analytic expressions for the above-mentioned figures of merit.

UI MeSH Term Description Entries
D008962 Models, Theoretical Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment. Experimental Model,Experimental Models,Mathematical Model,Model, Experimental,Models (Theoretical),Models, Experimental,Models, Theoretic,Theoretical Study,Mathematical Models,Model (Theoretical),Model, Mathematical,Model, Theoretical,Models, Mathematical,Studies, Theoretical,Study, Theoretical,Theoretical Model,Theoretical Models,Theoretical Studies
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D004574 Electromagnetic Fields Fields representing the joint interplay of electric and magnetic forces. Electromagnetic Field,Field, Electromagnetic,Fields, Electromagnetic
D017711 Nonlinear Dynamics The study of systems which respond disproportionately (nonlinearly) to initial conditions or perturbing stimuli. Nonlinear systems may exhibit "chaos" which is classically characterized as sensitive dependence on initial conditions. Chaotic systems, while distinguished from more ordered periodic systems, are not random. When their behavior over time is appropriately displayed (in "phase space"), constraints are evident which are described by "strange attractors". Phase space representations of chaotic systems, or strange attractors, usually reveal fractal (FRACTALS) self-similarity across time scales. Natural, including biological, systems often display nonlinear dynamics and chaos. Chaos Theory,Models, Nonlinear,Non-linear Dynamics,Non-linear Models,Chaos Theories,Dynamics, Non-linear,Dynamics, Nonlinear,Model, Non-linear,Model, Nonlinear,Models, Non-linear,Non linear Dynamics,Non linear Models,Non-linear Dynamic,Non-linear Model,Nonlinear Dynamic,Nonlinear Model,Nonlinear Models,Theories, Chaos,Theory, Chaos
D044085 Microfluidics The study of fluid channels and chambers of tiny dimensions of tens to hundreds of micrometers and volumes of nanoliters or picoliters. This is of interest in biological MICROCIRCULATION and used in MICROCHEMISTRY and INVESTIGATIVE TECHNIQUES. Microfluidic

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