A perspective-driven and technical evaluation of machine learning in bioreactor scale-up: A case-study for potential model developments.

Bioreactor scale-up and scale-down have always been a topical issue for the biopharmaceutical industry and despite considerable effort, the identification of a fail-safe strategy for bioprocess development across scales remains a challenge. With the ubiquitous growth of digital transformation technologies, new scaling methods based on computer models may enable more effective scaling. This study aimed to evaluate the potential application of machine learning (ML) algorithms for bioreactor scale-up, with a specific focus on the prediction of scaling parameters.

Biochemical production of bioenergy from agricultural crops and residue in Iran.

The present study assessed the potential for biochemical conversion of energy stored in agricultural waste and residue in Iran. The current status of agricultural residue as a source of bioenergy globally and in Iran was investigated. The total number of publications in this field from 2000 to 2014 was about 4294.

A combined model for large scale batch culture MFC-digester with various wastewaters through different populations.

In this study, a new model of microbial fuel cell (MFC) was obtained for the first time. The modeled MFC was made using a combination of two approaches; the conduction-based method and two-step anaerobic digestion. Performance of the MFC was based on calculations for current evolution and polarization curves with different subsequent variables of the biofilm and anolyte.