Classification of Transitions in Upconversion Luminescence of

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Classification of Transitions in Upconversion Luminescence of Lanthanides by Two-Dimensional Correlation Analysis KINGSHUK MUKHUTI, Venkata N K B Adusumalli, Venkataramanan Mahalingam, and Bhavtosh Bansal J. Phys. Chem. A, Just Accepted Manuscript • DOI: 10.1021/acs.jpca.8b11052 • Publication Date (Web): 28 Feb 2019 Downloaded from http://pubs.acs.org on March 1, 2019

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The Journal of Physical Chemistry

Classification of Transitions in Upconversion Luminescence of Lanthanides by Two-dimensional Correlation Analysis Kingshuk Mukhuti, Venkata N. K. B. Adusumalli, Venkataramanan Mahalingam, and Bhavtosh Bansal∗ Indian Institute of Science Education & Research Kolkata, Mohanpur, Nadia 741246, West Bengal, India E-mail: [email protected]

Abstract

tween many of the different 4f levels in Er3+ , Tm3+ and Ho3+ is in the visible range 11 , the 4f →4f transitions have very poor efficiency due to their being electric-dipole-forbidden. 12 Hence for use as light emitters, lanthanide ions are incorporated in a suitable host matrix (such as NaGdF4 ) that provides a strong crystal field environment. This relaxes the selection rules by lifting the degeneracies of Starkdoublets. 13 Very efficient upconversion luminescence can then be achieved by introducing an additional ion (e.g., Yb3+ ), and thus codoping two lanthanides such that they form a sensitizer-activator system (e.g. Yb3+ /Er3+ is the system studied in this paper), within the suitable matrix (NaGdF4 ). 14,15 The random location of these dopant atoms within the matrix implies that the crystal field experienced by different atoms differs both in direction and magnitude. With the symmetry constraints completely lifted, one possibly observes all the intra-4f transitions for the given lanthanide ion within the closely spaced Stark states of different spin-orbit coupled levels. Thus the spectrum from any macroscopic volume of the sample is inhomogeneously broadened leading to broad emission bands with many poorly resolved peaks [as can be seen in Fig. 1(b) to be discussed below]. 16 Thus while exact calculations may be possible for an isolated multielectron atom in an electric field,

Upconversion luminescence bands from Yb3+ /Er3+ co-doped into a matrix such as NaGdF4 can show very complex structure on account of multiple intra-f shell transitions occurring in presence of random crystal fields. We demonstrate that two-dimensional correlation analysis, applied to such time-integrated luminescence spectra measured as a function of excitation power, allows us to gain substantial information about the states involved in transitions, without any additional theoretical input. The detailed correlation analysis allows us not only to identify the location of various transitions but further club them into groups based on their quantum mechanical origin, and finally subclassify the transitions with each group depending on whether they have a common initial or final state.

Introduction Upconversion phosphors are a class of light converters, typically consisting of lanthanides or transition-metal ions, which absorb two or more low energy photons to emit high energy photons. 1 Lanthanide-doped oxide and fluoride upconverters have long been actively researched for laser, solar cell, sensor, and bioimaging applications. 2–10 Although the energy spacing be-

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for the real scenario of such an atom inside a matrix, it is almost impossible to theoretically identify particular transitions with sufficient accuracy. In this paper, we propose the use of two-dimensional (2D) correlation analysis 17 as a simple but very powerful tool for identifying connections among various transitions and classifying them.

total spin and orbital angular momenta respectively, and J = L + S being the total angular momenta. Each of these bands originate from transitions between Stark levels. Apart from these, there are two more weaker bands at ∼505 nm (blue) B (4 F7/2 →4 I15/2 ) and ∼700 nm (red) R2 (4 F7/2 →4 I13/2 ) respectively. 19 As B and G1 bands are close in energy, they are designated as a single B − G1 band. Similar reasoning is also applied to R1 − R2 band. The spectrum of B − G1 band, with emission intensity varying over four order of magnitude, is shown in Fig. 1(b). The spectrum shows many poorly-resolved broad features arising from various possible transitions between the Stark levels shown in Fig. 1(a). 12

(a)

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Area Normalized Intensity (a.u.)

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1 mW 2mW

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Figure 1: The upconversion process in Yb+3 Er+3 system. (a) Spin-orbit coupled levels shown in gray shade and Stark levels in circular inset. (b) The spectrum of the B −G1 band due to inter Stark level transitions measured at 260 K and excitation power of 6 mW is also shown. Note that the intensity is plotted on log scale.

Figure 2: Power dependence of the upconversion luminescence spectra of the B − G1 transitions at 260 K are shown. Area normalization is done with respect to the whole spectrum and only a part (495 nm - 532 nm) is shown here. The actual process of upconversion studied here involves a 980 nm laser sensitizing the Yb3+ ions, which absorb the energy to go from ground state (2 F7/2 ) to an excited state (2 F5/2 ). Yb3+ then transfers energy to the activator Er3+ ions via Förster energy transfer and other mechanisms. 13,20 The upconversion occurs because Er3+ ions successively absorb two or more transferred photons to get to high excited states. A combination of various non-radiative and then radiative de-excitation pathways leads to the observed emission from different bands. To understand these transitions, we have done a detailed excitation power, temperature and mag-

Experimental Lanthanide ions show a number of different spectral bands in the ultraviolet, visible and infrared region. 12,18 Within visible range, Er3+ produces two major bands at ∼520 nm and ∼550 nm in the green and one more at ∼650 nm in the red spectral window. Let us mark these transitions as G1 (2 H11/2 →4 I15/2 ), G2 (4 S3/2 →4 I15/2 ), and R1 (4 F9/2 →4 I15/2 ). Here the notation stands for 2S+1 LJ with S, L being the


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able. 23–28 Let I(λ, P ) denote a series of spectra measured as function of wavelength λ and an

netic field dependent study of the Er3+ emission lines in the visible wavelength range. The spectral characteristics were found to change significantly both with temperature and excitation power. The effect of the magnetic field was less pronounced and it in general only reduced the emission intensity. In this paper, we will focus on the excitation power dependent changes in the spectra which result from successive filling and saturation of the states. 21,22 The value of the temperature where this change is analyzed was chosen to be the one where the changes were the most significant. B-G1 transitions seemed to be thermally activated and most pronounced at higher temperatures. This spectral band was almost absent below 80 K for low excitation powers and only become discernible at high powers. Thus in Fig. 2 and the rest of the paper, the spectra for B-G1 transitions at 260 K data are studied. On the contrary, other two transitions G2 and R1 -R2 become more intense at lower temperature and thus the 4 K spectra are analyzed for these bands. Details of the analysis for these other two bands is discussed in the Supplementary Material.

(a)

Synchronous Spectrum

(b)

Asynchronous Spectrum

(c)

Synchronous - Asynchronous Overlap

Theory An important characteristic of the spectra of Lanthanide ions is that the positions of various peaks do not change appreciably with excitation power or temperature. This makes the 2D correlation technique particularly useful for characterizing the transitions. 17 In this work we specifically aim to use the 2D correlation analysis to (i) resolve different transitions within a broad luminescence band, (ii) find correlations and anti-correlations among those peaks, (iii) cluster them into groups for transitions upon common initial or final states, (iv) tentatively further classify the members with a common initial state and common final state. Two-dimensional correlation analysis.— Pioneered by Noda, Ozaki and coworkers, the generalized 2D correlation spectroscopy is applied in different contexts to study the change in a spectrum with respect to an external vari-

Figure 3: Normalized 2D correlation spectra for B-G1 transitions. Here we generated the correlation plots from the excitation power dependent dynamic spectra acquired at 260 K. (a) Synchronous spectrum Φ(λ1 , λ2 ), (b) Asynchronous spectrum, Ψ(λ1 , λ2 ), and (c) Overlap of the synchronous (line contours) and the asynchronous (filled contours) spectra to generate a hybrid plot. This helps identify special correlated transitions [λl , λk ] where the synchronous signal is strong but the asynchronous signal is missing.


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matrix Ψ(λ1 , λ2 ) is defined as

additional parameter P , which may be time, temperature, concentration, magnetic field or (as it is in the present case) power of the laser excitation. One may then construct two correlation matrices, Φ(λ1 , λ2 ) and Ψ(λ1 , λ2 ), denoting respectively the ‘synchronous’ and ‘asynchronous’ correlations. The synchronous 2D correlation is expressed as Φ(λ1 , λ2 ) =

Ψ(λ1 , λ2 ) =

Pmax Pmin

Pmax

Pmin

˜ 1 , P ) ⋅ J(λ ˜ 2 , P )dP. (3) I(λ

This asynchronous spectrum Ψ(λ1 , λ2 ) is anti-symmetric by construction and is meant to pick out only the ‘out-of-phase’ correlations in spectral features with the change in the variable P . Since the intensity at a particular wavelength must be perfectly correlated or in phase with itself, the asynchronous spectrum has no diagonal or autopeaks. The actual algorithms for calculating these correlation spectra from a discrete set of dynamic spectra are given in Ref. 17 and also discussed in the Supplementary Material.

˜ 1 , P ) ⋅ I(λ ˜ 2 , P )dP. (1) I(λ

Here we assume that the ‘dynamic’ parameter P is the power of laser excitation with respect to which correlation in the spectra are ˜ P ) = I(λ, P ) − ⟨I(λ, P )⟩P calculated. I(λ, is defined such that the spectra have zero mean. Pmax and Pmin denote the largest and the smallest value of the parameter P , and Pmax I(λ, P )dP , ⟨I(λ, P )⟩P = (Pmax − Pmin )−1 ∫Pmin the average spectrum. The synchronous spectrum Φ(λ1 , λ2 ) is symmetric by construction and shows how correlated the changes in the spectral intensity at two wavelengths, λ1 and λ2 , are as the external parameter P is varied. As will be seen below, Φ(λ1 , λ2 ) is very effective in picking out the peaks in the spectrum and canceling the noise. In analogy with the formulation of analytical signals used in optics and other fields, one can ˜ P ) as the Hilbert transform further define J(λ, ˜ P ) (with respect to excitation power in of I(λ, our case) 17 ′ ˜ ˜ 2 , P ) = 1 P V [∫ I(λ2 , P ) dP ′ ] J(λ π P′ − P

1 Pmax − Pmin

×∫

1 Pmax − Pmin

×∫

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Results and Discussions Fig. 3(a) shows the normalized synchronous spectrum Φ(λ1 , λ2 ) calculated from the power dependence of the B-G1 band shown in Fig. 2. By taking derivative of I(λ, P )’s with respect to λ as an alternative mean of estimating peaks in the spectrum, it could be verified that all the autopeaks visible in Φ(λ1 , λ2 ) matched with peaks identified from the derivative of the spectrum. However, the weakest peaks could only be resolved if we constructed correlation matrices in smaller wavelength ranges. As it is evident from Fig. 3(a), the autopeaks are always positive. Strongest autopeak evolves at the wavelength where variation in emission intensity is maximum with power. Crosspeaks mark concurrent spectral changes at two different wavelengths and indicate the possibility (necessary but not sufficient) that such transitions may have a common origin. With respect to any autopeak, a positive crosspeak (i.e. both peaks are in same color) implies simultaneous growth or decay, whereas a negative crosspeak (i.e. both peaks are in different color) suggests competitive variation. We can clearly see from Fig. 3(a) that the 2D correlation scheme digs out the buried weak transitions in a very pic-

(2)

where P V [∫ ..] denotes the principal value of the integral whose limits should extend to as large a range of P as possible, ideally between 0 and ∞. Loosely speaking the Hilbert transform ˜ P ) is ‘orthogonal’ or ‘out of phase’ to the J(λ, ˜ P ) with respect to the change in function I(λ, ˜ P ), the ’asynchronous’ variable P . Using J(λ,


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torial way. Within B-G1 transitions, the autopeak at 519.3 nm is the strongest and is either correlated or anticorrelated to other peaks in the band. We call a correlation (or anticorrelation) coherent if it is among two peaks

in the same band, and incoherent if it is among two peaks in different bands. Fig. 3(a) can visually be divided in two correlated bands with broadly two sets of correlation patches. One set is nearly from 496 nm to 515 nm and the other is roughly from 515 nm up to 534 nm. These two are B and G1 transitions. Similar features are also evident for G2 and R1 − R2 transitions, shown in the Supplementary Material. Fig. 3(b) shows the corresponding asynchronous spectrum, Ψ(λ1 , λ2 ). If two wavelengths λ1 (along horizontal) and λ2 (along vertical) are positively correlated in the synchronous spectrum, then a positive crosspeak in the asynchronous spectrum shows that any change with respect to external parameter (excitation power in this case) occurred at λ1 a rate faster than in λ2 . The convention is reversed when they generate a negative correlation peak in synchronous spectrum. Fig. 3(c) was generated by superimposing Φ(λ1 , λ2 ) (line contours) and Ψ(λ1 , λ2 ) (color contours), both plotted at lower resolution. Instead of a regular 256 shade colorbar, here, the available quantitative information was depicted in a qualitative coarse grained 5 color scheme. The colors represent strong, weak correlation and anticorrelation and no correlation. This plot brings out the true power of the 2D correlation method as it allows us to pick out pairs [λl , λk ] where one observes a synchronous peak (in line contour) but the asynchronous signal (in color contour) is absent. Since this implies that the change of the intensities at λl and λk with excitation power occurs ‘in phase’, it would be a nearly definitive evidence that the two transitions at λl and λk have either a common initial or final state. Assuming that emission intensity is proportional to the occupation of a particular state, positive correlation between [λl , λk ] in the synchronous spectrum should indicate a common initial state and negative correlations a common final state. The negative correlation being the result of Pauli blocking. Finally, the correlations seen between transitions belonging to two separate classes may be termed incoherent and should be distinguished from the coherent correlations seen between the transitions in a given class. The incoherent correlations are

(a)

(b)

(c)

Figure 4: One representative spectrum is displayed for each band. Intensity is area normalized and plotted on a log scale. Various transitions are identified and grouped into classes (A, B, .., L). In each case, the strength of correlations with respect to the strongest autopeak is shown. (a) B-G1 band with the strongest peak at 519.3 nm, (b) G2 band with the strongest peak at 537.4 nm, (c) R1 -R2 band with the strongest peak at 653.3 nm.


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likely to be due to classical distribution of energy (e.g. due to thermal activation) which prepares the multiparticle initial state on optical excitation. Here we mainly concentrate on coherent cases. Only B-G1 transitions are from close proximity bands where incoherent correlations (anti-correlations) were observed. The summary of the complete analysis is presented in Fig. 4 where the transitions in all three bands, B-G1 , G2 , and R1 -R2 are presented in the three subfigures. The strongest autopeaks are marked in red in each case. Other peaks are marked with ‘+’ (‘−’) signs if they are positively (negatively) correlated to the strongest peak, with the number of ‘+’s or ‘−’s within parentheses indicating the correlation strength relative to the strongest peak. It is worth clarifying that all ‘−’ peaks in a band are positively correlated within themselves and the same is true for all ‘+’ peaks. In Fig. 4(a), we have been able to identify 20 different transitions (among maximum possible [(8 × 6) + (8 × 4) =] 80 in B-G1 band. This reduced number indicates that many of them may still be overlapping or forbidden. Using the prescription discussed above, we could create five classes [A–E in Fig. 4(a)] and accommodate 18 out of these 20 transitions. 2 others did not fall into any of the classes. Applying the same procedure, a combined total of 25 more transitions were found in G2 and R1 -R2 bands. Fig. 4(b) and (c) represent, 16 of them clustered in 7 other classes, with 9 standing alone. The actual 2D correlation diagrams for the G2 and R1 R2 bands are shown in Supplementary Material. Peaks within any one class have either their initial or final states common between them. The states which have the same relative sign have common initial states and states having opposite signs have a common final state.

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lanthanide-doped nanoparticles, we have shown that two-dimensional correlation analysis on the spectra measured at different excitationpowers does indeed work very well in discerning different emission lines. Apart from resolving the transitions, we were also able to get some insight on the origin of different transitions if they have common initial or final states. The fact that we have been able to identify and classify as many as 45 different transitions reveals the power of this technique. It is also perhaps remarkable that so much could be inferred without any quantum mechanical input, though of course further comparison with detailed microscopic calculation would be very useful. Combining an additional variable such as the magnetic field can also potentially yield interesting complementary information. This technique may become very helpful in understanding energy transfer and cross relaxation processes. Acknowledgement The authors thank Bipul Pal and Nirmalya Ghosh for many valuable suggestions and Rajesh Jana, Kamal Raj R, and Anjana Krishna for help in performing the experiments. The work was not funded through any external agency.

Supporting Information Available Sample preparation procedure is given. Additional discussions on experimental details and power dependent spectra of G2 and R1 -R2 bands. Along with required algorithms for the analysis, figures illustrating correlation diagrams of G2 and R1 -R2 bands. This Supporting Information is available free of charge via the Internet at http://pubs.acs.org.

Conclusions

References

In this paper we have addressed the general problem of resolving individual transitions in an inhomogeneously broadened spectrum containing a large number of peaks. Working in the context of the upconversion luminescence from

(1) Singh-Rachford, T. N.; Castellano, F. N. Photon Upconversion Based on Sensitized Triplet-triplet Annihilation. Coordination Chemistry Reviews 2010, 254, 2560–2573.


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Page 7 of 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(2) Scheps, R. Upconversion Laser Processes. Progress in Quantum Electronics 1996, 20, 271–358.

(11) Suyver, J.; Grimm, J.; van Veen, M.; Biner, D.; Krämer, K.; Güdel, H. Upconversion Spectroscopy and Properties of NaYF4 Doped with Er3+ , Tm3+ and/or Yb3+ . Journal of Luminescence 2006, 117, 1–12.

(3) Huang, X.; Han, S.; Huang, W.; Liu, X. Enhancing Solar Cell Efficiency: The Search for Luminescent Materials as Spectral Converters. Chem. Soc. Rev. 2013, 42, 173–201.

(12) Henderson, B.; Imbusch, G. F. Optical Spectroscopy of Inorganic Solids; Oxford University Press, 2006; Vol. 44.

(4) Zhang, P.; Rogelj, S.; Nguyen, K.; Wheeler, D. Design of a Highly Sensitive and Specific Nucleotide Sensor Based on Photon Upconverting Particles. Journal of the American Chemical Society 2006, 128, 12410–12411.

(13) Auzel, F. Upconversion and Anti-Stokes Processes with f and d Ions in Solids. Chemical Reviews 2004, 104, 139–174. (14) Wang, F.; Liu, X. Recent Advances in the Chemistry of Lanthanide-doped Upconversion Nanocrystals. Chemical Society Reviews 2009, 38, 976.

(5) Wang, F.; Banerjee, D.; Liu, Y.; Chen, X.; Liu, X. Upconversion Nanoparticles in Biological Labeling, Imaging, and Therapy. The Analyst 2010, 135, 1839.

(15) Naccache, R.; Vetrone, F.; Mahalingam, V.; Cuccia, L. A.; Capobianco, J. A. Controlled Synthesis and Water Dispersibility of Hexagonal Phase NaGdF4 :Ho3+ / Yb3+ Nanoparticles. Chemistry of Materials 2009, 21, 717–723.

(6) Vetrone, F.; Naccache, R.; Zamarrón, A.; de la Fuente, A. J.; Sanz-Rodríguez, F.; Maestro, L. M.; Rodriguez, E. M.; Jaque, D.; Solé, J. G.; Capobianco, J. A. Temperature Sensing Using Fluorescent Nanothermometers. ACS Nano 2010, 4, 3254–3258.

(16) Kisliuk, P.; Krupke, W. F.; Gruber, J. B. Spectrum of Er3+ in Single Crystals of Y2 O3 . The Journal of Chemical Physics 1964, 40, 3606–3610.

(7) Brites, C. D. S.; Lima, P. P.; Silva, N. J. O.; Millán, A.; Amaral, V. S.; Palacio, F.; Carlos, L. D. Thermometry at the Nanoscale. Nanoscale 2012, 4, 4799.

(17) Noda, I.; Ozaki, Y. Two-dimensional Correlation Spectroscopy: Applications in Vibrational and Optical Spectroscopy; John Wiley & Sons, 2005.

(8) Jaque, D.; Vetrone, F. Luminescence Nanothermometry. Nanoscale 2012, 4, 4301. (9) Hazra, C.; Adusumalli, V. N. K. B.; Mahalingam, V. 3,5-Dinitrobenzoic AcidCapped Upconverting Nanocrystals for the Selective Detection of Melamine. ACS Applied Materials & Interfaces 2014, 6, 7833–7839.

(18) Adusumalli, V. N. K. B.; Koppisetti, H. V. S. R. M.; Mahalingam, V. Ce3+ Sensitized Bright White Light Emission from Colloidal Ln3+ Doped CaF2 Nanocrystals for the Development of Transparent Nanocomposites. Journal of Materials Chemistry C 2016, 4, 2289–2294.

(10) Ananias, D.; Almeida Paz, F. A.; Carlos, L. D.; Rocha, J. Near-Infrared Ratiometric Luminescent Thermometer Based on a New Lanthanide Silicate. Chemistry - A European Journal 2018, 24, 11926– 11935.

(19) Klier, D. T.; Kumke, M. U. Upconversion Luminescence Properties of NaYF4 :Yb:Er Nanoparticles Codoped with Gd3+ . The Journal of Physical Chemistry C 2015, 119, 3363–3373.


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(20) Rabouw, F. T.; Prins, P. T.; VillanuevaDelgado, P.; Castelijns, M.; Geitenbeek, R. G.; Meijerink, A. Quenching Pathways in NaYF4 :Er3+ , Yb3+ Upconversion Nanocrystals. ACS Nano 2018, 12, 4812–4823.

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Repressor Protein. Proceedings of the National Academy of Sciences 1999, 96, 13153–13158. (28) Morita, S.; Shinzawa, H.; Noda, I.; Ozaki, Y. Perturbation-correlation Moving-window Two-dimensional Correlation Spectroscopy. Applied Spectroscopy 2006, 60, 398–406.

(21) Singh, S.; Geusic, J. E. Observation and Saturation of a Multiphoton Process in NdCl3 . Physical Review Letters 1966, 17, 865–868. (22) Pollnau, M.; Gamelin, D. R.; Lüthi, S. R.; Güdel, H. U.; Hehlen, M. P. Power Dependence of Upconversion Luminescence in Lanthanide and Transition-metal-ion Systems. Physical Review B 2000, 61, 3337– 3346. (23) Cloarec, O.; Dumas, M.-E.; Craig, A.; Barton, R. H.; Trygg, J.; Hudson, J.; Blancher, C.; Gauguier, D.; Lindon, J. C.; Holmes, E. et al. Statistical Total Correlation Spectroscopy: An Exploratory Approach for Latent Biomarker Identification from Metabolic 1H NMR Data Sets. Analytical Chemistry 2005, 77, 1282–1289. (24) Noda, I. Two-dimensional Infrared Spectroscopy. Journal of the American Chemical Society 1989, 111, 8116–8118. (25) Noda, I. Generalized Two-dimensional Correlation Method Applicable to Infrared, Raman, and Other Types of Spectroscopy. Applied spectroscopy 1993, 47, 1329–1336. (26) Czarnik-Matusewicz, B.; Murayama, K.; Tsenkova, R.; Ozaki, Y. Analysis of Near-infrared Spectra of Complicated Biological Fluids by Two-dimensional Correlation Spectroscopy: Protein and Fat Concentration-dependent Spectral Changes of Milk. Applied Spectroscopy 1999, 53, 1582–1594. (27) Fabian, H.; Mantsch, H. H.; Schultz, C. P. Two-dimensional IR Correlation Spectroscopy: Sequential Events in the Unfolding Process of the Lambda Cro-V55C


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Classification of Transitions in Upconversion Luminescence of

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