Semiconductor RRAM Memory Technology to Mimic Biological Neuron
Professor: Prof Sandip Mondal
UID: EE01
Neuromorphic Memory Devices for Artificial Intelligence
Professor: Prof Sandip Mondal
UID: EE02
Defects in Semiconductor Nanodevices
Professor: Prof Sandip Mondal
UID: EE03
Advanced Spin-coated Flash Memory
Professor: Prof Sandip Mondal
UID: EE04
Charge Injection Mechanism in Semiconductor Memory Devices
Professor: Prof Sandip Mondal
UID: EE05
Quantum Technology: Probing the Density of State Using Modulated
Charge Injection and Sensing Method
Professor: Prof Sandip Mondal
UID: EE06
Investigation of Extremely High Breakdown, on/off ratio in
AlGaN/GaN HEMT-on-Si with solution processed dielectric
Professor: Prof Sandip Mondal
UID: EE07
Bio-interface with Neuromorphic Devices
Professor: Prof Sandip Mondal
UID: EE08
Solid Oxide Fuel Cells (SOFC) for power generation
Professor: Prof Sandip Mondal
UID: EE09
Graphene based neuromorphic device for highly sensitive charge
measuring system
Professor: Prof Sandip Mondal
UID: EE10
Diabetes Detection and Curing Using Neuromorphic Chip
Professor: Prof Sandip Mondal
UID: EE11
Development of low-cost electrical resistivity imaging equipment
Professor: Anand Singh
UID: EE12
EE01
Description: Intelligence in the animal kingdom is
manifested over the vast length and time scales, spanning
neuronal levels in the brain to collective learning in social
colonies. The typical characteristic of the living neuro system
is the capability to learn from incidences and respond to their
atmosphere leading to habit formation and decision-making. This
learning behavior is common across all forms of life with a
dominant nervous system which is also detected in single-cell
organisms. This brings an experimental challenge to emulate the
memory, learning and information transfer resembling features in
solid-state memory technology and their implementation to
neuromorphic computing. In this project, we will use the
prototypical solidstate RRAM memory device architecture using
strongly correlated oxides to first illustrate the neuromorphic
system to emulation learning behaviour. We will then describe the
challenges in fabricating such solid-state memory technology and
measuring neural characteristics using a high-speed electronic
measurement system. In the latter part, we will investigate the
proposals for incorporating optics into the neuromorphic system
for learning.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE02
Description: Biological neural systems can learn and
forget information which is one possible mechanism for the
stability and lifelong learning of neural circuits. Emulating
such features in electronic devices is essential for advancing
neuromorphic electronics for Artificial Intelligence. In this
project, we will explore memory devices using oxides to
illustrate learning behavior. We will examine the transient
memory and forgetting dynamics by controlling the material’s
chemistry. Using examples of prototypical Mott insulators such
as NiO and VO2 and nanoparticles, we will present our vision for
a neuromorphic platform utilizing quantum materials. Our studies
will inform the design of electronic hardware in emerging
Artificial Intelligence and can in the future be extended to
brain-machine interfaces.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE03
Description: The revolutionary impact of advanced
semiconductor physics on our daily lives remains unabated. We
continually interact with computational, memory, and imaging
devices where a large number of electrons are pushed around
various defect states at every nanosecond inside semiconductors.
As these technologies are rapidly evolving from traditional
circuit boards to flexible electronics, new materials, physics,
and processing technologies are being explored to improve their
functionality and efficiency. This brings unique experimental
challenges to evaluate the fundamental interaction of defects
with electrons in novel semiconductors. In this project, we will
first design a prototypical MIS capacitive device architecture
to illustrate the electron trapping in memory devices fabricated
at low temperatures. Unlike the conventional the measurement
system, we will then focus on the challenges in measuring the
defect state in semiconductors and our approach to probing the
defect state during charge pumping operations
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE04
Description: The field of advanced spin-coated
electronics has rapidly expanded over the last few decades
towards the development of low-cost, large area and low power
consumer electronics such as system-on-panel, system-on-glass,
system-on-chip and see-through applications for wearable and
textile integrated devices, seamless and twistable systems, soft
skin systems, as well as roll-to-roll light-weight, transparent,
conformable, stretchable, and even biodegradable systems. The
essential electronic component of all these systems is the three
terminal floating gate flash memory thin film transistor (memory
TFT) which should be fabricated by a similar spin-coated
solution processing compatible technique. The first
demonstration of floating memory TFT by Kahng and Sze in 1967 on
transparent glass substrates utilized silicon nitride charge
storage layers deposited by sophisticated ultrahigh vacuum
technology. Since then, there has been intensive research on
silicon nitride technology. However this technology is
incompatible with the large area, flexible and low cost
electronics due to the process integration issue. Hence the
alternative challenge was taken on developing the solution
processed spin-coated memory TFT for sol-gel electronics.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE05
Description: Charge injection mechanism has to be
investigated in the two nonvolatile, semiconductor flash memory
devices using a high-speed capacitance-voltage (HSCV)
measurement system. The capacitance measurement process is fast
in terms of measurement speed such that it completes capturing the
entire CV curve in less than 10 µs. The system will be capable
of generating sequential pulsing sessions to inject the charges
into the defect states and simultaneously measuring the HSCV
curve.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
CPI eligibility criteria: 8
Prerequisites: none
Duration: 6 months
Learning outcome: Paper/ Patent
Weekly time commitment:20 hours
General expectations:
Assignment: http://www.sandipmondal.com
Instructions for assignment: Will be provided after
selection
EE06
Description: "The electrical characterization technique
to determine the effective density of states in semiconductor
nanoparticles without the interference of interface, surface
state. The state energies will be determined by modulating the
gate potential and injecting the charges to the specific quantum
state. The density of charge in the energy state is to be sensed
from the shift of flatband band voltage of the
capacitance-voltage curve in less than 2.5µs. The density of
state spectrum has to be measured for semiconductor CdTe quantum
nanoparticles with size."
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE07
Description: We will investigate AlGaN/GaN MOS HEMT with
solution processed spin coated dielectric which can demonstrate
a very high on/off ratio with three terminal breakdown voltages
of nearly 400V and negligible frequency dispersion in C-V
characteristics.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE08
Description: In this project, we will measure physical
characteristics such as heart rate, blood pressure, and diabetes
using the neuromorphic chip. This chip will be fabricated on a
flexible electronic substrate that can be directly implemented
in human beings.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE09
Description: Solid oxide fuel cells are one of the many
types of fuel cells and produce electricity, water, heat and
small amounts of carbon dioxide using natural gas as the fuel.
In this project, we will investigate how neuromorphic technology
can be used as a Fuel Cell for power generation.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE10
Description: Storing the charges in the material either
in semiconductor, dielectric, or conductors are important to
preserve the information for the future which caters to a
diverse range of applications from biomedical sensor to quantum
information processing. In-spite of extensive fundamental and
engineering progress, a unified design of charge sensors that
caters to this diversity is still absent. The technological
objective today is to determine the maximum amount of charges
present in the material due to the unavailability of
charge-sensing material.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE11
Description: Storing the charges in the material either
in semiconductor, dielectric, or conductors are important to
preserve the information for the future which caters to a
diverse range of applications from biomedical sensor to quantum
information processing. In-spite of extensive fundamental and
engineering progress, a unified design of charge sensors that
caters to this diversity is still absent. The technological
objective today is to determine the maximum amount of charges
present in the material due to the unavailability of
charge-sensing material.
Number of students: 3
Year of study: Students entering 2nd year, Students
entering 3rd year, Students entering 4th/5th year
Instructions for assignment: Will be provided after
selection
EE12
Description: "The use of electrical resistivity
tomography in laboratory or field experiments for geophysical
application purposes has been increasing in recent years.
However, their costs and lack of flexibility to adapt to
specific applications have limited their prevalence in
geophysical applications. This project involves developing a
low-cost, open hardware resistivity meter to provide the
scientific community with a robust and flexible tool for
small-scale experiments. The basic resistivity meter should have
features of current injection and measurement functions
associated with a multiplexer that allows performing automatic
measurements with up to 32 electrodes (at the cost of less than
INR 1 Lakh). More detail about the development can be found in
the work of Clement et al. 2020
(https://doi.org/10.1016/j.ohx.2020.e00122) "
Number of students: 2
Year of study: Students entering 3rd year, Students
entering 4th/5th year
CPI eligibility criteria: 8
Prerequisites: Electrical Engineering Department students
Duration: One year
Learning outcome: This project will benefit the student
immensely as it involves multi-disciplinary work. It will also
lead us to a paper/patent.
Weekly time commitment: 7-8 Hour
General expectations:
Assignment: The use of electrical resistivity tomography
in laboratory or field experiments for geophysical application
purposes has been increasing in recent years. However, their
costs and lack of flexibility to adapt to specific applications
have limited their prevalence in geophysical applications. This
project involves developing a low-cost, open hardware
resistivity meter to provide the scientific community with a
robust and flexible tool for small-scale experiments. The basic
resistivity meter should have features of current injection and
measurement functions associated with a multiplexer that allows
performing automatic measurements with up to 32 electrodes (at
the cost of less than INR 1 Lakh). More detail about the
development can be found in the work of Clement et al. 2020
(https://doi.org/10.1016/j.ohx.2020.e00122)
Instructions for assignment: More detail about the
development can be found in the work of Clement et al. 2020
(https://doi.org/10.1016/j.ohx.2020.e00122)