# Boron-doped carbon nanowalls as effective electrodes for non-enzymatic electrochemical glucose detection: A novel bimodal EC-SALDI-MS approach

Ioana Silvia Hosu, M. Sobaszek, M. Ficek, R. Bogdanowicz, Yannick Coffinier

## ► To cite this version:

Ioana Silvia Hosu, M. Sobaszek, M. Ficek, R. Bogdanowicz, Yannick Coffinier. Boron-doped carbon nanowalls as effective electrodes for non-enzymatic electrochemical glucose detection: A novel bimodal EC-SALDI-MS approach. Materials Today Nano, 2025, 30, 10.1016/j.mtnano.2025.100635. hal-05123168

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Submitted on 20 Jun 2025

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# Boron-doped carbon nanowalls as effective electrodes for non-enzymatic electrochemical glucose detection: A novel bimodal EC-SALDI-MS approach

I.S. Hosu<sup>a,b</sup>, M. Sobaszek<sup>c</sup>, M. Ficek<sup>c</sup>, R. Bogdanowicz<sup>c</sup>, Y. Coffinier<sup>a,*</sup> <sup>Δ</sup>

<figure><img src="image_2.png" /></figure>

## ARTICLE INFO

### Keywords:

- Non-enzymatic detection
- Glucose
- Gluconic acid
- EC
- LDI-MS
- Bimodal detection

## ABSTRACT

For the first time, boron-doped carbon nanowalls (B-CNWs) have been used as effective working electrodes for non-enzymatic electrochemical glucose detection. To achieve optimal response time and sensitivity, we activated B-CNWs by polarising them at 1.1 V in NaOH for 60 min. We established a robust linear dynamic range for glucose concentrations from 10 to 550 µM and calculated a limit of detection (LoD) of 10 µM. Additionally, B-CNWs demonstrated excellent selectivity for glucose, even in the presence of various interfering compounds like its isomer, galactose. Importantly, we showed that B-CNWs could detect gluconic acid, the oxidation product of glucose, using mass spectrometry in an off-line configuration. This novel approach combines electrochemical (EC) and surface-assisted laser desorption/ionisation mass spectrometry (SALDI-MS) detection, utilising the same nanomaterial (B-CNWs) in a bimodal configuration. This coupling represents a significant advancement in glucose sensing technology by leveraging the unique properties of B-CNWs and providing a powerful analytical tool for detecting, identifying, and understanding a wide range of chemical compounds and processes.

## 1. Introduction

Glucose sensors are mainly based on amperometric read-out comprising both enzymatic and non-enzymatic sensors [1,2]. Despite their lower selectivity, non-enzymatic sensors are generally more stable over time since they are not susceptible to denaturation or degradation like enzymes are, which is a common issue with their enzyme-based counter-part (e.g. Glucose oxidase, GOx). Non-enzymatic sensors can operate under a wider range of environmental conditions, making them suitable for use in on-site detection, and greatly simplifying their storage between the different tests, since there is no need for special storage conditions (e.g., refrigeration, buffers, pH, etc.) to maintain enzyme activity. In addition, avoiding the use of enzymes will strongly reduce the production costs, as enzymes can be expensive to produce and purify and provide a longer shelf life compared to enzyme-based ones [3]. The latter is beneficial for commercial and consumer applications and helps to reduce waste and lower the replacement frequency. Recently, working electrodes made of or modified by a noble metal, transition metal particles or metal-organic framework have been proposed as an alternative to enzymatic glucose detection. Their high electrocatalytic

activity and high sensitivity to the electro-oxidation of glucose make them a good alternative to enzyme-based sensors. Such electrodes mainly work in an alkaline electrolyte, allowing the conversion of glucose into gluconolactone and then to gluconic acid, where hydroxide (OH⁻) ions and hydroxyl groups on the analyte play a crucial role in the electro-oxidation mechanism [4]. These materials provide a high surface area for the interaction with glucose, leading to better detection limits and good sensitivity thanks to a higher electron transfer rate [5]. Since, no enzyme molecules are involved in the detection process, they are generally more robust and reliable, as they are not affected by factors that can impact enzyme activity (e.g., inhibitors, temperature, pH fluctuations, folding and orientation issues), thus making them suitable for continuous and long-term monitoring. Finally, since they do not require immobilisation of enzymes via complex bio-functionalisation steps, the manufacturing process is straightforward and is compatible with micro-nanofabrication, integration and packaging processes to develop compact and portable devices. Several examples of enzyme-free glucose sensing have been published in the last decade. One of them, which showed the use of gold electrodes modified by Co or Cu nano-particles in the presence of a ferrocene-glutathione mediator, showed

<footnote><sup>a</sup> Univ. Lille, CNRS, IEMN, UMR CNRS 8520, Avenue Poincaré, Villeneuve d'Ascq, BP 60069 59652, France</footnote>

<footnote><sup>b</sup> National Institute for Research & Development in Chemistry and Petrochemistry—ICECHIM, Emerging Nanotechnologies Group, 202 Spl. Independentei, Sector 6, Bucharest, Romania</footnote>

<footnote><sup>c</sup> Faculty of Electronics, Telecommunication and Informatics, Gdansk University of Technology, 11/12 Narutowicza St, 80-233, Gdańsk, Poland</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: yannick.coffinier@univ-lille.fr (Y. Coffinier).</footnote>
improved performance in terms of linear range detection from 0.70 to 3.6 mM and a sensitivity of 378.70 µA* mM⁻¹/cm² [6].

Carbon-based nanomaterials such as diamond nanostructures have also been used for non-enzymatic glucose detection. For example, diamond nanowires coated with nickel particles were developed for the electrochemical oxidation of glucose and reduction of hydrogen [7]. Another example was given by Luo et al. who showed that diamond nanorods can detect glucose in the range of 100 µM to 7 mM [8]. In our group, we compared boron-doped diamond nanowires of different lengths and demonstrated better sensitivity and a good linear dynamic range for glucose detection for the longer ones [9]. Such good sensitivity, selectivity and linear range are thus due to the increased surface area of nanostructured electrodes compared to planar ones. More recently, another allotropic form of carbon made of vertically aligned graphene sheets called carbon nanowalls (CNWs) has emerged as a good electrochemical (EC) working electrode. The effectiveness of Boron-doped CNWs (B-CNWs) is attributed to their high electrical conductivity and to the increased electroactive surface area of B-CNW-based working electrodes compared to planar electrodes. A high surface area provides more active sites for electron transfer, improving the sensitivity and detection limits. Like other carbon-based materials, B-CNWs exhibit excellent electrical conductivity, enabling fast electron transfer kinetics and enhancing the efficiency of electrochemical reactions. Unlike planar graphene, B-CNWs have a high density of edge planes, which are more electrochemically active than basal planes. These edge sites facilitate better adsorption of analytes and enhance the catalytic activity for redox reactions. B-CNWs have been used as working electrodes, showing their ability to detect various compounds by electrochemical means, including herbicides [10], plant pathogens [11], and viruses [12].

In addition, B-CNWs have shown great potential as efficient surface-assisted laser desorption/ionisation mass spectrometry (SALDI-MS) nanomaterials that primarily rely on their physicochemical properties, including: surface morphology, dimensions, roughness, surface chemistry, and ultraviolet (UV) absorption (typically around 365 nm) and anti-reflective properties, which matches the laser wavelength of commercial mass spectrometers. Additionally, the thermal properties of B-CNWs play a crucial role in heat confinement, enabling the more efficient transfer of internal energy from the B-CNWs to the analyte, thereby minimising fragmentation. While B-CNWs exhibit good electrical conductivity, the voids between the walls reduce thermal conductivity, helping to trap heat within the material, allowing the use of lower laser fluence and thus limiting the fragmentation of compounds and the background. Recently, B-CNWs have been used in mass spectrometry for the detection of various compounds, including carbohydrates, lipids, peptides, and proteins, such as cytochrome C and ricin [13,14].

This means that the combination of both EC and MS, particularly through the use of B-CNWs in dual mode, could provide several significant advantages for compound detection and analysis. These advantages include enhanced sensitivity and specificity, the ability to study redox-active compounds and their transformation products—analytes that may be challenging to analyse using either technique alone—and the provision of detailed mechanistic insights into electrochemical reactions by identifying transient intermediates and end products. Building on this concept, we propose to combine the EC and LDI-MS techniques for the first-time using B-CNWs for the enzyme-free detection of glucose, along with the detection of its oxidation product by mass spectrometry. This proof of concept aims to demonstrate that the combination of EC and LDI-MS can be a powerful analytical tool, enhancing the detection, identification, and understanding of a wide range of chemical compounds.

# 2. Materials & methods

## 2.1. Chemicals

Sodium chloride (NaCl), α-D-glucose (Glc), D-(+) xylose (Xyl), D-(-)

fructose (Fru), D-(+) galactose (Gal), gluconic acid (GlcA), potassium chloride (KCl), sodium hydroxide (NaOH), Lithium chloride (LiCl), ascorbic acid (AA), uric acid (UA), and potassium hexacyanoferrate (II) trihydrate (K₄ [Fe(CN)₆]) were all purchased from Sigma-Aldrich and used as received. Calibration mixtures were purchased from SCIEX. Ultrapure water (Milli-Q, 18 MΩ cm⁻¹) was used in the preparation of the solutions and in all rinsing steps.

## 2.2. Boron-doped carbon nanowalls synthesis

Boron-doped carbon nanowalls were synthesised by microwave plasma-enhanced chemical vapour deposition (ME-CVD) following the protocol previously described [14]. The boron doping in H₂/CH₄ plasma was performed on a p-type Si (100) substrate, on a 700 °C heated plate and 1200 ppm of B/C in the gas chamber.

## 2.3. Surface characterisation techniques

*Scanning electron microscopy.* SEM images were obtained using an ULTRA 55 electron microscope (Zeiss), equipped with a thermal field emission emitter with three different detectors: EsB filter grid detector, high efficiency in-lens SE detector, and Everhart-Thornley secondary electron detector. Image processing achieved using ImageJ software.

*Water contact angle (WCA) measurements.* WCA values were measured using deionised water. A DIGIDROP goniometer system from GBX, France, was used to measure the contact angles. The accuracy is ±2°. All measurements were made in an ambient atmosphere at room temperature at 3 different locations on each surface.

## 2.4. Glucose detection

### 2.4.1. Electrochemical experiments

Electrochemical studies were performed by chronoamperometry (CA) using an Autolab PGSTAT 101 potentiostat (Eco Chemie, Utrecht, The Netherlands). The electrochemical cell consisted of a working electrode, WE (B-CNWs surface), Ag/AgCl as the reference electrode, and a platinum wire as the counter electrode. Glucose detection was performed in a freshly prepared 0.1 M NaOH solution before each experiment. A potential centred at 0.56 V was determined from the cyclic voltammetry (CV) studies. However, 0.5 V was selected for chronoamperometry as it minimising interference from other species that typically oxidize closer to 0.6 V (see Fig. S1 in supplementary data). While applying an overpotential (e.g., ≥0.6 V) can sometimes help overcome kinetic barriers in the electrochemical detection of analytes such as glucose, in our case, it was not necessary. Instead, we opted for a slightly lower potential (underpotential) of 0.5 V to improve selectivity.

### 2.4.2. Laser desorption ionisation-mass spectrometry

In LDI-MS experiments, the sample deposition method, unless otherwise stated, was as follows: 0.5 µl droplets were dropped on at least 3 different locations on 3 different as-received B-CNW surfaces and allowed to dry in air. The B-CNWs were then fixed to an MTP TLC adapter (Bruker) using carbon conductive double-sided adhesive tape. The plate was then inserted directly into the ion source of the mass spectrometer. External calibration was performed with commercial peptide mixtures. Matrix-assisted laser desorption/ionisation (MALDI) mass spectra were recorded on a Bruker Autoflex Speed instrument (Bruker Daltonics, Wissembourg, France) equipped with a Time-of-flight (TOF) analyser and a LIFT module. A pulsed Smartbeam II 2 kHz laser at a wavelength of 355 nm (~3.49 eV) was operated at a frequency of 1000 Hz (MS data) with a delayed extraction time of 350 ns. The source was operated in reflectron positive mode. An acceleration voltage of 25.0 kV (IS1) was applied for a final acceleration of 21.95 kV (IS2). Random laser irradiation was performed according to the partial sample mode with 1000–5000 shots/point. Ions were detected in different mass ranges according to the samples analysed, usually in the 100–1000 m/z
mass range. Data were acquired using the FlexControl software and processed using the FlexAnalysis software. The signal-to-noise ratio (S/N) was set to a minimum of 3 and all laser percentages represent the absolute value of the laser, not the relative laser power as shown in the GUI (Graphical User Interface) of the FlexControl 3.4 software.

### 3. Results and discussion

Carbon nanowalls are composed of multi-layered graphene nano-sheets vertically aligned on a surface [15]. In this study, B-CNWs were synthesised by ME-CVD, as described in previous studies [16]. The B-CNWs used here were doped *in situ* in the presence of 1200 ppm of $B_2H_6$. Recently, CNWs have attracted significant attention due to their unique properties, such as high conductivity and large surface area. Many researchers have already proposed some applications of CNWs for electron field emitters [17], catalyst supports for fuel cells [18], biosensors [19] and electrodes for electrical double layer capacitors (EDLCs) [20] for lithium-ion batteries [21] and for redox flow batteries [22]. Here, we propose to combine electrochemistry and mass spectrometry techniques to provide a suitable dual-mode analytical tool. Such a combination is of great interest, especially when it is difficult to elucidate the redox chemical reactions, to identify some products/by-products or when interfering species have the same redox potential, which could lead to false positives. In the latter case, mass spectrometry will clearly help to identify the correct compounds. Therefore, we propose here an original approach for the detection of glucose by means of non-enzymatic EC combined with SALDI-MS. Fig. 1 presents the strategy as well as the redox mechanism of glucose detection by EC.

In this procedure, the growth time was set to 6 h, and the concentration of the boron precursor ($B_2H_6$) was maintained at 1200 ppm [B]/[C] (1.2k) in the reaction chamber. It is well understood that the surface morphology and nanostructure dimensions of these nanomaterials play critical roles in both LDI processes and EC detection performances [14, 23]. As shown in Fig. 2, SEM images revealed a B-CNW layer with a height of 3.5 µm, featuring nanowalls with lengths of 400–600 nm and thicknesses ranging from 10 to 30 nm. Specific nanostructure dimensions (<500 nm) are known to enhance physical properties such as the thermal dissipation, optical absorption, energy confinement, plasmon resonances, local field effects, and surface-specific area [24]. Building on our previous studies, Raman spectroscopy confirmed the graphene-like structure of B-CNWs. The analysis revealed characteristic peaks, including the D-band at $1352 \text{ cm}^{-1}$ (indicative of defects in the π-electron system), the G-band at $1590 \text{ cm}^{-1}$ (associated with $sp^2$ carbon vibrations), the 2D-band at $2727 \text{ cm}^{-1}$ (corresponding to graphene layer stacking), and the band at $2960 \text{ cm}^{-1}$ (attributed to $sp^2$ C-H stretching) [13,14]. The as-synthesised B-CNWs are hydrophobic, with WCA of 127° (Fig. 1). Therefore, an oxidation step is necessary to introduce hydroxyl groups on the surface, converting them to a hydrophilic state to enhance their electrochemical performance [25]. A low WCA of B-CNWs ensures

good contact with the electrolyte aqueous solution (100 mM NaOH) and promotes the formation of the electrical double layer, thereby increasing the mass and electron transfer. After electrochemical oxidation, the WCA decreased to 13° (Fig. 1), confirming the hydrophilic nature of the B-CNWs and thereby improving the interaction with the glucose solution. Importantly, no change in the B-CNW morphology was observed.

The electrical polarisation of electrochemical electrodes is a crucial preparatory step before their use in sensing applications. This process involves applying a specific electrical potential (here 1.1 V) to the electrode to stabilise its surface properties and improve its performance during electrochemical sensing. This will help the surface stabilisation and activation. Indeed, electrodes, when initially fabricated or after being stored for long periods, often have surface impurities that can hinder their performance. Polarisation helps to remove these unwanted layers and contamination, ensuring that the electrode surface is clean and active. In parallel, the process activates the electrode surface by creating a consistent and stable oxide layer, which is essential for reproducible electrochemical measurements. Indeed, polarised electrodes exhibit improved sensitivity and selectivity due to their well-defined surface properties. This is particularly important in applications such as sensors, where detecting low concentrations of analytes is critical. The polarisation process can also help in introducing surface functional groups or facilitating the formation of specific chemical states (e.g. hydroxyl groups) that are more reactive to the target analyte. Finally, as already described above, the electrical polarisation aids in the formation of a stable electrical double layer at the electrode-electrolyte interface, which is needed for an efficient transfer of both mass and charge during electrochemical reactions, thus participating to noise reduction and enhancing the signal clarity, leading to more accurate and precise measurements. This means that electrical polarisation, by stabilising and activating the electrode surface, ensures that the electrodes function optimally, providing accurate and precise data essential for various applications. Fig. 3A presents the chronoamperometric curves obtained after varying polarisation times of B-CNWs at 1.1 V in 0.1 M NaOH for detecting 200 µM of glucose at 0.5 V. The oxidation potential of glucose varies depending on factors such as the pH and electrode material. In neutral to alkaline solutions glucose oxidation typically occurs between +0.2 V and +0.8 V vs. Ag/AgCl. Based on CV studies, a potential of 0.5 V was selected, as it maximised the glucose oxidation current while minimising interference from other species. This value is consistent with previous literature on boron-doped carbon nanomaterials, ensuring reliable and reproducible results. Polarisation for 60 min provided the best performance compared to shorter durations. Specifically, the faradaic current measured after 60 min was five times higher than after 30 min, and the response time was ten times faster. It is important to note that extending the duration beyond 60 min did not significantly enhance the sensor response but instead increased the noise and risk of electrode surface degradation. Consequently, a 1-h polarisation time was selected for further measurements. Fig. 3B shows the

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Schematic representation of the use of B-CNWs for bimodal detection of glucose via non-enzymatic electrochemical and mass-spectrometry read-out.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Fig. 2. SEM images of B-CNW 1.2k in cross view (A), top view (B) and at higher magnification illustrating the dimensions of CNWs (lengths and thicknesses) (C).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Fig. 3. (A) Chronoamperometry measurements for determining the best polarisation time of B-CNWs for the detection of 200 µM of glucose in 0.1 M NaOH @0.5V, and (B) Chronoamperometry measurement at 0.5 V using increasing glucose concentrations on polarised B-CNWs (60 min).</figcaption></figure>

currents measured by chronoamperometry for increasing glucose con-
centrations on B-CNWs polarised for 60 min in 0.1 M NaOH. The data
demonstrate that our B-CNWs can detect a wide range of glucose con-
centrations. Then, by using the data from Fig. 3B, calibration curves
were plotted (Fig. 4A) for before and after the polarisation. The results
clearly show that the polarisation significantly increased the sensitivity
of the glucose detection, primarily due to the hydrophilic groups created
on the surface, which facilitate the accessibility of glucose to the cata-
lytic sites. The calibration curve obtained after polarisation was 1/µA =
2.914 + 0.026*[glucose]/µM, and a linear dynamic range between 10
and 550 µM of glucose and a LoD value of 10 µM were determined. This
is in good accordance with a previous study, where glucose was detected

using B-CNWs in SALDI-MS with a linear dynamic range of 10–800 µM
[13]. This similarity suggests that the same analyte, here glucose, can be
detected for dual detection and quantification using the same type of
surface. Additionally, the mutual assistance of SALDI-MS can extend the
linear range beyond what is achievable with EC alone.

When dealing with electrochemical detection, we should ensure the
accuracy and specificity of the measurements, particularly when dealing
with complex samples containing multiple components. An interference
study is a crucial aspect of method development and validation in
electrochemical detection, addressing several critical needs. First, it can
help to determine how the presence of other substances in the sample
matrix affects the electrochemical response. This is essential for ensuring

<figure><img src="image_6.png" /><figcaption>Fig. 4. (A) Calibration curves using CA at 0.5 V after and before polarisation at 1.1 V, and (B) CA at 0.5 with injecting different interfering species: AA (ascorbic acid), UA (uric acid), Gal (Galactose), Xyl (Xylose), Fru (fructose), each at 600 µM.</figcaption></figure>
that the measured signal truly corresponds to the analyte of interest and is not being influenced by other interfering species. By identifying and quantifying potential interferents, we can then adjust their detection methods to minimise these effects (more dedicated sample preparation, for instance), thereby improving the accuracy and reliability of the measurements. By doing so, it provides insights into the selectivity of the sensor by revealing how it performs in the presence of common interferents. Again, understanding the specificity of the sensor makes it possible to develop more refined detection strategies, such as the use of selective coatings, membranes, or signal processing techniques that enhance the sensor's ability to distinguish between the target analyte and other substances. So, to validate the fact that our electrochemical sensor could be used in complex media, it must be tested under realistic conditions that mimic the actual sample environment. Interference studies simulate these conditions by introducing potential interferents that may be present in real samples. To evaluate the selectivity of our method, an interference study was conducted using various electrochemically active molecules at physiological concentrations including ascorbic acid (AA), uric acid (UA), xylose (Xyl), fructose (Fru), and galactose (Gal) (Fig. 4B). The results clearly show that even when the concentration of interfering species was three times higher than that of glucose, the glucose signal remained unaffected, and no measurable current was observed for the interfering compounds. This indicates that our method is suitable for detecting glucose in real samples. This excellent anti-interference capability can be attributed to the unique surface chemistry and high selectivity of B-CNWs, which enhance glucose oxidation while minimising interference from common species. The case of galactose is particularly interesting as it is an isomer (epimer) of glucose, sharing the same molecular weight but differing in chemical structure, specifically the orientation of the hydroxyl group (-OH). The specificity of glucose detection in enzyme-free sensors, as compared to galactose, is influenced by several key factors, particularly the electrode surface chemistry. For example, metal-based catalysts such as Ni(OH)₂/NiOOH or CuO, along with carbon materials, play a crucial role in selectively oxidising glucose at specific potentials [4]. Glucose and galactose have different oxidation potentials, which results in the preferential detection of glucose. Moreover, while both glucose and galactose are aldohexoses, they differ in molecular structure due to C4 epimerism, which leads to distinct oxidation pathways. Glucose typically exhibits more favourable oxidation kinetics due to its structure. Additionally, the electro-oxidation of glucose produces intermediates that are generally more stable and easier to detect than those of galactose. So, by carefully tuning the applied voltage during the CV and CA experiments, glucose can be selectively oxidised, minimising the response from galactose or other compounds with different oxidation potentials. This allows for better discrimination between glucose and galactose or any other compounds, either through peak current or potential shifts. Moreover, it is well known that the pH of the electrolyte influences the oxidation efficiency. Glucose oxidation tends to be more efficient in alkaline media, while galactose oxidation is less favourable under the same conditions. In our study, we used an alkaline solution, where these factors collectively enable high specificity for glucose over galactose and other interfering compounds.

As mentioned in the introduction, non-enzymatic EC methods have been previously described by our group and others worldwide. Our EC method demonstrates competitive performance compared to those listed in Table 1. However, further improvements could be achieved by exploring different doping levels and/or by combining B-CNWs with metal particles, such as gold, to enhance the electrical conductivity and thus directly improve the electrochemical performance.

The first MS analysis of products generated by redox reactions was demonstrated by Bruckenstein and Gabbe in 1971 [29]. They utilised a Teflon-based membrane positioned between a platinum-based porous working electrode and the ionisation chamber of a mass spectrometer. This setup allowed volatile compounds produced during the reactions to pass through the Teflon membrane and subsequently be ionised by

<table><caption>**Table 1**
Some examples of electrochemical non-enzymatic detection of glucose.</caption><thead><tr><th></th><th>Linear range (mM)</th><th>Sensitivity µA µM<sup>-1</sup> cm<sup>-2</sup></th><th>LOD µM</th><th>References</th></tr></thead><tbody><tr><td>CNWs</td><td>0.01–0.55</td><td>0.065</td><td>10</td><td>This work</td></tr><tr><td>rGO/Cu NPs</td><td>0.01–0.12</td><td>0.44</td><td>3.4</td><td>[26]</td></tr><tr><td>BD diamond nanowires</td><td>0.06–8</td><td>5</td><td>60</td><td>[9]</td></tr><tr><td>Cu NPs on CVD graphene</td><td>0.02–0.23</td><td>0.379</td><td>1.39</td><td>[27]</td></tr><tr><td>Fc-ECG/Cu NPs/GE</td><td>0.40–2.3</td><td>0.217</td><td>130</td><td>[6]</td></tr><tr><td>AuNPs@CuO NWs/ Cu2O/CF</td><td>0.0028–2</td><td>1.619</td><td>0.9</td><td>[28]</td></tr><tr><td>SALDI-MS method on CNWs</td><td>0.01–0.8</td><td>3658 (a.u.)</td><td>0.7</td><td>[13]</td></tr></tbody></table>

electron impact (EI), followed by mass spectrometry detection [29]. Since then, there has been increasing interest in combining EC and MS techniques. This powerful analytical tool allows researchers to gain a deeper understanding of electrochemical reaction mechanisms and to better identify compounds and by-products generated by redox reactions. This combination helps to distinguish EC signals from those caused by interfering compounds in complex samples, which is a significant challenge in bioanalytical applications. Additionally, electrochemistry can enhance the ionisation of analytes (e.g., through cationisation) or modify thiol-containing biomolecules, such as proteins and peptides (e.g., via thiol protection), to improve MS signals. MS serves as an ultrasensitive analytical tool, providing detailed information about the molecular weight and structural composition of analytes. Introduced in 1984 by Wolter and Heitbaum, the differential electrochemical mass spectrometry (DEMS) method has demonstrated the first real-time MS detection of electrochemically generated volatiles in an online configuration, with a response time of less than 1 s [30]. However, the ionisation methods applied in EC are still based on an electrospray ionisation (ESI) source, which remains the most widely used. Indeed, ESI is prevalent in many applications, including the study of electrochemical reactions (e.g., reduction/oxidation of compounds, polymerisation by oxidation) and metabolic pathway analysis through EC-based protein cleavage, which mimics tryptic digestion for MS proteomics studies. Here, for the first time, we present the combination of the EC and LDI methods for the detection of glucose and the product of its electro-oxidation in an off-line configuration using B-CNWs in a bimodal mode, EC and MS.

In this study, the electro-oxidation of glucose was performed under alkaline conditions (NaOH). Therefore, we first aimed to determine if these conditions were compatible with the LDI-MS experimental conditions. To assess this, various salts and sodium hydroxide were tested for glucose detection by LDI-MS. The best signal was obtained with NaCl (data not shown). It is well known that glucose is more effectively detected by MS in its cationised form, particularly with a sodium adduct. Our study demonstrated that, while NaOH can facilitate glucose cationisation, it produces a lower intensity signal compared to NaCl due to its lower ionicity. In addition, no peaks corresponding to glucose or its cationised form were detected in the presence of LiCl and KCl. Thus, despite the compatibility of NaOH with LDI-MS experiments, we chose to use NaCl prior to LDI-MS to enhance the sensitivity of the detection, for the optimal MS signals.

The electro-oxidation product of Glc into GlcA was first analysed using MS. Fig. 5A shows the MS spectra of GlcA, tested in water and in the presence of 10 mM NaCl. We can see that the intensity of the primary peak at 218 m/z, which is assigned to [GlcA + Na]⁺, remained unchanged, while the peak at 241 m/z, which is assigned to [GlcA +2Na]⁺, strongly increased in the presence of NaCl, with a maximum of the signal intensity reached for 30 % of laser fluence (Fig. 5B). This increase occurred because the presence of additional Na⁺ ions in the solution enhanced the peak at 241 m/z more than twofold, due to the formation
<figure><img src="image_7.png" /><figcaption>Fig. 5. (A) SALDI-MS spectra of 600 µM GlcA in water and in 10 mM NaCl. and (B) representation of MS intensities relative to laser fluence in both water and 10 mM NaCl, using the B-CNW 1.2K SALDI-MS substrate. The insert of (A) shows [GlcA + Na]$^+$ at same intensity for both water and NaCl.</figcaption></figure>

of the sodium adduct of gluconate. Additionally, gluconate is known to complex with metal cations in alkaline solutions. Since gluconic acid is a weak acid, it partially dissociates in solution, with both associated and dissociated species present.

In alkaline solutions, Glc can undergo auto-oxidation, converting it into GlcA. Therefore, peaks corresponding to GlcA are expected in NaOH glucose solutions. As shown in Fig. 6A, the mass spectrum of Glc in NaOH solution exhibits two peaks: one at *m/z* 203, assigned to [Glc + Na]$^+$ and with a higher intensity, and the other at *m/z* 241, assigned to [GlcA+2Na]$^+$, as previously mentioned. This confirms the presence of

GlcA at low levels in the glucose solution. Fig. 6B shows the mass spectrum obtained after the electro-oxidation of Glc on B-CNWs, revealing two peaks at 197 *m/z* and 241 *m/z*, corresponding to [GlcA + H]$^+$ and [GlcA-H+2Na]$^+$, respectively. It has to be noted that no peak at 203 *m/z* [Glc + Na]$^+$ was detected. In Fig. 6C, the MS spectrum of GlcA shows three main peaks: at 197 *m/z* [GlcA + H]$^+$, 218 *m/z* [GlcA + Na]$^+$, and 241 *m/z* [GlcA-H+2Na]$^+$.

To the best of our knowledge, there is only one example demonstrating the non-enzymatic catalysis of glucose to gluconic acid combined with SALDI-MS. In this example, porous silicon decorated with gold particles was used to promote the electro-oxidation of glucose into gluconic acid, which was then detected by matrix-free LDI-MS. Peaks corresponding to gluconic ions [GlcA-H]$^-$ at 196 *m/z* and 393 *m/z* were observed [31]. However, these two peaks might also correspond to Au$_1$ and Au$_2$ clusters. Our approach, which combines EC and SALDI-MS using B-CNWs, offers significant advantages over the individual use of B-CNWs for EC or MS alone. For instance, when two compounds have very similar electrochemical oxidation potentials, mass spectrometry can differentiate them based on their molecular masses and even structural characteristics. Conversely, when two compounds share a very similar or identical molecular weights, such as isomers, EC can help distinguish them based on their oxidation potential, as seen in the case of Glc and Gal.

4. Conclusion

In this study, we have demonstrated for the first time that B-CNWs can be effectively utilised as a working electrode for the non-enzymatic electrochemical detection of glucose. This represents a significant advancement in glucose sensing technology, leveraging the unique properties of B-CNWs. Our findings indicate that the activation of B-CNWs through polarisation at 1.1 V in NaOH for 60 min is crucial for achieving an optimal response time and sensitivity in glucose detection. This process enhances the electrochemical properties of B-CNWs, making them more reactive and efficient for glucose oxidation. Through rigorous testing, we established a robust linear dynamic range for glucose concentrations, although the specific range values need to be inserted (10–550 µM). Additionally, we determined a LoD for glucose that is comparable to other advanced carbon-based systems. This highlights the potential of B-CNWs to compete with existing glucose detection technologies in terms of sensitivity and accuracy. Moreover, our study revealed that B-CNWs exhibit excellent selectivity for glucose when tested against various interfering compounds, including galactose, a glucose isomer. This selectivity is a critical feature for practical glucose sensing applications, ensuring accurate measurements. In addition, we demonstrated that B-CNWs could be directly applied to the detection of

<figure><img src="image_8.png" /><figcaption>Fig. 6. MS spectra of Glucose before electro-oxidation (A, red spectrum) and after electro-oxidation of Glucose (B, blue spectrum) and MS spectrum of Gluconic acid (C, green spectrum) in NaOH (100 mM), using B-CNWs as EC-MS dual surface with [GlcA + H]$^+$ at 197 *m/z*, [Glc + Na]$^+$ at 203 *m/z*, [GlcA + Na]$^+$ at 218 *m/z*, and [GlcA-H+2Na]$^+$ at 241 *m/z*.</figcaption></figure>
gluconic acid, the oxidation product of glucose, using mass spectrometry in an off-line configuration. This novel application involves the first-ever combination of EC and SALDI-MS detection using the same nanomaterial in a bimodal configuration. This innovative approach combines the strengths of both electrochemistry and mass spectrometry, providing a powerful analytical tool for the detection, identification, and understanding of a wide range of chemical compounds and processes. The potential applications of our findings extend beyond glucose sensing. Given that B-CNWs have been previously utilised as anodes in lithium-ion batteries, our approach could be valuable for evaluating processes that limit battery lifetime [32]. For instance, the combination of EC and MS in an operando electrochemical mass spectrometry (OEMS) configuration has been shown to identify side reactions during battery cycling with high selectivity and sensitivity [33]. This capability could lead to improved battery designs and longer battery lifetimes by providing deeper insights into the electrochemical processes occurring within the battery. Finally, our study not only introduces B-CNWs as a novel and effective material for non-enzymatic glucose detection but also shows their versatility in various electrochemical and mass spectrometry applications. The combination of the EC and MS techniques using B-CNWs opens up new avenues for advanced analytical applications, from biomedical and environmental sensing to battery research, underscoring the broad potential and impact of this innovative approach.

## Author contributions

Conceptualisation, Y.C., R.B. and I.S.H.; Methodology, Y.C., R.B. and I.S.H.; Investigation, I.S.H., M.F., M.S.; Project Administration, Y.C., I.S.H., M.F., R.B.; Supervision, Y.C. and R.C.; Validation, M.F.; Visualisation, M.S., M.F. and I.S.H., Writing—original draft preparation, Y.C. and I.S.H.; Writing—review and editing, R.C., Y.C., I.S.H., M.F., M.S.; All authors have read and agreed to the published version of the manuscript.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

We gratefully acknowledge the financial support from the Centre National de la Recherche Scientifique (CNRS), the University of Lille, the Hauts-de-France region, and the CPER "Photonics for Society" program in France. I.S.H. thanks the University of Lille and the Direction générale de l'armement (DGA, France) for PhD funding. We also extend our appreciation to the Renatech⁺ Network (France) and the CMNF platform of the IEMN laboratory for their excellent support and technical assistance. M. Ficek acknowledges the funding from the National Science Centre, Poland, under the OPUS call in the Weave program (Project number: 2021/43/I/ST7/03205; GACR project no.23–04322L). This work was further supported by a grant of the Ministry of Research, Innovation and Digitization, CCCDI – UEFISCDI (Romania), project number PN-IV-P7-7.1-PED-2024-1966, within PNCDI IV. I.S.H and Y.C are grateful to Dr. Oleg Melnyk and Hervé Drobecq from the Centre d'Infection et d'Immunité de Lille (CIIL) for providing access to their mass spectrometer and for their technical assistance.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.mtnano.2025.100635.

## Data availability

Data will be made available on request.

## References

[1] J. Madden, C. Barrett, F.R. Laffir, M. Thompson, P. Galvin, A. O'Riordan, On-Chip glucose detection based on glucose oxidase immobilized on a platinum-modified, gold microband electrode, Biosensors 11 (2021) 249.

[2] K. Dhara, D.R. Mahapatra, Electrochemical nonenzymatic sensing of glucose using advanced nanomaterials, Microchim. Acta 185 (2018) 49.

[3] M. Adeel, K. Asif, M.M. Rahman, S. Daniele, V. Canzonieri, F. Rizzolino, Glucose detection devices and methods based on metal-organic frameworks and related materials, Adv. Funct. Mater. 31 (2021) 2106023.

[4] I.G. Casella, A. Destradis, E. Desimoni, Colloidal gold supported onto glassy carbon substrates as an amperometric sensor for carbohydrates in flow injection and liquid chromatography, Analyst 121 (1996) 249–254.

[5] N. Wongkaew, M. Simsek, C. Griesche, A.J. Baeumner, Functional nanomaterials and nanostructures enhancing electrochemical biosensors and lab-on-a-chip performances: recent progress, applications, and future perspective, Chem. Rev. 119 (2018) 120–194.

[6] T. Zhan, X.Z. Feng, Q.Q. An, S. Li, M. Xue, Z. Chen, G.C. Han, H.B. Kraatz, Enzyme-free glucose sensors with efficient synergistic electro-catalysis based on a ferrocene derivative and two metal nanoparticles, RSC Adv. 12 (2022) 5072–5079.

[7] N. Yang, W. Smirnov, C.E. Nebel, Three-dimensional electrochemical reactions on tip-coated diamond nanowires with nickel nanoparticles, Electrochem. Commun. 27 (2013) 89–91.

[8] D. Luo, L. Wu, J. Zhi, Fabrication of boron-doped diamond nanorod forest electrodes and their application in nonenzymatic amperometric glucose biosensing, ACS Nano 3 (2009) 2121–2128.

[9] Q. Wang, P. Subramanian, M. Li, W.S. Yeap, K. Haenen, Y. Coffinier, R. Boukherroub, S. Szunerits, Non-enzymatic glucose sensing on long and short diamond nanowire electrodes, Electrochem. Commun. 34 (2013) 286–290.

[10] S. Sain, M. Ficek, A. Olejnik, M. Sawczak, R. Bogdanowicz, S.S. Ray, Direct determination of paraquat herbicide by square-wave voltammetry by two-step transfer mechanism at heterogeneous boron-doped carbon nanowall electrodes, Diam. Relat. Mater. 140 (2023) 110504, https://doi.org/10.1016/j.diamond.2023.110504.

[11] M. Kowalski, M. Brodowski, K. Dziabowska, M. Skwarecka, M. Ficek, D. Nidzworski, R. Bogdanowicz, Electrochemical detection of plant pathogens using boron-doped carbon nanowalls immunosensor, IEEE Sens. J. 22 (2022) 7562, https://doi.org/10.1109/JSEN.2022.3157037.

[12] M. Brodowski, M. Kowalski, M. Skwarecka, K. Pałka, M. Skowicki, A. Kula, T. Lipiński, A. Dettlaff, M. Ficek, J. Ryl, K. Dziabowska, D. Nidzworski, R. Bogdanowicz, Highly selective impedimetric determination of Haemophilus influenzae protein D using maze-like boron-doped carbon nanowall electrodes, Talanta 221 (2021) 121623, https://doi.org/10.1016/j.talanta.2020.121623.

[13] I.S. Hosu, M. Sobaszek, M. Ficek, R. Bogdanowicz, H. Drobecq, O. Melnyk, A. Barras, R. Boukherroub, Y. Coffinier, Carbon nanowalls, a new versatile carbon based interfaces for laser desorption/ionization-mass spectrometry detection of small compounds in real samples, Nanoscale 9 (2017) 9701–9715.

[14] I.S. Hosu, M. Sobaszek, M. Ficek, R. Bogdanowicz, Y. Coffinier, Boron-doped carbon nanowalls for fast and direct detection of cytochrome C and ricin by matrix-free laser desorption/ionization mass spectrometry, Talanta 252 (2023).

[15] S. Mori, T. Ueno, M. Suzuki, Synthesis of carbon nanowalls by plasma-enhanced chemical vapor deposition in a CO/H2 microwave discharge system, Diam. Relat. Mater. 20 (2011) 1129–1132.

[16] M. Sobaszek, K. Siuzdak, J. Ryl, M. Sawczak, S. Gupta, S.B. Carrizosa, M. Ficek, B. Dec, K. Darowicki, R. Bogdanowicz, Diamond phase (sp3-C) rich boron-doped carbon nanowalls (sp2-C): physicochemical and electrochemical properties, J. Phys. Chem. C 121 (2017) 20821–20833.

[17] T. Itoh, S. Shimabukuro, S. Kawamura, S. Nonomura, Preparation and electron field emission of carbon nanowall by Cat-CVD, Thin Solid Films 501 (2006) 314–317.

[18] M. Taniguchi, R. Yoshie, K. Akikubo, A. Tateno, K. Hotozuka, N. Kawaguchi, T. Uchida, M. Tanimura, M. Tachibana, Effect on nitrogen and iron in carbon nanowalls on oxygen reduxtion reaction, Electrochem. Acta 306 (2019) 132–149, https://doi.org/10.1016/j.electacta.2019.03.088.

[19] P. Slobodian, U. Cvelbar, P. Riha, R. Olejnik, J. Matyas, G. Flilipic, H. Watanabe, S. Tajima, H. Kondo, M. Sekine, M. Mori, High sensitivity of a carbon nanowall-based sensor for detection of organic vapours, RSC Adv. 5 (2015) 90515–90520, https://doi.org/10.1039/C5RA12000D.

[20] J.R. Miller, R.A. Outlaw, B.C. Holloway, Graphene double-layer capacitor with ac line-filtering performance, Science 329 (2010) 1637–1639, https://doi.org/10.1126/science.1194372.

[21] O. Tanaike, N. Kitada, H. Yoshimura, H. Hatori, K. Kojima, M. Tachibana, Lithium insertion behavior of carbon nanowalls by dc plasma CVD and its heat-treatment effect, Solid State Ionics 180 (2009) 381–385, https://doi.org/10.1016/J.SSI.2009.01.012.

[22] Z. González, S. Vizireanu, G. Dinescu, C. Blanco, R. Santamaría, Carbon nanowalls thin films as nanostructured electrode materials in vanadium redox flow batteries, Nano Energy 1 (2012) 833–839, https://doi.org/10.1016/j.janoen.2012.07.003.
[23] Y.E. Silina, D.A. Volmer, Nanostructured solid substrates for efficient laser desorption/ionization mass spectrometry (LDI-MS) of low molecular weight compounds, *Analyst* **138** (2013) 7053–7065.

[24] J.A. Stolee, B.N. Walker, V. Zorba, R.E. Russo, A. Vertes, Laser-nanostructure interactions for ion production, *Phys. Chem. Chem. Phys.* **14** (2012) 8453–8471.

[25] S. Yamada, K. Tanabe, Y. Ieda, T. Suzuki, H. Sobue, T. Itoh, S. Nonomura, Changes in wettability of carbon nanowalls by oxygen plasma treatment, *Jpn. J. Appl. Phys.* **59** (2019) SAAB05, https://doi.org/10.7567/1347-4065/ab43b5.

[26] Q. Wang, Q. Wang, M. Li, S. Szunerits, R. Boukherroub, Preparation of reduced graphene oxide/Cu nanoparticle composites through electrophoretic deposition: application for nonenzymatic glucose sensing, *RSC Adv.* **21** (2015) 15861–15869, https://doi.org/10.1039/C4RA14132F.

[27] S. Wang, L. Zhao, R. Xu, Y. Ma, L. Ma, Facile fabrication of biosensors based on Cu nanoparticles modified as-grown CVD graphene for non-enzymatic glucose sensing, *J. of Electroanalytical chemistry* **853** (2019) 113527, https://doi.org/10.1016/j.jelechem.2019.113527.

[28] Z. Zhao, Q. Li, Y. Sun, C. Zhao, Z. Guo, W. Gong, J. Hu, Y. Chen, Highly sensitive and portable electrochemical detection system based on AnNPs@CuO NWs/Cu₂O/

CF hierarchical nanostructures for enzymless glucose sensing, *Sensor. Actuator. B Chem.* **345** (2021) 130379, https://doi.org/10.1016/j.snb.2021.130379.

[29] S. Bruckenstein, R.R. Gabbe, Use of porous electrode for in situ mass spectrometric determination of volatile electrode reaction products, *J. Am. Chem. Soc.* **93** (1971) 793–794, https://doi.org/10.1021/ja00732a049.

[30] O. Wolter, J. Heitbaum, Differential electrochemical mass spectroscopy (DEMS) – a new method for the study of electrode processes, method has demonstrated the first real-time, Ber. Bunsenges. Phys. Chem. **88** (1984) 2–6, https://doi.org/10.1002/bbpc.19840880103.

[31] C.W. Tsao, Z.J. Yang, High sensitivity and high detection specificity of gold-nanoparticle-grafted nanostructured silicon mass spectrometry for glucose analysis, *ACS Appl. Mater. Interfaces* **7** (2015) 22630–22637, https://doi.org/10.1021/acsami.5b07395.

[32] K. Kim, C.Y. Bon, J. Kim, J.M. Ko, W. Choi, Carbon nanowalls as anode materials with improved performance using carbon nanofibers, *Nanomaterials* **13** (2023) 2622.

[33] C. Misiewics, R. Lundström, I. Ahmed, M.J. Lacey, W.R. Brant, E.J. Berg, Online electrochemical mass spectrometry on large-format Li-ion cells, *J. Power Sources* **554** (2023) 232318, https://doi.org/10.1016/j.jpowsour.2022.232318.