Histamine Adsorption on Pristine and Doped Graphene for Biosensing: A First-Principles Study

Abstract

Histamine is a key immune regulator involved in allergic and inflammatory responses and is implicated in a range of immune dysregulation disorders. Reliable, continuous detection of histamine remains challenging due to its low concentrations and dynamic levels of release. In this investigation, the interaction of histamine with pristine and doped graphene monolayers, including oxygen-, boron nitride-, and silicon-doped graphene, was examined as a basis for potential biosensor materials. Density functional theory (DFT) calculations were performed to evaluate adsorption energies, defect formation energies, charge transfer, band structures, and recovery times. The results reveal that pristine graphene exhibits a weak interaction with histamine and a negligible electronic response. Silicon-doped graphene shows high sensitivity but exhibits excessively long recovery times. In contrast, graphene oxide with an oxygen concentration of 6.25% and boron nitride-doped graphene with a concentration of 12.5% display moderate adsorption energies, short recovery times, and favorable electronic responses. Notably, graphene oxide with a concentration of 6.25% exhibits band gap closure at the Fermi level following histamine adsorption. These results indicate that oxygen- and boron nitride-doped graphene monolayers with concentrations of 6.25% and 12.5%, respectively, are promising materials for histamine-sensing applications.

Introduction

Immune-mediated and inflammatory disorders impose a significant burden on patients and healthcare systems, driven by their recurrent, multisystem symptoms and diagnostic complexity that often delay effective treatment. , Among the molecular mediators underlying these conditions, histamine has been identified as a central regulator of immune signaling across a wide range of pathways. − Histamine is a biogenic amine primarily stored in mast cells and basophils that, upon release, can trigger diverse physiological effects including inflammation, pruritus, tachycardia, and hypotension. − Accordingly, the molecule has been associated with numerous conditions, including allergic rhinitis, psoriasis, systemic lupus erythematosus, and mast cell activation syndrome. ,, In addition, systemic studies have demonstrated its influence on cognition, cardiovascular regulation, and gastrointestinal function, extending its impact beyond the immune system. ,

Given the dynamic nature of histamine release and its involvement across multiple physiological systems, single-time-point measurements may not fully capture its variability. Continuous monitoring of histamine levels may therefore provide improved insight into symptom onset, severity, and diagnostic decisions. , However, existing histamine detection methods typically rely on laboratory-based techniques, such as high-performance liquid chromatography and enzyme-linked immunosorbent assay, which require costly instrumentation and lengthy processing times, ultimately limiting their applicability for continuous monitoring. These constraints motivate the development of alternative sensing platforms capable of rapid and sensitive detection.

In response to these constraints, biosensor research has progressed toward increasingly sensitive nanomaterial-based platforms capable of detecting low-abundance disease biomarkers. These advances have supported the conversion of biomolecular interactions into measurable signals, enabling more efficient monitoring strategies. Among these nanomaterials, graphene has received considerable attention due to its electronic sensitivity and high surface-to-volume ratio. As a result, graphene-based biosensors have been explored for a variety of biomedical applications, including neurological diseases. Liu et al. used density functional theory to examine molecular and graphene oxide chelators interacting with amyloid-β aggregates in Alzheimer’s disease, reporting strong adsorption behavior that highlights the potential of graphene-based materials for targeting biomolecules associated with disease. Biosensor research has also expanded beyond neurological disorders to include infectious and post-infectious conditions, such as long COVID. In this context, Zhu et al. demonstrated enhanced detection of the volatile biomarker heptanal on transition-metal-doped graphene, indicating improved sensitivity relative to pristine graphene. These studies indicate that graphene and modified graphene systems can exhibit measurable electronic responses following molecular adsorption.

Building on these studies, similar sensing approaches have been applied to immune mediators, including histamine. Early histamine biosensors largely relied on electrochemical platforms incorporating enzyme-based recognition elements to achieve selective and rapid detection. More recent work has incorporated nanomaterials to enhance signal amplification and lower detection limits, resulting in improved sensitivity compared with earlier designs. , Despite this progress, histamine biosensors continue to face challenges related to operational stability, interference from complex biological matrices, and limited capacity for time-resolved monitoring. These challenges suggest that further investigation of material–molecule interactions may be essential for optimizing sensing performance.

The unique structural and electronic characteristics of graphene are closely tied to its sensing behavior and therefore central to understanding its performance at the material level. The single-atom carbon honeycomb lattice of graphene gives rise to a distinctive atomic and band structure associated with exceptional carrier mobility, high electronic sensitivity, and a large surface-to-volume ratio. − Graphene monolayers have also been shown to exhibit reliable mechanical strength, maintaining structural integrity while under mechanical operations and stress. , Pristine graphene has a shortcoming, however, in that it has a zero band gap, which restricts its electrical conductivity upon molecular adsorption. , Additionally, first-principles studies reveal weak interactions between molecules and pristine graphene, leading to limited charge transfer, which reduces sensitivity and selectivity. − Thus, modifications to graphene’s electronic structure have been explored to improve adsorption behavior and electronic response.

Among these approaches, atomic doping has emerged as a widely adopted strategy for improving the sensing properties of graphene. Recent DFT studies have shown that various dopant configurations can effectively tailor the electronic structure of graphene, thereby enhancing adsorption behavior and sensitivity toward target molecules. , Both substitutional and interstitial doping have also previously been demonstrated to improve sensitivity and lower detection limits. In this study, silicon, boron nitride, and oxygen dopants were selected because each has been shown to modify graphene’s electronic structure and adsorption behavior in a distinct manner. Silicon doping has been reported to open the zero band gap of graphene and strengthen adsorption toward several gas molecules, including NO, NO₂, CO, O₂, and H₂O, due in part to silicon’s larger atomic radius and the resulting altered electronic environment. − Boron nitride co-doping was examined because previous studies have shown that combined boron nitrogen incorporation can more effectively modify graphene’s electronic properties near the Fermi level than single B or N doping, thereby altering its interactions with target molecules. Esrafili also reported that boron nitride co-doped graphene can be more energetically favorable than single B-doped graphene and can strengthen the adsorption, selectivity, and sensitivity of graphene toward NO and NO₂ gases. Oxygen doping was included because oxygen incorporation can alter the local electronic environment of graphene through electron localization, potentially increasing surface polarity. The increased surface polarity may enhance interactions with histamine through electrostatic effects involving histamine groups containing nitrogen, particularly the polar imidazole ring. , These dopants were therefore selected to compare how distinct modifications of graphene’s local electronic environment influence histamine adsorption and the resulting electronic response. Nonetheless, existing first-principles evaluations of histamine adsorption on specific doped graphene configurations remain limited.

In this study, the interaction of histamine with pristine graphene and several doped graphene monolayers is investigated to evaluate properties relevant to histamine sensing. First-principles calculations based on density functional theory (DFT) are employed to examine the structural and electronic characteristics of the pristine and doped graphene systems. The adsorption behavior of histamine, along with associated changes in electronic structure and charge transfer, is analyzed and compared across different graphene configurations.

Method

Computational Details

First-principles calculations were performed based on density functional theory (DFT) using the generalized gradient approximation (GGA) with Perdew–Burke–Ernzerhof (PBE) format implemented in the ABINIT package. The projected augmented wave (PAW) , method was used to generate pseudopotentials with the ATOMPAW code. The electron configuration and atomic radius for generating PAW pseudopotentials are listed for each element used in Table . The self-consistent field (SCF) total energy calculations were performed and considered converged when the total energy difference was less than 1.0 × 10^–6 hartree twice consecutively. The kinetic energy cut-off and Monkhorst–Pack k-point grid were considered converged when the total energy difference between consecutive datasets was less than 0.001 hartree twice consecutively. Structural optimization calculations were performed with the converged kinetic energy cut-off and k-point grid using the Broyden–Fletcher–Goldfarb–Shanno method. The optimization was considered converged when the maximum force difference was less than 2.0 × 10^–3 hartree/Bohr.

1. Electron Configuration and Atomic Radius of Each Element Used To Generate PAW Pseudopotentials.

atom	electron configuration	atomic radius (Bohr)
H	1s1	0.99
B	[He]2s 22p 1	1.70
C	[He]2s 22p 2	1.51
N	[He]2s 22p 3	1.20
O	[He]2s 22p 4	1.41
Si	[Ne]3s 23p 2	1.91

Atomic Structure

The histamine molecule is composed of 17 atoms: five carbon atoms, nine hydrogen atoms, and three nitrogen atoms (C₅H₉N₃), as seen in Figure (a). The coordinates for the molecule were retrieved from PubChem as an experimentally validated starting geometry.

1.

(a) Histamine atomic structure with grey indicating carbon, blue indicating nitrogen, and white indicating hydrogen. (b) Graphene 4×4 supercell atomic structure (c) Lattice vector of graphene monolayer primitive cell (d) Primitive cell in the reciprocal space with the red triangle indicating K-path Γ - K - M - Γ.

A graphene primitive cell, presented in Figure (c), was relaxed, and then expanded into a 4×4×1 graphene supercell with 32 carbon atoms. Several doped graphene monolayers were created by substituting one silicon atom, one pair of boron nitride atoms, and two pairs of boron nitride atoms. The defect formation energy (E _form ) of graphene monolayers doped by one or two boron nitride pairs or silicon is given by

$$E_{\mathit{form}}=E_{\mathrm{mL}+\mathit{dopant}}-E_{\mathit{mL}}-E_{\mathit{dopant}}+n\ast E_{\mathit{carbon}}$$ 1

Additionally, several graphene monolayers were interstitially doped with one or two oxygen atoms. The corresponding defect formation energy is given by

$$E_{\mathit{form}}=E_{\mathrm{mL}+\mathit{dopant}}-E_{\mathit{mL}}-E_{\mathit{dopant}}$$ 2

where E _mL+dopant , E _mL , E _dopant , and E _carbon represent, respectively, the total energies of the doped graphene monolayer, the pure graphene monolayer, the dopants, and the substituted carbon atom(s). The variable n represents the number of carbon atoms that were substituted out. The computational models considered pristine, substitutionally doped, and interstitially doped graphene structures and did not explicitly include vacancy defects, voids, or other lattice imperfections.

Adsorption Calculations

Histamine was placed above the pure or doped graphene monolayer to analyze its adsorption behavior. To quantify the strength of interaction, the adsorption energy (E _ad ) was calculated using

$$E_{\mathit{ad}}=E_{\mathrm{mol}+\mathit{mL}}-E_{\mathit{mL}}-E_{\mathit{mol}}$$ 3

where E _mol+mL represents the histamine adsorbed graphene complex total energy, E _mL represents the pure or doped graphene monolayer total energy, and E _mol represents the histamine molecule total energy.

Electronic Structures

The band structure calculations were performed for the monolayers and the molecule-monolayer complex. The high-symmetry k-point circuits were Γ (0.0, 0.0, 0.0), M (1/2, 1/2, 0.0), and K (1/3, 2/3, 0.0) as illustrated in Figure (d).

Charge transfer calculations were performed before and after the adsorption of histamine with the equation

$$\mathrm{\Delta }\rho (r)={\rho }_{\mathrm{mol}/\mathrm{mL}}-{\rho }_{\mathit{mL}}-{\rho }_{\mathit{mol}}$$ 4

where Δρ(r) represents the net charge transfer, ρ _mol/mL represents the charge of the histamine adsorbed monolayer, ρ _mL represents the charge of the monolayers, and ρ _mol represents the charge of the histamine molecule.

Recovery Time, Conductivity, and Sensitivity

The recovery times of the pure and doped graphene monolayers were calculated after histamine adsorption to assess reusability. Based on the conventional transition state theory, the recovery time (τ) , was determined by

$$\tau ={\nu }^{-1}\exp (-\frac{E_{\mathit{ad}}}{k_{\mathrm{B}}T})$$ 5

where ν represents the attempt frequency (ν = 10¹² s^–1 for visible light), E _ad represents the adsorption energy, k _B represents the Boltzmann constant (k _B = 8.617 × 10^–5 eV K^–1), and T represents the assumed desorption temperature (T = 300 K for room temperature).

The electrical conductivity (σ) of the graphene systems is given by

$$\sigma \propto \exp \left(\frac{-E_g}{2k_{\mathrm{B}}T}\right)$$ 6

where E _g represents the band gap of the graphene complex, k _B represents the Boltzmann constant, and T represents the thermodynamic temperature.

Another important component of sensor effectiveness is the monolayer’s sensitivity. As a variation of electrical resistance, the sensitivity (S) was calculated by

$$S=\left|\frac{{\sigma }_{\mathrm{mL}}-{\sigma }_{\mathrm{mL}+\mathrm{mol}}}{{\sigma }_{\mathrm{mL}}}\right|\times 100$$ 7

where σ _mL and σ _mL+mol represent the conductivity of the pure or doped graphene monolayer and the histamine adsorbed graphene system, respectively.

Results and Discussion

To determine the most suitable material for a histamine biosensor, evaluations on the atomic structure, band structure, adsorption energy, recovery time, sensitivity, and charge transfer were completed.

Pure Materials

The structural and electronic properties of the graphene monolayer were first compared to established values. The 4 × 4 graphene supercell was constructed and relaxed as shown in Figure . The resulting lattice constant was 9.887 Å, corresponding to a primitive cell lattice constant of 2.472 Å. The calculated value is in satisfactory agreement with the experimental value of 2.46 Å, with an error of 0.5%. The C–C bond length was determined to be 1.427 Å, consistent with the previously reported value of 1.420 Å. In the band structure shown in Figure , the Dirac point is located at the high-symmetry k-point K, confirming the zero band gap of pristine graphene. ,

2.

(a) Graphene 4 × 4 supercell atomic structure and band structure. In addition, the fully relaxed atomic structure and band structure of histamine adsorbed on pure graphene monolayer (b) top site, (c) bridge site, and (d) hexagonal site. Grey, blue, and white indicate carbon, nitrogen, and hydrogen, respectively. In the band structure, zero represents the Fermi level.

The bond lengths of the histamine molecule, shown in Figure (a), were similarly compared to experimental values. The values, shown in Table , are in satisfactory agreement.

2. Histamine Bond Length Comparisons.

bond	current (Å)	experimental (Å)	error
N–C	1.46	1.46	0%
C–C	1.55	1.53	1.3%
C–C	1.49	1.51	1.3%
N–C	1.38	1.35	2.2%
N–C	1.37	1.37	0%
NC	1.32	1.31	0.8%
N–C	1.38	1.37	0.7%
CC	1.38	1.35	2.2%

Histamine Adsorbed Pure Graphene

For the pristine graphene monolayer, three initial adsorption sites were considered to ascertain the most stable configuration. As presented in Figure , the pyridine-like nitrogen atom of the histamine imidazole ring was placed above the top site (T), the C–C bridge site (B), and the hexagonal site (H), and followed by a full structure optimization. Using eq , the adsorption energy values were calculated to be −2.872 eV, −2.853 eV, and −2.842 eV for the top, bridge, and hexagonal sites, respectively. Positive adsorption energy values indicate nonspontaneous adsorption coupled with an exothermic reaction, whereas negative adsorption energy values indicate spontaneous adsorption with an endothermic reaction. A more negative value indicates a stronger histamine-graphene interaction and, therefore, a more stable system. Because E _ad (T) < E _ad (B) < E _ad (H), the top site was selected as the most stable and used for further evaluation in this study.

An effective sensor requires a balance in the strength of the interaction between the monolayer and the molecule. The interaction cannot be strong enough as to elongate the desorption and recovery times of the substrate. However, a strong enough interaction is required to retain the molecule on the monolayer. Using eq , the recovery time was calculated to be 2.7 × 10¹¹ s, as seen in Table . A long recovery time such as this is neither appropriate nor effective for sensor operation. For a fast desorption process, a shorter recovery time is generally favorable; however, a recovery time that is extremely short, such as on the nanosecond scale, may indicate desorption that is too rapid to sustain a measurable sensing response under practical conditions.

5. Recovery Time (τ) in Seconds and Sensitivity (S) of Histamine Adsorbed Doped Monolayers.

Calculation	Gr441 (top)	GO1	GO2	BN1	BN2	SiC
τ	2.7 × 1011	2.8 × 10–10	4.2 × 10–6	6.7 × 10–12	7.7 × 10–6	1.3 × 1025
S (%)	N/A	N/A	N/A	13.7	12	85

Additional evidence for the limited sensing performance of pristine graphene complex adsorbed with histamine is provided by the observed charge transfer. A potentially more ideal complex would exhibit greater charge transfer, which, in the figure, would be indicated by an overlap between regions to represent electron exchange. However, in Figure (f), the electron depletion (green) and electron accumulation (pink) regions remain localized near the adsorption region, indicating electron movement without substantial net charge transfer between the molecule and monolayer. The strong adsorption energy may therefore reflect additional contributions from polarization or localized electronic interactions rather than net charge transfer alone. This limited redistribution is consistent with the absence of an adsorption-induced change in the electronic states near the Fermi level. The electrical properties of the material were also analyzed, as measurable changes in the presence of target molecules are also required for sensing suitability. The band structure before and after histamine adsorption, respectively shown in Figure (a),(b), remained the same around the Fermi level with no difference in band gap. Thus, based on eqs and , it can be concluded that pure graphene has low sensitivity to histamine. Overall, the suboptimal recovery time, limited electron redistribution, and unchanged band gap indicate that pristine graphene is unsuitable as a histamine sensing material, motivating the investigation of doped configurations.

6.

Charge transfer after histamine adsorption onto (a) GO1 (b) GO2 (c) BN1 (d) BN2 (e) Silicon-doped graphene, and (f) pure graphene, top site. The green region illustrates electron depletion, and the pink region illustrates electron accumulation.

Histamine Adsorbed Silicon Doped Graphene

To improve the limited response of pristine graphene, silicon was selected as a substitutional dopant due to its larger atomic radius relative to carbon, which was expected to distort the local structure and electronic environment. , After the substitution of one silicon atom, shown in Figure , the graphene monolayer was warped around the dopant area as predicted. The resulting stability was analyzed using the defect formation energy, given by eq , which was observed to be 3.682 eV and is also shown in Table . Furthermore, the band gap increased from 0 eV to 0.216 eV following the silicon substitution, as shown in the before-and-after band structures in Figures (a) and (a). Because of this opening, the monolayer’s conductivity is slightly lowered; however, the sensitivity to an adsorbed molecule would become higher due to eq .

3.

Atomic and band structure of silicon-doped graphene monolayer (a) before histamine attachment and (b) after histamine attachment. Grey, orange, blue, and white represent carbon, silicon, nitrogen, and hydrogen, respectively.

3. Resulting Defect Formation Energy (E _form ) from Doped Monolayers and Lattice Constant (a) of Each Doped Monolayer .

variable	GO1	GO2	BN1	BN2	SiC
E form (eV)	–0.544	0.036	3.588	1.089	3.682
a (Å)	9.87	9.88	9.87	9.90	10.05

^aGO1, GO2, BN1, and BN2 are short for graphene oxide 1, graphene oxide 2, one boron nitride pair, and two boron nitride pairs as dopants, respectively.

With this silicon-doped graphene monolayer, the adsorption of histamine was studied by placing the pyridine-like nitrogen atom of the histamine imidazole ring above the silicon atom, relaxing the structure, and an adsorption energy was calculated to be −2.318 eV using eq , as seen in Table . Because the value was negative, the reaction was endothermic and spontaneous, thereby creating a more stable system. Consequently, the recovery time was determined to be 1.3 × 10²⁵ s using eq and is shown in Table ; the calculated recovery time is impractically long for an efficient, reusable sensor. Lastly, the electrical properties of the adsorption were analyzed for suitability. The charge transfer in Figure shows little overlap between the electron regions of the silicon-doped monolayer and the histamine molecule, pointing to a largely localized electron redistribution around the adsorption site. Despite this limited redistribution, the electronic states near the Fermi level changed following histamine adsorption. The band gap at point K increased from 0.216 to 0.314 eV following histamine adsorption, as illustrated in Figure , signifying reduced conductivity and yielding a calculated sensitivity of 85% according to eq and shown in Table . Despite a strong electronic response, silicon-doped graphene is rendered impractical for sensing applications due to its unrealistic recovery time.

4. Histamine Adsorbed Doped Monolayers Adsorption Energy (E _ad ) and Distance (h) between Histamine’s Nitrogen and the Dopant or Pure Monolayer.

variable	Gr441 (top)	GO1	GO2	BN1	BN2	SiC
E ad (eV)	–2.872	–0.417	–0.658	–0.063	–0.430	–2.318
h (Å)	2.07	2.69	2.74	2.86	3.29	1.86

Histamine Adsorbed Boron Nitride Doped Graphene

Boron nitride pairs were introduced as substitutional dopants to assess whether co-doping could improve the balance between adsorption strength and recovery time compared with silicon-doped graphene. Both one pair, referenced as BN1, and two pairs, referenced as BN2, were tested, as shown in Figure . Each pristine graphene supercell contained 32 carbon atoms. For BN1, one boron and one nitrogen with the 32 total atoms results in a concentration of 2/32, or 6.25%, and for BN2, two borons and two nitrogens with the same total results in a concentration of 4/32, or 12.5%. The structural distortion was quantified through the defect formation energy, calculated via eq and shown in Table . The results for one boron nitride pair and two boron nitride pairs were 3.588 eV and 1.089 eV, respectively. Additionally, the band structure was affected by boron nitride doping, with the band gap increasing from 0 eV to 0.223 eV after one dopant pair and to 0.296 eV after two dopant pairs. The non-zero band gap introduced by the doping reduces the conductivity of the monolayer, while increasing its sensitivity to adsorbed molecules.

4.

Atomic structure and band structure of (a) one BN pair doped graphene (b) two BN pairs doped graphene (c) histamine adsorbed on one BN pair doped graphene (d) histamine adsorbed on two BN pairs. Carbon, boron, nitrogen, and hydrogen are indicated by grey, pink, blue, and white, respectively. In the band structure, zero indicates the Fermi level.

To test for biosensor adequacy, histamine was adsorbed onto the boron nitride-doped monolayers by placing the nitrogen atom(s) of the histamine imidazole ring atop the boron atom(s) from the dopant pair. After adsorption, the adsorption energy, described in eq , was calculated to be −0.063 eV for one boron nitride pair and −0.430 eV for two boron nitride pairs, both shown in Table . Since both values are negative, the systems are more stable because the reaction is spontaneous and endothermic. Furthermore, the charge transfer analysis in Figure indicated limited electron redistribution near the nitrogen and boron sites. This weak redistribution is consistent with the relatively small electronic response and low calculated sensitivity at 13.7% for BN1 and 12% for BN2, as determined through eqs and and shown in Table . The minimal band gap changes following adsorption, 0.223 eV to 0.230 eV for BN1 and 0.296 eV to 0.303 eV for BN2, further reflect the modest electronic response of both configurations. Although both systems exhibit relatively low calculated sensitivity, BN2 provides a more favorable balance of adsorption energy and recovery time than BN1, showing greater overall potential among the two configurations.

Histamine Adsorbed Graphene Oxide

The pure graphene monolayer was also interstitially doped with oxygen to create graphene oxide with concentrations of 3.125% and 6.25%, as illustrated in Figure . Hereinafter, GO1 will refer to graphene oxide with a concentration of 3.125%, or 1/32, due to having one oxygen atom in a monolayer of 32 atoms; similarly, GO2 will hereinafter refer to graphene oxide with a concentration of 6.25%, or 2/32, due to having two oxygen atoms in a monolayer of 32 atoms. The configuration of oxygen atoms was selected for evaluation based on their demonstrated adsorption properties as reported in previous theoretical studies. As with substitutional doping, the atomic structure of the pristine graphene monolayer is affected by the additional interstitial oxygen atoms, calculated through the defect formation energy described by eq . As described in Table , GO1 and GO2 yielded defect formation energies of −0.544 eV and 0.036 eV, respectively. GO1’s negative defect formation energy is indicative of a more energetically favorable formation. On the other hand, the positive defect formation energy of GO2 indicates a less favorable formation. As a result of doping, the GO1 band structure was unaffected, with the band gap remaining at 0 eV before and after doping. However, the GO2 band gap increased from 0 eV to 0.123 eV.

5.

Atomic structure and band structure of (a) graphene oxide GO1 (b) histamine adsorbed on GO1 (c) graphene oxide GO2 (d) histamine adsorbed on GO2. Carbon, oxygen, nitrogen, and hydrogen are represented by grey, red, blue, and white, respectively. Zero represents the Fermi level in the band structure.

For further biosensor studies, histamine adsorption was performed by placing the nitrogen atom(s) of the histamine imidazole ring above the oxygen atom(s) in the doped monolayer. Afterward, the reaction was observed to be endothermic with spontaneous adsorption due to adsorption energy values of −0.417 eV and −0.658 eV for GO1 and GO2, respectively, as calculated through eq and shown in Table . Thereafter, the recovery time was calculated to be 2.8 × 10^–10 s for GO1 and 4.2 × 10^–6 s for GO2 utilizing eq and shown in Table . Analysis of the charge transfer, shown in Figure , indicates localized electron redistribution near the adsorption site. Although an electron region extends from the histamine molecule, the limited overlap suggests that the interaction is localized rather than indicative of substantial net charge transfer. The band gap of the GO1 monolayer remained at 0 eV, whereas the GO2 band gap closed after histamine adsorption, which is a pronounced change in the electronic states near the Fermi level and corresponds to an increase in conductivity. Such characteristics are favorable for biosensing, as the increase in conductivity leads to higher sensitivity per eq .

Scope of Selectivity

For practical biomolecular sensing, the biosensor material’s selectivity for histamine is an important criterion. An effective histamine biosensor should selectively detect histamine in the presence of interfering biological molecules such as dopamine, epinephrine, and glutamate. Because these interferents may exhibit similar chemical or electrochemical behavior, selectivity issues are plausible and may be partially addressed by preferential adsorption of the target molecule. In addition to stronger histamine adsorption, future designs of a device may incorporate strategies such as permselective membranes, electrostatic exclusion films, or mediators to further reduce interference. Therefore, while this study identifies promising candidate monolayers for histamine sensing, further assessment is required to determine practical selectivity, including adsorption calculations of representative interferents on the same monolayers. Experimental selectivity measurements may also be carried out to complement theoretical calculations. ,

Conclusion

In summary, through first-principles calculations based on density functional theory, the adsorption behavior and electrical characteristics of histamine on monolayers of pristine graphene, graphene oxide with a concentration of 3.125%, graphene oxide with a concentration of 6.25%, boron nitride-doped graphene with a concentration of 6.25%, boron nitride-doped graphene with a concentration of 12.5%, and silicon-doped graphene were examined. The effectiveness of a biosensor depends on several factors, including appropriate adsorption energy, defect formation energy, recovery time, and sensitivity to the target molecule.

Analysis of histamine adsorption behavior reveals weak interactions with the pristine graphene monolayer and stronger interactions with doped monolayers. Of the five doped monolayers, the monolayers with the most favorable recovery times among the investigated systems were graphene oxide with a concentration of 6.25% at 4.2 × 10^–6 s and boron nitride with a concentration of 12.5% at 7.7 × 10^–6 s. Silicon-doped graphene at 1.3 × 10²⁵ s had, comparatively, the least favorable recovery time. In addition, graphene oxide with a concentration of 6.25% and boron nitride with a concentration of 12.5% exhibited moderate adsorption energies of −0.658 eV and −0.430 eV, respectively. Thus, it can be concluded that graphene oxide with a concentration of 6.25% and boron nitride with a concentration of 12.5% show the most overall promise as histamine biosensor materials. Moreover, the band gap of graphene oxide with a concentration of 6.25% closes at the Fermi level after histamine adsorption, further supporting its sensing potential.

Future work should evaluate the adsorption behavior of biological interferents, including but not limited to dopamine, epinephrine, and glutamate. Additional studies using larger graphene models and incorporating lattice imperfections could extend the present findings to more realistic graphene systems. To complement these computational studies, experimental validation of stability and sensing performance under realistic biological conditions is also needed to assess practical histamine sensing applications.

The authors declare no competing financial interest.