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Researchers at Washington State University have achieved a significant breakthrough in 3D printing technology. Their innovative artificial intelligence algorithm promises to transform the manufacturing of complex structures, showing potential applications in the production of artificial organs, flexible electronics, and wearable biosensors.
The study showcased the algorithm’s capability to not only detect but also to perfect the printing of organ models such as kidneys and prostates, enhancing them through 60 iterations. This advancement could drastically alter the 3D printing field and drive forward innovation at an extraordinary pace.
“You can optimize the results, saving time, cost, and labor,” stated Kaiyan Qiu, co-corresponding author of the study and Berry Assistant Professor in the WSU School of Mechanical and Materials Engineering.
The advancement of 3D printing technology has dramatically increased its utility across various sectors, enabling professionals in industrial engineering to seamlessly convert designs from digital files to real-world applications. These applications include everything from wearable technology to components used in aerospace and even advanced battery systems.
Yet, the process remains challenging and time-consuming for engineers as they strive to identify the best printing conditions for their particular projects. Deciding on the appropriate materials, printer settings, and the pressure used in the nozzle is crucial as these factors greatly affect the end product’s quality.
“The vast array of possible settings combinations is daunting, and experimenting can be costly both in terms of time and resources,” stated Jana Doppa, co-corresponding author and the Huie-Rogers Endowed Chair Associate Professor of Computer Science at WSU.
Significant efforts by researchers such as Qiu and Doppa have been channelled into creating sophisticated, realistic 3D-printed models of human organs. These models are especially valuable for medical training and device testing as they closely mimic the real physical and mechanical properties of human organs, including detailed structures like veins and arteries.
To optimize 3D printing settings for intricate models, researchers Qiu, Doppa, and their team utilized a method known as Bayesian Optimization. This technique allowed them to enhance three crucial aspects of their organ models: geometric accuracy, porosity or weight, and the time taken to print. The porosity is especially important in surgical settings as it affects the model’s mechanical characteristics depending on its density.
“Balancing all the objectives is challenging, yet we managed to find an optimal balance and achieved the highest quality print possible, regardless of the type of print or the shape of the material,” explained Eric Chen, co-first author and visiting student at WSU in Qiu’s group within the School of Mechanical and Materials Engineering.
Alaleh Ahmadian, another co-first author and WSU graduate student in the School of Electrical Engineering and Computer Science, stressed the importance of achieving balanced objectives for successful outcomes. She noted the rewarding nature of conducting interdisciplinary research that combines physical lab experiments to generate real-world effects, by adding, “It is very rewarding to work on interdisciplinary research by performing physical lab experiments to create real-world impact.”
The team initially used the AI program to create a rehearsal model of a prostate surgically, showcasing the versatility of the algorithm. Remarkably, they were able to fine-tune the system with only minor changes to produce a model of a kidney.
“That means that this method can be used to manufacture other more complicated biomedical devices and even to other fields,” said Qiu.
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