QSense Omni, the 4th generation QSense QCM-D platform. An easy to use modular and upgradeable QCM-D instrument suite that offers unsurpassed performance and data quality, designed to make it easier for scientists and researchers to generate high quality and trustworthy QCM-D data. In this post, we show a case example to demonstrate what a measurement setup, instrument performance, and work time efficiency could look like using QSense Omni.
In this case example we used QSense Omni to analyze surfactant absorption. This is a general surface science example where we explore the complexity of something seemingly simple, such as an amphiphilic molecule, and adsorb it to the surface to measure the adsorption dynamics and surfactant arrangement at the surface.
Surfactants can adsorb in a number of different ways. One and the same surfactant may take many different conformations at the surface, Fig 1, such as monolayers, bilayers, hemicelles, micelles or vesicles, depending on the conditions. There are also possibilities of mixed situations between them, or unorganized adsorption, or adsorption of larger structures penetrating far into the solvent. Whereas optical methods, would usually not be able to distinguish between these different types of adsorption, they would only observe the mass, the dissipation factor in QCM-D, allows us to detect what type of adsorption we a looking at.
Figure 1. Depending on surface, solution and surfactant properties, surfactants could adsorb in a number of different ways, such as monolayers, bilayers, hemicelles, micelles and vesicles.
Aspects that control what type of surfactant adsorption we get are the surface itself, such as the hydrophobicity and charge of the surface. For example, we may get a monolayer on a hydrophobic surface or a bilayer on a hydrophilic surface.
The surfactant also affects what types of adsorption we get, where aspects like the concentration, charge, the hydrophilic-lipophilic balance of the molecule, and even the geometry have an impact. A rodlike molecule could promote monolayer or bilayer formation, whereas if the hydrophilic sides are branched, or wider than the lipophilic side of the molecule, curvature would be introduced into the system resulting in structures like micelles or vesicles. The solvent also influences the behavior by the polarity of the solvent compared to the hydrophobicity at the surface. And the pH and the ionic strength could also influence. In other words, surfactant adsorption is complex, but by selecting the right experimental setup, we can investigate
In the case example shown in this post, we use a linear non-ionic surfactant, Brij L4. It is a commercial grade surfactant consisting of linear lauryl tail with a linear polyethylene oxide head group. The polyethylene chain has some length variation but in average is four units long, matching the length of the tail. From a water solution it has shown to adsorb to SiO2 in highly repeatable way, with very low dissipation shift, indicating a highly ordered structure. It is expected to form a bilayer since there is no curvature induced by the geometry of the surfactant. Another favorable property of this system is that the SiO2 surface can quickly be generated by a 10% solution of Isopropanol, which quickly dissolves the adsorbed surfactant layer.
The protocol set up in the software QSoft Omni was as follows
The measurement starts with a baseline in water and then the surfactant is introduced to study the adsorption to SiO2. This is followed by a rinse step to assess the desorption. Finally, the surface is regenerated by a rinse off step using an isopropanol solution. One measurement takes 30 minutes, and the process is then repeated using the next concentration. All in all, three different concentrations were used, 50μg/ml, 500 μg/ml and 5000μg/ml. The total time for the measurement script was 1h 40 min. All surfactant concentrations are above cmc.
Table 1. Overview of measurement protocols used in the study.
The data, Fig. 2, reveals that we got two different absorption speeds depending on the surfactant concentration. The graph shows that the surfactant first adsorbs and then it desorbs in the water rinse step. For the two higher concentrations, equilibrium is reached, and they show same adsorbed amount, so there is no situation where adsorption/desorption balance leads to a partially covered surface for these concentrations. But we do see increased adsorption speed with higher concentration. Together this would indicate that the adsorption is mass transport limited, i.e. it is the transport of surfactant to the surface that determines the kinetics of the adsorption.
Figure 2. QCM-D data showing three sequential measurements at different surfactant concentrations as listed in Table 1.
In the rinse off step there is a large signal due to the viscosity shift. Thereafter, we return to the baseline, and we note that the drift is very low. Zooming in, Fig. 3, it is noted that even though the dissipation shift is very low, ~0.3 - 0.5, the dissipation data is of very good quality with a low relative noise. The noise is also really low in the frequency data.
Figure 3. Zoom in of Fig. 2 showing the low noise in both f and D.
So how about work time efficiency and productivity with this QSense system? To estimate what this could look like, we timed the different experimental steps.
We started with a clean instrument and stock solution of the Brij molecule, and then we started the timer. The sensors were UV/ozoned for 20 minutes and the instrument started, setting the temperature to 25°C. And all in all, the measurement preparations took ~50 minutes, including preparing the sensors, samples, dilution series, pipetting samples into to the instrument, and preparing the script in QSoft Omni.
Next, we clicked the start button, let the QC complete and baselines stabilize before the measurements started. This part was automatically handled by the instrument. The measurement time went up from 1h 40 min predicted by the script, to 1h 46 min due to the fact that the valves need some time to switch between the positions, and also there is a brief flush of the valves to get a clean liquid exchange between the samples. After the experiment, there was an automatic cleaning with one flush of isopropanol and two flushes of water, which took ~30 min.
All in all, the timing is quite efficient with 50 minutes hands on time, and the rest is handled by the instrument.
The QSense Omni platform represents a significant advancement in QCM-D technology, delivering exceptional performance and data quality that facilitate high-quality and reliable QCM-D data generation. The case example demonstrates some of the platform's standout features, low drift and low noise levels, which contribute to the high quality of the dissipation and frequency data obtained during experiments. These attributes ensure that the data produced is of superior quality, with minimal interference and high reliability. Regarding operational efficiency, the QSense Omni system offers a streamlined workflow that significantly reduces manual labor. The hands-on preparation time was approximately 50 minutes, with the automated measurement and cleaning processes efficiently managed by the instrument.
Watch the webinar to learn more about the experimental details
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Fredrik is a Senior Application Scientist at Biolin Scientific. After his Master of Science in Biosensors- and Microsystems technology he has worked with technology and application development in as diverse fields as electroporation, multivariate gas sensing, drug screening and surface science.