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20182020
most citedMachine Learning in Materials Modeling -- Fundamentals and the Opportunities in 2D Materials

1 citations · 1 across the 3 of their papers we have counts for

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cond-mat.mtrl-sci20201 cited

Machine Learning in Materials Modeling -- Fundamentals and the Opportunities in 2D Materials

Shreeja Das, Hansraj Pegu, Kisor Sahu +4

The application of machine learning in materials presents a unique challenge of dealing with scarce and varied materials data - both experimental and theoretical. Nevertheless, sev…

cond-mat.mtrl-sci2020

Comprehensive understanding of water-driven graphene wrinkle life-cycle towards applications in flexible electronics: A computational study

Jatin Kashyap, Eui-Hyeok Yang, Dibakar Datta

The presence of wrinkles in Graphene Nanoribbons (GNR) and other two-dimensional (2D) materials significantly alter their mechanical, electronic, optical properties, which can be e…

cond-mat.mtrl-sci2018

The Inherent Behavior of Graphene Flakes in Water: A Molecular Dynamics Study

Priyanka Solanky, Vidushi Sharma, Kamalika Ghatak +2

Graphene-water interaction has been under scrutiny ever since graphene discovery and realization of its exceptional properties. Several computational and experimental reports exist…

cond-mat.mtrl-sci2018

Effect of Cobalt Content on the Electrochemical Properties and Structural Stability of NCA Type Cathode Materials

Kamalika Ghatak, Swastik Basu, Tridip Das +2

At present, the most common type of cathode materials, NCA [Li_(1-x)Ni_(0.80)Co_(0.15)Al_(0.05)O_(2), x = 0 to 1], have a very high concentration of cobalt. Since cobalt is toxic a…

cond-mat.mtrl-sci2018

Amorphous Germanium as a Promising Anode Material for Sodium Ion Batteries: A First Principle Study

Vidushi Sharma, Kamalika Ghatak, Dibakar Datta

The abundance of Sodium (Na), its low-cost, and low reduction potential provide a lucrative inexpensive, safe, and environmentally benign alternative to Lithium Ion Batteries (LIBs…