Computational Scientist
AT SCALE (Adaptive Tunability for Synthesis/Control via Autonomous Learning on Edge)
Computational Scientist
AT SCALE (Adaptive Tunability for Synthesis/Control via Autonomous Learning on Edge)

Biography

Ankit Roy is on the Adaptive Tunability for Synthesis/Control via Autonomous Learning on Edge (AT SCALE) team at Pacific Northwest National Laboratory (PNNL). He graduated with a PhD in mechanical engineering from Lehigh University in August 2021, and joined PNNL in September 2021. He works on Li-Al-O ceramics to model the radiation damage in them using molecular dynamics (MD). He is also working on modeling radiation damage in some titanium (Ti) alloys using molecular dynamics. As a part of this doctoral research, Roy used density-functional theory (DFT), MD, and machine learning to explore mechanical and chemical properties of high entropy alloys (HEAs).

Research Interest

  • Computational materials science
  • Molecular dynamics
  • Density-functional theory (DFT)
  • Machine learning as applied to materials science
  • Interest in experiments involving:
    • X-ray diffraction (XRD)
    • Mechanical testing
    • Alloy synthesis by arc melting
    • Open to learning and trying new computational and experimental domains in material science.

Education

PhD in mechanical engineering and mechanics, Lehigh University, 2021

ME in power engineering, Jadavpur University, India, 2018

BE in mechanical engineering, MS Ramaiah Institute of Technology, India, 2014

Awards and Recognitions

  • Peer reviewer: Nature Communications (2022), Scientific Reports (2022), Scripta Materialia (2022), Journal of Molecular Modeling (2022), Metals (2022), Physical Chemistry Chemical Physics (2021), Advanced Engineering Materials (2021)
  • Invited reviewer, IEEE Global Humanitarian Technology Conference, 2022
  • Data visualization high school mentoring, Delta High School, Washington, 2022
  • Best PhD dissertation award, Department of Mechanical Engineering and Mechanics, Lehigh University, 2022
  • Full scholarship, 13th Annual Modeling, Experimentation, and Validation Summer School, Oak Ridge National Laboratory, 2022
  • Award for Paper, Acta Students Awards, Acta Materialia, Inc., July, 2021
  • Intern, Ames National Laboratory, National Science Foundation, 2021
  • Doctoral Fellowship for Teaching and Professoriate Excellence, P.C. Rossin College of Engineering and Applied Science, Lehigh University, 2019-2020
  • Cohort, Creative Scholarship Institute, Lehigh University, 2019-2020
  • Teaching Fellowship, P.C. Rossin College of Engineering and Applied Science, Lehigh University, 2018-2019

Publications

2022

  • Roy, A., P. Singh, G. Balasubramanian, and D. D. Johnson. 2022. "Vacancy Formation Energies and Migration Barriers in Multi-principal Element Alloys." Acta Materialia 226: 117611, 1-9.
  • Roy, A., M. F. N. Taufique, H. Khakurel, R. Devanathan, D. D. Johnson, and G. Balasubramanian. 2022. "Machine-learning-guided Descriptor Selection for Predicting Corrosion Resistance in Multi-principal Element Alloys." npj Materials Degradation 6: 1-10.
  • Roy, A., R. Devanathan, D. D. Johnson, and G. Balasubramanian. 2022. "Grain-size Effects on the Deformation in Nanocrystalline Multi-principal Element Alloy." Materials Chemistry and Physics 277: 125546.
  • Roy, A., I. Roy, L. J. Santodonato, and G. Balasubramanian. 2022. "Data-Guided Feature Identification for Predicting Specific Heat of Multicomponent Alloys." JOM: 1-8.

2021

  • Sreeramagiri, P., A. Roy, and G. Balasubramanian. 2021. "Effect of Cooling Rate on the Phase Formation of AlCoCrFeNi High-entropy Alloy." Journal of Phase Equilibria and Diffusion 42 (5): 772-780.
  • Khakurel, H., M. F. N. Taufique, A. Roy, G. Balasubramanian, G. Ouyang, J. Cui, D. D. Johnson, and R. Devanathan. 2021. "Machine Learning Assisted Prediction of the Youngs Modulus of Compositionally Complex Alloys." Scientific Reports 11 (1): 1-10.
  • Munshi, J., A. Roy, S. Hansen, C. E. Ekuma, and G. Balasubramanian. 2021. "Effect of Vacancy Defects on the Thermal Transport of -Ga2O3." Molecular Simulation 47 (12): 1017-1021.
  • Roy, A. and G. Balasubramanian. 2021. "Predictive Descriptors in Machine Learning and Data-enabled Explorations of High-entropy Alloys." Computational Materials Science 193: 110381.
  • Roy, A., J. Munshi, and G. Balasubramanian. 2021. "Low Energy Atomic Traps Sluggardize the Diffusion in Compositionally Complex Refractory Alloys." Intermetallics 131: 107106 (1-6).
  • Roy, A., P. Sreeramagiri, T. Babuska, B. Krick, P. K. Ray, and G. Balasubramanian. 2021. "Lattice Distortion as an Estimator of Solid Solution Strengthening in High-entropy Alloys." Materials Characterization 172: 110877 (1-10).

2020

  • Sarkar, S., T. Roy, A. Roy, S. Moitra, R. Ganguly, and C. M. Megaridis. 2020. "Revisiting the Supplementary Relationship of Dynamic Contact Angles Measured by Sessile-droplet and Captive-bubble Methods: Role of Surface Roughness." Journal of Colloid and Interface Science 581: 690-697.
  • Gianelle, M., A. Kundu, K. P. Anderson, A. Roy, G. Balasubramanian, H. Chan. 2020. "A Novel Ceramic Derived Processing Route for Multi-Principal Element Alloys." Materials Science and Engineering: A. 793: 139892 (1-6).
  • Roy, A., T. Babuska, B. Krick, and G. Balasubramanian. 2020. "Machine Learned Feature Identification for Predicting Phase and Youngs Modulus of Low, Medium and High Entropy Alloys." Scripta Materialia 185: 152-158.

Prior to 2020

  • Rickman, J., H. Chan, M. Harmer, J. Smeltzer, C. Marvel, A. Roy, and G. Balasubramanian. 2019. "Materials Informatics for the Screening of Multi-Principal Elements and High-Entropy Alloys." Nature Communications 10(1): 1-10.
  • Gupta, R., C. Das, A. Roy, R. Ganguly, and A. Datta. 2018. "Arduino Based Temperature and Humidity Control for Condensation on Wettability Engineered Surfaces." Emerging Trends in Electronic Devices and Computational Techniques (EDCT): 1-6.

Currently under review

  • Roy, A., A. M. Casella, D. J. Senor, and R. Devanathan. "Comparison of Lithium Diffusion in -LiAlO2 and LiAl5O8 Using Molecular Dynamics Simulations." Journal of Nuclear Materials, under review.