Francesca Tavazza

Publications

Uncertainty Quantification of Atomistic (DFT and MD), Mesoscale (PFM) and Continuum (CALPHAD) Methods and the Impact on Thermodynamic Models of Metals: A Review

March 5, 2021

Author(s)

Gabriel Joshua, Noah Paulson, Thien Duong, Francesca Tavazza, Chandler Becker, Santanu Chaudhuri, Stan Marious

Design of improved metals relies on multi-scale computer simulations to provide thermodynamic properties when experiments are difficult to conduct. In

Topological surface states of MnBi2Te4 at finite temperatures and at domain walls

February 24, 2021

Author(s)

Kevin F. Garrity, Sugata Chowdhury, Francesca Tavazza

MnBi2Te4 has recently been the subject of intensive study, due to the prediction of axion insulator, Weyl semimetal, and quantum anomalous Hall insulator phases

Examining Experimental Raman Mode Behavior in Mono- and Bilayer 2H-TaSe2 via Density Functional Theory: Implications for Quantum Information Science

February 16, 2021

Author(s)

Sugata Chowdhury, Heather M. Hill, Albert Rigosi, Andrew Briggs, Helmuth Berger, David Newell, Angela Hight Walker, Francesca Tavazza

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

November 12, 2020

Author(s)

Kamal Choudhary, Kevin Garrity, Andrew C. Reid, Brian DeCost, Adam Biacchi, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, Aaron Kusne, Andrea Centrone, Albert Davydov, Francesca Tavazza, Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, David Vanderbilt, Karin Rabe

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using

High-throughput Density Functional Perturbation Theory and Machine Learning Predictions of Infrared, Piezoelectric and Dielectric Responses

May 27, 2020

Author(s)

Kamal Choudhary, Kevin F. Garrity, Vinit Sharma, Adam J. Biacchi, Francesca M. Tavazza, Angela R. Hight Walker

In this work, combining high-throughput (HT) density functional perturbation theory and supervised machine learning approaches, we explored the territory of

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Francesca Tavazza (Fed)

Publications