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Article

Research on Os-Modified C3N Nanosheets for Sensing and Adsorbing Dissolved Gases in 10 kV Distribution Transformer Oil for Fault Diagnosis

by
Yuanhao Zheng
1,
Haixia Wang
2,*,
Fei Wang
3 and
Hongbo Zou
4,*
1
School of Materials Science and Engineering, University of New South Wales, Sydney 2052, Australia
2
State Grid Talent Exchange Service Center Co., Ltd., Beijing 100089, China
3
School of Electrical and Automation, Wuhan University, Wuhan 430072, China
4
School of Electricity and New Energy, Three Gorges University, Yichang 443002, China
*
Authors to whom correspondence should be addressed.
Processes 2025, 13(11), 3517; https://doi.org/10.3390/pr13113517
Submission received: 28 September 2025 / Revised: 27 October 2025 / Accepted: 29 October 2025 / Published: 2 November 2025
(This article belongs to the Section Energy Systems)
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Abstract

Online monitoring technology for transformers is a crucial safeguard for power supply, and diagnosing dissolved gases in 10 kV distribution transformer oil is considered an effective criterion for transformer fault detection. Using density functional theory, this paper simulated the adsorption process of five dissolved gases in a 10 kV distribution transformer on Os-modified C3N nanosheets, and by calculating the band structure, differential charge density, density of states, and work function, the related sensing and adsorption mechanisms were revealed. The results indicate that Os modification significantly enhances the gas-sensing response of C3N nanosheets, particularly for capturing C2H2 and CO, which is primarily attributed to the d-orbital electrons of the doped metal. The adsorption capability of Os-modified C3N nanosheets of dissolved gases follows the order C2H2 > CO > H2 > CO2 > CH4, with the adsorption type being physico-chemical adsorption, and these findings provide a theoretical foundation for developing high-sensitivity gas sensors for detecting dissolved gases in a 10 kV distribution transformer.

1. Introduction

In modern power systems, 10 kV distribution transformers are critical pieces of equipment widely used in urban and rural power distribution networks [1,2,3]; simultaneously, the number of 10 kV distribution transformers far exceeds that of higher voltage-level equipment (110 kV, 220 kV), and their operational safety and reliability are vital for power system stability. During operation, the insulating oil in 10 kV distribution transformers serves not only for cooling and insulation but also significantly influences transformer lifespan and performance [4,5]. However, under various operating conditions, 10 kV distribution transformers are subjected to multiple thermal and electrical stresses, which can cause decomposition of dissolved gases in the 10 kV distribution TO [6]. These dissolved gases generally include methane, hydrogen, acetylene, ethylene, and carbon monoxide, among others [7,8], and their types and concentrations can indicate the nature and severity of internal transformer faults [9,10]. For example, overheating may increase ethylene and ethane levels, while electrical arcing can markedly increase acetylene concentration [11,12]. Hence, online monitoring of dissolved gases in 10 kV distribution TO has become an essential approach for transformer fault diagnosis and condition assessment [13,14].
Dissolved Gas Analysis (DGA) is a well-established technique for assessing transformer health [15,16,17], allowing early identification of potential faults through periodic or continuous monitoring of dissolved gas concentrations, thereby helping prevent equipment damage and power outages. In recent years, advances in sensor technology and data analysis have enabled online monitoring systems to provide real-time, detailed dissolved gas data, assisting maintenance personnel in taking timely preventive measures to extend transformer service life and reduce operating costs [18,19].
Existing gas sensors—such as metal oxide semiconductor (MOS) and electrochemical sensors—though widely used, still face considerable limitations in sensitivity, selectivity, response time, and long-term stability [20,21,22]. Since the landmark discovery of graphene in 2004, carbon-based two-dimensional materials have attracted extensive research interest. Subsequently, novel 2D materials such as MoS2, GeSe, and SnS have been synthesized and applied across electronics, chemistry, and biomedicine [23,24,25]. However, achieving controllable bandgaps in such materials remains a challenge in nanomaterials research [26], prompting ongoing global exploration of new 2D materials. Among them, C3N nanosheets have shown promise for gas sensing due to their distinctive chemical and physical properties [27,28], including high specific surface area, excellent conductivity, mechanical strength, and a distinctive electronic structure that can significantly enhance sensor sensitivity and selectivity [29,30]. Studies indicate that C3N nanosheets perform exceptionally in detecting low-concentration gases such as hydrogen, carbon monoxide, ammonia, and methane, demonstrating great potential for high-performance gas sensors [31,32].
Research on C3N nanosheets is still in its early stages. Although pristine C3N nanosheets already exhibit good gas sensing performance, researchers aim to further improve it through metal nanoparticle doping [33,34]. Studies show that introducing metal nanoparticles can enhance intrinsic conductivity and gas adsorption capacity, as well as improve selectivity via synergistic interactions with gas molecules, thereby boosting overall sensor performance [35,36]. Various metal dopants—such as Au, Ag, Pt, Pd, and Rh—have been studied [37,38], yet a heavy metal atom with great potential, Os, has been overlooked. Given the excellent properties of Os as a dopant, this study employs Os-doped C3N nanosheets.
This paper investigates the potential application of Os nanoparticle-modified C3N nanosheets in detecting dissolved gases in 10 kV distribution TO. By analyzing binding energy, adsorption energy, DOS, DCD, and work function, the response mechanism to target gases is revealed. Through systematic analysis of the response characteristics of doped C3N nanosheets in different gas environments, we evaluate their feasibility for practical application, providing a theoretical basis and technical support for developing next-generation high-performance gas sensors. This research aims to advance intelligent online monitoring technology for transformers and promote progress in ultra-high voltage infrastructure construction.

2. Computational Details

The entire computation and optimization in this paper were performed by using the Materials Studio software (V2024), with theoretical analysis primarily based on DFT [39]. Initially, a C3N nanosheet with 24 C atoms and 8 N atoms was constructed, and periodic boundary conditions were set to 25 Å × 25 Å × 13 Å to avoid interference from adjacent supercells. The Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA) functional and the double numerical plus polarization (DNP) basis set were employed for electron exchange-correlation [40]. Dispersion corrections beyond the TS method were incorporated, and convergence tests for k-points and cutoff energy were systematically performed. Spin polarization calculations were unrestricted in all structural optimizations. The DFT semi-core pseudopotential treated core-valence interactions, while van der Waals (vdW) forces were corrected with the TS scheme. A 4 × 4 × 1 mesh was applied for Brillouin zone sampling. The convergence criteria were set as follows: energy tolerance of 10−6 Ha, maximum stress of 2 × 10−3 Ha/Å, maximum displacement of 5 × 10−3 Å, and an SCF convergence threshold of 1.0 × 10−6 Ha. The global orbital cutoff was set to 5.0 Å.
An effective gas adsorption process must involve significant changes in electronic and energetic properties, which are essential for developing gas sensors with high selectivity and sensitivity. The energy change during gas adsorption is defined as adsorption energy (Eads), calculated using Equation (1), where Esur/gas, Egas, and Esuf represent the total energies of the adsorption system, the target gas molecule, and the isolated Os-modified C3N system, respectively. A negative Eads indicates a spontaneous adsorption process, and a more negative Eads corresponds to a stronger interaction. Furthermore, we employed Mulliken population analysis to assess the charge transfer (Qtrans). This value is characterized by the net electron population on the gas molecule post-adsorption, as given by Equation (2).
Eads = Esur/gas − Egas − Esuf
Qtrans = Qa − Qbf

3. Results and Discussion

3.1. The Most Stable Geometries and Electronic Properties of Os Modified C3N Nanosheets

Figure 1 presents the geometrically optimized structures of the pristine C3N nanosheet and gaseous species. This study focuses on the principal characteristic gases generated under fault conditions in 10 kV distribution TO, namely methane (CH4), hydrogen (H2), carbon monoxide (CO), acetylene (C2H2), and carbon dioxide (CO2), whose molecular structures are shown in Figure 1a–e. Among them, H2, CO, CO2, and C2H2 are linear molecules. Prior to adsorption, the H–H bond possesses the shortest length, measuring 0.749 Å, while the C–O bond lengths in CO and CO2 are 1.142 Å and 1.175 Å, respectively. CH4 exhibits a tetrahedral configuration with a C–H bond length of 1.097 Å. The C3N nanosheet is characterized by a two-dimensional honeycomb lattice, analogous to that of pristine graphene, consisting of uniformly distributed carbon and nitrogen atoms, as illustrated in Figure 1f. During Os modification, multiple potential doping sites were considered (N-substitutional, C-substitutional, hollow, bridge, or top), and the most stable configuration was determined by comparing physical structures and doping energies. The most stable optimized doped configuration (Figure 1f) has a binding energy of –2.268 eV. According to Mulliken population analysis, a charge transfer of −2.106 e is observed, indicating that the Os dopant acts as an electron acceptor and that the system exhibits strong stability with significant energy release. Furthermore, originating from the van der Waals forces of the doped Os atom, three carbon atoms on the C3N surface are displaced upward, forming stable chemical bonds with the Os atom. Figure 1g,h display the band structure and DCD of the Os-modified C3N nanosheet, respectively. The band structure indicates that the bandgap of the modified Os-C3N is 0.381 eV, which is 14.6% lower than that of the pristine C3N nanosheet, suggesting that the Os nanoparticle enhances electron activity on the C3N surface, thereby enhancing the system’s overall conductivity by facilitating electron transfer from the valence to the conduction band. Regarding the DCD distribution, the red regions correspond to an increase in electron density, while the green regions indicate a decrease, with the colormap ranging from −0.2 to 0.2 e/Å3. The findings demonstrate that the electron activity increases significantly in the doped region, indicating that the Os atom captures a substantial number of electrons from the C3N surface, leading to considerable lattice strain in the doped area.

3.2. Adsorption Structures of Pure C3N and Os Modified C3N to Dissolved Gases in Oil

To explore the surface reaction properties of the target gases on the adsorbent, numerous adsorption models were constructed, and the ten most stable physical configurations, shown in Figure 2, were selected for analysis. Models M1–M5 display the geometric configurations of H2, CO, CO2, CH4, and C2H2 adsorbed on the pristine C3N surface, while N1–N10 present the corresponding adsorption scenarios on the Os-modified C3N. Corresponding data for adsorption distance, adsorption energy, and charge transfer are provided in Table 1. Since gas adsorption occurs under non-zero temperature conditions in actual operating transformers, we have incorporated entropy-based finite temperature corrections when comparing gas adsorption trends. In the pristine C3N adsorption systems, the adsorption distances for all five target gases are around 3 Å, with adsorption energies close to zero and negligible charge transfer, indicating that pristine C3N has limited capacity to effectively capture dissolved gases from 10 kV distribution TO. In contrast, after Os doping, the adsorption performance toward these gases is significantly enhanced. Strong physicochemical interactions occur in the surface reaction region, enabling the Os dopant to efficiently capture gas molecules. For instance, when H2 interacts with Os–C3N, the H–H bond dissociates and the resulting H atoms form bonds with the Os atom at a length of 1.644 Å. CO and CO2 preferentially orient their carbon atoms toward the Os–C3N surface, with adsorption energies of −3.447 eV and −2.252 eV, respectively. Notably, the doped region maintains structural stability after adsorption, underscoring the robustness of the system. Unlike the previous gases, CH4 exhibits the shortest adsorption distance and the lowest adsorption energy, which can be ascribed to the feeble van der Waals interactions and the inherent inertness of CH4. Meanwhile, C2H2 undergoes a notable structural change upon adsorption, transitioning from a linear to a planar configuration with an H–C–H angle of about 135°, due to the activating influence of the Os dopant. Moreover, C2H2 shows the highest adsorption energy among all target gases, reaching −4.479 eV, making its desorption from the Os–C3N surface highly unlikely.
In summary, Os-modified C3N exhibits a significantly stronger ability to capture dissolved gases in oil compared to pristine C3N. The adsorption strength follows the order C2H2 > CO > H2 > CO2 > CH4, allowing precise sensing of target gases. Furthermore, based on adsorption energy, adsorption distance, and structural analysis, the adsorption of H2 and C2H2 is primarily chemisorption, while CO, CO2, and CH4 involve a combination of physisorption and chemisorption.

3.3. The Electronic Properties of Different Adsorption Systems

The DOS serves as a crucial tool for investgating electronic characteristics, particularly for showing how electronic states are distributed across energy levels and explaining gas adsorption mechanisms. As illustrated in Figure 3, the DOS for each adsorption system (N1–N5) is presented, along with the DOS distributions of the adsorbed gas molecules and the Os dopant. To more clearly highlight changes in the DOS, both the total DOS (TDOS) and the projected DOS (PDOS) are provided, with TDOS given in Figure 3a–e and PDOS in Figure 3a1–e1. In the H2 adsorption system, a notable reduction in the number of electrons occurs on both sides of the Fermi level, accompanied by a widening of the gap between the valence band and the conduction band, which hinders electron transitions. This results in an increase in the whole system resistivity, primarily due to contributions from the 4d orbitals of the Os atom. Moreover, the influence of the H2 molecules on the TDOS is mainly observed between −5 eV and −2.5 eV, with negligible effect on the electron distribution within the conduction band.
In the system of CO adsorption, the presence of CO gas increases the electron density at energy levels around −6 eV and 3.5 eV, which is primarily attributed to the contributions of the 2p orbitals of the C (from CO) and O atoms. Furthermore, the significant overlap between the TDOS and PDOS suggests that surface reactions have only a minor influence on the system’s conductivity. As shown in Figure 3c,c1, CO2 adsorption reduces the DOS near the Fermi level, showing a considerable impact on electron distribution. This leads to the appearance of pronounced peaks in the energy range from −10 eV to 5 eV. For the CH4 and C2H2 adsorption systems, additional impurity states emerge at multiple energy levels, altering electron occupancy and generating distinct electrical signals, which provides the cornerstone underlying gas detection.
Importantly, the PDOS distributions for the five adsorption systems reveal diverse orbital hybridizations, with peaks corresponding to H-1s, C-2p, and Os-4d orbitals appearing at different energy levels. This indicates that different physical and chemical reactions occurred during the surface reaction process. These variations originate from the differing degrees of physical and chemical adsorption involved in the surface reactions. The final ranking of conductivity is N2 > N4 > N3 > N5 > N1, offering strong theoretical support for the sensing performance of the corresponding nanostructured sensors.
Band structure analysis offers valuable insights into the electronic manifestations and properties inherent in materials and serves as an effective means to assess their conductivity. Figure 4a–e show the band structures of the gas/Os–C3N systems, calculated using the HCTH functional. The trends in band gap changes following Os doping are consistent with those obtained with the PBE functional, confirming the reliability of our calculations. As previously shown in Figure 1, the band structure of Os-doped C3N shows a band gap of 0.381 eV. After adsorption of the target gases, the band gap (E9) values of the systems display clear variations. In the CO system, E9 remains almost unchanged, suggesting that the hybrid system’s conductivity is largely unaffected by the surface reaction, with no major shifts in the conduction and valence bands. In contrast, the band gap increases for H2, CO2, CH4, and C2H2 systems after surface reactions, with growth rates of 117%, 64%, 18%, and 99%, respectively, indicating varying degrees of enhancement in system conductivity.
A detailed analysis of the band distributions reveals that these changes stem mainly from an upward shift in the conduction band, which increases the energy difference between the Fermi level and the conduction band, thereby raising the energy barrier for electron transitions. The differential charge density (DCD) distributions, presented in Figure 4a1–e1, highlight regions of electron accumulation (red) and depletion (blue), with the colormap scaled from −0.2 to 0.2 e/Å3. These distributions point to relatively moderate surface reactions, where electron accumulation is largely localized around the adsorbed gas molecules, indicating that the dissolved gases primarily act as electron acceptors during adsorption. Moreover, the charge transfer patterns visible in the DCD plots align well with the quantitative charge transfer values listed in Table 1. It is noteworthy that the electron accumulation regions in the CO and CH4 adsorption systems are relatively weak, consistent with the small charge transfers calculated for these cases.
As illustrated in Equation (3), the conductivity of complex systems is evaluated by calculating the molecular orbital energy gap between the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO), where EHOMO and ELUMO represent the energies of HOMO and LUMO, respectively. A lower Eg value indicates higher electron mobility.
Eg = |ELUMO − EHOMO|
Figure 5 presents the frontier molecular orbital analysis for each adsorption system, with the corresponding HOMO and LUMO energies explicitly indicated. Prior to gas adsorption, the HOMO energy (EHOMO) is −3.739 eV and the LUMO energy (ELUMO) is −3.338 eV, resulting in an energy gap (Eg) of 0.401 eV. Following the adsorption of the five gaseous species, the calculated Eg values are 0.374 eV, 0.382 eV, 0.408 eV, 0.441 eV, and 0.367 eV, respectively.
The spatial distributions of the HOMO and LUMO are primarily concentrated near the Os dopant, reflecting the strong electronic activity of the Os metal atom. Before gas adsorption, the HOMO and LUMO are uniformly distributed across the C3N surface, indicating a homogeneous electron density. After the adsorption of CO, H2, and CO2 molecules, both EHOMO and ELUMO increase, although the resulting energy gap changes differently depending on the adsorption mechanism and degree of charge transfer. In these systems, the abundance of LUMO states around the adsorbed gas molecules suggests a tendency for electron transitions to lower-energy orbitals, facilitating molecular activation and enhancing the all-around conductivity that the adsorption system shows. In contrast, for CH4 adsorption, no significant HOMO or LUMO density is observed near the gas molecule, which impedes electron transport and limits any improvement in electrical signal response, a finding consistent with prior electronic property analyses. Meanwhile, C2H2 adsorption leads to a noticeable reduction in the HOMO–LUMO gap, which can be attributed to the influence of the highly active outermost electrons of the Os dopant. The frontier molecular orbital analysis provides essential insight into the evolution of electronic properties and electrical signals before and after gas adsorption, offering a solid theoretical basis for the design of highly sensitive and selective Os–C3N-based gas sensors.

3.4. Exploration and Application of Sensing Properties

Figure 6 provides a visual summary of the adsorption data and band gap values, assisting in clarifying specific sensing characteristics. Figure 6a indicates that the adsorption distances for the five target gases are generally similar, with C2H2 exhibiting the strongest adsorption performance, while CH4 shows relatively weak adsorption. According to the extant literature, the adsorption energies exhibited by dissolved gases within oil generally lie in the range of 1 to 2 eV [18,41,42,43], underscoring the significantly enhanced gas capture capability of Os–C3N, particularly for C2H2. In terms of desorption characteristics, however, CH4 holds a greater advantage. Figure 6b displays the changes in band gap, offering a visual reflection of the variations in conductivity across the adsorption systems. The CO system remains nearly unchanged compared to the original system, while the other adsorption systems show increases to various degrees.
The work function (WF) of a metal or semiconductor is the minimal energy required to eject an electron from the Fermi level to the vacuum outside the material. As the WF is intrinsically linked to the material’s surface, it plays a critical role in surface conductivity and serves as a key factor in determining the sensing properties of the adsorption surface. As illustrated in Figure 6b, upon the adsorption of dissolved gases in oil onto Os-doped C3N, the WF values increase from 3.548 eV (pristine) to 4.675 eV (H2 system), 4.324 eV (CO system), 4.168 eV (CO2 system), 4.587 eV (CH4 system), and 4.11 eV (C2H2 system). This represents an approximate 20% increase in WF across the systems, promoting the efficient identification of target gases. Notably, the WF of the H2 system is the highest among the five systems, attributed to the disruption of gas molecules. In contrast, the WF of the C2H2 adsorption system is the lowest, reflecting the unique sensing behavior of C2H2 compared to other gases. These variations in conductivity characteristics provide a reliable basis for distinguishing target gases in practical applications.

4. Conclusions

In this research, we investigated the adsorption behavior and electronic characteristics of dissolved gases in 10 kV distribution TO (H2, CO, CO2, CH4, C2H2) on pure Os nanoparticle-doped C3N using DFT. By analyzing the band structure, DOS, DCD, WF, and frontier molecular orbitals; the adsorption and sensing characteristics of five target gases were also evaluated. The research results offer a solid theoretical underpinning for the development and utilization of C3N-based nanosensors. The main conclusions are as follows:
(1)
A 4 × 4 × 1 k-point mesh and an SCF convergence threshold of 1.0 × 10−6 Ha were employed in the simulations. After Os nanoparticle doping, no physical deformation occurred on the C3N surface, demonstrating that the integration of nanoparticles yields adsorption sites while maintaining the material’s structural integrity. Additionally, the band gap of C3N was significantly reduced from 1.274 eV to 0.381 eV, enhancing the system’s conductivity.
(2)
Pure C3N exhibits poor adsorption performance for dissolved gases in oil and lacks significant improvement in electronic properties. This suggests the potential for surface modifications to enhance its gas capture capability.
(3)
Os-modified C3N shows a marked improvement in gas capture capability for dissolved gases in 10 kV distribution TO, with the adsorption strength ranked as C2H2 > CO > H2 > CO2 > CH4. Notably, the adsorption of C2H2 is significantly enhanced, accompanied by molecular activation. Furthermore, gas adsorption induces a leftward shift in the overall DOS, while the system’s resistivity decreases post-adsorption, promoting the efficient acquisition and juxtaposition of electrical signals.
(4)
For the CO system, the band gap remains almost unchanged. In contrast, the band gap growth rates for H2, CO2, CH4, and C2H2 after surface reactions are 117%, 64%, 18%, and 99%, respectively, indicating varying degrees of enhanced system conductivity.
The newly developed two-dimensional Os-doped C3N material demonstrates potential as an advanced sensor for gas removal and sensing. It offers excellent performance in the adsorption and detection of dissolved gases in 10 kV distribution TO, enabling online monitoring of transformer faults. These findings underscore the promise of Os-doped C3N as a next-generation sensor material for transformer fault diagnosis and monitoring and significantly enhances the stability of the power grid supply. In future research, we will focus more on the fabrication and performance testing of Os-C3N sensors and evaluate the material’s environmental adaptability and long-term stability to determine its potential for significant application in transformer fault monitoring.

Author Contributions

Conceptualization: Y.Z., H.W., F.W. and H.Z.; software: Y.Z., H.W., F.W. and H.Z.; writing—original draft preparation: Y.Z., H.W., F.W. and H.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

Author Haixia Wang was employed by State Grid Talent Exchange Service Center Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. The most stable geometries of target gases and Os modified C3N nanosheets and electronic properties: (a) H2 (b) CO (c) CH4 (d) CO2 (e) C2H2 and (f) Os modified C3N nanosheets. (g) Band structure of Os modified C3N nanosheets. (h) Differential charge density of Os modified C3N nanosheets.
Figure 1. The most stable geometries of target gases and Os modified C3N nanosheets and electronic properties: (a) H2 (b) CO (c) CH4 (d) CO2 (e) C2H2 and (f) Os modified C3N nanosheets. (g) Band structure of Os modified C3N nanosheets. (h) Differential charge density of Os modified C3N nanosheets.
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Figure 2. The most stable adsorption structures of pure C3N and Os modified C3N to dissolved gases in oil M1–M5: target gases adsorbed on pure C3N N1–N5: target gases adsorbed on Os modified C3N.
Figure 2. The most stable adsorption structures of pure C3N and Os modified C3N to dissolved gases in oil M1–M5: target gases adsorbed on pure C3N N1–N5: target gases adsorbed on Os modified C3N.
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Figure 3. TDOS and PDOS of different adsorption systems. (a,a1): H2 system; (b,b1): CO system; (c,c1): CO2 system; (d,d1): CH4 system; (e,e1): C2H2 system.
Figure 3. TDOS and PDOS of different adsorption systems. (a,a1): H2 system; (b,b1): CO system; (c,c1): CO2 system; (d,d1): CH4 system; (e,e1): C2H2 system.
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Figure 4. The band structures and DCD of different adsorption systems. (a,a1): H2 system; (b,b1): CO system; (c,c1): CO2 system; (d,d1): CH4 system; (e,e1): C2H2 system.
Figure 4. The band structures and DCD of different adsorption systems. (a,a1): H2 system; (b,b1): CO system; (c,c1): CO2 system; (d,d1): CH4 system; (e,e1): C2H2 system.
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Figure 5. Molecular orbital distribution. (a): Os-C3N system; (b): H2/Os-C3N system; (c): CO/Os-C3N system; (d): CO2/Os-C3N system; (e): CH4/Os-C3N system; (f): C2H2/Os-C3N system; (g): Energy gap values of different systems.
Figure 5. Molecular orbital distribution. (a): Os-C3N system; (b): H2/Os-C3N system; (c): CO/Os-C3N system; (d): CO2/Os-C3N system; (e): CH4/Os-C3N system; (f): C2H2/Os-C3N system; (g): Energy gap values of different systems.
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Figure 6. Exploration and application of sensing properties. (a) Adsorption data analysis; (b) WF and band gap analysis of different systems.
Figure 6. Exploration and application of sensing properties. (a) Adsorption data analysis; (b) WF and band gap analysis of different systems.
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Table 1. Adsorption data of pure C3N and Os modified C3N to dissolved gases in oil.
Table 1. Adsorption data of pure C3N and Os modified C3N to dissolved gases in oil.
Adsorption SystemStructureEads (eV)D (Å)Qtrans (e)
H2/C3NM1−0.0522.858−0.001
CO/C3NM2−0.0033.148−0.015
CO2/C3NM3−0.0053.247−0.002
CH4/C3NM4−0.0052.980−0.080
C2H2/C3NM5−0.1133.2780.004
H2/Os-C3NN1−2.8781.644−0.098
CO/Os-C3NN2−3.4471.841−0.067
CO2/Os-C3NN3−2.2522.003−0.373
CH4/Os-C3NN4−0.7731.952−0.078
C2H2/Os-C3NN5−4.4791.966−0.151
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Zheng, Y.; Wang, H.; Wang, F.; Zou, H. Research on Os-Modified C3N Nanosheets for Sensing and Adsorbing Dissolved Gases in 10 kV Distribution Transformer Oil for Fault Diagnosis. Processes 2025, 13, 3517. https://doi.org/10.3390/pr13113517

AMA Style

Zheng Y, Wang H, Wang F, Zou H. Research on Os-Modified C3N Nanosheets for Sensing and Adsorbing Dissolved Gases in 10 kV Distribution Transformer Oil for Fault Diagnosis. Processes. 2025; 13(11):3517. https://doi.org/10.3390/pr13113517

Chicago/Turabian Style

Zheng, Yuanhao, Haixia Wang, Fei Wang, and Hongbo Zou. 2025. "Research on Os-Modified C3N Nanosheets for Sensing and Adsorbing Dissolved Gases in 10 kV Distribution Transformer Oil for Fault Diagnosis" Processes 13, no. 11: 3517. https://doi.org/10.3390/pr13113517

APA Style

Zheng, Y., Wang, H., Wang, F., & Zou, H. (2025). Research on Os-Modified C3N Nanosheets for Sensing and Adsorbing Dissolved Gases in 10 kV Distribution Transformer Oil for Fault Diagnosis. Processes, 13(11), 3517. https://doi.org/10.3390/pr13113517

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