The authors would like to acknowledge the financial support from NSF (CBET 1638893), (CBET 1638896), NIH (P20 GM113131), and the Hamel Center for Undergraduate Research at UNH. Further, the authors would like to recognize the assistance of Darcy Fournier for the assistance in cabling and Scott Greenwood for access to the DLS.

1. Example polymer preparations
<ol>
	<li>pNIPAM polymer synthesis 
	NOTE: This preparation produces 10 mL of 1 g/L solution, which is enough for 3-4 experiments.
	<ol>
		<li>Prepare the Schlenk line apparatus. Ensure the cold trap Dewar flask is filled with a slurry of dry ice and acetone, or if a mechanical refrigeration trap is used, ensure that the trap has reached an appropriate temperature.</li>
		<li>In a 50 mL round-bottom flask, add 0.566 g of N-isopropylacrylamide (NIPAM) monomer, 0.016 g of reversible addition fragmentation chain transfer polymerization (RAFT) agent (phthalimidomethyl butyl trithiocarbonate), 0.0008 g of 2,2-azobis(2-methylpropionitrile) (AIBN) and 10 mL of 1,4-dioxane. Put a stir bar into the flask. Seal the flask with a rubber septum, wrap with vinyl tape, and dissolve the monomers in 1,4-dioxane.</li>
		<li>Perform freeze-pump-thaw degassing as follows: Freeze the solution by immersing the round-bottom flask in a Dewar flask containing a slurry of dry ice and methanol. Once all material is frozen, use the vacuum manifold of the Schlenk line to evacuate the flask to an internal pressure under 100 kPa. Isolate the flask, and thaw under static vacuum, using warm water. Return the flask to atmospheric pressure using the nitrogen manifold of the Schlenk line.</li>
		<li>Repeat step 1.1.3 three times to minimize the internal oxygen concentration.</li>
		<li>Sparge the solution with nitrogen to balance the pressure to atmosphere. Heat the mixture to 85 &#176;C using an oil bath and stir at 200 rpm for 36 h.</li>
		<li>To a 50 mL beaker, add 40 mL of hexane. Then add the polymer mixture to the hexane dropwise. The pNIPAM should precipitate out as white floccule. 
		NOTE: NIPAM monomer is soluble in hexane, but pNIPAM has a poor solubility in hexane.</li>
		<li>Pour the cloudy mixture into a B&#252;chner funnel to collect the white pNIPAM powder. Transfer the powder to a 20 mL vial and put it in a vacuum oven overnight to remove leftover solvent. Store in a sealed container at room temperature until needed.</li>
	</ol>
	</li>
	<li>pNIPAM-block-poly(ferrocenylmethyl methacrylate) block-copolymer (p(NIPAM-b-FMMA)) synthesis 
	NOTE: This preparation produces 10 mL of 1 g/L solution, which is enough for 3-4 experiments.
	<ol>
		<li>Prepare the Schlenk line apparatus. Ensure the cold trap Dewar flask is filled with a slurry of dry ice and acetone, or if a mechanical refrigeration trap is used, ensure that the trap has reached an appropriate temperature.</li>
		<li>In a 50 mL round-bottom flask, add 0.057g of ferrocenylmethyl methacrylate (FMMA) monomer, 0.016 g of RAFT agent, 0.0008 g of AIBN and 10 mL of 1,4-dioxane. Put a stir bar into the flask. Seal the flask with a rubber septum, wrap with vinyl tape, and dissolve the monomers in 1,4-dioxane.</li>
		<li>Perform freeze-pump-thaw degassing as follows: Freeze the solution by immersing the round-bottom flask in a Dewar flask containing a slurry of dry ice and methanol. Once all material is frozen, use the vacuum manifold of the Schlenk line to evacuate the flask to an internal pressure under 100 kPa. Isolate the flask, and thaw under static vacuum, using warm water. Return the flask to atmospheric pressure using the nitrogen manifold of the Schlenk line.</li>
		<li>Repeat step 1.2.3 three times to minimize the internal oxygen concentration.</li>
		<li>Sparge the solution with nitrogen to balance the pressure to atmosphere. Heat the mixture to 85 &#176;C using an oil bath and stir it for 10 h.</li>
		<li>Dissolve 0.543 g of NIPAM and 0.0002 g of AIBN into 3 mL of 1,4-dioxane. Add the solution into the flask under nitrogen and sparge for 30 min. Heat the mixture to 85 &#176;C using an oil bath and stir it at 200 rpm for another 36 h.</li>
		<li>Add 40 mL of hexane to a 50 mL beaker. Then add the polymer mixture to the hexane dropwise. The p(NIPAM-b-FMMA) should precipitate out as brown powder because the FMMA monomer has a dark yellow color. 
		NOTE: NIPAM and FMMA monomers are soluble in hexane, but p(NIPAM-b-FMMA) has poor solubility in hexane.</li>
		<li>Pour the yellow cloudy mixture into a B&#252;chner funnel to collect the brown p(NIPAM-b-FMMA) powder. Transfer the powder to a 20 mL vial and put it in vacuum oven overnight to remove leftover solvent. Store in a sealed container at room temperature until needed.</li>
	</ol>
	</li>
</ol>
2. DLS sample and cuvette preparation
NOTE: This section prepares the cuvette for applied voltage and the sample for DLS measurements.
<ol>
	<li>Measure 10 mg of polymer powder and dissolve in 10 mL of filtered deionized (DI) water. Put the mixture in a refrigerator overnight. When ready to start the experiment, keep the sample on ice. 
	NOTE: The polymer concentration used in these experiments was 1 g/L, but the optimal range of concentrations for each sample will be unique. Also, best practice is to keep the polymer below the LCST until it is ready for testing.</li>
	<li>Cut two pieces of 6.3 mm x 7 cm single-sided copper tape (Figure 1). Use tweezers to stick each piece to opposite sides of the inside of the DLS sample cuvette, perpendicular to the light path. The bottom of the tape should reach near the bottom of the cuvette. Fold the edges of the copper tape over the top of the cuvette. Make sure the copper tape is near/wrapped on the top of the sample cuvette to ensure good electrical contact. Also make sure the copper tape does not connect with the metal contacts associated with the DLS equipment used for Zeta potential measurements.</li>
	<li>Wash the cuvette with DI water three times, then dab the excess water off with a Kimwipe.</li>
</ol>
3. DLS instrument controls and set up
NOTE: Three controls are recommended to complete before running each DLS experiment: (1) blank water solution; (2) a size standard; (3) measurement of the polymer before the start of a temperature ramp or applied voltage. Please consult the instrument manual before operation for guidance on preparing a sample, choosing settings, and assessing sample and data quality.
<ol>
	<li>Transfer 1.5 mL of filtered solvent to the cuvette. Use DI water.</li>
	<li>Insert the cuvette to the cuvette holder, ensuring the small arrow on the top of the cuvette is aligned with the cuvette holder. Close the lid.</li>
	<li>Within the Zetasizer software, select Measure on the toolbar. Manual measurements were set up for the controls. Set the Temperature to the experimental starting point. Select 20 &#176;C for this experiment.</li>
	<li>Once the text at the bottom of the window says, Insert cell and press start when ready, hit the green triangle start button at the top of the screen. This starts the experiment, and the cuvette holder should not be opened after this.</li>
	<li>Click on the tab Multi-view to observe real-time results. Continuously monitor the sample and data quality by observing count rate and the correlation function. Because this sample is just solvent, no clear signal corresponding to the presence of particles should be observed.</li>
	<li>Add two drops of a standard solution to the cuvette or just use the water control, and repeat steps 3.2-3.6. Use a 20 nm NIST-traceable polystyrene size standard for this experiment. 
	NOTE: If the water or standard solution control runs show data that are inconsistent with the expected results, troubleshoot the error and repeat until the controls read as expected.</li>
	<li>Rinse the cuvette and add the filtered polymer/test solution. Repeat steps 3.2-3.5. A clear measurement of the initial test solution should be observed. It is recommended to do this before any temperature ramp or applied voltage for a baseline measurement.</li>
</ol>
4. DLS SOP set up
NOTE: This section refers specifically to the temperature ramping operation of a Malvern Zetasizer NanoZS DLS instrument. Before starting experiments, it is strongly recommended to consult the instrument manual extensively for guidance on selecting a cell, preparing a sample, choosing measurement settings, and assessing sample and data quality.
<ol>
	<li>Within the Zetasizer software (version 7.11), choose File, then click New to set up a new SOP (Figure 2).</li>
	<li>Click Measurement type to select Trend &#62; Temperature &#62; Size.</li>
	<li>In Material, choose the appropriate material and refractive index. Choose Protein and the refractive index (RI) of 1.450 for this experiment. If exact values for refractive index are desired for more accurate calculation of volume distribution, the experimenter should determine the refractive index of their sample experimentally.</li>
	<li>In Dispersant, choose the appropriate solvent. Choose Water as a solvent in this experiment.</li>
	<li>In Cell, choose the cuvette being used. Use Disposable cuvettes (DTS0012) for this experiment.</li>
	<li>In Sequence, set Start temperature and End temperature. For heating experiments, set the Start temperature at 20 &#176;C and set the End temperature as 40 &#176;C. For cooling experiments, choose the opposite. Uncheck the Return to starting temperature box.</li>
	<li>Select an interval for each temperature step change. For these experiments, select 1.5 &#176;C.</li>
	<li>In Size measurement, set Equilibration time. For these experiments, set the duration to 120 s. Choose number of measurements. Choose 3 measurements and Automatic for measurement duration.</li>
	<li>Save SOP, then close the file.</li>
	<li>If applied voltage is to be used, set up the potentiostat (Section 5) before continuing.</li>
	<li>Once the potentiostat is set up, or if applied voltage is not used, return to the Zetasizer software and click Measure on the toolbar, then click Start SOP.</li>
	<li>Once the text at the bottom of the SOP window says, Insert cell and press start when ready, hit the green triangle start button at the top of the screen. This starts the experiment, and the cuvette holder should not be opened after this.</li>
	<li>Click on the tab Multi-view to observe real-time results. Continuously monitor the sample and data quality by observing count rate and the correlation function. See Figures 3-5 for representative experimental results.</li>
</ol>
5. Potentiostat Setup
NOTE: It is recommended to use the same computer for particle size and applied voltage operations to time-sync the data and thereby making it easier to evaluate later. Please consult the applied voltage instrument manuals for guidance on wiring set up, software consultation, and choosing appropriate parameters. A Gamry potentiostat was used in these experiments.
<ol>
	<li>Prepare two wires that are thin enough to fit through the small crevice on the upper right edge of the DLS cuvette holder area (Figure 6). On one end of the prepared wire, strip off the insulation to allow for a connection to the potentiostat. On the opposite end, solder a short alligator clamp to the wire and connect to the cuvette. Make sure the DLS sample lid is closed.</li>
	<li>Clamp the white reference potentiostat lead and the red counter potentiostat lead together to one of the prepared wires. Clamp the green working potentiostat lead and the blue working sense potentiostat lead to the other prepared wire. For this experiment, do not use the orange counter sense and black ground potentiostat leads and leave them floating. To ensure the circuit does not short, these wires should not touch any other lead or conductive surface. 
	NOTE: It does not matter which side each lead is connected to.</li>
	<li>Within the software toolbar, click Experiment, then click option E Physical Electrochemistry, and select Chronoamperometry. For the purposes of this protocol, use a simple applied voltage by applying a single voltage with current response measured over time (i.e., chronoamperometry). Regardless of the specific electrochemical methodology, it is recommended to monitor the system response over time.
	<ol>
		<li>Set Pre-step, Step 1, and Step 2 Voltage vs Reference. This will be the applied voltage across the entire field/cuvette. Set Voltage to 1 V vs Reference for all three steps.</li>
		<li>Set Pre-step Delay Time. For these experiments, set to 0.5 s to make sure the system is stable at the desired voltage before recording a signal.</li>
		<li>Set the time for both Step 1 Time and Step 2 Time. This controls how long the voltage will be applied. Set both to 14,400 s to make sure the applied voltage will continue throughout the DLS experiment.</li>
		<li>Set Sample Period. This is how frequently the graph will read and record current and voltage values. Use 10.0 s in this experiment. 
		NOTE: The other settings are not significant for the data presented here. The default values in the system were used.</li>
	</ol>
	</li>
	<li>Click OK. Top toolbar will display an Active sign, indicating voltage is being applied. The current should give a moderate response (&#181;A), and not overload the potentiostat. If no signal or excessive signal is observed, the system might be connected incorrectly, and therefore, troubleshoot the error and repeat until the expected current is observed.</li>
	<li>Return to step 4.10 to start the DLS SOP.</li>
</ol>
6. Data analysis
NOTE: This section details preliminary analysis to understand the data obtained.
<ol>
	<li>Import data into preferred data analysis and graphing software.</li>
	<li>For each run within a set of measurements at a given temperature, determine the particle volume size of the peak with the largest volume percent.</li>
	<li>Calculate the average and standard deviation of the volume size over the three recorded measurements at a given temperature.</li>
	<li>For each experiment, plot average size &#177; standard deviation on the y-axis (log scale) versus temperature on the x-axis (linear scale).</li>
	<li>Import Gamry current data for analysis. Plot current data with time on the x-axis and current (in microamps) on the y-axis.</li>
	<li>In order to relate current data to particle size data, compare the timestamp of the Zetasizer data to the Gamry current timestamp. This is possible if the two types of data are collected from the same computer. Otherwise, match recorded times as best as possible.</li>
</ol>

<ol><li>Xu, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Particuology+Light+scattering+%3A+A+review+of+particle+characterization+applications%5BTitle%5D)+AND+%22Particuology%22%5BJournal%5D)">Particuology Light scattering : A review of particle characterization applications.</a> Particuology. 18, 11-21 (2015).</li>
<li>Szczubiałka, K., Nowakowska, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Response+of+micelles+formed+by+smart+terpolymers+to+stimuli+studied+by+dynamic+light+scattering%5BTitle%5D)+AND+%22Polymer%22%5BJournal%5D)">Response of micelles formed by smart terpolymers to stimuli studied by dynamic light scattering.</a> Polymer. 44 (18), 5269-5274 (2003).</li>
<li>Kotsuchibashi, Y., Ebara, M., Aoyagi, T., Narain, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Recent+Advances+in+Dual+Temperature+Responsive+Block+Copolymers+and+Their+Potential+as+Biomedical+Applications%5BTitle%5D)+AND+%22Polymers%22%5BJournal%5D)">Recent Advances in Dual Temperature Responsive Block Copolymers and Their Potential as Biomedical Applications.</a> Polymers. 8, 380(2016).</li>
<li>Lanzalaco, S., Armelin, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Poly%28N-isopropylacrylamide%29+and+Copolymers%3A+A+Review+on+Recent+Progresses+in+Biomedical+Applications%5BTitle%5D)+AND+%22Gels%22%5BJournal%5D)">Poly(N-isopropylacrylamide) and Copolymers: A Review on Recent Progresses in Biomedical Applications.</a> Gels. 3, 36(2017).</li>
<li>Lessard, D. G., Ousalem, M., Zhu, X. X., Eisenberg, A., Carreau, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Study+of+the+phase+transition+of+poly%28N%2CN-diethylacrylamide%29+in+water+by+rheology+and+dynamic+light+scattering%5BTitle%5D)+AND+%22Journal+of+Polymer+Science+Part+B%3A+Polymer+Physics%22%5BJournal%5D)">Study of the phase transition of poly(N,N-diethylacrylamide) in water by rheology and dynamic light scattering.</a> Journal of Polymer Science Part B: Polymer Physics. 41, 1627-1637 (2003).</li>
<li>Garner, B. W., Cai, T., Hu, Z., Neogi, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Electric+field+enhanced+photoluminescence+of+CdTe+quantum+dots+encapsulated+in+poly+%28N-isopropylacrylamide%29+nano-spheres%5BTitle%5D)+AND+%22Optics+express%22%5BJournal%5D)">Electric field enhanced photoluminescence of CdTe quantum dots encapsulated in poly (N-isopropylacrylamide) nano-spheres.</a> Optics express. 16, 19410-19418 (2008).</li>
<li>Gallei, M., Schmidt, B. V. K. J., Klein, R., Rehahn, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Defined+Poly%5Bstyrene-+block+-%28ferrocenylmethyl+methacrylate%29%5D+Diblock+Copolymers+via+Living+Anionic+Polymerization%5BTitle%5D)+AND+%22Macromolecular+Rapid+Communications%22%5BJournal%5D)">Defined Poly[styrene- block -(ferrocenylmethyl methacrylate)] Diblock Copolymers via Living Anionic Polymerization.</a> Macromolecular Rapid Communications. 30, 1463-1469 (2009).</li>
<li>Grenier, C., Timberman, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High+Affinity+Binding+by+a+Fluorescein+Templated+Copolymer+Combining+Covalent%2C+Hydrophobic%2C+and+Acid-Base+Noncovalent+Crosslinks%5BTitle%5D)+AND+%22Sensors%22%5BJournal%5D)">High Affinity Binding by a Fluorescein Templated Copolymer Combining Covalent, Hydrophobic, and Acid-Base Noncovalent Crosslinks.</a> Sensors. 18, 1330(2018).</li>
<li>Chiefari, J., Chong, Y. K. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Living+Free-Radical+Polymerization+by+Reversible+Addition%E2%88%92Fragmentation+Chain+Transfer%3A+The+RAFT+Process%5BTitle%5D)+AND+%22Macromolecules%22%5BJournal%5D)">Living Free-Radical Polymerization by Reversible Addition−Fragmentation Chain Transfer: The RAFT Process.</a> Macromolecules. 31, 5559-5562 (1998).</li>
<li>Perrier, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((50th+Anniversary+Perspective+%3A+RAFT+Polymerization-A+User+Guide%5BTitle%5D)+AND+%22Macromolecules%22%5BJournal%5D)">50th Anniversary Perspective : RAFT Polymerization-A User Guide.</a> Macromolecules. 50, 7433-7447 (2017).</li>
</ol>

The authors declare no conflicts of interest.

Applying voltage to either pNIPAM or p(NIPAM-b-FMMA) solutions changed the polymer aggregation behavior in response to temperature. With both materials, when an applied voltage was present, the polymers&#39; volume size remained high even when the solutions were cooled below their LCST. This was an unexpected result, as the trials with no voltage showed the polymers returning to their original sizes. These experiments allow us to conclude that for our temperature range, and with an applied voltage, polymer aggregation is not fully reversible, regardless of electroactive monomers added to the pNIPAM.
Another interesting result can be seen upon further inspection of Figure 9 and p(NIPAM-b-FMMA) LCST changes. Without voltage, the maximum volume size is around 1000 nm, and aggregation is reversible. However, with applied voltage, the stable agglomeration is approximately 100 nm and non-reversible. This would indicate a new stable agglomeration state formed with applied voltage compared to the absence of voltage.
The current response from the constant applied voltage may also provide insights into aggregation response. Because the files are timestamped, the current with relative changes in temperature can be matched, although there is not equal spacing between the temperature and time due to the automatic optimization at each step based on the scattering intensity and attenuation settings in the DLS. Our data indicate the current increases with temperature, then starts decreasing immediately after the LCST is passed. Clear trends are associated with the approximate time of aggregation, showing a low resistance in solution, resulting in less current. During cooling, current increases, but does not increase as rapidly as it did during heating. The current data adds information and possible insight into the polymer behavior.
The methodology of applying a voltage to dynamic light scattering particle size distribution measurements was successful. Differences in polymer aggregation behavior associated with particle size distribution measurements were observed when an applied voltage was present during a temperature ramp trend compared to the no-voltage case. The observed behavior was only present when both an applied voltage and temperature ramp were used.

Dynamic light scattering (DLS) is a technique to determine particle size through the use of random changes in intensity of light scattered through solution1. DLS is capable of measuring aggregation of polymers by determining particle size. For this experiment, DLS was coupled with controlled temperature changes to observe when a polymer aggregates which is indicative of exceeding the lower critical solution temperature (LCST)2,3. Below the LCST, there exists one homogeneous liquid phase; above the LCST, the polymer becomes less soluble, aggregates, and condenses out of solution. An applied voltage (i.e., applied potential or electric field) was introduced across the scattering field to observe the effects of the electric field on aggregation behavior and LCST. The application of voltage in particle sizing measurements allows for new insights into particle behavior and subsequent applications in the fields of sensors, energy storage, drug delivery systems, soft robotics, and others.
In this protocol, two example polymers were used. Poly(N-isopropylacrylamide), or pNIPAM, is a thermal sensitive polymer, which contains both a hydrophilic amide group and a hydrophobic isopropyl group on the macromolecular chain4,5. Thermal-responsive polymer materials like pNIPAM have been widely used in controlled drug release, biochemical separation, and chemical sensors in recent years3,4. The LCST literature value of pNIPAM is around 30-35 &#176;C4. pNIPAM is typically not electrochemically active. Therefore, as a second sample polymer an electrochemically-active block was added to the polymer. Specifically, ferrocenylmethyl methacrylate was used to create a poly(N-isopropylacrylamide)-block-poly(ferrocenylmethyl methacrylate) block-copolymer, or p(NIPAM-b-FMMA)6,7. Both example polymers were synthesized by reversible addition fragmentation chain-transfer polymerization with controlled chain length8,9,10. The non-electrochemically active polymer, pNIPAM, was synthesized as 100 mer pure pNIPAM. The electrochemically active polymer, p(NIPAM-b-FMMA), was also 100 mer chain length, which contains 4% ferrocenylmethyl methacrylate (FMMA) and 96% NIPAM.
In this article, a protocol and methodology to study the effect of applied voltage on polymer aggregation is demonstrated. This method could also be extended to other applications of DLS, such as the analysis of protein folding/unfolding, protein-protein interactions, and agglomeration of electrostatically charged particles to name a few. The sample was heated from 20 &#176;C to 40 &#176;C to identify the LCST in the absence and presence of a 1 V applied field. Then, the sample was cooled from 40 &#176;C to 20 &#176;C without disrupting the applied field to study any hysteretic or equilibrium effects.

<table><tbody><tr><td>&lt;em&gt;N&lt;/em&gt;-Isopropylacrylamide</td><td>Tokyo Chemical Industry CO., LTD</td><td>I0401-500G</td><td></td></tr><tr><td>1,4-Dioxane</td><td>Alfa Aesar</td><td>39118</td><td></td></tr><tr><td>2,2&quot;-Azobis(2-methylpropionitrile)</td><td>SIGMA-ALDRICH</td><td>441090-100G</td><td></td></tr><tr><td>Cuvette</td><td>Malvern</td><td>DTS0012</td><td></td></tr><tr><td>Dynamic Light Scattering</td><td>Malvern</td><td>Zetasizer NanoZS</td><td></td></tr><tr><td>Ferrocenylmethyl methacrylate</td><td>ASTATECH</td><td>FD13136-1G</td><td></td></tr><tr><td>Phthalimidomethyl butyl trithiocarbonate</td><td>SIGMA-ALDRICH</td><td>777072-1G</td><td></td></tr><tr><td>Potentiostat</td><td>Gamry</td><td>Reference 600</td><td></td></tr></tbody></table>

application of voltage in dynamic light scattering particle size analysis

Dynamic light scattering (DLS) is a common method for characterizing the size distribution of polymers, proteins, and other nano- and microparticles. Modern instrumentation permits measurement of particle size as a function of time and/or temperature, but currently there is no simple method for performing DLS particle size distribution measurements in the presence of applied voltage. The ability to perform such measurements would be useful in the development of electroactive, stimuli-responsive polymers for applications such as sensing, soft robotics, and energy storage. Here, a technique using applied voltage coupled with DLS and a temperature ramp to observe changes in aggregation and particle size in thermoresponsive polymers with and without electroactive monomers is presented. The changes in aggregation behavior observed in these experiments were only possible through the combined application of voltage and temperature control. To obtain these results, a potentiostat was connected to a modified cuvette in order to apply voltage to a solution. Changes in polymer particle size were monitored using DLS in the presence of constant voltage. Simultaneously, current data were produced, which could be compared with particle size data, to understand the relationship between current and particle behavior. The polymer poly(N-isopropylacrylamide) (pNIPAM) served as a test polymer for this technique, as pNIPAM's response to temperature is well-studied. Changes in the lower-critical solution temperature (LCST) aggregation behavior of pNIPAM and poly(N-isopropylacrylamide)-block-poly(ferrocenylmethyl methacrylate), an electrochemically active block-copolymer, in the presence of applied voltage are observed. Understanding the mechanisms behind such changes will be important when trying to achieve reversible polymer structures in the presence of applied voltage.

The real-time file output of each run in the temperature ramp is presented as a table, as seen in Figure 3. Each record can be chosen independently to see the volume size (Figure 4) and correlation coefficient (Figure 5). Volume particle size distribution (PSD) is the most accurate data to interpret the overall distribution and LCST, but the quality of data should be assessed via correlation graph (Figure 5) to determine if any points should be excluded from analysis. Correlation graphs (Figure 5) that have a generally smooth curve are considered good quality, where non-smooth graphs or low-quality data should be considered for exclusion in the analysis. The curves at 24.5 &#176;C have some bumps and minor peaks in the curves, but this can be attributed to the rapid change in polymer aggregation, and therefore these data were included. This confirms that DLS data collected in our modified system in the presence of voltage are of equivalent quality to normal DLS data.
As seen in Figure 7 (red lines), pNIPAM exhibited an LCST at 30 &#176;C, a temperature close to the literature-described values4. Without voltage, pNIPAM was able to aggregate and disaggregate within the tested temperature range, returning to its original size and indicating expected reversibility. With voltage (Figure 7, black lines) pNIPAM went from being soluble to aggregating to a size of 2000 nm, then being reduced to a size of around 1000 nm during cooling, never returning to the original soluble state. Figure 8 shows the current data from pNIPAM with applied voltage and heating and cooling experiments corresponding to Figure 7 (black lines). The vertical red line at 26 &#176;C is a key transition point of pNIPAM where a phase change is observed with DLS. The vertical line at 40 &#176;C shows the maximum temperature in our measurement before the cooling cycle.
As seen in Figure 9 (red lines), the p(NIPAM-b-FMMA) polymer containing an electroactive FMMA block exhibited an LCST at 33 &#176;C. Without voltage, p(NIPAM-b-FMMA) was able to aggregate and disaggregate, returning to its original size. With voltage (Figure 9, black lines), the LCST of p(NIPAM-b-FMMA) shifted to 28 &#176;C. Again, with applied voltage, the p(NIPAM-b-FMMA) was not able to disaggregate and return to its original size during the cooling cycle. Figure 10 shows the current data from p(NIPAM-b-FMMA) with applied voltage and heating and cooling experiments corresponding to Figure 9 (black lines). The vertical red line at 28 &#176;C is just above the phase change observed with DLS. The vertical line at 40 &#176;C is at the maximum temperature in our measurement before cooling.
Evaluation of the current response data from the applied voltage is crucial to understanding the size response. If current is not carefully monitored, data will be misconstrued and potentially misunderstood. In one trial displayed in Figure 11, the voltage cut in and out as a result of accidental short circuiting. As a result of a short circuit, the voltage was only applied randomly and sporadically, and this resulted in a trend more similar to the no-voltage condition.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60257/60257fig1a.jpg" /> 
Figure 1: Disposable DLS cuvettes modified by adding copper tape to the sides to allow for applied voltage. The copper tape extends to the bottom and is wrapped around the top to ensure a good connection. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/60257/60257fig2a.jpg" /> 
Figure 2: A screenshot of DLS SOP setup, including sequence set up, size measurement specifications, and trend set up procedures. The screen depicted here acts as a main page where all other, more specific aspects and subpages of the data can be observed. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/60257/60257fig3a.jpg" /> 
Figure 3: Example of record view of data collection in Zetasizer software. These records contain in-depth measurements of factors like intensity, volume size, correlation data, and quality of data. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/60257/60257fig4a.jpg" /> 
Figure 4: Volume particle size distribution (PSD) for a single measurement at 31 &#176;C of pNIPAM with 1 V of applied voltage. This screen can be accessed by selecting the desired data point found in the records view tab (Figure 4) and provides detailed sizing information. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/60257/60257fig5a.jpg" /> 
Figure 5: Correlation data of an experiment with acceptable, reproducible correlation functions for each temperature in the presence of applied voltage. The correlation functions of three repeated runs at three different temperatures are plotted. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/60257/60257fig6a.jpg" /> 
Figure 6: DLS experiment setup using Gamry Potentiostat to apply constant voltage to the solution. This image depicts the wiring setup and general assembly of the circuitry required for this system. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/60257/60257fig7a.jpg" /> 
Figure 7: Plot of pNIPAM particle size versus temperature. Black lines = applied voltage, red lines = no voltage, square data points = heating trend, triangle data points = cooling trend. Without applied voltage, the LCST was 30 &#176;C during heating and 24 &#176;C during cooling. With applied voltage, the LCST was 26 &#176;C during heating and no disaggregation was observed during cooling. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/60257/60257fig8b.jpg" /> 
Figure 8: Current data from pNIPAM with heating and cooling. The vertical red line at 26 &#176;C is the LCST of pNIPAM where the phase change is observed in the DLS data (Figure 7). The vertical line at 40 &#176;C shows the time at which heating was completed and cooling was initiated. The x-axis indicates time since start of experiment, as well as temperature at various time points. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig8blarge.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/60257/60257fig9a.jpg" /> 
Figure 9: Plot of p(NIPAM-b-FMMA) particle size versus temperature. Black lines = applied voltage, red lines = no voltage, square data points = heating trend, triangle data points = cooling trend. Without applied voltage, the LCST was 33 &#176;C during heating and 28 &#176;C during cooling. With applied voltage, the LCST was 28 &#176;C during heating and no disaggregation was observed during cooling. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/60257/60257fig10a.jpg" /> 
Figure 10: Current data from the p(NIPAM-b-FMMA) with heating and cooling. The vertical red line at 29 &#176;C is just above the LCST of p(NIPAM-b-FMMA) where the phase change is observed in the DLS data (Figure 9). The x-axis indicates time since start of experiment, as well as temperature at various time points. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 11" class="xfigimg" src="/files/ftp_upload/60257/60257fig11a.jpg" /> 
Figure 11: Poorly connected circuit leading to error in data in a pNIPAM trial. The DLS data, pictured left, is similar to data from trials without voltage, which is explained by a disconnected and incomplete circuit. This theory of a poorly connected circuit is supported by the scattered current data, pictured right. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60257/60257fig11large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Application of Voltage in Dynamic Light Scattering Particle Size Analysis at JoVE.com

Application of Voltage in Dynamic Light Scattering Particle Size Analysis

Here, a protocol to apply voltage to solution during dynamic light scattering particle size measurements with the intent to explore the effect of voltage and temperature changes on polymer aggregation is presented.

Dynamic light scattering (DLS) is a common method for characterizing the size distribution of polymers, proteins, and other nano- and microparticles. ...

application-voltage-dynamic-light-scattering-particle-size

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Chemistry

9.9K Views.  University of New Hampshire. Here, a protocol to apply voltage to solution during dynamic light scattering particle size measurements with the intent to explore the effect of voltage and temperature changes on polymer aggregation is presented.

Video: Application of Voltage in Dynamic Light Scattering Particle Size Analysis

Growing Protein Crystals with Distinct Dimensions Using Automated Crystallization Coupled with In Situ Dynamic Light Scattering

The automated crystallization device is a patented technique1 especially developed for monitoring protein crystallization experiments with the aim to precisely maneuver the nucleation and crystal growth towards desired sizes of protein crystals. The controlled crystallization is based on sample investigation with in situ Dynamic Light Scattering (DLS) while all visual changes in the droplet are monitored online with the help of a microscope coupled to a CCD camera, thus enabling a full investigation of the protein droplet during all stages of crystallization. The use of in situ DLS measurements throughout the entire experiment allows a precise identification of the highly supersaturated protein solution transitioning to a new phase &#8211; the formation of crystal nuclei. By identifying the protein nucleation stage, the crystallization can be optimized from large protein crystals to the production of protein microcrystals. The experimental protocol shows an interactive crystallization approach based on precise automated steps such as precipitant addition, water evaporation for inducing high supersaturation, and sample dilution for slowing induced homogeneous nucleation or reversing phase transitions.

Growing Protein Crystals with Distinct Dimensions Using Automated Crystallization Coupled with In Situ Dynamic Light Scattering

Here we present a protocol for controlled production of protein microcrystals. The process uses an automated device allowing controlled manipulation of several crystallization parameters. The protein crystallization is carried-out by controlled and automated addition of crystallization solutions while monitoring and investigating the radius distribution of particles in the crystallization droplet.

The automated crystallization device is a patented technique1 especially developed for monitoring protein crystallization experiments with the aim to ...

Biochemistry

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

A protocol for measuring polydispersity of concentrated polymer solutions using dynamic light scattering is described. Dynamic light scattering is a technique used to measure the size distribution of polymer solutions or colloidal particles. Although this technique is widely used for the assessment of polymer solutions, it is difficult to measure the particle size in concentrated solutions due to the multiple scattering effect or strong light absorption. Therefore, the concentrated solutions should be diluted before measurement. Implementation of the confocal optical component in a dynamic light scattering microscope1 helps to overcome this barrier. Using such a microscopic system, both transparent and turbid systems can be analyzed under the same experimental setup without a dilution. As a representative example, a size distribution measurement of a temperature-responsive polymer solution was performed. The sizes of the polymer chains in an aqueous solution were several tens of nanometers at a temperature below the lower critical solution temperature (LCST). In contrast, the sizes increased to more than 1.0 &#181;m when above the LCST. This result is consistent with the observation that the solution turned turbid above the LCST.

A protocol for the direct measurement of particle size distribution in concentrated solutions using dynamic light scattering microscopy is presented.

A protocol for measuring polydispersity of concentrated polymer solutions using dynamic light scattering is described. Dynamic light scattering is a ...

DNA-magnetic Particle Binding Analysis by Dynamic and Electrophoretic Light Scattering

Isolation of DNA using magnetic particles is a field of high importance in biotechnology and molecular biology research. This protocol describes the evaluation of DNA-magnetic particles binding via dynamic light scattering (DLS) and electrophoretic light scattering (ELS). Analysis by DLS provides valuable information on the physicochemical properties of particles including particle size, polydispersity, and zeta potential. The latter describes the surface charge of the particle which plays major role in electrostatic binding of materials such as DNA. Here, a comparative analysis exploits three chemical modifications of nanoparticles and microparticles and their effects on DNA binding and elution. Chemical modifications by branched polyethylenimine, tetraethyl orthosilicate and (3-aminopropyl)triethoxysilane are investigated. Since DNA exhibits a negative charge, it is expected that zeta potential of particle surface will decrease upon binding of DNA. Forming of clusters should also affect particle size. In order to investigate the efficiency of these particles in isolation and elution of DNA, the particles are mixed with DNA in low pH (~6), high ionic strength and dehydration environment. Particles are washed on magnet and then DNA is eluted by Tris-HCl buffer (pH = 8). DNA copy number is estimated using quantitative polymerase chain reaction (PCR). Zeta potential, particle size, polydispersity and quantitative PCR data are evaluated and compared. DLS is an insightful and supporting method of analysis that adds a new perspective to the process of screening of particles for DNA isolation.

This protocol describes the synthesis of magnetic particles and evaluation of their DNA-binding properties via dynamic and electrophoretic light scattering. This method focuses on monitoring changes in particle size, their polydispersity and zeta potential of particle surface which play major role in binding of materials such as DNA.

Isolation of DNA using magnetic particles is a field of high importance in biotechnology and molecular biology research. This protocol describes the ...

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a standard fluid dynamic diagnostic, particle image velocimetry (PIV), to measure: i) velocities of individual particles (grains), extant on short, grain-collision time-scales, ii) velocities of systems of particles, on both short collision-time- and long, continuum-flow-time-scales, iii) collective hydrodynamic modes known to exist in dense molecular fluids, and iv) short- and long-time-scale velocity autocorrelation functions, central to understanding particle-scale dynamics in strongly interacting, dense fluid systems. The basic system is composed of an imaging system, light source, vibrational sensors, vibrational system with a known media, and PIV and analysis software. Required experimental measurements and an outline of the theoretical tools needed when using the analog technique to study molecular-scale hydrodynamic processes are highlighted. The proposed technique provides a relatively straightforward alternative to photonic and neutron beam scattering methods traditionally used in molecular hydrodynamic studies.

An experimentally accessible analog method for studying molecular hydrodynamic processes in dense fluids is presented. The technique uses particle image velocimetry of vibrated, high-restitution grain piles and allows direct, macroscopic observation of dynamical processes known and predicted to exist in strongly interacting, high density gases and liquids.

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a ...

Engineering

Asymmetrical Flow Field-Flow Fractionation for Sizing of Gold Nanoparticles in Suspension

Particle size is arguably the most important physico-chemical parameter associated with the notion of a nanoparticle. Precise knowledge of the size and size distribution of nanoparticles is of utmost importance for various applications. The size range is also important, as it defines the most &#8220;active&#8221; component of a nanoparticle dose.
Asymmetrical Flow Field-Flow Fractionation (AF4) is a powerful technique for sizing of particles in suspension in the size range of approximately 1&#8211;1000 nm. There are several ways to derive size information from an AF4 experiment. Besides coupling AF4 online with size-sensitive detectors based on the principles of Multi-Angle Light Scattering or Dynamic Light Scattering, there is also the possibility to correlate the size of a sample with its retention time using a well-established theoretical approach (FFF theory) or by comparing it with the retention times of well-defined particle size standards (external size calibration).
We here describe the development and in-house validation of a standard operating procedure (SOP) for sizing of an unknown gold nanoparticle sample by AF4 coupled with UV-vis detection using external size calibration with gold nanoparticle standards in the size range of 20&#8211;100 nm. This procedure provides a detailed description of the developed workflow including sample preparation, AF4 instrument setup and qualification, AF4 method development and fractionation of the unknown gold nanoparticle sample, as well as the correlation of the obtained results with the established external size calibration. The SOP described here was eventually successfully validated in the frame of an interlaboratory comparison study highlighting the excellent robustness and reliability of AF4 for sizing of nanoparticulate samples in suspension.

This protocol describes the use of Asymmetrical Flow Field-Flow Fractionation coupled with UV-vis detection for the determination of the size of an unknown gold nanoparticle sample.

Particle size is arguably the most important physico-chemical parameter associated with the notion of a nanoparticle. Precise knowledge of the size and ...

Bioengineering

Improving Reproducibility to Meet Minimal Information for Studies of Extracellular Vesicles 2018 Guidelines in Nanoparticle Tracking Analysis

Nanoparticle tracking analysis (NTA) has been one of several characterization methods used for extracellular vesicle (EV) research since 2006. Many consider that NTA instruments and their software packages can be easily utilized following minimal training and that size calibration is feasible in-house. As both NTA acquisition and software analysis constitute EV characterization, they are addressed in Minimal Information for Studies of Extracellular Vesicles 2018 (MISEV2018). In addition, they have been monitored by Transparent Reporting and Centralizing Knowledge in Extracellular Vesicle Research (EV-TRACK) to improve the robustness of EV experiments (e.g., minimize experimental variation due to uncontrolled factors).
Despite efforts to encourage the reporting of methods and controls, many published research papers fail to report critical settings needed to reproduce the original NTA observations. Few papers report the NTA characterization of negative controls or diluents, evidently assuming that commercially available products, such as phosphate-buffered saline or ultrapure distilled water, are particulate-free. Similarly, positive controls or size standards are seldom reported by researchers to verify particle sizing. The Stokes-Einstein equation incorporates sample viscosity and temperature variables to determine particle displacement. Reporting the stable laser chamber temperature during the entire sample video collection is, therefore, an essential control measure for accurate replication. The filtration of samples or diluents is also not routinely reported, and if so, the specifics of the filter (manufacturer, membrane material, pore size) and storage conditions are seldom included. The International Society for Extracellular Vesicle (ISEV)&#39;s minimal standards of acceptable experimental detail should include a well-documented NTA protocol for the characterization of EVs. The following experiment provides evidence that an NTA analysis protocol needs to be established by the individual researcher and included in the methods of publications that use NTA characterization as one of the options to fulfill MISEV2018 requirements for single vesicle characterization.

Nanoparticle tracking analysis (NTA) is a widely used method to characterize extracellular vesicles. This paper highlights NTA experimental parameters and controls plus a uniform method of analysis and characterization of samples and diluents necessary to supplement the guidelines proposed by MISEV2018 and EV-TRACK for reproducibility between laboratories.

Nanoparticle tracking analysis (NTA) has been one of several characterization methods used for extracellular vesicle (EV) research since 2006. Many ...

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Cells can crawl, self-heal, and tune their stiffness due to their remarkably dynamic cytoskeleton. As such, reconstituting networks of cytoskeletal biopolymers may lead to a host of active and adaptable materials. However, engineering such materials with precisely tuned properties requires measuring how the dynamics depend on the network composition and synthesis methods. Quantifying such dynamics is challenged by variations across the time, space, and formulation space of composite networks. The protocol here describes how the Fourier analysis technique, differential dynamic microscopy (DDM), can quantify the dynamics of biopolymer networks and is particularly well suited for studies of cytoskeleton networks. DDM works on time sequences of images acquired using a range of microscopy modalities, including laser-scanning confocal, widefield fluorescence, and brightfield imaging. From such image sequences, one can extract characteristic decorrelation times of density fluctuations across a span of wave vectors. A user-friendly, open-source Python package to perform DDM analysis is also developed. With this package, one can measure the dynamics of labeled cytoskeleton components or of embedded tracer particles, as demonstrated here with data of intermediate filament (vimentin) networks and active actin-microtubule networks. Users with no prior programming or image processing experience will be able to perform DDM using this software package and associated documentation.

Differential dynamic microscopy (DDM) combines features of dynamic light scattering and microscopy. Here, the process of using DDM to characterize reconstituted cytoskeleton networks by quantifying the subdiffusive and caged dynamics of particles in vimentin networks and the ballistic motion of active myosin-driven actin-microtubule composites is presented.

Cells can crawl, self-heal, and tune their stiffness due to their remarkably dynamic cytoskeleton. As such, reconstituting networks of cytoskeletal ...

An Innovative Method for Exosome Quantification and Size Measurement

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about their complex pathways, their bioavailability and their diverse functions in health and disease. Current work focuses on the presence and the behavior of exosomes (in vitro as well as in vivo) in the context of different human disorders, especially in the fields of oncology, gynecology and cardiology.
Unfortunately, neither a consensus regarding a gold standard for exosome isolation exists, nor is there an agreement on such a method for their quantitative analysis. As there are many methods for the purification of exosomes and also many possibilities for their quantitative and qualitative analysis, it is difficult to determine a combination of methods for the ideal approach. 
Here, we demonstrate nanoparticle tracking analysis (NTA), a semi-automated method for the characterization of exosomes after isolation from human plasma by ultracentrifugation. The presented results show that this approach for isolation, as well as the determination of the average number and size of exosomes, delivers reproducible and valid data, as confirmed by other methods, such as scanning electron microscopy (SEM).

A method for isolation of exosomes from whole blood and further analysis by nanoparticle tracking using a semi-automatic instrument is presented in this article. The presented technology provides an extremely sensitive method for visualizing and analyzing particles in liquid suspension.

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about ...

Biology

Dynamic Light Scattering Analysis for the Determination of the Particle Size of Iron-Carbohydrate Complexes

Intravenously administered iron-carbohydrate nanoparticle complexes are widely used to treat iron deficiency. This class includes several structurally heterogeneous nanoparticle complexes, which exhibit varying sensitivity to the conditions required for the methodologies available to physicochemically characterize these agents. Currently, the critical quality attributes of iron-carbohydrate complexes have not been fully established. Dynamic light scattering (DLS) has emerged as a fundamental method to determine intact particle size and distribution. However, challenges still remain regarding the standardization of methodologies across laboratories, specific modifications required for individual iron-carbohydrate products, and how the size distribution can be best described. Importantly, the diluent and serial dilutions used must be standardized. The wide variance in approaches for sample preparation and data reporting limit the use of DLS for the comparison of iron-carbohydrate agents. Herein, we detail a robust and easily reproducible protocol to measure the size and size distribution of the iron-carbohydrate complex, iron sucrose, using the Z-average and polydispersity index.

Dynamic light scattering (DLS) has emerged as a suitable assay for evaluating the particle size and distribution of intravenously administered iron-carbohydrate complexes. However, the protocols lack standardization and need to be modified for each iron-carbohydrate complex analyzed. The present protocol describes the application and special considerations for the analysis of iron sucrose.

Intravenously administered iron-carbohydrate nanoparticle complexes are widely used to treat iron deficiency. This class includes several structurally ...

Medicine

Nanoparticle Tracking Analysis for the Quantification and Size Determination of Extracellular Vesicles

The physiological and pathophysiological roles of extracellular vesicles (EVs) have become increasingly recognized, making the EV field a quickly evolving area of research. There are many different methods for EV isolation, each with distinct advantages and disadvantages that affect the downstream yield and purity of EVs. Thus, characterizing the EV prep isolated from a given source by a chosen method is important for interpretation of downstream results and comparison of results across laboratories. Various methods exist for determining the size and quantity of EVs, which can be altered by disease states or in response to external conditions. Nanoparticle tracking analysis (NTA) is one of the prominent technologies used for high-throughput analysis of individual EVs. Here, we present a detailed protocol for quantification and size determination of EVs isolated from mouse perigonadal adipose tissue and human plasma using a breakthrough technology for NTA representing major advances in the field. The results demonstrate that this method can deliver reproducible and valid total particle concentration and size distribution data for EVs isolated from different sources using different methods, as confirmed by transmission electron microscopy. The adaptation of this instrument for NTA will address the need for standardization in NTA methods to increase rigor and reproducibility in EV research.

We demonstrate how to use a novel nanoparticle tracking analysis instrument to estimate the size distribution and total particle concentration of extracellular vesicles isolated from mouse perigonadal adipose tissue and human plasma.

The physiological and pathophysiological roles of extracellular vesicles (EVs) have become increasingly recognized, making the EV field a quickly evolving ...

Application of Voltage in Dynamic Light Scattering Particle Size Analysis

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Przeglądaj więcej filmów

Growing Protein Crystals with Distinct Dimensions Using Automated Crystallization Coupled with In Situ Dynamic Light Scattering

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

DNA-magnetic Particle Binding Analysis by Dynamic and Electrophoretic Light Scattering

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Asymmetrical Flow Field-Flow Fractionation for Sizing of Gold Nanoparticles in Suspension

Improving Reproducibility to Meet Minimal Information for Studies of Extracellular Vesicles 2018 Guidelines in Nanoparticle Tracking Analysis

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

An Innovative Method for Exosome Quantification and Size Measurement

Dynamic Light Scattering Analysis for the Determination of the Particle Size of Iron-Carbohydrate Complexes

Nanoparticle Tracking Analysis for the Quantification and Size Determination of Extracellular Vesicles