Micro-patterned graphite electrodes: An analysis and optimization of process parameters on hydrogen evolution in water electrolysis

Kowthaman, C.N.; Kumar, P. Senthil; Selvan, V. Arul Mozhi

doi:10.1016/j.fuel.2021.121542

Cited by 8 publications

(2 citation statements)

References 35 publications

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“…Table 2 shows the actual and anticipated results for the volume of H 2 generation produced by the D-optimal design. Equation ( 1 ) illustrates the response surface that was estimated by the RSM model using the secondary polynomial model 38 . where Y is the predicted output response, A, B, and C are independent factors, β a , β b and β c are the coefficients, β 0 is the intercept constant term and β aa , β bb and β cc are the interactive coefficients.…”

Section: Methodsmentioning

confidence: 99%

Experimental, predictive and RSM studies of H2 production using Ag-La-CaTiO3 for water-splitting under visible light

Ragab,

Elkatory,

Hassaan

et al. 2024

Sci Rep

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Ag-La-CaTiO3 was used in place of sacrificial agents to assess the influence of operational factors on hydrogen generation in a photocatalytic water splitting system. After being synthesized, the physicochemical features of this substance were accurately described. Several characterization techniques including UV–Vis spectroscopy, FTIR, XRD, XPS, EDX, SEM, TGA, DRS and BET were applied to study the prepared Ag-La-CaTiO3 photocatalyst. Ag-La-CaTiO3 shows a band in the visible wavelength between 400 and 800 nm at < 560 nm compared to the main CaTiO3 band at 350 nm. Ag 4d5s electrons transition to the conduction band (CB), which is responsible for the absorption band at ~ 560 nm (> 2.21 eV). The effects of catalyst concentration, light intensity, and beginning solution pH on the H2 generation rate may all be evaluated simultaneously using experimental design procedures. Up to a maximum threshold, where a drop in the rate of gas evolution occurs, it was confirmed that the increase in catalyst dose positively affects system productivity. The initial solution pH plays a crucial role in H2 production, and pH = 4 and 10 are the optimum pH with a higher yield of H2 production. The highest total H2 production rate, 6246.09 μmol, was obtained using a catalyst concentration of 700 mg and solution pH equal to 10 under 1200 W Vis lamp for 3 h. For prediction and optimization, a D-Optimal design was applied and the optimal results were pH 4, the catalyst dose of 645.578 mg and 1200 W with H2 production of 6031.11 μmol.

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Section: Methodsmentioning

confidence: 99%

Experimental, predictive and RSM studies of H2 production using Ag-La-CaTiO3 for water-splitting under visible light

Ragab,

Elkatory,

Hassaan

et al. 2024

Sci Rep

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show abstract

“…In the regime of gap >1.3 μm, bubble size increases with gap width. Linear ridge structure can also be widely used to optimize the electrode surface texture for other gas evolution reactions. − These works demonstrate that the striped models not only improve the nucleation sites of catalysts but also activate the preexisting catalysts by changing the interaction between the gaseous products and the catalysts.…”

Section: Surface Texture Designmentioning

confidence: 99%

Bubble Management for Electrolytic Water Splitting by Surface Engineering: A Review

Cheng,

Du,

Ding

et al. 2023

Langmuir

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Prediction and optimization of the process of generating green hydrogen by electrocatalysis: A study using response surface methodology

Özgür

Mert

2022

Fuel

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Micro-patterned graphite electrodes: An analysis and optimization of process parameters on hydrogen evolution in water electrolysis

Cited by 8 publications

References 35 publications

Experimental, predictive and RSM studies of H2 production using Ag-La-CaTiO3 for water-splitting under visible light

Experimental, predictive and RSM studies of H2 production using Ag-La-CaTiO3 for water-splitting under visible light

Bubble Management for Electrolytic Water Splitting by Surface Engineering: A Review

Prediction and optimization of the process of generating green hydrogen by electrocatalysis: A study using response surface methodology

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