Browsing by Author "Tan Hark"

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Browsing by Author "Tan Hark"

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  • Controlling the properties of InGaAs quantum dots by selective-area epitaxy 
    Mokkapati Sudha; Lever Penelope; Tan Hark; Jagadish Chennupati; Mcbean Katie; Phillips Matthew (American Institute of Physics, 2005)
    Selective growth of InGaAs quantum dots on GaAs is reported. It is demonstrated that selective-area epitaxy can be used for in-plane bandgap energy control of quantum dots. Atomic force microscopy and cathodoluminescence ...
  • Integration of quantum dot devices by selective area epitaxy 
    Tan Hark; Jagadish Chennupati; Mokhapati S; Mcbean Katie; Phillips Matthew (The Institute of Electrical and Electronic Engineers Inc (IEEE), 2006)
    The results of nucleation of InGaAs and InAs quantum dots by selective area epitaxy are presented. By prepatterning the substrates with different (SiO2) mask dimensions, the bandgap of the quantum dots can be tuned over ...
  • Observation of blue shifts in ZnO/ZnMgO multiple quantum well structures by ion-implantation induced intermixing 
    Coleman V; Buda M; Tan Hark; Jagadish Chennupati; Phillips Matthew; Koike K; Sasa S; Inoue M; Yano M (Institute of Physics Publishing, 2006)
    Implantation with low-energy (80 keV) oxygen ions and subsequent rapid thermal annealing at 800 ◦C are used to induce intermixing in a stack of 19 ZnO/Zn0.7Mg0.3O multiple quantum wells grown on sapphire by molecular beam ...
  • Tuning the bandgap of InAs quantum dots by selective-area MOCVD 
    Mokkapati Sudha; Wong-Leung Jennifer; Tan Hark; Jagadish Chennupati; Mcbean Katie; Phillips Matthew (IOP Publishing Ltd, 2008)
    In-plane bandgap energy control of InAs quantum dots (QDs) grown on GaAs substrates is demonstrated using selective-area epitaxy. Transmission electron microscopy and cathodoluminescence are used for characterization of ...
  • X3-Miner: mining patterns from an XML database 
    Tan Hark; Dillon Tharam; Feng Ling; Chang Elizabeth; Hadzic Fedja (WIT Press, 2005)
    An XML enabled framework for representation of association rules in databases was first presented in [4]. In Frequent Structure Mining (FSM), one of the popular approaches is to use graph matching that use data structures ...