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Latvian Exponential Technologies secures funding from Horizon Europe for advancing multi-material 3D printing techniques

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Exponential Technologies, a startup based in Riga, obtained €280K funding from the Horizon Europe programme. This funding is meant to support their efforts in developing advanced multi-material 3D printing techniques using machine learning and data science. The company specializes in creating digital models for these innovative printing processes. With this financial backing, Exponential Technologies plans to further refine their technology, particularly focusing on improving their xT SAAM platform. This platform aims to automate the creation of chemical formulations and material innovations, which can significantly speed up research and development in manufacturing sectors.

Exponential Technologies Ltd. was founded in 2019 by the 3 co-founders Pavel Cacivkin, Matthias Kaiser and Girts Smelters to further develop and market the AI/ML algorithms developed by Pavel Cacivkin. It specializes in developing cutting-edge technologies, focusing on areas such as chemical processes, additive fabrication, and biotechnology. They utilize machine learning and data science to create digital models that enable advanced manufacturing techniques, particularly in the field of multi-material 3D printing. Their main goal is to innovate and automate processes in industries by using their xT SAAM platform, which helps in quickly generating chemical formulations, material innovations, and bioprocess parameters. This technology aims to streamline research and development, offering a way for experts and lab workers to create new solutions efficiently without needing extensive expertise in statistics or programming.

“This is our first time taking part in a research project with so many players. It is simultaneously a huge challenge and a great opportunity to find valuable partners,” says Ģirts Smelters, Exponential Technologies CEO.

The MADE-3D project, spearheaded by Exponential Technologies in collaboration with a consortium of esteemed partners including Fraunhofer Institute, Paderborn University, CSEM, Safran S.A., Skyrora, AVL, SLM Solutions, and others, aims to revolutionize the metal 3D printing industry. Funded by the Horizon Europe programme, this initiative endeavors to develop a groundbreaking method for manufacturing multi-material components through a single 3D printing process. By leveraging cutting-edge technologies such as machine learning, data science, and additive manufacturing, the project targets the enhancement of mechanical, electrical, thermal, and magnetic characteristics of components. The primary objective is to create lighter yet more efficient components, potentially reducing their weight by up to 50% compared to existing materials. Scheduled to run until 2025, this collaborative effort seeks to significantly impact industries like automotive, aviation, and space by introducing innovative advancements in manufacturing capabilities.

“Multi-material manufacture using 3D printing is still at the beginning of its development. A lack of ability to combine materials is the greatest challenge currently hindering the forward surge of this technology. In this sense, MADE-3D could be a step forward,” emphasizes Professor Thomas Tröster, MADE-3D Project Coordinator and Head of the Institute for Lightweight Design with Hybrid Systems and Institute for Additive Fabrication of Paderborn University.


“Our aim is to use the discoveries made by the project to achieve more trustworthy processes and greater speed in the multi-material additive manufacturing industry, thus ensuring this innovative technology is even more industrialised,” emphasises Professor Mirko Schaper, Co-Head of the project and Dean of the Faculty of Mechanical Engineering at Paderborn University.

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Nurcin Metingil
Nurcin Metingil
A permanent student, a passionate first reader and nowadays doing master’s degree in Publishing Management. Beside these, I am up for games! I have been playing games since I was 6. Now, I am whispering "Business. Business. Numbers. Is this working?"

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