McAlpine Research Group
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Browsing McAlpine Research Group by Author "Haghiashtiani, Ghazaleh"
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Item Supporting data for "3D printed electrically-driven soft actuators"(2020-06-09) Haghiashtiani, Ghazaleh; Habtour, Ed; Park, Sung-Hyun; Gardea, Frank; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research GroupSoft robotics is an emerging field enabled by advances in the development of soft materials with properties commensurate to their biological counterparts, for the purpose of reproducing locomotion and other distinctive capabilities of active biological organisms. The development of soft actuators is fundamental to the advancement of soft robots and bio-inspired machines. Among the different material systems incorporated in the fabrication of soft devices, ionic hydrogel–elastomer hybrids have recently attracted vast attention due to their favorable characteristics, including their analogy with human skin. Here, we demonstrate that this hybrid material system can be 3D printed as a soft dielectric elastomer actuator (DEA) with a unimorph configuration that is capable of generating high bending motion in response to an applied electrical stimulus. We characterized the device actuation performance via applied (i) ramp-up electrical input, (ii) cyclic electrical loading, and (iii) payload masses. A maximum vertical tip displacement of 9.78 ± 2.52 mm at 5.44 kV was achieved from the tested 3D printed DEAs. Furthermore, the nonlinear actuation behavior of the unimorph DEA was successfully modeled using an analytical energetic formulation and a finite element method (FEM).Item Supporting data for "3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors"(2020-05-22) Qiu, Kaiyan; Zhao, Zichen; Haghiashtiani, Ghazaleh; Guo, Shuang-Zhuang; He, Mingyu; Su, Ruitao; Zhu, Zhijie; Bhuiyan, Didarul B; Murugan, Paari; Meng, Fanben; Park, Sung Hyun; Chu, Chih-Chang; Ogle, Brenda M; Saltzman, Daniel A; Konety, Badrinath R; Sweet, Robert M; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research GroupThe data set includes the experimental data and the corresponding MRI stereolithography (STL) file supporting the results reported in Kaiyan Qiu; Zichen Zhao; Ghazaleh Haghiashtiani; Shuang-Zhuang Guo; Mingyu He; Ruitao Su; Zhijie Zhu; Didarul B. Bhuiyan; Paari Murugan; Fanben Meng; Sung Hyun Park; Chih-Chang Chu; Brenda M. Ogle; Daniel A. Saltzman; Badrinath R. Konety; Robert M. Sweet; Michael C. McAlpine. 3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors. Adv. Mater. Technol. 2018, 3, 1700235. The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-like tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.Item Supporting data for "3D printed patient-specific aortic root models with internal sensors for minimally invasive applications"(2020-06-09) Haghiashtiani, Ghazaleh; Qiu, Kaiyan; Sanchez, Jorge D Zhingre; Fuenning, Zachary J; Nair, Priya; Ahlberg, Sarah E; Iaizzo, Paul A; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research GroupMinimally invasive surgeries have numerous advantages, yet complications may arise from limited knowledge about the anatomical site targeted for the delivery of therapy. Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure for treating aortic stenosis. Here, we demonstrate multi-material 3D printing of patient-specific soft aortic root models with internally-integrated electronic sensor arrays that can augment testing for TAVR preprocedural planning. We evaluated the efficacies of the models by comparing their geometric fidelities with postoperative data from patients, as well as their in vitro hemodynamic performances in cases with and without leaflet calcifications. Furthermore, we uniquely demonstrated that internal sensor arrays can facilitate the optimization of bioprosthetic valve selections and in vitro placements via mapping of the pressures applied on the critical regions of the aortic anatomies. Such models may pave new avenues for mitigating the risks of postoperative complications, as well as facilitating the development of next-generation medical devices.