Material extrusion has shown promise in the fabrication of biocompatible scaffolds for tissue engineering using medical biodegradable hydrogel materials. However, the uncontrollable shape of prepared 3D architecture decelerates the development of large-size complex hydrogel models for the fabrication of human-scale tissue or organs. A primary cause of the collapse as well as shrinkage of prepared architectures is the uncontrollable ambient temperature distribution during the extruding process for hydrogel materials. Therefore, there is a need to accurately control the temperature gradient in the printing space during the material extrusion. The study proposed a novel temperature-controlled substrate configuration with a multilayered enclosure, by which the temperature gradient in the printing space can be regulated by varying the height as well as the internal diameter of the enclosure. Subsequently, a finite element simulation model, as well as a self-developed temperature measuring device, was established to numerically and experimentally investigate the temperature distribution in the printing space. Furthermore, printing trials were implemented on the novel substrate. The collapse of 3D architectures was successfully avoided, and the height of scaffolds was improved obviously from 2.21 mm to 13.24 mm.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.compbiomed.2023.107722 | DOI Listing |
KN J Cartogr Geogr Inf
December 2024
Department of Neuropsychology, Ruhr-University Bochum, Bochum, Germany.
When using navigation devices the "cognitive map" created in the user's mind is much more fragmented, incomplete and inaccurate, compared to the mental model of space created when reading a conventional printed map. As users become more dependent on digital devices that reduce orientation skills, there is an urgent need to develop more efficient navigation systems that promote orientation skills. This paper proposes to consider brain processes for creating more efficient maps that use a network of optimally located cardinal lines and landmarks organized to support and stabilize the neurocognitive structures in the brain that promote spatial orientation.
View Article and Find Full Text PDFComput Biol Med
December 2024
Center for Lightweight Materials, Design, and Manufacturing, Department of Mechanical Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi (KMUTT), Bangmod, Bangkok, 10140, Thailand; OsseoLabs Co. Ltd., Bangkok, 10400, Thailand. Electronic address:
Sacral chordoma, an invasive tumor, necessitates surgical removal of the tumor and the affected region of the sacrum, disrupting the spinopelvic connection. Conventional reconstruction methods, relying on rod and screw systems, often face challenges such as rod failure, sub-optimal stability, and limited osseointegration. This study proposes a novel design for a porous-based sacral reconstruction prosthesis.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China.
The wind-induced vibration energy harvester is a type of ideal power source for wireless sensor nodes. To adapt to the uncertainty of wind direction in natural environments, this paper proposes a three-dimensional multi-directional piezoelectric wind energy harvester (WEH), whose bluff body is an external shell with the shape like a lampshade, supported by three internal piezoelectric composite beams. A harvester prototype was made using 3D printing technology, and its multi-directional energy harvesting characteristics were systematically tested in a wind tunnel.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
The abrasives of traditional grinding wheels are usually randomly arranged on the substrate, reducing the number of effective abrasive grains involved in the machining during the grinding process. However, there are some problems such as uneven distribution of chip storage space, high grinding temperature, and easy surface burn. In trying to address this issue, an ultrasonic vibration 3D printing method is introduced to fabricate the structured CBN (Cubic Boron Nitride) grinding wheel.
View Article and Find Full Text PDFFoods
November 2024
Department of Food Engineering, Dankook University, 119, Dandae-ro, Dongnam-gu, Cheonan-si 31116, Chungcheongnam-do, Republic of Korea.
The Food Process Robot Intelligent System (FPRIS) integrates a 3D-printed six-axis robotic arm with Artificial Intelligence (AI) and Computer Vision (CV) to optimize and automate the coffee roasting process. As an application of FPRIS coffee roasting, this system uses a Convolutional Neural Network (CNN) to classify coffee beans inside the roaster and control the roaster in real time, avoiding obstacles and empty spaces. This study demonstrates FPRIS's capability to precisely control the Degree of Roasting (DoR) by combining gas and image sensor data to assess coffee bean quality.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!