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Graphene on A Metal Surface with an h-BN buffer layer: Gap Opening and N-doping
Tao Wang,Yunhao Lu,Y.P. Feng 한국물리학회 2016 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.68 No.7
Graphene grown on a metal surface, Cu(111), with a boron-nitride (h-BN) buffer layer is studied. Our first-principles calculations reveal that charge is transferred from the copper substrate to graphene through the h-BN buffer layer which results in n-doped graphene in the absence of a gate voltage. More importantly, a gap of 0.2 eV, which is comparable to that of a typical narrow gap semiconductor, opens just 0.5 eV below the Fermi level at the Dirac point. The Fermi level can be easily shifted inside this gap to make graphene a semiconductor, which is crucial for graphene-based electronic devices. A graphene-based p-n junction can be realized with graphene eptaxially grown on a metal surface.
State of Health Estimation for Lithium-ion Battery Based on D-UKF
Wang Qiuting,Jiang Yinzhu,Lu Yunhao 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.7
This paper considers an accurate estimation method of State of Health (SOH) for lithium battery. An improved battery model is proposed which is based on equivalent circuit model and battery internal electrochemical characteristics. In our study, Double Unscented Kalman Filtering (D-UKF) algorithm is designed to calculate State of Charge (SOC) and SOH of lithium battery at the same time. The feature of our new method is SOH estimation model is derived based on battery internal resistances. The Ohmic resistance (one of internal resistances) can be identified online based on D-UKF algorithm. Two filters defined as UKF1 and UKF2 are working together to calculate the real-value of SOC and Ohmic resistance to obtain final SOH value. The experimental results indicate that our new battery model considers different value of battery internal resistances on different working condition (as different voltages, different currents). Besides, our study verifies the performance and feasibility of new estimation method based on D-UKF. This new algorithm has the practical value to further study for other types of lithium battery.