J
John B. Pendry
Researcher at Imperial College London
Publications - 546
Citations - 94437
John B. Pendry is an academic researcher from Imperial College London. The author has contributed to research in topics: Metamaterial & Plasmon. The author has an hindex of 100, co-authored 536 publications receiving 88802 citations. Previous affiliations of John B. Pendry include University of California, San Diego & Duke University.
Papers
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Theory of the extended x-ray absorption fine structure
TL;DR: In this article, a theory of the absorption fine structure starting from theoretically obtained electron-atom scattering phase shifts is presented, where the electron scattering is treated using a spherical wave expansion which takes into account the finite size of the atoms.
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Full-wave simulations of electromagnetic cloaking structures.
TL;DR: Full electromagnetic simulations of the cylindrical version of this cloaking structure are reported, using ideal and nonideal electromagnetic parameters that show that the low-reflection and power-flow bending properties of the electromagnetic cloaky structure are not especially sensitive to modest permittivity and permeability variations.
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Design of electromagnetic cloaks and concentrators using form-invariant coordinate transformations of Maxwell’s equations
TL;DR: In this article, a square electromagnetic cloak and an omni-directional electromagnetic field concentrator are described and the functionality of the devices is numerically confirmed by two-dimensional finite element simulations.
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Calculation of material properties and ray tracing in transformation media.
TL;DR: The calculation of material properties for coordinate transformations that describe spaces with spherical or cylindrical holes in them can then implement invisibility cloaks in flat space and a method is described for performing geometric ray tracing in these materials.
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Reliability factors for LEED calculations
TL;DR: In this paper, the double-R reliability factor (RR) was introduced, where R*RR is the variance of R. This enables quantitative statements to be made about the significance of minima in R.