Three-dimensional N/S Co-doped holey graphene oxide based hydrogel electrodes for high performance supercapacitors

Zhu, Zhenxiang; Wang, Zhenxing; Ba, Zhaohu; Dong, Jie; Zhang, Qinghua; Zhao, Xin

doi:10.1016/j.est.2021.102658

Cited by 22 publications

(9 citation statements)

References 36 publications

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“…The energy densities of N/S‐rGO//N/S‐rGO Sc is 21.3 Wh kg −1 at a power density of 890 W kg −1 . The electrochemical performance of the N/S‐rGO electrodes and N/S‐rGO//N/S‐rGO symmetric supercapacitor assembled in this article is better than that of similar N,S doped graphene materials reported in the literature (Table 1), 49‐53 indicating that the supramolecular‐driven co‐doping strategy proposed in this article can significantly improve the supercapacitive performance of graphene. Figure 6D shows two supercapacitor in series, after charging the to 2.4 V, it is connected to the LED, and the electric energy provided by the flexible supercapacitor makes the LED light last for 2 min.…”

Section: Resultsmentioning

confidence: 60%

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Supramolecular‐driven fabrication of porous nitrogen/sulfur co‐doped graphene toward high‐performance supercapacitor

Cheng

Meng

et al. 2022

Intl J of Energy Research

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Summary Practical applications of graphene‐based materials are still inhibited by the serious restacking of graphene nanosheets and single electrical double‐layer capacitor energy storage mechanism. To address these issues, nitrogen/sulfur‐co‐doped reduced graphene oxide (N/S‐rGO) was ingeniously prepared by supermolecular‐driven in‐situ co‐dope method. In this article, the GO/L‐cysteine supermolecular system was assembled first, the hydrogen bond between L‐cysteine and GO is confirmed by the Fourier‐transform infrared spectroscopy (FTIR). The theoretical calculation result indicating that L‐cysteine is uniformly assembled on GO surface by supermolecular interaction force (dispersion force and hydrogen bond). Due to the oriented supermolecular force, the thus‐fabricated N/S‐rGO affords customized three‐dimensional (3D) porous structure, uniform N,S co‐doping, effective electrolyte ion‐transport pathways, and satisfactory structural stability. Attributing to the inherent plentiful 3D cavity structure and synergistic effect between N, S heteroatoms, N/S‐rGO shows outstanding electrochemical performance, the best‐performed N/S‐rGO2 possess delightful capacitance (416 F g−1), after 20 000 cycles the capacitance retention of N/S‐rGO is 110% of the initial value, shows excellent cycle reliability. The N,S‐rGO all‐solid flexible symmetrical supercapacitor can light up luminous diode for 30 seconds when fully charged, indicating that it provides the possibility of practical application.

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Section: Resultsmentioning

confidence: 60%

“…Three-dimensional N-and S co-doped holey graphene hydrogel (N/S-HGH) 346 F g À1 @ 1 A g À1 -205 F g À1 @ 20 A g À1 93.9% @ 10 000 cycles 24.6 415.4 [53] This work 416 F g À1 @ 0.5 A g À1 85.5 F g À1 @ 0.5 A g À1…”

Section: Discussionmentioning

confidence: 99%

Supramolecular‐driven fabrication of porous nitrogen/sulfur co‐doped graphene toward high‐performance supercapacitor

Cheng

Meng

et al. 2022

Intl J of Energy Research

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“…The data were collected from multiple literature and compiled into a CSV file (available in Supporting Information .CSV and their source in Table S1), with references to the sources provided ,,,− ,− and our previous work. , The collected information includes parameters such as SA, DG, percentage of nitrogen dopant (% N), oxygen dopant (% O), sulfur dopant (% S), current density (CD), electrolyte concentration (CONC), and CAP. In the case of missing data (e.g., DG), the K -Nearest Neighbors imputation (KNN imputation) will be used to fill in the gaps.…”

Section: Methodsmentioning

confidence: 99%

“…Doping graphene with heteroatoms has shown to significantly enhance its CAP compared to its pure counterpart, as evidenced by various studies. − However, the electrochemical field is still debating the optimal conditions for doping graphene electrodes . Hence, it is essential to investigate the underlying factors that influence supercapacitor CAP, such as SA, doping contents including oxygen, sulfur, and nitrogen, as well as the defect ratio (DG).…”

Section: Introductionmentioning

confidence: 99%

Unlocking the Full Potential of Heteroatom-Doped Graphene-Based Supercapacitors through Stacking Models and SHAP-Guided Optimization

Deshsorn,

Payakkachon,

Chaisrithong

et al. 2023

J. Chem. Inf. Model.

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Graphene-based supercapacitors have emerged as a promising candidate for energy storage due to their superior capacitive properties. Heteroatom-doping is a method of improving the capacitive properties of graphene-based electrodes, but the optimal doping conditions and electrochemical properties are not yet fully understood due to the synergistic effects that occur. Many parameters, such as doping content, defects, specific surface area (SA), electrolyte, and more, could affect the capacitance (CAP). In this study, we use machine learning to solve these critical issues. We applied many models, such as Light Gradient Boost Machine, Extreme Gradient Boost, Polynomial Regression, Neural Network, Elastic Net, Lasso Regression, Ridge Regression, Random Forest, Support Vector Machine, K-Nearest Neighbors, Gradient Boost, AdaBoost, and Decision Tree, to find a suitable model for CAP prediction. Moreover, we enhance the prediction result by taking advantage of the top candidate model and creating a stacking concept (called “stacking models”). The SHAP value was used to identify the range of properties that affect CAP, and it was discussed in detail. Our results suggest that high-CAP graphene supercapacitors should have a large SA, with 4–5% nitrogen, 10–15% oxygen, high percentages of sulfur, a defect ratio close to 1, with acid electrolyte, and a low current density. These findings, along with the developed model and code, are expected to serve as a valuable computational tool for future electrochemical research from fundamental to applications.

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“…Supercapacitors are an improved adaptation of flat-plate capacitors using high surface area as electrode materials. They can provide substantially higher power density while maintaining a sufficient energy density, relatively similar to conventional batteries. , Graphene is a promising carbon-based material for supercapacitor electrodes because it possesses a tunable surface area of up to ∼2630 m 2 g –1 (depending on the synthesis conditions) and an expected theoretical capacitance of 550 F g –1 , which facilitates excellent electrical conductivity and chemical stability. − However, the intrinsic capacitance of graphene is not as high as expected due to several factors. For example, the calculation of the theoretical value is based on many assumptions, such as similar surface properties between graphene and platinum, and ignores the effect of quantum and diffuse layer capacitance. − Hence, the Helmholtz capacitance of 21 μF cm –2 is obtained .…”

Section: Introductionmentioning

confidence: 99%

Insights into Heteroatom-Doped Graphene Supercapacitor Data through Manual Data Separation and Statistical Analysis

Jitapunkul,

Deshsorn,

Payakkachon

et al. 2023

J. Phys. Chem. C

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The integration of data science with graphene-based supercapacitors has emerged as a promising approach for optimizing their performance. Graphene-based electrodes exhibit unique pseudo-capacitive properties, but optimizing their supercapacitors requires balancing multiple variables, including electrode features, electrolyte composition, and operating conditions. This is because the pseudo-capacitive effect can create different charge-storage mechanisms via surface redox reactions during charging/discharging. In this paper, we discuss the use of statistical data analysis for gaining insights into the complex interplay between material properties and electrochemical performance. We shed more light on the analysis of large datasets generated from experiments of heteroatom-doped graphene supercapacitors using data preprocessing techniques, such as scattered interpolation–extrapolation and Pearson correlation, instead of traditional machine learning models. We investigate the effects of various electrochemical features on capacitive performance and the influence of heteroatom doping, such as nitrogen, sulfur, and oxygen. Our analysis provides valuable insights into the essential electrochemical features and heteroatom doping that relate to capacitive-boosting performance, serving as a guideline for accelerating the development of energy storage, particularly for graphene-based supercapacitors, in both experimental and machine learning aspects.

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Three-dimensional N/S Co-doped holey graphene oxide based hydrogel electrodes for high performance supercapacitors

Cited by 22 publications

References 36 publications

Supramolecular‐driven fabrication of porous nitrogen/sulfur co‐doped graphene toward high‐performance supercapacitor

Supramolecular‐driven fabrication of porous nitrogen/sulfur co‐doped graphene toward high‐performance supercapacitor

Unlocking the Full Potential of Heteroatom-Doped Graphene-Based Supercapacitors through Stacking Models and SHAP-Guided Optimization

Insights into Heteroatom-Doped Graphene Supercapacitor Data through Manual Data Separation and Statistical Analysis

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