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About

Manuel Tsotsalas is a leading researcher at the intersection of advanced materials chemistry and automation, whose work is pioneering the fabrication of "living" microstructures and the intelligent optimization of metal–organic frameworks (MOFs). His key research areas include 3D laser printing, dynamic polymer chemistry, and the machine learning-driven synthesis of MOF thin films. Tsotsalas made a major contribution by developing "covalent adaptable microstructures" through the combination of two-photon laser printing and alkoxyamine chemistry, a breakthrough that allows for the creation of programmable 3D microstructures whose mechanical properties can be adapted on demand—a critical advance for soft robotics and microfluidics. In parallel, he has been a trailblazer in the automated synthesis of MOF thin films, demonstrating how machine learning can dramatically enhance film quality and device integration. His highly cited works, including a 2022 study on robot-based MOF growth (44 citations) and a 2024 case study on HKUST-1 optimization (14 citations), underscore his impact in establishing data-driven, reproducible methods for materials discovery. With over 47 citations on his most prominent work, Tsotsalas is shaping the future of adaptive, intelligent materials.