Hello everyone! Today our Group will introduce the experiment Emulsion Polymerization.
It is a free-radical chain-growth polymerization method carried out in an aqueous dispersed medium.
Polymer particles undergo nucleation and growth during this process, with particle size continuously increasing until large latex particles are finally formed.
At the initial nucleation stage, since the particle size is much smaller than the wavelength of incident light, light scattering follows the Rayleigh scattering law.
At this stage, the incident light undergoes elastic scattering by small particles, and the scattering intensity is described by this equation.
Noting its dependence on wavelength and particle size, small particles at the initial stage preferentially scatter shorter-wavelength blue light, so blue light scattering can be observed.
As the particle size keeps increasing and becomes comparable to λ, the Rayleigh approximation fails.In this case, we need to use the Mie scattering theory without size limitation.
It provides an exact analytical solution for the scattering of a plane electromagnetic wave by a homogeneous isotropic spherical particle, obtained by rigorously solving Maxwell’s equations.
The scattering intensity is described by the scattering amplitude functions and Mie coefficients.
At this stage, the particles strongly scatter all visible wavelengths, so the latex appears milky white.
That is, when the particle size is smaller than λ/10, Rayleigh scattering should be applied, and when it exceeds this threshold, Mie scattering should be used.
Based on this, the Dynamic Light Scattering (DLS) technique characterizes particle size distribution by detecting the small fluctuations in scattered light intensity caused by the Brownian motion of particles.
This is a typical DLS system. Its three main components are as follows:
The laser provides a phase-stable, single-wavelength, collimated beam;
The sample in the cuvette is kept transparent and thermostated;
The Detector detects weak scattered light signals, and the Detector at 173° measures backscattering.
The Digital Correlator calculates the autocorrelation function G₂(τ), and finally, the PC computes the particle size distribution.
The Detector used is an Avalanche Photodiode (APD) with an internal gain mechanism.
Incident photons generate electron–hole pairs, which are accelerated and cause an avalanche producing more carriers.
Thus, the weak light signal is amplified into a detectable current pulse, achieving high-sensitivity detection.
The time autocorrelation function is a mathematical function describing how a random signal correlates with itself at different times.
In DLS, the Digital Correlator calculates the intensity time autocorrelation function to quantitatively describe light intensity fluctuations over time.
Because particles undergo Brownian motion in liquid, their positions change continuously, leading to random fluctuations in the total scattered intensity.
Therefore, this function measures the similarity of scattered intensity at different times, reflecting the particle motion speed.
After the Digital Correlator, the PC calculates the translational diffusion coefficient Dₜ from G₂(τ).
Since light intensity originates from interference of the electric field, G₂(τ) and the electric field autocorrelation function G₁(τ) satisfy the Siegert relation.
For a monodisperse system, G₁(τ) is a single exponential decay function, hence the following relationship.
Note that Γ (Gamma) is used here because the PC fitting result gives Γ.
As the scattering vector q is a fixed experimental parameter, Dₜ can be calculated from the fitted Γ and q.
With Dₜ, we can calculate the hydrodynamic radius and diameter according to the Stokes–Einstein relation.
This relation establishes a quantitative connection between Dₜ, particle size, and fluid properties, forming the theoretical foundation of this experiment.
We maintain a constant temperature in the experiment because of the parameters in the D_H calculation formula.
On one hand, T is a direct parameter, we must know the exact T to calculate D_H.
On the other hand, temperature variations change viscosity η, Brownian motion rate, and diffusion coefficient Dₜ, leading to incorrect D_H results.
The main difference between Hydrodynamic Radius (R_H) and Radius of Gyration (R_g) is that R_H includes the solvation layer, while R_g does not.
The Zeta potential can also characterize particles.
It is the potential at the slipping plane between a moving colloidal particle and the surrounding stationary liquid, located between the Stern layer and the diffuse layer, and can be calculated from electrophoretic mobility μ_e.
These are the materials we used, including the medium.
These are the micro syringes used to transfer reagents.
This is the core reactor of our setup. All materials except ascorbic acid are sequentially added into the scintillation vial.
This is our nitrogen purging system, used for degassing for 10 minutes in step 2.
In step 3, we inject AA and record the starting time t₀.
This is the core characterization instrument of this experiment — DLS and AFM instruments are used to measure particle size and zeta potential.
When the solution becomes turbid, take the solution into a cuvette and place it into the DLS instrument for measurement.
When the solution shows noticeable opalescence (cloudy appearance), a laser pointer can clearly reveal the light path, that is, the Tyndall effect.
Record the nucleation time.
We collected these data to plot the particle growth curve.
The same data were also exported to plot the normalized DLS spectra.
We measured these data to calculate the conversion percentage.
EM can also be used to measure particle size. It produces a 2D mapping of solid samples based on differences in electron beam scattering intensity.
Unfortunately our EM image was unsuccessful. Ideally, we expect to collect such data and calculate the average particle size. The smaller the d_avg, the bluer the film color.
The core components of Atomic Force Microscopy (AFM) include these.
It uses a laser to precisely measure the tiny deflection of the cantilever caused by tip–sample interaction forces.
Then, through a feedback loop, the piezoelectric ceramic is controlled to maintain constant deflection, and the Z-direction compensation displacement is recorded to construct the nanometer-scale 3D surface topography of the sample.