What is he best known for?
The fields of study he is best known for:
- Polymer
- Organic chemistry
- Enzyme
Srinivasa R. Raghavan mainly investigates Micelle, Rheology, Pulmonary surfactant, Viscosity and Organic chemistry.
The concepts of his Micelle study are interwoven with issues in Amphiphile and Small-angle neutron scattering.
He interconnects Fumed silica, Polymer nanocomposite, Viscoelasticity and Polystyrene in the investigation of issues within Rheology.
The study incorporates disciplines such as Light scattering, Cationic polymerization, Vesicle and Neutron scattering in addition to Pulmonary surfactant.
His work investigates the relationship between Vesicle and topics such as Bilayer that intersect with problems in Polymer.
His Viscosity research incorporates themes from Micellar solutions, Inorganic chemistry, Chromatography, Salt and Aqueous solution.
His most cited work include:
- Flame retardant mechanism of polyamide 6–clay nanocomposites ☆ (380 citations)
- Highly Viscoelastic Wormlike Micellar Solutions Formed by Cationic Surfactants with Long Unsaturated Tails (334 citations)
- Rheology of Silica Dispersions in Organic Liquids: New Evidence for Solvation Forces Dictated by Hydrogen Bonding (319 citations)
What are the main themes of his work throughout his whole career to date?
Srinivasa R. Raghavan mainly focuses on Polymer, Micelle, Nanotechnology, Pulmonary surfactant and Rheology.
His Polymer research includes themes of Self-healing hydrogels and Polymer chemistry.
His Micelle research focuses on Viscosity and how it relates to Inorganic chemistry.
His work deals with themes such as Light scattering, Small-angle neutron scattering, Neutron scattering, Chromatography and Cationic polymerization, which intersect with Pulmonary surfactant.
His Rheology course of study focuses on Colloid and Dispersion.
Within one scientific family, Srinivasa R. Raghavan focuses on topics pertaining to Lecithin under Organic chemistry, and may sometimes address concerns connected to Phosphatidylcholine.
He most often published in these fields:
- Polymer (23.11%)
- Micelle (21.01%)
- Nanotechnology (18.49%)
What were the highlights of his more recent work (between 2016-2021)?
- Polymer (23.11%)
- Biopolymer (13.87%)
- Nanotechnology (18.49%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Polymer, Biopolymer, Nanotechnology, Rheology and Micelle.
As part of his studies on Polymer, he frequently links adjacent subjects like Aqueous solution.
His Nanotechnology study incorporates themes from Composite number, Oxide and Porosity.
His Rheology research is multidisciplinary, incorporating perspectives in Chemical physics, Relaxation, Work, Neutron scattering and Viscosity.
His biological study spans a wide range of topics, including Cationic polymerization, Polymer chemistry, Rheometry, Reptation and Pulmonary surfactant.
His Pulmonary surfactant research includes elements of Mesophase, Drop, Lamellar structure, Surface tension and Small-angle neutron scattering.
Between 2016 and 2021, his most popular works were:
- Extrusion‐Based 3D Printing of Hierarchically Porous Advanced Battery Electrodes (97 citations)
- Liposomes: Clinical Applications and Potential for Image-Guided Drug Delivery. (80 citations)
- High-Fluorinated Electrolytes for Li–S Batteries (64 citations)
In his most recent research, the most cited papers focused on:
- Polymer
- Organic chemistry
- Enzyme
Srinivasa R. Raghavan mostly deals with Polymer, Nanotechnology, Electrolyte, Micelle and Pulmonary surfactant.
His Polymer study integrates concerns from other disciplines, such as Layer thickness, Resilience and Core.
His Nanotechnology research integrates issues from Porosity and Shell.
His research integrates issues of Electrochemistry and Anode in his study of Electrolyte.
His study in Micelle is interdisciplinary in nature, drawing from both Self-assembly, Cationic polymerization, Rheology and Polyacrylamide.
His Pulmonary surfactant study combines topics from a wide range of disciplines, such as Persistence length, Viscosity, Polymer chemistry and Neutron scattering.
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.
