What is he best known for?
The fields of study he is best known for:
- Enzyme
- Organic chemistry
- Biochemistry
Brent S. Murray mainly investigates Chromatography, Emulsion, Rheology, Chemical engineering and Particle size.
The Chromatography study combines topics in areas such as Oil droplet, Zeta potential, Viscosity and Aqueous solution.
His research in Emulsion intersects with topics in Catechin, Polyphenol, Vegetable oil and Flavonoid.
His studies deal with areas such as Organic chemistry, Polymer science and Viscoelasticity as well as Rheology.
The concepts of his Chemical engineering study are interwoven with issues in Crystallography and Aqueous two-phase system.
His work carried out in the field of Particle size brings together such families of science as Pickering emulsion and Volume fraction.
His most cited work include:
- Modulation of the Degree and Pattern of Methyl-esterification of Pectic Homogalacturonan in Plant Cell Walls IMPLICATIONS FOR PECTIN METHYL ESTERASE ACTION, MATRIX PROPERTIES, AND CELL ADHESION (461 citations)
- Foam stability: proteins and nanoparticles (261 citations)
- Outstanding Stability of Particle-Stabilized Bubbles (241 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Chemical engineering, Chromatography, Emulsion, Rheology and Adsorption.
His work on Pulmonary surfactant as part of general Chemical engineering study is frequently linked to Coalescence, bridging the gap between disciplines.
His biological study spans a wide range of topics, including Pectin, Phase, Particle size, Casein and Viscoelasticity.
His Emulsion study combines topics from a wide range of disciplines, such as Flocculation and Whey protein.
His study looks at the relationship between Rheology and fields such as Microstructure, as well as how they intersect with chemical problems.
His Adsorption research includes elements of Crystallography, Molecule and Oil water.
He most often published in these fields:
- Chemical engineering (44.87%)
- Chromatography (32.05%)
- Emulsion (27.56%)
What were the highlights of his more recent work (between 2017-2021)?
- Chemical engineering (44.87%)
- Pickering emulsion (7.69%)
- Adsorption (20.51%)
In recent papers he was focusing on the following fields of study:
Chemical engineering, Pickering emulsion, Adsorption, Coalescence and Emulsion are his primary areas of study.
His research in Chemical engineering intersects with topics in Apparent viscosity, Viscosity, Shear thinning, Egg white and Aqueous solution.
His Apparent viscosity study improves the overall literature in Rheology.
The study incorporates disciplines such as Cellulose, Phase boundary, Sunflower oil and Polymer in addition to Adsorption.
His work deals with themes such as Polymer science and Starch, which intersect with Emulsion.
His study looks at the relationship between Biopolymer and topics such as Chromatography, which overlap with Particle size.
Between 2017 and 2021, his most popular works were:
- Pickering emulsions for food and drinks (41 citations)
- Emulsion Microgel Particles as High-Performance Bio-Lubricants. (35 citations)
- Water-In-Oil Pickering Emulsions Stabilized by Water-Insoluble Polyphenol Crystals (34 citations)
In his most recent research, the most cited papers focused on:
- Enzyme
- Organic chemistry
- Biochemistry
His main research concerns Chemical engineering, Pickering emulsion, Emulsion, Starch and Scanning electron microscope.
In the field of Chemical engineering, his study on Contact angle overlaps with subjects such as Oral cavity.
His Pickering emulsion research incorporates elements of Ionic strength, Optical microscope, Aspect ratio, Surface tension and Microstructure.
His Emulsion research includes themes of Cellulose, Polymer science, Desorption, Adsorption and Food components.
Brent S. Murray interconnects Lubrication, Polydimethylsiloxane, Emulsion droplet and Tribology in the investigation of issues within Starch.
His Scanning electron microscope research is multidisciplinary, incorporating perspectives in Brittleness and Bubble.
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.
