What is he best known for?
The fields of study he is best known for:
- Semiconductor
- Electrical engineering
- Transistor
The scientist’s investigation covers issues in Optoelectronics, Electrical engineering, Non-volatile memory, Memory cell and Dielectric.
His Optoelectronics research is mostly focused on the topic High-κ dielectric.
In general Electrical engineering study, his work on Insulator, Transistor and Gate stack often relates to the realm of Polymer capacitor, thereby connecting several areas of interest.
His research in Non-volatile memory tackles topics such as Low voltage which are related to areas like EEPROM and Work function.
His work in Memory cell tackles topics such as Node which are related to areas like Semiconductor memory, Volatile memory, Anode, Line and Diode.
His Electronic engineering study incorporates themes from Layer and Silicon-germanium.
His most cited work include:
- Hafnium aluminium oxynitride high-K dielectric and metal gates (239 citations)
- Hafnium tantalum oxynitride high-k dielectric and metal gates (211 citations)
- Scalable flash/NV structures and devices with extended endurance (183 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Optoelectronics, Electrical engineering, Memory cell, Transistor and Dielectric.
His Optoelectronics study combines topics from a wide range of disciplines, such as Electronic engineering and Thin-film transistor.
His Electrical engineering research is multidisciplinary, incorporating perspectives in Layer and Body region.
His research investigates the connection with Memory cell and areas like Quantum tunnelling which intersect with concerns in Blocking.
His Transistor research includes themes of Semiconductor and Thyristor.
His research in the fields of High-κ dielectric overlaps with other disciplines such as Electronic systems and Lanthanide.
He most often published in these fields:
- Optoelectronics (81.89%)
- Electrical engineering (40.16%)
- Memory cell (29.92%)
What were the highlights of his more recent work (between 2009-2017)?
- Optoelectronics (81.89%)
- Dielectric (24.41%)
- Memory cell (29.92%)
In recent papers he was focusing on the following fields of study:
Arup Bhattacharyya mainly focuses on Optoelectronics, Dielectric, Memory cell, Quantum tunnelling and Non-volatile memory.
His biological study spans a wide range of topics, including Layer and Semiconductor device.
His work on High-κ dielectric is typically connected to Electronic systems, Oxygen and Lanthanide as part of general Dielectric study, connecting several disciplines of science.
The concepts of his Quantum tunnelling study are interwoven with issues in Blocking, Electrical engineering and Low voltage.
His Electrical engineering study integrates concerns from other disciplines, such as Band gap and Charge retention.
His Non-volatile memory research incorporates themes from Universal memory and Dram.
Between 2009 and 2017, his most popular works were:
- Nanocrystal based universal memory cells, and memory cells (35 citations)
- Lanthanide dielectric with controlled interfaces (22 citations)
- Memory cells containing charge-trapping zones (21 citations)
In his most recent research, the most cited papers focused on:
- Semiconductor
- Electrical engineering
- Integrated circuit
Optoelectronics, Dielectric, Electronic systems, Charge and Memory cell are his primary areas of study.
His primary area of study in Optoelectronics is in the field of Silicon.
His work deals with themes such as Dynamic random-access memory, Chemical engineering and Parallel computing, which intersect with Dielectric.
Throughout his Electronic systems studies, Arup Bhattacharyya incorporates elements of other sciences such as High-κ dielectric, Metal electrodes, Aluminum oxynitride, Monolayer and Atomic layer deposition.
His Charge studies intersect with other subjects such as Nanodot, Optics, Blocking, Electrical engineering and Erasure.
His research integrates issues of Dram, Nanocrystal, Non-volatile memory, Universal memory and Quantum tunnelling in his study of Memory cell.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
