Hierarchically Structured Magnetic Nanoconstructs with Enhanced Relaxivity and Cooperative Tumor Accumulation

Iron oxide nanoparticles are formidable multifunctional systems capable of contrast enhancement in magnetic resonance imaging, guidance under remote fields, heat generation, and biodegradation. Yet, this potential is underutilized in that each function manifests at different nanoparticle sizes. Here, sub‐micrometer discoidal magnetic nanoconstructs are realized by confining 5 nm ultra‐small super‐paramagnetic iron oxide nanoparticles (USPIOs) within two different mesoporous structures, made out of silicon and polymers. These nanoconstructs exhibit transversal relaxivities up to ≈10 times (r ₂ ≈ 835 mm ^?1 s^?1) higher than conventional USPIOs and, under external magnetic fields, collectively cooperate to amplify tumor accumulation. The boost in r ₂ relaxivity arises from the formation of mesoscopic USPIO clusters within the porous matrix, inducing a local reduction in water molecule mobility as demonstrated via molecular dynamics simulations. The cooperative accumulation under static magnetic field derives from the large amount of iron that can be loaded per nanoconstuct (up to ≈65 fg) and the consequential generation of significant inter‐particle magnetic dipole interactions. In tumor bearing mice, the silicon‐based nanoconstructs provide MRI contrast enhancement at much smaller doses of iron (≈0.5 mg of Fe kg^?1 animal) as compared to current practice.     

Reconstruction and modeling of 3D percolation networks of carbon fillers in a polymer matrix

In the present work, we illustrate a methodology for the reconstruction and modeling of three-dimensional micro-structures of highly anisotropic composite materials. Specifically, we focus on disk-shaped nano-fillers dispersed in a polymer matrix and detailed numerical investigations, based on the lattice Boltzmann method (LBM), are carried out on the global thermal conductivity.     

Enhancing surface heat transfer by carbon nanofins: towards an alternative to nanofluids?

Background  

Nanofluids are suspensions of nanoparticles and fibers which have recently attracted much attention because of their superior thermal properties. Nevertheless, it was proven that, due to modest dispersion of nanoparticles, such high expectations often remain unmet. In this article, by introducing the notion of nanofin, a possible solution is envisioned, where nanostructures with high aspect-ratio are sparsely attached to a solid surface (to avoid a significant disturbance on the fluid dynamic structures), and act as efficient thermal bridges within the boundary layer. As a result, particles are only needed in a small region of the fluid, while dispersion can be controlled in advance through design and manufacturing processes.     

Convective Heat Transfer Enhancement for Electronic Device Applications Using Patterned MWCNTs Structures

This article reports on the heat transfer characteristics of columnar, vertically aligned, multiwall carbon nanotubes grown on a patterned Si surface. In the first part, we describe the procedure for patterning the silicon (Si) surface and the growth of multiwall carbon nanotubes (MWCNTs) on these patterned surfaces. The diameter of MWCNTs grown by chemical vapor deposition technique was in the range of 30–80 nm. In the second part, structures mimicking macroscopic finned heat sinks are used for enhancing forced convective heat transfer on a silicon substrate. Convective heat transfer coefficient has been experimentally measured for silicon substrates with and without MWCNT-based fins on it. The configuration with MWCNTs based fins shows an enhancement in convective heat transfer of 40% and 20%, as maximum and average value, respectively, compared to the bare silicon. Experiments have been carried out in a wind tunnel with air as coolant in fully turbulent regime. These encouraging results and the possibility of growing structures directly on silicon can be regarded as a first step.     

Fast computation of multi-scale combustion systems

In the present work, we illustrate the process of constructing a simplified model for complex multi-scale combustion systems. To this end, reduced models of homogeneous ideal gas mixtures of methane and air are first obtained by the novel relaxation redistribution method, and thereafter used for the extraction of all the missing variables in a reactive flow simulation with a global reaction model.     

Water transport control in carbon nanotube arrays

Based on a recent scaling law of the water mobility under nanoconfined conditions, we envision novel strategies for precise modulation of water diffusion within membranes made of carbon nanotube arrays (CNAs). In a first approach, the water diffusion coefficient D may be tuned by finely controlling the size distribution of the pore size. In the second approach, D can be varied at will by means of externally induced electrostatic fields. Starting from the latter strategy, switchable molecular sieves are proposed, where membranes are properly designed with sieving and permeation features that can be dynamically activated/deactivated. Areas where a precise control of water transport properties is beneficial range from energy and environmental engineering up to nanomedicine.     

Coupling of the model reduction technique with the lattice Boltzmann method for combustion simulations

A new framework of simulation of reactive flows is proposed based on a coupling between accurate reduced reaction mechanism and the lattice Boltzmann representation of the flow phenomena. The model reduction is developed in the setting of slow invariant manifold construction, and the simplest lattice Boltzmann equation is used in order to work out the procedure of coupling of the reduced model with the flow solver. Practical details of constructing slow invariant manifolds of a reaction system under various thermodynamic conditions are reported. The proposed method is validated with the two-dimensional simulation of a premixed counterflow flame in the hydrogen-air mixture.