A room temperature 9CB-based chemical sensor

Abstract

The gas sensing potential of the 9CB (4-cyano-4′-nonylbiphenyl) liquid crystal compound at ambient conditions is investigated. The solid at room temperature 9CB is incorporated in a hybrid gel formulation of ionic liquid/liquid crystal droplets immobilized in a gelatin matrix. Several ionic liquids are tested in order to tackle the crystallization of 9CB and also a 9CB-based mixture with a different smectogen is considered. The resulting formulation demonstrates great analyte responding capabilities and can be considered an alternative format for artificial olfaction purposes.

INTRODUCTION

Liquid crystals are unique materials that combine long-range orientational order and fluidity. A rich variety of liquid crystal phases (or mesophases) exists, such as nematic, cholesteric and smectic phases. They depend on the degree of order in the material and result in distinct physical properties. Liquid crystals exhibit macroscopic anisotropy which manifests in many of their physical properties, the most important one being their optical anisotropy. They are also highly sensitive to disturbances occurring in their organization by external influences such as temperature, electrical or magnetic fields, mechanical shear, surface effects, and chemical analytes. As a consequence, liquid crystals are deemed a fascinating class of functional and responsive materials, which can be used as probes to detect and translate events at the molecular level into measurable outputs and hence find use within a wide variety of technological applications,^[1–9] namely in liquid crystal-assisted chemical and biological sensing technologies.^[6,10–23] The most commonly used liquid crystal sensor geometries include liquid crystal confinement in thin films with a free surface,^[24–28] droplets,^[29–36] and fibers.^[37–41]

Liquid crystal droplets show great potential in sensing platforms because the large surface-area-to-volume ratio enhances the sensitivity and responsiveness. Confinement in a spherical geometry can result in a rich textural diversity, with distinct optical signatures, providing new approaches for manipulating the liquid crystal ordering and the design of sensitive and responsive liquid crystal-based systems for targeted molecular species.

Recently, we have proposed a novel format of volatile organic compounds (VOCs) sensors, representing a new class of hybrid liquid crystal-based gels.^[31,34–36] The gel compositions are comprised by polydisperse self-assembled ionic liquid/liquid crystal droplets which are embedded in a gelatin matrix. The liquid crystals used in our previous studies were the cyanobiphenyl-based 5CB-8CB, exhibiting liquid crystal properties at room temperature. The gel-like materials were tested as chemical sensors in the presence of vapors from various analytes from distinct chemical groups in a custom-made electronic nose (e-nose) device designed to monitor light transmittance. The systematic study of the collected optical signals coupled with microscopy observations revealed two trends for the gel-like sensors. The nematic-based gels (5CB-7CB) respond in a dynamic on/off way during VOC sorption-desorption, as they transition repeatedly between the nematic and the isotropic states. Conversely, the 8CB-based materials yielded more complex responses as they successively transition from the smectic A to the nematic the isotropic states.

In this respect, smectic liquid crystal systems can be very attractive with regards to the topological landscapes that their layered nature has to offer. It should be noted though that for room temperature potential sensor applications, the materials available are quite limited. In this work, we explored the idea of implementing 9CB in the hybrid gel formulation as a systematic continuation of our previous work. Pure 9CB is crystalline at room temperature. It melts at 41.2°C and exhibits the smectic A and the nematic phases at higher temperatures. With the aim of producing a room temperature functional hybrid gel and tackling the high crystallization point, various imidazolium-based ionic liquids were investigated. It is well known that the crystallization process and overall mesophase behavior can be strongly influenced by confinement.^[42] The possibility of incorporating in the hybrid formulation a 9CB mixture instead of the pure compound was also considered. Our proof-concept investigation shows that by tuning the hybrid gel formulation, it is possible to use 9CB-based sensing materials to detect VOCs at room temperature conditions.

RESULTS AND DISCUSSION 9CB-based gel formulations and sensing capabilities

In previous works we have reported a multicomponent gel formulation containing polydisperse self-assembled ionic liquid/liquid crystal droplets embedded in a gelatin matrix^[31,34,35] (see Figure 1). The formulation enables physical compartmentalization of the constituents, since the liquid crystal is confined within droplets with a stable interface established by the ionic liquid component, which in turn provides a preferred liquid crystal anchoring. In addition, the ionic liquid also dissolves the gelatin and allows jellification to occur. An important feature that arises from the formation of the gelatin ionogels is the high robustness of the material to air exposure due to the ionic liquid low vapor pressure.^[36] There,^[31,34,35] the imidazolium-based ionic liquid [C₄MIM][DCA] (Figure 1B) was used to provide homeotropic anchoring to the liquid crystal component. Members of the cyanobiphenyl homologous series (nCB) with n ranging from 5 to 8 (5CB-8CB) were tested in the gel formulation. Those compounds exhibit mesomorphic behavior at room temperature. On the contrary, the next member of the series, 9CB, which similarly to 8CB exhibits the smectic A and the nematic phases, is solid at room temperature and melts at roughly 41.2°C (see Figure 1B for structure and Table 1 in the ESI for phase transitions).

FIGURE 1. A, Hybrid gel spread as a thin film and schematic illustration of the corresponding organization depicting the self-assembled droplets embedded in the gelatin network, (B) chemical structures of the ionic liquids and liquid crystal compounds used here

Unfortunately, when incorporating 9CB in the hybrid formulation the liquid crystal droplets crystallize within a few minutes from spreading, as seen in Figure 2. In addition to this, the crystallization process deforms permanently the spherical shape of the droplets. Upon heating from room temperature and while monitoring the phase transitions of the liquid crystal inside the droplets (Figure 2B) from the smectic A to the nematic phases, one can unequivocally deduce that the droplet interfaces are essentially damaged. It is interesting to note that when rushed to the polarizing optical microscope (POM) immediately after gel spreading, we were able to observe (before crystallization occurred) that the self-assembled droplets presented a ring of toric focal conic defects (see Figure 2A), similar to what has been reported for [C₄MIM][DCA]/8CB droplets.^[31] We need to clarify that the gel preparation and spreading processes were conducted under specific temperature conditions, where 9CB was in the isotropic state, in order to ensure full miscibility in the final formulation. The presence of the ring defects denotes that during our observations the liquid crystal had already cooled down to the smectic A phase. We were never able to observe the nematic phase of the 9CB droplets before the first crystallization occurred, however we can hypothesize that in the nematic phase the formed droplets would exhibit a radial director profile, as previously reported for other cyanobiphenyl liquid crystals. ^[31,34,35]

FIGURE 2. Textural details of [C4MIM][DCA]-based hybrid gels with 9CB for liquid crystal a seen in the POM with crossed polarizers (A) [C4MIM][DCA]/9CB droplet exhibiting a ring of toric focal conic defects before the first crystallization occurs, (B) hybrid gel morphology after crystallization occurred, (C) deformed droplet morphology in the smectic A phase and (D) in the nematic phase upon heating from crystal. The white line corresponds to 50 µm

It is evident that [C₄MIM][DCA] is not the appropriate ionic liquid to contain 9CB and facilitate the formation of stable spherical droplets at room temperature. Due to this finding we opted to explore alternative ionic liquids from the 1-alkyl-3-methylimidazolium chloride family ([C_nMIM][Cl]), which we have investigated in previous studies and have confirmed that they enable droplet formation in the case of 5CB.^[36,43] We tested [C₄MIM][Cl], which is the chloride counterpart of [C₄MIM][DCA], and also [C₈MIM][Cl] and [C₁₂MIM][Cl].

Figure 3 summarizes our findings when using a [C_nMIM][Cl] ionic liquid and 9CB for liquid crystal in the hybrid gel formulation. It is well known that the ionic liquid cation - more specifically the structure, length, and conformation of the aliphatic chain - is mainly responsible for the liquid crystal orientation within the droplets.^[44] It is also possible that the anion presence aids in the stabilization of the droplet interface via hydrogen bonding and electrostatic interactions with the imidazolium headgroup and the gelatin matrix.^[36] Nonetheless, [C₄MIM][Cl] did not promote any orientation in the liquid crystal. It also appears that this ionic liquid cannot sustain a stable spherical shape for the droplets and more importantly the hybrid formulation crystallized within hours from spreading (Figure 3A).

FIGURE 3. Droplet morphology of 9CB-based hybrid gel formulations as viewed with the POM under crossed polarizers and in bright field after gel preparation and subsequent crystallization when using (A) [C4MIM][Cl], (B) [C8MIM][Cl], (C) [C12MIM][Cl] ionic liquids. The white line corresponds to 50 µm

[C₈MIM][Cl]/9CB hybrid gels (Figure 3B), when viewed in the POM with crossed polarizers, present both small radial droplets (roughly 5–7 µm) and droplets featuring typical smectic defects. More interestingly though, in bright field microscopy ionic liquid interfaces can be observed, which are filled with 9CB. Similar droplets^[31] were also detected previously for [C₄MIM][DCA]/8CB droplets embedded in gelatin matrix. We believe that the orientation of 9CB is along the observation axis, that is perpendicular to the [C₈MIM][Cl] interface at the top of the droplet surface and also perpendicular to the glass surface, hence those droplets cannot be visualized with crossed polarizers. From now on we will refer to this type of droplets as dark droplets. Thermal investigations during cooling from the isotropic phase and upon POM observation with crossed polarizers were performed with a temperature rate of 3°C min⁻¹ (see Table 2 in ESI for transition temperatures). The isotropic to nematic transition occurred at 49.8°C (an example is seen in Figure 4A at 49.3°C). We observed that in the nematic phase the dark droplets feature a radial profile. The nematic to smectic A transition, occurring at 47.5°C, manifested via the appearance of a striped texture which originated from the periphery of the droplet (as it was previously observed for [C₄MIM][DCA]/8CB droplets). However, the striped pattern is not stable^[31] and upon further cooling it quickly shrinks into a pseudo-isotropic texture, as seen for example in Figure 4A at 47.3°C. As a final note, the hybrid formulation crystallized within a day from production.

FIGURE 4. Thermal investigations using the POM, of 9CB droplet morphology in hybrid gel formulations prepared with (A) [C8MIM][Cl]. Investigation upon cooling from the isotropic state with crossed polarizers, (B) [C12MIM][Cl].Observation of the smectic A phase at room temperature and of the nematic phase at 49.9°C. Photos were taken with crossed polarizers and in bright field, (C) [C12MIM][Cl]. Monitoring droplet textural transformations upon heating from the smectic A phase to the nematic phase. The white line corresponds to 50 µm

[C₁₂MIM][Cl]/9CB droplets at room temperature feature a bright peripheral ring with short extinction bands matching the direction of the crossed polarizers and a central pseudo-isotropic dark zone, which remains dark upon rotation (see Figure 3C). Within this gel formulation 9CB exhibits the smectic A phase at room temperature. In bright field images the droplets exhibit a circular defect. This optical appearance could be interpreted as an axial director profile with a disclination loop probably located between the equator and the droplet pole^[45,46] (i.e., the pole is perpendicular to the field of view), indicative of a tilted alignment at the interface. In the nematic phase (see for example Figure 4B at 49.9°C and Table 2 in ESI for transition temperatures) the droplets present a radial organization with central point defect. In fact, thermal investigations upon heating from the smectic A phase revealed that during the transition to the nematic phase the disclination loop seems to shrink until it transforms into the hedgehog core defect of the radial organization (see Figure 4C). Finally, the gel formulation was stable at ambient conditions and visible crystallization started after a week from production. An interesting observation is that using methylimidazolium chloride-based ionic liquids clearly has an effect on suppressing the crystallization of 9CB, the most prominent example being [C₁₂MIM][Cl]. This is possibly due to the fact that ionic liquids from this family can form strong interfaces which do not allow droplet coalescence,^[36,43] unlike [C₄MIM][DCA]. This is evidenced in the bright field images in Figures 3C and B.

Since we were able to produce stable 9CB gel formulations at room temperature we proceeded to test their responsiveness in the presence of gas analytes. According to our previous studies,^[31,34–36] the diffusion of analyte vapors within the droplets can decrease the liquid crystal order parameter and potentially trigger a phase transition, similar to the effect of an impurity presented in the system which shifts the liquid crystal isotropization transition towards lower values. However, the clearing temperature of the liquid crystal is sensitively associated with the amount of VOC needed to prompt a response.^[31,38] The higher the clearing temperature, the more analyte amount is required to achieve a response. Here, we considered both [C₈MIM][Cl]/9CB and [C₁₂MIM][Cl]/9CB hybrid formulations and we tested them to the vapors of 12 gas analytes (see Materials and Methods for details). During our VOC exposure experiments we tested analyte volumes of 10 mL and unfortunately no response was recorded from either of the two hybrid formulations. This signifies that the high clearing temperature of 9CB (i.e., 51.6°C) requires larger volumes of vapor analyte to trigger a liquid crystal response. We need to clarify that in this study we are not investigating the threshold VOC concentration for 9CB response. Determining the limits of detection is an important procedure required when a sensor format is coupled with a well-defined sensing application. Here, we are focusing on a proof-of-concept study in order to investigate the possibility of developing a stable and VOC responsive 9CB-based gel material. Hence, we are working with a well-established e-nose setup and are using pre-determined and evaluated protocols, whose merit has already been assessed.^[31,34–36] Therefore, a fixed VOC volume of 10 mL is used to determine whether the chosen 9CB-based hybrid formulations are functional sensors under these testing conditions.

9CB mixtures in the hybrid formulations and sensing capabilities

Despite our efforts to tackle the crystallization of 9CB at room temperature, the high clearing temperature was a critical issue to overcome. In light of this information, we opted to lower the 9CB transition temperatures via mixing it with another mesogen, whilst ensuring that 9CB is in excess. 8CB was chosen as a dopant, in order to maintain the smectic A phase at room temperature. Mixture 1 (20% v/v 8CB–80% v/v 9CB) was prepared according to the details provided in Materials and Methods and according to POM phase identification studies it exhibits the following transition temperatures at heating SmA 44°C N 47.4°C Iso and at cooling Iso 46.6°C N 42.3°C SmA. Mixture 1, which does not crystallize at room temperature, was used to prepare a hybrid formulation using [C₄MIM][DCA] as ionic liquid.

The morphology presented by the hybrid gel composition was very similar to the case of the [C₈MIM][Cl]/9CB gel. When using the POM with crossed polarizers tiny radial droplets (roughly 5 µm) and droplets presenting smectic defects were viewed (see Figure 5A). In bright field however dark droplets were observed, similar to the [C₈MIM][Cl]/9CB gel case. When conducting thermal studies upon cooling from the isotropic phase (rate 3°C min⁻¹) the transition to the nematic phase occurred at 45.1°C, with the droplets featuring a radial director profile (for example Figure 5B at 40.9°C). Upon further cooling, the transition to the smectic A phase, observed at 40.7°C, was marked by the appearance of a striped pattern which contracts rather quickly as the cooling continues and transforms to a pseudo-isotropic texture. Similarly, to the pure Mixture 1, the liquid crystal in the gel formulation did not crystallize at room temperature, instead it remained in the smectic A phase.

FIGURE 5. [C4MIM][DCA]/Mixture 1 gel morphology and thermal behavior when using the POM. A, Droplet morphology with crossed polarizers and in bright field, (B) transitional behavior of a dark droplet observed upon cooling from the isotropic phase. The white line corresponds to 50 µm

It is interesting to note that the ionic liquid anion in the gel formulation has an impact on the droplet diameters. The [DCA]- and [Cl]-anions can potentially induce different physical limitations upon interaction with the corresponding imidazolium headgroup.^[36] Both nitrile and chloride anions exhibit a similar ionic radius (191 and 181 pm, respectively)^[47] and considering that [DCA]- contains two nitrile groups, it is possible that due to steric hindrance at the droplet interface the [DCA]- anion facilitates the formation of larger droplets when compared to those containing a tested member of the methylimidazolium chloride family ([C_nMIM][Cl]). Here, the average diameters of the [C₈MIM][Cl]/9CB and [C₁₂MIM][Cl]/9CB droplets are 23 µm and 19.6 µm respectively, whereas the [C₄MIM][DCA]/Mixture 1 droplets exhibit an average diameter of 52 µm.

When we exposed the [C₄MIM][DCA]/Mixture 1 hybrid gels to VOC vapors under the microscope we were able to observe optical changes in response, on par with our previous work.^[31,34,35] More specifically, the presence of analyte vapors decreases the liquid crystal order parameter and reduces its clearing temperature (impurity effect) potentially to the extent of triggering an analyte-induced phase transition. The effect is reversible upon expelling from the system the analyte vapors with ambient air. According to our previous POM investigations,^[31] these analyte-induced phase transitions exhibit optical features akin to thermally-induced transitions. During our VOC experiments under POM observation (see Materials and Methods section for the setup and experimental details) videos and images were recorded for subsequent analysis.

The case of acetone exposure (10 s exposure period/15 s recovery period) is depicted in Figure 6A where we monitored a dark droplet. Upon exposure, the absorbance of the acetone vapor inside the droplet triggers a decrease in the order parameter of Mixture 1. This is marked by the appearance of a bright ring located at the droplet periphery (see Figure 6A at 2.6 s), the entry point of the diffusant, which evolves into a brighter dynamic texture of focal conic defects (Figure 6A at 8 s). As the exposure continues, the VOC is able to prompt a smectic A to nematic transition evidenced by a color change and a smoothening of the smectic defects (Figure 6A at 9.3 s). In this experiment, a nematic to isotropic transition was not prompted during analyte exposure. When the recovery period with ambient air starts and the acetone vapors are expelled from the droplet, the reverse process is observed. First, the bright peripheral ring appears again (exit point of the diffusant, Figure 6A at 10.1 s). Then, the nematic droplet pattern progressively changes into a smectic pattern (Figure 6A at 11 s), which in turn almost disappears leaving a few remaining smectic defects (Figure 6A at 13.4 s).

FIGURE 6. A, Optical changes of a [C4MIM][DCA]/Mixture 1 hybrid gel upon exposure (10 s) to acetone vapors and subsequent recovery (15 s) as observed via POM with crossed polarizers at room temperature. The white line corresponds to 50 µm, (B) cycle signals during exposure to different VOCs obtained from a single sensor. Each curve represents the average and corresponding standard deviation of at least 15 replicate cycles. VOC exposure periods (5 s) are highlighted in grey, (C) correct VOC prediction rates obtained for the [C4MIM][DCA]/Mixture 1 hybrid gel and plotted against the previously reported results for the [C4MIM][DCA]/8CB hybrid gel for comparison purposes

Frame analysis on the captured videos during these POM experiments using the ImageJ software, enabled the determination of the brightness of the frames, which is a measure of the light intensity variation transmitted by the gels. The results were plotted against time, allowing for a preliminary assessment on how the gels could perform with the e-nose (see Figure S1 in the ESI for exposure to toluene, dichloromethane, and diethyl ether). In Figure S2 in the ESI signals obtained through ImageJ treatment are depicted for the same gel composition when exposed to chloroform and acetone vapors both after the day of production and several days later. One can observe that the signal shape remains almost the same. Namely, the brightness signal of consecutive exposure/recovery cycles to the same analyte presents a reproducible waveform pattern and the pattern is maintained after a number of days. We expect that similar results will be obtained with the e-nose, in agreement with previously published data for a hybrid gel composed of gelatin, [C₄MIM][DCA] and 5CB.^[34]

It is interesting to note that our previous POM studies upon VOC exposure^[31,35] have revealed that the polydispersity of the liquid crystal droplets has an effect on the development rate of an occurring analyte-induced transition. More specifically, analyte-induced pattern changes were always observed first for smaller droplets, followed by the larger ones. This behavior was also detected in this study for the [C₄MIM][DCA]/Mixture 1 hybrid gels as evidenced by the example depicted in Figure 6A. Acetone exposure triggered a rather slow progressing smectic A to nematic transition, but not a subsequent nematic to isotropic transition for the large observed droplet.

It is important to discuss the interactions between the tested volatiles and the Mixture 1-based gel composition. We have already established from our previous work^[31,34–36] that the chemical nature of the analyte is key for the gel response. Hydrophobic apolar analytes such as hexane, heptane, and toluene tend to interact directly with the liquid crystal component by lowering its clearing temperature (impurity effect). An example can be found in Video S1 in the Supporting Information for exposure to toluene. Protic and hydrogen bond forming volatile compounds (such as ethanol and acetic acid) interact preferentially with the gelatin and ionic liquid components. Those analytes may distort the ionic liquid interface and hence indirectly slightly disorganize the liquid crystal. For VOCs with intermediate polarity and hydrogen bond tendencies, it is believed their interaction is a combination of their degree of preference toward the different compartments of the hybrid gel composition (see Video S2 in the Supporting Information for dichloromethane exposure). Therefore, preferred VOC affinities towards specific gel compartments may prompt different magnitudes of response and uniquely affect the disorganization and reorganization process of the liquid crystal. It is likely that acetone, Figure 6A, interacts preferentially with both the liquid crystal compound by lowering its clearing temperature and also with the ionic liquid interface by disrupting it. As can be seen in Video S3 in the Supporting Information exposure to acetone vapors disturbs the interface of some droplet creating a liquid crystal leaking in the gelatin matrix.

After our POM investigations, we concluded that the [C₄MIM][DCA]/Mixture 1 hybrid gels can be evaluated as chemical sensors in our tailor-made e-nose setup (see Figure S3 in the ESI for a schematic depiction of the setup). Nine sensors from three different batches were prepared and tested (see Materials and Methods for details) with twelve different analytes (acetic acid, acetone, acetonitrile, chloroform, dichloromethane, diethyl ether, ethanol, ethyl acetate, heptane, hexane, methanol, and toluene). By recording the light intensity variations due to VOC sorption to the [C₄MIM][DCA]/Mixture 1 hybrid gels in the tailor-made e-nose setup, we were able to collect signals generated by the dynamic molecular disorganization and reorganization of the ionic liquid/liquid crystal droplets within the gelatin matrix, as observed through our POM studies. The signals are the collaborative result of the distinct dynamics and interactions of the gel components with each tested gas analytes.^[31,34,35] The gel formulations were recorded upon analyte exposure for 22 consecutive cycles (see Materials and Methods for details) and the sensors yielded relatively stable and repeatable signals with a maximum variability between 5% (for toluene) and 14% (for diethyl ether) for each individual sensor (Figure 6B). Due to the distinct chemical nature of the tested VOCs, some analytes generate more stable responses than others. This could be related to a gradual accumulation of permanent changes in the liquid crystal organization with time, due to potential adsorption of analytes molecules during the experiments. The sensors from different batches gave reproducible signal shapes. For example, in the case of chloroform exposure an interbatch shape variability in the order of 22% was observed (see Figure S4 in the ESI). Shape similarity between cycles for each analyte (or reproducibility) is important for VOC recognition, because our goal is to train a machine learning algorithm to predict the analyte nature from the shape of sensors signals (see details below).

Relative signals obtained from a single sensor for different VOCs are depicted in Figure 6B (see Materials and Methods for details). Raw signals collected from a single sensor are presented in Figure S5. The signal shape variations reflect the dynamic liquid crystal disorganization and corresponding brightness decrease (i.e., decrease of signal amplitude) and subsequent recovery. The [C₄MIM][DCA]/Mixture 1 hybrid gels respond rather quickly to the presence of VOCs and exhibit variability in their recovery profiles. The response times vary between 1.3 s in the case of chloroform and 2.5 s for toluene, reflecting the potential affinity of the corresponding analyte towards distinct gel compartments. With regards to recovery times we believe, based on our previous investigations,^[31] they are probably affected by the system's geometry and the subsequent restrictions imposed on the gel components. As an example, for toluene exposure the gel recovers within roughly 3.9 s, whereas for the dichloromethane case recovery was recorded at 9.9 s.

The pool of data collected from the nine sensors (three sensors per batch) was used for the training of a machine learning algorithm, more specifically an automatic classifier based on support vector machines (SVM). The classifier uses features related to the signals shape^[48] as input in order to recognize VOCs. The rate of correct predictions (%) for each tested VOC is presented in Figure 6C and plotted against the previously published results for the [C₄MIM][DCA]/8CB formulation for comparison purposes. The overall correct prediction rate for the [C₄MIM][DCA]/Mixture 1 hybrid gels was 69% and the classifier performed greatly, with an accuracy rate above 65%, for acetic acid, acetone, chloroform, dichloromethane, and toluene. When compared to the [C₄MIM][DCA]/8CB formulation (81% overall correct prediction rate), the [C₄MIM][DCA]/Mixture 1 hybrid gel might seem to fall behind. This could be attributed to the large amount of 9CB present in Mixture 1 (80% v/v in 9CB). Arguably pure 9CB has a higher clearing temperature than pure 8CB, meaning that it requires larger amounts of analyte to trigger a VOC response. We might have achieved to lower the clearing temperature of 9CB, albeit its dominant presence in Mixture 1 hampers correct VOC recognition.

A potential improvement to the sensor sensitivity would be to lower even more the 9CB clearing temperature by using larger amounts of 8CB or even consider other mesogens with room temperature mesogenic behavior. That way the analyte-induced responses, which are correlated with the amount of VOC used, could be significantly more sensitive. For future investigations, another intriguing mesogen could be 10CB which melts at 44°C and exhibits only the smectic A phase. Clearly, we would have to lower its clearing temperature to achieve a VOC response, but it could be insightful to study a single-phase smectogenic compound. Selectivity could be introduced to the composition by using a different ionic liquid, or via the addition of a VOC targeting moiety or even by modifying the glass chemistry with VOC-responsive species. These strategies however can have a serious effect on the droplet morphology and liquid crystal organization and require careful planning and thorough investigation for future work. Here, the aim of this proof-of-concept study was to develop a functional and responsive room temperature 9CB-based chemical sensor and on this matter the [C₄MIM][DCA]/Mixture 1 hybrid gels are perfectly stable, they respond fast to the presence of gas analytes and yield measurable optical signals. Overall, the simplicity of the gel preparation process coupled with the room temperature performance render the [C₄MIM][DCA]/Mixture 1 hybrid gels a promising alternative for real-time gas sensing.

CONCLUSIONS

Liquid crystal-assisted gas sensing platforms are increasingly relevant for molecular recognition and analyte detection. They are associated with enhanced selectivity and low-cost instrumentation, while operating at ambient conditions. For this purpose, we have tested the sensing capabilities of the liquid crystal compound 9CB, a smectogen which is solid at room temperature, in a multicomponent hybrid gel formulation. Changing the ionic liquid component in the formulation, had a different effect in the crystallization of 9CB but also in the corresponding self-assembled ionic liquid/liquid crystal droplet organization. Furthermore, a 9CB mixture instead of the pure compound was also investigated. The resulting hybrid gels were tested as chemical gas sensors. As there is a sensitive correlation between the clearing temperature of a liquid compound and the amount of analyted required to trigger a response, it was revealed that only the 9CB mixture-based gel could report the presence of gas analytes. Even though the chemical sensors could benefit from further optimization for the enhancement of selectivity, their simple preparation process and room temperature responsiveness prove that 9CB-based droplets can be a useful tool in gas sensing applications.

MATERIALS AND METHODS Materials and reagents

The imidazolium-based ionic liquids 1-butyl-3-methylimidazolium dicyanamide ([C₄MIM][DCA], > 98%), 1-butyl-3-methylimidazolium chloride ([C₄MIM][Cl], purity > 98%), 1-octyl-3-methylimidazolium chloride ([C₈MIM][Cl], purity > 98%), 1-dodecyl-3-methylimidazolium chloride ([C₁₂MIM][Cl], purity > 98%) were acquired from Iolitec (Heilbronn, Germany). The liquid crystals 4-cyano-4′-nonylbiphenyl (9CB, purity > 98%) and 4-cyano-4′-n-octylbiphenyl (8CB, purity > 98%) were acquired from TCI Europe. Gelatin from bovine skin (gel strength ≈225 g; Bloom, type B) were supplied by Sigma–Aldrich. The solvents dichloromethane and hexane (purity ≥99.9%) were acquired from VWR, and ethanol (purity ≥99.8%) was purchased from Sigma–Aldrich. Acetonitrile (purity ≥99.9%), chloroform, diethyl ether (HPLC grade), ethyl acetate, heptane, methanol (HPLC grade), and toluene were supplied by Fisher Scientific. Acetone (purity ≥99.5%) was purchased from Honeywell. Milli-Q water was used. Solvents were of analytical grade and used as received.

Liquid crystal mixture preparation

The liquid crystal Mixture 1 (20% v/v 8CB–80% v/v 9CB) was prepared by co-dissolving pre-measured amounts of the individual components in chloroform and allowing the solvent to slowly evaporate at room temperature.

Hybrid gel and sensor preparation

The polydisperse gels were produced through gelation of viscous solutions containing (in wt%) MilliQ water (10%–30%), gelatin (10%–25%), liquid crystal (2%–10%) and ionic liquid (30%–70%), and following the protocol reported elsewhere.^{[31,34,35,49]} The final formulation was deposited onto an untreated glass slide and spread into a film, using an automatic film applicator (TQC Sheen) equipped with a heated bed and a quadruplex with a predefined thickness of 30 µm. The films were left at room temperature for 24 h before being used either for characterization or an e-nose experiment. The effect of film thickness on the gel production and gas sensing performance has been evaluated by Esteves et. al.^[35] There, it was observed that the average diameter of the droplets tends to be larger for thicker films, thus yielding ‘'brighter'’ sensors when tested in the e-nose. However, the optimal gel thickness for gel production reproducibility and performance was found to be a 30 µm thickness.

Hybrid gel characterization

All the tested gels were characterized via polarizing optical microscopy (POM) using a Zeiss Axio Observer.Z1 microscope equipped with an Axiocam 503 color camera. Micrographs were taken and processed by the ZEN 203 software. The thermal behavior of the gels was investigated using a Zeiss Axioskop 40 microscope, equipped with a Linkam hotstage, an ECP water circulating pump for cooling below room temperature, and an Axiocam 503 color camera. Photographs taken were processed by the ZEN 203 software.

Analyte effect on hybrid gels

Investigations of the analyte effect on the gels were conducted using the POM. An in-house-designed glass chamber fixed between the polarizers of the Axio Observer.Z1 microscope was used to place the sensors. The gels were exposed to vapors of 12 different solvents (10 mL of the solvent preheated at 37°C in a water bath) for five consecutive cycles. Each cycle consists of a 5 s exposure (unless stated otherwise) to gas using an air pump, followed by a 15 s recovery period with ambient air via a second air pump. During each VOC experiment, images and videos were recorded using the ZEN software. The software ImageJ was used to conduct frame analysis on the recorded videos. The corresponding optical signal responses were calculated via the variation of the brightness of the video frames along time, which represents the light intensity transmitted by the gels along time. The results were plotted against time.

The gels were also used as chemical sensors in an in-house-assembled e-nose device.^[31,35,48] The detection chamber of the e-nose, where the sensors are placed, is isolated from light and ambient air and holds 12 independent sensor slots placed between crossed polarizers. The chamber is coupled with a light-emitting diode and a photodiode for light transmittance monitoring. The optically active area of a sensor is defined as the birefringent area that contributes to the signal generated by the surface of the gel (i.e., the liquid crystal droplets). When analyte vapors interact with the hybrid gel formulations, they decrease the liquid crystal order parameter, hence the droplets gradually become less birefringent and consequently the light intensity that reaches the photodiode changes. The variation in the light intensity during exposure/recovery periods, as read by the photodiode, is digitalized with an Arduino Due and stored for further analysis.

The gels are exposed sequentially to vapors of 12 solvents (10 mL of the solvent preheated at 37°C) for 22 consecutive cycles (a cycle is defined above). Analyte concentrations have been measured indirectly via solvent evaporation^[35] (see Table 3 in the ESI). The VOCs used belong to distinct groups, such as alcohol, ketones, aliphatic, aromatic, and halogenated compounds (i.e., heptane, hexane, toluene, chloroform, dichloromethane, diethyl ether, ethyl acetate, acetone, acetonitrile, ethanol, methanol, acetic acid). Three batches of each tested formulation were produced and three replicates per batch (nine replicates in total) were used to generate a sufficiently large pool of signal data, including potential signal variability, for the efficient training of the automatic classifier (see details below). The goal here is that the classifier learns from these data to recognize the signal patterns associated with each VOC. The collected signals were processed using data analysis tools based on Python libraries (SciPy, scikit-learn, and novanistrumentation). A smoothing filter (20 points sliding window) followed by a median filter were applied first. Then the signals were divided into cycles. The relative signal for each cycle (Sr) was calculated according to the equation: [Image Omitted. See PDF]where S is the filtered cycle signal and baseline is the average of the filtered cycle signal taken from 10 points immediately before VOC exposure.

The normalized signal for each cycle (Sn) was calculated using the percentile values instead of the absolute maximum and minimum to avoid interference from signal fluctuations near the peaks of the cycle, according to the equation: [Image Omitted. See PDF]where S is the filtered cycle signal, S_P5% is the signal percentile 5% value, that is, the value which 5% of the cycle signal values are less than or equal to, and S_P95% is signal percentile 95% value.

To access the stability and reproducibility of signals, the maximum variability was used. The maximum variability of a set of cycles was determined as follows: first, the mean cycle signal and standard deviation of the set of cycles were calculated; then, the maximum variability was estimated as the ratio between the standard deviation and the mean cycle signal values at the point where the standard deviation is maximum (see Figure S5 in the ESI).

The stability of the sensors signals was assessed via calculation of the maximum variability of the relative signal from10 consecutive cycles of a single sensor. The reproducibility of the sensors signal was determined via the calculation of the maximum variability of the normalized signal of 3 cycles form sensors of independent batches (1 cycle per sensor).

For the evaluation of the sensors ability to identify VOCs based on the shape of the signals, the cycles were also normalized. After that, the outliers were removed. Twelve features related to the morphology of the signal curves were extracted per cycle^[48] and used as input to train an automatic classifier based on SVM and make VOC identification predictions. The classifier results were presented in confusion matrices, which depict both correct and incorrect prediction rates and accuracy plots, which show only the correct prediction rates. The SVM classification model used in this work was implemented and optimized by our research group, as described in a previous publication,^[48] using a data pool of signals generated by 5CB hybrid gels upon exposure to the same set of 12 VOCs used in this work. More details can also be found in Ramou et al.^[31]

ACKNOWLEDGMENTS

This project has received funding from the European Research Council (ERC) under the EU Horizon 2020 research and innovation programme (SCENT-ERC-2014-STG-639123, 2015−2022) and by national funds from FCT-Fundação para a Ciência e a Tecnologia, I.P., in the scope of the project PTDC/BII-BIO/28878/2017, PTDC/CTM-CTM/3389/2021, UIDP/04378/2020 and UIDB/ 04378/2020 of the Research Unit on Applied Molecular Biosciences-UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy-i4HB.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.