162 citations · 227 across the 14 of their papers we have counts for
16 papers · 1 filter
On the Allowable or Forbidden Nature of Vapor-Deposited Glasses
Zhe Wang, Tao Du, N. M. Anoop Krishnan +2
Vapor deposition can yield glasses that are more stable than those obtained by the traditional melt-quenching route. However, it remains unclear whether vapor-deposited glasses are…
Deep Learning Aided Rational Design of Oxide Glasses
R. Ravinder, Karthikeya H. Sreedhara, Suresh Bishnoi +5
Despite the extensive usage of oxide glasses for a few millennia, the composition-property relationships in these materials still remain poorly understood. While empirical and phys…
Revealing the Atomic Structure of Silicate Glasses by Force-Enhanced Atomic Refinement
Qi Zhou, Tao Du, Lijie Guo +2
Although experiments can offer some fingerprints of the atomic structure of glasses (coordination numbers, pair distribution function, etc.), atomistic simulations are often requir…
Cooling Rate Effects on the Structure of 45S5 Bioglass: Computational and Experimental Evidence of Si--P Avoidance
Pratik Bhaskar, Yashasvi Maurya, Rajesh Kumar +10
Due to its ability to bond with living tissues upon dissolution, 45S5 bioglass and related compositions are promising materials for the replacement, regeneration, and repair of har…
Predicting Young's Modulus of Glasses with Sparse Datasets using Machine Learning
Suresh Bishnoi, Sourabh Singh, R. Ravinder +4
Machine learning (ML) methods are becoming popular tools for the prediction and design of novel materials. In particular, neural network (NN) is a promising ML method, which can be…
Machine Learning Forcefield for Silicate Glasses
Han Liu, Zipeng Fu, Yipeng Li +2
Developing accurate, transferable, and computationally-efficient interatomic forcefields is key to facilitate the modeling of silicate glasses. However, the high number of forcefie…