These guidelines suggest microscopy is the best choice for materials that exhibit high contrast, complex and heterogeneous shapes, low polydispersity, few three-dimensional particle clusters, considerable two-dimensional clusters, and constituent particle modal sizes.
These improvements in mechanical properties were accompanied by higher stiffness as well as considerable improvements in dimensional stability of the anodes and better creep characteristics.
It was observed by dynamic mechanical analysis, that the Tg, flow temperature (Tfl) and modulus of the rubbery plateau of PETA increased with increasing T2T content, implying a considerable improvement in the dimensional stability.
The aim of our trip was to use a strong X-ray to shoot the crystals of the T cell receptor (TCR) we had just managed to grow after considerable effort for three-dimensional structure determination.
Since point observations of subsurface materials and groundwater head are often the basis for modelling these complex, dynamic, three-dimensional systems, considerable uncertainties are inevitable, but are rarely assessed.
1 While certain computationally expensive techniques 2 can construct predictive models with considerable accuracy from high-dimensional data, reduction of these data prior to modeling is a separate problem that has received recent attention.
This approach for manufacturing GEM-like radiation imaging detectors allows for precise dimensional control and considerable geometrical design freedom.
Quantum dots (QDs) and other nanoobjects, where electrons are subjected to dimensional confinement, attract considerable interest of researchers and technologists because of their anticipated application in optoelectronics and quantum informatics [1 5].
Since carbon nanotubes (CNTs) possess unique one dimensional (1D) structure, considerable attention has been paid to constructing CNTs into macroscopic materials with different dimensions, including 1D fibers, 2D films, and 3D foams.
Network-based approaches have recently gained considerable popularity in high- dimensional regression settings.
