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MAY 2024 I PCB007 MAGAZINE 51 With ongoing advance- ments in machine learn- ing algor ithms, A M t e c h n o l o g i e s , a n d material science, the barriers to innovation are rapidly diminish- ing, paving the way for a new era of cre- ativity and making the future of electronics prototyping very prom- ising. PCB007 Nick Geddes is chief technol- ogy officer at Nano Dimension, a leading provider of additively manufactured electronics (AME) technol- ogy—an alternative in-house method of fabricating PCBs and other electronic devices. Images provided by Nano Dimension. rithms and computational modeling, researchers can expedite the dis- cover y and develop- ment of novel con- ductive and dielec- tric materials tai- lored for specific AM applications. These a d v a n c e d m a t e r i - als exhibit enhanced conductivity, flexibil- ity, and thermal stability, enabling the fabrication of high-performance PCBs with greatly improved functionality. Furthermore, machine learning algo- rithms can optimize material compositions and print configurations to achieve specific elec- trical properties, such as impedance match- ing and signal integrity. is fine-tuned control over material properties empowers designers to realize complex PCB designs that were pre- viously unattainable with conventional manu- facturing methods.