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researcher

N. Krishnan

10 papers hereh-index 322.9k citations98 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author8

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cond-mat.mtrl-sci6
  • cs.CL1
  • cs.DL1
  • physics.comp-ph1
  • physics.optics1
same name
  • N. Krishnan — 7 papers, h 12
  • N. Krishnan — 6 papers, h 4
  • N. Krishnan — 3 papers, h 4
  • N. Krishnan — 3 papers, h 3
  • N. Krishnan — 2 papers, h 2
  • N. Krishnan — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172022
most citedCooling-Rate Effects in Sodium Silicate Glasses: Bridging the Gap between Molecular Dynamics Simulations and Experiments

162 citations · 183 across the 9 of their papers we have counts for

collaborators
Showing 2019Show all

3 papers · 1 filter

cond-mat.mtrl-sci2019★ 5 cited

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…

cond-mat.mtrl-sci2019★ 1 cited

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…

cond-mat.mtrl-sci2019

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…

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