Modelling hydrogen production from biomass pyrolysis for energy systems using machine learning techniques.

In the context of Industry 4.0, hydrogen gas is becoming more significant to energy feedstocks in the world. The current work researches a novel artificial smart model for characterising hydrogen gas production (HGP) from biomass composition and the pyrolysis process based on an intriguing approach that uses support vector machines (SVMs) in conjunction with the artificial bee colony (ABC) optimiser. The main results are the significance of each physico-chemical parameter on the hydrogen gas production through innovative modelling and the foretelling of the HGP. Additionally, when this novel technique was employed on the observed dataset, a coefficient of determination and correlation coefficient equal to 0.9464 and 0.9751 were reached for the HGP estimate, respectively. The correspondence between observed data and the ABC/SVM-relied approximation showed the suitable effectiveness of this procedure.

Energy Self-Sufficiency Conditions of Ethanol Autothermal Reforming: a Simulation Study

Abstract Natural gas steam reforming is commonly used for hydrogen production. However, research has shown that ethanol autothermal reforming can produce cleaner hydrogen gas efficiently. Despite this, there is a lack of studies on the energy self-sufficiency conditions of the ethanol autothermal reform. In this paper, we use simulations and the Response Surface Methodology (RSM) for the multivariate analysis of the energy self-sufficiency conditions in this process. First, we constructed and validated an industrial flowchart. After that, RSM allowed us to assess the process variables effects. The process variables studied were temperature (0 to 1000 ºC), pressure (20 to 30 bar), steam/ethanol ratio (2 to 5 mol/mol) and O2/ethanol ratio (0 to 1.5 mol/mol). We observe that the temperature and steam/ethanol ratio increase have a positive effect on hydrogen production. On the contrary, the O2/ethanol ratio increase has a negative effect, and the pressure increase is not statistically significant on hydrogen production. Therefore, the pressure was used at its minimum level (20 bar) while the temperature and the steam/ethanol ratio at its maximum levels (1000 ºC and 5 mol/mol). We also evaluated the energy consumption for the Autothermal Reactor (ATR). The reactor consumed 477.92 kJ/mol ethanol to produce 5.12 mol H2/mol ethanol when we use 1000 ºC, 20 bar, steam/ethanol 5 mol/mol, and O2/ethanol 0 mol/mol. ATR's energy self-sufficiency is achieved by using 1000 ºC, 20 bar, steam/ethanol 5 mol/mol, and O2/ethanol 0.86 mol/mol. In these conditions, 3.95 mol H2/mol ethanol is produced with 0 kJ/mol ethanol.

Anoxic growth optimization for metal respiration and photobiological hydrogen production by arsenic-resistant Rhodopseudomonas and Rhodobacter species.

The current research focuses on anaerobic respiration of arsenic and other toxic metals by purple nonsulfur bacteria (PNSB). Among the optimization assays performed were carbon utilization, cross metal resistance, and metal respiration, along with a comparison of each assay in photoheterotrophic and chemoheterotrophic growth. The bacteria were identified by the classification of 16S ribosomal RNA gene sequences. Rhodobacter sp. PI3 proved to be more versatile in carbon source utilization (acetate, lactate, citrate, and oxalate), whereas Rhodopseudomonas palustris PI5 proved to be more versatile in metal resistance (arsenate, arsenite, cobalt, lead, selenium, and nickel). Both the strains were found to be positive for photofermentative hydrogen production along with arsenic respiration. This study reveals that anaerobic conditions are more appropriate for better efficiency of PNSB. Our study demonstrates that R. palustris PI5 and Rhodobacter sp. PI3 can be promising candidates for the biohydrogen production along with metal detoxification using heavy metal-polluted effluents as a substrate.

Photocatalytic Applications of Heterostructure Graphitic Carbon Nitride: Pollutant Degradation, Hydrogen Gas Production (water splitting), and CO2 Reduction.

Fabrication of the heterojunction composites photocatalyst has attained much attention for solar energy conversion due to their high optimization of reduction-oxidation potential as a result of effective separation of photogenerated electrons-holes pairs. In this review, the background of photocatalysis, mechanism of photocatalysis, and the several researches on the heterostructure graphitic carbon nitride (g-C3N4) semiconductor are discussed. The advantages of the heterostructure g-C3N4 over their precursors are also discussed. The conclusion and future perspectives on this emerging research direction are given. This paper gives a useful knowledge on the heterostructure g-C3N4 and their photocatalytic mechanisms and applications. IMPACT STATEMENTS: The paper on g-C3N4 Nano-based photocatalysts is expected to enlighten scientists on precise management and evaluating the environment, which may merit prospect research into developing suitable mechanism for energy, wastewater treatment and environmental purification.

Effects of the deletion of hup genes encoding the uptake hydrogenase on the activity of hydrogen production in the purple photosynthetic bacterium Rubrivivax gelatinosus IL144.

The efficiency of hydrogen gas production by nitrogenase in bacteria has been improved by the inhibition of antagonistic activity by the uptake hydrogenase. In this study, a mutant lacking the gene coding for the uptake hydrogenase was generated from the photosynthetic beta-proteobacterium Rubrivivax gelatinosus IL144 to explore new ways of hydrogen gas production driven by light energy. The mutant cells produced 25-30% higher amounts of molecular hydrogen than the wild-type cells under nitrogen-deficient conditions under light. Furthermore, by the addition of 5 mM glutamate, the photosynthetic growth rate was greatly enhanced, and the hydrogen gas production activity reached 41.1 (mmol/l) in the mutant.