Kuntal Roy


Assistant Professor
Electrical Engineering and Computer Science (EECS) Department
Room No. 302, Academic Building - 1/Infinity
Indian Institute of Science Education and Research (IISER) Bhopal
Bhopal Bypass Road, Bhauri
Bhopal - 462 066, Madhya Pradesh, INDIA
Email: kuntal@iiserb.ac.in

Research Works @ Quantum NanoDevice Lab (QNDL)

Our group Quantum NanoDevice Lab (QNDL) performs various interesting and challenging interdisciplinary research on experimental, theretical, and computational fronts.

The research topics, but not limited to, are on the following.

Nanoelectronics

Quantum Computing

Energy Conversion

Nanoelectronics/Spintronics and Nanomagnetics

Electron's spin-based counterpart, so-called "Spintronics" exploits the quantum-mechanical spin of an electron to store, process, and communicate information. The 2007 Nobel Prize in Physics (awarded to Fert and Grunberg for the discovery of Giant Magnetoresistance in magnetic multilayers) recognizes the remarkable transition of spintronics from fundamental studies to a critical device technology. Spintronics has profound potential to be the replacement of current transistor-based technology in our future energy-efficient information processing systems. In fact, magnetic memories are being commercially manufactured for computers, cars, mission to Mars etc.

Although there is no Ohmic loss due to flow of charge in spintronic devices, unlike in charge-based transistors, the energy dissipation to switch magnetization in spintronic devices can be higher than that of transistors, if we use magnetic field or spin-polarized current to switch the spins. However, if we use electric field to switch the magnetization in strain-mediated piezoelectric-magnetostrictive multiferroic composites, with a suitable choice of materials and dimensions, the energy dissipation can be reduced to a miniscule amount of ~1 attojoule in sub-nanosecond switching delay at room-temperature [Switching up spin, Nature, Research Highlights (Physics) 476, 375 (25 Aug 2011)].

Also, an ongoing challenge in the field of multiferroic materials in single-phase is to understand new mechanisms and to realize new materials with correct parameters for application purposes, e.g., energy barrier for polarization/magnetization, room-temperature operation, damping. The giant spin-Hall effect and giant spin-orbit torque from the surface states of topological insulators (the 2016 Nobel Prize in Physics was awarded to Thouless, Haldane, and Kosterlitz for theoretical discoveries of topological phase transitions and topological phases of matter) are very active area of research globally now-a-days too.

On theory and simulation, Density Functional Theory (DFT) [the 1998 Nobel Prize in Chemistry, awarded to Kohn and Pople] based ab initio studies, spin transport using Non-Equilibrium Green Function (NEGF) formalism [which has been proved fruitful for demonstrating quantum effects in nanoscale], and stochastic Landau-Lifshitz-Gilbert (LLG) equation of magnetization dynamics [hand-written MATLAB code for critical understandings] can be utilized. On experimental side, for the fabrication of such spin-devices, it requires several state-of-the-art facilities e.g., Scanning Electron Microscope (SEM), Electron Beam Lithography (EBL), Vibrating Sample Magnetometer (VSM), Magnetic Force Microscopy (MFM), Pulsed laser deposition (PLD), E-Beam Evaporation.

This is an interdisciplinary field of research with different streams of science and engineering involved e.g., Electrical and Computer Engineering, Physics, Chemistry, Materials Science and Engineering, Nanoscale Science and Engineering. Some other research topics, but not limited to, are the following.

Quantum Computing/Quantum Machine Learning

Quantum computers directly utilize the quantum mechanical phenomena, e.g., superposition and entanglement. The basic idea of quantum information processing is that the superposition of huge number of wave functions can be manipulated in parallel, thereby achieving a massive speedup in computation compared to conventional computers. In fact, such quantum computers can be capable of cracking problems that are inaccessible to the most powerful classical computers in foreseeable future. The examples where quantum computation can be useful are determining two prime factors of a number and breaking a cryptographic key.

While a classical binary bit can have two allowed states, 0 and 1 (ON/OFF states of a transistor, UP/DOWN spins in a nanomagnet), a qubit, the phase information of a quantum state, can exist as arbitrary superpositions of 0 and 1. However, a qubit is extremely sensitive to environment, which is the major bottleneck behind the implementation of quantum computers. While a strong interaction is required between a qubit and the external field to manipulate the quantum states, it needs to switch off these interactions to maintain phase coherence during a computation, which are contradictory requirements. The 2012 Nobel Prize in Physics (awarded to Haroche and Wineland) recognizes the advancement of the field of quantum information processing.

Quantum mechanics is the most successful quantitative theory of nature that is not only the key to understanding physics behind all length scales, from elementary particles like electrons and quarks to gigantic objects like stars and galaxies, but also dictated the device physics behind modern technologies ranging from light-emitting diodes, lasers, solar cells and transistors to nuclear magnetic resonance and quantum computers. Over the past two decades, machine learning has progressed dramatically and many problems that were extremely challenging or even intractable to automated learning have now been solved. These successes clearly call forth new possibilities for machine learning to solve open problems in quantum physics. The purpose is to explore the open problems in quantum many-body physics for application in quantum machine learning and quantum computers.

Energy Conversion (Photovoltaics and Thermoelectrics)

The role of energy is very noteworthy - both the need to supply electrical energy to devices and the need to manage the dissipated energy in a chip. While the information-processing equipments consume a significant fraction of the total electricity production, the hotspots on a chip due to excessive energy dissipation causing system failure has posed a severe challenge to the continuing growth of electronics. While photovoltaic devices have promise to tackle the first issue, the dissipated heat on chips can be taken away by on-chip thermoelectric devices.

The 3rd generation solar cells exploiting the size quantization effects (e.g., phonon-bottleneck effects, multiple-excitation generation from a single photon) of low-dimensional structures (e.g., quantum wells, wires, dots) have shown promise of being simultaneously high-efficiency and low-cost. Also, with the advent of low-dimensional nanostructures, there have been a surge of radical efforts in constructing highly-efficient thermoelectric devices (the figure of merit, ZT > 3). Deeper understandings of charge and heat transport in nanostructures are the fundamental scientific challenges, which could facilitate in predicting materials for building thermoelectric devices suitable for our needs.

The spin-based counterparts for the energy conversion devices (e.g., using phot-spin-voltaic effect, spin Seebeck effect) are fundamentally intriguing and promising for technological applications too.

Low-dimensional Nanoelectronics

Carbon is an wonderful material that can form both two-dimensional structures (Graphene) and one-dimensional structures (carbon nanotube), which are promising candidates for electronics. While carbon nanotube field-effect transistors (CNT FETs) are being manufactured commercially for nanoelectronics, the (re)discovery of Graphene [the 2010 Nobel Prize in Physics, Geim and Novoselov] has gained world-wide endeavours for building electronics. However, Graphene is inherently a zero-bandgap semiconductor (OFF state leakage would be high), but its high speed of operation makes it suitable for applications in communications and RF electronics.

The emergence of two-dimensional van der waals materials and transitional metal dichalcogenides (e.g., MoS2, WS2) with energy band gaps have stimulated a lot of interests in the community for technological applications. Also, black phosphorus has recently joined the family. While the multilayers of semiconducting dichalcogenides possess an indirect bandgap (unlike the monolayer case), the bandgaps of black phosphorus is direct for all thicknesses and this is a benefit for optoelectronic applications. For transistor applications, the ON/OFF ratio, subthreshold swing, short-channel effects, mobility degradation at low thicknesses are important technological challenges.

Experimental

Theoretical/Computational