Biomimicry and Functional Materials: 5th Edition

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Biomimetics of Materials and Structures".

Deadline for manuscript submissions: 15 January 2026 | Viewed by 1299

Special Issue Editors


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Guest Editor
School of Chemical Engineering and Translational Nanobioscience Research Center, Sungkyunkwan University, Seoul, Republic of Korea
Interests: biomembranes; biointerfacial science; supported lipid bilayers
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Healthcare and Biomedical Engineering, Chonnam National University, Yeosu 59626, Republic of Korea
Interests: antimicrobial lipids; lipid membrane biotechnology; biosensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biomimicry is a highly sought-out feature in various research fields and applications, such as biointerfacial science and biosensors, where natural biological structures and/or properties are required and/or desired for the intended functions. This is achieved by using functional materials that are built with inspiration from biology via bottom-up self-assembly and/or the top-down process to replicate various aspects of biology. This allows for control over those aspects with reproducibility and the ability to finetune, which otherwise is limited in biology, so that relevant research and application needs are met.     

In this Special Issue, we welcome a wide range of research works, from fundamental studies to applications dealing with biofunctional materials. The goal of this Special Issue is to present and promote the valuable contributions of researchers and scientists across different disciplines to the development and applications of bioinspired and biomimetic functional materials, which will benefit the scientific community, and, hopefully, society at large.            

Dr. Tun Naw Sut
Dr. Bo Kyeong Yoon
Guest Editors

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Keywords

  • biomimetic systems
  • bioinspired materials
  • functional biomaterials
  • biointerfaces
  • bioengineering
  • biotechnology

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Published Papers (2 papers)

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13 pages, 4063 KiB  
Article
Outcomes of Regenerative Endodontic Therapy Using Dehydrated Human-Derived Amnion–Chorion Membranes and Collagen Matrices: A Retrospective Analysis
by Anjali K. Dave, Julia Y. Cheung and Sahng G. Kim
Biomimetics 2025, 10(8), 530; https://doi.org/10.3390/biomimetics10080530 - 13 Aug 2025
Viewed by 406
Abstract
Dehydrated human-derived amnion–chorion membranes (ACM), known for their bioactive composition of growth factors and cytokines, have demonstrated potential as a bioactive scaffold in regenerative medicine; however, their clinical application in regenerative endodontic procedures (REPs) remains unexplored. This retrospective study aimed to evaluate the [...] Read more.
Dehydrated human-derived amnion–chorion membranes (ACM), known for their bioactive composition of growth factors and cytokines, have demonstrated potential as a bioactive scaffold in regenerative medicine; however, their clinical application in regenerative endodontic procedures (REPs) remains unexplored. This retrospective study aimed to evaluate the clinical and radiographic outcomes of REPs using ACM compared to collagen matrices (CM) in immature necrotic permanent teeth. Forty-one immature necrotic teeth from 38 patients (mean age: 14.68 ± 7.43 years) were treated with REPs using either ACM (n = 21) or CM (n = 20) scaffolds over a mean follow-up period of 23.23 months. Outcomes assessed included survival, success, root development measured by radiographic root area (RRA), and pulp sensibility. Independent t-tests compared outcomes between groups, while Cox regression and generalized linear models identified predictors of treatment outcomes. Overall survival and success rates were 87.8% and 82.9%, respectively. ACM-treated teeth achieved 90.5% survival and 85.7% success rates, while CM-treated teeth demonstrated 85.0% survival and 80.0% success rates, with no statistically significant differences between groups (p > 0.05). Root development occurred in 85.4% of cases overall, with significant RRA increases of 13.89 ± 13.95% for ACM and 11.24 ± 11.21% for CM (p < 0.05 within each group). Pulp sensibility recovery was observed in 51.2% of treated teeth overall, with 42.9% for ACM-treated teeth and 55.0% for CM-treated teeth (p > 0.05). Notably, ACM-treated teeth demonstrated earlier sensibility recovery compared to those of CM-treated teeth. Age was identified as a significant negative predictor of root development outcomes (p < 0.05). This clinical study demonstrates that both ACM and CM are clinically effective scaffolds for REPs, achieving high survival rates and promoting root development in immature necrotic teeth. While overall success rates were comparable, ACM showed faster sensibility recovery, suggesting potential biological advantages for enhanced tissue regeneration and earlier functional recovery. Full article
(This article belongs to the Special Issue Biomimicry and Functional Materials: 5th Edition)
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18 pages, 4607 KiB  
Article
Multi-Objective Machine Learning Optimization of Cylindrical TPMS Lattices for Bone Implants
by Mansoureh Rezapourian, Ali Cheloee Darabi, Mohammadreza Khoshbin and Irina Hussainova
Biomimetics 2025, 10(7), 475; https://doi.org/10.3390/biomimetics10070475 - 18 Jul 2025
Viewed by 720
Abstract
This study presents a multi-objective optimization framework for designing cylindrical triply periodic minimal surface (TPMS) lattices tailored for bone implant applications. Using an artificial neural network (ANN) as a surrogate model trained on simulated data, four key properties—ultimate stress (U), energy absorption (EA), [...] Read more.
This study presents a multi-objective optimization framework for designing cylindrical triply periodic minimal surface (TPMS) lattices tailored for bone implant applications. Using an artificial neural network (ANN) as a surrogate model trained on simulated data, four key properties—ultimate stress (U), energy absorption (EA), surface area-to-volume ratio (SA/VR), and relative density (RD)—were predicted from seven lattice design parameters. To address anatomical variability, a novel implant size-based categorization (small, medium, and large) was introduced, and separate optimization runs were conducted for each group. The optimization was performed via the NSGA-II algorithm to maximize mechanical performance (U and EA) and surface efficiency (SA/VR), while filtering for biologically relevant RD values (20–40%). Separate optimization runs were conducted for small, medium, and large implant size groups. A total of 105 Pareto-optimal designs were identified, with 75 designs retained after RD filtering. SHapley Additive exPlanations (SHAP) analysis revealed the dominant influence of thickness and unit cell size on target properties. Kernel density and boxplot comparisons confirmed distinct performance trends across size groups. The framework effectively balances competing design goals and enables the selection of size-specific lattices. The proposed approach provides a reproducible pathway for optimizing bioarchitectures, with the potential to accelerate the development of lattice-based implants in personalized medicine. Full article
(This article belongs to the Special Issue Biomimicry and Functional Materials: 5th Edition)
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