Cellulose Nanocrystal-based Colored Thin Films for Colorimetric

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Cellulose Nanocrystal-based Colored Thin Films for Colorimetric Detection of Aldehyde Gases Wonbin Song, Jong-Kwon Lee, Mi Sic Gong, Kwang Heo, Woo-Jae Chung, and Byung Yang Lee ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b19738 • Publication Date (Web): 02 Mar 2018 Downloaded from http://pubs.acs.org on March 3, 2018

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ACS Applied Materials & Interfaces

Cellulose Nanocrystal-based Colored Thin Films for Colorimetric Detection of Aldehyde Gases Wonbin Song,1 Jong-Kwon Lee,2 Mi Sic Gong,3 Kwang Heo,4 Woo-Jae Chung,3 and Byung Yang Lee1,* 1

Department of Mechanical Engineering, Korea University, Seoul 02841, Korea

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Department of Nanostructure Technology, National Nanofab Center, Daejeon, 34141, Korea

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Department of Integrative Biotechnology, Sungkyunkwan University, Suwon 16419, Korea

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Department of Nanotechnology and Advanced Materials Engineering, Sejong University, Seoul

05006, Korea KEYWORDS: Cellulose nanocrystals, Colorimetric sensor, Ionic liquid, 1-butyl-3methylimidazolium, Aldehyde sensor

ABSTRACT

We demonstrate a controllable and reliable process for manifesting color patterns on solid substrates using cellulose nanocrystals (CNCs) without the use of any other chemical pigments. The color can be controlled by adjusting the assembly conditions of the CNC solution during a

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dip-and-pull process while aiding the close packing of CNCs on a solid surface with the help of ionic liquid (1-butyl-3-methylimidazolium (BmimCl)) molecules that screen the repelling electrostatic charge between CNCs. By controlling the pulling speed from 3 to 9 mm/min during the dip-and-pull process, we were able to control the film thickness from 100 to 300 nm, resulting in films with different colors in the visible range. The optical properties were in good agreement with the finite-difference time-domain (FDTD) simulation results. By functionalizing these films with amine groups, we developed colorimetric sensors that can change in color when exposed to aldehyde gases such as formaldehyde or propanal. A principal component analysis (PCA) showed that we can differentiate between different aldehyde gases and other interfering molecules. We expect that our approach will enable inexpensive and rapid volatile organic compound (VOC) detection with on-site monitoring capabilities.

1. INTRODUCTION Cellulose nanocrystals (CNCs) are nanoscale materials derived from various native cellulose sources such as bacteria, cotton, algae, wheat straw, and softwood pulp.1-3 Recently, CNCs have attracted considerable research interest owing to their remarkable physical and chemical properties.4 In particular, CNCs show unique optical properties where they form colored structures due to their liquid-crystalline arrangements.5-6 These optical properties of CNCs have been used to demonstrate biofriendly wrapping papers,7 humidity and pH sensors,8-9 and security encryption in banknotes.10 However, the mass production and commercialization of these devices still require a reliable and fast CNC color formation method. Thus, there have been extensive efforts to develop facile processes to form structural colors using CNCs in both the


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solution and solid phases. For example, the tuning and aligning of the liquid-crystalline structures in the liquid phase have been demonstrated using the CNC’s ability to self-organize into chiral nematic phases induced by external electric fields,11 magnetic fields,12 or chemically interactive additives.13 On the other hand, the formation of colored structures on solid substrates has been proposed, e.g., by Dumanli et al., where CNC-based color films on Petri dish surfaces were formed by self-assembly during evaporation as the solvent slowly evaporated to create stacked structures of CNCs with optical characteristics.14 However, this evaporation approach inevitably suffers from certain limitations, making them unsuitable for practical use. First, it takes a few days for the solvent in the colored film to completely dry and become solid.14 Second, the fabricated films generally show polydomained patterns with uneven colorization at the surface.15-16 Third, the solid films often have poor mechanical properties such as a large brittleness. To overcome these problems, a much faster method based on the vacuum filtration of CNCs was proposed by Chen et al.17 However, the resulting color had a low saturation value, and the substrate of the colored film was limited to vacuum filter papers. Therefore, simple alternative strategies for fabricating colored CNC films on solid substrates are still in demand. In this paper, we show a simple and controllable color formation method of CNCs on solid substrates. This was made possible by using an ionic-liquid-assisted assembly method of CNCs. This resulted in CNC films with controllable colors and with structures stable enough for further chemical modifications. Compared to previous works, this method provides faster fabrication and a wider range of color-controlling ability. Furthermore, our process is versatile enough to be applied to diverse solid substrates, in contrast to Chen et al.17 The robust structure and controllable color of our CNC films enabled the demonstration of CNC-based colorimetric sensors for aldehyde gas detection by chemically functionalizing the CNC films with amine


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groups. When aldehyde gases reacted with the amine groups, the CNC films showed both chemical and physical changes such as swelling, resulting in a color change detectable by the naked eye at high concentrations and by digital cameras at parts per million levels. Data processing based on a principal component analysis (PCA) shows that we can differentiate between aldehyde gases and other volatile organic compounds (VOCs) such as chloroform, isopropanol, and xylene. Since CNCs also have other advantages such as a wide availability, low cost, and biocompatibility compared to other nanoscale biomaterials such as viruses, peptides, or chitosan

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, we expect that the proposed CNC-based film sensor may be used in the future as

low-cost, disposable, and environmentally friendly aldehyde detection systems with on-site monitoring capabilities.

2. EXPERIMENTAL SECTION 2.1 Materials A pulp-based filter paper (Filter Paper No.1, Whatman, USA) was used as the CNC source. Deionized (DI) water (resistivity = 18 MΩ·cm) was used for all experiments. Sulfuric acid (H2SO4, 69–71 wt%, Daejung, Korea) was prepared and used for the cellulose hydrolysis process. 3-Aminopropyltriethoxysilane (APTES, ≥98.0%, Sigma-Aldrich, USA), toluene (anhydrous, ≥99.8%, Sigma-Aldrich, USA), and 1-butyl-3-methylimidazolium chloride (BmimCl, ≥98.0%, Sigma-Aldrich, USA) were purchased and used without further purification. Standard formaldehyde gas (≥99.999%, 100 ppm, Rigas Inc., Korea) was used as the target material for the sensing experiments. Other gas sources (propanal, chloroform, isopropanol, and xylene) were purchased from Sigma-Aldrich.


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2.2 Preparation of the CNC solution CNCs suspended in DI water were prepared by performing hydrolysis, centrifugation, and dialysis in sequence.21 First, H2SO4 (65 wt%) and Whatman Filter Paper No.1 (7 g of filter paper per 10 mL) were mixed by magnetic stirring at 63°C for 30 min and quenched in 5 L of DI water for 6 h. The resulting ivory-white suspension was centrifuged at 12000 rpm three times for 10, 20, and 30 min, respectively. Each time, the suspension was redistributed and sonicated at 300 W for 15 min in DI water. After the final centrifugation, a syringe filter (Whatman GX/D PVDF 0.45 µm, GE Healthcare Life Science, USA) was used to remove cellulose bundles that were not fully chopped by the hydrolysis process. Afterwards, the acidity of the CNC solution was controlled to pH ~ 4.3 by dialysis (MWCO 10 kDa membrane, 35 mm ID, Thermo-Fisher Scientific, USA) while changing the bath DI water every 12 h for 5 days. One more round of centrifugation and filtering followed after the dialysis. The CNC concentration in DI water was calibrated to have a concentration of 4 mg/mL at an absorbance of 0.36 under 266-nm light using a spectrophotometer (Cary 8454, Agilent, USA). Finally, for each 1 mL of the above CNC solution, 0.8 mg of BmimCl was added, and the resulting solution was left to stand for more than 3 h before use.

2.3 CNC film fabrication and analysis Silicon substrates (5 mm × 20 mm) were washed with acetone and cleaned with O2 plasma for 15 min. The substrates were then vertically immersed in the prepared BmimCl/CNC solution and then pulled at a rate of 3–9 µm/min to deposit the CNCs on the silicon substrate. This pulling process was performed in a N2-ambient glove box to eliminate external noise and impurities. At each pulling speed, a discrete visible-colored thin film formed by the self-assembly of the CNCs.


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The speed of drawing the substrate from the solution was precisely controlled by using a vertically positioned syringe pump (LEGATO 110, Kid Scientific, USA) to dip and pull the substrate. Height measurements were obtained by using an atomic force microscope (AFM, NTEGRA Prima, NT-MDT, Russia) in the noncontact mode and by using Gwyddion software (gwyddion.net) for the analysis. The reflective spectra of the color bands were collected using an ultraviolet–visible–near-infrared (UV-Vis-NIR) spectrophotometer (Cary 5000, Agilent, USA) with an integrating sphere module attached for light collection. Visible QI lamp and Deuterium UV lamp were used in spectrophotometer during the reflectance measurement. The integrating sphere was designed to have an incident angle of 8° to collect both scattered and directional reflection, which is similar to the color reception seen with naked eyes. The finite-difference time-domain (FDTD) simulation for modeling the effect of the CNC thickness on the spectral reflectance was performed using Lumerical software (Lumerical Solutions Inc., Vancouver, Canada). The refractive indices of the CNC films were taken from spectroscopic ellipsometry measurements, and the dielectric function of the Si substrates was adopted from Palik.22

2.4 CNC surface modification After fabrication of the colored films, the CNCs, which have abundant hydroxyl groups on their surfaces,23 were functionalized with amine groups. For this purpose, APTES molecules were suspended in 1% v/v toluene. The prepared CNC thin film was immersed in the APTES solution at 60°C for 1 h. The film was then rinsed several times with toluene and annealed at 120°C to dry. This process resulted in no damage to or color change in the CNC films. The modification of the surface functional groups was verified using X-ray photoelectron spectroscopy (XPS) equipment (X-TOOL, ULVAC-PHI Inc., Japan).


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2.5 Aldehyde detection using a CNC colorimetric sensor To monitor and analyze the color changes of the CNC-based color films in response to aldehyde gases and other VOCs, two different experimental setups were designed: static and dynamic. (1) In the static gas sensor setup, a 50-mL Nessler tube was used as the chamber for the placement of the CNC colorimetric sensor and gas injection. A digital microscope (5M, Dinolite, Taiwan) was attached outside the tube to monitor the red, green, and blue (RGB) color change (ΔRGB) of each color band of the CNC color film viewed through the Nessler tube. A MATLAB program (Mathworks Inc., USA) was used for the real-time tracking of the RGB color component intensities of the selected area and data processing. Microsyringes (10 µL and 100 µL, Hamilton, USA) were used to inject a precise amount of target material into the tube. The concentration of the target gas was controlled by adjusting the temperature and vapor pressure of the aldehyde gases (formaldehyde and propanal) and other VOCs (chloroform, isopropanol, and xylene). These gases were selected from well-known list of indoor polluting gases such as VOCs.24 The temperature was controlled by a hotplate with a proportional–integral–derivative (PID) temperature controller (HSD120, Misung, Korea). (2) In the dynamic setup, formaldehyde gas was allowed to flow by connecting one of the branches of the Nessler tube to a flow and pressure controller (GMC1200, Atovac, Korea) and the other branch to an outlet. The flow and pressure controller consisted of two mass flow controllers (water-bubbled N2 and formaldehyde). Water-bubbling was performed to enhance the inverse etherification reaction, where the hydrolysis reaction breaks the ether bond. By adjusting the ratio of these two gases, the concentration of the formaldehyde gas mixture exposed to the CNC film was controlled from 0 to 100 ppm. (SI Figure S1)


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Fourier-transform infrared (FTIR) spectroscopy (LabRam ARAMIS IR2, Horiba Jobin Yvon, Japan) was used to check the specific binding between the target molecules and the amine groups.

3. RESULTS AND DISCUSSION The morphology of the purified CNCs after dialysis was observed with an AFM by fixing a dilute concentration of CNCs on a flat mica substrate (SI Figure S2(a)). The CNCs had a rod-like shape with an average length and diameter of 300 and 6.5 nm, respectively (SI Figure S2(b)). CNCs are known to form chiral nematic structures when dispersed in liquids and reflect a specific optical wavelength, presumably due to their rod-like morphology, surface charge, or molecular structure.25 To show the liquid crystallinity of our CNCs, a CNC solution in DI water was placed between two orthogonally placed linear polarizers (SI Figure S2(c)). The birefringence observed from the CNC solution indicated liquid-crystalline structures in the solution.23 The CNC solution concentration was calibrated from the absorbance-to-concentration relation using a spectrophotometer (Figure S3). We used 266-nm light to measure the CNC absorbance, as per previous reports.26-27 For CNC concentrations below 4 mg/mL, a linear relationship was observed between the CNC concentration and the absorbance for 266-nm light. Below the 4mg/mL range, according to the Beer–Lambert law, the theoretical calibration curve fit well to the absorbance data. By fitting the graph for the 0 to 4 mg/mL region to a straight line passing the origin, we obtained a slope of 0.09571 with a standard error of 0.00314. At high concentrations, the calibration curve showed a negative deviation from the fitting line, which can be attributed to


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the increase in the number of interaction between the CNC particles and water molecules.28 Throughout our experiments, we utilized only CNC solutions with a concentration of 4 mg/mL. Figure 1 shows a schematic of the fabrication of the CNC-based color film. A silicon wafer was simply dipped into and pulled from the CNC solution including the ionic liquid BmimCl at a constant speed. The role of the Si wafer was to provide a mirror-like flat surface for CNC assembly and also enhance the intensity of the reflected light under ambient light conditions. Here, the CNCs have a negative surface charge due to the –C–O–SO3– motifs on the surface created during the acidic hydrolysis process.21 Many additives such as polyethylene glycol, carbon nanotubes, and dimethylformamide, have been used to manipulate the interactions among CNC particles.29-31 These studies succeeded in changing the interparticle interactions and the corresponding pitch of the self-assembly structure. In particular, Liu et al. proposed the use of the ionic liquid 1-allyl-3-methylimidazolium chloride (AmimCl) as a plasticizer to fill the spaces between cellulose fibers, resulting in iridescent CNC films with adjustable mechanical and optical properties.32 However, their film lacked clear colors, and control of color was limited to only a certain hue. In this study, BmimCl was not used as a plasticizer but instead used as a charge screening agent that aids the close packing of CNC fibers during CNC self-assembly, resulting in more stable structures and clear color patterns. BmimCl is a material that has a similar structure to AmimCl, except for the length of the carbon backbone chain, and is more stable at room temperature owing to its higher melting temperature. It is also lower in cost compared to AmimCl. The FTIR measurements of CNCs, BmimCl, and the mixture thereof showed results similar to those obtained previously with AmimCl (SI Figure S4). In the spectra, the peak (1600– 1650 cm-1) related to the N=H double bonds abundant in BmimCl increased after BmimCl


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incorporation, whereas the peak (850–900 cm-1) related to the symmetrical C–O–S vibration from the –C–O–SO3– end decreased, probably owing to the electrostatic interaction with imidazolium32. Furthermore, the peak from the vibration of the hydroxyl group on the CNCs with the initial broad range of 300–3600 cm-1 decreased slightly owing to the interaction between cellulose hydroxyl protons and chlorine anions (Cl-) from BmimCl. According to these results, we can observe substantial chemical interactions between the butyl-imidazolium cations (Bmim+) and the negatively charged sulfate half ester groups of the CNCs and the interactions between chlorine anions (Cl-) and the hydroxyl protons of cellulose. As shown in the inset in Figure 1, the BmimCl ionic liquid interacts across the functional groups of CNCs via an ionic interaction. BmimCl is water-soluble and effectively screens the negative charges on the CNC surfaces, resulting in more close-packed structures of CNCs during assembly. By following the fabrication process described in the section above, we obtained thin CNC films with several color variations covering the visible color range (Figure 2(a)). At a pulling speed of 3 µm/min, we obtained a CNC film color with large amount of red hue. As the pulling speed increased, the wavelength of the reflective colors of the films shifted to shorter wavelengths until a dark blue color was obtained at a pulling speed of 9 µm/min. At pulling speeds over 9 µm/min, the color quality decreased significantly, and the CNC films produced a color close to gray, probably due to the insufficient time for assembling CNCs in the water meniscus to form stable structures.33 At pulling speeds below 3 µm/min, the CNCs aggregated to form thick hydrogel-like structures on the solid substrate, which became transparent after drying. Therefore, we concluded that the optimum pulling speed for a CNC film was between 3 and 9 µm/min. It should be noted that the incorporation of BmimCl (0.8 mg per 1 mL of CNC solution) in our CNC solution was critical in obtaining CNC color patterns on a solid substrate. A solution


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with a concentration of BmimCl that was too low did not render color patterns, whereas an excessive concentration resulted in the aggregation of CNCs (SI Figure S5). This shows that the BmimCl ionic liquid enhances the close packing of CNCs, resulting in more stable structures and clear color patterns. The CNC film morphology was investigated by scanning electron microscopy (SEM) and an AFM. Figure 2(b) shows an SEM image of the cross section of a CNC-based colored film. The cross section shows a layered structure. Compared to previous studies, evidence of a chiral nematic structure was not clearly observed from the side view.14 However, we confirmed that we can obtain CNC films with compactly packed CNCs with the dip-and-pull method. To compare the cross-sectional characteristics of samples fabricated at different pulling speeds, we used an AFM to measure the height of the CNC film. We set the silicon substrate as the reference level and measured the average height of the CNC film region as the film height. Figure 2(c) shows an AFM image of a CNC-based colored film (top view). This figure shows that the film has locally aligned CNCs but no long-range alignment, as seen from the top. The uniform film thickness and the lack of chiral nematic structures suggested the use of a thin-film model for optical simulations (to be discussed later). Figure 2(d) shows the relationship between the pulling speed of the substrate from the solution and the thickness of the CNC films deposited during the pulling process. The black line, the blue line and red line in Figure 2(d) correspond to the thicknesses of CNC films measured by AFM, ellipsometry and UV-Vis spectrometer, respectively. All three approaches to find out the thicknesses of the various colored films showed very similar results. This figure shows that the thickness of the self-assembled CNC film decreased with the increase in the extraction speed of the substrate from the prepared solution and vice versa. When the film became thinner, the CNC


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film produced a reflective color closer to blue (shorter wavelength), whereas when the film was thicker, the CNC film showed a reflective color closer to red (longer wavelength). The total reflectance of the CNC films was measured using a UV-Vis-NIR spectrophotometer with an integrating sphere. The intensity of the reflectance included both directional and scattered reflected light. The region between the sample area and the measurement area of the instrument due to a sample/stage size discrepancy was filled with carbon tape (Figure 3(a)). The reflectance of the carbon tape was 1.6% throughout the visible range. The spectral reflectance of the CNC films fabricated at pulling speeds of 3, 4, 5, 6, 7, 8, and 9 µm/min are shown as solid lines in Figures 3(b)–(h), respectively. As the pulling speed increased, the peak wavelength of the measured spectral reflectance blue-shifted. For each prepared sample, the thickness (dCNC) and refractive index (nCNC) of the CNC films were measured by an AFM and ellipsometry, respectively (SI Figure S6). The peak wavelength of the reflectance increased in the visible range with the increase in the thickness of the CNC film, which agrees with the trend shown in Figures 2(a) and (d). Here, it should be noted that the measured refractive index remained around 1.58 for all samples, regardless of the extraction speed. To analyze the observed results, we performed an FDTD simulation assuming that the film is composed of a CNC layer uniformly covering the silicon substrate, as shown in the inset of Figure 3(a). Here, all of the spectral reflectances estimated by the FDTD method were adjusted by a factor of 52.7% to compensate for the size discrepancy between the simulated and measurement areas (Figure 3(a)). As a result, the simulated results were well-fitted to the measured ones (the dashed lines in Figures 3(b)–(h)). A minor discrepancy in the thickness existed between the FDTD simulation fitting and the AFM thickness measurement, as can be seen from Figure 2(d). The variation in the surface roughness of the fabricated samples accounts for this discrepancy. It should be noted that the refractive


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index (1.56–1.59) of the CNC films in the visible range was lower than that of the Si substrate (4–4.5). Thus, when the optical thickness nCNC × dCNC is equal to one-quarter of the wavelength, the destructive interference of light reflected from the interfaces of each layer causes an antireflection effect. The position of the reflectance minimum depended on the optical thickness of the coating and shifted towards longer wavelengths as the optical thickness increased. Moreover, the reflectance increased rapidly on both sides of the minimum reflectance position. Therefore, we observed that the peak position of the spectral reflectance of our samples also shifted to longer wavelengths as the CNC thickness increased. Since we can obtain CNC stable color patterns on solid substrates with an ionic-liquid-assisted self-assembly method, we demonstrated colorimetric sensors for aldehyde detection by functionalizing the films with reactive amine groups. Figure 4(a) shows a schematic of a CNC film used as an aldehyde gas sensor. First, we prepared CNC films with multiple color bands by pulling the solid substrate from the CNC solution with step-wise pulling speeds. The purpose of multiple color bands is to provide an increased amount of data for a successive principal component analysis (to be discussed later). Then, we coated the CNC film surface with APTES by using silane chemistry since CNCs are rich in hydroxyl groups.34-35 The amine functionalization resulted in no significant changes in the color or structure of the CNC films. XPS measurements showed an increased nitrogen (N 1s region) binding energy peak from 399 to 401 eV after APTES surface modification (Figure 4(b)). The increased X-ray count indicates the formation of –C-NH2 bonds.36 To observe the sensing properties of the CNC colorimetric sensor, the amine-functionalized multiple-color-band film was exposed to formaldehyde gas at a high concentration (100 ppm). The reaction formula is R–COH (target gas molecule) + R’–NH2 (sensor surface) → R–CH=N–R


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’+ H2O. According to this formula, aldehyde gas can selectively react with aldehyde group gases. We prepared a CNC colorimetric sensor with three color bands for the gas sensing experiment. Figure 4(c) shows optical images before (left) and after (right) exposure to a formaldehyde concentration of 100 ppm. For concentrations lower than 100 ppm, the color change became more difficult to detect with the naked eye. Therefore, we utilized a USB digital microscope camera and tracked the color change of each band in their corresponding RGB channels (∆RGB). As shown in Figure 4(d), the CNC colorimetric sensor was exposed successively to formaldehyde at concentrations of 10 ppm and 50 ppm, followed by water-bubbled N2 gas to show the recovery of the CNC colorimetric sensor. Here, the water molecules help the recovery of the sensor by helping the hydrolysis of the previously formed ether (R–CH=N–R’+ H2O → R–COH + R’–NH2). As a control, we also tested the CNC colorimetric sensor without any surface modification (SI Figure S7). For 100ppm formaldehyde gas, the color shift was too minute to be discerned with the naked eye, and the value of ∆RGB measured with the USB digital microscope was also negligible compared to those shown in Figure 4(c). The binding event between the amine groups on the CNCs and the aldehydes was confirmed by FTIR spectroscopy. Figure 4(e) shows the FTIR absorbance spectrum from the CNC colorimetric sensor before (black) and after (red) exposure to 100-ppm aldehyde gas for 60 min. The peak corresponding to a C=N double bond (1640–1690 cm-1) is attributed to the chemical reaction between aldehyde and the amine-functionalized group. Furthermore, the peak at 1470 cm-1 related to the stretching of the alkyl C–H bond increased significantly owing to the creation of an alkyl hydrogen branch after the chemical reaction. At the same time, in order to identify the physical changes in the CNC colorimetric sensor during the chemical reaction, an AFM was used for height measurements. Figure 4(f) compares the


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thickness of the amine-modified CNC colorimetric sensor before (black) and after (red) exposure to aldehyde gas. For this, the sample was scratched with a hard indenter to prepare a step height profile. When the film was exposed to 100-ppm aldehyde gas, the thickness increased by 26%. These results indicate that the exposure to aldehyde gas results in both chemical and physical changes in the CNC colorimetric sensor in the form of etherification and swelling. We also observed the morphology of the CNC particles before and after aldehyde gas reaction (Figure S8). The individual CNC particles showed a swelled shape after formaldehyde gas exposure. This infers that the mechanical change is the dominant factor for the reflectance shift in gas reaction. The above real-time sensing experiment was further performed to show the sensitivity and selectivity of our CNC colorimetric sensor. First, ∆RGB in each band was visualized by showing the absolute value of ∆RGB (multiplied by a gain factor of 5) of the bands as representative color bands for different formaldehyde concentrations (Figure 5(a)). Therefore, the less the color change, the darker the representative color, and vice versa. The left-most column in Figure 5(a) shows the control corresponding to no exposure to aldehyde gas. The concentration versus ∆RGB can be used to determine the dissociation constant between the receptor and the target gas molecules.37-38 Figure 5(b) shows the calibration curve for the CNC colorimetric sensor’s color change with respect to the formaldehyde concentration. The most sensitive ∆RGB output to formaldehyde, which was the blue color of the 2nd band, was used in the analysis. A dissociation constant (Kd) of 7.3 ppm was determined for the interaction between the amine functional group and formaldehyde by using Hill’s equation.37-38 It should be noted that 7.3 ppm level reported in our manuscript refers to the dissociation constant, where half of the receptors are occupied by target matters. Actually, as shown in Fig 5(b), the limit of


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detection (minimum concentration with detectable color change) was under 0.5 ppm, which is sub-ppm level. The K constant from Hill’s equation can be an indication of the concentration detectable with naked eyes. The value of Kd = 7.3 ppm is similar to or lower than (more sensitive) the previously reported M13-bacteriophage-based color film, where the typical binding dissociation constant between the bacteriophage-based colorimetric sensors and benzene gas was reported as 23.9 ppm.38 To evaluate the selectivity, the CNC colorimetric sensor was exposed to other VOCs. By using a method similar to the one shown in Figure 5(a), each reaction was visualized as shown in Figure 5(c). The data were the change in the RGB value of the CNC colorimetric sensor for various gases at 100 ppm in a chamber filled with the corresponding gases for a static gas sensor setup. When exposed to aldehyde gases (propanal, formaldehyde) and non-aldehyde gases (chloroform, isopropanol, xylene), our CNC colorimetric films showed superior sensitivity to aldehyde gases. It should be noted that the each gas resulted in different color change ∆RGB pattern and amplitude. PCA was performed for up to two components. A PCA can be used to reduce the dimensional space by enabling the representation of the features of each gas. Here, two principal components accounted for 90% of the variance in the analysis (SI, Table S1). For repeated sensing experiments, exposure to the same type of gas resulted in a very similar color change trend in the ∆RGB trace (SI Figure S9). This similar response to the same gas resulted in the clustering of the data sets in the PCA plot, as shown in Figure 5(d). The response to the aldehyde gases showed data clustering while showing significant separation between clusters on the two-dimensional (2D) PCA plot. This shows that our CNC colorimetric sensor can detect and distinguish different types of aldehydes. Moreover, exposure to nonaldehyde gases showed a negligible data change,


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resulting in data clustering in an isolated narrow region in the PCA plot. This shows that our CNC colorimetric sensor can differentiate between aldehyde and nonaldehyde gases, at least for the gases tested in this work. In spite of the long reaction time, our sensor can enable a powerfree detection to harmful but not critical chemicals that affect indoor air quality.

4. CONCLUSION We demonstrated a controllable and reliable process for manifesting CNC color patterns on solid substrates using an ionic-liquid-assisted self-assembly method. The CNC film color was controlled by adjusting the CNC assembly conditions while aiding the close packing of CNCs on the solid surface with the aid of the ionic liquid BmimCl. The optical properties were in good agreement with the FDTD optical simulations using a simple thin-film model. By functionalizing these films with amine groups, we demonstrated colorimetric sensors that can change in color when exposed to aldehyde gases such as formaldehyde or propanal. A PCA showed that we can differentiate between different aldehyde gases and other interfering molecules. Combined with the other advantages of CNCs such as their availability, low cost, and biocompatibility, we expect that our CNC color manifestation strategy on solid surfaces can be used in developing inexpensive and rapid colorimetric sensors for the detection of VOCs and harmful gases in the near future.

ASSOCIATED CONTENT AFM images, photographs showing birefringence, absorbance measurements, FTIR spectra, photographs of CNC-based films, measurements of the CNC film thickness and refractive index, exposure data, color shift profiles (PDF)


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AUTHOR INFORMATION Corresponding Author *Tel: +82 2 3290 3365; e-mail: [email protected] Give contact information for the author(s) to whom correspondence should be addressed. Present Addresses * Department of Mechanical Engineering, Korea University, Seoul 02841, Korea

ACKNOWLEDGMENTS This project was supported by the National Research Foundation (NRF) (2016M3A7B4909581) and the Global Frontier Project from the Center for Integrated Smart Sensors (CISS-20110031866), funded by the Ministry of Science, ICT & Future Planning. J.-K.L. acknowledges financial support from the R&D Convergence Program of the National Research Council of Science & Technology, Republic of Korea (CAP-16-10-KIMS). ABBREVIATIONS 2D, two-dimensional; AFM, atomic force microscope; AmimCl, 1-allyl-3-methylimidazolium chloride; APTES, 3-aminopropyltriethoxysilane; BmimCl, 1-butyl-3-methylimidazolium; CNC, cellulose nanocrystal; DI, deionized; FDTD, finite-difference time-domain; FTIR, Fouriertransform infrared; NIR, near infrared; PCA, principal component analysis; PID, proportional– integral–derivative; RGB, red, green, and blue; SEM, scanning electron microscopy; UV, ultraviolet; Vis, visible; VOC, volatile organic compound; XPS, X-ray photoelectron spectroscopy.


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Figure 1. Schematic showing the fabrication of CNC-based color films on solid substrates with the aid of ionic liquids. The incorporation of ionic liquids (BmimCl, 1-butyl-3methylimidazolium) enabled more stable color patterns on the solid substrate. The change in the substrate pulling speed during assembly resulted in different film thickness and colors.


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Figure 2. Fabrication of CNC-based colored films. (a) Optical images of the assembled color bands at different pulling speeds (marked as numbers in units of micrometers per minute). (b) Scanning electron microscopy (SEM) image of the cross section of a CNC-based colored film. The cross section showed a layered structure that can be attributed to the helical pitch of liquidcrystalline CNC structures. (c) Atomic force microscope (AFM) images of a CNC-based colored film. The film showed localized alignment but no large-area alignment. (d) Dependence of film thickness of CNC films on the pulling speed during assembly. Thickness value was acquired with AFM (black line), ellipsometry (blue line) and UV-Vis spectrophotometer (red line). The colors can be controlled by modulating the pulling speed during the assembly process.


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Figure 3. Reflectance measurements and simulation results for CNC films. The reflectance spectra were measured (solid line) by a UV-Vis-NIR spectrophotometer equipped with an integrating sphere. An FDTD simulation was performed for each film thickness (dashed line). (a) Schematic representing the optical measurement setup. (b-h) Absolute reflectances of films fabricated with pulling speeds of (b) 3, (c) 4, (d) 5, (e) 6, (f) 7, (g) 8, and (h) 9 µm/min. In the visible wavelength range, as the extraction speed increased, the waveform of the reflectance shifted from right to left.


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Figure 4. Structural and chemical changes in CNC films. (a) Schematic showing the surface modification and target gas binding of CNC-based aldehyde gas sensors. (i) CNC hydroxyl groups on the CNCs are (ii) functionalized with amine using APTES. (iii) Next, a CNC film is exposed to aldehyde, (iv) resulting in etherification and a color shift of the CNC film. (b) X-ray photoelectron spectroscopy (XPS) data in the bonding energy range of 399–401 eV. The new peak after APTES treatment (red) indicates increased N 1s shell emission. (c) Optical images of a CNC colorimetric sensor before (left) and after (right) exposure to 300-ppm formaldehyde gas. (d) RGB color intensity change (∆RGB) during formaldehyde detection and recovery (waterbubbled N2) for three different color bands. (e) Fourier-transform infrared (FTIR) spectra of CNC films after formaldehyde exposure. (f) AFM height profile before (black) and after (red) aldehyde exposure. After aldehyde exposure, the thickness of the CNC film increases. The measurement was performed for the sample in Figure 4(c).


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Figure 5. Selectivity and sensitivity of CNC colorimetric sensors. (a) Visualization of the absolute value of ∆RGB (multiplied by a gain factor of 5) of each band as representative colors for different formaldehyde concentrations. (b) Calibration curve for the color change of a CNC colorimetric sensor with respect to the formaldehyde concentration. The data were fitted to Hill’s equation, and a dissociation constant (Kd) of 7.3 ppm was extracted. (c) Visualization of the absolute value of ∆RGB (no gain factor) of each band as representative colors for several other gases. (d) Principal component analysis (PCA) plot of the color shifts of both aldehyde (black, red) and other nonaldehyde gases (magenta, blue, green); it shows the selectivity of the color film sensor.


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TOC Figure


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Cellulose Nanocrystal-based Colored Thin Films for Colorimetric

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