Results 11 to 20 of about 66,497 (248)

Polydisperse packings [PDF]

open access: yesBrazilian Journal of Physics, 2003
The manufacture of high resistance concrete or hard ceramics needs extremely dense granular packings. They can only be realised when the size distribution of grains is strongly polydisperse. Typically powerlaw distributions give the best results. We present a simple packing model for polydisperse distributions, namely a generalized reversible parking ...
Herrmann, H.J.   +2 more
openaire   +3 more sources

Polydisperse lattice-gas model [PDF]

open access: yesPhysical Review E, 2008
We describe a lattice-gas model suitable for studying the generic effects of polydispersity on liquid-vapor phase equilibria. Using Monte Carlo simulation methods tailored for the accurate determination of phase behaviour under conditions of fixed polydispersity, we trace the cloud and shadow curves for a particular Schulz distribution of the ...
Wilding, N B, Sollich, P, Buzzacchi, M
openaire   +4 more sources

Modelling Thermal Conduction in Polydispersed and Sintered Nanoparticle Aggregates

open access: yesNanomaterials, 2021
Nanoparticle aggregation has been found to be crucial for the thermal properties of nanofluids and their performance as heating or cooling agents. Most relevant studies in the literature consider particles of uniform size with point contact only.
Nikolaos P. Karagiannakis   +2 more
doaj   +1 more source

Rheological Characterization of a Concentrated Phosphate Slurry

open access: yesFluids, 2021
Phosphate ore slurry is a suspension of insoluble particles of phosphate rock, the primary raw material for fertilizer and phosphoric acid, in a continuous phase of water. This suspension has a non-Newtonian flow behavior and exhibits yield stress as the
Souhail Maazioui   +4 more
doaj   +1 more source

Effects of Polydispersity on the Phase Behavior of Additive Hard Spheres in Solution

open access: yesMolecules, 2021
The ability to separate enzymes, nucleic acids, cells, and viruses is an important asset in life sciences. This can be realised by using their spontaneous asymmetric partitioning over two macromolecular aqueous phases in equilibrium with one another ...
Luka Sturtewagen, Erik van der Linden
doaj   +1 more source

The influence of polydispersity and inhomogeneity on EXAFS of bimetallic catalysts [PDF]

open access: yes, 1995
The effect of polydispersity and inhomogeneity of supported bimetallic catalysts on the EXAFS analysis is investigated with some simple model calculations. These show that EXAFS is very insensitive to polydispersity.
Bazin, D.   +4 more
core   +2 more sources

Theoretically predicting the solubility of polydisperse polymers using Flory–Huggins theory

open access: yesJPhys Materials, 2023
Polydispersity affects physical properties of polymeric materials, such as solubility in solvents. Most biobased, synthetic, recycled, mixed, copolymerized, and self-assembled polymers vary in size and chemical structure.
Stijn H M van Leuken   +3 more
doaj   +1 more source

Magnetophoretic Equilibrium of a Polydisperse Ferrofluid

open access: yesNanomaterials, 2021
The equilibrium concentration distribution of magnetic nanoparticles in a nonuniform magnetic field is studied theoretically. A linear current-carrying wire is used as a source of a nonuniform field.
Andrey A. Kuznetsov, Ivan A. Podlesnykh
doaj   +1 more source

Granular column collapse: The role of particle size polydispersity on the velocity and runout [PDF]

open access: yesE3S Web of Conferences, 2023
Geophysical mass flows involve particles of different sizes, a property termed polydispersity. The granular column collapse is a simplified experiment for studying transitional granular flows.
Polanía Oscar   +4 more
doaj   +1 more source

How can polydispersity information be integrated in the QSPR modeling of mechanical properties?

open access: yesScience and Technology of Advanced Materials: Methods, 2022
Polymer informatics is an emerging discipline that has benefited from the strong development that data science has experienced over the last decade. Machine learning methods are useful to infer QSPR (Quantitative Structure-Property Relationships) models ...
F. Cravero   +4 more
doaj   +1 more source

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