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Note to readers: Relevant theory for this laboratory on light scattering is typically covered in two lectures. Here, we present only a short introduction to theory, a standards-reading exercise, and the procedures, data analysis, and discussion questions corresponding to a laboratory exercise. Theory sections may be expanded into additional chapters at a later time.

1. Introduction

Nanoparticles and colloids in suspension scatter electromagnetic radiation (light) at various angles from the incident light direction. For particles that are small relative to the wavelength of the incident light, the intensity of the scattered light and its dependence on the particle properties (e.g., size and refractive index) and scattering angle can be modeled by Rayleigh-Gans scattering theory, while particles of any arbitrary size are modeled by Mie scattering theory.

In static or multi-angle light scattering (SLS or MALS), scattering intensities are averaged over the measurement duration. Measurements taken at multiple angles enable the determination of properties such as molecular weight and radius of gyration for polymers, or fractal dimension for particle aggregates. In contrast, dynamic light scattering (DLS) evaluates fluctuations of the scattering intensity over time, typically at a fixed scattering angle. The rate of the fluctuation in the scattered light intensity corresponds to the diffusion coefficient of the particles, with smaller (faster-diffusing) particles producing more rapid intensity fluctuations. Hence, DLS is utilized to determine particle size distributions based on their diffusion coefficient. The Stokes-Einstein equation is applied to convert diffusion coefficients to particles sizes for spherical particles.

In the DLS data processing, raw data on the light intensity measurements are first evaluated by computing an autocorrelation function representing the rate of decay (loss) of correlation between the intensity measured at each time point, t, and a delayed time point, t + 𝜏. Faster decay of the autocorrelation function vs. t corresponds to more rapid intensity fluctuations (smaller particle sizes). A broader or shallower decay of the autocorrelation function corresponds to a broader or more polydisperse size distribution. To quantitatively estimate diffusion coefficients or particle size distributions, two modeling approaches are commonly applied to fit the autocorrelation function: (1) cumulants analysis to fit the autocorrelation function with a single polynomial equation, yielding single values for the z-average size and polydispersity index; or (2) deconvolution/regularization analysis, such as a non-negative least squares (NNLS) analysis, to estimate a best-fit histogram for the intensity-weighted particle size distribution, from which other averaged size distributions (e.g., volume-average) can be computed using Mie theory when given the particle refractive index.

This laboratory will apply DLS measurements to determine particle sizes for a series of purchased gold (Au) nanoparticles (nominally 10 nm, 30 nm, 60 nm, and 100 nm), a mixture of the four sizes of Au nanoparticles, two unknown Au nanoparticle samples synthesized in class with different visible colors (pink and purple), the 60 nm Au nanoparticles with an adsorbed polymeric surface coating (polyvinylpyrrolidone), and titanium dioxide (TiO2) nanoparticles. The learning objectives of the laboratory include: (1) evaluating and explaining similarities or differences between the DLS sizes and the manufacturer’s reported sizes; (2) identifying uncertainties or errors in the measurement based on the results acquired; (3) interpreting and critically evaluating the quality of the raw data collected, the autocorrelation function, and the model fitting results; and (4) implementing best practices for sample preparation and handling for DLS measurements.

This laboratory is paired with ASTM E3247–20: Standard Test Method for Measuring the Size of Nanoparticles in Aqueous Media Using Dynamic Light Scattering, to support the learning objectives.

2. Relevant Documentary Standards and Reading Exercises

Exercise L2.1

Review the following ASTM test standards:

Reading of both standards is recommended, but this exercise will focus specifically on the sections listed below from ASTM E3247-20:

Section X2.3 — Sample Concentration and Scattering Intensity and Section 12.4

  1. What issues arise if the sample concentration is too low?
  2. What issues arise if the sample concentration is too high?
  3. If the sample concentration is not within a suitable or optimal range for analysis, what approaches can be used to address this issue? What are the limitations or potential issues with these approaches?

Section X2.4 — Salt (Electrolyte) Concentration

  1. What issues arise if the background salt concentration is too low?
  2. What issues arise if the background salt concentration is too high?

Section X2.5 — Dust Contamination and Sample Cleanliness

  1. What issues arise if there is dust contamination in the sample?
  2. What possible approaches could be used to mitigate the presence of dust or its effects on the measurements? What are the limitations or potential issues with these approaches?

Section X2.6 — Handling of Measurement Cuvettes and Section 12.9 — Loading Test Specimen

  1. What are the recommendations for handling cuvettes and loading and inspecting samples?
  2. Why are cuvette and sample inspection and cleanliness important for the dynamic light scattering measurement?

Section 13 — Calculation and Interpretation of Results

  1. What is the difference between the cumulants and deconvolution (regularization) algorithms? What are the advantages and limitations of each data analysis algorithm?
  2. Which size distribution weigthings (e.g., intensity-, volume-, surface- or number-) are recommended or discouraged to report from a dynamic light scattering measurement?
  3. What sample or solvent properties are important to report, and why?
  4. When is refractive index required for the nanoparticles being measured?

3. Experimental Procedure

3.1 Chemical reagents

  • Deionized (DI) water
  • 10 nm Au nanoparticle stock suspension (BBI Solutions, EM.GC10)
  • 30 nm Au nanoparticle stock suspension (BBI Solutions, EM.GC30)
  • 60 nm Au nanoparticle stock suspension (BBI Solutions, EM.GC60)
  • 100 nm Au nanoparticle stock suspension (BBI Solutions, EM.GC100)
  • Au nanoparticles synthesized in Activity 1 (pink color)
  • Au nanoparticles synthesized in Activity 2 (purple color)
  • TiO2 nanoparticle stock suspension (Evonik Aeroxide® P25, 2 g/L in DI water)
  • Polyvinylpyrrolidone (PVP) stock solution (≈ 40 kDa molar mass, 10 g/L in DI water)

3.2 Equipment and supplies

  • Malvern Zetasizer Nano ZS dynamic light scattering instrument
  • Pipettors and pipet tips
  • Polystyrene cuvettes (semi-micro volume), 1 cuvettte per sample

3.3 Procedures

Sample preparation

Rinse and inspect a polystyrene cuvette and cap for sample preparation following the guidelines from the ASTM E3247-20 standard. Prepare a total volume of 0.5 mL of each the following samples directly into the polystyrene cuvettes:

    1. 5X dilution of 10 nm Au nanoparticles in DI water (i.e., 0.1 mL of the purchased Au nanoparticles + 0.5 mL of DI water)
    2. 5X dilution of 30 nm Au nanoparticles in DI water
    3. 5X dilution of 60 nm Au nanoparticles in DI water
    4. 5X dilution of 100 nm Au nanoparticles in DI water
    5. Mixture of 10, 30, 60, and 100 nm Au nanoparticles in DI water, with each particle at 20X dilution in the final mixture (i.e., 0.025 mL of each size of purchased Au nanoparticles + 0.9 mL of DI water)
    6. Synthesized Au nanoparticles (pink) (undiluted from Activity 1)
    7. Synthesized Au nanoparticles (purple) (undiluted from Activity 1)
    8. 5X dilution of 60 nm Au nanoparticles with 1 g/L of PVP in DI water (i.e., 0.1 mL of purchased Au nanoparticles + 0.05 mL of PVP stock solution + 0.35 mL of DI water)
    9. 50X dilution of the TiO2 nanoparticle stock suspension in DI water (i.e., 0.01 mL of TiO2 stock suspension + 0.48 mL of DI water)

Instrument setup

Turn on the Zetasizer instrument, and open the Manual measurement dialogue. Table L2.1 below specifies the instrument settings to apply for the measurements.

Table L2.1. Zetasizer Measurement Settings for Particle Size Analysis by Dynamic Light Scattering

PARAMETER TAB SETTING NOTES
Measurement Type Size
Material


Material: Gold The properties listed here for gold are those already loaded in the Zetasizer software.
RI: 0.2
Absorption: 3.32
Dispersant



Dispersant: Water The properties listed here for water are those already loaded in the Zetasizer software.
Temperature:25 °C
Viscosity: 0.8872 cP
RI: 1.330
Temperature

Temperature: 25 °C
The default equilibrium time is listed to the left; for courses with time restrictions, a shorter time of 30 s may be inputted.
Equilibration Time: 120 s
Cell Disposable cuvettes
Measurement


Measurement angle: 173° Selecting an angle in the “backscattering” direction reduces the degree of measurement interference from very large particles, such as dust, and improves the capability to identify small particles in the population.
Measurement duration: Automatic
Number of measurements: 5
Delay between measurements: 0 s
Measurement → Advanced
Positioning method: Automatic The positioning refers to the distance from the face of the cuvette into the sample where the scattered laser light is probed and can automatically be optimized by the instrument to reduce multiple scattering effects in high concentrations of particles. The attenuator setting determines the percentage of the initial laser light intensity that enters the sample and can range from attenuator values of 0 (complete reduction of the laser light intensity) to 11 (no reduction of the laser light intensity).
Automatic attenuation: Yes
Data Processing Analysis model: General purpose (normal resolution) Selecting “multiple narrow modes (high resolution)” can enable better distinction of multimodal size distributions but also increases the risk of overfitting the data and observing erroneous peaks.

Sample analysis

  1. Insert the cuvette for the first sample into the DLS sample compartment. Ensure the cuvette is oriented properly with respect to the laser and inserted all the way to the bottom of the cell holder. Close the compartment.
  2. In the Zetasizer software, open the Manual measurement dialogue. Input the sample name and verify the measurement settings listed in Table L2.1.
  3. Click “Start measurement” to collect the measurements on your sample.
  4. Record your observations on the measurements collected during the lab in the table below (one per sample).

Table L2.2. Observations Noted During Dynamic Light Scattering Measurements

RESULT TYPE OBSERVATIONS NOTES
Attenuation factor Attenuator value: You should observe the attenuator being automatically optimized by the instrument prior to the collection of the sample data for analysis. If the automatic attenuator is optimized to the lowest position (1) or highest position (11), the sample concentration may be too high or too low, respectively, to be suitable for analysis. If the attenuator value is 1, consider diluting the sample and retesting. If the attenuator value is 11, consider preparing a more concentrated sample (if possible) or measuring a blank solvent sample to evaluate whether or not the signal (count rate) from the nanoparticle sample is significantly higher than that of the blank.
Count rate (raw data) Is the mean count rate stable over time? Count rates that drift upwards or downwards could be indicative of sample stability issues (refer to guidance from the ASTM E3247-20 standard).
Are there any large, intermittent spikes in the count rate as the data are being collected? Sharp spikes in the data are indicative of large agglomerates or dust particles that intermittently pass the laser and scatter high intensities of light, which could bias the measurement toward large sizes and interfere with the measurement of smaller particles in the population (refer to guidance from the ASTM E3247-20 standard).
Measured count rate: The actual count rate should fall within an optimal range, as specified by the instrument manufacturer (e.g., 100 kcps to 500 kcps). The attenuator optimization step is intended to satisfy this requirement.
Derived count rate:  The derived count rate adjusts the measured count rate by the attenuation factor, allowing count rates to be compared for different samples measured with different attenuator settings.
Autocorrelation function Sketch the appearance of the autocorrelation function: The autocorrelation function should show a smooth decay toward zero with increasing delay time. If the autocorrelation function is very noisy, the sample count rate may be insufficient. If the autocorrelation functions shows multiple shoulders, the sample contains a multimodal size population. If there is a shoulder at a very long decay time, this feature could be indicative of dust contamination or very large agglomerates.
Qualitative comparison to example data (60 nm polystyrene latex): The Zetasizer software installation comes with sample data sets. Overlaying the autocorrelation function plot for your sample with a monodisperse sample of known size, e.g., 60 nm polystyrene latex, can be helpful to qualitatively get a sense of the mean size and polydispersity of your sample with respect to the example data.
Model fits to the autocorrelation function Cumulants analysis — Does the model fit to the experimental data points appear to be a good fit or poor fit? The reported z-average diameter and polydispersity index (from cumulants analysis) and other size measurands, e.g., intensity-mean diameter (from distribution fitting) are the results of a model fit to the autocorrelation function. If the model fitting is observed to be poor, the reported value will not be reliable. Scenarios that could result in poor model fits include the presence of dust contamination peaks, which can skew the model fit.
Distribution fitting — Does the model fit to the experimental data points appear to be a good fit or poor fit?
Results: Cumulants analysis Are there any outliers in the z-avearge diameter or PDI from the 5 replicated measurements? If outliers are present, you may inspect the autocorrelation functions more carefully to identify possible issues.
Results: Distribution plots Are there outliers or variability in the size distribution plots from the 5 replicated measurements? If the size distribution plots are not consistent, the distribution fitting may not be suitable for the sample

Shutdown procedure

Save and export all of your data. Discard all samples to the waste containers provided.

4. Data Analysis

The attached Excel file (UH – Exptl Methods Nano – Laboratory 2 Data Analysis Template) contains a set of example data to process, along with figures showing the autocorrelation functions and size distributions from the distribution fit.

  1. Review all the observations noted in Table L2.2 during the lab. Report whether any of the samples may be too dilute or too concentrated for a reliable DLS analysis. Also, report whether there appeared to be any dust interference that could have influenced the results for any of the samples. Briefly explain the specific guidance from the ASTM E3247-20 standard that you are applying to evaluate the data, as well as which specific results or observations (from Table L2.2) you are evaluating to make each of these assessments.
  2. Complete Table L2.3 with the results indicated. Report the mean +/- standard deviation of the triplicate measurements for each sample, and round the reported values to an appropriate number of significant figures based on the standard deviation.

Table L2.3. Summary of Results

Sample z-average diameter (nm) PdI Intensity-average diameter (nm) Number-average diameter (nm) Derived count rate (kcps)
(i) Au NPs, 10 nm          
(ii) Au NPs, 30 nm          
(iii) Au NPs, 60 nm          
(iv) Au NPs, 100 nm          
(v) Au NP mixture
(10, 30, 60, 100 nm)
         
(vi) Au NPs, Pink          
(vii) Au NPs, Purple          
(viii) Au NPs, 60 nm, with PVP          
(ix) TiO2 NPs          

5. Discussion Questions

  1. Measurement settings
    Several pieces of information related to the sample and measurement properties were carefully inputted to set up the dynamic light scattering measurement (as shown in Table L2.2). Discuss why the temperature and solvent viscosity are important to input accurately by identifying where (i.e., in what model equation) errors in these parameter inputs would propagate to errors in the size determination by DLS. It is encouraged to refer to the introductory theory section of this laboratory and/or the ASTM E3247-20 standard for relevant discussion to answer this question.
  2. Comparison of sizing methods

    1. The manufacturer of the purchased nanoparticles noted in the materials list provides certificates with each batch of nanoparticles that report the mean diameters, as determined by transmission electron microscopy (TEM). Examples are listed in Table L2.4 for some specific batches of nanoparticles:
      Table L2.4. Properties reported by BBI Solutions for purchased Au nanoparticles

      Sample Name Batch Number Mean Diameter, TEM (nm) Gold chloride concentration in the synthesis Estimated Number Concentration (particles/mL)
      Au 10 nm 22090119 9.5 0.01% 5.7 × 1012
      Au 30 nm 014022 29.6 0.01% 2.0 × 1011
      Au 60 nm 22050119 58.6 0.01% 2.6 × 1010
      Au 100 nm 22100048 103.7 0.01% 5.6 × 109

      You may retrieve the certificates for your specific batches of purchased Au nanoparticles, if available. Do you observe any systematic deviations (i.e., consistently higher or lower values) when comparing the z-average DLS size or intensity-averaged DLS size to the TEM sizes reported? Provide at least one theoretical reason why these DLS sizes would show the observed deviation from the TEM size. It is encouraged to refer to the introductory theory section of this laboratory and/or the ASTM E3247-20 standard for relevant discussion to answer this question.

    2. Compare the DLS cumulants analysis results for the pink and purple Au NPs (Samples vi and vii). Are the z-average size and PdI higher or lower for one of the samples? Compare to your interpretation of the results for these two unknown samples from Laboratory 1 (UV-Vis spectrophotometry)do the results of your analyses from the two methods appear to agree or not?
  3. Trends in scattering count rate vs. size
    According to the table above, the mass concentration of Au should be identical across all four purchased sizes (which were all diluted by the same factor for the measurements). The number concentration of particles decreases with increasing size, because the larger particles contain more mass per particle. Review your data for Samples i-iv. Is there any trend in the derived count rate versus particle size? Does it match your expectations from scattering theory? It is encouraged to refer to the introductory theory section of this laboratory and/or the ASTM E3247-20 standard for relevant discussion to answer this question.
     
  4. Data analysis uncertainties
    The ASTM standards related to DLS provide guidance that the number-average size from the distribution fit analysis should not be reported. Based on your actual measured results on the samples with known particle sizes, do you observe substantial errors in any of the number-average results that would support the ASTM guidance?
  5. Sensitivity/robustness to surface coatings
    Based on your actual measured results from Lab 1 (UV-Vis Spectrophometry) and this lab for the uncoated and PVP-coated 60 nm Au nanoparticles, which of the two measurements – UV-Vis or DLS – appears to be more sensitive to the presence of the PVP coating, i.e. which measurement shows a greater percent deviation between the results for the uncoated and PVP-coated particle? Explain theoretically why the DLS measurement would or would not be expected to be sensitive to an adsorbed coating layer. It is encouraged to refer to the introductory theory section of this laboratory and/or the ASTM E3247-20 standard for relevant discussion to answer this question.
  6. Multimodal size distributions
    For Sample v (the mixture of four Au nanoparticle sizes), was the DLS measurement on the mixture able to resolve that there were four different sizes of nanoparticles mixed together – i.e., did four separate peaks appear in the intensity-weighted histogram? If not, which size particle most influenced the result? Explain whether the results match your expectations based on scattering theory and your observations in your table of results from the lab. It is encouraged to refer to the introductory theory section of this laboratory and/or the ASTM E3247-20 standard for relevant discussion to answer this question.
  7. Challenges for nanomaterial characterization in products
    Recall the ASTM E3025-16 standard for characterization of silver nanomaterials in textiles from Chapter 8. In the summary list of analytical techniques for detection and characterization of silver in textiles (Table X2.1 in the standard), DLS is not listed as a suggested technique. Briefly explain a major reason why DLS would be highly challenging or unsuitable to apply in this scenario.

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