Effect of Ammonium Chloride Electrolyte on the Performance of Graphene Nano Sheets Electrode

1. Introduction

Batteries are electrochemical devices that store electrical energy in chemical form, which can later be converted back into electrical energy to generate an electric current. In daily life, two main types of batteries are commonly used: primary batteries and secondary batteries. A primary battery typically consists of three essential components: a carbon rod as the cathode (positive terminal), zinc (Zn) as the anode (negative terminal), and a paste electrolyte [1,2]. The main drawbacks of primary batteries include their limited lifespan and low electrical conductivity. One approach to address these issues involves the use of graphitic carbon-based materials (C-π), such as graphene, in combination with suitable electrolytes to enhance the efficiency of the electrochemical system [3,4,5].

Graphene is a two-dimensional carbon material with an sp² hybridized structure, forming a flat hexagonal lattice. It possesses exceptional electrical and thermal conductivity [6]. Due to its outstanding properties—such as catalytic activity [7], ultrathin structure (0.335 nm thickness), mechanical strength due to van der Waals bonding, and a high specific surface area of approximately 2630 m²/g—graphene is widely explored for applications in battery electrodes, supercapacitors, and sensors [8,9,10]. These advantages make graphene a primary target for large-scale production [11,12,13]. However, large-scale production of graphene remains challenging due to limitations in raw material availability and insufficient understanding of optimal production techniques. Most existing production methods rely on graphite as the primary raw material. Several studies have proposed biomass-derived precursors containing cellulose compounds, such as coconut shell [14,15,16], candlenut (Aleurites moluccana) shells [17,18], corn waste [19], and dead leaf biomass [20]. They can be converted into graphene via pyrolysis, producing large-scale graphene.

On the other hand, electrolytes play a vital role in ensuring the stability and performance of electrodes in battery systems. Electrolytes are substances that can conduct electric current and are classified into two categories: liquid and solid electrolytes [21,22,23,24]. Liquid electrolytes such as ammonium chloride (NH₄Cl) offer several advantages, including low cost, high ionic conductivity, low toxicity, and enhanced safety [25,26,27]. The electrochemical behavior of zinc electrodes in aqueous NH₄Cl solutions of various concentrations without additives, focusing on their protective effects, was investigated [28]. Other research revealed that the concentration of Cl⁻ and NH₄⁺ ions significantly influences the electrochemical behavior of zinc electrodes and highlighted the importance of optimizing NH₄Cl concentration to support efficient ion transport; excessively high concentrations may reduce ion mobility due to increased solution viscosity, whereas lower concentrations allow freer ion movement, thereby increasing conductivity. Interestingly, a concentration of approximately 1 M NH₄Cl in graphene-based systems resulted in optimal electrochemical performance, with pore structures that facilitate faster and more efficient ion transport [29].

In response to the growing demand for environmentally friendly energy solutions, the utilization of biomass-derived graphene, such as that from candlenut shells, represents a promising and sustainable strategy. Siburian et al.l reported that graphene synthesized from candlenut shells through pyrolysis at 600 °C demonstrated a current density of up to 1016 A/cm². However, previous combinations of Graphene Nano Sheets (GNS) and electrolyte exhibited limitations in homogeneity, which hindered the effectiveness of electrical conductivity testing [30]. Based on these issues, the present study aims to improve the homogeneity of GNS and electrolyte mixtures by processing them into paste form. Although biomass-derived graphene has demonstrated considerable potential as a sustainable electrode material, the influence of electrolyte composition on its electrical and electrochemical behavior remains insufficiently understood. NH₄Cl is an attractive electrolyte owing to its low cost, environmental friendliness, and high ionic conductivity. However, the effect of NH₄Cl concentration on the electrical conductivity, power density, and energy density of biomass-derived graphene nanosheets has not been systematically investigated, as shown in Figure 1(d). Understanding this relationship is essential for optimizing ion transport and maximizing electrode performance. Therefore, this study investigates the effect of NH₄Cl electrolyte concentration on the structural characteristics and electrical performance of graphene nanosheets synthesized from candlenut shell biomass.

Therefore, this research investigates the effect of NH₄Cl electrolyte on the performance of GNS electrodes derived from candlenut shells (Aleurites moluccana (L.) Willd) as potential cathodes in primary batteries. It is expected that this study will contribute to the development of graphene as a superior material for primary batteries and supercapacitor applications. Finally, this research may be expected to analyze the effect of ammonium chloride (NH₄Cl) electrolyte concentration on GNS-based electrodes used as cathodes in primary batteries and to evaluate the electrical conductivity, power density, and energy density of the NH₄Cl/GNS system at various NH₄Cl electrolyte concentrations in paste form.

2. Materials and Methods

2.1. Production of Candlenut Shell Charcoal

First, we produced the charcoal from candlenut shell as a raw material Aleurites moluccana (L.) Willd.. One kilogram of cleaned candlenut shells was sun-dried and oven-dried at 105 °C for 24 hours. The dried biomass was carbonized at 600 °C for 4 hours to yield charcoal chips.

2.2. Synthesis of Graphene Nano Sheets (GNS)

Charcoal was brushed to remove ash, mixed with activated carbon (1: 1 weight ratio), and pyrolyzed at 700 °C for 1 hour. The resulting GNS was washed, dried, ground, and sieved. [31]. Approximately 680 grams of GNS were obtained.

2.3. Preparation of NH₄Cl Electrolyte Solutions

Each of 0.2675, 0.535, 1.07, and 1.605 g NH₄Cl dissolved in 10 mL water to produce the series of concentrations was labeled as 0.5, 1.0, 2.0, and 3.0 M NH₄Cl solutions, respectively.

2.4. Preparation of Active Materials

For each concentration, 0.3 g of GNS was mixed with 10 mL NH₄Cl solution, stirred for 2 hours, filtered, and dried at 105 °C for 2 hours. This process yielded G-N x (x= 0.5 M, 1.0 M, 2.0 M, and 3M) active powders.

2.5. Electrode Preparation

The working electrodes were prepared by mixing the active material, PVDF, and Super P in a mass ratio of 8:1:1. PVDF was dissolved in N-methyl-2-pyrrolidone (NMP), followed by the addition of Super P and the active material to form a homogeneous slurry. The slurry was coated onto a graphite sheet (1 × 1 cm²) and dried in a vacuum oven at 90 °C overnight before electrochemical testing.

2.6. Characterization

2.6.1. X-Ray Diffraction (XRD)

X-ray diffraction (XRD) analysis was carried out using a Cu Kα radiation source (λ = 1.5406 Å) operated at 40 kV with a monochromator system (Rigaku Corporation, Japan). The measurements were performed using a beam size of 10 mm × 10 mm. The diffraction patterns were recorded over a 2θ range of 20°–90° with a scanning step of 2.0°.

2.6.2. Scanning Electron Microscopy with an Energy-Dispersive X-Ray Spectroscopy (SEM-EDX)

The morphology and microstructure of the samples were examined using SEM-EDX system (JEOL JSM-7600F, Japan). The EDX measurements were conducted at an accelerating voltage of 20 kV, while SEM imaging was performed at 5 kV.

2.6.3. Brunauer–Emmett–Teller (BET)

The specific surface area and pore characteristics of the samples were determined by N₂ adsorption–desorption measurements using a Quantachrome NOVA Surface Area Analyzer. Prior to analysis, the samples were degassed at 250 °C for 3 h under vacuum. The adsorption–desorption isotherms were recorded at 77.35 K, and the specific surface area was calculated using the Brunauer–Emmett–Teller (BET) method, while the pore size distribution was determined using the Barrett–Joyner–Halenda (BJH) method.

2.6.4. Electrical Conductivity Testing

Electrical conductivity analysis was carried out for each sample using a fuse tube (length = 2.3 cm; diameter = 0.3 cm) filled with the prepared material (mass = 0.15 g). The measurement system consisted of a DC power supply (CODY 3005DT) connected to a digital multimeter (ZOTEK ZT98) to record the electrical response of the samples, following previously reported procedures [3]. The applied voltages were set at 0.5 V, 1.0 V, and 1.5 V, and the resulting current was recorded at different time intervals.

The electrical conductivity (σ) was determined based on the relationship between current, voltage, and the geometric dimensions of the sample. The conductivity can be expressed as:

$$\mathsf{\sigma }={\displaystyle \frac{\mathrm{I}\mathrm{x}\mathrm{l}}{\mathrm{V}\mathrm{x}\mathrm{A}}}$$

(1)

where σ is the electrical conductivity (S·cm⁻¹), I is the measured current (A), V is the applied voltage (V), L is the length of the sample (cm), and A is the cross-sectional area of the tube (cm²). This equation is derived from the fundamental relationship between resistance and resistivity, where conductivity is the inverse of resistivity [32].

In addition to conductivity, the electrochemical performance of the samples was evaluated in terms of energy density and power density. The energy density (ED) represents the amount of energy stored per unit mass and was calculated using:

$$\mathrm{E}\mathrm{D}={\displaystyle \frac{\mathrm{V}\mathrm{x}\mathrm{I}\mathrm{x}\mathrm{t}}{\mathrm{m}}}$$

(2)

where V is the applied voltage (V), I is the current (A), t is the discharge time (hour), and m is the mass of the active material (kg) [33].

Meanwhile, the power density (PD), which indicates the rate at which energy can be delivered, was calculated using:

$$\mathrm{P}\mathrm{D}={\displaystyle \frac{\mathrm{V}\mathrm{x}\mathrm{I}}{\mathrm{m}}}$$

(3)

where V is the applied voltage (V), I is the current (A), and m is the mass of the active material (kg) [34].

2.6.5. Electrochemical Characterization

Electrochemical measurements were carried out using a CorrTest electrochemical workstation in a three-electrode system with the prepared electrode as the working electrode, Ag/AgCl as the reference electrode, platinum (Pt) as the counter electrode, and 6 M KOH as the electrolyte. Cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) measurements were performed to evaluate the electrochemical performance of the prepared electrodes.

2.7. Bibliometric Analysis

A bibliometric analysis was conducted to evaluate the research landscape of graphene-based electrochemical systems using data retrieved from the Scopus database. The search query TITLE-ABS-KEY (graphene AND electrode AND electrolyte AND “electrochemical performance”) was applied, limited to publications from 2020 to 2025, yielding 962 documents. The data were exported in CSV format and analyzed using VOSviewer software through a keyword co-occurrence approach. A minimum occurrence threshold of 30 was applied to identify relevant keywords, followed by manual refinement to remove irrelevant and duplicate terms, resulting in 55 representative keywords grouped into clusters. Network and overlay visualizations were generated to examine keyword relationships and temporal research trends, while additional analyses, including publication trends, document types, and geographical distribution, were performed using Scopus analytical tools.

3. Results and Discussion

We first evaluate the research trend of graphene for electrochemical applications from 2020 to 2025 to establish a comprehensive understanding of the current scientific landscape. A bibliometric analysis was conducted based on 962 publications retrieved from the Scopus database, followed by keyword co-occurrence mapping using VOSviewer. By applying a minimum occurrence threshold of 30 and subsequent manual refinement, a total of 55 representative keywords were selected and classified into five distinct clusters. The data show that the number of publications increased significantly in 2025, reaching 188 documents, with research articles representing the dominant contribution. In addition, China and India are identified as the leading countries in terms of publication output (Figure 1(a–c)).

The resulting network visualization (Figure 1 (d)) reveals that “graphene”, “electrochemical electrodes”, and “electrolytes” are the most dominant and highly interconnected keywords, indicating their central role in the research field. The strong linkage among these keywords highlights that current studies are primarily directed toward optimizing the interaction between electrode materials and electrolyte systems to achieve enhanced electrochemical performance.

A more detailed examination of the clustering structure provides insight into the main research directions. The first cluster is associated with electrochemical performance optimization, including keywords such as “electrochemical electrodes”, “electrochemistry”, and “performance”, reflecting efforts to improve efficiency and stability. The second cluster focuses on graphene-based materials and their applications, including “graphene”, “supercapacitor”, and “electrolytes”, emphasizing the dominant role of graphene in energy storage systems. The third cluster relates to material synthesis and structural characteristics, such as “reduced graphene oxide”, “carbon”, and “morphology”, indicating continuous advancements in material design and fabrication techniques. The fourth cluster highlights energy storage applications, including “energy storage”, “energy density”, and “specific capacitance”, which are critical parameters for high-performance devices. The fifth cluster represents electrochemical processes and interfacial phenomena, including “charge transfer” and “conductivity”, underscoring the importance of ion transport mechanisms in determining overall device performance. The dominance of graphene-related keywords confirms that graphene remains the core material in electrochemical energy storage research. Moreover, the strong interconnection between graphene, electrolytes, and electrochemical performance suggests that recent research trends are increasingly focused on improving electrode–electrolyte interactions as a key strategy to enhance device efficiency.

The overlay visualization (Figure 1. (e)) further provides insight into the temporal evolution of research topics. Earlier studies were primarily centered on fundamental material properties and conventional electrochemical systems, whereas more recent investigations emphasize advanced graphene-based materials, improved conductivity, and high-performance energy storage applications. Keywords associated with performance optimization and energy-related applications appear more prominently in recent years, indicating a clear transition from fundamental studies toward application-oriented and scalable technologies. This shift suggests that future research will continue to focus on improving electrochemical performance through innovative material design and advanced electrolyte engineering. In particular, the development of alternative electrolyte systems is expected to play a crucial role in advancing next-generation energy storage technologies.

Notably, keywords related to ammonium chloride (NH₄Cl) are absent from the co-occurrence network, indicating that this electrolyte system has not been widely explored in graphene-based electrochemical research. This absence highlights a significant gap in the current literature. Despite its potential advantages, such as low cost and environmental friendliness, ammonium-based electrolytes remain underutilized. Therefore, the present study focuses on investigating the effect of ammonium chloride electrolyte on the electrochemical performance of graphene nanosheets. To further validate this approach, detailed material characterization and electrochemical analyses, including X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDX), and conductivity measurements, are conducted to elucidate the structural, morphological, and electrical properties of the synthesized materials.

3.1. XRD Studies

These findings highlight that structural properties play a crucial role in determining the electrochemical performance of graphene-based materials. Therefore, to further understand the structural characteristics of the synthesized graphene nanosheets, X-ray diffraction (XRD) analysis was performed. The crystalline structure of the synthesized graphene nanosheets was investigated using XRD analysis in order to evaluate the structural ordering and layer stacking of the carbon framework [35]. XRD is a widely used technique for identifying the degree of graphitization and crystallographic arrangement in carbon-based materials, particularly for distinguishing graphitic domains from amorphous carbon structures [36,37]. The diffraction pattern provides important information regarding the interlayer spacing, stacking order, and crystallinity of graphene-derived materials, which are critical parameters influencing their electrochemical performance [38,39].

The XRD diffractogram of GNS derived from candlenut shells displayed characteristic peaks at 2θ = 25° and 44.27°, which correspond to the C (002) and C (100) planes of graphene [40]. These broad and relatively low-intensity peaks are indicative of a predominantly amorphous structure—an expected feature for graphene synthesized from biomass precursors—confirming the successful formation of graphene nanosheets [41,42]. However, the incorporation of NH₄Cl into the G–N samples gradually reduces the intensity of the (002) diffraction peak [43]. This decrease in peak intensity suggests an increase in structural disorder within the graphene layers, which is likely associated with the combined influence of NH₄⁺ and Cl⁻ ions. Based on previous studies, NH₄⁺ is proposed to preferentially interact with oxygen-containing functional groups and defect-rich edge sites, whereas Cl⁻ is believed to reduce the interlayer van der Waals interactions between adjacent graphene nanosheets, thereby suppressing excessive sheet restacking and improving the accessibility of the layered structure, as presented in Figure 2(a).

Furthermore, the G–N samples exhibit several additional diffraction peaks. For example, the G–N (0.5 M) sample shows peaks at 2θ = 22.93°, 32.73°, 40.36°, 46.94°, 52.88°, and 58.40°, corresponding to the (111), (200), (220), (311), (222), and (400) planes of crystalline NH₄Cl, respectively [44,45]. Similar diffraction features are also observed in other G–N samples, although slight shifts in peak positions are detected depending on the NH₄Cl concentration, as shown in Figure 2(b). The presence of these characteristic reflections confirms that NH₄Cl was successfully incorporated into the graphene nanosheet (GNS) matrix.

To further analyze the structural characteristics, peak deconvolution was performed to separate overlapping contributions from crystalline and amorphous phases. This approach enables a more accurate identification of the (002) peak position, which is essential for evaluating structural parameters such as interlayer spacing and crystallinity [46,47,48]. The deconvoluted XRD pattern of pristine GNS is shown in Figure 2(c), where the broad (002) peak can be resolved into multiple components corresponding to amorphous carbon and graphitic domains. The dominant broad feature indicates that the GNS structure is largely disordered with limited graphitic stacking [49,50]. Interestingly, the incorporation of NH₄Cl leads to both a reduction and a shift of the (002) diffraction peak of GNS, indicating structural distortion and strong interaction between the electrolyte and graphene framework. Notably, the (002) peak overlaps with the (111) reflection of crystalline NH₄Cl, complicating peak assignment in the composite system [51]. To address this, a magnified diffraction region centered on the (111) peak is shown in Figure 2(d), followed by peak deconvolution analysis (Figure 2(e–h)) to resolve the overlapping contributions and provide a more accurate interpretation of the structural evolution [52].

The crystallinity index (CI) was evaluated to quantify the degree of structural ordering in the GNS and G-N samples. The CI reflects the proportion of crystalline regions relative to the overall structure and is commonly used to distinguish between ordered graphitic domains and amorphous carbon phases [53]. A higher CI value indicates a more ordered and graphitic structure, whereas a lower value suggests increased structural disorder [54,55]. The crystallinity index was calculated using the following equation:

$$\mathrm{C}\mathrm{I}\left(\mathrm{\%}\right)={\displaystyle \frac{{\mathrm{A}}_{\mathrm{c}}}{{\mathrm{A}}_{\mathrm{c}}+{\mathrm{A}}_{\mathrm{A}}}}\mathrm{x}100$$

(4)

where ${\mathrm{A}}_{\mathrm{c}}$ is a crystalline area and ${\mathrm{A}}_{\mathrm{A}}$ is an amorphous area. This method enables a reliable comparative evaluation of structural ordering across all samples [56].

The crystallinity index (Figure 2(i)) was evaluated to quantify the degree of structural ordering in the graphene nanosheets after NH₄Cl incorporation. The pristine GNS exhibits a crystallinity of 80%, indicating a moderate level of graphitic ordering with the coexistence of amorphous carbon domains, which is typical for biomass-derived graphene materials [57].

Upon the addition of NH₄Cl at a concentration of 0.5 M, the crystallinity significantly decreases to 55.24%, suggesting a pronounced disruption of the graphene structure. This reduction can be attributed to the initial interaction between NH₄Cl species and the graphene framework, which likely introduces defects, disturbs π–π stacking, and increases the amorphous carbon fraction.

Interestingly, further increasing the NH₄Cl concentration to 1 M and 2 M results in a substantial increase in crystallinity to 85.73% and 86.25%, respectively. This trend indicates a reorganization of the structure, where the presence of NH₄Cl may facilitate partial ordering or contribute to the formation of crystalline domains associated with NH₄Cl phases within the composite system. The coexistence of graphitic and crystalline NH₄Cl phases likely contributes to the overall increase in the calculated crystallinity index. At the highest concentration of 3 M, the crystallinity reaches 95.46%, indicating a highly ordered structure. However, this high value does not necessarily reflect an improvement in graphene ordering alone but is more likely influenced by the dominant contribution of crystalline NH₄Cl phases, as evidenced by the increasing intensity of characteristic diffraction peaks. This suggests that the crystallinity index in composite systems must be interpreted carefully, as it represents the combined contribution of all crystalline phases present. The crystallinity evolution demonstrates a concentration-dependent behavior, where initial NH₄Cl addition induces structural disorder, followed by increased apparent crystallinity due to the growing contribution of crystalline NH₄Cl phases. This finding highlights the dual role of NH₄Cl in modifying both the structural disorder of graphene and the crystalline nature of the composite system, which may significantly influence its electrochemical properties. Therefore, the crystallinity index in this composite system reflects the combined contribution of graphene and NH₄Cl phases rather than the intrinsic ordering of graphene alone [58].

To gain deeper insight into the structural evolution after NH₄Cl impregnation, the diffraction peaks of each sample (GNS, G–N 0.5, G–N 1, G–N 2, and G–N 3) were analyzed quantitatively. The interlayer spacing (d₀₀₂) of the graphene structure was estimated from the (002) diffraction peak using Bragg’s equation:

$$d_{002}={\displaystyle \frac{\lambda }{2\mathrm{s}\mathrm{i}\mathrm{n}\theta }}$$

(5)

where λ = 1.5406 Å corresponds to the Cu Kα radiation source [59]. The calculated d₀₀₂ value represents the distance between stacked graphene layers and is widely used to evaluate the degree of graphitic ordering in carbon-based materials [60]. Variations in d₀₀₂ after NH₄Cl incorporation indicate structural distortion and possible expansion of the graphene interlayer spacing, which may arise from the intercalation or interaction of ammonium species within the carbon framework [61].

As shown in Table 1, the variation of crystallinity observed in this study is consistent with the evolution of the interlayer spacing (d₀₀₂), as presented in Figure 2(j). The pristine GNS exhibits the lowest d₀₀₂ value (3.557 Å), reflecting relatively compact layer stacking with moderate graphitic ordering. Upon NH₄Cl incorporation, a significant increase in d₀₀₂ is observed, reaching a maximum value at G–N (2.0 M) (3.858 Å), followed by G–N (3.0 M) and G–N (1.0 M). This expansion clearly indicates the insertion of NH₄⁺ and Cl⁻ ions into the interlayer region of graphene, which weakens van der Waals interactions and induces layer separation. This expansion further supports the intercalation of ionic species within the graphene layers rather than simple surface adsorption [62,63].

Interestingly, this interlayer expansion correlates with the crystallinity behavior, where an initial decrease at low concentration (0.5 M) is followed by a substantial increase at higher concentrations. The lowest crystallinity at G–N (0.5 M) can be attributed to the initial disruption of graphene stacking without sufficient formation of crystalline NH₄Cl domains. In contrast, at higher concentrations (1–3 M), the increased d₀₀₂ values suggest more effective intercalation, accompanied by the growing contribution of crystalline NH₄Cl phases, which leads to an apparent increase in the overall crystallinity index.

The structural ordering of the graphene nanosheets was evaluated through the crystallite size along the c-axis ($L_c$), which represents the stacking height of graphitic domains [64]. The $L_c$ value was estimated using the Scherrer equation:

$$L_c={\displaystyle \frac{K\lambda }{{\beta }_{002}\mathrm{c}\mathrm{o}\mathrm{s}{\theta }_{002}}}$$

(6)

where $L_c$ is the crystallite size along the c-axis (nm), K is the shape factor (typically 0.89), λ is the X-ray wavelength (commonly 0.15406 nm for Cu Kα radiation), ${\beta }_{002}$ is the full width at half maximum (FWHM) of the (002) diffraction peak (in radians), and ${\theta }_{002}$ is the Bragg diffraction angle corresponding to the (002) plane. The Scherrer equation is commonly used to estimate the average crystallite size based on peak broadening in XRD patterns, where narrower peaks indicate larger crystallite domains and improved structural ordering [65].

Further insight into the structural ordering is provided by the crystallite size ($L_c$), which reflects the stacking height of graphitic domains along the c-axis. The pristine GNS exhibits relatively low $L_c$ values, with 2.362 for the (002) plane and 2.535 for the (100) plane, indicating limited stacking and a predominantly disordered structure. Upon NH₄Cl incorporation, a significant increase in L_c is observed, rising to 65.014 for G–N (0.5 M), 76.596 for G–N (1.0 M), and reaching maximum values of 127.999 and 128.024 for G–N (2.0 M) and G–N (3.0 M), respectively [66].

This substantial increase in $L_c$ suggests the formation of larger coherent crystalline domains within the composite system. However, this increase is likely dominated by the contribution of crystalline NH₄Cl phases rather than intrinsic graphene stacking. However, similar to the crystallinity trend, this increase should not be solely attributed to improved graphene ordering but rather to the growing contribution of crystalline NH₄Cl phases, which dominate the diffraction signal at higher concentrations. The presence of these crystalline domains contributes to an apparent increase in structural ordering, while the graphene framework itself may still experience local disorder and distortion [67].

The highest d₀₀₂ value observed at G–N (2.0 M) suggests that this concentration provides the most effective intercalation of ionic species, resulting in maximum layer expansion and structural distortion [68]. This expanded and more open structure is expected to enhance ion accessibility and facilitate electrolyte penetration, which is beneficial for electrochemical applications. However, excessive incorporation at higher concentration (3.0 M) may lead to phase domination by NH₄Cl, where the increase in crystallinity and $L_c$is more influenced by the salt phase rather than intrinsic graphene ordering [69,70].

Overall, these findings demonstrate that NH₄Cl acts as a strong structural modifier, inducing interlayer expansion, increasing defect density, and transforming the graphene nanosheets into a heterogeneous composite system with both disordered carbon and crystalline salt phases [71]. The combined analysis of d₀₀₂, crystallinity index, and crystallite size ($L_c$) highlights a concentration-dependent structural evolution governed by intercalation, phase contribution, and structural reorganization.

These structural modifications provide a fundamental basis for understanding the electrochemical behavior discussed in the following sections [72]. To establish a comprehensive structure–property relationship, the structural insights obtained from XRD analysis were further complemented by SEM–EDX characterization to investigate the surface morphology and elemental distribution of the synthesized graphene nanosheets.

3.2. SEM-EDX Studies

SEM-EDX analysis was employed to investigate the surface morphology and elemental composition of GNS and G-N composites. This combined technique provides complementary information on the physical and chemical characteristics of the materials [73,74]. SEM enables detailed observation of surface features such as layer structure, porosity, and aggregation, while EDX provides quantitative analysis of elemental composition [75]. These parameters are essential for understanding the effect of NH₄Cl incorporation on the graphene framework, particularly in relation to electron transport, ion diffusion, and overall electrochemical performance [76].

The morphology of pristine GNS derived from candlenut shells exhibits a typical layered and stacked sheet-like structure with relatively smooth and continuous surfaces, as shown in Figure 3. The graphene sheets appear thin, wrinkled, and loosely stacked, forming a porous network with minimal aggregation. This morphology indicates the successful formation of multilayer graphene with a relatively open structure, which is beneficial for providing a large surface area and facilitating ion transport. The well-organized stacking also suggests good structural integrity, which is important for maintaining electrical conductivity [77,78,79].

The EDX results indicate that GNS is predominantly composed of carbon, with a minor contribution from oxygen. The high carbon content confirms the formation of a graphene-based structure, while the presence of oxygen is associated with residual oxygen-containing functional groups or slight surface oxidation during the synthesis process [80,81]. These functional groups may originate from the biomass precursor or incomplete carbonization. The absence of other elements indicates that the material has high purity, which is advantageous for maintaining efficient electron transport and minimizing unwanted side reactions [82,83]. We also provide a spectrum of EDX as shown in Figure S1.

The incorporation of NH₄Cl induces significant changes in the morphology of the graphene nanosheets. The G–N samples exhibit more irregular, distorted, and partially agglomerated sheet structures compared to pristine GNS, as shown in Figure 4. The originally well-defined layered structure becomes less uniform, indicating that the presence of NH₄Cl disrupts the stacking arrangement of graphene layers. This disruption is attributed to the interaction of NH₄⁺ and Cl⁻ ions with the graphene surface, which introduces defects and weakens interlayer interactions [84,85].

As the NH₄Cl concentration increases, the degree of structural modification becomes more pronounced. At lower concentration (0.5 M), the layered morphology is still relatively preserved, although slight roughening and distortion can be observed. At moderate concentration (1.0–2.0 M), the sheets become more wrinkled and disordered, indicating increased defect formation and structural distortion. At higher concentration (3.0 M), the graphene sheets tend to restack and form denser aggregates, likely due to excessive ionic species promoting particle–particle interaction. These morphological changes result in a more heterogeneous structure, which may enhance ion accessibility but can also reduce structural stability if excessive aggregation occurs [86].

EDX analysis (Table 2) indicates the incorporation of NH₄Cl into the graphene structure, as evidenced by the presence of chlorine in all G–N samples. The carbon content shows a slight decrease compared to pristine GNS, suggesting partial disruption of the carbon framework, while the oxygen content varies with NH₄Cl concentration, reflecting changes in surface functional groups and defect density. Chlorine content increases from 3.2% in G–N 0.5 M to 5.9% in G–N 1.0 M, then decreases at higher concentrations to 3.3% (2.0 M) and 2.0% (3.0 M), likely due to aggregation or saturation effects. This trend indicates that varying NH₄Cl concentrations affect the elemental composition and defect density of graphene, resulting in samples with distinct structural characteristics [87].

In terms of electrode performance, carbon serves as the primary conductive pathway, whereas chlorine provides additional active sites that can enhance ion interaction with the electrolyte. The balance between these elements determines the electrochemical potential of each variation. For instance, G–N (2.0 M) retains a relatively high carbon content (93.1%) while containing sufficient chlorine (3.3%), maintaining conductivity while providing active sites for ion interaction. This composition can be used as a reference to compare the effects of other NH₄Cl concentrations, where lower concentrations may provide fewer active sites and higher concentrations may introduce excessive defects that disrupt conductive pathways [88].

3.3. Brunauer–Emmett–Teller (BET) Studies

Nitrogen adsorption–desorption analysis was carried out to evaluate the effect of NH₄Cl treatment on the textural properties of graphene nanosheets. The adsorption–desorption isotherms of pristine GNS and the NH₄Cl-treated sample (G-N2) are presented in Figure 4, while the corresponding textural parameters are summarized in Table 3. Compared with GNS, the G-N2 exhibited a substantially higher nitrogen uptake over the entire relative pressure (P/P₀) range, indicating an increase in the accessible surface area and pore volume after modification. This observation demonstrates that NH₄Cl effectively promotes pore formation during the thermal treatment of biomass-derived graphene nanosheets.

Quantitative BET analysis further confirms this improvement. The specific surface area increased from 124.6 m² g⁻¹ for GNS to 307.4 m² g⁻¹ after NH₄Cl modification. Similarly, the total pore volume increased from 0.1007 cm³ g⁻¹ to 0.1949 cm³ g⁻¹, while the micropore surface area increased markedly from 102.6 m² g⁻¹ to 280.5 m² g⁻¹. The significant enhancement in these textural parameters indicates that NH₄Cl acts as an effective pore-forming agent, generating additional accessible pores throughout the carbon framework.

The average pore diameter decreased from 3.23 nm for GNS to 2.54 nm following NH₄Cl modification. Despite this reduction, both samples remain within the mesoporous region according to the IUPAC pore classification (2–50 nm). Moreover, the BJH pore size distribution (Figure 4) shows that the dominant pore diameter is centred at approximately 3.0–3.4 nm for both samples, indicating that the original mesoporous framework is largely preserved after modification. The remarkable increase in micropore surface area together with the relatively unchanged mesoporous distribution suggests that NH₄Cl predominantly generates additional microporous domains while maintaining the interconnected mesoporous channels, resulting in a hierarchical micro/mesoporous structure.

Such hierarchical porosity is highly desirable for carbon-based electrode materials because each pore regime plays a distinct role in electrochemical processes. Micropores provide abundant active sites for charge storage, whereas mesopores facilitate electrolyte infiltration and accelerate ion transport by reducing diffusion resistance. In addition, the enlarged specific surface area increases the electrode–electrolyte interfacial contact, allowing more efficient utilization of the carbon surface during electrochemical reactions. The combination of increased surface area, larger pore volume, and hierarchical pore architecture is therefore expected to contribute positively to the enhanced electrical conductivity, power density, and energy density observed for the G-N2.

The superior performance observed for the 2.0 M NH₄Cl electrolyte can be attributed to the optimum balance between ion availability and the accessible porous structure of the graphene nanosheets. Increasing the NH₄Cl concentration increases the number of mobile charge carriers within the electrolyte, thereby facilitating ion transport and reducing charge-transfer resistance at the electrode–electrolyte interface. Simultaneously, the BET results indicate that the NH₄Cl-treated graphene nanosheets possess a significantly larger specific surface area and pore volume, providing more accessible active sites for electrolyte penetration and charge storage. The combination of enhanced ionic transport and improved electrode–electrolyte interfacial contact promotes more efficient charge transfer, leading to the highest electrical conductivity, power density, and energy density at 2.0 M NH₄Cl

Overall, the BET results demonstrate that NH₄Cl modification effectively tailors the textural properties of biomass-derived graphene nanosheets by simultaneously increasing the specific surface area, pore volume, and microporous fraction while preserving the mesoporous network. These structural improvements provide a favorable porous architecture for carbon-based electrode materials and further support the potential of NH₄Cl as a simple and environmentally friendly pore-forming agent for the preparation of biomass-derived graphene.

3.4. Electrical Conductivity Analysis

Electrical conductivity reflects the ability of the electrode material to transport charge efficiently, which is strongly influenced by both electron mobility within the graphene structure and ion transport from the electrolyte [89,90]. In this study, the conductivity behavior demonstrates a clear dependence not only on the applied voltage but also on the electrolyte composition, highlighting the synergistic role of electronic and ionic contributions in the system. Increasing voltage from 0.5 V to 1.5 V consistently enhances conductivity due to the higher driving force for charge movement [91]. Moreover, the introduction of electrolyte species plays a crucial role in facilitating charge transport, as evidenced by the significant improvement in conductivity compared to pristine graphene nanosheets (GNS).

As presented in Figure 5(a–f), a substantial enhancement in electrical conductivity is observed upon NH₄Cl incorporation compared to the pristine GNS. The GNS sample exhibits relatively low conductivity (~0.05–0.09 S·cm⁻¹), whereas the addition of NH₄Cl increases conductivity significantly, reaching above 0.5 S·cm⁻¹ even at low concentration. The highest conductivity is obtained at 2.0 M NH₄Cl, with values around 1.30–1.31 S·cm⁻¹, indicating an optimal ionic environment for charge transport. This enhancement can be attributed to the presence of NH₄⁺ and Cl⁻ ions, which not only improve ionic conductivity but also facilitate the formation of continuous charge transfer pathways within the electrode–electrolyte interface. However, at higher concentration (3.0 M), the conductivity does not increase further and tends to stabilize, suggesting that excessive ionic concentration may lead to ion crowding and increased viscosity, thereby limiting ion mobility. As a result, the system reaches an optimal condition at 2.0 M, where the balance between ion availability and mobility is maximized [92,93].

The relationship between energy density and power density is illustrated in Figure 5(g–l). A consistent increase in energy density with both applied voltage and electrolyte concentration is observed, indicating enhanced charge storage capability under optimized electrochemical conditions [94,95]. Among all samples, the highest energy density is achieved at 2.0 M NH₄Cl, reaching approximately 605 Wh·kg⁻¹ at 1.5 V. This significant improvement compared to GNS and the commercial battery can be attributed to enhanced ion diffusion, improved electrical conductivity, and more efficient utilization of active sites within the graphene structure. The incorporation of NH₄Cl enhances the electrochemical activity of graphene by increasing the number of available charge carriers, resulting in better energy storage performance [96].

The power density results demonstrate a similar trend, where NH₄Cl-modified electrodes exhibit superior performance compared to GNS and the commercial battery. Notably, the optimal performance is again observed at 2.0 M NH₄Cl, where the system achieves a power density of approximately 605 W·kg⁻¹ at 1.5 V. This indicates that the system is capable of delivering energy rapidly, which is essential for high-performance energy storage devices. The improved power density is closely associated with enhanced electrical conductivity and reduced internal resistance, enabling faster charge–discharge kinetics and more efficient energy delivery [97]. However, at higher concentration (3.0 M), no significant improvement is observed, further confirming that excessive ion concentration can hinder ion mobility and limit overall electrochemical performance. Therefore, 2.0 M NH₄Cl provides the best overall performance, as it offers an optimal balance between ion transport, electrical conductivity, and electrochemical activity, resulting in simultaneously high energy density and power density [98,99,100]. All summary data were tabulated in Table S1.

3.5. Electrochemical Performance

Based on the electrical conductivity results discussed in the previous section, G–N 2 exhibited the highest electrical conductivity among all investigated samples, indicating the most efficient electron transport. Therefore, pristine graphene nanosheets (GNS) and the optimum NH₄Cl-modified sample (G–N 2) were selected for further electrochemical characterization using cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) measurements to comprehensively evaluate their charge-storage behavior and electrochemical performance.

As shown in Figure 6a,b, the CV curves of GNS and G–N 2 recorded at scan rates ranging from 10 to 50 mV s^-1 exhibit quasi-rectangular shapes with slight distortion, indicating that the charge-storage mechanism is predominantly governed by electric double-layer capacitance (EDLC) accompanied by a minor pseudocapacitive contribution. The slight deviation from an ideal rectangular profile suggests the presence of electrochemically active surface functional groups that participate in reversible faradaic reactions. Compared with pristine GNS, the G–N 2 electrode exhibits a noticeably larger enclosed CV area and higher current response over the entire scan-rate range, indicating enhanced electrochemical activity and improved charge-storage capability. This behavior is consistent with the previous electrical conductivity results, confirming that the higher conductivity of G–N 2 promotes more efficient electron transport and facilitates charge accumulation during the electrochemical process.

To quantitatively evaluate the capacitive behavior, the specific capacitance (Cₛ) was calculated using:

$$\begin{array}{cc}& C_s={\displaystyle \frac{\int I\left(V\right)dV}{m\times \mathsf{\Delta }V\times \nu }}\end{array}$$

(7)

where I(V) is the current (A), m is the mass of the active material (g), ΔV is the potential window (V), and ν is the scan rate (V s⁻¹).

As summarized in Table 4, G–N 2 exhibits a higher specific capacitance than pristine GNS over most of the investigated scan-rate range. At the lowest scan rate (10 mV s⁻¹), G–N 2 delivers the highest specific capacitance (74.85 F g⁻¹), which is approximately 35% higher than that of GNS (55.47 F g⁻¹). The higher capacitance indicates that NH₄Cl modification enhances the utilization of electrochemically active sites and improves charge-storage capability. As the scan rate increases, the specific capacitance of both electrodes gradually decreases because electrolyte ions have insufficient time to diffuse into all accessible active sites during the rapid potential sweep. Nevertheless, G–N 2 maintains superior capacitive performance throughout most of the scan-rate range, demonstrating better rate capability than pristine GNS. These results are in good agreement with the electrical conductivity analysis, where G–N 2 exhibited the highest conductivity, indicating that improved electron transport contributes directly to the enhanced electrochemical performance.

To further evaluate the practical charge-storage performance, galvanostatic charge–discharge (GCD) measurements were subsequently carried out at current densities ranging from 0.2 to 1.0 A g⁻¹. As shown in Figure 6c,d, both GNS and G–N 2 exhibit nearly symmetric triangular charge–discharge profiles, indicating highly reversible charge-storage behavior and good coulombic efficiency. Moreover, G–N 2 exhibits a noticeably longer discharge time than pristine GNS at the same current density, indicating a higher charge-storage capability. The relatively small voltage drop observed at the beginning of the discharge process further suggests low internal resistance and efficient charge transport within both electrodes.

The specific capacitance (Cₛ) was calculated from the discharge curve using:

$$\begin{array}{cc}& C_s={\displaystyle \frac{I\mathsf{\Delta }t}{m\mathsf{\Delta }V}}\end{array}$$

(7)

where I is the applied current (A), Δt is the discharge time (s), m is the mass of the active material (g), and ΔV is the potential window (V) excluding the IR drop.

The energy density (E) was calculated according to:

$$\begin{array}{cc}& E={\displaystyle \frac{1}{2}}{C}_s{\left(\mathsf{\Delta }V\right)}^2\end{array}$$

(8)

where Cₛ is the specific capacitance (F g⁻¹) and ΔV is the discharge potential window (V).

The power density (P) was determined using:

$$\begin{array}{cc}& P={\displaystyle \frac{E}{\mathsf{\Delta }t}}\end{array}$$

(9)

where E is the energy density (Wh kg⁻¹) and Δt is the discharge time (h).

As summarized in Table 5, G–N 2 consistently outperforms pristine GNS at all investigated current densities. At 0.2 A g⁻¹, G–N 2 exhibits the highest specific capacitance (202.79 F g⁻¹) and energy density (35.79 Wh kg⁻¹), representing improvements of approximately 31.8% and 37.4%, respectively, compared with pristine GNS. As the current density increases from 0.2 to 1.0 A g⁻¹, both electrodes show a gradual decrease in specific capacitance and energy density because electrolyte ions cannot fully penetrate all active sites within the shortened charge–discharge time. Nevertheless, G–N 2 maintains higher capacitance than GNS throughout the investigated current-density range, indicating superior electrochemical stability and rate capability. The enhanced electrochemical performance is consistent with the previous electrical conductivity measurements, demonstrating that the improved electrical conductivity of G–N 2 facilitates faster electron transport and more efficient charge storage during both the charging and discharging processes. We also compare the electrochemical performance with others previous work as presented in Table 6.

From an electrode performance perspective, these results clearly demonstrate that NH₄Cl electrolyte plays a dual role in enhancing both charge transport and charge storage mechanisms. The improved electrical conductivity indicates more efficient electron transfer within the graphene network, while the increased energy and power densities reflect enhanced ion diffusion and faster electrochemical kinetics at the electrode–electrolyte interface. This suggests that the electrolyte does not merely act as an ionic medium but actively modifies the electrochemical behavior of the graphene electrode [101,102].

These findings confirm that the electrochemical performance of graphene nanosheet electrodes is strongly governed by electrolyte-induced modifications, where NH₄Cl enhances conductivity, promotes ion accessibility, and improves charge storage capability. Therefore, controlling electrolyte concentration is a key strategy for optimizing graphene-based electrodes for advanced energy storage applications [29].

4. Conclusions

This study demonstrates that the incorporation of NH₄Cl electrolyte significantly influences the structural, morphological, and electrochemical properties of graphene nanosheets (GNS) derived from candlenut shells. XRD analysis confirms successful NH₄Cl integration, as indicated by the appearance of crystalline peaks, increased interlayer spacing, and reduced crystallinity, reflecting enhanced structural disorder. SEM-EDX results reveal morphological transformation from layered sheets to more distorted structures and confirm the presence of chlorine, indicating effective electrolyte incorporation and its role in modifying the graphene framework. BET analysis demonstrated that the specific surface area and total pore volume increased to 307.4 m² g⁻¹ and 0.1949 cm³ g⁻¹, respectively, indicating the development of a more accessible porous structure. The improved electrode performance is attributed to the synergistic roles of NH₄⁺ and Cl⁻ ions in enhancing electrolyte accessibility and regulating the stacking behavior of graphene nanosheets, thereby facilitating efficient charge transport.

Electrochemical results show that NH₄Cl concentration plays a key role in determining electrode performance. The G–N (2.0 M) sample exhibits the highest electrical conductivity (~1.30 S·cm⁻¹), energy density (~605 Wh·kg⁻¹), and power density (~605 W·kg⁻¹). This optimal performance is attributed to the balanced interaction between ion availability and mobility, which enhances charge transport and storage. At higher concentration (3.0 M), performance slightly decreases due to ion crowding effects. Overall, G–N (2.0 M) demonstrates strong potential as an efficient and environmentally friendly cathode material for energy storage applications.