Nature-Inspired Science and Engineering for Sustainable Future

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

Deadline for manuscript submissions: closed (20 June 2025) | Viewed by 3610

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Guest Editor
1. ABSCUBE Engineering & Education Services Pty Ltd., Melbourne, VIC, Australia
2. School of Engineering, RMIT University, Melbourne, VIC 3000, Australia
Interests: aerodynamics; bioengineering; turbo machinery; mechanical design; energy and power; renewable energy; engineering education and accreditation
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Special Issue Information

Dear Colleagues,

In the quest for sustainable and renewable energy sources, scientists and engineers have increasingly turned to nature for inspiration. Biomimicry learns from and mimics the strategies found in nature and has become an effective tool for creating ground-breaking renewable energy solutions. Several new technologies have been inspired by nature as designers increasingly look to biomimicry for creating new ideas for wind turbines, solar cells, and hydropower. For instance, scientists studied the effective distribution of water and nutrients by leaf veins, which provided inspiration for the microchannel design of solar panels. Scientists also studied the structure and movement of bird wings, using bionic concepts to develop flexible wing structures and streamlined shapes.

This Special Issue will investigate biomimetics as drivers of design on several scales as a tool for sustainable development, which focused on bio-inspired approaches used for reducing the operational energy of different engineering systems including that of buildings, road vehicles, passenger cars, trucks, locomotives, aeroplanes/aircrafts, submarines, or underwater vehicles. Scientific contributions are invited from scientists, researchers, engineers, and industry professionals as a means of disseminating recent design strategies, inventions, and developments in the field. Review papers presenting the state of the art of this research area and identifying new directions for further research are also welcome.

This Special Issue was developed in collaboration with the Australian Society of Energy and Power (ASEP) and aligned with the 5th International Conference on Energy and Power (ICEP2024), and for the Conference details, see the following link: https://www.asep.org.au/icep-conference/5th-icep-2024.

Dr. Harun Chowdhury
Guest Editor

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. Biomimetics 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 2200 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

  • biomimicry design
  • power and energy technologies
  • bio-energy
  • renewable
  • efficiency
  • sustainability

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Published Papers (3 papers)

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Research

38 pages, 9771 KiB  
Article
Global Research Trends in Biomimetic Lattice Structures for Energy Absorption and Deformation: A Bibliometric Analysis (2020–2025)
by Sunny Narayan, Brahim Menacer, Muhammad Usman Kaisan, Joseph Samuel, Moaz Al-Lehaibi, Faisal O. Mahroogi and Víctor Tuninetti
Biomimetics 2025, 10(7), 477; https://doi.org/10.3390/biomimetics10070477 - 19 Jul 2025
Viewed by 704
Abstract
Biomimetic lattice structures, inspired by natural architectures such as bone, coral, mollusk shells, and Euplectella aspergillum, have gained increasing attention for their exceptional strength-to-weight ratios, energy absorption, and deformation control. These properties make them ideal for advanced engineering applications in aerospace, biomedical devices, [...] Read more.
Biomimetic lattice structures, inspired by natural architectures such as bone, coral, mollusk shells, and Euplectella aspergillum, have gained increasing attention for their exceptional strength-to-weight ratios, energy absorption, and deformation control. These properties make them ideal for advanced engineering applications in aerospace, biomedical devices, and structural impact protection. This study presents a comprehensive bibliometric analysis of global research on biomimetic lattice structures published between 2020 and 2025, aiming to identify thematic trends, collaboration patterns, and underexplored areas. A curated dataset of 3685 publications was extracted from databases like PubMed, Dimensions, Scopus, IEEE, Google Scholar, and Science Direct and merged together. After the removal of duplication and cleaning, about 2226 full research articles selected for the bibliometric analysis excluding review works, conference papers, book chapters, and notes using Cite space, VOS viewer version 1.6.20, and Bibliometrix R packages (4.5. 64-bit) for mapping co-authorship networks, institutional affiliations, keyword co-occurrence, and citation relationships. A significant increase in the number of publications was found over the past year, reflecting growing interest in this area. The results identify China as the most prolific contributor, with substantial institutional support and active collaboration networks, especially with European research groups. Key research focuses include additive manufacturing, finite element modeling, machine learning-based design optimization, and the performance evaluation of bioinspired geometries. Notably, the integration of artificial intelligence into structural modeling is accelerating a shift toward data-driven design frameworks. However, gaps remain in geometric modeling standardization, fatigue behavior analysis, and the real-world validation of lattice structures under complex loading conditions. This study provides a strategic overview of current research directions and offers guidance for future interdisciplinary exploration. The insights are intended to support researchers and practitioners in advancing next-generation biomimetic materials with superior mechanical performance and application-specific adaptability. Full article
(This article belongs to the Special Issue Nature-Inspired Science and Engineering for Sustainable Future)
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16 pages, 1648 KiB  
Article
Biomimetic Stator Vane Design for Radial Turbines in Waste Heat Recovery Applications
by Fuhaid Alshammari, Ibrahim Alatawi and Muapper Alhadri
Biomimetics 2025, 10(7), 463; https://doi.org/10.3390/biomimetics10070463 - 15 Jul 2025
Viewed by 285
Abstract
Organic Rankine Cycle (ORC) systems are widely used for converting low-temperature waste heat into useful power, but their overall efficiency depends heavily on the turbine’s performance, particularly the stator vane design in radial turbines. This study introduces a biomimetic approach to turbine design [...] Read more.
Organic Rankine Cycle (ORC) systems are widely used for converting low-temperature waste heat into useful power, but their overall efficiency depends heavily on the turbine’s performance, particularly the stator vane design in radial turbines. This study introduces a biomimetic approach to turbine design by implementing cambered stator vanes inspired by bird feather geometry. These specially shaped vanes are added to a radial inflow turbine and compared to a traditional design that uses straight (symmetric) vanes. The new cambered design helps guide the airflow more effectively, leading to higher tangential speeds and better energy transfer. Simulations show that this design increases the turbine’s power output from 388.6 kW to 394.87 kW and improves the system’s overall efficiency from 8.78% to 10.12%. A detailed study of different camber levels found that moderate curvatures (around 8–12%) gave the best results. Overall, this study demonstrates that implementing biomimetic cambered stator vanes in radial turbines can significantly enhance turbine performance and improve cycle-level efficiency in ORC systems for waste heat recovery. Full article
(This article belongs to the Special Issue Nature-Inspired Science and Engineering for Sustainable Future)
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25 pages, 1355 KiB  
Article
Performance Comparison of Bio-Inspired Algorithms for Optimizing an ANN-Based MPPT Forecast for PV Systems
by Rafael Rojas-Galván, José R. García-Martínez, Edson E. Cruz-Miguel, José M. Álvarez-Alvarado and Juvenal Rodríguez-Resendiz
Biomimetics 2024, 9(10), 649; https://doi.org/10.3390/biomimetics9100649 - 21 Oct 2024
Cited by 5 | Viewed by 1799
Abstract
This study compares bio-inspired optimization algorithms for enhancing an ANN-based Maximum Power Point Tracking (MPPT) forecast system under partial shading conditions in photovoltaic systems. Four algorithms—grey wolf optimizer (GWO), particle swarm optimization (PSO), squirrel search algorithm (SSA), and cuckoo search (CS)—were evaluated, with [...] Read more.
This study compares bio-inspired optimization algorithms for enhancing an ANN-based Maximum Power Point Tracking (MPPT) forecast system under partial shading conditions in photovoltaic systems. Four algorithms—grey wolf optimizer (GWO), particle swarm optimization (PSO), squirrel search algorithm (SSA), and cuckoo search (CS)—were evaluated, with the dataset augmented by perturbations to simulate shading. The standard ANN performed poorly, with 64 neurons in Layer 1 and 32 in Layer 2 (MSE of 159.9437, MAE of 8.0781). Among the optimized approaches, GWO, with 66 neurons in Layer 1 and 100 in Layer 2, achieved the best prediction accuracy (MSE of 11.9487, MAE of 2.4552) and was computationally efficient (execution time of 1198.99 s). PSO, using 98 neurons in Layer 1 and 100 in Layer 2, minimized MAE (2.1679) but had a slightly longer execution time (1417.80 s). SSA, with the same neuron count as GWO, also performed well (MSE 12.1500, MAE 2.7003) and was the fastest (987.45 s). CS, with 84 neurons in Layer 1 and 74 in Layer 2, was less reliable (MSE 33.7767, MAE 3.8547) and slower (1904.01 s). GWO proved to be the best overall, balancing accuracy and speed. Future real-world applications of this methodology include improving energy efficiency in solar farms under variable weather conditions and optimizing the performance of residential solar panels to reduce energy costs. Further optimization developments could address more complex and larger-scale datasets in real-time, such as integrating renewable energy sources into smart grid systems for better energy distribution. Full article
(This article belongs to the Special Issue Nature-Inspired Science and Engineering for Sustainable Future)
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