Machine Learning Applications in Polymeric Biomaterials
A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Biomacromolecules, Biobased and Biodegradable Polymers".
Deadline for manuscript submissions: closed (25 August 2023) | Viewed by 3712
Special Issue Editors
Interests: bionanomaterials; bionanotechnology; machine learning; drug discovery; deep learning
Interests: biomaterials; biocomposites; biofabrication; biomechanics; biomedical implants; nanomaterials; nanocomposites; nanotechnology; rapid prototyping technology; rehabilitation engineering; stem cells; tissue engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Polymers are the largest and most versatile class of biomaterials extensively applied for therapeutic applications. From natural to synthetic polymers, the possibilities to design and modify their physical–chemical properties make these systems of great interest in a wide range of biomedical applications as diverse as drug delivery systems, organ-on-a-chip, diagnostics, tissue engineering, and so on.
While there is constant evolution and innovation in materials with time, biomaterials research has been hampered by the relatively long development period required. With rapid advances in computational power, machine learning (ML) has boomed as an effective tool to discover new materials. The combination of machine learning with high-throughput theoretical predictions and high-throughput experiments has shifted from the traditional trial and error paradigm to a data-driven paradigm. In the field of polymers, ML has also found its applications in finding new materials with the desired performance.
The purpose of this Special Issue is to highlight recent achievements from biomaterials discovery and characteristic prediction to final applications in the field of biomedicine.
Dr. Muhammad E. H. Chowdhury
Prof. Dr. Md. Enamul Hoque
Guest Editors
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. Polymers is an international peer-reviewed open access semimonthly 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 2700 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.
Keywords
- machine learning framework for polymer discovery
- machine learning in polymerization process
- prediction of organic materials
- machine learning for the nanomaterials–biology interface
- prediction of tensile strength of polymer
- prediction in the biomedical effects of nanomaterial application
- machine learning for drug discovery
