Oblique Hanle Effect in Semiconductor Spin Transport Devices

Spin precession and dephasing ("Hanle effect") provides an unambiguous means to establish the presence of spin transport in semiconductors. We compare theoretical modeling with experimental data from drift-dominated silicon spin-transport devices, illustrating the non-trivial consequences of employing oblique magnetic fields (due to misalignment or intentional, fixed in-plane field components) to measure the effects of spin precession. Model results are also calculated for Hanle measurements under conditions of diffusion-dominated transport, revealing an expected Hanle peak-widening effect induced by the presence of fixed in-plane magnetic bias fields

Geometric dephasing-limited Hanle effect in long-distance lateral silicon spin transport devices

Evidence of spin precession and dephasing ("Hanle effect") induced by an external magnetic field is the only unequivocal proof of spin-polarized conduction electron transport in semiconductor devices. However, when spin dephasing is very strong, Hanle effect in a uniaxial magnetic field can be impossible to measure. Using a Silicon device with lateral injector-detector separation over 2 millimeters, and geometrically-induced dephasing making spin transport completely incoherent, we show experimentally and theoretically that Hanle effect can still be measured using a two-axis magnetic field

35% magnetocurrent with spin transport through Si

Efficient injection of spin-polarized electrons into the conduction band of silicon is limited by the formation of a silicide at the ferromagnetic metal (FM)/silicon interface. In the present work, this "magnetically-dead" silicide (where strong spin-scattering significantly reduces injected spin polarization) is eliminated by moving the FM in the spin injector from the tunnel junction base anode to the emitter cathode and away from the silicon surface. This results in over an order-of-magnitude increase in spin injection efficiency, from a previously-reported magnetocurrent ratio of ~2% to ~35% and an estimated spin polarization in Si from ~1% to at least ~15%. The injector tunnel-junction bias dependence of this spin transport signal is also measured, demonstrating the importance of low bias voltage to preserve high injected spin polarization

Clustering documents with active learning using Wikipedia

Wikipedia has been applied as a background knowledge base to various text mining problems, but very few attempts have been made to utilize it for document clustering. In this paper we propose to exploit the semantic knowledge in Wikipedia for clustering, enabling the automatic grouping of documents with similar themes. Although clustering is intrinsically unsupervised, recent research has shown that incorporating supervision improves clustering performance, even when limited supervision is provided. The approach presented in this paper applies supervision using active learning. We first utilize Wikipedia to create a concept-based representation of a text document, with each concept associated to a Wikipedia article. We then exploit the semantic relatedness between Wikipedia concepts to find pair-wise instance-level constraints for supervised clustering, guiding clustering towards the direction indicated by the constraints. We test our approach on three standard text document datasets. Empirical results show that our basic document representation strategy yields comparable performance to previous attempts; and adding constraints improves clustering performance further by up to 20%