Vanessa
Lautenbach
a,
Georgy
Onishchukov
abc,
Simon E.
Wawra‡
ab,
Uwe
Frank§
ab,
Lukas
Hartmann
a,
Wolfgang
Peukert
ab and
Johannes
Walter
*ab
aInstitute of Particle Technology (LFG), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Cauerstraße 4, 91058 Erlangen, Germany. E-mail: johannes.walter@fau.de
bInterdisciplinary Center for Functional Particle Systems (FPS), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Haberstraße 9a, 91058 Erlangen, Germany
cMax Planck Institute for the Science of Light, Staudtstraße 2, 91058 Erlangen, Germany
First published on 19th February 2024
An advanced design of the analytical ultracentrifuge with multiwavelength emission detection (MWE-AUC) is presented which offers outstanding performance concerning the spectral resolution and range flexibility as well as the quality of the data acquired. The excitation by a 520 nm laser is complemented with a 405 nm laser. An external spectrograph with three switchable tunable gratings permits optimisation of the spectral resolution in an order of magnitude range while keeping the spectral region broad. The new system design leads also to a significant reduction of systematic signal noise and allows the assessment and control of inner filter effects. Details regarding the very large signal dynamic range are presented, an important aspect when studying samples in a broad concentration range of up to five orders of magnitude. Our system is validated by complementary studies on two biological systems, fluorescent BSA and GFP, using the commercial Optima AUC with absorbance detection for comparison. Finally, we demonstrate the capabilities of our second generation MWE-AUC with respect to multiwavelength characterisation of gold nanoclusters, which exhibit specific fluorescence depending on their structure. Overall, this work depicts an important stepping stone for the concept of multiwavelength emission detection in AUC. The MWE-AUC developed, being to our knowledge the first and sole one of its kind, has reached the development level suitable for the future in-depth studies of size-, shape- and composition-dependent emission properties of colloids.
In this regard, analytical ultracentrifugation (AUC) stands out as a particularly powerful technique for multidimensional colloid characterisation. AUC capitalises on the principles of sedimentation and diffusion in a centrifugal field to analyse the distributions of mass, size, and shape anisotropy of particles and macromolecules in solution with outstanding accuracy and reproducibility. The versatility of AUC, offering a comprehensive view on the structural heterogeneity of a system, is highlighted by its applicability to a wide variety of colloids including nanoparticles,1–3 polymers,4–6 and biomolecules.7,8 Its ability to discern minute variations in particle properties and interactions makes it invaluable for unravelling the complexity inherent in these systems. Moreover, having the sample in the native solution environment preserves the colloid's integrity and minimises artefacts, which can arise from sample preparation.
In the past 20 years, AUC experienced a significant boost for its application in characterising colloids with increasing complexity by implementing new hardware and data analysis tools. Modern AUCs can feature wavelength-resolved absorbance, interference as well as integral fluorescence detection. In addition, a multiwavelength absorbance detection system has significantly extended capabilities for multidimensional characterisation of nanoparticles and macromolecules.4,9–15 Recently, our group presented a multiwavelength emission detector (MWE-AUC),16,17 which permits measurements of sample fluorescence spectra as a function of the sedimentation coefficient. For the first time, the fluorescence features could be directly linked to the sedimentation coefficient and in this way to the particle size. This first generation (Gen1) MWE-AUC setup featured a miniature spectrometer with a fixed spectral resolution and excitation at 518 nm only. A critical downside of the Gen1 MWE-AUC was the presence of some excess signal variations. While such systematic noise contributions can in principle be corrected via dedicated algorithms in data analysis software such as SEDFIT,18,19 it hampers possibilities for multiwavelength analysis due to the necessity to perform such corrections using additional fit parameters for each wavelength, which is computationally expensive.
In this paper, we report on the design of a second generation (Gen2) MWE-AUC setup with improved performance further extending its applicability for investigations of complex systems, which require high spectral resolution and straightforward multiwavelength analysis. First, the hardware developments concerning the optical and mechanical design, excitation laser options, sample fluorescence detection, and new sample cells as well as extended software features are considered. New aspects of system alignment and calibration are also discussed. Next, the characterisation of the Gen2 MWE-AUC performance especially concerning signal linearity and noise, dynamic range, and the possibility to control inner filter effects are reported. Using fluorescein iso-thiocyanate conjugate of bovine serum albumin (F-BSA) and green fluorescent protein (GFP) as two representative macromolecules, results of sedimentation velocity experiments are validated by complementary measurements using the Optima AUC as a commercial machine with the absorbance detection system. Finally, we demonstrate the efficiency of the MWE-AUC for the characterisation of gold nanoclusters (AuNCs) with respect to their hydrodynamic and fluorescence properties.
Assuming the AuNCs to be of spherical shape, the continuous c(s) model with fixed frictional ratio of 1.0 and floating partial specific volume (starting the fit with a value of 0.4) implemented in SEDFIT was used for the evaluation. The confidence level for the second derivative regularisation was set to 0.683. The fitted parameters were then used as input for the 2D analysis to speed up calculations in our custom code. The best-fit partial specific volumes were 0.547 cm3 g−1 and 0.63 cm3 g−1 for excitation at 405 nm and 520 nm, respectively. For the 2D analysis, we performed consecutive c(s) analyses for all wavelengths rather than just for certain wavelengths as done in SEDFIT based on our previous work24 using the algorithms developed by Schuck et al.18,25 Regularisation was performed using the second derivative and a confidence level of 0.683. The partial specific volume was taken constant for all wavelengths. A sedimentation coefficient resolution of 150 values was used, and the wavelength step was 1.5 nm. For analysis in SEDPHAT (version 14.0), we used the “Species Analysis” model and performed a single fit prior to the global fit (including floating meniscus and time as well as radial noise fitted).
These modifications proved to successfully dampen vibration-inducted fluctuations of the detected fluorescent signal. Furthermore, no light-spot misalignment due to steel-ring deformation under vacuum has been observed now using a miniature wireless camera; but a 2 mm shift of the focal plane in z-position is still apparent under operation conditions. This effect is caused by the warping of the heat sink when vacuum is applied.26 However, as the chamber deformation is well reproducible, it can be easily compensated by tuning the z-stage. To simplify optimisation of the z-position of the confocal plane in the sample and, in consequence, of the signal collection volume under operating conditions, the manual translation z-stage of Gen1 MWE-AUC has been replaced by a motorised stage with computer software control. This allows to perform z-scans during rotation in vacuum for all samples in the rotor, which showed to be very important for control and prevention of inner filter effects (for details it is referred to the section on the inner filter effects below). Usually, all the cells in the rotor have very similar z-position of the sample if the same cell components, i.e., housings, centrepieces, windows, are used. Nevertheless, if necessary, the z-position can be individually adjusted for each cell in the rotor.
Changing of the excitation wavelength can be performed by reconnecting the single-mode fibre between the two laser-to-fibre coupling units, each one optimised for a particular laser, and by placing the corresponding spectral long-pass filter before the multi-mode fibre in the signal-coupling unit. Usually only optimisation of the laser-to-fibre coupling and neither realignment nor radial recalibration are necessary; but at least a check of the beam overlap is recommended.
To minimise the contribution of the broadband background (amplified spontaneous emission from the laser diode chip) in the spectral region close to the cut-off of the long-pass filter in the signal-coupling unit, the lasers are normally operated at a constant high current of 150 mA. A manually tuneable neutral-density disk filter before the fibre-coupling unit is then used as a variable optical attenuator for optimisation of the excitation light power. If necessary, computer software control of the laser diode current can also be used to control the excitation power for the cells in the rotor individually. Two additional spectral band-pass filters have been installed for laser-line cleaning before the fibre-coupling units, which can also be placed between the mirrors M1 and M2 in the scanning unit, if it becomes necessary to suppress also the fluorescence or Raman scattering in the single-mode fibre.
The use of a 200 μm core fibre in Gen2 MWE-AUC increases the signal confocal spot size to 135 μm, by a factor of 4, while the size of the laser beam remains the same. In this case, the laser beam spot remains within the signal confocal spot even for drifts of about 50 μm and coupling of the fluorescence signal into the fibre does not change assuring strongly reduced radius-dependent, time-invariant signal distortions during radial scans. Furthermore, the large fibre core size increases the confocal depth from about 0.7 mm to 1.5 mm making it comparable with the depth of the 3 mm measurement cell. In consequence, the fluorescence signal from nearly the full sample volume is collected rather than only from a part of it, which leads to a corresponding increase of the signal amplitude.
As the excitation-laser beam profile, being close to the fundamental mode for both 405 nm and 520 nm lasers, has very low divergence (estimated Rayleigh length ∼2 mm), its spot size is very similar over the depth of the confocal volume in the sample. Hence, the radial resolution of ∼40 μm remains practically the same as for the old small-core fibre used in the Gen1 MWE-AUC, because the radial resolution is defined now by the excitation laser spot diameter only rather than by the convolution of the two beam spots, one having a flat-top profile (cf. ESI, Fig. S5†). Notably, this is quite different from the fluorescence-detection system (AU-FDS),27,28 where the numerical aperture of the excitation beam and of the fluorescence signal collection are similar and determine together the radial resolution.
Periodical control of optics alignment can be performed in a straightforward manner by using an additional common camera at the cell position in the AUC chamber and a dedicated light source. Instead of an additional laser pointer coupled in the multi-mode fibre from the spectrograph side to simulate back-propagation of the fluorescence signal, just a common 20 W white LED floodlight illuminating the bent fibre in the transparent 900 μm buffer from the side can be used without need of any intervention to the fibre connections. Light intensity coupled mainly in the cladding modes is quite low but still sufficient for a complementary metal oxide semiconductor (CMOS) camera with exposure times of about 200–500 ms. Accordingly, the power of the excitation laser must be strongly reduced by setting its current to just a few mA in the CW operation mode. The large sensor size of the CMOS camera used to observe the beams in the focal plane allows the control of the beam spot overlap in the full radial scan range. Mounting the CMOS camera on a manual translation stage enables the check of the beam shape along the z-axis in a few mm region. Control of the beam overlap is strongly recommended each time the scanning unit has been accidently touched during rotor installation in the chamber.
A multi-mode fibre couples light into the spectrograph, which is positioned outside the vacuum chamber, as before in the Gen1 MWE-AUC. The width of the entrance slit, located right behind the fibre output facet, is usually optimised for a minimal decrease of the signal amplitude but can be made smaller to improve the spectral resolution at the expense of a signal amplitude decrease. The EMCCD camera with 1600 × 200 pixels is usually operated in the full vertical binning mode providing spectral data with 1600 points. When no multiwavelength characterisation is necessary, and just the total fluorescence signal is to be measured similar to the AU-FDS, binning along both dimensions over the pixel area, covering the full signal spectrum on the sensor chip, is possible. Due to a higher quantum efficiency of the EMCCD camera (>80% in the 420–800 nm region vs. ∼40–20% for best photomultipliers) and the low binning and read noise, this approach can lead to similar or even better sensitivity performance compared to the AU-FDS system with a spectral filter and a photomultiplier detector.
The signal dynamic range of the 16 bit analogue-to-digital converter (ADC) can be additionally extended by switching the camera electronic gain from 1 electron per count to 4 electrons per count. The sensor-internal electron multiplication is not usually used because it hardly improves the signal-to-noise ratio (SNR) of a reasonably strong signal when the read noise is negligible and rather makes it worse by the excess multiplication noise. Deep sensor cooling allows exposure times up to 500 ms without an increase of signal background offset by the dark current signal above the noise level. The camera is usually operated in the exposure trigger mode. To avoid sensor illumination outside the camera exposure time window, the train of laser trigger pulses is additionally gated by the camera exposure signal using simple custom-made electronics (cf. ESI, Fig. S1 and S2†).
The step size and movement linearity of the step motor, providing the radial scan, and the absolute radial position can be evaluated using the known gap layout of the calibration disc. The estimated calibration accuracy of the absolute radial position is ∼100 μm, which is determined mainly by the accuracy of the positioning of the calibration disk in the cell housing. Still, related positioning errors are insignificant as the error in the determined sedimentation coefficient will be <0.2%. Overall, step size and movement linearity are much more accurate.
The calibration cell was scanned with both 405 nm and 520 nm excitation lasers (cf.Fig. 3). The step size is practically identical, no non-linearity due to imperfections of the translation stage can be observed. A radial shift of ∼80 μm can be observed, which most likely is a consequence of optics realignment in a timespan of three months between the measurements.
Using this type of calibration, such potential radial shifts can be easily compensated for. As can be seen in Fig. 3a, the fluorescent acryl glass of type 2C01 provides a much weaker signal for the 405 nm laser because it was selected earlier for green excitation only. Another glass type, better suitable for multiwavelength operation, can be used if necessary.
Fig. 4 (a) Linearity check for five target concentrations of coumarin 153 diluted in ethanol. The signal intensity is given for the fluorescence at 540 nm. (b) Signal-to-noise ratio (SNR) over signal intensity for the target concentrations at 540 nm; the two dash lines indicate slopes of 1 and 0.5. Negative error bars are not shown in the logarithmic representation. For better illustration, the first data points of the two lowest concentrations at small exposure times can be found in the ESI† as a linear plot of the signal intensity (cf. Fig. S6†). (c) Comparison of the SNR between measured data for a single wavelength (540 nm) and integrated spectrum (485–650 nm) for the lowest target concentration (0.0001 mg L−1). |
The intensity-dependent relationship between SNR and signal amplitude is shown in Fig. 4b. The overlapping of the SNR values for different concentrations points out the excellent detector linearity. As expected, the SNR is linearly proportional to the signal amplitude for low counts (<10) being mainly determined by the camera read noise there. It becomes proportional to the square root of the signal amplitude at high counts (>100), when shot noise becomes the main noise component. At high signal amplitudes, it is important to avoid detector saturation by noise spikes.
For low concentrations or low exposure times, the signal becomes weaker and therefore noisier. Hence, the SNR can be improved either by increasing the camera exposure time up to ∼250 ms or even 500 ms or by averaging over several acquisitions as employed for the AUC with multiwavelength extinction detection, which takes more time due to additional digitalisation and data transfer cycles and is less efficient due to an increase of the overall read noise. If a further increase of the camera exposure time is not possible, e.g., due to detector saturation, additional averaging can be used but will lead to an increased measurement time, which can be problematic for sedimentation velocity runs but still applicable for sedimentation equilibrium experiments.
By virtue of the multiwavelength capabilities of our system, if similar to the AU-FDS high spectral resolution is not necessary, then the signal data can be integrated across different wavelengths to increase the SNR. As shown in Fig. 4c, an improvement in SNR by about a factor of 10 can be achieved for the lowest concentration by data integration over 487 sensor pixels in the spectral range of 485–650 nm (nearly full fluorescent band of the dye).
An improvement of the SNR for weak signals while keeping the spectral resolution is also possible by changing the ADC sampling rate from 1 MHz to 100 kHz, which results in a read-noise reduction from 7 electrons to 4 electrons rms, according to the camera specifications, at the expense of an increase of the read time from 1.6 ms to 16 ms.
In addition to the excitation-related inner filter effect, such disproportionalities can also be caused by self-absorption of the fluorescence, the secondary inner filter effect.38 This occurs usually on the blue side of the fluorescence spectrum when the absorption and emission bands of the sample overlap (cf. ESI, Fig. S7†). The secondary inner filter effect is typically much weaker than the primary inner filter effect and can therefore be observed especially, when the extinction at the excitation wavelength is comparable or even weaker than that for the fluorescence, which is usually the case when the excitation is far aside of the absorption peak. Then, the light emitted from the depth of the sample can be reabsorbed before leaving the cell, which weakens the detected signal. Care should be taken especially for complex colloids where the absorption and fluorescence bands of different components might overlap.
As sedimentation results in changes of the local concentration, mainly dilution with sometimes a significant increase at the bottom due to back-diffusion, the relation between concentration and signal intensity might become quite non-linear due to the inner filter effects. That makes the interpretation of the measurement data during evaluation difficult or even impossible.
With the motorised z-stage added in the Gen2 MWE-AUC, so-called z-scans can be easily made any time during measurements. Being especially practical to perform prior to the measurement, z-scans make it very easy to determine whether the samples are in a suitable concentration range or not and to set the optimum measuring depth (z-position of the confocal volume in the sample). If the sample concentration is in an appropriate range, a mostly symmetrical signal profile is generated, which has its maximum in the middle of the cell.
However, if the sample is too concentrated, the inner filter effects make the profile of the z-scan asymmetrical and shift its peak (Fig. 5). To avoid this situation, either the sample must be diluted or the signal must be collected from a smaller z-range around or better before the signal maximum (on the maximum's right side in Fig. 5) with corresponding decrease of the signal amplitude. However, this approach can lead to distortions in the measured fluorescence profiles due to slight variations of the z-position of the confocal volume during radial scans, as the measurement takes place then in a region of a relatively strong signal gradient.
The secondary inner filter effect is illustrated in Fig. S8 in the ESI† using coumarin 153 samples excited at 405 nm by z-scans at the wavelengths of 455 nm and 470 nm. For a fixed excitation wavelength, different from the primary inner filter effect, the influence of the secondary inner filter effect can easily be avoided by the proper choice of the fluorescence wavelength.
Furthermore, radial and z-scans of different wavelengths were compared with each other (cf. ESI, Fig. S5 and S8†). As already shown by Wawra et al.,16 wavelength-independence could be confirmed. This allows the determination of useable measurement results for samples with homogeneous spectral broadening even at very high signal intensities that lead to camera saturation at the spectrum maximum by evaluation of the data in a spectral region of a lower signal at a different wavelength.
Furthermore, a better wavelength resolution is achieved using a spectrograph with tuneable gratings instead of the miniature spectrometer. Overall, data obtained by the Gen2 MWE-AUC exhibits significantly less, if any time-invariant and fluorescence-specific noise components as can be seen from the direct comparison of both generations depicted in Fig. 6. This opens up opportunities to perform efficient multiwavelength analysis of data as only radial-invariant noise needs to be accounted for during data analysis. Having shown the excellent wavelength reproducibility and linearity, we will report next the analysis results for three exemplary systems, i.e., two proteins F-BSA and GFP as well as AuNCs.
Fig. 6 Sedimentation velocity data demonstrating data quality improvement from (a) Gen1 MWE-AUC to (b) Gen2 MWE-AUC. (a and b) show the data of 9.0 μM F-BSA diluted in a 12 M tris and 15 M NaCl buffer, measured at 40000 rpm. The F-BSA sample was excited at 518 nm and 520 nm and its emission was evaluated at 550 nm and 555 nm for (a and b), respectively. (a) is adapted from Wawra et al.16 Copyright (2019) Nanoscale Advances. All raw data were analyzed using SEDFIT (version 16.1c) and plotted together with the best-fit profiles and respective residuals using Gussi (version 1.4.2). Data were analyzed with fluorescence corrections switched on and off for the Gen1 and Gen2 data, respectively. |
Fig. 7 Comparison of sedimentation coefficient distributions obtained using emission (straight line) and absorbance (dotted line) detection in the Gen2 MWE-AUC and Optima AUC, respectively. The 520 nm laser was used for excitation in the MWE-AUC measurements. F-BSA was diluted in a tris (12 M)/NaCl (15 M) buffer and was measured at 0.45 μM in both devices. F-BSA data was evaluated at 550 nm for the MWE-AUC. GFP was diluted in a glycerol/PBS buffer and was measured at 2.5 μM in the MWE-AUC (data are shown for emission at 570 nm) and 5 μM in the Optima AUC. The presence of glycerol led to a comparably high solvent density (1.057 g cm−3) and viscosity (1.9 mPas),22,23 which explains the small apparent sedimentation coefficients of GFP. All protein measurements were carried out at 40000 rpm and 20 °C. The fit results and residuals are shown in the ESI, Fig. S9.† |
In contrast to F-BSA, the sedimentation coefficient distributions for GFP show only one main peak which can be attributed to the monomer. Measurements made using the two machines overlap perfectly, which validates the accuracy of our MWE-AUC, when it comes to resolving hydrodynamic characteristics of macromolecules. The additional peak close to 0 S indicates the presence of free fluorescein and light-absorbing impurities with very little molar weight as can be observed with both detection systems.
After confirming the credibility of our measurements, GFP was additionally measured at different concentrations in the nanomolar range (cf.Fig. 8). A good data quality and consistent sedimentation coefficients distributions are retrieved for concentrations (1–100 nM) spanning two orders of magnitude (>three orders of magnitude when considering the data shown in Fig. 7). The additional peaks at larger sedimentation coefficients might originate from agglomerates of GFP with unlabelled BSA, an effect which apparently increases at higher relative BSA concentrations.
Fig. 8 Sedimentation coefficient distributions for GFP measured at 40000 rpm with the Gen2 MWE-AUC at several concentrations with an excitation at 405 nm. Measurement data were evaluated at 511 nm. Following similar procedure as Schuck et al.,39 GFP was diluted in a 1.5 μM BSA solution to prevent the adsorption at the cell windows.20 |
Based on our detailed studies of the detector linearity reported above, we expect that the measurement range can be extended to much lower concentrations in the pM range. Detailed investigations of the detection limit for strongly associating systems will be followed in subsequent work.
As shown in Fig. 9, the glutathione-stabilised AuNCs were measured at the two different excitation wavelengths. The derived 2D sedimentation coefficient–wavelength distributions are clearly different for the two excitation wavelengths and indicate that the sample contains a variety of AuNCs with different composition having respectively different absorption and fluorescent properties. Depending on the excitation wavelength, different species contribute to the overall fluorescence signal, which is resolved by the underlying sedimentation coefficients of the different species. Two species are apparent with sedimentation coefficients of 3.4 S and 3.9 S for an excitation at 405 nm, while only one species with a sedimentation coefficient of 4.0 S is observed for an excitation at 520 nm. The corresponding emission maxima are retrieved at about 800 nm, 705 nm and 740 nm for the 3.4 S, 3.9 S and 4.0 S species, respectively. Overall, the size-dependent fluorescence of AuNCs is a well-known property which can be resolved by our Gen2 MWE-AUC in a single experiment.
Fig. 9 2D analysis of sedimentation velocity experiment with AuNCs performed at 40000 rpm and 20 °C using two different excitation lasers with wavelengths of (a) 405 nm and (b) 520 nm. |
For the measurement at an excitation at 405 nm, an artefact shift for the 3.9 S species towards larger sedimentation coefficient is apparent as soon as the 3.4 S is observed at longer than 750 nm wavelengths. A possible explanation for this phenomenon is the fact that the data was analysed with a fixed frictional ratio and partial specific volume, while both species should have different shapes as well as densities due to the altering gold–glutathione composition.21 As the contribution of each species to the overall signal is wavelength dependent, this can induce shifts in the sedimentation coefficient distributions. This is supported by the observation that the wavelength shifts can be eliminated when the frictional ratio and partial specific volume are optimised manually instead of using the fixed frictional ratio of 1 and best-fit values for the partial specific volume (cf. Fig. S10a†). In addition, our hypothesis is supported by a global analysis at three selected wavelengths (700 nm, 760 nm, 825 nm) using the single species model in SEDPHAT. The analysis with three discrete species provided sedimentation coefficients of 3.35 S, 3.97 S and 4.82 S, which are in line with the findings from the multiwavelength analysis.
Besides, the comparably broad distribution observed for the excitation at 520 nm indicates that there are presumably more than one species present, which would also explain the shift in the emission maximum when comparing the species to the one found at 3.9 S for the excitation at 405 nm. Multiple species with only slightly varying sedimentation coefficients are hardly distinguishable when using second derivate regularisation as it is currently implemented in our 2D analysis procedure. Remarkably, at least two species are observed when considering the non-regularised 2D distribution (cf. Fig. S10b†). Therefore, future work needs to focus on extending the capabilities of data analysis, e.g., by implementing different regularisation schemes such as maximum entropy or Monte Carlo analysis, or by making use of established algorithms which permit altering partial specific volumes or frictional ratios as a function of the sedimentation coefficient such as the c(s, ff0)42 or discrete species method implemented in SEDFIT or the 2DSA43 and PCSA44 techniques implemented in UltraScan3, to allow for an in-depth multidimensional analysis of structure–property relationship of AuNCs using MWE-AUC.
Being complementary to other AUC detection systems, our ready-for-use Gen2 MWE-AUC, being to our knowledge the first and sole one of its kind, constitutes an important next step for the multidimensional characterisation of complex colloids, now also comprising size-, shape- and composition-dependent multiwavelength emission properties. Future work will thus mainly target the systematic and in-depth investigations of colloids making use of the manifold possibilities of the Gen2 MWE-AUC. This includes the investigation of the structure–property relations of particles and macromolecules including quantum dots and AuNCs.
To make use of the new possibilities offered by the MWE-AUC, current data processing algorithms must be upgraded to include all the specific features of the measurement data and of the samples to be investigated. Particularly, the dependence of the fit parameters on the sedimentation coefficient value, especially of the partial specific volume and frictional ratio, must be included to properly analyse strongly interacting macromolecules and particle interactions with specific optical footprints.
Global analysis schemes will give rise to more efficient multiwavelength analysis and might even allow coupling of data from different detection systems for deeper insights into structure–property relationships of colloids such as the size-dependent fluorescence quantum yield of quantum dots. For such investigations, possibility to measure the sample extinction at the excitation wavelength simultaneously with fluorescence would be very useful. Importantly, the optical efficiency of the MWE-AUC needs to be evaluated to retrieve quantitative data from such investigations. Besides, there are still several interesting subjects for further MWE-AUC performance improvements such as the increase of the signal-to-noise ratio by a decrease of the digitalisation rate or the use of on-sensor pixel binning over a large area as well as activation of electron multiplication in the EMCCD camera. The latter is important, when Raman detection is targeted, a possibility which is in principle available with our setup. A fast variable optical attenuator with computer software control would allow the setting of sample-specific excitation power for extending the concentration range. Finally, multiwavelength sample excitation could be used to study complex systems of particles with different absorption spectra.
Footnotes |
† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d3na00980g |
‡ Current affiliation: Boehringer Ingelheim Pharma GmbH & Co. KG, Innovation Unit, Analytical Development Biologicals, Birkendorfer Straβe 65, 88400 Biberach an der Riβ, Germany. |
§ Current affiliation: Carl Zeiss Vision GmbH, Turnstraβe 27, 73430 Aalen, Germany. |
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