Johannes Kiefer

Raman spectroscopy in the near-infrared spectral range is commonly used in many application areas, including in the analysis of beverages, such as whisky. For this purpose, lasers with 785 or 1064 nm wavelength are very popular. In the studies presented here, we compare the two wavelengths in the context of whisky analysis and authentication. Our results reveal that both excitation wavelengths have benefits and drawbacks. For example, 1064 nm is capable of performing through-container measurements even in green glass bottles, which is not possible with 785 nm. On the other hand, the moderate fluorescence signal generated with 785 nm makes it possible to determine a variety of additional parameters including the type of cask in which the whisky was matured.

Raman spectroscopy is gaining ever increasing attention in the analysis of food products and especially of beverages such as spirits. Its capability to analyze samples through the wall of glass and polymer bottles is a particularly interesting feature (1–3). When valuable spirits (such as single malt Scotch whisky that was aged in casks for decades) need to be authenticated, analysis using methods that require sampling are not the first choice, because opening the bottle would mean a significant loss in value. Therefore, many techniques such as gas chromatography (GC), mass spectrometry (MS), Fourier-transform infrared (FT-IR) spectroscopy, X-ray fluorescence, and the recently developed nanoplasmonic tongue cannot be used despite their demonstrated capability for whisky authentication (4–11). As a result, Raman spectroscopy is a suitable alternative in this context.

The laser wavelength (λ) used in a Raman experiment is a crucial parameter, because it has a manifold impact. The Raman scattering cross section depends on λ-4, which means that a shorter wavelength results in a higher signal intensity. Moreover, this is further enhanced by the excellent quantum efficiency of commercially available detectors in the visible spectral range. On the other hand, owing to the higher photon energy, a shorter wavelength increases the probability certain species in the sample that will photodissociate and generate laser-induced fluorescence that could completely mask the desired Raman signal (12). Moreover, if the measurement needs to be done though the original sample container, the transmission properties of the bottle need to be considered as well. Figure 1a displays the UV-vis transmission spectrum of a typical whisky sample. It exhibits a strong and broad absorption band in the UV with a wing that lasts up to about 700 nm. The figure also shows the wavelengths of the typical lasers used in Raman spectroscopy instruments. It becomes clear that excitation at wavelengths shorter than ~700 nm results in significant levels of fluorescence as electronic transitions in certain molecules are excited resonantly. As will be shown later, even with a 785-nm laser the spectrum will contain moderate fluorescence signals. Figure 1a also shows a non-negligible absorption around 1064 nm, which is a common Raman wavelength as well. However, this absorption is not associated with electronic excitation. Instead, this band originates from vibrational overtone and combination bands (13) and hence its excitation does not result in laser-induced fluorescence signals.

Published data suggest that even an excitation wavelength of 830 nm results in noticeable fluorescence signatures (1). From the absorption spectrum in Figure 1a and the above discussion, a schematic energy level diagram can be developed, as shown in Figure 1b. The figure shows that wavelengths shorter than ~850 nm yield electronic excitation and subsequent fluorescence emission from the vibrational ground state of the excited electronic state. Photons at longer wavelengths (such as 1064 nm) cannot excite the molecules in the sample electronically; because of this, they cannot fluoresce. A detailed theoretical and mathematical account of the underlying scattering and fluorescence phenomena can be found in the literature (14,15).

There have been a number of Raman studies of whisky samples using a variety of laser wavelengths, mainly in the near-infrared spectral range. Because whisky commonly contains natural or artificial colorants (caramel color), the interference from fluorescence emission obscures the inherently weak Raman signal when lasers in the visible or ultraviolet are used. Because of this, an 830-nm diode laser was used for spatially offset Raman spectroscopy (SORS) in whisky bottles (1). They achieved high sensitivity detection of minor species, allowing the authentication of the whisky. The common 785-nm excitation was employed by Backhaus (16) and Kiefer and Cromwell (2). This work showed that data analysis by chemometrics and machine learning tools enable whisky classification. Vaskova’s team demonstrated methanol detection in whisky using 785-nm lasers while Goodacre’s team used 1064–nm lasers (3,17,18). However, a systematic comparison of different near-infrared Raman schemes to identify the most versatile approach for practical and potentially industrial whisky analysis has not been performed.

This article aims to discuss the benefits and drawbacks of using Raman spectroscopy at different near-infrared excitation wavelengths. We applied Raman spectroscopy with 785– and 1064–nm excitation to 83 different whisky samples (mainly Scotch single malt whiskies, two German single malts, three Irish whiskies, one American whisky, and four blended Scotch whiskies). The measurements were carried out through the glass walls of the container bottles (see Figure 2) using Raman devices from Avantes (785 nm) and Anton Paar (785 and 1064 nm), both equipped with fiber probes. For each sample, 10 spectra were recorded. The details of the data analysis have been outlined in our previous work (2). In brief, principal component analysis (PCA) was used to classify the samples and partial least squares regression (PLSR) was employed for the quantitative analysis. The methods were implemented in Matlab using the functions “princomp“ and “plsregress.”

The first aspect investigated was the ability to perform the measurements through the container wall. Whiskies (as well as other beverages) are typically contained in glass bottles made of clear, green, or brown glass. Colored glass results from adding metal oxides such as iron oxide (pure and in combination with others) during the production process, and the metal ions yield a characteristic optical absorption spectrum. Similar to the phenomena discussed in the introduction (see Figure 1b), colored glass can fluoresce upon optical excitation. Previous experiments (1,3) have shown that 785 and 830 nm, respectively, excite significant levels of fluorescence inside green and brown glass. Moreover, due to the strong absorption inside the glass, not much of the laser light will reach the actual sample. Therefore, these wavelengths are not suitable for through-container analysis when a spirit is contained in colored glass bottles. On the other hand, 1064–nm radiation as well as the corresponding Raman signal is transmitted through green glass. Hence, 1064–nm Raman spectroscopy has wider applicability in this respect.

We note that basically all the sharp signatures in the Raman spectra of the whiskies (see Figure 3 for an example) can be assigned to the vibrational modes of ethanol. The assignment of the main peaks is summarized in Table I using a previous study (19) as a benchmark. The peak positions agree well within the limited spectral resolution of the instruments. The ethanol signatures can be used to quantify the amount of alcohol in the samples.

The second aspect studied was the capability to classify the samples. In previous work (2), it has been shown that PCA is suitable to determine the cask type a whisky was aged in. This can be a key in the authentication of whisky. An important feature in this classification, however, was the presence of moderate but characteristic fluorescence signals in the data. These fluorescence signals are not present in the Raman spectra recorded with the 1064–nm laser, as shown in Figure 3. As a consequence, feeding the 1064–nm spectra into the PCA algorithm did not result in a classification of the casks. The scores plots obtained from the data acquired with 785 and 1064 nm are displayed in Figures 4a and 4b, respectively. Note that only those data points associated with whiskies that could clearly be assigned to one cask type are shown. Whiskies that were matured in multiple casks (such as sherry and port) are not included for clarity. The plot in Figure 4a reveals that the excitation at 785 nm facilitates the distinction of the different cask types. On the other hand, the score plot of the Raman spectra acquired with the 1064–nm laser mainly provides information about the ethanol content. We note that the higher principal components in the 1064–nm data set were not meaningful because they essentially represent noise.

The potential to do a quantitative analysis was tested, examining the alcohol content. For this purpose, PLSR was used. Figure 5 shows the PLSR model employed to two components and resulted in strong accuracy for all data sets. The plot shows that the results obtained from the 1064–nm data set are slightly more accurate, because the scattering of the data points is reduced. The presence of the fluorescence background in the 785-nm spectra may be the reason for the observed behavior. Its impact can certainly be minimized by employing a baseline correction prior to the PLSR analysis. This was not done here because we wanted to keep the method as simple as possible and hence the raw data were evaluated.

In addition, previous experiments (3) have shown that 1064 nm excitation is well suited for detecting methanol in whisky. In addition to the points described above, the ability to determine the presence of methanol and artificial colorants was tested in terms of caramel color. The results of the entire comparison are summarized in Table II. The individual aspects have been graded with a plus (+) and minus (–) to allow a straightforward qualitative assessment for decision-making in a data or instrument procurement process

In conclusion, a detailed comparison of Raman spectroscopy with near-infrared lasers at 785 and 1064 nm revealed the particular advantages and disadvantages of detecting methanol in various whiskies. Both approaches demonstrate that they are capable of quantitative measurements such as for the determination of the ethanol or methanol content. Moreover, both can be applied through the wall of clear glass bottles. The 1064–nm wavelength can also measure through green glass, which is not possible with 785 nm. In the case of brown glass, both methods failed. The spectra recorded with 785 nm contain a moderate level of fluorescence signals, which turn out to carry important additional information. These signatures enhance the capability of Raman spectroscopy for authentication and a wider qualitative analysis, for example with respect to determining the cask type and the presence of artificial colorants. Overall, the combination of Raman and fluorescence signals can draw a detailed picture of a whisky and can help to identify adulterated or counterfeit products. For example, producing fake whisky may yield a fluid with very similar properties in terms of alcohol content, color, and taste using artificial colors and flavors. However, because the spectra are sensitive to the cask type and the aging period, they are very difficult to produce artificially. Therefore, Raman spectroscopy in the near-infrared is a powerful tool for the analysis of whisky. The increasing number of handheld, easy-to-use instruments on the market makes it likely that it will become the standard in the whisky industry in the
foreseeable future.

The authors would like to thank Avantes BV (Apeldoorn, The Netherlands) and Anton Paar Germany GmbH (Ostfildern-Scharnhausen, Germany) for the instrument loans.

D.I. Ellis, R. Eccles, Y. Xu, J. Griffen, H. Muhamadali, P. Matousek, I. Goodall, and R. Goodacre, 

https://doi.org/10.1038/s41598-017-12263-0

D.I. Ellis, H. Muhamadali, Y. Xu, R. Eccles, I. Goodall, and R. Goodacre, 

C.N. Rhodes, K. Heaton, I. Goodall, and P.A. Brereton, 

A. Wanikawa, K. Hosoi, T. Kato, and K. Nakagawa, 

J.S. Garcia, B.G. Vaz, Y.E. Corilo, C.F. Ramires, S.A. Saraiva, G.B. Sanvido, E.M. Schmidt, D.R. J. Maia, R.G. Cosso, J.J. Zacca, and M.N. Eberlin, 

A.C. McIntyre, M.L. Bilyk, A. Nordon, G. Colquhoun, and D. Littlejohn, 

P. Wisniewska, T. Dymerski, W. Wardencki, and J. Namiesnik, 

C.A. Shand, R. Wendler, L. Dawson, K. Yates, and H. Stephenson,

G. Macias, J.R. Sperling, W.J. Peveler, G.A. Burley, S.L. Neale, and A.W. Clark, 

J. Kiefer, N. Ebel, E. Schlücker, and A. Leipertz, 

Molecular Physics and Elements of Quantum Chemistry

A. Backhaus, P.C. Ashok, B.B. Praveen, K. Dholakia, and U. Seiffert, “Classifying scotch whisky from near-infrared Raman spectra with a radial basis function network with relevance learning,” presentation at the 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2012, (2012), 411–416.

H. Vašková and M. Tomeček, MATEC Web of Conferences 210, 02035 (2018).

are with the University of Bremen in Bremen, Germany. Direct correspondence to: 

Articles

We compare the advantages and disadvantages of each laser wavelength.

 Whisky Analysis with Raman Spectroscopy in the Near-Infrared Spectral Range: Comparison of 785– and 1064–nm Excitation

Raman backscattering facilitates measurements in systems with limited optical access. In such experiments, spatial filtering is of paramount importance to collect signals only from a well-defined probe volume. In the present work, a straightforward numerical approach is presented to estimate the performance of a spatial filter in a given application. A systematic investigation is carried out for an experimental system using a metallic mirror with a hole acting as a spatial filter. In this configuration, a small hole results in poor spatial resolution but high signal intensity whereas a large hole yields good spatial resolution but low signal. It is shown that the approach allows the optimal hole diameter to be determined that offers a compromise between spatial resolution and signal intensity. Spatially filtered Raman backscattering measurements in a fed-batch stirred tank reactor are presented, where the conversion of citric acid is monitored.

	During the last few decades, Raman spectroscopy has become an important diagnostic tool in many research areas, both in industry and academia. It offers the possibility for nonintrusive determination of the temperature and virtually all major species concentrations. Therefore, Raman applications can now be found in combustion and fuel research (1,2), monitoring of chemical and biotechnological reactors (3,4), arts and archaeology (5), and in the life sciences (6).

	A common way to apply Raman spectroscopy is to detect the signal in the direction perpendicular to the laser beam. A benefit of this arrangement is the simple scattering geometry and the resulting well-defined measurement volume (the probe volume can be calculated by multiplying the dimension of the spectrometer slit with the inverse magnification of the signal collecting optical system). On the other hand, a disadvantage is that separate optical accesses for the laser beam and the signal collection are required. Many objects of interest, however, have limited optical access and, hence, there is a strong need for a keyhole technology. Raman backscattering is a potential solution to this problem.

	The classical use of backward-scattered Raman photons is light detection and ranging (LIDAR) for environmental and atmospheric investigations (7,8), but it has also been applied, for example, to plasma and engine diagnostics (9–11). In principle, a LIDAR system consists of a transmitter (pulsed laser and optics) and a receiver (telescope, detector, and computer). Laser pulses of a few nanoseconds are sent into the object of investigation, such as the atmosphere. The backscattered photons are collected by the telescope and are eventually analyzed. The delay time between the start of the laser pulse and the signal detection defines the location of the measurement; the pulse duration determines the spatial resolution. A review as well as a detailed description is given by Weitcamp (12). However, Raman LIDAR requires a pulsed laser source and precisely controlled signal detection timing. Moreover, the study of small objects, in which a spatial resolution of the order of millimeters or centimeters is needed, calls for ultrashort short laser pulses (for example, picoseconds). On the one hand, the shorter the pulse the better the spatial resolution. On the other hand, the shorter the pulse the worse the spectral resolution. Consequently, the applicability of Raman LIDAR is limited.

	Spatially filtered Raman backscattering spectroscopy is an alternative. Its main application is confocal Raman microscopy, in which a pinhole is placed at the confocal plane of the collecting lens to eliminate out-of-focus light (13). A disadvantage, however, is that supplementary optical components are necessary to ensure sufficient spatial filtering; otherwise, scattered light from the complete laser beam pathway is collected and falsifies the results. A second approach to spatially filtered Raman backscattering was introduced by Hug (14), which enables measurements without additional optics in the setup. It uses a pierced metallic mirror that reflects the signal toward the spectrometer and undertakes the task of spatial filtering at the same time. Physically speaking, the arrangement acts as a high-pass filter, which is known in the field of microscopy as the 

. A detailed theoretical description was given by Lauterborn and Kurz (15).

	In both the pinhole and the pierced mirror backscattering arrangement (see Figure 1 for a schematic comparison), it is difficult to estimate the performance of the spatial filter a priori. To overcome this problem, we present a straightforward numerical approach for the determination of the probe volume length. It uses only common geometrical optics and trigonometric equations. The method is used to investigate the effect of the hole diameter in the metallic mirror on the performance of the spatial filter. Thereafter, experimental results from Raman backscattering measurements in a fed-batch stirred tank reactor are presented as a potential application.

	In the classical backscattering setup (Figure 1a), the laser beam is reflected by a dichroic mirror (DC) while the backward-scattered light is transmitted. A spatial filter (SF) ensures that only photons from the area of interest can reach the spectrometer. Figure 1b shows the modified setup, including the mirror with a hole acting as spatial filter. The incident laser beam passes the hole and backscattered light is reflected at an angle of 45° towards the detection system. The determination of the measurement volume using a backscattering setup, however, is not straightforward.

	A possible experimental approach would be to introduce a thin target (for example, a glass plate or plastic foil) and move it along the laser beam while recording the scattered light as a function of the target position. A drawback of this method is that the setup has to be built first and may have to be modified should the experiment show that the measurement volume does not meet the specifications. Therefore, the a priori estimation of the length of the probe volume is desirable.

	The proposed method for estimating the probe volume length is based on a numerical approach that uses only geometrical optics equations for lenses (see, for example, Hecht [16]) and trigonometric relations. Figure 2 shows the simplified arrangement of optical components. The hole is indicated at position A. Since it was drilled at 45° in the experimental part of this work, the assumption of a circular shape in the model is justified. At position B, a lens is placed for collecting and collimating the signal. The distance 

 = 0 coordinate is exactly the focal length of the lens. A second lens (position C) focuses the collimated signal to the slit (position D). The distance between C and D is the focal length of the second lens. Note that there is a substantial difference between the setups in Figures 1a and 1b. In the setup shown in Figure 1a, the spatial filter consists of a plate that blocks part of the signal and a hole that transmits that part of the signal which is to be detected. This means that the bigger the hole, the worse the spatial resolution, but the higher the signal intensity. On the other hand, the hole in the mirror of setup Figure 1b acts as the opposite (basically as the plate in the setup shown in Figure 1a) since the transmitted signal will not reach the detector. Consequently, the bigger the hole, the worse the signal intensity but the better the spatial resolution.

	For the calculation, only photons emitted from the optical axis were considered, which is reasonable when only the length of the probe volume is of interest. However, it should be noted that the concept can easily be extended to three dimensions (3D). In Figure 2, three signal pathways are drawn starting at different positions 

 at the same angle α to the optical axis (

-value at the positions A–D can be computed as a function of 

 and α using the equation for thin lenses:

 is the focal length. From this equation, the incoming and outgoing beam of a thin lens have the relationship:

	where α and β are the incident and emergent angles, respectively; 

 is the distance from the optical axis; and 

 is the focal length. Using the distance of the hole from the ordinate, 

 and the focal lengths of the collimating and the focusing lenses, 

, respectively, yields a simple set of equations:

	To estimate the probe volume length from this set of equations, the starting position 

 is varied in small steps over a certain distance, and at every point 

 beams with systematically varied angle α are considered. For example, 

 can be varied from -20 to 20 mm in steps of 0.1 mm and for every step, the angle α can be varied from 0 to 90° in steps of 0.01°. For each individual pair of 

-values according to equations 3–6 are calculated. The geometric dimensions of the optical components are then used as boundary conditions to decide whether a beam emitted at 

 and α actually reaches the detector. For instance, if a signal photon has the 

 = 30 mm while the lens radius is only 25 mm, the signal photon will not reach the spectrometer, and therefore it is not counted. Counting the detected signal photons as a function of 

 yields an estimate of the probe volume shape along the optical axis.

	A systematic investigation was carried out using the method described above. For this purpose, the focal lengths of the lenses were set as 

 = 200 mm. The lenses had diameters of 25 mm each and the distance between them was 

 = 300 mm. The slit had a width of 0.1 mm, and the hole was placed at 

 was varied between -20 and 20 mm, and the angle α was varied between 0 and 20° in steps of 0.002°. Angles larger than 20° were not considered to save computational time. The corresponding beams would have missed the first lens anyway.

	Figure 3 displays the normalized intensity distributions for systematically varied hole diameter. 

 means the number of detected photons for each position along the x-axis. The individual profiles were normalized by dividing them by their maximum value to improve the comparability. The dashed line in Figure 3 represents the case without a spatial filter, that is, a hole diameter of zero. It can be clearly seen that this case results in signal being collected for each position along the considered line. In other words, the spatial resolution is poor because the signal reaching the detector comes from a wide region. The solid lines in Figure 3 are the profiles for different nonzero hole diameters. The values were varied between 1 and 15 mm in steps of 1 mm. A diameter less than 1 mm is not useful because the laser beam needs to be able to pass through this hole in an experiment. The solid line profiles show that the region from which the signal can reach the detector becomes well-defined and finite whenever the spatial filter is present. The range of 

-values with a signal decreases with increasing hole diameter.

	To visualize the effects more clearly, Figure 4 illustrates the intensity and the probe volume length as function of the hole diameter. For the intensity, the profiles in Figure 3 have been integrated without initial normalization. The probe volume length was determined as the difference between the two 

 values limiting the range of signal collection. The most significant signal intensity drop is between a hole diameter of 0 and 1 mm as we move from signal collection without spatial filtering to the filtered scenario. The same observation is made for the probe volume length. Increasing the hole diameter further reduces the intensity and length, but rather moderately. This indicates that in the considered setup, a hole diameter of a few millimeters is sufficient to reduce the probe volume to a few millimeters and maintain reasonable signal levels. A hole diameter of about 5 mm also seems best suited from an experimental point of view because it can align the laser beam through the hole without producing a lot of elastic scattering from the surfaces.

	For an experimental demonstration, a mirror with a 5 mm hole was prepared. The mirror used was a simple cosmetic mirror and the hole was drilled through it at an angle of 45°. The setup was the same as the one in Figure 1b. A 532-nm continuous wave laser was used as the light source. The signal was collected and focused on the slit by achromatic lenses. Using the numerical a priori approach, a probe volume length of 2.4 mm was determined. Details of the Raman equipment used can be found in a previous paper (17).

	The experiments were performed inside a stirred tank reactor, where the fed-batch conversion of citric acid with sodium hydroxide was monitored. The reactor had walls made from Perspex (acrylic sheet) so that the Raman measurement could be carried out directly through the wall. With the spatial filtering technique described beforehand, it was possible to precisely locate the measurement volume inside the vessel. This is an advantage compared to commercial fiber-based Raman probes. Such probes usually collect the Raman signal that is generated at distances of a few millimeters from the collecting lens. Hence, the probe needs to be immersed into the reacting fluid and the method can no longer be considered nonintrusive.

	The reactor was filled with 1 L of citric acid solution (0.5 mole/L), and a continuous flow of sodium hydroxide solution (0.67 mL/s) was added while stirring the mixture. Raman spectra were recorded every 5 s for a period of 1800 s. The spectra obtained as a function of time are displayed in Figure 5a. The broad band between 3000 and 4000 cm

 is attributed to the OH stretching vibrations of water and remains almost constant. On the other hand, systematic changes over reaction time are clearly visible around 3000 cm

, see Figure 5b. This behavior is partly surprising. Upon the addition of sodium hydroxide, the carboxylic acid groups in citric acid are deprotonated one after the other. This explains the change in the 1710 cm

 band, which is assigned to C=O double bond vibrations (18). In the deprotonated carboxylate groups, the net negative charge is delocalized in the O-C-O moiety and, thus, a classical C=O double bond is absent. As a consequence, the C=O peak decreases when sodium hydroxide is added. 

 results from CH stretching vibrations. The two CH

 groups in citric acid are not involved in the chemical reaction. Hence, the significant change in the Raman band is unexpected. A possible explanation may be that the charge distribution changes across the entire molecule when the carboxylic acid groups are deprotonated. The redistributed charge may affect the polarizability of the CH bonds and thus reduce the Raman activity. This would explain the observed behavior. The detailed analysis of this phenomenon, however, is not the scope of the present work.

	The inset in Figure 5b illustrates the intensity changes of the 1710 and 2950 cm

 peaks as a function of reaction time. It can be seen that the curves are qualitatively almost identical-initially a rather straight line until the final constant value is reached after ~1500 s. Note that the intensity axis is logarithmic. This means the signal intensity initially decreases exponentially. After the entire reactant is converted, the signal intensity remains constant.

	In conclusion, a straightforward numerical approach to estimate the performance of a spatial filter in Raman backscattering spectroscopy has been proposed. A systematic investigation was carried out for an experimental system using a metallic mirror with a hole acting as the spatial filter. The hole diameter was varied systematically to unravel its influence on the performance of the system. A small hole results in poor spatial resolution but high signal intensity whereas a large hole yields good spatial resolution but low signal. It was shown that the approach allows for determining the optimal hole diameter that offers a compromise between spatial resolution and signal intensity. Eventually, spatially filtered Raman backscattering measurements in a batch stirred tank reactor were presented. The chemical conversion of citric acid with sodium hydroxide was monitored via the Raman spectra recorded from a probe volume with a length of ~2.4 mm, which was located in the 1-L reactor volume.

	The authors thank Professor Frank Beyrau and Professor Thomas Seeger for their helpful discussions. They also gratefully acknowledge financial support for part of this work from Deutsche Forschungsgemeinschaft (DFG, Grant KI1396/4-1).

Laser Diagnostics for Combustion Temperature and Species

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 is with Technische Thermodynamik at the Universität Bremen in Bremen, Germany, the School of Engineering at the University of Aberdeen in the United Kingdom, and the Erlangen Graduate School of Advanced Optical Technologies at the Universität Erlangen-Nürnberg in Erlangen, Germany. 

 is with the School of Engineering at the University of Aberdeen. 

 is with the Technische Thermodynamik, at the Universität Bremen. Direct correspondence to: 

A straightforward numerical approach to estimate the performance of a spatial filter in Raman backscattering spectroscopy has been developed. This approach enabled the authors to determine an optimal hole diameter that balances spatial resolution and signal intensity.

Johannes Kiefer

Articles

Whisky Analysis with Raman Spectroscopy in the Near-Infrared Spectral Range: Comparison of 785– and 1064–nm Excitation

A Priori Performance Estimation of Spatial Filtering in Raman Backscattering Experiments