Controlled Preparation of Nanoparticle Gradient Materials by Diffusion

Abstract

Nanoparticle gradient materials combine a concentration gradient of nanoparticles with a macroscopic matrix. This way, specific properties of nanoscale matter can be transferred to bulk materials. These materials have great potential for applications in optics, electronics, and sensors. However, it is challenging to monitor the formation of such gradient materials and prepare them in a controlled manner. In this study, we present a novel universal approach for the preparation of this material class using diffusion in an analytical ultracentrifuge. The nanoparticles diffuse into a molten thermoreversible polymer gel and the process is observed in real-time by measuring the particle concentrations along the length of the material to establish a systematic understanding of the gradient generation process. We extract the apparent diffusion coefficients using Fick’s second law of diffusion and simulate the diffusion behavior of the particles. When the desired concentration gradient is achieved the polymer solution is cooled down to fix the concentration gradient in the formed gel phase and obtain a nanoparticle gradient material with the desired property gradient. Gradients of semiconductor nanoparticles with different sizes, fluorescent silica particles, and spherical superparamagnetic iron oxide nanoparticles are presented. This method can be used to produce tailored nanoparticle gradient materials with a broad range of physical properties in a simple and predictable way.

Ultracentrifugation Techniques for the Ordering of Nanoparticles

“…This approach was also proven to be versatile, as the gradient superstructures can be applicable to nanoparticles of different sizes, shapes and materials. More interestingly, nanoparticle gradient materials can also be fabricated in an AUC band-forming cell, by the diffusion process at a very low angular velocity in an AUC synthetic boundary experiment [ 101 ], as shown in Figure 7 C. In this experiment, the nanoparticles were overlayed onto a solution column of molten gelatin at around 40 °C at a low angular velocity. Afterwards, the nanoparticle layer continued to diffuse into the solvent column, which can be detected by AUC in real-time.…”

Self-Limiting Shell Formation in Cu@Ag Core–Shell Nanocrystals during Galvanic Replacement

“…We developed a quantitative model with this understanding of shell formation via GRR by modifying the equations of diffusion 41 to include terms for the enthalpy of mixing. For the case without mixing terms, the governing equation for systems with spherical symmetry is…”

“…We developed a quantitative model with this understanding of shell formation via GRR by modifying the equations of diffusion to include terms for the enthalpy of mixing. For the case without mixing terms, the governing equation for systems with spherical symmetry is C ( r , t ) is the dimensionless concentration or mole fraction for either Cu or Ag as a function of the reaction time t , and the distance from the center of the NC, r .…”

Rational route to fabrication of uni-dimensional surface gradients presenting stochastic and periodic arrangement of nanoparticles

“…The low standard deviations with which nanoparticles can be produced, reduces the spread of geometric variables of features obtained on the gradient. Nanoparticle density gradients have been reported to be obtained using diffusion-limited transport through polymer melts [30], electrostatic self-assembly of negatively charged nanoparticles to positively charged molecular gradients [2,17,31], or via kinetic control over nanoparticle deposition by dip-coating processes [22,23]. Control over kinetic processes provides more flexibility in determining the geometric attributes, viz.…”