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Hamid Garmestani

Researcher at Georgia Institute of Technology

Publications -  267
Citations -  7474

Hamid Garmestani is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Microstructure & Texture (crystalline). The author has an hindex of 41, co-authored 258 publications receiving 6293 citations. Previous affiliations of Hamid Garmestani include Cornell University & Florida A&M University – Florida State University College of Engineering.

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Opposite Sensing Response of Heterojunction Gas Sensors Based on SnO2–Cr2O3 Nanocomposites to H2 against CO and Its Selectivity Mechanism

TL;DR: In this paper, the p-n nanojunction of xSnO2-yCr2O3 nanocomposites (NCs) are prepared and used as sensing materials, and the gas sensing properties, crystal structure, morphology, and chemical states are characterized by employing an electrochemical workstation, an Xray diffractometer, a transmission electron microscope, and an X-ray photoelectron spectrometer.
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Viscoplastic analysis of structural polymer composites using stress relaxation and creep data

TL;DR: A structural carbon based composite material has been investigated for its high temperature viscoplastic properties using a model based on an overbearing stress concept and using the data obtained from load relaxation and creep.
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A texture evolution model in cubic-orthotropic polycrystalline system

TL;DR: In this article, a new methodology based on a conservation principle in the orientation space is developed to simulate the texture evolution in a cubic-orthotropic polycrystalline system, which is applied to uniaxial tension, compression and rolling for a large deformation of more than 50% using a single evolution parameter.
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Effects of high magnetic field annealing on texture and magnetic properties of FePd

TL;DR: In this paper, the effects of magnetic annealing on the preferred orientation distribution (texture) and magnetic anisotropy of arc-melted FePd alloy were studied by recalculated pole figure method and vibrating sample magnetometry.
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Statistical continuum theory for the effective conductivity of fiber filled polymer composites: Effect of orientation distribution and aspect ratio

TL;DR: In this article, the effect of fiber orientation on the effective conductivity of polymer composites, filled with conducting fibers such as carbon nanotubes, is studied using statistical continuum theory.