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Subramanian K. R. S. Sankaranarayanan

Subramanian K. R. S. Sankaranarayanan

D-Index & Metrics

Materials Science

D-Index
50
Citations
10117
World Ranking
10171
National Ranking
2439

Overview

Subramanian K. R. S. Sankaranarayanan is affiliated with the University of Illinois at Chicago in the United States. Their research spans multiple intersecting fields, with a focus on materials science and engineering. Key areas of study include materials chemistry, electrical and electronic engineering, molecular biology, atomic and molecular physics and optics, and biomedical engineering.

The scientist's work covers various advanced topics within materials science and related disciplines. Main research themes include machine learning applications in materials science, advanced memory and neural computing, diamond and carbon-based materials research, graphene research and applications, transition metal oxide nanomaterials, protein structure and dynamics, and computational drug discovery methods.

Frequent collaborators in their research include Sukriti Manna, Henry Chan, Troy D. Loeffler, Suvo Banik, and Mathew J. Cherukara. These collaborations have contributed to a substantial volume of research outputs across different venues.

Subramanian K. R. S. Sankaranarayanan has published extensively in well-known scientific journals and platforms. Frequent publication venues include:

  • arXiv (Cornell University)
  • Nature Communications
  • npj Computational Materials
  • Nano Letters
  • Zenodo (CERN European Organization for Nuclear Research)

Some of their recent notable papers are:

  • "Machine learning enabled autonomous microstructural characterization in 3D samples" (2020), published in npj Computational Materials
  • "High-Entropy 2D Carbide MXenes: TiVNbMoC 3 and TiVCrMoC 3" (2021), published in ACS Nano
  • "Reconfigurable perovskite nickelate electronics for artificial intelligence" (2022), published in Science
  • "Machine learning overcomes human bias in the discovery of self-assembling peptides" (2022), published in Nature Chemistry
  • "Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies" (2020), published in The Journal of Physical Chemistry Letters

Best Publications

  • Macroscale superlubricity enabled by graphene nanoscroll formation

    Diana Berman;Sanket A. Deshmukh;Subramanian K. R. S. Sankaranarayanan;Ali Erdemir

  • Carbon-based tribofilms from lubricating oils

    Ali Erdemir;Giovanni Ramirez;Osman L. Eryilmaz;Badri Narayanan

  • Machine learning enabled autonomous microstructural characterization in 3D samples

    Henry Chan;Mathew Cherukara;Troy D. Loeffler;Badri Narayanan;Badri Narayanan

  • High-Entropy 2D Carbide MXenes: TiVNbMoC 3 and TiVCrMoC 3

    Srinivasa Kartik Nemani;Bowen Zhang;Brian C. Wyatt;Zachary D. Hood

  • Extraordinary Macroscale Wear Resistance of One Atom Thick Graphene Layer

    Diana Berman;Sanket A. Deshmukh;Subramanian K. R. S. Sankaranarayanan;Ali Erdemir

  • Operando tribochemical formation of onion-like-carbon leads to macroscale superlubricity

    Diana Berman;Diana Berman;Badri Narayanan;Mathew J. Cherukara;Subramanian K. R. S. Sankaranarayanan

  • Reconfigurable perovskite nickelate electronics for artificial intelligence

    Unknown

  • Molecular dynamics simulation study of the melting of Pd-Pt nanoclusters

    Subramanian K. R. S. Sankaranarayanan;Venkat R. Bhethanabotla;Babu Joseph

  • Role of solvation dynamics and local ordering of water in inducing conformational transitions in poly(N-isopropylacrylamide) oligomers through the LCST.

    Sanket A. Deshmukh;Subramanian K. R. S. Sankaranarayanan;Kamlesh Suthar;Derrick C. Mancini

  • Perovskite nickelates as electric-field sensors in salt water

    Zhen Zhang;Derek Schwanz;Badri Narayanan;Michele Kotiuga

  • Crude-Oil-Repellent Membranes by Atomic Layer Deposition: Oxide Interface Engineering.

    Hao-Cheng Yang;Yunsong Xie;Henry Chan;Badri Narayanan

  • Machine Learning Force Field Parameters from Ab Initio Data

    Ying Li;Hui Li;Frank C. Pickard;Badri Narayanan

  • Quantitative 3D evolution of colloidal nanoparticle oxidation in solution

    Yugang Sun;Xiaobing Zuo;Subramanian K. R. S. Sankaranarayanan;Sheng Peng

  • Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data

    Henry Chan;Badri Narayanan;Badri Narayanan;Mathew J. Cherukara;Fatih G. Sen

  • Self-Improving Anode for Lithium-Ion Batteries Based on Amorphous to Cubic Phase Transition in TiO2 Nanotubes

    Hui Xiong;Handan Yildirim;Elena V. Shevchenko;Vitali B. Prakapenka

  • Trends in Na-Ion Solvation with Alkyl-Carbonate Electrolytes for Sodium-Ion Batteries: Insights from First-Principles Calculations

    Mehdi Shakourian-Fard;Ganesh Kamath;Kassiopeia Smith;Hui Xiong

  • Flow induced by acoustic streaming on surface-acoustic-wave devices and its application in biofouling removal: a computational study and comparisons to experiment.

    Subramanian K. R. S. Sankaranarayanan;Stefan Cular;Venkat R. Bhethanabotla;Babu Joseph

  • Habituation based synaptic plasticity and organismic learning in a quantum perovskite

    Fan Zuo;Priyadarshini Panda;Michele Kotiuga;Jiarui Li

  • Ab Initio-Based Bond Order Potential to Investigate Low Thermal Conductivity of Stanene Nanostructures.

    Mathew J. Cherukara;Badri Narayanan;Alper Kinaci;Kiran Sasikumar

  • Metal-induced rapid transformation of diamond into single and multilayer graphene on wafer scale

    Diana Berman;Sanket A. Deshmukh;Badri Narayanan;Subramanian K. R. S. Sankaranarayanan

  • High-Entropy 2D Carbide MXenes

    Nemani Sk;Zhang B;Wyatt Bc;Hood Zd

Frequent Co-Authors

Shriram Ramanathan
Shriram Ramanathan Rutgers, The State University of New Jersey
Maria K. Y. Chan
Maria K. Y. Chan Argonne National Laboratory
Fatih G. Sen
Fatih G. Sen Argonne National Laboratory
Stephen K. Gray
Stephen K. Gray Victoria University
Jeffrey Greeley
Jeffrey Greeley Purdue University West Lafayette
Hua Zhou
Hua Zhou Argonne National Laboratory
Anirudha V. Sumant
Anirudha V. Sumant Argonne National Laboratory
Kaushik Roy
Kaushik Roy Purdue University West Lafayette
Jianguo Wen
Jianguo Wen Argonne National Laboratory
Ali Erdemir
Ali Erdemir Texas A&M University

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