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Micromachines
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3D Printed Implants for Biomedical Applications
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3D Printed Implants for Biomedical Applications

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "B：Biology and Biomedicine".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 12037

Special Issue Editors

Dr. ALOK Sutradhar

E-Mail Website
Guest Editor
Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, OH, USA
Interests: intelligent designs for mechanical, thermal, biological, and photonic structures; understanding and unlocking the design principles of nature; topology optimization; additive manufacturing; bio-inspired designs; implant design; bomedical modeling
Dr. Jaejong Park

E-Mail Website
Co-Guest Editor
Department of Mechanical Engineering, Prairie View A&M University, Prairie View, TX 77446, USA
Interests: VR-based engineering education; structural optimization; computational mechanics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development and manufacturing of customized implants for a wide variety of medical conditions allow more reliable and controlled restoration with better functional outcomes in biomedical applications. With the dawn of 3D printing technology, a paradigm shift in patient-specific implant designs have occured. It also provides the ability to generate sophisticated internal geometric features compared to traditional machining processes. Various researchers and clinicians have been taking these advantages of 3D printing to create patient-specific implants with advanced features such as stiffness matching, evolving geometries, functional structures, drug delivery, etc. The purpose of this Special issue, accordingly, is to gather and exhibit exiting research performed in this area in the form of short communications, full research articles, and review papers. The topics of interest include

  • 3D printed medical devices inlcuding implants and other rehabilitation devices
  • Design algorithms for patient-specific implants for 3D printing
  • Mechanical evaluation of 3D printed medical devices
  • Geometric design and study of 3D printable structures
  • 4D printing, evolving structures
  • Multifunctional, and multiscale structural design
Prof. Dr. Alok Sutradhar
Dr. Jaejong Park
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. Micromachines 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 2600 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

  • 3D printing
  • Medical implants
  • Flexible Brain Implants
  • Soft biomedical Implants
  • Tissue regenerative scaffolds
  • Bionic Constructs
  • Patient-specific design
  • 4D printing
  • Nanoprinted Implants
  • Functional Materials
  • Architected Biomaterials

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Published Papers (4 papers)

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Research

20 pages, 18801 KiB  
Article
Research on Task-Service Network Node Matching Method Based on Multi-Objective Optimization Model in Dynamic Hyper-Network Environment
by Cheng-lei Zhang, Jia-jia Liu, Hu Han, Xiao-jie Wang, Bo Yuan, Shen-le Zhuang and Kang Yang
Micromachines 2021, 12(11), 1427; https://doi.org/10.3390/mi12111427 - 21 Nov 2021
Cited by 3 | Viewed by 2119
Abstract
In order to reduce the cost of manufacturing and service for the Cloud 3D printing (C3DP) manufacturing grid, to solve the problem of resources optimization deployment for no-need preference under circumstance of cloud manufacturing, consider the interests of enterprises which need Cloud 3D [...] Read more.
In order to reduce the cost of manufacturing and service for the Cloud 3D printing (C3DP) manufacturing grid, to solve the problem of resources optimization deployment for no-need preference under circumstance of cloud manufacturing, consider the interests of enterprises which need Cloud 3D printing resources and cloud platform operators, together with QoS and flexibility of both sides in the process of Cloud 3D printing resources configuration service, a task-service network node matching method based on Multi-Objective optimization model in dynamic hyper-network environment is built for resource allocation. This model represents interests of the above-mentioned two parties. In addition, the model examples are solved by modifying Mathematical algorithm of Node Matching and Evolutionary Solutions. Results prove that the model and the algorithm are feasible, effective and stable. Full article
(This article belongs to the Special Issue 3D Printed Implants for Biomedical Applications)
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22 pages, 3130 KiB  
Article
Evaluation of Cloud 3D Printing Order Task Execution Based on the AHP-TOPSIS Optimal Set Algorithm and the Baldwin Effect
by Chenglei Zhang, Cunshan Zhang, Jiaojiao Zhuang, Hu Han, Bo Yuan, Jiajia Liu, Kang Yang, Shenle Zhuang and Ronglan Li
Micromachines 2021, 12(7), 801; https://doi.org/10.3390/mi12070801 - 6 Jul 2021
Cited by 10 | Viewed by 2168
Abstract
Focusing on service control factors, rapid changes in manufacturing environments, the difficulty of resource allocation evaluation, resource optimization for 3D printing services (3DPSs) in cloud manufacturing environments, and so on, an indicator evaluation framework is proposed for the cloud 3D printing (C3DP) order [...] Read more.
Focusing on service control factors, rapid changes in manufacturing environments, the difficulty of resource allocation evaluation, resource optimization for 3D printing services (3DPSs) in cloud manufacturing environments, and so on, an indicator evaluation framework is proposed for the cloud 3D printing (C3DP) order task execution process based on a Pareto optimal set algorithm that is optimized and evaluated for remotely distributed 3D printing equipment resources. Combined with the multi-objective method of data normalization, an optimization model for C3DP order execution based on the Pareto optimal set algorithm is constructed with these agents’ dynamic autonomy and distributed processing. This model can perform functions such as automatic matching and optimization of candidate services, and it is dynamic and reliable in the C3DP order task execution process based on the Pareto optimal set algorithm. Finally, a case study is designed to test the applicability and effectiveness of the C3DP order task execution process based on the analytic hierarchy process and technique for order of preference by similarity to ideal solution (AHP-TOPSIS) optimal set algorithm and the Baldwin effect. Full article
(This article belongs to the Special Issue 3D Printed Implants for Biomedical Applications)
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23 pages, 12276 KiB  
Article
A Layer-Arranged Meshless Method for the Simulation of Additive Manufacturing with Irregular Shapes
by Ming-Hsiao Lee, Wen-Hwa Chen and Ying Mao
Micromachines 2021, 12(6), 674; https://doi.org/10.3390/mi12060674 - 9 Jun 2021
Cited by 1 | Viewed by 2087
Abstract
Additive manufacturing (3D Printing) has become a promising manufacturing method as it can produce parts in a flexible and efficient way, especially for very irregular parts. However, during the printing process, the material experiences a great temperature change from the melting temperature to [...] Read more.
Additive manufacturing (3D Printing) has become a promising manufacturing method as it can produce parts in a flexible and efficient way, especially for very irregular parts. However, during the printing process, the material experiences a great temperature change from the melting temperature to room temperature; this causes high thermal strains and induces distinct deformations which degrade the quality of the printed parts, especially in metal 3D printing. In order to reduce possible problems and find possible solutions, a prior evaluation by simulation is often adopted. Nevertheless, since the 3D printing process generates parts in a layer-by-layer way, the analysis model should also be layer-by-layer arranged and used with a layer-by-layer based analysis process to simulate the layer-by-layer additive printing; otherwise, the simulation may not match the real behavior. In order to meet these requirements, a new meshless method is proposed to match the situations and handle these problems. As a meshless method, the modeling is not constrained by the element distribution. In addition, the analysis model generated with the proposed method can be arranged in a layer-by-layer way and combined with the proposed layer-by-layer analysis scheme, so it can then match and simulate the printing processes. Furthermore, the layer-by-layer arranged models can be automatically created, directly based on the STL (STereo-Lithography) geometry model, which is a de facto standard in the 3D printing industry. This makes the proposed approach more straightforward and efficient. To validate the proposed method, two parts with holes inside have been printed and simulated for comparison. The results show a good agreement. In addition, a highly irregular part has also been simulated to demonstrate the effectiveness and efficiency of this proposed method. Full article
(This article belongs to the Special Issue 3D Printed Implants for Biomedical Applications)
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19 pages, 16034 KiB  
Article
A Two-Scale Multi-Resolution Topologically Optimized Multi-Material Design of 3D Printed Craniofacial Bone Implants
by Jaejong Park, Tareq Zobaer and Alok Sutradhar
Micromachines 2021, 12(2), 101; https://doi.org/10.3390/mi12020101 - 20 Jan 2021
Cited by 14 | Viewed by 4656
Abstract
Bone replacement implants for craniofacial reconstruction require to provide an adequate structural foundation to withstand the physiological loading. With recent advances in 3D printing technology in place of bone grafts using autologous tissues, patient-specific additively manufactured implants are being established as suitable alternates. [...] Read more.
Bone replacement implants for craniofacial reconstruction require to provide an adequate structural foundation to withstand the physiological loading. With recent advances in 3D printing technology in place of bone grafts using autologous tissues, patient-specific additively manufactured implants are being established as suitable alternates. Since the stress distribution of these structures is complicated, efficient design techniques, such as topology optimization, can deliver optimized designs with enhanced functionality. In this work, a two-scale topology optimization approach is proposed that provides multi-material designs for both macrostructures and microstructures. In the first stage, a multi-resolution topology optimization approach is used to produce multi-material designs with maximum stiffness. Then, a microstructure with a desired property supplants the solid domain. This is beneficial for bone implant design since, in addition to imparting the desired functional property to the design, it also introduces porosity. To show the efficacy of the technique, four different large craniofacial defects due to maxillectomy are considered, and their respective implant designs with multi-materials are shown. These designs show good potential in developing patient-specific optimized designs suitable for additive manufacturing. Full article
(This article belongs to the Special Issue 3D Printed Implants for Biomedical Applications)
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