• Publications
  • Influence
Dynamic strain loading of cubic to tetragonal martensites
Abstract We present three-dimensional simulations of the microstructure and mechanical response of shape memory alloys undergoing cubic to tetragonal transitions, using FePd as an example. TheExpand
  • 49
  • 7
Machine Learning Strategy for Accelerated Design of Polymer Dielectrics
TLDR
The ability to efficiently design new and advanced dielectric polymers is hampered by the lack of sufficient, reliable data on wide polymer chemical spaces, and the difficulty of generating such data given time and computational/experimental constraints. Expand
  • 147
  • 5
  • PDF
Accelerated search for materials with targeted properties by adaptive design
TLDR
We show how an adaptive design strategy, tightly coupled with experiments, can accelerate the discovery process by sequentially identifying the next experiments or calculations, to effectively navigate the complex search space. Expand
  • 246
  • 5
Adaptive Strategies for Materials Design using Uncertainties
TLDR
We compare several adaptive design strategies using a data set of 223 M2AX family of compounds for which the elastic properties [bulk (B), shear (G), and Young’s (E) modulus] have been computed using density functional theory. Expand
  • 100
  • 4
Multi-fidelity machine learning models for accurate bandgap predictions of solids
Abstract We present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model thatExpand
  • 102
  • 4
Information Science for Materials Discovery and Design
Introduction.- Data-Driven Discovery of Physical, Chemical, and Pharmaceutical Materials.- Cross-Validation and Inference in Bioinformatics/Cancer Genomics.- Applying MQSPRs - New Challenges andExpand
  • 62
  • 4
An informatics approach to transformation temperatures of NiTi-based shape memory alloys
The martensitic transformation serves as the basis for applications of shape memory alloys (SMAs). The ability to make rapid and accurate predictions of the transformation temperature of SMAs isExpand
  • 63
  • 4
  • PDF
Strain-induced metal–insulator phase coexistence in perovskite manganites
The coexistence of distinct metallic and insulating electronic phases within the same sample of a perovskite manganite, such as La1-x-yPryCaxMnO3, presents researchers with a tool for tuning theExpand
  • 405
  • 3
  • PDF
Machine learning bandgaps of double perovskites
TLDR
The ability to make rapid and accurate predictions on bandgaps of double perovskites is of much practical interest for a range of applications. Expand
  • 167
  • 3
  • PDF
How to generate high twin densities in nano-ferroics: Thermal quench and low temperature shear
High domain boundary densities in ferroic nano materials are generated in computer simulation studies by (1) fast quench from a para-elastic into a ferroelastic phase and (2) by shear of smallExpand
  • 32
  • 3
  • PDF