A Versatile Probe for Caffeine Detection in Real-Life Samples via

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A Versatile Probe for Caffeine Detection in Real-Life Samples via Excitation Triggered Alteration in Sensing Behavior of Fluorescent Organic Nanoaggregates Nilanjan Dey, Basudeb Maji, and Santanu Bhattacharya Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b03520 • Publication Date (Web): 16 Nov 2017 Downloaded from http://pubs.acs.org on November 16, 2017

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Analytical Chemistry

A Versatile Probe for Caffeine Detection in Real-Life Samples via Excitation Triggered Alteration in Sensing Behavior of Fluorescent Organic Nanoaggregates Nilanjan Dey,a Basudeb Maji,a and Santanu Bhattacharyaa,b,* a

Department of Organic Chemistry, Indian Institute of Science, Bangalore 560012, India. Present Address: Director’s Research Unit, Indian Association for Cultivation of Science, Kolkata 700032, India.

b

*Fax No: +91 33 2483 6561, Email ID: [email protected]

ABSTRACT: Excitation triggered alteration in the sensing behavior of fluorescent nanoaggregates was explored in water, considering caffeine as the ‘target analyte’. Merely by changing the excitation wavelength, we could specifically excite either the monomeric species or the fluorescent nanoaggregates. The monomer showed highly sensitive interaction with caffeine despite poor selectivity, while the ‘strongly associated’ fluorescent nanoaggregates displayed relatively high selectivity with low sensitivity. Additionally, the extent of self-aggregation was also found to be influenced by the micropolarity of the local surroundings and the electronics of the core carbazole unit. Furthermore, the present protocol was utilized for the estimation of caffeine in different beverages and biological fluids with reasonably high accuracy. Inexpensive, portable paper-strips were designed for a rapid, on-site detection of caffeine without involving sophisticated instruments or trained technicians.

INTRODUCTION Fluorescent organic nanoaggregates (FONs) are the nanoscale entities solely composed of emissive organic molecules ranging in diameter from ~10 nm to ~1 µm.1 Recently, these self-assembled luminescent materials have received enormous attention due to their wide range of applications in the field of pharmaceutical or cosmetic industries, optoelectronic device making and in the development of semiconducting or stimuliresponsive biomaterials.2-8 Unlike the conventional inorganic or semiconducting nanoparticles, organic nano-aggregates mainly exploit weak noncovalent interactions such as Van der Waals force, π-π stacking or hydrogen bonding for their association and thus exhibit easily tuneable photophysical characteristics.9-10 Effects of solvent polarity, temperature, and pH on the extent of self-assembly formation of these nano-aggregates have already been demonstrated in the literature.11-13 However, till date, no attempt has been made to investigate the effect of excitation wavelengths on the photophysical properties of these self-organized assemblies. Considering this present scenario, herein we have designed a series of easily synthesizable carbazole-based fluorescent nanoaggregates (FONs) and investigated their excitation dependent alteration in sensing behavior (Fig. 1). For this, we have chosen caffeine as the ‘target analyte’. Reasonable intake of caffeine can result in enhancement of alertness, attention, activity of nerve cells and even reduce the possibility of type 2 diabetes, while excess consumption may cause a headache, high blood pressure, irregularity in small muscle movements or allergy especially to minors and pregnant women.14-17 Though detection of caffeine utilizing expensive, sophisticated techniques like HPLC-MS or immunoassay is known, these are hardly convenient for public usage.18-20 Thus, in 2000, Waldvogel et al. reported an optical sensor for caffeine using triphenylene ketal derivatives

with three anchored urea groups, which could easily form hydrogen bonds with Lewis-basic carbonyl oxygen atoms and imine nitrogen (N 9) of caffeine in organic media.21 Following this first report, a handful optical probes have appeared in the literature for caffeine detection in last seventeen years (Table S1).22-30 However, a majority of the sensors suffered from significant interference from other structurally alike xanthene metabolites, such as theophylline, theobromine etc, which eventually restricted their applicability in real-life sample analysis. THF solution (non-fluorescent)

R

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Effect of substitutions

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Temperature Micropolarity pH

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R2 = -H, Compound 1 = -CHO, Compound 2 FONs formation in water

R

R N N

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N N N

Figure 1. Schematic diagram showing fluorescent nanoaggregate (FON) formation in water and also structures of the probe molecules involved in the present study.

Most importantly, this is the first instance, when fluorescent nanoaggregates (FONs) have been employed for ‘ratiometric sensing’ of caffeine at a nanomolar concentration in water. Merely by changing the excitation wavelength, we could specifically excite either the monomeric species or the nanoaggregates. The monomer showed better sensitivity towards caffeine with poor selectivity, whereas the ‘stronglyassociated’ aggregates exhibited superior selectivity for caffe-

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ine with low sensitivity. Thus, a simple way to establish a balance between selectivity and sensitivity was achieved without involving a large number of probe molecules or even multiple solvent systems. To best of our knowledge, this kind of excitation triggered alteration in sensing properties of fluorescent organic nanoaggregates has not been explored till date. Further, the protocol was utilized for real-time sample analysis including complex biological fluids, common beverages, and pharmaceutical tablets etc. Rapid onsite detection of caffeine without involving sophisticated instrumentation facility was achieved on low-cost paper strips.

diInnova SPM instrument: Tapping mode, 10 nm tip radius, silicon tip, 292 KHz resonant frequency, 0.7-1 Hz scan speed, 256 × 256 and 512 × 512 – pixels. Fluorescence Decay Experiments Fluorescence lifetime values were estimated by using a time-correlated single photon counting fluorimeter (Horiba Jobin Yvon). The system was excited with 300 nm nano LED of Horiba - Jobin Yvon with the pulse duration of 1.2 ns (slit width of 5/5, emission wavelengths were 370 nm and 470 nm). Average fluorescence lifetimes (av) for the exponential iterative fitting were calculated from the decay times (ai) and the relative amplitudes (ai) using the following equation [1],

EXPERIMENTAL SECTION Materials and Methods All chemicals including reagents, starting materials, solvents and silica gel for TLC and column chromatography were purchased from well-known commercial sources and were used without further purification. Solvents were distilled and dried by standard procedure prior to use. FTIR spectra were recorded on a Perkin-Elmer FT-IR Spectrum BX system and were reported in wave numbers (cm−1). 1H NMR and 13C NMR spectra were recorded on a Bruker Advance DRX 400 spectrometer operating at 400 and 100 MHz respectively. Synthesis of compounds The compounds 1 and 2 were synthesized following the literature reported procedure with slight modification.31-32 Please see ESI for 1H-NMR, 13C-NMR and ESI-MS spectra of compounds 1 and 2. (Fig. S35-S40). For the synthesis of other compounds (3-11), please see supporting information. UV-Visible and Fluorescence spectroscopy Sensing of different xanthene derivatives in pure water was carried out by injecting 10 μL DMSO solution of different compounds from a stock (1 × 10−3 M) in pure water to have the final volume of 1mL (1 × 10−5 M). For the variation of pH, various buffer solutions had been used. Like, HCO2Na/ HCl buffer for pH 24.5, CH3CO2Na/HCl buffer for pH 4.5-6.5, Tris/HCl for pH 79 and Na2B4O7·10H2O/NaOH for pH 10-12. The UV−vis and fluorescence spectra were recorded on a Shimadzu model 2100 spectrometer and Cary Eclipse spectrofluorimeter respectively. The excitation wavelength was set at 300 nm for the major number of studies (except for the studies with the variation of excitation wavelengths). 1 H NMR Titration Studies 1H NMR titration of compounds 1 and 2 was performed in DMSOd6-D2O mixture by gradual addition of caffeine and the spectra were recorded using identical parameters after each addition. Dynamic Light Scattering and Zeta Potential Measurement DLS measurements were performed at room temperature using a Malvern Zetasizer Nano ZS particle sizer (Malvern Instruments Inc., Westborough, MA). Samples were prepared and examined under dust-free conditions. Mean hydrodynamic diameters reported were obtained from the Gaussian analysis of the intensity-weighted particle size distributions. TEM Analysis TEM samples were made using the drop coating method from compounds 1 and 2 (10 µM) in water with and without adding PQ. TEM images were collected using a JEOL field emission Transmission-Electron-Microscope JEM2100F under 80KV working voltage. Atomic Force Microscopy Solutions of compounds 1 and 2 (10 µM in water pH 7.0) were drop-coated on mica and then carefully air-dried. Each sample was analyzed using a Bruker

av = (a112 + a222 + a332)/(a11 + a22 + a33)……………[1] Where a1, a2 and a3 are the relative amplitudes and 1, 2, and 3 are the lifetime values, respectively. For data fitting, a DAS6 analysis software version 6.2 was used. Calculation of fluorescence quantum yield The fluorescence quantum yield was calculated by considering rhodamine 6G (Φ = 0.94 in EtOH) as the reference dye. And the quantum yield is calculated using the following equation [2], Φunk = Φref [(Iunk/Aunk)/ (Iref/Aref)](ηunk/ηref)2……………….[2] where, Φunk and Φref are the radiative quantum yields of the unknown sample and standard, Iunk and Iref are the integrated emission intensities of the corrected spectra for the sample and standard, Aunk and Aref are the absorbance of the sample and standard at the excitation wavelength, and ηunk and ηref are the indices of refraction of the sample and standard solutions, respectively. Procedure for caffeine extraction from soft drinks, tea, and coffee The extractions of caffeine from these sources were performed following the literature reported procedure. 5 mL of each soft drink (Red bull, Pepsi, Coca-cola, Mountain Dew) was taken in a separating funnel and equal amount of CHCl3 was added. The mixture was then shaken well and the organic layer (CHCl3) was separated using a separating funnel. Then the organic layer was evaporated in vacuum and 1 mL of water was added in each of the residues. This solution was treated with caffeine extract from the corresponding soft-drinks. In the case of tea or coffee, first, the tea or coffee seeds were boiled in water (50 mg in 10 mL) and then that water solution was mixed with CHCl3. Then they were extracted in the similar way as mentioned above. But here brine solutions were added to break the emulsion. RESULTS and DISCUSSION Nanoassembly formation by carbazole probes in water The excellent solid-state luminescence of the compounds (1, 2) prompted us to investigate their nano-cluster forming property at pH 7.0 in water. Owing the presence of carbazole moiety, absorption spectrum of 1 showed existence of two distinct bands at ~273 nm ( = 9.31 x 104 mol-1cm-1) and ~352 nm ( = 9.89 x 104 mol-1cm-1). However, the presence of –CHO functional groups at the peripheral 3, 6-positions of compound 2 resulted in the appearance of a long-edged absorption band at the higher wavelength region with concomitant hypsochromic shift at 352 nm. Upon excitation at 300 nm, both the compounds 1 and 2 showed highly structured fluorescence spectra in THF with two emission maxima at 352 and 372 nm (Fig. S1). In water, compound 1 could retain the similar spectral signature, whereas, compound 2 showed appearance of a new


red-shifted aggregate emission band at 467 nm band (ΦF = 0.18) (Fig. 2a & S2). Even in THF-water mixtures with higher H2O contents and in polar organic solvents, the formation of ‘close-contact’ aggregates was observed with 2, resulting in red-shifts in the emission maxima (Fig. 2b & S3-S4). Aggregate Emission

2 in water in THF

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the formation of an H-type (face to face) stacking with caffeine.37-38 Job’s plot revealed the stoichiometry of the molecular interaction as 1:1 with an affinity constant of 642.96 ± 3.1 M-1 (Fig. S9).39-40 Though compound 1 did not show any noticeable agglomeration in water, the extent of interaction was found to be higher with caffeine (Fig. S10 - S11). Even the calculated detection limit also reflected higher sensitivity for compound 1 (95 nM) towards caffeine in comparison to 2 (175 nM) (Fig. S12 – S13, Table S3). However, cross-reactivity studies revealed that the interference from other xanthene metabolites was quite higher with compound 1 (Fig. 3c).

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Figure 2. (a) Fluorescence spectra of 2 (10 µM, ex = 300 nm) in THF and water; inset shows the solid- and solution-state emission from 2. (b) Images showing the change in emission color of 2 (10 µM, ex = 300 nm) in different organic solvents (1: CHCl3, 2: acetone, 3: propanol, 4: ethanol, 5: methanol, 6: water) under long UV lamp. (c) Fluorescence microscopy (left), AFM (middle) and TEM (right) images of 2 (10 µM) prepared in water.

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Interaction of Fluorescent Nanoaggregates with caffeine in water As part of our constant quest of designing small molecule based new optical probes,33-36 herein we have investigated the effect of caffeine on the π-stacking abilities of these electron rich poly-aromatic compounds in water. As expected, the addition of caffeine resulted in the enhancement of monomer emission of 2 with concomitant quenching (~3.5 fold) at the aggregated (FONs) emission band in water. Titration studies indicated a dose-dependent (0-3.5 mM) ratiometric response of compound 2 towards caffeine at pH 7.0 in water (Fig 3a). Surprisingly, in comparison with the other structurally related xanthene derivatives, such as theophylline and theobromine, the compound 2 showed considerably higher affinity towards caffeine (Fig. 3c & S8). Moreover, the presence of these analytes in excess also did not affect the response of 2 towards caffeine (Fig. 3b). A clear blue shift in the emission maxima (~8 nm shift at 470 nm band) was observed probably due to

100 50

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As anticipated, DLS studies of 1 revealed the formation of relatively smaller aggregates with an average diameter of 50.3 ± 3.2 nm, while compound 2 formed relatively larger aggregates with an average diameter of 143.7 ± 8.5 nm (Table S2). This difference in the size of aggregates was also confirmed by AFM and TEM analysis (Fig 2c). Unlike compound 1, PXRD pattern of 2 prepared in water (pH 7.0) showed presence of prominent π-π stacking interaction (2 = 31.2◦, d = ~2.8 Å) between carbazole units, which essentially concluded the hydrophobic collapse of molecules in water upon protonation of the piperazine moieties (Fig. S5). Again, the 2D-ROSY spectra of compound 2 (in DMSO-d6/D2O mixture medium) also showed appearance of additional cross-peaks due to spatial interaction of carbazole unit with the flexible aliphatic chains upon nanoaggregate formation (Fig. S6). Further, the stability of fluorescent nanoaggregates of compound 2 was investigated over a period of several days (Fig. S7). The remarkable stability of the nanoaggregates in the aqueous medium prompted us to explore its molecular recognition property.

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Figure 3. (a) Emission spectra of 2 (10 µM, ex = 300 nm) upon addition of different amount of caffeine (0-3.5 mM) in water (pH 7.0). (b) The response of 2 (10 µM, ex = 300 nm) towards caffeine in presence of other structurally related xanthene analogs (in excess) in water (pH 7.0). Points on the left side show response without caffeine and right side with caffeine. (c) Selective response of compounds 1 and 2 (10 µM, ex = 300 nm) towards caffeine in water (pH 7.0), monitored at 470 nm (II: Adenine, III: guanine, IV: cytosine, V: thymine, VI: uracil, VII: indole, VIII: theophylline, IX: theobromine, X: caffeine, XI: tryptophan, XII: serotonin, XIII: melamine, XIV: uric acid, XV: imidazole).

In both the cases, caffeine-induced lowering of fluorescence quantum yield was observed, indicating the non-fluorescent nature of complex formation between caffeine with the probe compound. As expected, the lowering of quantum yield was most pronounced with compound 1 (Table S5). In order to unveil the mode of interaction with caffeine, 1H-NMR titrations of both the compounds 1 and 2 were performed in DMSO-d6/D2O (1:1) mixture with caffeine (Fig. S14 - S15). In both the cases, significant upfield shifts were observed at the aromatic protons confirming the previously mentioned caffeine induced H-type stacking phenomenon.41 However, the extent of the upfield shift was higher with compound 1 in comparison to 2, reflecting stronger interaction in the case of the former compound (Fig. 4). Surprisingly, the peak corresponding to the aldehyde proton remained unaffected even in presence of >1 equiv. of caffeine. This clearly ruled out the possibility of direct involvement of the aldehyde functionality in the interaction process. Additionally, it also suggested that the extent of aggregation indeed has a strong influence on the caffeine sensing behavior of these compounds.



Comp 1

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Excitation triggered alteration in sensing behavior: Monomer vs. Aggregate From the above observations, we realized the decisive role of molecular self-assembly on the extent of caffeine sensing. To substantiate this speculation further, we investigated the influence of different stimuli on the self-association of these compounds in water and their subsequent influence on the caffeine sensing property. For this, we attempted to study the sensing behavior of the monomer as well as the nanoaggregate forms of compound 2 independently at pH 7.0 in water. The time-resolved emission spectra of 2 (ex = 300 nm) revealed the existence of a long-lived excited state with multiexponential decay (av=1.18 ns) at 470 nm band and a shortlived excited state with single exponential decay at 370 nm (Fig 5a). This suggested that the emission at 470 nm band was originated from the fluorescent nano-aggregates, whereas monomeric compound showed emission at 370 nm band.42-43 Now, upon scanning the whole emission range, we found two distinctive excitation spectra for compound 2, indicating their origin from two different photoexcited species (Fig. S16).44-45 The excitation spectra correspond to the lower emission wavelengths (350 and 370 nm) resembled with the carbazole monomers, whereas broad excitation spectra observed at higher emission wavelengths (420, 450 and 470 nm) correspond to the nanoaggregates in water. Upon excitation at 250 nm band (monomer excitation), compound 2 showed ~2 fold higher interaction with caffeine (Fig 5b) in comparison to what observed in the case of 300 nm excitation. On the other hand, choosing an excitation wavelength of 350 nm, which was exclusive for the aggregated species, poor sensitivity was observed with caffeine. However, a completely reverse situation was obtained during the selectivity studies. In this case, better selectivity was observed upon excitation at 350 nm as compared to what observed at 300 or 250 nm excitation (Fig. 5c & S17, Table S4). As expected, an increase in the caffeine interaction was observed (at ex = 300 nm) in the presence of chaotropic agents, such as urea, which might be due to urea-induced disruption of the preformed molecular assembly (Fig. S18).46 Similarly, temperature induced dissociation of the nanoaggregates also caused an increase in the extent of caffeine-interaction (Fig. S19). As the compound possessed pH sensitive piperazine unit, the intensity of the ‘aggregate emission’ was found to be decreased with increas-

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Figure 4. Partial 1H-NMR spectra of 1 and 2 (8 mM) in DMSO-d6/D2O (1:1) mixture both in presence and absence of 1 equiv. of caffeine. (The assigned protons are showed in a general structure of the probes).

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ing pH (Fig. S20a). As the propensity of aggregate formation increased at the acidic pH medium, the extent of interaction with caffeine reduced significantly (Fig. S20b).

Intenisty (a. u.)

Comp 2 + Caffeine

I0-I at 470 nm

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Figure 5. (a) Fluorescence decay profile of 2 at 370 and 470 nm upon excitation at 300 nm in water. b) Fluorescence titrations of 2 (10 µM) with caffeine at pH 7.0 in water (excitations at two different wavelengths 250 and 350 nm). (c) Selectivity studies with 2 (10 µM, em = 470 nm) at two different wavelengths 250 and 350 nm (1: +adenine, 2: +guanine, 3: +cytosine, 4: +thymine, 5: +uracil, 6: +indole, 7:+ theophylline, 8: +theobromine, 9: +caffeine, 10: +tryptophan, 11: +serotonin, 12: +melamine, 13: +uric acid, 14: +imidazole).

Role of substitutions in alteration of sensing behavior: Monomer vs. Aggregate Next we modulated the extent of aggregation by changing the substitutions on the carbazole unit (for all the studies here, ex = 300 nm). For this purpose, a library of diverse probes was constructed by varying both the R1 and R2 sites of carbazole moiety with different functionalities (Fig. S21). First, emission spectra of all the compounds were recorded at pH 7.0 in water and the corresponding quantum yields were determined (Table S5). Variations at the carbazole N-centre (R1) exhibited less pronounce effect on the molecular selfassembly, which consecutively showed not much alteration in the caffeine-sensing property of the probe molecules (Fig. S22). However, a change at the R2 site showed a prominent influence on the molecular aggregation as well as their sensing behaviour. The presence of an electron-donating functionality like -C≡CH, -CH2OH, -CO2- induced decrease in the extent of aggregation, as evidenced by the blue shift in emission maxima. On the other hand, the introduction of electron withdrawing groups like -CHO, -NO2 resulted in the formation of highly red-shifted emission spectra corresponding to the aggregated species (Fig 6a & 6b). Accordingly, we have focused on three compounds having different R2 functionalities such as -CHO, -C≡CH, and -NO2 and investigated their interaction pattern with caffeine in more detail (Fig. 6c). The compound with the strongest electron-donating group (R2 = -C≡CH, in least aggregated state) showed the highest degree of interaction with caffeine followed by –CHO and –NO2. On the other hand, the selectivity coefficient toward caffeine followed the exactly opposite trend, R2 = -NO2 > -CHO > -C≡CH. Thus, the optimum selectivity for caffeine over other structurally related


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analytes with sufficiently high sensitivity was observed with the compound having R2 = –CHO (Fig. S23, Table S6). -CCH

(b) (a) 1.0 0.8

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potential map (b) diagram (B3LYP/6-31 G* method). (c) Molecular characteristics of compounds (B3LYP/6-31 G* method).

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Figure 6. (a) Emission spectra of compounds (10 µM, ex = 300 nm) with different peripheral substitutions in water, pH 7.0. (b) Solid-state emission of compounds (R2= -NO2, R2= -CHO and R2= -CCH). (c) Change in the emission intensity of compounds (at 470 nm) upon gradual addition of caffeine in water (pH 7.0).

In addition to this, we have also studied the effect of changing the number of –CHO functionality on the extent of caffeine sensing. As expected, an increase in the number of –CHO groups could enhance the extent of molecular assembly and induce prominent red-shift in emission maxima. Here also, the sensitivity toward caffeine was found to be inversely proportional to the propensity to molecular self-aggregation (Fig. S24). Further, to verify this fact, we included another compound 11 in the sensing studies. The compound showed the existence of both monomer and aggregate emission band in water due to the presence of two hydrophobic carbazole units along with a hydrophilic piperazine appended oxyethylene linker. The addition of caffeine showed a relatively higher degree of emission quenching at the monomer band (at 370 nm) than that of the aggregate band (at 470 nm) (Fig. S25).

The electronic features of the compounds were well described in terms of two structural parameters: i) Mullikan charge distribution at the peripheral carbon ends (assigned as ‘a’) and ii) the overall dipole moments of the compounds, µD. The presence of electron withdrawing substituents induced lowering of negative charge density on the carbon center ‘a’ with a sharp increase in the dipole moment value (Fig. 7c). Higher extent of charge separation (high µD value) could be correlated with the greater degree of self-aggregation. Overall charge distribution as visualized from the electrostatic potential map (EPM) also supported the above conjecture (Fig 7b). The π-stacked conformations of the caffeine complexes were found to be greatly affected by the electronics of the carbazole end-functionality. In the presence of electron withdrawing substituents (R2 = NO2), two interactive moieties (caffeine and compound) were found to be shifted far apart from each other, rendering smaller spectral change (Fig S26). The possession of low-lying LUMO by the electron-deficient caffeine in comparison with each of these carbazole derivatives indicated that electron-transfer always occurred from compounds to caffeine (Fig. S27). As expected, in caffeine complexes also, the HOMO was found to be largely concentrated on the carbazole moiety, while LUMO mainly located on the caffeine. (a)

R2 = -CCH

(c)

Theoretical investigations: Insights into the substituent effect To investigate the mode of interaction with caffeine, density functional calculations were performed employing hybrid B3LYP functional and 6-31G* as the basis set.47-48 For the complete understanding, we have considered three different compounds with various end functional groups (R1 = -C2H5, and R2 = -C≡CH, -CHO, -NO2) (Fig 7a).

R2 = -CHO

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Figure 8. (a) Energy minimized structures of compound (R2 = -CHO) with different analytes (B3LYP/6-31 G* method) (b) Interaction parameters of different analytes with compound (R2=-CHO).

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Figure 7. Energy minimized structures of compounds (R1 = -C2H5, R2 = C≡CH, R2 = -CHO, and R2 = -NO2) (a) with corresponding electro-

To elucidate the selectivity of the probe (R2 = CHO) toward caffeine, we performed energy minimization of the complexes with theophylline and theobromine as well (Fig. 8a). The higher π-stacking distances for theophylline (d = 7.15 Å) and theobromine (d = 6.04 Å) complexes suggested less effective interaction as compared to caffeine (d = 3.72 Å). A more negative value of ΔΔG≠ (-6.35 Kcal/mol) was observed for caffeine interaction indicating the spontaneous nature of the caffeine-induced hetero-aggregation process with others (Fig. 8b & Table S7). Even the binding energy (considering BSSE counterpoise correction) for caffeine adduct (ΔE = 13.1 kcal/mol) was estimated to be higher than that of theophylline (5.9 kcal/mol) and theobromine (9.2 kcal/mol) analogs (Fig 8b).49-50 Single probe with multifaceted applications in real-life



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Wavelength (nm)

600

Analytes added 3.6 mM

Figure 9. (a) Emission spectra of compound 2 (10 µM, ex = 300 nm) upon gradual addition of caffeine (0-0.5 mM) in 20% urine solution (b) Interaction of different components of Anacin® tablet with 2 in water (pH 7.0).

A good correlation (r2 = 0.998) between these two parameters concluded that the present system does not suffer from any potential interference from the other urinary components. Furthermore, to prove this, we also recorded the emission spectra of 2 in presence of other commonly encountered urine metabolites (uric acid, creatinine, nicotine etc). No other analytes except caffeine induced any detectable change in the fluorescence response (Fig. S28). Similarly, quantification of caffeine level in human blood serum is also important for preventing the health diseases caused by excess caffeine intake. Blood plasma caffeine level for regular coffee drinkers generally varies from 2-10 mg/L, while it could be raised up to 40400 mg/L in case of acute overdose.52 Thus we also monitored the change in the emission intensity of the compound 2 upon addition of caffeine (0.1 to 0.5 mM) in diluted serum condition, 10% in water (Fig. S29). The linear correlation between the emission responses and the concentrations of injected caf-

Tea Coffee Decaff coffee

1.0

Intensity of Cyan Color

(b)

Only Comp 2

120

60

Estimation of caffeine in pharmaceutical drugs The tablet ‘Anacin’ is commonly prescribed for severe forms of headache. It mainly contains aspirin and caffeine as the major constituents. However, excess intake of Anacin may cause dizziness, nervousness, irritability, nausea etc.53 Therefore we were interested in measuring the caffeine level present in Anacin for its quality verification (Fig. S30). For this purpose, we have studied interaction of 2 with caffeine in diluted (20%) water extract of Anacin by measuring the changes in the emission intensity at 470 nm band. A fluorescence recovery experiment was performed to compare the concentrations of actually injected caffeine with its calculated values (Table S8). A good linear correlation between these two parameters again concluded the robustness of the present protocol. Moreover, no potential interference was observed from the other components like aspirin, ibuprofen, sucrose, glycerol etc. present in Anacin (Fig 9b).

50

100

150

200

Vol of tea or coffee extract ( L)

Vol of soft-drinks extract ( L)

150

I0/I at 470 nm

(a)

feine (r2 = 0.977) again ensured a quantitative estimation of caffeine in the unknown serum sample. The minimum detectable concentration, in this case, was calculated as low as 10.3 µg/L.

F0/F at 470 nm

Estimation of caffeine in human urine sample: Instant ‘dope-test’ Caffeine is known for stimulating the central nervous system and reduces fatigue. Till 2004, caffeine was considered as the restricted drug by the International Olympic Committee. Even now, NCAA (National Collegiate Athletic Association) has imposed a restriction on the maximum caffeine intake by setting a urinary cut-off level of 15 µg/mL for athletes.51 Therefore, effective detection of the caffeine level in the urine sample is an essential part of conventional ‘dope-analysis’. To validate this, we have further recorded the emission spectra of 2 in diluted urine (20% in water) with the gradual addition of caffeine from 0.1 to 0.5 mM (Fig. 9a). A good linear correlation between the emission response and the concentration of spiked caffeine (r2 = 0.993) indicates that this could be exploited for the estimation of an unknown amount of caffeine in urine. The minimum detectable concentration, in this case, was found to be 8.2µg/L, which is lower than the NCAA permitted cut-off level. To ensure the quantitative nature of the protocol, a recovery experiment was performed by comparing the concentrations of actually injected caffeine in the urine sample with its calculated values as obtained from spectral changes. F. I. (a. u.)

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To endorse the present protocol in addressing different reallife problems, we selected compound 2 as the representative candidate. The high selectivity toward caffeine, more prominent visual response and higher water solubility together ensured the supremacy of 2 over others.

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0

0.5

1

1.5

2

2.5 3 mM

1.0 0.8 0.6

(d)

0.4

2

2

0.2 0.0 0.0

0.5

1.0

1.5

2.0

2.5

Caffeine added (mM)

3.0

Coffee extract Addition of coffee extract

Figure 10. Changes in the emission intensity of 2 (10 µM, ex = 300 nm) upon addition of caffeine extract obtained from (a) different cold-drinks (b) tea/coffee. (c) Images captured under 365 nm UV lamp after addition of increasing amounts of caffeine (the change in intensities have been quantified by ImageJ software). (d) Change in emission color of test strips upon addition of coffee extract.

Estimation of caffeine in common beverages Caffeine is one of the most popular psychoactive drugs resulting in a global annual consumption of 120,000 tons.54 The common sources of caffeine are tea, coffee, and different commercially available soft drinks, like Pepsi, Coca-Cola, Red bull, Mountain dew etc. Monitoring of caffeine level in these beverages is crucial for the patients suffering from osteoporosis, heart disease etc. Considering this, we have measured caffeine level in tea, coffee and four different popular soft drinks (Mountain dew, Pepsi, Coca-cola and Red-bull) using the protocol developed herein (Fig. S31 & S32, Table S9). In every instance, depending upon the amount of caffeine present in the sample, we observed quenching in the molecular emission to a different extent (at 470 nm band) (Figure 10a). Furthermore, we have also estimated caffeine level in commercially available tea, coffee and decaffeinated coffee (Fig. S31). The amount of caffeine in decaffeinated coffee was appeared to be


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significantly low as compared to normally available coffee (Fig. 10b). Thus, our developed method showed an enormous potential in detection and quality control of various caffeinated and decaffeinated daily life products (Table S10). Rapid on-site detection Considering the huge popularity of the caffeinated beverages across the globe, we felt it will be useful to apply the present method for rapid, onsite detection of caffeine. In this context, low-cost paper strips appears to be one of the most attractable options.55-56 Immobilization of 2 on precoated TLC plates was achieved by dipping them into the CHCl3/MeOH (1:1) solution of 2 and then air-dried. The cyan fluorescence of 2 was clearly visible under a standard UV light source. The paper strips were kept at room temperature (open-air condition) for several days. No significant loss in the emission intensity was observed (as quantified by ImageJ software) even after >6 days (Fig. S33). This high stability of the paper strips at ambient conditions suggests that they can easily be used for on-site applications. However, upon treatment with a few drops of caffeine-containing water, a rapid change in emission color was observed from cyan to blue. The concentrationvariation studies with caffeine indicated a dose-dependent variation in the emission color. A linear dependency between these two parameters also indicated that the probe can quantify the concentration of caffeine even in the unknown samples (Fig. 10c). Additionally, the interference studies were performed in the presence of other structurally-relevant analytes (Fig. S34). Among them, the extent of color change was found to be the most pronounced with caffeine. This same effect was also witnessed, when instead of pure caffeine solution we directly applied diluted coffee extract (Fig. 10d). Thus these observations clearly indicated that the present inexpensive protocol can be used for rapid on-site estimation of caffeine without involving any sophisticated instrumental facilities or trained technicians. Thus common people with very limited knowledge in science will also be able to use this method without many difficulties. CONCLUSIONS In conclusion, we have developed a series of easily synthesizable carbazole-based fluorescent organic nanoaggregates (FONs) and investigated their excitation triggered alteration in sensing behavior involving caffeine as model analyte. By choosing proper excitation channel, specific stimulation of either the monomer or the aggregated species was possible, which in turn affected the sensing ability of the probe molecules to a great extent. The monomer species showed better sensitivity with caffeine, while ‘strongly assembled’ nanoaggregates exhibited superior selectivity. The extent of selforganization was also found to be regulated by the micropolarity of the local environment and the electronic influence of the functional groups attached to the core organic scaffold. Moreover, this is the first report on caffeine sensing in water utilizing fluorescent organic nanomaterials. Additionally, the present protocol was employed in real-life sample analysis including complex biological fluids, pharmaceutical drugs, and common beverages. Portable color strips were developed for rapid, on-site estimation of caffeine.

ASSOCIATED CONTENT

Supporting Information The file contains additional UV-visible and fluorescence spectra, 1 H-NMR titrations plots, microscopic images, DLS/Zeta potential measurements and detail characterization of compounds involved in the present study.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT S.B. thanks DST (J. C. Bose Fellowship) for the financial support of this work. N.D. and BM thanks IISc for research associate fellowship and the Indian Association for the Cultivation of Science, Kolkata for the financial support of this work presented in this manuscript.

REFERENCES 1. 2. 3.

4. 5.

6. 7. 8. 9. 10. 11.

12. 13.

14. 15. 16. 17. 18.

19.

20. 21. 22. 23. 24.

Couvreur, P.; Crit Rev Ther Drug Carrier Syst. 1988, 5, 1 - 20. Wang, F.; Han, M. Y.; Mya, K. Y.; Wang, Y.; Lai, Y. H. J. Am. Chem. Soc. 2005, 127, 10350 - 10355. Barman, S.; Mukhopadhyay, S. K.; Behara, K. K.; Dey, S.; Pradeep Singh, N. D. ACS Appl. Mater. Interfaces 2014, 6, 7045 - 7054. Tang, F.; Wang, C.; Wang, J.; Wang, X.; Li, L. ACS Appl. Mater. Interfaces 2014, 6, 18337 - 18343. Wang, Z.; Yong, T. Y.; Wan, J.; Li, Z. H.; Zhao, H.; Zhao, Y.; Gan, L.; Yang, X. L.; Xu, H. B.; Zhang, C. ACS Appl. Mater. Interfaces 2015, 7, 3420 – 3425. Zhang, J.; Chen, R.; Zhu, Z.; Adachi, C.; Zhang, X.; Lee, C. S. ACS Appl. Mater. Interfaces 2015, 7, 26266 - 26274. Yang, Y.; Wang, X.; Cui, Q.; Cao, Q.; Li, L. ACS Appl. Mater. Interfaces 2016, 8, 7440 –7448. Cui, J.; Kwon, J. E.; Kim, H. J.; Whang, D. R.; Park, S. Y. ACS Appl. Mater. Interfaces 2017, 9, 2883 – 2890. Silinsh, E. A.; Springer-Verlag, Berlin, 1980, Chap. 1. Bhattacharya, S.; Biswas, J. Nanoscale 2011, 3, 2924 - 2930. Bhosale, S. V.; Kalyankar, M. B.; Nalage, S. V.; Lalander, C. H.; Bhosale, S. V.; Langford, S. J.; Oliver, R. F. Int J Mol Sci. 2011, 1464 - 1473. Huang, J.; Peng, A.; Fu, H.; Ma, Y.; Zhai, T.; Yao, J. J. Phys. Chem. A 2006, 110, 9079 –9083. Tanioka, M.; Kamino, S.; Muranaka, A.; Shirasaki, Y.; Ooyama, Y.; Ueda, M.; Uchiyama, M.; Enomoto, S.; Sawada, D. Phys. Chem. Chem. Phys. 2017, 19, 1209-1216. Nehlig, A.; Daval, J. L.; Debry, G. Brain Res. Brain Res. Rev. 1992, 17, 139-170. Rapuri, P. B.; Gallagher, J. C.; Kinyamu, H. K.; Ryschon, K. L. Am J Clin Nutr. 2001, 74, 694-700. Smith, A. Food Chem Toxicol 2002, 40, 1243 - 1255. Lovallo, W. R.; Whitsett, T. L.; Absi, M. Al.; Sung, B. H.; Vincent, A. S.; Wilson, M. F. Psychosom Med. 2005, 67, 734 - 739. Oberleitner, L.; Grandke, J.; Mallwitz, F.; Resch-Genger, U.; Garbe, L. A.; Schneider, R. J. J. Agric. Food Chem. 2014, 62, 2337 – 2343. Huang, M.; Gao, J. Y.; Zhai, Z. G.; Liang, Q. L.; Wang, Y. M.; Bai, Y. Q.; Luo, G. A. J Pharm Biomed Anal. 2012, 62, 119 128. Wu, J.; Xie, W.; Pawliszyn, J. Analyst 2000, 125, 2216 - 2222. Waldvogel, S. R.; Frohlich, R.; Schalley, C. A. Angew. Chem., Int. Ed. 2000, 39, 2472 - 2475. Fiammengo, R.; Crego-Calama, M.; Timmerman, P.; Reinhoudt, D. N. Chem.–Eur. J. 2003, 9, 784 - 792. Wu, J.; Isaacs, L. Chem.–Eur. J. 2009, 15, 11675 - 11680. Rochat, S.; Steinmann, S. N.; Corminboeuf, C.; Severin, K. Chem. Commun. 2011, 47, 10584 - 10586.



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

25. Luisier, N.; Ruggi, A.; Steinmann, S. N.; Favre, L.; Gaeng, N.; Corminboeuf, C.; Severin, K. Org. Biomol. Chem. 2012, 10, 7487 - 7490. 26. Xu, W.; Kim, T. H.; Zhai, D.; Er, J. C.; Zhang, L.; Kale, A. A.; Agrawalla, B. K.; Cho, Y. K.; Chang, Y. T. Sci. Rep. 2013, 3, 2255 (1-7). 27. Goswami, S.; Mahapatra, A. K.; Mukherjee, R. J. Chem. Soc., Perkin Trans. 1 2001, 0, 2717 - 2726. 28. Mahapatra, A. K.; Roy, J.; Sahoo, P.; Mukhopadhyay, S. K.; Roy Mukhopadhyay, A.; Mandal, D. Bioorg. Med. Chem. Lett. 2012, 22, 5379 - 5383. 29. Siering, C.; Kerschbaumer, H.; Nieger, M.; Waldvogel, S. R. Org. lett. 2006, 8, 1471 – 1474. 30. Ghosh, A. K.; Ghosh, C.; Gupta, A. J. Agric. Food Chem. 2013, 61, 3814 – 3820. 31. Maji, B.; Kumar, K.; Kaulage, M.; Muniyappa, K.; Bhattacharya, S. J. Med. Chem. 2014, 57, 6973- 6988. 32. Maji, B.; Kumar, K.; Muniyappa, K.; Bhattacharya, S. Org. Biomol. Chem. 2015, 13, 8335 - 8348. 33. Dey, N.; Bhattacharya, S. Chem. Commun. 2017, 53, 5392 – 5395. 34. Bhattacharya, S.; Thomas, M. Tetrahedron Lett. 2000, 41, 10313 - 10317. 35. Bhattacharya, S.; Guliyani, A. Chem. Commun. 2003, 0, 1158 1159. 36. Kumari, N.; Jha, S.; Bhattacharya, S. Chem. Asian J. 2014, 9, 830 - 837. 37. Dey, N.; Samanta, S. K.; Bhattacharya, S. ACS Appl. Mater. Interfaces, 2013, 5, 8394-8400. 38. Dey, N.; Bhattacharya, S. Anal Chem., 2017, 89, 10376- 10383. 39. Ballesteros, E.; Moreno, D.; Gomez, T.; Rodrıguez, T.; Rojo, J.; Garcıa-Valverde, M.; Torroba, T. Org. Lett. 2009, 11, 1269 1272. 40. Dey, N.; Samanta, S. K.; Bhattacharya, S. Chem. Commun. 2017, 53, 1486 - 1489. 41. Dey, N.; Bhattacharya, S. A. Chem. Rec. 2016, 16, 1934 - 1949. 42. Lu, Y. W.; Tan, Y. Q.; Gong, Y. Y.; Li, H.; Zhang, W.; Zhang, Y. M.; Tang, B. Z. Chin Sci Bull. 2013, 58, 2719 - 2722. 43. Fuentealba, D.; Thurber, K.; Bovero, E.; Pace, T. C. S.; Bohne, C. Photochem Photobiol Sci. 2011, 10, 1420 - 1430. 44. Amirjani, M. R.; Sundqvist, C. Photosynthetica 2006, 44, 83 92. 45. Naik, L. R.; Math, N. N. Indian J Pure & Appl Phys 2005, 43, 743 - 749. 46. Proc, J. L.; Kuzyk, M. A.; Hardie, D. B.; Yang, J.; Smith, D. S.; Jackson, A. M.; Parker, C. E.; Borchers, C. H. A J. Proteome Res. 2010, 9, 5422 - 5437. 47. Dey, N.; Ali, A.; Podder, S.; Majumdar, S.; Nandi, D.; Bhattacharya, S. Chem. ‐ Eur. J., 2017, 23, 11891-11897. 48. Dey, N.; Bhattacharya, S. Chem ‐Eur J., 2017, 10.1002/chem.201703034. 49. Daza, M. C.; Dobado, J. A.; Molina, J. M. J. Chem. Phys. 1999, 110, 11806 - 11813. 50. Han, Y. K.; Kim, K. H.; Son, S. K.; Lee, Y. S. Bull. Korean Chem. Soc. 2002, 23, 1267 – 1271. 51. Burke, L. M. Appl Physiol Nutr Metab. 2008, 33, 1319 - 1334. 52. Franco, R.; Onatibia-Astibia, A.; Martinez-Pinilla, E. Nutrients. 2013, 5, 4159 - 4173. 53. http://www.drugs.com/cdi/anacin.html 54. Gilbert, R. M. Prog Clin Biol Res. 1984, 158, 185 - 213. 55. Kumari, N.; Dey, N.; Bhattacharya, S. Chem. Asian J., 2014, 9, 3174 - 3181. 56. Dey, N.; Bhagat, D.; Cherukaraveedu, D.; Bhattacharya, S. Chem. –Asian J., 2017, 12, 76-85.


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For TOC only Tunable Sensing

Tunable Aggregation

Monomer

O

Caffeine

O

H N N

N

N

N

O

N

N

Caffeine H O

Nanoaggregate


A Versatile Probe for Caffeine Detection in Real-Life Samples via

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