Effects of Topology Optimization in Multimaterial 3D Bioprinting of Soft Actuators

Ali Zolfagharian, Martin Denk, Abbas Z. Kouzani, Mahdi Bodaghi, Saeid Nahavandi, Akif Kaynak

Article ID: 260
Vol 6, Issue 2, 2020, Article identifier:260

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Recently, there has been a proliferation of soft robots and actuators that exhibit improved capabilities and adaptability through three-dimensional (3D) bioprinting. Flexibility and shape recovery attributes of stimuli-responsive polymers as the main components in the production of these dynamic structures enable soft manipulations in fragile environments, with potential applications in biomedical and food sectors. Topology optimization (TO), when used in conjunction with 3D bioprinting with optimal design features, offers new capabilities for efficient performance in compliant mechanisms. In this paper, multimaterial TO analysis is used to improve and control the bending performance of a bioprinted soft actuator with electrolytic stimulation. The multimaterial actuator performance is evaluated by the amplitude and rate of bending motion and compared with the single material printed actuator. The results demonstrated the efficacy of multimaterial 3D bioprinting optimization for the rate of actuation and bending.


Multimaterial, Three-dimensional bioprinting, Topology optimization, Soft actuator, Soft robot

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Cohen E, Trimmer BA, Vikas V, et al., 2015, Design Methodologies for Soft-Material Robots Through Additive Manufacturing, From Prototyping to Locomotion. In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, New York. DOI: 10.1115/detc2015-47507.

Bodaghi M, Damanpack A, Liao W, 2017, Adaptive Metamaterials by Functionally Graded 4D Printing. Mater Des, 135:26–36. DOI: 10.1016/j.matdes.2017.08.069.

Choong YY, Maleksaeedi S, Eng H, et al., 2020, High Speed 4D Printing of Shape Memory Polymers with Nanosilica. Appl Mater Today, 18:100515. DOI: 10.1016/j.apmt.2019.100515.

Zolfagharian A, Khoo S, Kouzani A, et al., 2016, Evolution of 3D Printed Soft Actuators. J Sens Actuators A Physical, 250:258–72. DOI: 10.1016/j.sna.2016.09.028.

Bodaghi, M., Zolfagharian A, Serjouei A, et al., 2020, Reversible Energy Absorbing Meta-Sandwiches by 4D FDM Printing. Int J Mech Sci, 173:105451. DOI: 10.1016/j.ijmecsci.2020.105451.

Maute K, Tkachuk A, Wu J, et al., 2015, Level set Topology Optimization of Printed Active Composites. J Mech Des, 137:111402.

Yu C, Jiang J, 2020, A Perspective on Using Machine Learning in 3D Bioprinting. Int J Bioprint, 6:95. DOI: 10.18063/ijb.v6i1.253.

Hamel CM, Roach DJ, Long KN, et al., 2019, Machine learning Based Design of Active Composite Structures for 4D Printing. J Smart Mater Struct, 28:65005. DOI: 10.1088/1361-665x/ab1439.

Bodaghi M, Noroozi R, Zolfagharian A, et al., 2019, 4D Printing Self-morphing Structures. J Mater, 12:1353. DOI: 10.3390/ma12081353.

Zolfagharian A, Kaynak A, Khoo SY, et al., 2018, Pattern-driven 4D Printing. J Sens Actuators A Physical,274:231–43. DOI: 10.1016/j.sna.2018.03.034.

Zolfagharian A, Denk M, Bodaghi M, et al., 2019, Topology-Optimized 4D Printing of a Soft Actuator. J Acta Mech Solida Sin, 253:1–13. DOI: 10.1007/s10338-019-00137-z.

Lee J, Sing S, Yeong W, 2020, Bioprinting of Multimaterials with Computer-aided Design/Computer-aided Manufacturing. Int J, 6:47. DOI: 10.18063/ijb.v6i1.245.

Zhang B, Chrisey DB, Cristescu R, et al., 2020, Solvent based Extrusion 3D Printing for the Fabrication of Tissue Engineering Scaffolds. Int J Bioprint, 6:211. DOI: 10.18063/ijb.v6i1.211.

Kaynak A, Zolfagharian A, 2019, Stimuli-Responsive Polymer Systems Recent Manufacturing Techniques and Applications. Multidisciplinary Digital Publishing Institute, Switzerland. DOI: 10.3390/ma12152380.

Pilate F, Mincheva R, De Winter J, et al., 2014, Design of Multistimuli-responsive Shape-memory Polymer Materials by Reactive Extrusion. Chem Mater, 26:5860–7. DOI: 10.1021/cm5020543.

Shiga T, Kurauchi T, 1990, Deformation of Polyelectrolyte Gels under the Influence of Electric Field. J Appl Polym Sci, 39:2305–20. DOI: 10.1002/app.1990.070391110.

Li Y, Sun Y, Xiao Y, et al., 2016, Electric Field Actuation of tough Electroactive Hydrogels Cross-linked by Functional Triblock Copolymer Micelles. ACS Appl Mater Interfaces, 8:26326–31. DOI: 10.1021/acsami.6b08841.

Sigmund O, Maute KJ, 2013, Optimization, Topology Optimization Approaches. Struct Multidiscip Optim, 48:1031–55. DOI: 10.1007/s00158-013-0978-6.

Huang X, Xie YM, 2007, Design, Convergent and Mesh independent Solutions for the bi directional Evolutionary Structural Optimization Method. Finite Elem Anal Des, 43:1039–49. DOI: 10.1016/j.finel.2007.06.006.

van Dijk NP, Maute K, Langelaar M, et al., 2013, Level-set Methods for Structural Topology Optimization: A Review. 48:437–72. DOI: 10.1007/s00158-013-0912-y.

Bendsøe MP, Sigmund O, 1999, Material Interpolation Schemes in Topology Optimization. J Arch Appl Mech.,69:635–54.

Zolfagharian A, Denk, Bodaghi M, et al., 2018, Polyelectrolyte Soft Actuators: 3D Printed Chitosan and Cast Gelatin. J 3D Print Addit Manuf, 5:138–50. DOI: 10.1089/3dp.2017.0054.

Yang R, Chen C, 1996, Stress-based Topology Optimization. J Struct Optim, 12:98–105.

Hongying Z, 2018, Development of Topology Optimized 3D Printed Soft Grippers and Dielectric Soft Sensors, Theses and Dissertations.

Schumacher A, 2013, Mathematische Grundlagen derOptimierung, in Optimierung mechanischer Strukturen. Springer, Berlin. pp. 45–55. DOI: 10.1007/978-3-642-34700-9_3.

Harzheim L, 2016, Der Natur in die karten geschaut optimierungsverfahren aus dem bereich der bionik. In: Karosseriebautage Hamburg. Springer, Berlin. pp. 3–16.DOI: 10.1007/978-3-658-14144-8_1.

Huang X, Xie M, 2010, Evolutionary Topology Optimization of Continuum Structures: Methods and Applications. John Wiley & Sons, New York.

Zhang H, Kumar AS, Chen F, et al., 2019, Topology Optimized Multimaterial Soft Fingers for Applications on Grippers, Rehabilitation, and Artificial Hands. J IEEE/ASME Trans Mechatron, 24:120–31. DOI: 10.1109/tmech.2018.2874067.

He D, Liu SJ, 2008, BESO Method for Topology Optimization of Structures with High Efficiency of Heat Dissipation. Int J Simul Multidiscip Des Optim, 2:43–8. DOI: 10.1051/smdo:2008005.

Kim MG, Kim JH, Cho SH, 2010, Topology Design Optimization of Heat Conduction Problems Using Adjoint Sensitivity Analysis Method. Adv Mech Eng, 23:683–91.

Gersborg-Hansen A, Bendsøe MP, Sigmund O, 2005, Topology Optimization Using the Finite Volume Method. Struct Multidiscipl Optim, 50:523–35. DOI: 10.1007/s00158-005-0584-3.

Kaup IA, 2018, Rekonstruktion Verrauschter Nichtregelmäßig Abgetasteter Bilddaten. Bachelor Thesis.

Svanberg K, 1987, The Method of Moving Asymptotes a New Method for Structural Optimization. 24:359–73.

Wiedemann J, 2007, Leichtbau: Elemente und Konstruktion.Springer-Verlag, Berlin.

Tavakoli R, Mohseni SM, 2014, Alternating Active-phase Algorithm for Multimaterial Topology Optimization Problems: A 115-line MATLAB Implementation. Struct Multidiscip Optim, 49:621–42. DOI: 10.1007/s00158-013-0999-1.

Zhang H, Wang Y, Cao J, et al., 2018, Topology Optimized Design, Fabrication and Evaluation of a Multimaterial Soft Gripper. In: 2018 IEEE International Conference on Soft Robotics (RoboSoft). DOI: 10.1109/robosoft.2018.8405363.

Lee JM, Yeong WY, 2016, Design and Printing Strategies in 3D Bioprinting of Cell-Hydrogels: A Review. Adv Healthc Mater, 5:2856–65. DOI: 10.1002/adhm.201600435.

Wu Q, Maire M, Lerouge S, et al., 2016, Solvent-cast 3D Printing of Chitosan Hydrogel Scaffolds for Guided Cell Growth. Front. Bioeng. Biotechnol. Conference Abstract: 10th World Biomaterials Congress. DOI: 10.3389/conf. FBIOE.2016.01.00336.

Zhang J, Allardyce BJ, Rajkhowa R, et al., 2018, 3D Printing of Silk Particle-reinforced Chitosan Hydrogel Structures and their Properties. ACS Biomater Sci Eng, 4:3036–46. DOI: 10.1021/acsbiomaterials.8b00804.

Zolfagharian A, Kouzani AZ, Khoo SY, et al., 2018, 3D Printed Soft Parallel Actuator. J Smart Mater Struct, 27:45019. DOI: 10.1088/1361-665x/aaab29.

Bouguet JY, 2010, Camera Calibration Toolbox for Matlab. International Conference on Indoor Positioning and Indoor Navigation.

Choong YY, Maleksaeedi S, Eng H, et al., 2017, 4D Printing of High-Performance Shape Memory Polymer Using Stereolithography. Mater Des, 126:219–25. DOI: 10.1016/j.matdes.2017.04.049.

Donnan FG, 1924, The Theory of Membrane Equilibria. Chem Rev, 1:73–90.

Zolfagharian A, Kouzani AZ, Khoo SY, et al., 2017, Development and Analysis of a 3D Printed Hydrogel Soft Actuator. J Sen Actuators A Physical, 265:94–101. DOI: 10.1016/j.sna.2017.08.038.

DOI: http://dx.doi.org/10.18063/ijb.v6i2.260


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