What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Mathematical analysis
- Composite material
His primary scientific interests are in Condensed matter physics, Composite material, Ferroelectricity, Martensite and Shape-memory alloy.
He interconnects Crystallography, Ceramic, Ferroelectric ceramics, Energy minimization and Ansatz in the investigation of issues within Condensed matter physics.
His studies deal with areas such as Dielectric and Crystallite as well as Composite material.
His Ferroelectricity research includes elements of Actuator, Hysteresis, Optics and Electrostriction.
His work carried out in the field of Martensite brings together such families of science as Geometry and Austenite.
His Shape-memory alloy research is classified as research in Metallurgy.
His most cited work include:
- Microstructure of martensite : why it forms and how it gives rise to the shape-memory effect (663 citations)
- Domain switching in polycrystalline ferroelectric ceramics. (294 citations)
- Crystal symmetry and the reversibility of martensitic transformations (237 citations)
What are the main themes of his work throughout his whole career to date?
Kaushik Bhattacharya spends much of his time researching Composite material, Condensed matter physics, Mechanics, Ferroelectricity and Shape-memory alloy.
As part of his studies on Composite material, Kaushik Bhattacharya frequently links adjacent subjects like Thin film.
His Condensed matter physics research is multidisciplinary, relying on both Crystallography, Ferroelectric ceramics, Optics and Martensite.
His Martensite research is multidisciplinary, incorporating elements of Slip, Phase and Plasticity.
The Ferroelectricity study combines topics in areas such as Polarization, Electric field, Electrostriction, Space charge and Barium titanate.
His research in Shape-memory alloy tackles topics such as Crystallite which are related to areas like Texture.
He most often published in these fields:
- Composite material (20.35%)
- Condensed matter physics (18.95%)
- Mechanics (12.28%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial neural network (2.81%)
- Composite material (20.35%)
- Partial differential equation (2.81%)
In recent papers he was focusing on the following fields of study:
Artificial neural network, Composite material, Partial differential equation, Condensed matter physics and Phase transition are his primary areas of study.
His study looks at the relationship between Artificial neural network and topics such as Discretization, which overlap with Deep learning and Artificial intelligence.
His study in the field of Line defects also crosses realms of Photovoltaic effect.
His work deals with themes such as Phase diagram, Nucleation, Elasticity, Polymer and Liquid crystal, which intersect with Phase transition.
Kaushik Bhattacharya interconnects Light intensity and Phase in the investigation of issues within Nucleation.
The concepts of his Composite number study are interwoven with issues in Compressive strength, Percolation, Conductivity, Electrical conductor and Microstructure.
Between 2018 and 2021, his most popular works were:
- Fourier Neural Operator for Parametric Partial Differential Equations (38 citations)
- Model Reduction and Neural Networks for Parametric PDEs (24 citations)
- Neural Operator: Graph Kernel Network for Partial Differential Equations (21 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Mathematical analysis
- Algebra
His scientific interests lie mostly in Artificial neural network, Discretization, Partial differential equation, Stress and Elastomer.
His Stress research is multidisciplinary, incorporating perspectives in Elastic modulus, Phase diagram, Condensed matter physics, Liquid crystal and Toughness.
Toughness is a subfield of Composite material that Kaushik Bhattacharya explores.
His research in Composite material intersects with topics in Percolation and Conductivity.
His Elastomer study combines topics from a wide range of disciplines, such as Phase transition, Perpendicular, Azobenzene, Liquid metal and Microstructure.
His studies deal with areas such as Mechanics, Plane stress, Plasticity and Nucleation as well as Fracture mechanics.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
