Abstract
Nanocomposite materials benefit from the diverse physicochemical properties featured by nanoparticles, and the presence of nanoparticle concentration gradients can lend functions to macroscopic materials beyond the realm of classical nanocomposites. It is shown here that linearity and time-shift invariance obtained via the synergism of two independent physical phenomena-translational self-diffusion and shear-driven dispersion-may give access to an exceptionally high degree of flexibility in the design of scalable and programmable long-range concentration gradients of nanoparticles in solidifiable liquid matrices.
Highlights
Nanocomposite materials benefit from the diverse physicochemical properties featured by nanoparticles, and the presence of nanoparticle exponential concentration gradients were generated when sedimentation and diffusion were in equilibrium at lower centrifconcentration gradients can lend functions to macroscopic materials beyond ugal forces.[13]
The history of functionally graded materials began far from 2) may be designed and tailored accurately by mathematical the realm of soft matter,[1,2,3] yet the emerging promise of bio- means, we present an approach dedicated to creating continmimicry, biomimetics, and eventually true bioinspiration,[4,5] uous and smooth long-range longitudinal concentration gradibrought the necessity to design and fabricate smooth mac- ents of NPs in macroscopic 1D soft materials, such as fibers
∑i Ai x (t,ωi ) where Ai > 0, provide limitless combinations of ∑ sine functions i Ai yi, and gives access to an exceptionally versatile particle-gradient design. While both the fundamental principles and arbitrary special cases can be captured with exact mathematical models, to demonstrate experimentally the full versatility of the design of particle gradients is well beyond the capacity of our current Taylor dispersion setup
Summary
Nanocomposite materials benefit from the diverse physicochemical properties featured by nanoparticles, and the presence of nanoparticle exponential concentration gradients were generated when sedimentation and diffusion were in equilibrium at lower centrifconcentration gradients can lend functions to macroscopic materials beyond ugal forces.[13]. This relationship means that the impulse response function h(t) describes completely the relationship between the input and output signals y(t), and by programming x(t), one can design and tailor y(t), which is the concentration gradient profile of the NPs. one can even reverse the order, i.e., for creating a given output y(t), one can find the required input x(t) via deconvolution, by using the convolution theorem.
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