Study on native and extrinsic defects in p-type Zn0 semiconductors - by density functional theory and experimental methods

Ph.DDOCTOR OF PHILOSOPH

A novel data-driven controller for plug-in hybrid electric vehicles with improved adaptabilities to driving environment

Instantaneous application optimality is one of the indispensable indicators to assess energy management performance of plug-in hybrid electric vehicles (PHEVs). The momentary optimality, nevertheless, cannot be flexibly reachable under various driving environments due to the partial unobservabilities in control algorithms. To cope with it, a novel data-driven controller for PHEVs is proposed in this paper to achieve the instantaneous optimality of energy management. The well-designed machine learning based controller translates the knowledge of global optimization to real-time controlling scheme with the consideration of adaptabilities to disperse driving conditions. To start with, the universal global optimal control policies for varying driving environment are generated offline based on the chaotic quantum particle swarm optimization with sequential quadratic programming (CQPSO-SQP). Then, the offline optimized global control policies are assembled to construct the dataset for training the least square support vector machine (LSSVM) based controller, which features the superior capability in instantly optimal policy making under different driving conditions. At last, the detailed assessment is performed in simulation test and hardware-in-loop (HIL) test to validate the promising role of CQPSO-PSO and LSSVM in designing the novel energy management controller, and the corresponding results highlight the preferable controlling performance of the proposed novel controller in practical applications

Design‐Dependent Switching Mechanisms of Schottky‐Barrier‐Modulated Memristors based on 2D Semiconductor

Abstract For Schottky barrier‐modulated memristors based on 2D semiconductors, it has, to date, not been possible to achieve control over defect type and concentration as the measured switching characteristics vary considerably even under similar fabrication conditions. In this work, four distinct types of memristors are identified based on the combination of low and high resistance sequences, as well as volatile and nonvolatile characteristics. All these four types of memristors were previously observed experimentally by different research labs. It is found that the specific behavior of each memristor type can be explained by the Schottky barrier height modulation and current rectification arising from the concerted effects of the concentration, charge polarity and mobility of defects. The conditions required to realize the four types of 2D semiconductor‐based memristors are analyzed and design guidelines for fabricating each of these four types of memristors are provided

Full Defects Passivation Enables 21% Efficiency Perovskite Solar Cells Operating in Air

10.1002/aenm.202001958ADVANCED ENERGY MATERIAL

In-memory computing using memristor arrays with ultrathin 2D PdSeOx/PdSe2 heterostructure

https://doi.org/10.1002/adma.202201488Advanced Materials342

Optimization of oxygen evolution activity by tuning e*(g) band broadening in nickel oxyhydroxide

10.1039/d2ee03413aENERGY & ENVIRONMENTAL SCIENCE16

Significant improvement in electronic properties of transparent amorphous indium zinc oxide through yttrium doping

10.1209/0295-5075/106/17006EPL1061