High-throughput combinatorial printing illustration. The new 3D printing technique, high-throughput combinatorial printing (HTCP), drastically accelerates the discovery and production of new materials. Credit: University of Notre Dame
A novel 3D printing approach called high-throughput combinatorial printing (HTCP) has been produced that significantly speeds up the discovery and production of new materials.
The process involves blending several aerosolized nanomaterial inks throughout printing, which enables great control over the printed products architecture and regional structures. This method produces materials with gradient structures and properties and can be used to a wide variety of compounds including metals, semiconductors, polymers, and biomaterials.
The time-honored Edisonian trial-and-error process of discovery is labor-intensive and sluggish. This hampers the advancement of urgently needed new innovations for clean energy and environmental sustainability, in addition to for electronic devices and biomedical gadgets.
The brand-new 3D printing technique, high-throughput combinatorial printing (HTCP), considerably speeds up the discovery and production of new products. Now Zhang has done just that, developing an unique 3D printing technique that produces products in methods that conventional production cant match. The new procedure blends several aerosolized nanomaterial inks in a single printing nozzle, varying the ink blending ratio on the fly during the printing process. This technique– called high-throughput combinatorial printing (HTCP)– controls both the printed materials 3D architectures and local compositions and produces materials with gradient structures and residential or commercial properties at microscale spatial resolution.
” It usually takes 10 to 20 years to find a new product,” stated Yanliang Zhang, associate teacher of aerospace and mechanical engineering at the University of Notre Dame.
” I believed if we could shorten that time to less than a year– and even a few months– it would be a video game changer for the discovery and production of new materials.”
Now Zhang has done just that, producing a novel 3D printing approach that produces products in ways that conventional production cant match. The brand-new process blends several aerosolized nanomaterial inks in a single printing nozzle, varying the ink mixing ratio on the fly during the printing procedure. This approach– called high-throughput combinatorial printing (HTCP)– controls both the printed materials 3D architectures and regional compositions and produces products with gradient compositions and properties at microscale spatial resolution.
His research was published on May 10, 2023, in the journal Nature.
The aerosol-based HTCP is extremely flexible and applicable to a broad series of dielectrics, semiconductors, and metals, as well as biomaterials and polymers. It creates combinational products that function as “libraries,” each containing countless special structures.
Combining combinational materials printing and high-throughput characterization can considerably accelerate materials discovery, Zhang said. His group has already used this approach to identify a semiconductor material with exceptional thermoelectric properties, a promising discovery for energy harvesting and cooling applications.
In addition to speeding up discovery, HTCP produces functionally graded materials that gradually shift from stiff to soft. This makes them especially beneficial in biomedical applications that require to bridge between soft body tissues and stiff wearable and implantable devices.
In the next stage of research, Zhang and the trainees in his Advanced Manufacturing and Energy Lab strategy to apply artificial intelligence and artificial intelligence-guided strategies to the data-rich nature of HTCP in order to speed up the discovery and development of a broad range of products.
” In the future, I intend to develop a self-governing and self-driving process for products discovery and device production, so trainees in the laboratory can be complimentary to concentrate on top-level thinking,” Zhang said.
Referral: “High-throughput printing of combinatorial products from aerosols” by Minxiang Zeng, Yipu Du, Qiang Jiang, Nicholas Kempf, Chen Wei, Miles V. Bimrose, A. N. M. Tanvir, Hengrui Xu, Jiahao Chen, Dylan J. Kirsch, Joshua Martin, Brian C. Wyatt, Tatsunori Hayashi, Mortaza Saeidi-Javash, Hirotaka Sakaue, Babak Anasori, Lihua Jin, Michael D. McMurtrey and Yanliang Zhang, 10 May 2023, Nature.DOI: 10.1038/ s41586-023-05898-9.
