Sathish Marimuthu

About

I am a research scholar working to better understand how nanostructure devices work. I had a passion to research right from my school days. Curiosity to know Why and How things work led me to ask questions borne our of curiosity. I believe curiosity is the driving force behind the research.

My expertise includes device fabrication, data analysis, Machine Learning and interpretation, and the development and implementation of research tools. I enjoy generating new ideas and devising feasible solutions to broadly relevant problems.

Currently, I’m doing Ph.D (Physics) in VIT. Specific fields of interest include Energy Harvesting devices (Perovskite photovoltaics) & Energy storage devices.

Employment

• Bharathidasan University Masters project
  2019 - 2020
• Indira Gandhi Centre for Atomic Research Summer Research Fellow
  2019 - 2019

Education

• Bharathidasan University M.Sc
  2018 - 2020

Projects & Funding

Projects & funding information is unavailable.

Publications (14)

• Drift-diffusion modelling of ZnSe–TiO2 based photoanode for bifacial dye sensitised solar cells
  Nano Futures 2026 DOI: 10.1088/2399-1984/ae79bc
  +Save
• Design and synthesis of Ti3C2 and Ti3C2Tx MXenes for sensing, energy, and electromagnetic interference shielding: Advancing multifunctional applications with machine learning-assisted material design
  Advanced Sensor and Energy Materials 2026 DOI: 10.1016/j.asems.2026.100204
  +Save
• Operando Evaluation of NIR-Absorbing Squaraine Molecules for Dye-Sensitized Solar Cells: An Informatics-Driven Molecular Machine Learning Framework
  ACS Applied Energy Materials 2025 DOI: 10.1021/acsaem.5c01621
  +Save
• MXenes and its composite structures: synthesis, properties, applications, 3D/4D printing, and artificial intelligence; machine learning integration
  Progress in Materials Science 2025 DOI: 10.1016/j.pmatsci.2025.101433
  +Save
• Synthesis, properties, applications, 3D printing and machine learning of graphene quantum dots in polymer nanocomposites
  Progress in Materials Science 2024 DOI: 10.1016/j.pmatsci.2024.101282
  +Save
• Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets
  Chemical Engineering Journal 2024 DOI: 10.1016/j.cej.2024.149502
  +Save
• The dawn of MXene duo: revolutionizing perovskite solar cells with MXenes through computational and experimental methods
  Nanoscale 2024 DOI: 10.1039/D4NR01053A
  +Save
• Drift diffusion modelling of cell parameters effect on the performance of perovskite solar cells with MXene as additives
  Solar Energy 2023 DOI: 10.1016/j.solener.2023.111804
  +Save
• Ceramics for solid oxide fuel cells
  Advanced Ceramics for Energy Storage, Thermoelectrics and Photonics 2023 DOI: 10.1016/b978-0-323-90761-3.00006-1
  +Save
• DSSC to Perovskites – Overview
  Reference Module in Earth Systems and Environmental Sciences 2023 DOI: 10.1016/b978-0-323-93940-9.00099-2
  +Save