Soumyajit Samal

Email
soumyajits2000@gmail.com
Location

Bhubaneswar, Odisha, IN

About me

Hello! I am Soumyajit Samal, a 5th year Physics Majors at IISER Berhampur. I am currently doing my masters thesis on 2D Nanoelectronic Devices at TIFR. I also have a minors in Computer Science from IISER. Our civilization is strongly dependent on technology to aid its progress. For a long time now, sillicon serves as the backbone of the whatever-cutting-edge-device we use daily, be it our ipads to cars. Understanding the behavior of these materials at the atomic scale is very crucial to understand its bulk properties and hence manipulate them. I work with similiar 2D materials to simulate and fabricate them, to understand them better. These materials seem to have promising results for a wide paradigm from electrical implants inside the human body to some of the superfast devices on the planet.

Education

Ludwig-Maximilians-Universität München (LMU Munich), Germany
Starting September 2024
Doctor of Philosophy (PhD)
Advisor: Prof. Dmitri Efetov
Tata Institute of Fundamental Research(TIFR), Mumbai, IN
2023 — Present
Masters Thesis
Advisor: Prof. Mandar M. Deshmukh
Topic: Superconducting Waveguide Resonator-assisted Microwave Probing of 2D Materials

Indian Institute of Science Education and Research(IISER), Berhampur
2019 — Present
BS-MS
Majoring in Physical Sciences
Minoring in Computer Sciences

Activities: Finance and Tech Advisor, Ex-President of Jigyansa (A Science Communication Platform under IISER Berhampur and Vigyan Prasar)
Core Team Member of Naxatra (Astrocosmo Club)
Former Secretary and Tech Team Lead Innovation Incubation and Entrepreneurship Cell(IIEC)
Research Demonstrator STREAM (Open Day@IISERBPR)

DAV Public School, Pokhariput, Bhubaneswar
2018
Central Board of Secondary Education(CBSE), New Delhi
Subjects: Physics, Chemistry, Biology, Mathematics & English

DAV Public School, Pokhariput, Bhubaneswar
2016
Central Board of Secondary Education(CBSE), New Delhi
Subjects: Science, Mathematics, Odia, Social Science & English

What I do?

Physicist

I wrangle electrons through atomically thin sheets, hoping to unlock the secrets to better computers.
Illustration

From doodles to masterpieces, my illustrations have no boundaries.
Web development

A front-end finesse digital architect who thrives on the symphony of HTML, CSS & Javascript.
Technical Writing

With the precision of a scientist and the artistry of a wordsmith, I craft compelling narratives around intricate scientific phenomena.

Experience

Professional Skills

Nanofabrication of van der Waals heterostructures
90%
MATLAB
75%
Data Analysis and Representation
90%
Python
45%
Electron Beam Lithography
60%
Photolithography
60%
Team Management
90%
Machine Learning
35%
Microwave Simulations
20%

My Publications and Writings

Research Experience

Superconducting Coplanar Waveguide Resonator-assisted Microwave Probing of 2D Materials
(MS Thesis) Advisor: Prof. Mandar M. Deshmukh, Tata Institute of Fundamental Research (TIFR), Mumbai

The Moore's law states that number of transistors on a chip must double every two year. However using silicon as the material, we have reached the quantum limit beyond which we cannot scale the transistors down. The motivation for this project comes from the high contact resistance of monolayer TMDC to metal contacts which have proved their potential to revolutionise our modern transistors, theoritically! As a result majority of the work has been focussed on optical measurements of these devices. We propose a method to probe these type of materials and study their properties using RF. We are capacitively coupling our van der Waals heterostructure(Bilayer Graphene Stack) to a transmission line resonator and extracting its capacitance and density of states. The resonator operates in the 1-10GHz regime and has quality factor of about 500. This technique was also tested on other 2D heterostructures like twisted double bilayer graphene & twisted trilayer graphene and is seen to perform well. A part of the work was published in ACS Nanoletters.
Numerical Modelling and Simulation of DNA Detection using Graphene FETs
Advisor: Dr. Achanta Venugopal, Tata Institute of Fundamental Research (TIFR), Mumbai

This project focuses on simulating and analyzing DNA detection using Graphene Field-Effect Transistors (GFETs). Through computational modeling techniques, including Monte Carlo simulation and numerical methods, the behavior of GFETs in the presence of DNA molecules is explored. The project involves calculating the electrostatic potential distribution, determining the drain-source current (IDS), and visualizing the potential distribution and IDS-VG/IDS-VDS characteristics. The aim is to investigate the potential of GFETs for DNA sensing and gain insights into their behavior and performance. The following plot shows the voltage variation when a DNA molecule is detected. With approach of the molecule the potential on the surface appears distorted.
Describing wavefunction of nucleons inside a spherical nucleus
Advisor: Dr. Achanta Venugopal, Tata Institute of Fundamental Research (TIFR), Mumbai

A scientific study that involves solving and plotting wavefunctions for different values of principal quantum number. The study also includes finding the solutions of spherical bessel functions using the Newton Raphson method and plotting them. Furthermore, the code used in the study is modifiable for larger values of l and lower tolerances. This research provides valuable insight into the behavior of wavefunctions and the use of numerical methods in physics.
Determining the impact of dielectric environment on graphene properties by Deep Learning
Advisor: Prof. Radha Krishna & Dr. Gopi Krishna Guntupalli

As part of my scientific research, I conducted a study that focused on analyzing the Raman spectral data of graphene in different charge and dielectric environments. To augment the data, I applied additive noise and peak shifting techniques. I then implemented a convolutional neural network (CNN) to analyze the data, which resulted in an accuracy rate of 99%. Through this study, I gained valuable insights into the behavior of graphene under different conditions, and the effectiveness of CNN in analyzing Raman spectral data.
Determining Critical temperature of superconductors using ML
Advisor: Prof. Radha Krishna & Dr. Gopi Krishna Guntupalli

As part of my scientific research, I analyzed the superconductivity dataset from the SuperCon database. By plotting the correlation matrix, I found that thermal conductivity, valency, density, and other features are important in determining the critical temperature of a superconductor. In addition, I analyzed metals that attain superconductivity at higher temperatures. To further enhance the research, I developed a machine learning algorithm that predicts the critical temperature of a superconductor by analyzing these properties at room temperature. Through this study, I gained valuable insights into the properties of superconductors and the development of predictive algorithms for superconductivity research.
Review on usage of MXene based devices for Human Machine Interaction
Advisor: Dr. Kaushik Parida, IIT Rookee

I contributed to writing a review on MXene-based devices and how their utility can be enhanced through the use of machine learning techniques. In another project, I worked on piezoelectric and triboelectric devices and developed an algorithm that can classify different types of actions such as tapping, folding, and bending. Through these studies, I gained valuable insights into the application of machine learning in improving the functionality of devices and the classification of actions.
WiFi indoor navigation using Quantum Machine Learning
Advisor: Dr. Ahmed Farouk, Wilfrid Laurier University, Canada

I worked on a quantum simulation of a CML algorithm using Qiskit. In another project, I developed a model that could predict an individual's location within a large building using wifi access points that sweep the entire area. The insights gained from these studies could prove useful in predicting the aftermath of natural disasters on buildings.
Quantum Simulation of Graphene
Advisor: Prof. Prashanta Kumar Panigrahi, IISER Kolkata

I used the Variational Quantum Eigensolver algorithm and Qiskit Nature package. Through this work, I estimated the ground state and excited state energies for a graphene system. This study provided valuable insights into the application of quantum computing algorithms in the field of material science.
Methods of Preparation of graphene
Advisor: Dr. Pranat Jain, IISER Berhampur

Did a reading project on several methods of preparing graphene using top-down and bottom-up processes. I also discussed various methods that can enhance the yield of these processes. Through this study, I gained a deeper understanding of the methods and techniques involved in the preparation of graphene, and how they can be optimized to increase the yield.
Spam Detection using Quantum Tools
Advisor: Prof. Prashanta Kumar Panigrahi, IISER Kolkata

I designed a machine learning algorithm to filter spam mails using the IBMQ interface and a real-world 5-qubit quantum computer, IBM X2. The algorithm was designed to perform at its utmost performance even in noisy environments. Through this study, I gained valuable insights into the application of quantum computing in enhancing the performance of machine learning algorithms for real-world applications.
Fabrication of Microscale Metallic Contacts on Mechanically Exfoliated Graphene
Advisor: Dr. Satyaprakash Sahoo, Institute Of Physics, Bhubaneswar

As part of my research, I mechanically exfoliated graphene using the Scotch tape method. I then fabricated metallic contacts (Au, Ag, and Al) on the exfoliated graphene and observed the resulting structure using a Photo Lithography system. During the study, I tried several configurations with different circuit designs, varying thickness of photoresist (ma P 1205), and different photoresist cleaning processes. Through this study, I gained a deeper understanding of the processes involved in the fabrication of graphene-based electronic devices, and how various parameters can be optimized to improve their performance.