Rampi Ramprasad

Research.com Recognitions

• 2020 - Fellow of the Materials Research Society For pioneering contributions to the computation, data- and informatics-guided design of materials, and the creation of machine-learning-based tools for on-demand instantaneous predictions of complex materials properties.

Overview

Best Publications

• Machine learning in materials informatics: recent applications and prospects

  Rampi Ramprasad;Rohit Batra;Ghanshyam Pilania;Ghanshyam Pilania;Arun Mannodi-Kanakkithodi

  1614
  Citations

• Machine Learning Force Fields: Construction, Validation, and Outlook

  V. Botu;R. Batra;J. Chapman;R. Ramprasad

  528
  Citations

• Pathways towards ferroelectricity in hafnia

  Tran Doan Huan;Vinit Sharma;George A. Rossetti;Rampi Ramprasad

  496
  Citations

• Machine learning bandgaps of double perovskites

  Ghanshyam Pilania;Arun Mannodi-Kanakkithodi;Blas Uberuaga;Rampi Ramprasad

  472
  Citations

• Mesoporous MoO 3- x Material as an Efficient Electrocatalyst for Hydrogen Evolution Reactions

  Zhu Luo;Ran Miao;Tran Doan Huan;Islam M. Mosa;Islam M. Mosa

  461
  Citations

• Polymer Genome: A Data-Powered Polymer Informatics Platform for Property Predictions

  Chiho Kim;Anand Chandrasekaran;Tran Doan Huan;Deya Das

  446
  Citations

• Adaptive machine learning framework to accelerate ab initio molecular dynamics

  Venkatesh Botu;Rampi Ramprasad

  437
  Citations

• Advanced polymeric dielectrics for high energy density applications

  Tran Doan Huan;Steve Boggs;Gilbert Teyssedre;Christian Laurent

  387
  Citations

• Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

  Arun Mannodi-Kanakkithodi;Ghanshyam Pilania;Tran Doan Huan;Turab Lookman

  383
  Citations

• Machine Learning in Materials Science

  Tim Mueller;Aaron Gilad Kusne;Rampi Ramprasad

  362
  Citations

• Rational design of all organic polymer dielectrics

  Vinit Sharma;Chenchen Wang;Robert G. Lorenzini;Rui Ma

  335
  Citations

• Emerging materials intelligence ecosystems propelled by machine learning

  Rohit Batra;Le Song;Rampi Ramprasad

  328
  Citations

• Solving the electronic structure problem with machine learning

  Anand Chandrasekaran;Deepak Kamal;Rohit Batra;Chiho Kim

  312
  Citations

• Physically informed artificial neural networks for atomistic modeling of materials.

  G. P. Purja Pun;R. Batra;R. Ramprasad;Y. Mishin

  301
  Citations

• Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers.

  Shruti Venkatram;Chiho Kim;Anand Chandrasekaran;Rampi Ramprasad

  238
  Citations

• A universal strategy for the creation of machine learning-based atomistic force fields

  Tran Doan Huan;Rohit Batra;James Chapman;Sridevi Krishnan

  237
  Citations

• Machine-learning predictions of polymer properties with Polymer Genome

  Huan Doan Tran;Chiho Kim;Lihua Chen;Anand Chandrasekaran

  234
  Citations

• Flexible Temperature-Invariant Polymer Dielectrics with Large Bandgap.

  Chao Wu;Ajinkya A. Deshmukh;Zongze Li;Lihua Chen

  231
  Citations

• Learning scheme to predict atomic forces and accelerate materials simulations

  V. Botu;R. Ramprasad

  227
  Citations

• Polymer informatics: Current status and critical next steps

  Lihua Chen;Ghanshyam Pilania;Rohit Batra;Tran Doan Huan

  217
  Citations

• Magnetic properties of metallic ferromagnetic nanoparticle composites

  R. Ramprasad;P. Zurcher;M. Petras;M. Miller

  214
  Citations

• Factors Favoring Ferroelectricity in Hafnia: A First-Principles Computational Study

  Rohit Batra;Tran Doan Huan;Jacob L. Jones;George Rossetti

  198
  Citations

• Scoping the polymer genome: A roadmap for rational polymer dielectrics design and beyond

  Arun Mannodi-Kanakkithodi;Arun Mannodi-Kanakkithodi;Anand Chandrasekaran;Chiho Kim;Tran Doan Huan

  175
  Citations

• Machine Learning and Materials Informatics: Recent Applications and Prospects

  Rampi Ramprasad;Rohit Batra;Ghanshyam Pilania;Arun Mannodi-Kanakkithodi

  10
  Citations