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Hadamard-transform fluorescence excitation-emission-matrix spectroscopy Nicholas L P Andrews, Travis Ferguson, Alana M. M. Rangaswamy, Adam Bernicky, Niklas Henning, Alexander Dudelzak, Oliver Reich, Jack A. Barnes, and Hans-Peter Loock Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b02400 • Publication Date (Web): 18 Jul 2017 Downloaded from http://pubs.acs.org on July 20, 2017

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Analytical Chemistry

Hadamard-transform Fluorescence Excitation-emission-matrix Spectroscopy N.L.P Andrews1, T. Ferguson1, A.M.M. Rangaswamy1, A.R. Bernicky1, N. Henning1, A. Dudelzak1,2, O. Reich3, J.A. Barnes1, H-P. Loock1* 1 Department of Chemistry, Queen’s University, Kingston, ON, K7L 3N6, Canada 2 GasTOPS Ltd., 1011 Polytek Street, Ottawa, ON, Canada K1J 9J3, Canada 3 innoFSPEC, Physical Chemistry, University of Potsdam, Potsdam D-14476, Germany

Abstract: We present a fluorescence excitation emission spectrometer with superior data acquisition rates over previous instruments. White light from a white light emitting diode (LED) source is dispersed onto a digital micromirror array (DMA) and encoded using binary n-size Walsh functions (”barcodes”). The encoded excitation light is used to irradiate the liquid sample and its fluorescence is dispersed and detected using a conventional array spectrometer. After exposure to excitation light encoded in n different ways, the 2-dimensional EEM spectrum is obtained by inverse Hadamard transformation. Using this technique we examined the kinetics the fluorescence of rhodamine B as a function of temperature, and the acid driven demetallation of chlorophyll-a into pheophytin-a. For these experiments EEM spectra with 31 excitation channels and 2048 emission channels were recorded every 15 seconds. In total, data from over 3000 EEM spectra were 𝒏𝒏(𝒏𝒏+𝟏𝟏) -fold over conventional included in this report. It is shown that the increase in data acquisition rate can be as high as 𝟐𝟐 EEM spectrometers. Spectral acquisition rates of more than two spectra per second were demonstrated.

1. INTRODUCTION Fluorescence spectroscopy is a highly sensitive, nearly background-free technique for chemical detection, limited mainly by the fluorescence quantum yield of the analyte and the complexity of the matrix, which may produce interferences, quenching or autofluorescence. Fluorescence detection is typically achieved by either singleline UV excitation and dispersion of the entire fluorescence emission spectrum (e.g., laser induced fluorescence, LIF) or by tuning the excitation source over a wide wavelength range and detecting the entire spectrum of emitted light as a function of excitation wavelength with a broad band detector (photoluminescence excitation spectroscopy). In liquid samples excitation and emission bands are broad, making it difficult to distinguish fluorophores in mixtures. Excitation emission matrix (EEM) spectroscopy combines both techniques. The excitation wavelength is scanned and an EEM is produced by recording a fluorescence emission spectrum at each of the many excitation wavelengths. A two-dimensional spectrum is thereby generated that allows analytes to be distinguished in a mixture of fluorophores by separating broad fluorescent features into key spectroscopic components that may correspond to the individual fluorophores, in some cases.1

Determining the concentration of specific fluorophores within a mixture can prove complicated, especially when the broad fluorescence peaks overlap in the EEM. This problem can be addressed using multivariate data analysis, such as self-modeling curve resolution 2, positive matrix factorization3-4 or parallel factor analysis (PARAFAC).1, 5-6 Through such analyses the EEM spectra can be decomposed into its various components and hence number of fluorophores. 1 Currently, fluorescence EEM spectrometers typically use two monochromators to select the excitation and fluorescence wavelengths and direct the light to a broad-band photodetector, such as an avalanche photodiode or photomultiplier tube (PMT). The EEM spectrum is therefore acquired by sequentially measuring the intensity of each pair of excitation and emission wavelengths (λexc/λem). In an alternative spectrometer, the second monochromator and single channel detector are replaced with a spectrograph and array detector for higher data acquisition rates.7 Since array detectors tend to be less sensitive than broad-band photodetectors the latter instrument is less suitable for weakly fluorescing samples and/or requires longer integration times. In both designs, only a fraction of the light is used to generate the EEM spectrum - about 1/10,000 for the former and 1/100 for the latter design, depending on the required spectral resolution and spectral

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range. Commercial instruments are still quite slow, requiring up to an hour to acquire a single EEM spectrum. These instruments are therefore not capable of following reaction kinetics or to map EEM features across inhomogeneous samples in real time, although the kinetics of quenched reactions may still be analyzed.8-11 The time-resolution of fluorescence EEM measurements has been improved with a number of innovative approaches. Acousto-optical filters12 and linear interference filters13 greatly accelerate the selection of the excitation and emission wavelengths. Other approaches use fast switching and bright light sources, such as lasers, dye cells,14-15 and LEDs16 to excite at a smaller number of distinct wavelengths, and either monochromators or array detectors are used to obtain the dispersed fluorescence spectra. The EEM spectra acquisition rate can be as high as 5/s, but at a cost of very limited spectral resolution.14 In a different approach Muroski, Booksh, and Myrick dispersed the excitation light into the liquid sample to irradiate an area of about 4-5 mm with a vertical “rainbow” of light from 240 to 360 nm.17 The fluorescence was collected at 90 degrees to the excitation direction and the dispersion spectra arising from each of the points of this linear array were dispersed in the second (horizontal) dimension to create an image of the resulting EEM on a CCD array detector. Of more relevance to the present work Peng et al. realized a Fourier transform fluorescence EEM spectrometer that uses two Michelson interferometers – one each for the excitation and emission arm of the spectrometer.18 The system was capable of recording an EEM spectrum from (λexc = 425nm/λem = 580nm) to (550/750nm) in 41 seconds with a remarkable resolution of 81 cm-1. The complexity of the setup was somewhat reduced by Yuan et al. who demonstrated high speedmeasurements of Förster Resonance Energy Transfer (FRET) using a double-pass Fourier–transform fluorescence EEM spectrometer.19 The instrument measures the excitation and emission spectrum (the two projections of the EEM spectrum) as well as a diagonal projection that contains the cross-correlation between the excitation and emission properties. Motz et al. reported on a technique that used FT-modulated excitation light which was spatially dispersed while the fluorescence was analyzed using a conventional monochromator. With this method it was possible to image fluorescence EEM features across a 1.4 mm field of view.20 A concern with techniques that require Michelson interferometers to generate FT-modulated light is the high demand on the optical alignment to avoid wavefront distortion. Furthermore, the accuracy of the FT-analysis relies on a high dynamic range of the intensity measurement. FTs require analogue or high-bit digital modulation of light intensities and when the modulation exceeds the detector’s linear dynamic range, they can be afflicted with harmonics that confound the results. One not only requires comparably expensive detection systems but is also limited to samples that are homogeneous, and do not vary much over the course of the measurement. To our

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knowledge chemical reactions involving the interconversion of fluorophores have not been characterized, yet, in real time using fluorescence EEM. Here, we present a different technique to utilize wavelength division multiplexing using Hadamard-transform spectroscopy. As in FT-EEM spectroscopy, each excitation wavelength is separately modulated with a unique frequency and the entire spectrum of the light source can be used to excite the sample. The EEM spectrum is then obtained through demodulation of the resultant signal. Analogous to FT spectroscopy, Hadamard transform (HT) spectroscopy is also a multiplexing technique and thus has the same multiplex advantages over dispersive techniques. HT spectroscopy techniques maybe understood as using a “binary version” of conventional Fourier transform spectroscopy, i.e. the encoding functions are binary Walsh functions (akin to “barcodes”) in the time domain instead of sine and cosine functions. Previously researchers used Hadamard-encoding masks each representing one of these Walsh functions to record absorption spectra. Light was dispersed onto the masks and the wavelengths that pass through the masks are detected. The spectrally integrated transmission signal from each mask is recorded and the resultant vector array is decoded using the inverse of the Hadamard matrix.21-24 HTs have also been widely used in several other spectroscopic techniques. They have found applications in NMR,25 MRI,26 UV-Vis,27 Raman,28 and NIR spectroscopy.21, 29 All these applications were in one-dimensional spectroscopy, with the exception of a previously reported 2D Hadamard NMR technique.30 We believe that the HT provides a unique advantage in multidimensional spectroscopic techniques, i.e. when the intensities of two or more orthogonal spectra need to be modulated. In our experiments the Hadamard mask is generated using a digital micromirror array (DMA) with a maximal response rate of 22 kHz instead of a stepping through a Hadamard mask using a motor as has been done previously.21, 31-32 The fluorescence spectra are recorded through dispersion onto a conventional back-thinned CCD linear array detector.

2. THEORY 2.1 Hadamard Transform The Hadamard transform (HT) may be regarded as a binary counterpart of the analogue Fourier transform (FT). As basis functions the HT uses a set of Walsh functions, which are binary with values 1 and -1, instead of using sine functions as in FTs.33 Walsh functions are mutually orthogonal and the Hadamard matrix is constructed as a square symmetric matrix from rows and columns of Walsh functions. The HT involves multiplying a signal (dimension of m) with the Hadamard matrix, Hm, where m is the length of the square matrix. The elements of the Hadamard matrix were created using a Paley type I construction 34. For example, the 4×4 Hadamard matrix, H*4 , is:


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1

1

1

1

1   1 −1 1 −1 2 H*4 =  (1) 3 1 −1 −1 1    4 1 1 −1 −1 5 6 The orthogonality of the Walsh functions implies that 7 HH T = I , where I is the identity matrix. Ideally the noise8 free intensities (or spectra) recorded at differing wave9 lengths (or times) will not affect one another; similar to 10 the basis functions forming a Fourier series.25 11 Hadamard transform spectroscopy is a two-detector 12 technique where the difference between the signals aris13 ing from the (1)-input and from the (-1)-input must be 14 read simultaneously. This is problematic when performFigure 1: Method of the Hadamard mask generation. 15 ing fluorescence spectroscopy since the (1) and (-1) inputs Each row in this 7×7 Hadamard-matrix (top) generates a 16 correspond to excitation light “on” and “off”, requiring mask that is displayed by the DMA as an image (bottom). 17 therefore a second excitation channel which contains the As each column on the DMA represents a different wave18 corresponding “off” and “on” inputs. As was described belength of light, only the “on” (1) values will be detected 19 for each image, thereby creating a mask. fore, the Hadamard matrix (H*m) is therefore best con20 verted into a matrix Hn, where n = m - 1. This conversion  n  21 retains all advantages of the Hadamard transform but is H1k S k  ∑  22  S1  designed for a one detector system35, and is also slightly  k =1  23 faster. The transformation is simply performed by removE=   (4) = H ×    24  n  ing the first row and column of the Hadamard matrix fol  S 25  n  H S  lowed by the conversion of all 1 elements to 0, and -1 ele∑ nk k 26    k =1  ments to 1, that is 27 1 1 1 1  28 The spectrum of the light source, S1  S j , can be ob1 0 1   29 1 1 1 1 − −   1→ 0, −1→1 tained by multiplying E with the inverse of the binary   = H*4  = → H3  1 1 0  (2) 30 1 −1 −1 1  Hadamard matrix 0 1 1 31      n  32 1 1 −1 −1 H1k S k  ∑  33  S1  k =1 We found that the conversion from the Hadamard matrix  34  =  Η −1 ×  to the Hn matrix (sometimes called the S-matrix) greatly  (5)    35  n  reduces the amount of artifacts in the resulting EEM.36   S 36  n  H S  Computers are able to decode HT encoded signals much nk k  ∑  37 k =1 faster than their FT equivalents and decoding can fre38 21, 37 quently be done in real-time. When the encoded excitation light, HS, is used to excite 39 fluorescence in a sample, the resulting fluorescence maFor example, to encode the emission spectrum of a light 40 trix is given by source - here represented as rows in the Source matrix [S] 41 where all rows are identical - each wavelength is modu42 lated separately in the time domain by an individual row  f11 f12  f1 j   H11 S1 H12 S 2  H1n S n  43   of the Hadamard matrix. The resulting sequence of spec- =       × M 44   tra is represented by the Hadamard product giving matrix  f n1   f nj   H n1 S1 45   H nn S n    HS in which each row represents a spectrum 46 = F HS × M (6) HS ≡ H  S 47 Where Mij is the fluorescence intensity at wavelength j 48  S11 S12  S1n   H11 S11 H12 S12  H1n S1n  (3) with the normalized decoded excitation intensity at 49      =    H  wavelength i, meaning that M is the desired EEM spec50  Sn1 S j 2  Snn   H n1 Sn1   H nn Snn  trum. In this article we follow common notation and dis51   play the excitation wavelength on the abscissa, i.e. all 52 If only the integrated intensity of each spectrum is measEEM spectra are displayed as the transpose of M. Each 53 ured, then the intensity for each mirror configuration can row of matrix F, represents the fluorescence spectrum for 54 be represented by the column vector: a given mirror configuration. 55 56 −1 (7) M = [ HS ] × F 57 58 59 60

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A program was written using MatlabTM to generate Hadamard matrices and to decode the fluorescence signal F thereby generating the EEM spectrum, MT .

2.2 Modulation of the excitation spectrum using a digital micromirror array Walsh functions are binary and therefore binary switches are required to modulate the excitation light in Hadamard spectroscopy. Digital Micromirror Arrays (DMA; also called Digital Micromirror Devices, DMD) are easily configurable binary switches. DMAs consist of an array of mirrors - in our case 768 x 1024 mirrors - that can be individually switched to an “on” or “off” state.38 In our experiment white light is dispersed along the DMA so that each mirror column represents a separate wavelength of light (see below). Each excitation wavelength is then independently modulated with its own distinct Walsh function by flipping the mirrors of the DMA. Each row in the Hadamard matrix (2) is used to generate a separate Walsh mask, where the value in each column of the Hadamard matrix is applied to all rows, i.e. to 768 mirrors on our DMA (Figure 1). Each mask is played in sequence by loading the “image” corresponding to the row of the Hadamard matrix into the memory of the DMA. As a consequence, at each instance in time the wavelengths of the light source are modulated by the binary Walsh function, and each of the wavelengths is also modulated in the time domain by a distinct Walsh function. Figure 2 shows how the source spectrum of a light source may be encoded and subsequently decoded using an 7×7 Hadamard matrix. The source spectrum is projected onto the DMA which displays the 7 masks sequentially. Since only those wavelengths are collected that are reflected by mirrors in the “on” state, the emission spectrum is modified. Its total (wavelength-integrated) intensity may be collected with a broadband photodetector. We create the vector E (see equation (4)) by integrating each of the

2: Modulation and demodulation of the light source. Step 1: the light source is modulated by the Hadamard masks (Fig 1) and the resulting spectrum is collected. Step 2: the spectrum obtained for each mask is integrated and each integrated intensity is placed into a 1D array. Step 3: the source spectrum is recovered by multiplication of the 1D intensity array with the inverse of the Hadamard matrix.

Figure 3: The generation of an EEM spectrum through Hadamard modulation. Step 1: The sequence of modulated excitation light spectra which is generated as in Figure 2 by modulation of a broad band source with a DMA, is used to excite a fluorescing or scattering sample which generates a corresponding emission spectrum. Step 2: the intensities at each of the wavelengths of the n emission spectra are placed into a 3D data set. Step 3: The EEM spectrum, M, is generated by converting the image number into excitation wavelength, i.e. by multiplying the Hadamard encoded 3D data set, F, with the inverse of the Hadamard matrix that is weighted by the excitation source as in equation (7).

seven modified spectra so that each integrated intensity corresponds to one entry. The emission spectrum of the light source, S, is obtained by multiplying E with the inverse of the loading matrix, H using equation (5). Figure 3 shows how an EEM spectrum, M, may be produced using the Hadamard transform technique. Each Hadamard mask displayed by the DMA generates an excitation spectrum, i.e. a row in the HS matrix, which in turn produces a characteristic fluorescence spectrum after interaction with a fluorescing sample. After having displayed all Hadamard masks on the DMA the resulting 3D array of spectral data, F, contains the fluorescence intensities as a function of Hadamard mask index and emission wavelength. To demodulate F into an EEM spectrum, M, the Hadamard index is converted to excitation wavelength through multiplication of F with the inverse of the source spectrum-weighted Hadamard matrix, [HS]-1, (see equation (7)). This operation may be executed using MATLAB or other suitable software so that the EEM can be generated from the modulated fluorescence rapidly, e.g., typically within 1.5 s or less for a 67-channel matrix and non-optimized code.

3. EXPERIMENTAL A schematic drawing of the HT-EEM spectrometer is shown in Figure 4. White light from a light emitting diode (Cree CXB 1830, approx. 3000 lm, Ø14 mm) is coupled into a custom-built fiber bundle comprised of 11 multimode fibers (core Ø400 µm, cladding Ø440 µm), which guides the light to the dispersive element, based on a


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Figure 4: (Top) Photo of the digital micromirror array (DMA) used to encode the excitation light. (Bottom) Schematic of the HT fluorescence EEM spectrometer.

miniature spectrometer from which the detector array has been removed (Ocean Optics). At the entrance of this dispersion spectrometer the fibers from the LED fiber bundle are arranged in a row to allow a large amount of light to enter the dispersive element while maintaining a good spectral resolution. The white light is dispersed by the spectrometer’s grating and focused onto the DMA, which is mounted on a linear translation stage to ensure that the dispersed light is focused onto the DMA. The DMA modulates the spectrum of the light source (Figure 5) so that each column and hence each wavelength is associated with a different Walsh function. This modulated light is collimated and refocused using two off-axis parabolic mirrors and coupled into the excitation fibers of a bifurcated fiber probe.8-9, 39 The light is directed into the sample, which then fluoresces and scatters light. The consequent encoded emission is captured by the collection fibers and spectrally dispersed and detected using an array spectrometer (Avantes ULS2048L-RS-USB2). The DMA is addressed using home-written software that permits binning of groups of mirror rows such that Hadamard matrices with different dimensions from (2×2) to (1024×1024) can be used. The data acquisition rate was not limited by the response of the DMA, since its mirrors can be flipped at a rate as high as 22 kHz. Its rate therefore far exceeds the highest acquisition rate used on this article, i.e. 67 Hz for a 15 ms integration time. Reference fluorescence EEM spectra were obtained using a fluorimeter with two scanning gratings and a broadband detector (Varian Cary Eclipse) as described previously.8-11

4. RESULTS

Figure 5: Spectra of the excitation source obtained by HT-spectroscopy showing the normalized emission spectrum of the white LED with all the mirrors switched to the “on” position using an integration time of 1 s (solid line). The points represent the HT demodulated excitation light using a 31 channel Hadamard matrix.

4.1 Characterization of the light source and spectral resolution As described in equations (3) to (5) the Hadamard transform spectrometer can be used to obtain the spectrum of the light source (see also Figure 2). A scattering surface (lens paper) was placed at the end of the fiber probe. With all the mirrors on the DMA set to the “on” position, the emission profile of the light source was recorded using an integration time of 1 s. Next, the light source was modulated using the Walsh functions. After wavelength calibration the wavelength of the light that is incident on the white reflector corresponds wavelength of the scattered light. Figure 5 shows that the demodulated spectrum agrees well with the spectrum of the light source. The source of the deviations near 550 nm and 620 nm is not clear. To determine the spectral resolution and to calibrate the DMA with respect to the excitation source wavelengths, we addressed only single columns of mirrors and turned them “on” while keeping all other mirrors turned “off”. The excitation wavelengths and the spectral resolution of the Hadamard-modulated source were obtained from Gaussian fits of the resulting scattering spectra (Figure 6a). We found that the average resolution δλ = 21 nm is limited by the dispersion of light onto the DMA. Consequently, for the current setup, there is no advantage in using Hadamard matrices having more than 31 elements. The limits of the spectral resolution are also apparent when recording HT-EEM spectra of scattered light that is directed from the HT-modulated source into the spectrometer. Figure 6b shows that HT-EEM spectra having 31 excitation channels show the same features as those obtained with more excitation channels.



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Figure 6: (a) Calibration Spectra for the 31 image conventional raster scan. Only 6 columns are shown out of the total 31 to reduce clutter. The dashed lines represent Gaussian fits through the data where the center wavelength is used to generate the excitation wavelength of the corresponding column. (b) The normalized calibration spectra obtained by conventional raster scanning across the mirror columns on the DMA. The excitation wavelength width of each mirror column is shown by the superimposed transparent areas and decreases as the excitation channel size increases.

4.2 Hadamard-Transform Fluorescence EEM on static sample Sulforhodamine 640 (50 µM in anhydrous ethanol) was used as a test dye to validate the proposed HTfluorescence EEM method. As a reference, the spectrum of Sulforhodamine 640 in ethanol was obtained using the standard EEM technique using a commercial scanning spectrometer (Figure 7a). The Hadamard fluorescence spectra of the same solutions of Sulforhodamine 640

were obtained using an integration time of 300 ms for each Hadamard mask. The acquisition time for each EEM spectrum is the product of integration time and number of images, n, and it therefore takes 2.1 s to acquire an 7channel spectrum, and 9.3 s for a 31-channel spectrum. The latter gives the maximal resolution whilst maintaining a high data acquisition rate. Figure 7b shows that the Hadamard spectra match those of the conventional spectrometer while taking only a fraction of the time to complete (~10 seconds compared to about 1 hour. To further highlight the advantages of the Hadamard technique, the integration time was reduced to 15 ms per channel. Figure

Figure 7: (a) EEM spectrum of Sulforhodamine 640 in anhydrous ethanol as obtained by the Varian Cary Eclipse spectrometer, using an excitation step and slit size of 20 nm, an emission step size of 10 nm and a scan rate of 120 nm/min. These parameters were chosen to match that of the Hadamard spectra at the right. The spectrum took approximately 1 hour to obtain. (b) Hadamard fluorescence spectra of 50 µM Sulforhodamine 640 in anhydrous ethanol using an integration time of 300 ms per channel. The total acquisition time of the 31 channels HT-EEM is less than 10 s.


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Figure 8: 31-channel Hadamard fluorescence spectra of 50 µM Sulforhodamine 640 in anhydrous ethanol using an integration time of 15 ms (total acquisition time of 33,000 hrs) and reported colour consistency by the manufacturer lead us to believe that source fluctuations or drifts are not a concern. Finally, the HT-EEM spectrometer was designed to operate in the visible region of the spectrum (440-660 nm). As most fluorescent compounds are excited in the range of 200-400 nm future designs will attempt to shift the excitation range into the UV. This requires that the light source will need to be replaced with a UV source such as a Xenon flash lamp and that the window protecting the DMA will then also have to be replaced with a UVtransparent window.

6. CONCLUSIONS We demonstrate the main advantage of the Hadamard Transform EEM spectrometer compared to a conventional scanning EEM fluorimeters: a high-resolution spectrum (31-channels and up to 2048 emission channels) can be acquired in a matter of seconds. For that reason, the HT-EEM -spectrometer is optimal for kinetic studies. The fiber probe can be inserted directly into a reaction flask, allowing the continuous acquisition of fluorescence EEM spectra while a reaction is occurring. After PARAFAC analysis the reaction rate can then be determined from the respective scores of the PARAFAC components and their change as a function of time. The instrumental method is illustrated using two simple systems. The temperature-dependent fluorescence of rhodamine-B and fluorescein dyes is recorded simultaneously and used to show the high acquisition rate and negligible cross talk between the two fluorescence components. The second test further emphasizes this point: chlorophyll-a is converted into pheophytin-a using dilute acid while the fluorescence of the system is monitored. At each of the four acid concentrations several hundred EEM spectra were recorded using the HT-EEM spectrometer. Again, the data was analyzed using PARAFAC analysis and yielded only two spectrally very similar components. From their respective scores the decomposition

rate constant of chlorophyll-a was estimated as k = 450±170 L2mol-2s-1. While we have used a digital micromirror array to encode the spectrum of an incoherent white light source, the method would, of course, also be valid if other encoding instruments such as spatial light modulators, or simply a very large number of discrete-wavelength light sources, were used.

AUTHOR INFORMATION Corresponding Author * Email: [email protected] ORCID of Hans-Peter Loock: 0000-0002-5468-1572 The authors declare no competing financial interest. Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

ACKNOWLEDGMENT The authors acknowledge the technical contributions by John Cullen, Amanda Rigg, James Fan and Goldwin Stewart towards the spectrometer design and helpful discussions with Dr. Dorit Munzke. Financial support by GasTOPS Ltd. and the Natural Sciences and Engineering Research Council of Canada is gratefully acknowledged. OR acknowledges financial support by the German Federal State of Brandenburg. 1.

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