Fabrication and Optimization of Fiber-Based Lithium Sensor: A Step towards Wearable Sensors for Lithium Drug Monitoring in Interstitial FluidMona N. Sweilam†, John R. Varcoe, Carol Crean*Department of Chemistry, University of Surrey, Guildford, GU2 7XH, United KingdomKeywords: electrochemical analysis; wearable sensor; ion-selective electrode; fiber; conductive cot-ton; lithium sensor; non-invasive monitoring.

ABSTRACT: A miniaturized, flexible fiber-based lithium sensor was fabricated from low-cost cotton using a simple, repeatable dip-coating technique. This lithium sensor is highly suited for ready-to-use wearable applications and can be used directly without the preconditioning steps normally required with tradi-tional ion-selective electrodes. The sensor has a stable, rapid and accurate response over a wide Li+ con-centration range that spans over the clinically effective and the toxic concentration limits for lithium in human serum. The sensor is selective to Li+ in human plasma even in the presence of a high concentra-tion of Na+ ions. This novel sensor concept represents a significant advance in wearable sensor technol-ogy which will target lithium drug monitoring from under the skin.

Lithium is one of the antipsychotic drugs used to treat mood disorders such as bipolar affective disorder and depression.1 Lithium must be moni-tored during patient administration due to its nar-row effective therapeutic range. The recom-mended therapeutic range for serum lithium lev-els is 0.4 – 1.0 mmol/L.1 Serum levels below this range are ineffective, while higher levels lead to acute toxicity, which may elicit severe effects like coma and convulsions (if levels rise above 2.0 mmol/L).1 Traditionally, blood samples must be frequently withdrawn from a patient to confirm that lithium serum levels are maintained within this effective and safe range. Lithium levels ini-tially need to be checked 5 – 7 days after the first dose followed by weekly checks until levels stabi-lize between two doses. After dose stabilization, lithium levels are then typically monitored every three months.

Many different analytical methods have been developed for the determination of Li+ concentra-tions including spectrophotometry,2-3 flame atomic emission spectroscopy (FAES),4 flame atomic absorption spectroscopy (FAAS),5-7 induc-tively coupled plasma atomic emission spectrom-etry,8 inductively coupled plasma mass spectrom-etry,9-10 spectrofluorometry,11-12 electrophoresis,6

and the use of optical chemical sensors.13 Electro-chemical methods have also been developed that include pulse amperometry,14 voltammetry 15-16

and potentiometry.17-18 The most commonly used laboratory methods are FAES, FAAS, and poten-tiometry using ion-selective electrodes (ISE).19-20

Recently, point-of-care devices based on mi-crochip capillary electrophoresis,21-24 paper-based potentiometry,25 and a finger stick device 26 have been developed specifically to provide decentral-ized lithium monitoring. All the above-mentioned methods still require invasive blood sampling. Blood sampling can be painful and may lead to in-fection, hematoma, bruising and in rare cases wounds may bleed excessively; this leads to a de-gree of patient noncompliance, especially when frequent blood sampling is required. Specifically, in the case of finger stick tests, the healthcare worker and local environment can be exposed to blood-borne diseases during sampling. A further disadvantage of venous blood sampling is the possibility of interferences resulting from the components present in collection containers, such as surfactants, anti-coagulants, and the separa-tion gel.27 A common cause of false lithium deter-mination stems from the coatings, containing lithium heparin anticoagulant, used for the inter-nal wall of collection containers, which varies from one manufacturer to another.28-29

As a result of the above factors and the result-ing costs, ongoing research aims to develop low-cost screening and detection devices based on decentralized, non-invasive procedures. Sweat, saliva, tears, and interstitial fluid (ISF) are all ex-amples of biological fluids that can be accessed using non-invasive techniques.30 An exciting re-cent advance is the development of wearable chemical sensors, which enable the monitoring and detection of different clinical conditions. Re-

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cent research has involved the fabrication of flexi-ble wearable sensors to detect both ionic and molecular species in a range of biological fluids including: Na+,31-32 K+,33-34 NH4+,35 and Cl– 36 in sweat; glucose,37-42 dopamine, norepinephrine, 41 and lactate in tears 43 and in saliva.44 Bandodkar et al. developed a proof-of-concept tattoo-based non-invasive sensor for glucose monitoring in ISF.45

Previous research into wearable sensors has in-volved the determination of endogenous sub-stances in biological fluids, while, to the best of our knowledge, no articles have described a wearable sensor for the non-invasive determina-tion of exogenous substances, such as drugs, in biological fluids. It is well known that not all drugs are distributed between the blood stream and other biological fluids, due to plasma protein binding of numerous drugs. The relationship be-tween the drug concentration in plasma and in other (non-invasively accessed) biological fluids must be fully understood before the determina-tion of drug concentrations in such biological flu-ids is attempted, to ensure measurement reliabil-ity. The study by Leboulanger et al. 46-47 suggested that the lithium concentration in ISF was propor-tional to concentration in serum and concluded that lithium could be effectively monitored in ISF. Their method involved laboratory analysis of ISF that was collected from the skin surface after re-verse iontophoresis (application of a low-level electric current through a pair of skin electrodes), which resulted in the transportation of both charged and neutral molecules through the skin.

The aim of this study was to fabricate a minia-turized, flexible, and wearable sensor for non-in-vasive point-of-care monitoring of lithium levels in patients taking lithium-based drugs. A fiber-based lithium sensor was developed with the intention of future incorporation into a reverse iontophore-sis dermal bandage/patch, to enable the simulta-neous extraction and analysis of lithium levels from a single sampling point. This article details the fabrication and optimization of a fiber-based lithium sensor as an initial, critical step towards the development of a wearable sensor for lithium ion monitoring in ISF. The principal challenge that was overcome was to fabricate a low-cost, accu-rate, and reproducible fiber-based lithium ISE that did not necessitate any conditioning steps (tradi-tionally required for ISEs); such conditioning steps are not feasible for wearable applications.

EXPERIMENTAL SECTIONMaterials and Chemicals. Single-walled car-

bon nanotubes (SWCNTs) of >70% carbon purity, were purchased from Nanocyl (Belgium) and used without further purification. Commercially avail-able carbon fibers (0.08 mm diameter, 6.4 mm length, 93% purity) were purchased from Alfa Ae-sar (Heysham UK). Potassium tetrakis(4-chlorophenyl)borate (KTClPB, >98% purity), lithium tetrakis(pentafluorophenyl)borate ethyl

etherate (LiTPFPB), 6,6-Dibenzyl-14-crown-4 (lithium ionophore VI), 2-nitrophenyl octyl ether (NPOE, >99% purity), trioctylphosphine oxide (TOPO), high molecular weight poly(vinyl chlo-ride) (PVC,), THF, sodium dodecylbenzenesul-fonate (SDBS) and analytical grage of the follow-ing salts; LiCl(s), KCl(s), NaCl(s), CaCl2(s), MgCl2(s), NH4Cl(s), and were all purchased from Sigma-Aldrich (UK) and used without any further purification. Ultrapure water (18.2 MΩ cm) was used through this study.

Conductive Cotton Fiber (CCF) Prepara-tion. The SWCNT ink was prepared using SDBS surfactant as described by Cui et al.48 SWCNTs were dispersed in 10 mg/mL aqueous solution of SDBS, to obtain 3 mgSWCNT/mL, by sonication at room temperature for 30 min using a probe soni-cator at 30% power (500 W AutoTune Series by Sonics & Materials Inc., USA). To avoid overheat-ing, the vial was kept in an ice water bath during sonication. The SWCNT ink was stable for 3 months when stored at 4°C. Commercial white cotton fibers, cut into lengths of ca. 10 cm, were dip-coated in the SWCNT ink following the proce-dure described by Guinovart et al.33 After each dip in SWCNT ink the cotton fiber was washed thor-oughly with de-ionized water (until the water ran clear with no obvious signs of detergent) to wash SDBS away before applying the lithium mem-brane cocktail. After 3 – 5 dip cycles, the now electronically conductive cotton fibers (CCF) were found to exhibit the targeted R ≤ 500 Ω (see be-low for details on how this was measured).Resistance measurements, The CCF resis-

tances were measured using the four-probe tech-nique. Fibers were mounted using silver paint across four electrical pins of equal spacing (2 mm). A constant current (1 mA) was then applied across the two outer pins using an eDAQ e-recorder 410 attached to an eDAQ EA161 poten-tiostat, and the resultant voltage measured across the inner two pins using a Keithley 2001 (7½ digit) multimeter.Construction of lithium sensors. Different

lithium ion-selective membrane cocktails were prepared using lithium ionophore VI, KTClPB, LiTPFPB, PVC, NPOE and TOPO in the proportions detailed in Table 1. The fabricated CCFs were shielded using micropipettes leaving both ends exposed: the upper 2.0 cm exposed end was used to connect the electrode to the electrochemical instruments while the lower 5 mm exposed end was coated with the ion-selective membrane.33

Two CCF sets (n = 3 replicates each) were dipped in membrane cocktail 1 or 2, respectively, for 5 dip cycles (designated CCF1-5 and CCF2-5, re-spectively). Another two CCFs sets (n = 3 repli-cates each) were dipped in membrane cocktail 1 or 2, respectively, for 9 dip cycles (CCF1-9 and CCF2-9). Each dipping cycle was for 2 s and the sensors were passively dried in air for 10 min be-tween dips.

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Table 1: The membrane cocktail formula-tions used to fabricate the CCF-based lithium sensors

wt.% Membrane 1 Membrane 2PVC 28.0 28.0NPOE 68.5 68.5Li ionophore

VI1.5 1.5

Lipophilic salt KTCPE: 0.5 LiPFBP: 0.5TOPO 1.5 1.5

Conditioning and storage. After completing the dip-coating procedure, the sensors were left to dry in air overnight to ensure complete solvent evaporation. The CCF1-5 and CCF2-5 sensors were conditioned overnight in aqueous LiCl (0.05 M) before first use with only a further 20 min con-ditioning step before each successive use (condi-tioning involved immersion in LiCl (0.05 M)). The CCF1-9 and CCF2-9 sensors were used to mea-sure different Li+ concentrations in aqueous LiCl solutions directly without any conditioning steps. All sensors were stored dried (stored in ambient air in a suitable container) between day-to-day measurements. Commercially available carbon fibers were also used to fabricate lithium sensors (without addition of SWCNTs) by initially cleaning with dichloromethane for 10 s and then coating with membrane cocktail 1 (5 dips, 2 s each) to compare with the fabricated CCF-based sensors. At the same time, glassy carbon electrodes (GCEs) were modified by drop casting 4 µl SWCNT ink followed by 30 µl membrane cocktail onto their surfaces for further comparison with the CCF-based sensors.

Electrochemical Measurements. The electrode potentials were measured using an eDAQ potentiostat/galvanostat (Model EA161) in high Z mode and eDAQ e-recorder 410. The potential of every sensor fiber was recorded vs. a double junction Ag/AgCl/KCl (3.0 M) reference electrode (part number 6.0726.100, Metrohm, UK, containing aqueous KCl (0.1 M) electrode bridge electrolyte). Solutions were stirred during the room temperature measurements. The total ionic strength was calculated for each calibration point. Activity coefficients were calculated using the Debye–Hückel formalism. No ionic strength adjusting solutions or supporting electrolytes were used in any of the measurements. The measured potentials were corrected using Henderson equation for liquid junction potential.

Instrumental Characterization. Raman spectra of the bare cotton fiber and the CCFs were recorded using a Renishaw Systems inVia Raman Microscope. A 532 nm 50 mW (green) laser was used at 0.5% power with 10 s exposure times along with a 50× objective.Scanning electron microscopy (SEM) images

were obtained using a JEOL USA JSM- 7100F Ana-lytical Field Emission SEM. CCF and CCF-based

lithium sensors were mounted on an alumina-coated sample stub and scanned directly without any pre-treatment. Bare cotton fibers were Au-coated prior to study using SEM: two applications of 2 nm Au coating were applied via an Ar source Au splutter.

RESULTS AND DISCUSSION Conversion of cotton fibers into CCF. Cotton

fibers were converted into conductive fibers by dipping in CNT ink until the required resistance was achieved. Figure S1 (supporting information) shows that 3 – 5 coats of CNTs yielded a resis-tance < 500 Ω, a value that is adequate for the intended application. The bare cotton fibers and the CCF were characterized using Raman spec-troscopy. The Raman spectra in Figure S2 (sup-porting information) confirms the adsorption of SWCNTs onto the cotton fiber due to the presence of well-defined G-band (1595 cm-1), G’-band (2673 cm-1), and D-band (348 cm-1) peaks of SWC-NTs that are not observed in the Raman spectrum of the bare cotton fiber.Optimizing the coating of CCF with mem-

brane cocktail 1. To convert the CCF into ion-se-lective sensors, they were initially dip-coated us-ing ion-sensing membrane cocktail 1 (see Table 1). The electrode response (change in CCF-sensor potential per decade of Li+ activity) of the fabri-cated CCF sensors was optimized as described below. The effect of the length of CCF dipped in the membrane cocktail, the duration of dipping, and the number of dipping cycles were all studied as follows:a) Different CCF dipping lengths (5 mm, 7

mm, and 8 mm) were used to evaluate the effect of CCF-sensor length. All lengths gave the same slope (mV dec-1) value but the smallest length yielded smaller standard deviations over n = 3 replicate fibers, so 5 mm length was chosen for all further studies.b) It was found that dipping duration is a key

variable. A dip-coating time of 2 s gave the high-est slope (after overnight conditioning) with longer dipping durations giving a sub-Nernstian (< 59 mV dec-1) response (see Figure 1).c) For the different numbers of dipping cy-

cles, it was found that 5 cycles was optimum to give CCF-sensors yielding responses closest to an ideal Nernstian response (after overnight condi-tioning).The optimized CCF1-5 sensor (5 dip-coat cycles,

2 s per cycle, membrane-1, 5 mm sensor length) yielded a Nernstian response of 62.6± 1.0 mV (n = 3 replicate sensors) after overnight condition-ing in aqueous LiCl (0.05 M).

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Figure 1. Potential change per decade of Li+ activity of CCF1-5 sensors (made by dipping CCFs in mem-brane cocktail 1 for 5 dipping cycles) as a function of dip cycle duration (measurements on n = 3 replicate sensors). The sensors were conditioned overnight in aqueous LiCl (0.05 M) before being tested. The po-tentials of the CCF1-5 sensors were measured vs. double junction Ag/AgCl reference electrode.

Comparing the response of a CCF-based sensor to GCE-based and carbon-fiber-based sensors. The performance of this CCF-based lithium sensor was compared to lithium sensors fabricated on glassy carbon electrodes (GCEs) and commercially available carbon fibers. GCEs were modified by drop-casting SWCNT onto the electrode, followed by coating with membrane 1, while carbon fibers were coated directly with membrane 1. Both GCEs and carbon fibers were conditioned overnight in LiCl as described earlier. The response of the CCF-based sensor, the car-bon fiber-based sensor and the GCE-based sensor were compared to each other. Figure 2 shows that all three types of sensor (using different solid-contact electrode materials) gave ideal Nernstian responses after overnight conditioning. All three sensor types had the same linear work-ing range (1.0 × 10-4 – 6.3 × 10-2 M) that spanned the ineffective, clinically relevant (4.0 × 10-4 – 1.0 × 10-3 M), and toxic concentrations of lithium in serum. CCF1-5 gave comparable standard devia-tions to that of the GCE-based sensors, while the carbon-fiber-based sensors yielded higher stan-dard deviations for all the concentrations tested. For this reason, the use of carbon fibers for fabri-cation of flexible, fiber-based sensors was not continued.

Figure 2. A comparison of the potentiometric re-sponses of CCF1-5 and the GCE-based and carbon-fiber-based lithium sensors (measurements on n = 3 replicates of each sensor type).

Inter-day variation of the response of the CCF-based sensors. Despite obtaining a stable inter-day response in terms of slope (mV dec-1), the potentials of CCF1-5 increased from day to day (as measured from the intercepts of the po-tential vs. log (Li+ activity) plots (Figure 3).

Sensors were conditioned overnight before first use after which they were stored dry (while not in use) and re-conditioned for 20 min before being re-used on later days. A 100 mV increase in the intercept value was observed on the second day of use (6 d after the sensor fabrication and 5 d af-ter the initial overnight conditioning process). The highest potential difference occurred on the sec-ond day of use, with lower variation observed on subsequent days. In contrast to these results, the GCEs (coated with SWCNTs and lithium mem-brane cocktail-1) did not exhibit this shift in inter-cept values and showed good inter-day stability. The relative standard deviation (RSD) of the po-tential intercept values were low (0.4%) for GCEs but much higher (23.8%) for CCF1-5 replicate sensors (n = 3). In terms of the variation in the slopes of potential vs. log (Li+ activity), the GCE sensor data ranged between 59 – 63 mV dec-1

over 8 days of storage and testing (RSD =2.8%), whereas CCF1-5 ranged between 61 – 64 mV dec-1 (RSD = 2.3%). These results showed that the variation in slopes were comparable for CCF1-5 and the GCE-sensors but larger differ-ences in potential (intercepts) were observed.

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Figure 3: The variation in the intercepts of the poten-tial vs. log (Li+ activity) plots for CCF5-1 and GCE-based sensors as a function of days since membrane fabrication. Sensors were conditioned overnight be-fore first use (day 1) after which they were stored dry and re-conditioned for 20 min before being re-tested on later days.

An essential investigation into the effect of con-ditioning time was conducted to evaluate the pos-sibility of minimizing conditioning time without any detrimental effect on the potential response (mV dec-1) of the CCF sensors. Different condition-ing times were trialed beginning with a protocol involving no conditioning at all through to an overnight conditioning protocol. An increase in conditioning time lowered the potential intercept values (of the potential vs. log (Li+ activity) plots), whilst the slopes were enhanced. It was also ob-served that there was only a 5 mV difference in the slope between sensors that had been sub-jected to 20 min and overnight conditioning pro-tocols (see Figure S3 in the supporting informa-tion).

The shift in potential between the first use and second use for different initial conditioning times was observed to decrease with decreasing conditioning time. Such potential shifts had been previously assigned to the formation of an aque-ous layer between the deposited membrane and the solid-contact electrode. In this work, this aqueous layer may have originated from using long conditioning times. The data in Figure S4 suggests that conditioning the sensors (sub-merged in the solution) for longer periods of time is detrimental to performance. The potential shift observed for 2 sets of triplicate sensors, over 18 d, can be seen in Figure S5 (supporting informa-

tion): set 1 is where sensors were conditioned for 20 min every day; set 2 is where sensors were ini-tially conditioned for 1 h before first use and then conditioned for 20 min on subsequent days. The potentials generally increased from day to day. A very high % RSD was obtained for the intercepts of potential vs. log (Li+ activity) data over 18 d (Table 2), while the slopes of potential vs. log (Li+

activity) data ranged between 57 – 63 mV and 59 - 63 for sets 1 and 2, respectively.

Table 2: % RSD of standard potential (inter-cept) for CCF1-5 lithium sensors over 18 days

%RSD of inter-cept*

Sensors condi-tioned 1st time for

20 min

Sensors condi-tioned 1st time

for 1 hInter-day variation

10.88% 15.04%

*Average of triplicate sensors (n = 3)

Water layer test. A water test was performed to evaluate the hypothesis of an aqueous layer forming between the solid electrode (CCF or GCE) and the sensing membrane layer. The CCF1-5 sensor to be tested was conditioned in aqueous LiCl (0.1 M) for 24 h and then immersed in aque-ous solutions (0.1 M), switching every 10 min be-tween LiCl and NaCl (Na+ being a highly interfer-ing ion). On changing from the sample ion to the interfering ion, a positive potential drift is ex-pected if an aqueous layer is present;49 similarly, a negative potential drift would be obtained when changing from the interfering ion to the sample ion. The thinner the membrane, the faster the oc-currence of the potential drift. It is clear that the CCF1-5sensors suffer from water layer formation (during conditioning), while the effect on the GCE-based sensors is diminished (Figure 4). A condi-tioning-free protocol was therefore targeted to specifically eliminate the formation of the aque-ous layer during the conditioning step of CCF1-5. The absence of a conditioning step is also an ideal characteristic of a wearable sensor.

Switching to a non-conditioning protocol. Rich et al.50 have recently studied the exclusion of a conditioning step by adding the primary ion in-side the membrane cocktail during preparation. Following on from this concept, we used a mem-brane cocktail containing LiPFBP as the lipophilic additive (instead of KTCIPB) in order to introduce Li+ ions into the sensing membrane. This mem-brane is referred to as membrane 2.

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Figure 4: The potential of the lithium sensors, CCF1-5 (left) and GCE (right), when alternatively immersed in LiCl (0.1 M) and NaCl (0.1 M) with switching of solution every 10 min. The sensors were conditioned for 24 h in LiCl (0.1 M) before these tests.

The results obtained suggest a similar behavior to that of membrane 1 (Table 3).

Table 3: The values of the slope of potential vs. log (Li+ activity) of lithium sensors fab-ricated from CCF1-5 and CCF2-5, before and after conditioning. Data from repeats on n = 3 replicate sensors.

Membrane 1 Membrane 2Condition-

ing None 1 h None 1 hSlope (mV) 52.0 60.1 49.2 59.9± SD 0.97 0.24 3.67 0.60

Following 5 dips in membrane cocktail 2, CCF2-5 gave a slope of 49.2 mV dec-1 without condi-tioning, which improved to 59.9 mV dec-1 (the ideal is 59.2 mV dec-1) after 1 h conditioning. This suggests that the new sensors containing Li+ (in the form of LiTPFPB) cannot be used directly with-out conditioning. To establish if this pre-condition-ing step could be eliminated, the number of dip-coating cycles, used to fabricate sensors with membrane 2, was varied from 1 to 10 and the slopes of potential vs. log (Li+ activity) were mea-sured; the CCF2-type sensors were left to dry (in ambient air) overnight, to ensure complete sol-vent evaporation, before testing the next day without any conditioning step. The results show an improved sensor response (increased slope) with increasing dip-coating cycles when using membrane cocktail 2 (Table 4). At least 8 dip-coating cycles are required if the CCF2-type sen-sors are to be used without a conditioning step. Evaluation of the response with repeat CCF2-9 sensors established that the procedure was repro-ducible with very small variances between one sensor and another (see Figure S6 in supporting information).

Scanning electron microscopy (SEM) was used to investigate the difference in morphology be-tween a bare cotton fiber, a CCF, and the final CCF-based lithium sensors (Figure S7 in the sup-

porting information). Figure S7A shows the differ-ence between the bare cotton fiber and the CCF (coated with SWCNT). The CCF SEM image shows the adsorption onto the cotton fibers of SWCNT as bundles. A noticeable contrast can be seen be-tween the surface of the CCF before and after coating with membrane 2. (Figure S7B in the sup-porting information). A growth of this coating on the CCF is clearly observed as the dipping cycles are increased. Care must be taken when coating CCFs with CNTs to avoid fibrillation of the cotton fiber, which could result in fragments protruding through the membrane causing part of the SWCNT transducer to be in direct contact with the solution. Figure S7C (supporting information) shows the cross-sectional analysis of CCF2-10, which exhibits a uniform coating over the cotton fiber surface; after 10 dip coats a thickness of less than 15 µm was observed (the total sensor diameter was ca. 0.35 mm). This membrane thickness is 15% of the thickness of traditional ion-selective membranes (ca. 100 µm). For exam-ple, Guinovart et al. fabricated a cotton-based ion-selective sensor in a similar fashion, but their sensor had a diameter of 1.5 mm and a mem-brane thickness of 100 µm;33 a conditioning step was also still necessary for this prior sensor (16 h conditioning before first use with re-conditioning steps of 20 min needed before each subsequent use).

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Figure 5: The potential vs. log (Li+ activity) response of CCF1-9 and CCF2-9 (fabricated from membrane cocktail 1 and 2, respectively with 9 dip coats each). Error bars are from experiments on n = 3 replicate sensors (error bars from membrane 1 are covered with data points at higher concentrations).

The importance of the presence of Li+ in-side the membrane cocktail. To elucidate if the near Nernstian response obtained from mem-brane 2 was the result of the presence of Li+ ions inside the membrane or if it was due to the mem-brane thickness, a further study was carried out. CCF-based lithium sensors containing KTClPB in-stead of LiTPFPB were fabricated using 9 dip-coat-ing cycles in membrane 1 (CCF1-9). Figure 5 compares this sensor’s response to CCF2-9 (ob-

tained using membrane 2 without conditioning). The similarity in the results suggests that mem-brane thickness is the critical factor that allows the CCF-based lithium sensors to be used without conditioning. These results agree with a recently published article that reported a Nernstian re-sponse with the use of a thin membrane (200 nm) without both the use of a pre-conditioning proto-col and the need for the analyte ion to be present in the membrane (before use of the sensor);51 this prior study did not involve fiber-based sensors. The only observed difference in response be-tween the CCF1-9 and CCF2-9 sensors was dur-ing first contact with the analyte solution. Lithium sensors fabricated from membrane 1 required 30 s to stabilize after first immersion, while the sen-sors fabricated from membrane 2 stabilized im-mediately. The latter response may be related to the presence of Li+ inside membrane 2, unlike when using membrane 1. This property is com-pared in the time traces shown in Figure S8 (sup-porting information).

Continuous monitoring of lithium concen-tration. One of the important features of a wear-able sensor is its ability to monitor variations in analyte concentration over time. An experiment was performed to test the ability of the CCF-based sensors to measure concentration changes when going from low concentrations (6.3 × 10-5 M) to high concentrations (6.3 × 10-2 M) and vice versa. A stable, sharp and reproducible response was obtained with CCF2-9 (Figure 6A).

Table 4. The values of the slope of potential vs. log (Li+ activity), over a concentration range of 1.0 × 10-4 M – 6.3 × 10-2 M, of CCF2-type sensors fabricated as a function of lithium (LiPFBP) membrane cocktail 2 dipping cycles. Means and sample standard deviations from measurements on n = 3 repeat sensor fabrications.

1 cycle

2 cycles

3 cycles

4 cycles

5 cycles

6 cycles

7 cycles

8 cycles

9 cycles

10 cycles

Slope± SD

40.8±

2.44

43.3±

1.84

43.9±

0.87

46.9±

1.56

52.7±

1.45

56.6±

0.82

57.8±

2.10

58.4±

3.66

58.5±

1.1558.7± 0.91

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Figure 6: Time traces showing the temporal responses of CCF2-9 When varying the concentrations of the LiCl solutions (concentration range 6.3 × 10-5 – 6.3 × 10-2 M). The values on the plots are log (Li+ activity). The data in Plot B involved the measurement of potential after a sudden reduction in Li+ concentration.

A further experiment was carried out that mea-sured a very low concentration directly after mea-surement of high concentrations. Results confirm the sensor’s capability to respond to this extreme change in Li+ concentration in a stable and re-peatable way (Figure 6B).

Stability of sensor response and lifetime. The potential intercepts and slopes from plots of potential vs. log (Li+ activity) data for of CCF-based lithium sensors was evaluated over 3 months for CCF1-9 and CCF2-9 sensors. Figure S9 (supporting information) shows the potential stability of both sets of sensors while Table 5 shows the variation of the potential vs. log (Li+

activity) data between 3 different sensors when evaluated on the same day and after 3 months of storage (in ambient air). The stability of the stan-dard potential of the CCF1-9 and CCF2-9 sensors over 3 months confirm the absence of a water layer accumulating between the membrane and solid contact electrode. In contrast to the first sensor iteration (CCF1-5), which suffered from water accumulation during conditioning leading to a high standard potential variability from one day to the next, the final iterations of the sensor CCF1-9/CCF2-9 were used directly without con-ditioning with a stable response time of less than 20 sec. Although the sensor has a good stability (Table 5) and can be used directly without pre-

conditioning, pre-calibration before use is re-quired to ensure accurate measurements. The lifetime of the membrane cocktail solution is 6 weeks when kept in a refrigerator at 4oC while the lifetime of sensors CCF1-9/CCF2-9 is 6 months.

Table 5: % RSD from the potential vs. log (Li+ activity) data for CCF-based lithium sen-sors for 3 repeat sensors evaluated over 3 months.

%RSD * CCF1-9 CCF2-9Inter-day inter-

cept 2.06% 3.37%

Inter-day slope 2.76% 4.59%

Selectivity of the fabricated sensors and pH effect. One of the most important features of a good ISE is its selectivity towards the ion of in-terest in the presence of other (potentially inter-fering) ions. The selectivity of CCF1-9 and CCF2-9 were tested using the separate solution method. According to Bakker et al.,52 the sensor should give a Nernstian response towards the in-terfering ions as well as the ion of interest to en-able the application of the Nicolsky−Eisenman equation and the calculation of the selectivity co-efficient. However, our CCF-based sensors did not give a Nernstian response to the interfering ions

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tested, which prevented the calculation of the se-lectivity coefficients. Calibration curves of the sensors in solutions containing either the interfer-ing species or Li+ are presented in Figure 7 and S10 (supporting information). It was observed that Na+ ions gave the highest interfering effect with the use of membrane cocktail 1, while Ca2+

was the most interfering ion for membrane cock-tail 2. However, the potentials recorded with the interfering species were much lower than those recorded with LiCl solutions. The CCF1-9 and CCF2-9 sensors were tested in Britton–Robinson buffer over a pH range from 2-12. Both CCF1-9 and CCF2-9 were stable over a pH range be-tween 6-12, which includes the physiological pH of plasma and ISF (data not shown).

Figure 7: The response of CCF2-9 to the presence of varying concentrations of interfering species (and Li+). Single species solutions were used over a con-centration range of 1.0 × 10-4 – 6.3 × 10-2 M.

Application to human plasma solutions. As the intended application of these sensors is to de-termine lithium concentration in interstitial fluid, the sensor response was tested in plasma solu-tion. A previous comparison between interstitial fluid and plasma shows a similarity in composi-tion with plasma having a higher protein content (Table S1 gives the compositions) 53. Synthetic in-terstitial fluid is not currently available commer-cially, therefore human plasma was used to test the response of CCF-based sensors. The assump-tion used in this study is that the sensor will re-spond in plasma in a similar way to ISF. The plasma solution was spiked with LiCl solution over varying concentration ranges. On switching from aqueous solutions to plasma solutions, the poten-tial response decreased by 4 - 6 mV for CCF1-9 and 2 - 3 mV for CCF2-9, while the linear re-sponse range contracted from 1.0 × 10-4 – 6.3 × 10-1 M to 4.0 × 10-4 – 8.0 × 10-3 M. These changes in response may be attributed to the high Na+

concentrations in plasma (139 × 10-3 – 142 × 10-3

M). The difference between the responses of sen-sors fabricated using membrane 1 and membrane 2 is explained by the observation that Na+ was more interfering for membrane 1 compared to

membrane 2, as discussed previously. Figure 8 and S11 (supporting information) give the calibra-tion curves of CCF2-9 and CCF1-9 respectively, by comparing responses between aqueous LiCl solutions and LiCl-spiked plasma solutions. De-spite the lower slopes, both types of CCF-based sensors have the same efficiency in determining lithium concentrations in human plasma samples with an excellent recovery of 100.0 % ± 1.07 and a 100.3 % ± 1.07 for CCF1-9 and CCF2-9, respectively (data shown in Table S2 and S3 in the supporting information). Crucially, the narrowing of the lin-ear response range of the sensors did not move the responses outside the clinical relevant range of lithium (4.0 × 10-4 M – 1.0 × 10-3 M).

Figure 8: Calibration curves obtained with CCF2-9 in both aqueous and plasma solutions of LiCl. The clini-cal relevant range for lithium is between the two dashed vertical lines.

CONCLUSION Fiber-based sensors were fabricated for lithium

ion determination. These sensors demonstrated good accuracies, selectivities, stabilities, as well as rapid response times and long lifetimes. This is the first time that fiber-based sensors were fab-ricated which are ready for use without the need for any pre-conditioning steps, rendering them suitable for wearable applications. Eliminating conditioning excluded both overnight conditioning prior to first use (formerly required for other ion-selective sensors) as well as any daily condition-ing before each use. Crucially, the sensors were capable of determining lithium ion concentrations in plasma, which indicated their suitability for the clinically-relevant determination of Li+ concentra-tions in interstitial fluid (thiswork is in progess).

ASSOCIATED CONTENT Supporting Information

The Supporting Information is available free of charge on the ACS Publications website. Figures of conversion of cotton fiber into a conductive fiber and its characterization using Raman spectroscopy and scanning electron microscope, conditioning effect, selectivity and plasma calibration curve. Tables of the composition of interstitial fluid and plasma. Ta-

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ble of determination of spiked lithium in plasma (PDF).

AUTHOR INFORMATIONCorresponding Author

* c.crean@surrey.ac.uk Addresses

†on study leave from Faculty of Pharmacy, Helwan University, Helwan, Egypt.

ACKNOWLEDGMENT The authors thank Newton-Mosharafa PhD pro-

gramme (British council and Egyptian cultural affairs & mission sector) for providing funding for this work. The authors would like to acknowledge EPSRC grant ‘High Spec Raman Spectrometer Regional Facility’ (EP/M022749/1).

REFERENCES1. Logan, J.; Main, T. NHS FORTH VALLEY, Guideline for the Management of Patients on Lithium; 2015.2. Tabata, M.; Nishimoto, J.; Kusano, T., Spectrophoto-metric determination of lithium ion using a water-solu-ble octabromoporphyrin in aqueous solution. Talanta 1998, 46 (4), 703-709.3. Gracia, L. G.; Rodríguez, L. C.; Ceba, M. R., Spec-trophotometric determination of lithium with quinizarin in drugs and serum. Talanta 1997, 44 (1), 75-83.4.Dol, I.; Knochen, M.; Vieras, E., Determination of lithium at ultratrace levels in biological fluids by flame atomic emission spectrometry. Use of first-derivative spectrometry. Analyst 1992, 117 (8), 1373-1376.5.Rocks, B. F.; Sherwood, R. A.; Riley, C., Direct determi-nation of therapeutic concentrations of lithium in serum by flow-injection analysis with atomic absorption spec-troscopic detection. Clinical chemistry 1982, 28 (3), 440-443.6. Strieglerová, L.; Kubáň, P.; Boček, P., Rapid and sim-ple pretreatment of human body fluids using elec-tromembrane extraction across supported liquid mem-brane for capillary electrophoretic determination of lithium. Electrophoresis 2011, 32 (10), 1182-1189.7. González, S.; Navarro, M.; López, H.; López, M. C.; Pérez, V., Determination of lithium in human serum by electrothermal atomic absorption spectrometry. Journal of AOAC International 2000, 83 (2), 377-381.8. Leflon, P.; Plaquet, R.; Rose, F.; Hennon, G.; Ledeme, N., Rapid determination of lithium in human serum and urine, at physiological concentrations, by inductively coupled argon plasma atomic emission spectrometry. Analytica chimica acta 1996, 327 (3), 301-306.9. Krachler, M.; Irgolic, K., The potential of inductively coupled plasma mass spectrometry (ICP-MS) for the si-multaneous determination of trace elements in whole blood, plasma and serum. Journal of trace elements in medicine and biology 1999, 13 (3), 157-169.10. Vanhoe, H.; Dams, R.; Versieck, J., Use of inductively coupled plasma mass spectrometry for the determina-tion of ultra-trace elements in human serum. Journal of analytical atomic spectrometry 1994, 9 (1), 23-31.11. Ceba, M. R.; Fernandez-Gutierrez, A.; Sánchez, C. M., Some observations on the use of 1, 4-dihydroxyan-thraquinone as a fluorometric reagent for traces of lithium. Microchemical journal 1985, 32 (3), 286-292.12. Rodríguez, L. C.; Linares, C. J.; Ceba, M. R., Selective spectrofluorometric determination of lithium (I) with

quinizarin by extraction into tributyl phosphate. Frese-nius' journal of analytical chemistry 1996, 356 (5), 320-325.13. Albero, M.; Ortuno, J.; Garcia, M.; Cuartero, M.; Al-caraz, M., Novel flow-through bulk optode for spec-trophotometric determination of lithium in pharmaceuti-cals and saliva. Sensors and Actuators B: Chemical 2010, 145 (1), 133-138.14. Sawada, S.; Torii, H.; Osakai, T.; Kimoto, T., Pulse amperometric detection of lithium in artificial serum us-ing a flow injection system with a liquid/liquid-type ion-selective electrode. Analytical Chemistry 1998, 70 (20), 4286-4290.15. SAWADA, S.; OSAKAI, T.; SENDA, M., Voltammetric lithium ion-selective electrodes based on ion transfer at the oil/water interface facilitated by neutral ionophores. Analytical sciences 1995, 11 (5), 733-738.16. Cuartero, M.; Crespo, G. A.; Bakker, E., Polyurethane ionophore-based thin layer membranes for voltammet-ric ion activity sensing. Analytical chemistry 2016, 88 (11), 5649-5654.17. Coldur, F.; Andac, M., All-solid-state polyvinyl chlo-ride membrane lithium-selective electrode with im-proved selectivity and its application in serum lithium assay. Sensor Letters 2011, 9 (5), 1738-1744.18. Sim, J. H.; Lee, G. M.; Lee, J. S.; Jo, D. H.; Nam, H. H.; Cha, G. S., Lithium ion-selective electrode with im-proved lifetime. Bulletin of the Korean Chemical Society 2001, 22 (7), 765-768.19.http://www.diazyme.com/websites/diazyme/images/proucts/pdf/L- ithiumBrochureN-061715.pdf.20. Christian, G. D., Analytical strategies for the mea-surement of lithium in biological samples. Journal of pharmaceutical and biomedical analysis 1996, 14 (8-10), 899-908.21. Vrouwe, E. X.; Luttge, R.; van den Berg, A., Direct measurement of lithium in whole blood using microchip capillary electrophoresis with integrated conductivity detection. Electrophoresis 2004, 25 (10‐11), 1660-1667.22. Vrouwe, E. X.; Luttge, R.; Olthuis, W.; van den Berg, A., Microchip analysis of lithium in blood using moving boundary electrophoresis and zone electrophoresis. Electrophoresis 2005, 26 (15), 3032-3042.23. Vrouwe, E. X.; Luttge, R.; Vermes, I.; Van Den Berg, A., Microchip capillary electrophoresis for point-of-care analysis of lithium. Clinical chemistry 2007, 53 (1), 117-123.24. Floris, A.; Staal, S.; Lenk, S.; Staijen, E.; Kohlheyer, D.; Eijkel, J.; van den Berg, A., A prefilled, ready-to-use electrophoresis based lab-on-a-chip device for monitor-ing lithium in blood. Lab on a Chip 2010, 10 (14), 1799-1806.25. Novell, M.; Guinovart, T.; Blondeau, P.; Rius, F. X.; Andrade, F. J., A paper-based potentiometric cell for de-centralized monitoring of Li levels in whole blood. Lab on a Chip 2014, 14 (7), 1308-1314.26. Glazer, W. M.; Sonnenberg, J. G.; Reinstein, M. J.; Ak-ers, R. F., A novel, point-of-care test for lithium levels: description and reliability. The Journal of clinical psychi-atry 2004, 65 (5), 652-655.27. Dimeski, G.; Badrick, T.; St John, A., Ion selective electrodes (ISEs) and interferences—a review. Clinica Chimica Acta 2010, 411 (5), 309-317.28. Lee, D. C.; Klachko, M. N., Falsely elevated lithium levels in plasma samples obtained in lithium containing tubes. Journal of Toxicology: Clinical Toxicology 1996, 34 (4), 467-469.29. Wills, B. K.; Mycyk, M. B.; Mazor, S.; Zell-Kanter, M.; Brace, L.; Erickson, T., Factitious lithium toxicity sec-

10

ondary to lithium heparin-containing blood tubes. Jour-nal of Medical Toxicology 2006, 2 (2), 61-63.30. Bandodkar, A. J.; Wang, J., Non-invasive wearable electrochemical sensors: a review. Trends in biotechnol-ogy 2014, 32 (7), 363-371.31. Schazmann, B.; Morris, D.; Slater, C.; Beirne, S.; Fay, C.; Reuveny, R.; Moyna, N.; Diamond, D., A wearable electrochemical sensor for the real-time measurement of sweat sodium concentration. Analytical Methods 2010, 2 (4), 342-348.32. Bandodkar, A. J.; Molinnus, D.; Mirza, O.; Guinovart, T.; Windmiller, J. R.; Valdés-Ramírez, G.; Andrade, F. J.; Schöning, M. J.; Wang, J., Epidermal tattoo potentiomet-ric sodium sensors with wireless signal transduction for continuous non-invasive sweat monitoring. Biosensors and bioelectronics 2014, 54, 603-609.33. Guinovart, T.; Parrilla, M.; Crespo, G. A.; Rius, F. X.; Andrade, F. J., Potentiometric sensors using cotton yarns, carbon nanotubes and polymeric membranes. Analyst 2013, 138 (18), 5208-5215.34. Cuartero, M.; del Río, J. S.; Blondeau, P.; Ortuño, J. A.; Rius, F. X.; Andrade, F. J., Rubber-based substrates modified with carbon nanotubes inks to build flexible electrochemical sensors. Analytica chimica acta 2014, 827, 95-102.35. Guinovart, T.; Bandodkar, A. J.; Windmiller, J. R.; An-drade, F. J.; Wang, J., A potentiometric tattoo sensor for monitoring ammonium in sweat. Analyst 2013, 138 (22), 7031-7038.36. Gonzalo-Ruiz, J.; Mas, R.; de Haro, C.; Cabruja, E.; Camero, R.; Alonso-Lomillo, M. A.; Muñoz, F. J., Early de-termination of cystic fibrosis by electrochemical chlo-ride quantification in sweat. Biosensors and Bioelec-tronics 2009, 24 (6), 1788-1791.37. Chu, M.; Shirai, T.; Takahashi, D.; Arakawa, T.; Kudo, H.; Sano, K.; Sawada, S.-i.; Yano, K.; Iwasaki, Y.; Akiyoshi, K., Biomedical soft contact-lens sensor for in situ ocular biomonitoring of tear contents. Biomedical microdevices 2011, 13 (4), 603-611.38. Yao, H.; Shum, A. J.; Cowan, M.; Lähdesmäki, I.; Parviz, B. A., A contact lens with embedded sensor for monitoring tear glucose level. Biosensors and Bioelec-tronics 2011, 26 (7), 3290-3296.39. Yao, H.; Liao, Y.; Lingley, A.; Afanasiev, A.; Lähdesmäki, I.; Otis, B.; Parviz, B., A contact lens with integrated telecommunication circuit and sensors for wireless and continuous tear glucose monitoring. Jour-nal of Micromechanics and Microengineering 2012, 22 (7), 075007.40. Liao, Y.-T.; Yao, H.; Lingley, A.; Parviz, B.; Otis, B. P., A 3-CMOS glucose sensor for wireless contact-lens tear glucose monitoring. IEEE Journal of Solid-State Circuits 2012, 47 (1), 335-344.41. Kagie, A.; Bishop, D. K.; Burdick, J.; La Belle, J. T.; Dymond, R.; Felder, R.; Wang, J., Flexible Rolled Thick‐Film Miniaturized Flow‐Cell for Minimally Invasive Am-

perometric Sensing. Electroanalysis 2008, 20 (14), 1610-1614.42. Iguchi, S.; Kudo, H.; Saito, T.; Ogawa, M.; Saito, H.; Otsuka, K.; Funakubo, A.; Mitsubayashi, K., A flexible and wearable biosensor for tear glucose measurement. Biomedical microdevices 2007, 9 (4), 603-609.43. Thomas, N.; Lähdesmäki, I.; Parviz, B. A., A contact lens with an integrated lactate sensor. Sensors and Ac-tuators B: Chemical 2012, 162 (1), 128-134.44. Kim, J.; Valdés-Ramírez, G.; Bandodkar, A. J.; Jia, W.; Martinez, A. G.; Ramírez, J.; Mercier, P.; Wang, J., Non-in-vasive mouthguard biosensor for continuous salivary monitoring of metabolites. Analyst 2014, 139 (7), 1632-1636.45. Bandodkar, A. J.; Jia, W.; Yardımcı, C.; Wang, X.; Ramirez, J.; Wang, J., Tattoo-based noninvasive glucose monitoring: a proof-of-concept study. Analytical chem-istry 2014, 87 (1), 394-398.46. Leboulanger, B.; Aubry, J.-M.; Bondolfi, G.; Guy, R. H.; Delgado-Charro, M. B., Lithium monitoring by re-verse iontophoresis in vivo. Clinical chemistry 2004, 50 (11), 2091-2100.47. Leboulanger, B.; Fathi, M.; Guy, R. H.; Delgado-Charro, M. B., Reverse iontophoresis as a noninvasive tool for lithium monitoring and pharmacokinetic profil-ing. Pharmaceutical research 2004, 21 (7), 1214-1222.48. Hu, L.; Pasta, M.; Mantia, F. L.; Cui, L.; Jeong, S.; De-shazer, H. D.; Choi, J. W.; Han, S. M.; Cui, Y., Stretchable, porous, and conductive energy textiles. Nano letters 2010, 10 (2), 708-714.49. Fibbioli, M.; Morf, W. E.; Badertscher, M.; de Rooij, N. F.; Pretsch, E., Potential drifts of solid‐contacted ion‐se-lective electrodes due to zero‐current ion fluxes through the sensor membrane. Electroanalysis 2000, 12 (16), 1286-1292.50. Rich, M.; Mendecki, L.; Mensah, S. T.; Blanco-Mar-tinez, E.; Armas, S.; Calvo-Marzal, P.; Radu, A.; Chumbimuni-Torres, K. Y., Circumventing traditional con-ditioning protocols in polymer membrane-based ion-se-lective electrodes. Analytical chemistry 2016, 88 (17), 8404-8408.51. Yuan, D.; Cuartero, M.; Crespo, G. A.; Bakker, E., Voltammetric Thin-Layer Ionophore-Based Films: Part 1. Experimental Evidence and Numerical Simulations. An-alytical chemistry 2016, 89 (1), 586-594.52. Bakker, E.; Pretsch, E.; Bühlmann, P., Selectivity of potentiometric ion sensors. Analytical Chemistry 2000, 72 (6), 1127-1133.53. Ebah, L., Extraction and Analysis of Interstitial Fluid, and Characterisation of the Interstitial Compartment in Kidney Disease, 2012 (Doctoral thesis, University of Manchester, UK), Retrived from https://www.escholar.-manchester.ac.uk/uk-ac-man-scw:167348 , on 27/9/2017.

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