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Browsing Data Repository for U of M (DRUM) by Subject "3D printing"
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Item Data for "3D Printing-Enabled DNA Extraction for Long-Read Genomics" published as ACS Omega 2020, 5, 20817-20824(2020-08-31) Agrawal, Paridhi; Reifenberger, Jeffrey G; Dorfman, Kevin D; agraw135@umn.edu; Agrawal, Paridhi; University of Minnesota Dorfman LabThe deposited data files have DNA size measurement critical to demonstrating long DNA extraction in the microfluidic device, and DNA concentration measurement to show the yield of the platform.Item Data for 3D Printed Organisms Enabled by Aspiration-Assisted Adaptive Strategies(2024-06-17) Han, Guebum; Khosla, Kanav; Smith, Kieran T; Ng, Daniel Wai Hou; Lee, JiYong; Ouyang, Xia; Bischof, John C; McAlpine, Michael C; hanguebum@gmail.com; Han, Guebum; University of Minnesota McAlpine Research Group; University of Minnesota Bischof Research GroupDevising an approach to deterministically position organisms could impact various fields such as bioimaging, cybernetics, cryopreservation, and organism-integrated devices. This requires continuously assessing the locations of randomly distributed organisms to collect and transfer them to target spaces without harm. Here we developed an aspiration-assisted adaptive printing system that tracks, harvests, and relocates living and moving organisms on target spaces via a pick-and-place mechanism that continuously adapts to updated visual and spatial information about the organisms and target spaces. These adaptive printing strategies successfully positioned a single static organism, multiple organisms in droplets, and a single moving organism on target spaces. Their capabilities were exemplified by printing vitrification-ready organisms in cryoprotectant droplets, sorting live organisms from dead ones, positioning organisms on curved surfaces, organizing organism-powered displays, and integrating organisms with materials and devices in customizable shapes. These printing strategies could ultimately lead to autonomous biomanufacturing methods to evaluate and assemble organisms for a variety of single and multi-organism-based applications.Item Supporting data for "3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments"(2020-05-29) Meng, Fanben; Meyer, Carolyn M; Joung, Daeha; Vallera, Daniel A; McAlpine, Michael C; Panoskaltsis-Mortari, Angela; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research GroupThe data set includes the experimental data and the corresponding code files for " 3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments", Fanben Meng, Carolyn M Meyer, Daeha Joung, Daniel A Vallera, Michael C McAlpine, Angela Panoskaltsis‐Mortari, Adv. Mater. 2019, 31 (10), 1806899. The development of 3D in vitro models capable of recapitulating native tumor microenvironments could improve the translatability of potential anticancer drugs and treatments. Here, 3D bioprinting techniques are used to build tumor constructs via precise placement of living cells, functional biomaterials, and programmable release capsules. This enables the spatiotemporal control of signaling molecular gradients, thereby dynamically modulating cellular behaviors at a local level. Vascularized tumor models are created to mimic key steps of cancer dissemination (invasion, intravasation, and angiogenesis), based on guided migration of tumor cells and endothelial cells in the context of stromal cells and growth factors. The utility of the metastatic models for drug screening is demonstrated by evaluating the anticancer efficacy of immunotoxins. These 3D vascularized tumor tissues provide a proof-of-concept platform to i) fundamentally explore the molecular mechanisms of tumor progression and metastasis, and ii) preclinically identify therapeutic agents and screen anticancer drugs.Item Supporting data for "3D Printed Anisotropic Tissue Simulants with Embedded Fluid Capsules for Medical Simulation and Training"(2025-02-10) Somayaji, Adarsh; Lawler, Matthew S; Gong, Alex T; Fuenning , Zachary M; Roach, Victoria A; S., Athira B; Traina, David J; Speich, Jason R; Wang, Ruikang K; Hackett, Matthew G; Hananel, David M; Sweet , Robert M; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C.; McAlpine Research GroupHuman tissues are primarily composed of collagen and elastin fiber networks that exhibit directional mechanical properties which are not replicable by conventional tissue simulants manufactured via casting. Here, we 3D print tissue simulants which incorporate anisotropic mechanical properties through the manipulation of infill voxel shape and dimensions. A mathematical model for predicting the anisotropy of single and multi-material structures with orthogonal infill patterns is developed. We apply this methodology to generate conformal printing toolpaths for replicating the structure and directional mechanics observed in native tissue within 3D printed tissue simulants. Further, a method to embed fluid-filled capsules within the infill structure of these tissue simulants to mimic blood is also presented. The improvements in simulation quality when using 3D printed anisotropic tissue simulants over conventional tissue simulants is demonstrated via a comparative acceptability study. These advances open new avenues for the manufacture of next-generation tissue simulants with high mechanical fidelity for enhanced medical simulation and training.Item Supporting data for "3D Printed Deformable Sensors"(2020-04-28) Zhu, Zhijie; Park, Hyun Soo; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research GroupThe data set includes the experimental data and the corresponding code files supporting the results reported in Zhijie Zhu; Hyun Soo Park; Michael C. McAlpine. 3D Printed Deformable Sensors. Sci. Adv., 2020, DOI: 10.1126/sciadv.aba5575. The ability to directly print compliant biomedical devices on live human organs could benefit patient monitoring and wound treatment, which requires the 3D printer to adapt to the various deformations of the biological surface. We developed an in situ 3D printing system that estimates the motion and deformation of the target surface to adapt the toolpath in real time. With this printing system, a hydrogel-based sensor was printed on a porcine lung under respiration-induced deformation. The sensor was compliant to the tissue surface and provided continuous spatial mapping of deformation via electrical impedance tomography. This adaptive 3D printing approach may enhance robot-assisted medical treatments with additive manufacturing capabilities, enabling autonomous and direct printing of wearable electronics and biological materials on and inside the human body.Item Supporting data for "3D Printed Functional and Biological Materials on Moving Freeform Surfaces"(2020-05-13) Zhu, Zhijie; Guo, Shuang-Zhuang; Hirdler, Tessa; Eide, Cindy; Fan, Xiaoxiao; Tolar, Jakub; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group; Tolar LaboratoryThe data set includes the experimental data supporting the results reported in Zhu, Zhijie, Shuang‐Zhuang Guo, Tessa Hirdler, Cindy Eide, Xiaoxiao Fan, Jakub Tolar, and Michael C. McAlpine. "3D printed functional and biological materials on moving freeform surfaces." Advanced Materials, 30(23), 1707495. Conventional 3D printing technologies typically rely on open‐loop, calibrate‐then‐print operation procedures. An alternative approach is adaptive 3D printing, which is a closed‐loop method that combines real‐time feedback control and direct ink writing of functional materials in order to fabricate devices on moving freeform surfaces. Here, it is demonstrated that the changes of states in the 3D printing workspace in terms of the geometries and motions of target surfaces can be perceived by an integrated robotic system aided by computer vision. A hybrid fabrication procedure combining 3D printing of electrical connects with automatic pick‐and‐placing of surface‐mounted electronic components yields functional electronic devices on a free‐moving human hand. Using this same approach, cell‐laden hydrogels are also printed on live mice, creating a model for future studies of wound‐healing diseases. This adaptive 3D printing method may lead to new forms of smart manufacturing technologies for directly printed wearable devices on the body and for advanced medical treatments.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.Item Supporting data for "3D Printed Polymer Photodetectors"(2020-05-29) Park, Sung Hyun; Su, Ruitao; Guo, Shuang-Zhuang; Qiu, Kaiyan; Joung, Daeha; Fanben, Meng; McAlpine, Michael C; Jeong, Jaewoo; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research GroupExtrusion-based 3D printing, an emerging technology, has been previously used in the comprehensive fabrication of light-emitting diodes using various functional inks, without cleanrooms or conventional microfabrication techniques. Here, polymer-based photodetectors exhibiting high performance are fully 3D printed and thoroughly characterized. A semiconducting polymer ink is printed and optimized for the active layer of the photodetector, achieving an external quantum efficiency of 25.3%, which is comparable to that of microfabricated counterparts and yet created solely via a one-pot custom built 3D-printing tool housed under ambient conditions. The devices are integrated into image sensing arrays with high sensitivity and wide field of view, by 3D printing interconnected photodetectors directly on flexible substrates and hemispherical surfaces. This approach is further extended to create integrated multifunctional devices consisting of optically coupled photodetectors and light-emitting diodes, demonstrating for the first time the multifunctional integration of multiple semiconducting device types which are fully 3D printed on a single platform. The 3D-printed optoelectronic devices are made without conventional microfabrication facilities, allowing for flexibility in the design and manufacturing of next-generation wearable and 3D-structured optoelectronics, and validating the potential of 3D printing to achieve high-performance integrated active electronic materials and devices.Item Supporting data for Renewable Lactam Monomer for Tunable and Processable Polyamides(2025-02-06) Häkkinen, Satu; Krajovic, Daniel; Chamberlain, Kari; Shippee, Joshua; Biswas, Arpan; Zhang, Honghu; Felsenthal, Lillian; Dichtel, William; Hillmyer, Marc; hillmyer@umn.edu; Hillmyer, Marc; Hillmyer GroupThis work aimed to improve the processability and application scope of polyamides by introducing a bio-derivable lactam co-monomer to controllably reduce the polyamides' crystallinity. Tuning the co-monomer composition modulated crystallinity, water uptake, and mechanical properties while achieving newfound solubilities, 3D printability, and structural adhesion properties.