Special Issue "Digital Bioprocessing and Fermentation Technology"
Deadline for manuscript submissions: 31 December 2023 | Viewed by 2911
Interests: bioreactor modelling; multivariate data analysis; machine learning; bioprocess; waste valorisation; enzyme technology; bioenergy; pharmaceutical products
Biological systems are often complex and difficult to optimize, automate, control and scale. Over decades of excellent research, significant time, effort and costs have been invested in our understanding of biological processes, creating substantial bodies of expert knowledge. Nonetheless, the fail-safe, resourceful and time-efficient exploration of the biological interactions and interconnectivities among a plethora of (bio)chemical variables in a biological system, such as a bioreactor, is still a far from trivial task. With this in mind, in recent years, a great deal of attention has been paid to the application of digital tools, namely, artificial intelligence (AI) and machine learning (ML) algorithms, statistical design of experiment (DoE) tools, computational fluid dynamics (CFD), process simulators and multivariate data analysis (MVDA), to mitigate the complexity of biochemical processes. Digitization—specifically with respect to the Fourth Industrial Revolution, described as Industry 4.0—is a state-of-the-art approach that integrates domain expert knowledge, including scientific principles, mechanistic descriptions and biological big data, with computer-based mathematical models, substantially transforming the ways in which researchers and industries formulate, create and analyse bioprocess data.
This Special Issue seeks to collect research articles and review papers investigating emerging computational solutions to address biochemical problems. This broad scope includes, but is not limited to, the modelling and simulation of cell cultures, microbial fermentation, cellular agriculture, waste valorisation, and agri-food and algal processes. Contributions that broaden the scope of expert-augmented ML modelling, scale-up/-down techniques, bioprocess simulations at scale, techno-economic assessments and environmental analysis are also welcomed.
Dr. Masih Karimi Alavijeh
Dr. Harini Narayanan
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fermentation is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- data analytics
- machine learning
- mechanistic models
- hybrid models
- computational fluid dynamics
- bioprocess optimization
- process analytical technology (PAT)
- multivariate data analysis
- time-series forecasting