Muratahan Aykol

Publication Activity (10 Years)

Years Active: 2020-2023
Publications (10 Years): 6

Top Topics

Statistical Mechanics

Disturbance Rejection

Weakly Supervised

Top Venues

J. Open Source Softw.

Publications

Amil Merchant, Simon L. Batzner, Samuel S. Schoenholz, Muratahan Aykol, Gowoon Cheon, Ekin Dogus Cubuk
Scaling deep learning for materials discovery. Nat. 624 (7990) (2023)
Muratahan Aykol, Amil Merchant, Simon L. Batzner, Jennifer N. Wei, Ekin Dogus Cubuk
Predicting emergence of crystals from amorphous matter with deep learning. CoRR (2023)
Gregory H. Teichert, Sambit Das, Muratahan Aykol, Chirranjeevi Balaji Gopal, Vikram Gavini, Krishna C. Garikipati
phase stability studied by machine learning-enabled scale bridging between electronic structure, statistical mechanics and phase field theories. CoRR (2021)
Roni Choudhury, Muratahan Aykol, Samuel Gratzl, Joseph Montoya, Jens S. Hummelshøj
MaterialNet: A web-based graph explorer for materials science data. J. Open Source Softw. 5 (47) (2020)
Peter M. Attia, Aditya Grover, Norman Jin, Kristen A. Severson, Todor M. Markov, Yang-Hung Liao, Michael H. Chen, Bryan Cheong, Nicholas Perkins, Zi Yang, Patrick K. Herring, Muratahan Aykol, Stephen J. Harris, Richard D. Braatz, Stefano Ermon, William C. Chueh
Closed-loop optimization of fast-charging protocols for batteries with machine learning. Nat. 578 (7795) (2020)
Patrick K. Herring, Chirranjeevi Balaji Gopal, Muratahan Aykol, Joseph Montoya, Abraham Anapolsky, Peter M. Attia, William Gent, Jens S. Hummelshøj, Linda Hung, Ha-Kyung Kwon, Patrick Moore, Daniel Schweigert, Kristen A. Severson, Santosh Suram, Zi Yang, Richard D. Braatz, Brian D. Storey
BEEP: A Python library for Battery Evaluation and Early Prediction. SoftwareX 11 (2020)