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Special Issue "Advances in Sustainable Hydrogen Production: Challenges and Opportunities"

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Dear Colleagues,

Currently, most developed countries are involved in a green transition in energy production. For that purpose, green hydrogen is considered the most interesting and promising vector. Since the main hydrogen production process has been, traditionally, steam reforming of natural gas or crude oil fractions, a deep transition to sustainable processes is needed. The Applied Sciences Special Issue “Advances in Sustainable Hydrogen Production: Challenges and Opportunities” will provide a unique opportunity to share the latest research and advances in sustainable hydrogen production developments, with a special focus on those based on the use of wastes as hydrogen sources.

Prof. Dr. Francisco Heras
Guest Editor

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Keywords

bio-hydrogen
green hydrogen
sustainable energy production
green energy transition
biomass
fermentation
gasification
reforming
pyrolysis
hydrothermal carbonization

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Research

Open AccessArticle

Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations

SK Safdar Hossain

Bamidele Victor Ayodele

Zaid Abdulhamid Alhulaybi

and

Muhammad Mudassir Ahmad Alwi

Appl. Sci. 2022, 12(24), 12914; https://doi.org/10.3390/app122412914 - 15 Dec 2022

Viewed by 673

Abstract

Biodiesel production often results in the production of a significant amount of waste glycerol. Through various technological processes, waste glycerol can be sustainably utilized for the production of value-added products such as hydrogen. One such process used for waste glycerol conversion is the bioprocess, whereby thermophilic microorganisms are utilized. However, due to the complex mechanism of the bioprocess, it is uncertain how various input parameters are interrelated with biohydrogen production. In this study, a data-driven machine-learning approach is employed to model the prediction of biohydrogen from waste glycerol. Twelve configurations consisting of the multilayer perceptron neural network (MLPNN) and the radial basis function neural network (RBFNN) were investigated. The effect of using different combinations of activation functions such as hyperbolic tangent, identity, and sigmoid on the model’s performance was investigated. Moreover, the effect of two optimization algorithms, scaled conjugate gradient and gradient descent, on the model performance was also investigated. The performance analysis of the models revealed that the manner in which the activation functions are combined in the hidden and outer layers significantly influences the performance of various models. Similarly, the model performance was also influenced by the nature of the optimization algorithms. The MLPNN models displayed better predictive performance compared to the RBFNN models. The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R² of 0.403 and a RMSE of 301.55. While the MLPNN configuration with the hyperbolic tangent as the hidden layer activation function and the sigmoid as the outer layer activation function yielded the best performance as indicated by an R² of 0.978 and a RMSE of 9.91. The gradient descent optimization algorithm was observed to help improve the model’s performance. All the input variables significantly influence the predicted biohydrogen. However, waste glycerol has the most significant effects. Full article

(This article belongs to the Special Issue Advances in Sustainable Hydrogen Production: Challenges and Opportunities)

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Open AccessArticle

Toward Sustainability of the Aqueous Phase Reforming of Wastewater: Heat Recovery and Integration

Francisco Heras

Adriana S. de Oliveira

and

Appl. Sci. 2022, 12(20), 10424; https://doi.org/10.3390/app122010424 - 16 Oct 2022

Viewed by 751

Abstract

Aqueous-phase reforming has been revealed as a novel, interesting and efficient process for the treatment of wastewater containing organic pollutants. However, due to the relatively severe operating conditions (above 15 bar and 200 °C), this process could become economically competitive if any solution for energy or material valorization is implemented. Most research has been devoted to direct the process to H₂ production as an alternative to reach economic sustainability, but the results obtained were not competitive in the current market of hydrogen and syngas. In this work, a preliminary simulation study (using Aspen HYSYS software) of the process heat balance in different conditions was implemented to induce a heat integration that would allow the auto-sustainability of the process, even generating in some cases an excess of energy that could constitute an opportunity for a positive economic balance. The results showed that this approach would only be possible by maximizing the methane production to the detriment of hydrogen production. Full article

(This article belongs to the Special Issue Advances in Sustainable Hydrogen Production: Challenges and Opportunities)

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Special Issue "Advances in Sustainable Hydrogen Production: Challenges and Opportunities"

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