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Design and Flight Experiment of a Motor-Directly-Driven Flapping-Wing Micro Air Vehicle with Extension Springs -
Multifunctional Liposomes: Smart Nanomaterials for Enhanced Photodynamic Therapy -
Development of Variable Elastic Band with Adjustable Elasticities for Semi-Passive Exosuits -
Regenerative Strategies for Vocal Fold Repair Using Injectable Materials
Journal Description
Biomimetics
Biomimetics
is an international, peer-reviewed, open access journal on biomimicry and bionics, published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Ei Compendex, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q1 (Engineering, Multidisciplinary) / CiteScore - Q2 (Biomedical Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.1 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the first half of 2025).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.9 (2024);
5-Year Impact Factor:
4.0 (2024)
Latest Articles
Organ-on-a-Chip and Lab-on-a-Chip Technologies in Cardiac Tissue Engineering
Biomimetics 2026, 11(1), 18; https://doi.org/10.3390/biomimetics11010018 (registering DOI) - 30 Dec 2025
Abstract
Microfluidic technologies have ushered in a new era in cardiac tissue engineering, providing more predictive in vitro models compared to two-dimensional culture studies. This review examines Organ-on-a-Chip (OoC) and Lab-on-a-Chip (LoC) platforms, with a specific focus on cardiovascular applications. OoCs, and particularly Heart-on-a-Chip
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Microfluidic technologies have ushered in a new era in cardiac tissue engineering, providing more predictive in vitro models compared to two-dimensional culture studies. This review examines Organ-on-a-Chip (OoC) and Lab-on-a-Chip (LoC) platforms, with a specific focus on cardiovascular applications. OoCs, and particularly Heart-on-a-Chip systems, have advanced biomimicry to a higher level by recreating complex 3D cardiac microenvironments in vitro and dynamic fluid flow. These platforms employ induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), engineered extracellular matrices, and dynamic mechanical and electrical stimulation to reproduce the structural and functional features of myocardial tissue. LoCs have introduced miniaturization and integration of analytical functions into compact devices, enabling high-throughput screening, advanced diagnostics, and efficient pharmacological testing. They enable the investigation of pathophysiological mechanisms, the assessment of cardiotoxicity, and the development of precision medicine approaches. Furthermore, progress in multi-organ systems expands the potential of microfluidic technologies to simulate heart–liver, heart–kidney, and heart–tumor interactions, providing more comprehensive predictive models. However, challenges remain, including the immaturity of iPSC-derived cells, the lack of standardization, and scalability issues. In general, microfluidic platforms represent strategic tools for advancing cardiovascular research in translation and accelerating therapeutic innovation within precision medicine.
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(This article belongs to the Special Issue Advancing Tissue Engineering and Regenerative Medicine Using Next-Gen Biomaterials)
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Open AccessReview
Bio-Inspired Reactive Approaches for Automated Guided Vehicle Path Planning: A Review
by
Shiwei Lin, Jianguo Wang and Xiaoying Kong
Biomimetics 2026, 11(1), 17; https://doi.org/10.3390/biomimetics11010017 (registering DOI) - 30 Dec 2025
Abstract
Automated guided vehicle (AGV) path planning aims to obtain an optimal path from the start point to the target point. Path planning methods are generally divided into classical algorithms and reactive algorithms, and this paper focuses on reactive algorithms. Reactive algorithms are classified
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Automated guided vehicle (AGV) path planning aims to obtain an optimal path from the start point to the target point. Path planning methods are generally divided into classical algorithms and reactive algorithms, and this paper focuses on reactive algorithms. Reactive algorithms are classified into swarm intelligence algorithms and artificial intelligence algorithms, and this paper reviews relevant studies from the past six years (2019–2025). This review involves 123 papers: 81 papers are about reactive algorithms, 44 are based on the swarm intelligence algorithm, and 37 are based on artificial intelligence algorithms. The main categories of swarm intelligence algorithms include particle swarm optimization, ant colony optimization, and genetic algorithms. Neural networks, reinforcement learning, and fuzzy logic represent the main trends in artificial intelligence–based algorithms. Among the cited papers, 45.68% achieve online implementations, and 33.33% address multi-AGV systems. Swarm intelligence algorithms are suitable for static or simplified dynamic environments with a low computational complexity and fast convergence, as 79.55% of papers are based on a static environment and 22.73% achieve online path planning. Artificial intelligence algorithms are effective for dealing with dynamic environments, which contribute 72.97% to online implementation and 54.05% to dynamic environments, while they face the challenge of robustness and the sim-to-real problem.
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(This article belongs to the Section Biological Optimisation and Management)
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Open AccessArticle
Flexural Strength of Different Restorative Materials Used for Direct Restoration in Pediatric Dentistry: An In Vitro Study
by
Ioana Elena Lile, Carolina Cojocariu, Ciprian Pasca, Andra-Alexandra Stăncioiu, Luminiţa Ligia Vaida and Diana Marian
Biomimetics 2026, 11(1), 16; https://doi.org/10.3390/biomimetics11010016 (registering DOI) - 29 Dec 2025
Abstract
Background: Preservation of tooth structure is a key principle in pediatric dentistry, where restorative materials must balance mechanical strength with the preservation of pulp vitality and minimally invasive techniques. The aim of this in vitro study, as it relates to pediatric dentistry, was
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Background: Preservation of tooth structure is a key principle in pediatric dentistry, where restorative materials must balance mechanical strength with the preservation of pulp vitality and minimally invasive techniques. The aim of this in vitro study, as it relates to pediatric dentistry, was to investigate the flexural strength of common composite resins, glass ionomer cements, and resin-modified glass ionomer cement within standardized and homogeneous laboratory conditions. Methods: This study evaluated the flexural strength of seven restorative materials: four composites (Filtek™ Z250, Filtek™ Supreme XT, Gradia, Premise), two GICs (Ketac™ Molar Easymix, GC Fuji IX GP), and one RMGIC (Vitremer). Standardized specimens were prepared and tested using a three-point bending protocol with a universal testing machine (Zwick-Roell Z005). A total of 49 specimens were fabricated and analyzed. Statistical analysis was performed with a one-way ANOVA followed by Tukey’s post hoc test. Results: The flexural strength value of composite resins was significantly greater than that of the glass ionomer and resin-modified glass ionomer cements (p < 0.001). Filtek™ Z250 had the highest flexural strength, and Vitremer, a resin-modified glass ionomer cement, exhibited intermediate performance. Ketac™ Molar Easymix had the lowest values among conventional glass ionomer cements, whilst the flexural strength values obtained for GC Fuji IX GP were similar to some composite materials but with higher variability. Conclusions: Composite resins remain the most durable option for pediatric restorations in stress-bearing areas, whereas RMGICs provide a compromise between mechanical performance and biological advantages such as fluoride release and biocompatibility. Conventional GICs, despite their lower flexural strength, retain clinical relevance in low-load sites and for patients at a high risk of caries. Material selection in pediatric dentistry should therefore be tailored to the child’s age, tooth location, and functional demands to ensure long-lasting, minimally invasive restorations. This study involved only mechanical properties alone, and biological aspects, such as fluoride release and biocompatibility, were not considered. Material selection in pediatric dentistry should therefore take into account mechanical requirements, restorative location, and clinical environment.
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(This article belongs to the Section Biomimetics of Materials and Structures)
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Open AccessArticle
Biomimetic Assessment of 3D-Printed T-Shape Joints Bio-Inspired by the Stem-Branch Junction in Common Ash (Fraxinus excelsior L.) Trees
by
Rastislav Lagaňa, Roman Nôta, Zuzana Tončíková, Tomáš Holeček, Nadežda Langová and Jaroslav Ďurkovič
Biomimetics 2026, 11(1), 15; https://doi.org/10.3390/biomimetics11010015 - 28 Dec 2025
Abstract
The stem–branch junction in trees demonstrates exceptional structural design. This study examined two key features of the branch junction in common ash (Fraxinus excelsior L.) wood: the interlocked area (ILA) formed above a knot and the spatial arrangement of fibers in the
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The stem–branch junction in trees demonstrates exceptional structural design. This study examined two key features of the branch junction in common ash (Fraxinus excelsior L.) wood: the interlocked area (ILA) formed above a knot and the spatial arrangement of fibers in the junction. Bio-inspired by the microstructural features revealed by micro-computed tomography imaging, we developed 3D-printed models and compared their mechanical performance to standard symmetrical T-joints. We evaluated the models using mechanical tests and finite element modeling (FEM). Asymmetrical 3D-printed joints mimicking vessel and fiber distribution in the stem–branch junction were 2% stiffer in the elastic region than symmetrical joints and showed, on average, 10% lower deflection at failure. While the ILA had minimal effect on elastic stiffness, measured surface strain analysis indicated that it positively influenced the redistribution of shear strain in the junctions. Thanks to the bio-inspired design, the joints were stiffer and can be utilized in multiple design configurations while maintaining the same underlying principle.
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(This article belongs to the Section Biomimetics of Materials and Structures)
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Biomimetic Approach to Designing Trust-Based Robot-to-Human Object Handover in a Collaborative Assembly Task
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S. M. Mizanoor Rahman
Biomimetics 2026, 11(1), 14; https://doi.org/10.3390/biomimetics11010014 - 27 Dec 2025
Abstract
We presented a biomimetic approach to designing robot-to-human handover of objects in a collaborative assembly task. We developed a human–robot hybrid cell where a human and a robot collaborated with each other to perform the assembly operations of a product in a flexible
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We presented a biomimetic approach to designing robot-to-human handover of objects in a collaborative assembly task. We developed a human–robot hybrid cell where a human and a robot collaborated with each other to perform the assembly operations of a product in a flexible manufacturing setup. Firstly, we investigated human psychology and biomechanics (kinetics and kinematics) for human-to-robot handover of an object in the human–robot collaborative set-up in three separate experimental conditions: (i) human possessed high trust in the robot, (ii) human possessed moderate trust in the robot, and (iii) human possessed low trust in the robot. The results showed that human psychology was significantly impacted by human trust in the robot, which also impacted the biomechanics of human-to-robot handover, i.e., human hand movement slowed down, the angle between human hand and robot arm increased (formed a braced handover configuration), and human grip forces increased if human trust in the robot decreased, and vice versa. Secondly, being inspired by those empirical results related to human psychology and biomechanics, we proposed a novel robot-to-human object handover mechanism (strategy). According to the novel handover mechanism, the robot varied its handover configurations and motions through kinematic redundancy with the aim of reducing potential impulse forces on the human body through the object during the handover when robot trust in the human was low. We implemented the proposed robot-to-human handover mechanism in the human–robot collaborative assembly task in the hybrid cell. The experimental evaluation results showed significant improvements in human–robot interaction (HRI) in terms of transparency, naturalness, engagement, cooperation, cognitive workload, and human trust in the robot, and in overall performance in terms of handover safety, handover success rate, and assembly efficiency. The results can help design and develop human–robot handover mechanisms for human–robot collaborative tasks in various applications such as industrial manufacturing and manipulation, medical surgery, warehouse, transport, logistics, construction, machine shops, goods delivery, etc.
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(This article belongs to the Special Issue Human-Inspired Grasp Control in Robotics 2025)
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Open AccessArticle
Mitigating Neural Habituation in Insect Bio-Bots: A Dual-Timescale Adaptive Control Approach
by
Le Minh Triet and Nguyen Truong Thinh
Biomimetics 2026, 11(1), 13; https://doi.org/10.3390/biomimetics11010013 - 27 Dec 2025
Abstract
Bio-cybernetic organisms combine biological locomotion with electronic control but face significant challenges regarding individual variability and stimulus habituation. This study introduces an Adaptive Neuro-Fuzzy Inference System (ANFIS) designed to dynamically calibrate to individual Gromphadorhina portentosa specimens. Using a miniaturized neural controller, we compared
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Bio-cybernetic organisms combine biological locomotion with electronic control but face significant challenges regarding individual variability and stimulus habituation. This study introduces an Adaptive Neuro-Fuzzy Inference System (ANFIS) designed to dynamically calibrate to individual Gromphadorhina portentosa specimens. Using a miniaturized neural controller, we compared ANFIS’s performance against natural behavior and non-adaptive control methods. Results demonstrate ANFIS’s superiority: obstacle navigation efficiency reached 81% (compared to 42% for non-adaptive methods), and effective behavioral modulation was sustained for 47 min (versus 26 min). Furthermore, the system achieved 73% target acquisition in complex terrain and maintained stimulus responsiveness 3.5-fold longer through sophisticated habituation compensation. Biocompatibility assessments confirmed interface functionality over 14-day periods. This research establishes foundational benchmarks for arthropod bio-cybernetics, demonstrating that adaptive neuro-fuzzy architectures significantly outperform conventional methods, enabling robust bio-hybrid platforms suitable for confined-space search-and-rescue operations.
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(This article belongs to the Special Issue Advancements in Nature-Inspired Engineering: Integrating Biomimicry into Modern Design Practices)
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Open AccessReview
Biomimetic Strategies for Bone Regeneration: Smart Scaffolds and Multiscale Cues
by
Sheikh Md Mosharof Hossen, Md Abdul Khaleque, Min-Su Lim, Jin-Kyu Kang, Do-Kyun Kim, Hwan-Hee Lee and Young-Yul Kim
Biomimetics 2026, 11(1), 12; https://doi.org/10.3390/biomimetics11010012 - 27 Dec 2025
Abstract
Bone regeneration remains difficult due to the complex bone microenvironment and the limited healing capacity of large defects. Biomimetic strategies offer promising solutions by using advanced 3D scaffolds guided by natural tissue cues. Recent advances in additive manufacturing, nanotechnology, and tissue engineering now
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Bone regeneration remains difficult due to the complex bone microenvironment and the limited healing capacity of large defects. Biomimetic strategies offer promising solutions by using advanced 3D scaffolds guided by natural tissue cues. Recent advances in additive manufacturing, nanotechnology, and tissue engineering now allow the fabrication of hierarchical scaffolds that closely mimic native bone. Smart scaffold systems combine materials with biochemical and mechanical signals. These features improve vascularization, enhance tissue integration, and support better regenerative outcomes. Bio-inspired materials also help connect inert implants with living tissues by promoting vascular network formation and improving cell communication. Multiscale design approaches recreate bone nano- to macro-level structure and support both osteogenic activity and immune regulation. Intelligent and adaptive scaffolds are being developed to respond to physiological changes and enable personalized bone repair. This review discusses the current landscape of biomimetic scaffold design, fabrication techniques, material strategies, biological mechanisms, and translational considerations shaping next-generation bone regeneration technologies. Future directions focus on sustainable, clinically translatable biomimetic systems that can integrate with digital health tools for improved treatment planning.
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(This article belongs to the Special Issue Advances in Bio-Inspired Design and Characterization of 3D-Printed Multimaterial Composites and Heterogeneous Structures)
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Open AccessArticle
Towards Biomimetic Robotic Rehabilitation: Pilot Study of an Upper-Limb Cable-Driven Exoskeleton in Post-Stroke Patients
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Develyn I. S. Bastos, Sergio C. M. Gomes, Eduardo A. F. Dias, Pedro H. F. Ulhoa, Raphaele C. J. S. Gomes, Fabiana D. Marinho and Rafhael M. Andrade
Biomimetics 2026, 11(1), 11; https://doi.org/10.3390/biomimetics11010011 - 26 Dec 2025
Abstract
Stroke is a leading cause of disability, often resulting in motor, cognitive, and language deficits, with significant impact on upper-limb function. Robotic therapy (RT) has emerged as an effective strategy, providing intensive, repetitive, and adaptable practice to optimize functional recovery. This pilot study
[...] Read more.
Stroke is a leading cause of disability, often resulting in motor, cognitive, and language deficits, with significant impact on upper-limb function. Robotic therapy (RT) has emerged as an effective strategy, providing intensive, repetitive, and adaptable practice to optimize functional recovery. This pilot study aimed to describe and evaluate the effects of robotic rehabilitation as a complement to conventional therapy, using a biomimetic activities-of-daily-living (ADL)-based protocol, on upper-limb function in post-stroke patients. Three participants (aged 30–80 years) undergoing occupational and/or physiotherapy received individualized robotic training with a lightweight cable-driven upper-limb exoskeleton, m-FLEX™, twice a week for ten weeks (30 min per session). Movements were designed to mimic natural upper-limb actions, including elbow flexion-extension, forearm pronation-supination, tripod pinch, and functional tasks such as grasping a cup. Assessments included the Fugl-Meyer (FM) scale, the Functional Independence Measure (FIM), and device satisfaction, performed at baseline, mid-intervention, and post-intervention. Descriptive analysis of the tabulated data revealed improvements in range of motion and functional outcomes. These findings suggest that biomimetic protocol of robotic rehabilitation, when combined with conventional therapy, can enhance motor and functional recovery in post-stroke patients.
Full article
(This article belongs to the Special Issue Bionic Technology—Robotic Exoskeletons and Prostheses: 3rd Edition)
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Open AccessArticle
Binary Pufferfish Optimization Algorithm for Combinatorial Problems
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Broderick Crawford, Álex Paz, Ricardo Soto, Álvaro Peña Fritz, Gino Astorga, Felipe Cisternas-Caneo, Claudio Patricio Toledo Mac-lean, Fabián Solís-Piñones, José Lara Arce and Giovanni Giachetti
Biomimetics 2026, 11(1), 10; https://doi.org/10.3390/biomimetics11010010 - 25 Dec 2025
Abstract
Metaheuristics are a fundament pillar of Industry 4.0, as they allow for complex optimization problems to be solved by finding good solutions in a reasonable amount of computational time. One category of important problems in modern industry is that of binary problems, where
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Metaheuristics are a fundament pillar of Industry 4.0, as they allow for complex optimization problems to be solved by finding good solutions in a reasonable amount of computational time. One category of important problems in modern industry is that of binary problems, where decision variables can take values of zero or one. In this work, we propose a binary version of the Pufferfish optimization algorithm (BPOA), which was originally created to solve continuous problems. The binary mapping follows a two-step technique, first transforming using transfer functions and then discretizing using binarization rules. We study representative pairings of transfer functions and binarization rules, comparing our algorithm with Particle Swarm Optimization, Secretary Bird Optimization Algorithm, and Arithmetic Optimization Algorithm with identical computational budgets. To validate its correct functioning, we solved binary problems present in industry, such as the Set Covering Problem together with its Unicost variant, as well as the Knapsack Problem. The results we achieved with regard to these problems were promising and statistically validated. The tests performed on the executions indicate that many pair differences are not statistically significant when both methods are already close to the optimal level, and significance arises precisely where the descriptive gaps widen, underscoring that transfer–rule pairing is the main performance factor. BPOA is a competitive and flexible framework whose effectiveness is mainly governed by the discretization design.
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(This article belongs to the Special Issue Advances in Biological and Bio-Inspired Algorithms)
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Open AccessArticle
Quantifying Nature’s Bistability: Simulation of Earwig Fan Folding
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Nele Binder, Leone Costi, Dario Izzo and Tobias Seidl
Biomimetics 2026, 11(1), 9; https://doi.org/10.3390/biomimetics11010009 - 24 Dec 2025
Abstract
In this work, a numerical tool is presented to simulate the dynamics of insect wing folding by example of the fan folding of the dermapteran hindwing. The scalability of the system is demonstrated by generalising the mechanical behaviour from the small geometry of
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In this work, a numerical tool is presented to simulate the dynamics of insect wing folding by example of the fan folding of the dermapteran hindwing. The scalability of the system is demonstrated by generalising the mechanical behaviour from the small geometry of the wing to a suitable scale for engineering applications, such as deployable structures for space applications. The tool is written in Python and based on the MuJoCo physics engine. Sections of the anal fan are modelled as a bar-and-hinge model with elastic tendons, allowing a high number of design parameters and fast computation. In light of these advantages, the wing folding and unfolding behaviour is investigated with respect to the tendon’s elastic properties and the actuation of the deformation. Bistability is characterised using a single tendon and the entire fan section. Given the upscaled geometry of the analysed section, the required tendon characteristics to transition between the stable states are identified within a reasonable range for technological transfer towards biomimetic structures modelled after the dermapteran hindwing.
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(This article belongs to the Section Biomimetics of Materials and Structures)
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Open AccessArticle
Composites Based on Collagen, Chondroitin Sulfate, and Sage Oil with Potential Use in Dentistry
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Bogdan Valeriu Sorca, Ana-Maria Rosca, Durmuş Alpaslan Kaya, Sergiu-Marian Vatamanu, Mădălina Georgiana Albu Kaya, Cristina Elena Dinu-Pîrvu, Mihaela Violeta Ghica, Alina Elena Coman, Laura Cristina Rusu and Irina Titorencu
Biomimetics 2026, 11(1), 8; https://doi.org/10.3390/biomimetics11010008 - 24 Dec 2025
Abstract
Osseointegration in dental implants involves the use of materials that mimic the bone tissue, with special properties such as biocompatibility and biodegradability. In this study, we describe the preparation and characterization of composites based on collagen, chondroitin sulfate, and sage oil obtained by
[...] Read more.
Osseointegration in dental implants involves the use of materials that mimic the bone tissue, with special properties such as biocompatibility and biodegradability. In this study, we describe the preparation and characterization of composites based on collagen, chondroitin sulfate, and sage oil obtained by freeze-drying method. Their morphological structures were determined by water uptake and scanning electron microscopy, the physical–chemical interactions between components by FT-IR, the stability by in vitro collagenase degradation, and the results indicate that the samples’ properties are highly influenced by the hydrophobic and hydrophilic character of sage essential oil and chondroitin sulfate, respectively, concluding that we can design a formulation with certain properties. The composite spongious forms were evaluated for cytocompatibility using the MG63 osteoblast cell line and subjected to histological observation. The results showed that the samples with sage essential oil were most resistant to enzymatic degradation, and the ones with chondroitin sulfate promoted the deposition of an abundant extracellular matrix. Taken together, the results suggest that incorporating chondroitin sulfate and sage oil in a controlled manner into collagen scaffolds represents a promising approach for enhancing bone tissue regeneration.
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(This article belongs to the Section Biomimetics of Materials and Structures)
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A Novel Gudermannian Function-Driven Controller Architecture Optimized by Starfish Optimizer for Superior Transient Performance of Automatic Voltage Regulation
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Davut Izci, Serdar Ekinci, Mostafa Jabari, Behçet Kocaman, Burcu Bektaş Güneş, Enver Adas and Mohd Ashraf Ahmad
Biomimetics 2026, 11(1), 7; https://doi.org/10.3390/biomimetics11010007 - 23 Dec 2025
Abstract
This paper proposes a Gudermannian function-based proportional–integral–derivative (G-PID) controller to enhance the transient performance of automatic voltage regulator (AVR) systems operating under highly dynamic conditions. By embedding the smooth and bounded nonlinear mapping of the Gudermannian function into the classical PID structure, the
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This paper proposes a Gudermannian function-based proportional–integral–derivative (G-PID) controller to enhance the transient performance of automatic voltage regulator (AVR) systems operating under highly dynamic conditions. By embedding the smooth and bounded nonlinear mapping of the Gudermannian function into the classical PID structure, the proposed controller improves adaptability to large signal variations while effectively suppressing overshoot. The controller parameters are optimally tuned using the starfish optimization algorithm (SFOA), which provides a robust balance between exploration and exploitation in nonlinear search spaces. Simulation results demonstrate that the SFOA-optimized G-PID controller achieves superior transient performance, with a rise time of 0.0551 s, zero overshoot, and a settling time of 0.0830 s. Comparative evaluations confirm that the proposed approach outperforms widely used optimization algorithms (particle swarm optimization, grey wolf optimizer, success history-based adaptive differential evolution with linear population size, and Kirchhoff’s law algorithm) and advanced AVR control schemes, including fractional-order and higher-order PID-based designs. These results indicate that the proposed SFOA optimized G-PID controller offers a computationally efficient and structurally simple solution for high-performance voltage regulation in modern power systems.
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(This article belongs to the Section Bioinspired Sensorics, Information Processing and Control)
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Open AccessArticle
Enhancing Flight Connectivity via Synchronization of Arrivals and Departures in Hub Airports with Evolutionary and Swarm-Based Metaheuristics
by
Halil Ibrahim Demir and Suraka Dervis
Biomimetics 2026, 11(1), 6; https://doi.org/10.3390/biomimetics11010006 - 23 Dec 2025
Abstract
Global air transport has become the dominant mode of long-distance travel, carrying more than four billion passengers in 2019 and projected to exceed 8 billion by 2040. Nevertheless, limited demand and economic inefficiencies often make direct connections unfeasible, forcing many passengers to rely
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Global air transport has become the dominant mode of long-distance travel, carrying more than four billion passengers in 2019 and projected to exceed 8 billion by 2040. Nevertheless, limited demand and economic inefficiencies often make direct connections unfeasible, forcing many passengers to rely on transfers. In such cases, synchronizing arrivals and departures at hub airports is crucial to minimizing transfer times and maximizing passenger retention. This study investigates the synchronization problem at Istanbul Airport, one of the world’s largest hubs, using metaheuristic optimization. Three algorithms—Genetic Algorithms (GA), Modified Discrete Particle Swarm Optimization (MDPSO), and Evolutionary Strategies (ES)—were applied in parallel to optimize arrival and departure schedules for a major airline. The proposed chromosome-based framework was tested through parameter tuning and validated with statistical analyses, including ANOVA and Games–Howell pairwise comparisons. The results show that MDPSO achieved strong improvements, while ES consistently outperformed both GA and MDPSO, increasing successful passenger transfers by more than 200% compared to the original schedule. These findings demonstrate the effectiveness of evolutionary metaheuristics for large-scale airline scheduling and highlight their potential for improving hub connectivity. This framework is generalizable to other hub airports and airlines, and future research could extend it by integrating hybrid metaheuristics or applying enhanced forecasting methods and more dynamic scheduling approaches.
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(This article belongs to the Special Issue Advances in Digital Biomimetics)
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Open AccessArticle
Impact of RAMPA Therapy on Nasal Cavity Expansion and Paranasal Drainage: Fluid Mechanics Analysis, CAE Simulation, and a Case Study
by
Mohammad Moshfeghi, Yasushi Mitani, Yuko Okai-Kojima and Bumkyoo Choi
Biomimetics 2026, 11(1), 5; https://doi.org/10.3390/biomimetics11010005 - 23 Dec 2025
Abstract
Background: Impaired mucus drainage from the paranasal sinuses is often associated with nasal obstruction and reduced airway function in growing patients. Orthopedic maxillary protraction and expansion techniques can enhance airway dynamics, but their underlying fluid–structure mechanisms remain insufficiently understood. Objective: To validate that
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Background: Impaired mucus drainage from the paranasal sinuses is often associated with nasal obstruction and reduced airway function in growing patients. Orthopedic maxillary protraction and expansion techniques can enhance airway dynamics, but their underlying fluid–structure mechanisms remain insufficiently understood. Objective: To validate that the Right Angle Maxillary Protraction Appliance (RAMPA), combined with a semi-rapid maxillary expansion (sRME) intraoral device gHu-1, improves mucus drainage by enhancing nasal airflow through nasal cavity expansion. Methods: The effects of RAMPA therapy were analyzed using computational fluid dynamics (CFD) for single-phase (air) and two-phase (air–mucus) flows within the nasal cavity, employing the unsteady RANS turbulence model. Finite element method (FEM) results from prior studies were synthesized to assess changes in the center and radius of maxillary rotation induced by RAMPA-assisted sRME. A male patient (aged 8 years 7 months to 11 years 7 months) treated with extraoral RAMPA and the intraoral appliance (gHu-1) underwent pre- and post-treatment cone-beam computed tomography (CBCT) and ear, nose, and throat (ENT) evaluation. Results: FEM analysis revealed an increased radius and elevated center of maxillary rotation, producing expansion that was more parallel to the palatal plane. CFD simulations showed that nasal cavity expansion increased airflow velocity and pressure drop, enhancing the suction effect that promotes mucus clearance from the frontal sinus. Clinically, nasal passages widened, paranasal opacities resolved, and occlusal and intermolar widths improved. Conclusions: RAMPA combined with sRME improves nasal airflow and maxillary skeletal expansion, facilitating paranasal mucus clearance and offering a promising adjunctive approach for enhancing upper airway function in growing patients.
Full article
(This article belongs to the Special Issue Dentistry and Craniofacial District: The Role of Biomimetics 2026)
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Open AccessReview
A Comprehensive Review of Computational and Experimental Studies on Skin Mechanics and Meshing: Discrepancies, Challenges, and Optimization Strategies
by
Masoumeh Razaghi Pey Ghaleh, Douglas Marques and Denis O’Mahoney
Biomimetics 2026, 11(1), 4; https://doi.org/10.3390/biomimetics11010004 - 22 Dec 2025
Abstract
Skin meshing is widely used to treat extensive burn injuries due to its cost-efficiency and capacity to cover large wound areas. As biomimetics focuses on deriving engineering principles from biological structure–function relationships, this review examines how to optimize skin-meshing expansion and investigates factors
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Skin meshing is widely used to treat extensive burn injuries due to its cost-efficiency and capacity to cover large wound areas. As biomimetics focuses on deriving engineering principles from biological structure–function relationships, this review examines how to optimize skin-meshing expansion and investigates factors contributing to reported discrepancies between clinical and manufacturer-reported expansion ratios. The biology and mechanical behavior of skin layer are discussed, emphasizing the anisotropic properties govern by collagen fiber orientation associated with Langer’s lines in the dermis. The epidermis and hypodermis show isotropic properties and therefore have minimal influence on load-bearing capacity. Surveying 111 studies, the review evaluates which constitutive equations employed for skin modelling is suitable to replicate mechanical behavior of skin meshing undergoing large expansion. Elastic models fail to capture large expansion ratios. Viscoelastic and QLV are excluded due to negligible sliding of collagen fibers at slow strain rates and limited importance of hysteresis. Consequently, hyperelastic models are recognized as more suitable for predicting large deformations. Among these, the structural GOH model, which represents fiber dispersion through a probability-density function, demonstrates strong agreement with experimental data using few parameters; its damage extensions improve prediction of mesh tearing. Additionally, emerging auxetic mesh geometries with negative Poisson ratios are examined, highlighting their potential to achieve greater expansion when combined with suitable structural anisotropic constitutive models, e.g., GOH.
Full article
(This article belongs to the Special Issue Mechanical Properties and Functions of Bionic Materials/Structures)
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Open AccessArticle
IHBOFS: A Biomimetics-Inspired Hybrid Breeding Optimization Algorithm for High-Dimensional Feature Selection
by
Chunli Xiang, Jing Zhou and Wen Zhou
Biomimetics 2026, 11(1), 3; https://doi.org/10.3390/biomimetics11010003 - 22 Dec 2025
Abstract
With the explosive growth of data across various fields, effective data preprocessing has become increasingly critical. Evolutionary and swarm intelligence algorithms have shown considerable potential in feature selection. However, their performance often deteriorates in large-scale problems, due to premature convergence and limited exploration
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With the explosive growth of data across various fields, effective data preprocessing has become increasingly critical. Evolutionary and swarm intelligence algorithms have shown considerable potential in feature selection. However, their performance often deteriorates in large-scale problems, due to premature convergence and limited exploration ability. To address these limitations, this paper proposes an algorithm named IHBOFS, a biomimetics-inspired optimization framework that integrates multiple adaptive strategies to enhance performance and stability. The introduction of the Good Point Set and Elite Opposition-Based Learning mechanisms provides the population with a well-distributed and diverse initialization. Furthermore, adaptive exploitation–exploration balancing strategies are designed for each subpopulation, effectively mitigating premature convergence. Extensive ablation studies on the CEC2022 benchmark functions verify the effectiveness of these strategies. Considering the discrete nature of feature selection, IHBOFS is further extended with continuous-to-discrete mapping functions and applied to six real-world datasets. Comparative experiments against nine metaheuristic-based methods, including Harris Hawk Optimization (HHO) and Ant Colony Optimization (ACO), demonstrate that IHBOFS achieves an average classification accuracy of 92.57%, confirming its superiority and robustness in high-dimensional feature selection tasks.
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(This article belongs to the Section Biological Optimisation and Management)
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Open AccessArticle
Optimization of Actuator Stiffness and Actuation Timing of a Passive Ankle Exoskeleton: A Case Study Using a Musculoskeletal Modeling Approach
by
Jania Williams, Cody P. Anderson, Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Sara A. Myers and Hafizur Rahman
Biomimetics 2026, 11(1), 2; https://doi.org/10.3390/biomimetics11010002 - 20 Dec 2025
Abstract
Objective: A modeling and simulation tool, OpenSim, was used to determine the optimal relationship between actuator stiffness and actuation timing of a passive ankle exoskeleton for reducing metabolic costs during walking. We hypothesized that the absolute minimum in total metabolic cost would exist
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Objective: A modeling and simulation tool, OpenSim, was used to determine the optimal relationship between actuator stiffness and actuation timing of a passive ankle exoskeleton for reducing metabolic costs during walking. We hypothesized that the absolute minimum in total metabolic cost would exist at an actuation timing of 15% of stance and at a spring stiffness of 7.5 kN/m. We also hypothesized that a local minimum in total metabolic cost would exist at an actuation timing of 50% of stance. Methods: Bilateral kinematics and kinetics data were collected on a healthy male walking overground wearing his regular tennis shoe. The passive ankle exoskeleton geometry and the spring actuator were integrated into the OpenSim model. Simulations were performed for every combination of 25 spring stiffnesses ranging from 5.5 kN/m to 17.5 kN/m (increments of 0.5 kN/m) and 10 actuation timings ranging from 15% to 60% of stance (increments of 5%). Total energy expenditure was calculated as the sum of the energy expenditure of all the muscles in the model. Results: The greatest reduction in energy consumption (−2.67%) was observed at an actuation timing of approximately 15% of the stance phase with a spring stiffness of ~5.5 kN/m. A quadratic relationship between spring stiffness and energy consumption was identified (R2 = 0.99), with an optimal stiffness of approximately 5.5 kN/m minimizing the energy cost. Conclusions: Our findings suggest that OpenSim effectively predicts optimal exoskeleton parameters, supporting personalized assistance to improve energy efficiency and rehabilitation outcomes.
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(This article belongs to the Special Issue Bioinspired Engineered Systems)
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Open AccessArticle
Stabilizing the Convergence of Pixel-Based Deep Active Inference Controllers Using Adaptive Smoothing Filters
by
Kazuma Nagatsuka, Kyo Kutsuzawa, Dai Owaki and Mitsuhiro Hayashibe
Biomimetics 2026, 11(1), 1; https://doi.org/10.3390/biomimetics11010001 - 19 Dec 2025
Abstract
In recent years, active inference has gained attention in robot control owing to its adaptability to environmental changes. However, its reliance on gradient descent of variational free energy offers no guarantee of convergence to an optimal solution. In this study, we propose an
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In recent years, active inference has gained attention in robot control owing to its adaptability to environmental changes. However, its reliance on gradient descent of variational free energy offers no guarantee of convergence to an optimal solution. In this study, we propose an approach that applies a smoothing filter to a pixel-based active inference controller to mitigate the risk of local minima. By smoothing the observed, predicted, and target values, the free energy function becomes smoother, yielding a broader distribution of gradients toward the target, thereby reducing the risk of being trapped in the local minima. In addition, in order to prevent excessive smoothing from eliminating the gradient of the free energy function, we also proposed a method for dynamically adjusting the intensity of smoothing based on prediction and target errors. To evaluate the effectiveness of our method, we applied it to two simulation environments: a simple object-tracking task using a 3-degrees-of-freedom camera, and a robot control task using a 2-degrees-of-freedom robotic arm, and compared it with the conventional active inference controller as a baseline. The experimental results demonstrate that the proposed approach achieves improved convergence performance over the conventional method.
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(This article belongs to the Section Locomotion and Bioinspired Robotics)
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Open AccessArticle
CQLHBA: Node Coverage Optimization Using Chaotic Quantum-Inspired Leader Honey Badger Algorithm
by
Xiaoliu Yang and Mengjian Zhang
Biomimetics 2025, 10(12), 850; https://doi.org/10.3390/biomimetics10120850 - 18 Dec 2025
Abstract
A key limitation of existing swarm intelligence (SI) algorithms for Node Coverage Optimization (NCO) is their inadequate solution accuracy. A novel chaotic quantum-inspired leader honey badger algorithm (CQLHBA) is proposed in this study. To enhance the performance of the basic HBA and better
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A key limitation of existing swarm intelligence (SI) algorithms for Node Coverage Optimization (NCO) is their inadequate solution accuracy. A novel chaotic quantum-inspired leader honey badger algorithm (CQLHBA) is proposed in this study. To enhance the performance of the basic HBA and better solve the numerical optimization and NCO problem, an adjustment strategy for parameter to balance the optimization process of the follower position is used to improve the exploration ability. Moreover, the chaotic dynamic strategy, quantum rotation strategy, and Lévy flight strategy are employed to enhance the overall performance of the designed CQLHBA, especially for the exploitation ability of individuals. The performance of the proposed CQLHBA is verified using twenty-one benchmark functions and compared to that of other state-of-the-art (SOTA) SI algorithms, including the Honey Badger Algorithm (HBA), Chaotic Sea-Horse Optimizer (CSHO), Sine–Cosine Quantum Salp Swarm Algorithm (SCQSSA), Golden Jackal Optimization (GJO), Aquila Optimizer (AO), Butterfly Optimization Algorithm (BOA), Salp Swarm Algorithm (SSA), Grey Wolf Optimizer (GWO), and Randomised Particle Swarm Optimizer (RPSO). The experimental results demonstrate that the proposed CQLHBA exhibits superior performance, characterized by enhanced global search capability and robust stability. This advantage is further validated through its application to the NCO problem in wireless sensor networks (WSNs), where it achieves commendable outcomes in terms of both coverage rate and network connectivity, confirming its practical efficacy in real-world deployment scenarios.
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(This article belongs to the Special Issue Advances in Swarm Intelligence Optimization Algorithms and Applications: 2nd Edition)
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Open AccessArticle
Additively Manufactured Dragonfly-Inspired Wings for Bio-Faithful Flapping MAV Development
by
Emilia Georgiana Prisăcariu, Oana Dumitrescu, Sergiu Strătilă, Mihail Sima, Claudia Săvescu, Iulian Vlăducă and Cleopatra Cuciumita
Biomimetics 2025, 10(12), 849; https://doi.org/10.3390/biomimetics10120849 - 18 Dec 2025
Abstract
This work presents a first-iteration bio-faithful dragonfly-inspired wing designed for future flapping micro air vehicle (MAV) applications. Using high-resolution imaging, the natural venation pattern of fore- and hindwings was reconstructed in CAD and reproduced through high-precision stereolithography at 1:1 and 3:1 scale. The
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This work presents a first-iteration bio-faithful dragonfly-inspired wing designed for future flapping micro air vehicle (MAV) applications. Using high-resolution imaging, the natural venation pattern of fore- and hindwings was reconstructed in CAD and reproduced through high-precision stereolithography at 1:1 and 3:1 scale. The printed polymeric wings successfully preserved the anisotropic stiffness distribution of the biological structure, enabling realistic bending and torsional responses. Modal analysis and dynamic testing confirmed that the lightweight designs operate within the biologically relevant 20–40 Hz range and that geometry and material choices allow predictable tuning of natural frequencies. Preliminary aerodynamic estimates captured the characteristic anti-phase lift behavior of four-wing flapping, while schlieren and infrared thermography demonstrated that heat dispersion and flow features follow the vein-driven structural pathways of the printed wings. Together, these results validate the feasibility and functional relevance of bio-faithful venation architectures and establish a solid foundation for future iterations incorporating membranes, full kinematic actuation, and higher-fidelity aeroelastic modeling.
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(This article belongs to the Section Biomimetic Design, Constructions and Devices)
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