DEM/CFD-DEM Modelling of Non-spherical Particulate Systems: Theoretical Developments and Applications

The performance of current microfluidic methods for exosome detection is constrained by boundary conditions, as well as fundamental limits to microscale mass transfer and interfacial exosome binding. Here, we show that a microfluidic chip designed with self-assembled three-dimensional herringbone nanopatterns can detect low levels of tumour-associated exosomes in plasma (10 exosomes μl−1, or approximately 200 vesicles per 20 μl of spiked sample) that would otherwise be undetectable by standard microfluidic systems for biosensing. The nanopatterns promote microscale mass transfer, increase surface area and probe density to enhance the efficiency and speed of exosome binding, and permit drainage of the boundary fluid to reduce near-surface hydrodynamic resistance, thus promoting particle–surface interactions for exosome binding. We used the device for the detection—in 2 μl plasma samples from 20 ovarian cancer patients and 10 age-matched controls—of exosome subpopulations expressing CD24, epithelial cell adhesion molecule and folate receptor alpha proteins, and suggest exosomal folate receptor alpha as a potential biomarker for early detection and progression monitoring of ovarian cancer. The nanolithography-free nanopatterned device should facilitate the use of liquid biopsies for cancer diagnosis. A microfluidic chip with self-assembled 3D herringbone nanopatterns detects, with high sensitivity and specificity, tumour-associated exosomes in few-microlitre plasma samples from patients.

/pdf/ultrasensitive-detection-of-circulating-exosomes-with-a-3d-56sjjlov7f.pdf

Ultrasensitive detection of circulating exosomes with a 3D-nanopatterned microfluidic chip.

https://pubs.rsc.org/en/content/articlepdf/2020/GC/D0GC00096E

Spherical lignin particles : a review on their sustainability and applications

Particle shape effects on fabric of granular random packing

Boosting the supercapacitor performances of activated carbon with carbon nanomaterials

Numerical simulation results show that the upper bound order of random packing densities of basic 3D objects is cube (0.78) > ellipsoid (0.74) > cylinder (0.72) > spherocylinder (0.69) > tetrahedron (0.68) > cone (0.67) > sphere (0.64), while the upper bound order of ordered packing densities of basic 3D objects is cube (1.0) > cylinder and spherocylinder (0.9069) > cone (0.7854) > tetrahedron (0.7820) > ellipsoid (0.7707) > sphere (0.7405); these two orders are significantly different. The random packing densities of ellipsoid, cylinder, spherocylinder, tetrahedron and cone are closely related to their shapes. The optimal aspect ratios of these objects which give the highest packing densities are ellipsoid (axes ratio = 0.8:1:1.25), cylinder (height/diameter = 0.9), spherocylinder (height of cylinder part/diameter = 0.35), tetrahedron (regular tetrahedron) and cone (height/bottom diameter = 0.8).

Maximum packing densities of basic 3D objects

Shape and size effects on the packing density of binary spherocylinders

Packing properties of binary mixtures in disordered sphere systems

Sphericities of non-spherical objects

Random packings of binary mixtures of spheres and spherocylinders with the same volume and the same diameter were simulated by a sphere assembly model and relaxation algorithm. Simulation results show that, independently of the component volume fraction, the mixture packing density increases and then decreases with the growth of the aspect ratio of spherocylinders, and the packing density reaches its maximum at the aspect ratio of 0.35. With the same volume particles, results show that the dependence of the mixture packing density on the volume fraction of spherocylinders is approximately linear. With the same diameter particles, the relationship between the mixture packing density and component volume fraction is also roughly linear for short spherocylinders, but when the aspect ratio of spherocylinders is greater than 1.6, the curves turn convex which means the packing of the mixture can be denser than either the sphere or spherocylinder packing alone. To validate the sphere assembly model and relaxation algorithm, binary mixtures of spheres and random packings of spherocylinders were also simulated. Simulation results show the packing densities of sphere mixtures agree with previous prediction models and the results of spherocylinders correspond with the simulation results in literature.

A computational investigation on random packings of sphere-spherocylinder mixtures

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