Featuring Selected Contributions for International Conference on Biomaterials and Biofabrication: Emerging Technologies

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Nanobiotechnology and Biofabrication".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1002

Special Issue Editors


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Guest Editor
Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA
Interests: nanomaterials; drug delivery; tissue engineering; in-space biotechnology
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Biomedical Engineering, University of Connecticut Health Center L6085, 263 Farmington Ave., Farmington, CT 06030, USA
Interests: tissue engineering; regenerative medicine; biomanufacturing; wound care; 3D printing
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Guest Editor
Laboratoire d’Ingénierie des Biomolécules (LIBio), Université de Lorraine, 54518 Vandoeuvre CEDEX, France
Interests: nanoliposome; biomaterials; molecular transfer; vectorization; multiscale characterization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Laboratoire d’Ingénierie des Biomolécules (LIBio), ENSAIA, Université de Lorraine, 54000 Nancy, France
Interests: stabilization of active molecules; food preservation and packaging

Special Issue Information

Dear Colleagues,

Biomaterials have been utilized by humans for millennia and represent the cornerstone of tissue engineering, regenerative medicine, and the bioencapsulation of active compounds. Biomaterial-based drug delivery systems are becoming more popular due to their improved delivery localization, longevity, and control. However, material composition is not the only important consideration in biomaterial development. The processes used to generate biomaterial structures also affect their use and function. Biofabrication techniques allow for precise control of biomaterial configuration. Researchers have developed an array of biofabrication tools and methods in this rapidly growing field, with improvements in technology and decreasing costs leading to increased democratization of their use. The "Biomaterials and Biofabrication: Emerging Technologies Conference and Workshop" aims to bring together researchers, scientists, and experts from various disciplines with an interest in biomaterials and biofabrication to explore and discuss the latest developments in the field. This Special Issue invites research and review papers from presenters, participants, and audience members of the conference with the goal of promoting emerging research in biomaterials and biofabrication.

Dr. Yupeng Chen
Dr. Ali Tamayol
Prof. Dr. Elmira Arab-Tehrany
Prof. Dr. Stéphane Desobry
Guest Editors

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Keywords

  • biomaterials
  • biofabrication
  • biotechnology

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Published Papers (1 paper)

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Review

26 pages, 1739 KiB  
Review
Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses
by Esra Imamoglu
Bioengineering 2024, 11(11), 1143; https://doi.org/10.3390/bioengineering11111143 - 13 Nov 2024
Viewed by 670
Abstract
This review examines the increasing application of artificial intelligence (AI) and/or machine learning (ML) in microalgae processes, focusing on their ability to improve production efficiency, yield, and process control. AI/ML technologies are used in various aspects of microalgae processes, such as real-time monitoring, [...] Read more.
This review examines the increasing application of artificial intelligence (AI) and/or machine learning (ML) in microalgae processes, focusing on their ability to improve production efficiency, yield, and process control. AI/ML technologies are used in various aspects of microalgae processes, such as real-time monitoring, species identification, the optimization of growth conditions, harvesting, and the purification of bioproducts. Commonly employed ML algorithms, including the support vector machine (SVM), genetic algorithm (GA), decision tree (DT), random forest (RF), artificial neural network (ANN), and deep learning (DL), each have unique strengths but also present challenges, such as computational demands, overfitting, and transparency. Despite these hurdles, AI/ML technologies have shown significant improvements in system performance, scalability, and resource efficiency, as well as in cutting costs, minimizing downtime, and reducing environmental impact. However, broader implementations face obstacles, including data availability, model complexity, scalability issues, cybersecurity threats, and regulatory challenges. To address these issues, solutions, such as the use of simulation-based data, modular system designs, and adaptive learning models, have been proposed. This review contributes to the literature by offering a thorough analysis of the practical applications, obstacles, and benefits of AI/ML in microalgae processes, offering critical insights into this fast-evolving field. Full article
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