M
Meng Lu
Researcher at Iowa State University
Publications - 140
Citations - 2550
Meng Lu is an academic researcher from Iowa State University. The author has contributed to research in topics: Photonic crystal & Laser. The author has an hindex of 26, co-authored 129 publications receiving 2179 citations. Previous affiliations of Meng Lu include University of Illinois at Urbana–Champaign.
Papers
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Temperature dependence of electrical and thermal conduction in single silver nanowire.
TL;DR: In this article, the thermal and electrical transport in an individual silver nanowire is characterized down to 35 K for in-depth understanding of the strong structural defect induced electron scattering.
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Temperature dependence of electrical and thermal conduction in single silver nanowire
TL;DR: The results indicate that, at room temperature, the electrical resistivity increases by around 4 folds from that of bulk silver, and proposes that the silver nanowire and bulk silver share the similar phonon-electron scattering mechanism for thermal transport.
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Tuneable complementary metamaterial structures based on graphene for single and multiple transparency windows
Jun Ding,Bayaner Arigong,Han Ren,Mi Zhou,Jin Shao,Meng Lu,Yang Chai,Yuankun Lin,Hualiang Zhang +8 more
TL;DR: The graphene-based quadrupole slot structure can realize a single transparency window, which is achieved without breaking the structure symmetry, and the transparency windows can be dynamically controlled over a broad frequency range by varying the Fermi energy levels of the graphene layer (through electrostatic gating).
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Application of photonic crystal enhanced fluorescence to cancer biomarker microarrays
Cheng-Sheng Huang,Sherine George,Meng Lu,Vikram Chaudhery,Ruimin Tan,Richard C. Zangar,Brian T. Cunningham +6 more
TL;DR: Dose-response characterization of the photonic crystal antibody microarrays shows the capability to detect common cancer biomarkers in the <2 pg/mL concentration range within a mixed sample.
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A Sensitivity Model for Predicting Photonic Crystal Biosensor Performance
TL;DR: In this paper, a model for predicting photonic crystal label-free biosensor performance based primarily on the spatial distribution of electromagnetic near fields at device resonance is presented, and the effect of each property on the resonant mode profile, and consequently on sensor performance, is illustrated.