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On the Cover
Vol. 10, Issue 2

Given the complexity and intricate nature of biofuel and bioproduct production systems, the demand for swift and precise modeling tools is evident to design, optimize, monitor, and control these systems. Machine learning holds immense potential to revolutionize the biofuel and bioproduct industry by enhancing processes, boosting efficiency, and fostering the emergence of sustainable solutions. By scrutinizing extensive datasets and detecting patterns, machine learning algorithms can fine-tune crucial parameters like feedstock selection, process conditions, and genetic engineering, leading to heightened yields and superior product quality. Predictive modeling and real-time monitoring further empower researchers to make well-informed decisions, curtail expenses, and optimize process control. Moreover, machine learning aids in identifying novel applications for waste streams, thus augmenting sustainability efforts. Overall, machine learning enables researchers to forge ahead in developing more efficient and sustainable approaches to biofuel and bioproduct production, propelling the world toward an eco-friendly and renewable future. In the June 2023 Issue of Biofuel Research Journal, the application of these techniques in producing biohydrogen (DOI: 10.18331/BRJ2023.10.2.4) and lignocellulosic ethanol (DOI: 10.18331/BRJ2023.10.2.5) was critically reviewed, and the future trends in this domain were presented. Cover art by BiofuelResJ. ©2023.


Biofuel Research Journal (BRJ) publishes high-quality original articles, review articles, case studies, book reviews, short communications, and hypotheses on the fundamentals, applications, processing, and management of biofuel and bioproduct research and technologies:
 

  • Biofuels
  • Bioproducts (including biocomposites and bio-based smart materials)
  • Biodiesel
  • Bioalcohols (bioethanol, biobutanol, etc.)
  • Biogas (biomethane & biohydrogen)
  • Biomass valorization
  • Algal biofuels & bioproducts
  • Bioprocess (bioreactions, bioreactors, membrane-bioreactors, fermentation, etc.)
  • Biorefineries for biofuels & bioproducts
  • Applied Microbiology
  • Combustion
  • Bioresource technologies associated with the conversion or production of biofuels & bioproducts

Moreover, novel and integrated biofuel & bioproduct processing and hybrid systems, as well as energy audits for biofuel & bioproduct production plants, are of interest. The journal also seeks to publish articles with a focus on the application of artificial photosynthesis for biofuels production, carbon footprint analysis, strategies for limiting greenhouse gas (GHG) emissions, life cycle assessment (LCA), and exergy analysis of biofuel & bioproduct production/application pathways, compliance with the international standards (such as PAS 2050:2011 and ISO 14040:2006), techno-economic analysis of biofuel & bioproduct production/application, impacts of biofuel & bioproduct production/consumption on climate change, futuristic pathways for biofuel & bioproduct production, and promotion of biofuel  & bioproduct applications in the developing world for indigenous development. In addition to the above, BRJ also considers articles with a focus on biofuels & bioproducts in Circular Economy as well as biofuels & bioproducts finance.

Biofuel Research Journal is indexed in Scopus and Web of Science.

BRJ does not charge any submission or publication fees. 

Editor-in-Chief: Vijai Kumar Gupta

 

> View Full Editorial Board

Current Issue: Volume 10, Issue 2, June 2023, Pages 1816-1875 

Review Paper

Machine learning in biohydrogen production: a review

Pages 1844-1858

10.18331/BRJ2023.10.2.4

Avinash Alagumalai; Balaji Devarajan; Hua Song; Somchai Wongwises; Rodrigo Ledesma-Amaro; Omid Mahian; Mikhail Sheremet; Eric Lichtfouse

Machine learning in biohydrogen production: a review