A model of an optical biosensor detecting environment

Heller et. Al. (Science 311, 508 (2006)) demonstrated the first DNA-CN optical sensor by wrapping a piece of double-stranded DNA around the surface of single-walled carbon nanotubes (CN). This new type of optical device can be placed inside living cells and detect trace amounts of harmful contaminants by means of near infrared light. Using a simple exciton theory in nanostructures and the phenomena of B-Z structural phase transition of DNA, we investigate the working principle of this new class of optical biosensor from DNA by using the nanostructure surface as a sensor to detect the property change of DNA as it responds to the presence of target ions. We also propose some new design models by replacing carbon nanotubes with graphene ribbon semiconductors.Comment: 4 pages, 4 figures, Accepte

The Yoneda algebra of a graded Ore extension

Let A be a connected-graded algebra with trivial module k, and let B be a graded Ore extension of A. We relate the structure of the Yoneda algebra E(A) := Ext_A(k,k) to E(B). Cassidy and Shelton have shown that when A satisfies their K_2 property, B will also be K_2. We prove the converse of this result.Comment: 9 page

Linear response within the projection-based renormalization method: Many-body corrections beyond the random phase approximation

The explicit evaluation of linear response coefficients for interacting many-particle systems still poses a considerable challenge to theoreticians. In this work we use a novel many-particle renormalization technique, the so-called projector-based renormalization method, to show how such coefficients can systematically be evaluated. To demonstrate the prospects and power of our approach we consider the dynamical wave-vector dependent spin susceptibility of the two-dimensional Hubbard model and also determine the subsequent magnetic phase diagram close to half-filling. We show that the superior treatment of (Coulomb) correlation and fluctuation effects within the projector-based renormalization method significantly improves the standard random phase approximation results.Comment: 17 pages, 7 figures, revised versio