Browsing by Author "Turgut, Berk Berkan"

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    Charge Trapping Memory with 2.85-nm Si-Nanoparticles Embedded in HfO2
    (ECS, 2015-05) El-Atab, N.; Turgut, Berk Berkan; Okyay, Ali Kemal; Nayfeh, A.
    In this work, the effect of embedding 2.85-nm Si-nanoparticles charge trapping layer in between double layers of high-κ Al2O3/HfO2 oxides is studied. Using high frequency (1 MHz) C-Vgate measurements, the memory showed a large memory window at low program/erase voltages due to the charging of the Si-nanoparticles. The analysis of the C-V characteristics shows that mixed charges are being stored in the Si-nanoparticles where electrons get stored during the program operation while holes dominate in the Si-nanoparticles during the erase operation. Moreover, the retention characteristic of the memory is studied by measuring the memory hysteresis in time. The obtained retention characteristic (35.5% charge loss in 10 years) is due to the large conduction and valence band offsets between the Si-nanoparticles and the Al2O3/HfO2 tunnel oxide. The results show that band engineering is essential in future low-power non-volatile memory devices. In addition, the results show that Si-nanoparticles are promising in memory applications.
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    Graphene Nanoplatelets Embedded in HfO2 for MOS Memory
    (Electrochemical Society Inc., 2015) El-Atab, N.; Turgut, Berk Berkan; Okyay, Ali Kemal; Nayfeh, A.
    In this work, a MOS memory with graphene nanoplatelets charge trapping layer and a double layer high-κ Al2O3/HfO2 tunnel oxide is demonstrated. Using C-Vgate measurements, the memory showed a large memory window at low program/erase voltages. The analysis of the C-V characteristics shows that electrons are being stored in the graphene-nanoplatelets during the program operation. In addition, the retention characteristic of the memory is studied by plotting the hysteresis measurement vs. time. The measured excellent retention characteristic (28.8% charge loss in 10 years) is due to the large electron affinity of the graphene. The analysis of the plot of the energy band diagram of the MOS structure further proves its good retention characteristic. Finally, the results show that such graphene nanoplatelets are promising in future low-power non-volatile memory devices.