What is he best known for?
The fields of study he is best known for:
- Semiconductor
- Electrical engineering
- Transistor
Optoelectronics, Transistor, Electrical engineering, MOSFET and Electronic engineering are his primary areas of study.
His research integrates issues of Nanotechnology, Resistive random-access memory and Coulomb blockade in his study of Optoelectronics.
His studies in Transistor integrate themes in fields like Dram, Quantum tunnelling, Dynamic random-access memory and Logic gate.
He has researched Electrical engineering in several fields, including Impact ionization and Semiconductor device.
His MOSFET study incorporates themes from CMOS, Transconductance, Miniaturization and Amplifier.
His Electronic engineering research includes elements of Radio frequency, Dielectric layer, Flash memory and Nanowire.
His most cited work include:
- Tunneling Field-Effect Transistors (TFETs) With Subthreshold Swing (SS) Less Than 60 mV/dec (1194 citations)
- Single-Crystalline Si STacked ARray (STAR) NAND Flash Memory (180 citations)
- RF Performance and Small-Signal Parameter Extraction of Junctionless Silicon Nanowire MOSFETs (142 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Optoelectronics, Transistor, Electrical engineering, Electronic engineering and MOSFET.
The various areas that Byung-Gook Park examines in his Optoelectronics study include Nanotechnology and Voltage.
Byung-Gook Park has included themes like Capacitance, Silicon on insulator and Nanowire in his Transistor study.
His Electrical engineering study often links to related topics such as Communication channel.
The concepts of his Electronic engineering study are interwoven with issues in Flash memory and Charge trap flash.
His study in MOSFET is interdisciplinary in nature, drawing from both Threshold voltage and Transconductance.
He most often published in these fields:
- Optoelectronics (63.49%)
- Transistor (21.99%)
- Electrical engineering (19.72%)
What were the highlights of his more recent work (between 2018-2021)?
- Optoelectronics (63.49%)
- Transistor (21.99%)
- Neuromorphic engineering (4.77%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Optoelectronics, Transistor, Neuromorphic engineering, Artificial neural network and Logic gate.
Byung-Gook Park is studying Quantum tunnelling, which is a component of Optoelectronics.
His Transistor research includes themes of Dram, Node and Inverter.
His Neuromorphic engineering research integrates issues from Non-volatile memory, Memristor, Resistive switching and Topology.
His Artificial neural network research includes elements of Electronic engineering and Inference.
In Resistive random-access memory, Byung-Gook Park works on issues like Silicon, which are connected to Doping.
Between 2018 and 2021, his most popular works were:
- Neuronal dynamics in HfOx/AlOy-based homeothermic synaptic memristors with low-power and homogeneous resistive switching (42 citations)
- Double-Gate TFET With Vertical Channel Sandwiched by Lightly Doped Si (23 citations)
- Adaptive learning rule for hardware-based deep neural networks using electronic synapse devices (19 citations)
In his most recent research, the most cited papers focused on:
- Semiconductor
- Transistor
- Electrical engineering
His primary scientific interests are in Optoelectronics, Neuromorphic engineering, Transistor, Logic gate and Memristor.
Byung-Gook Park studies Quantum tunnelling which is a part of Optoelectronics.
His Neuromorphic engineering research is multidisciplinary, incorporating perspectives in Computer hardware, Flash memory, Charge trap flash, MNIST database and Reliability.
His work on Tunnel field-effect transistor as part of general Transistor study is frequently linked to Fin, bridging the gap between disciplines.
His Logic gate study integrates concerns from other disciplines, such as D channel, Gate dielectric, Long term plasticity and Plasticity.
His Memristor study incorporates themes from Non-volatile memory, Substrate, Nitride and Boron nitride.
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