Lena Pilz
Papers
3
Total Citations
67
H-Index
3
About
Dr. Lena Pilz is a pioneering researcher at the forefront of integrating machine learning with materials chemistry, specializing in the automated synthesis and optimization of metal-organic framework (MOF) thin films. Her work addresses a critical bottleneck in MOF-based device integration: achieving high-quality, reproducible thin films with tailored properties. Dr. Pilz’s major contributions center on developing fully automated, robot-driven workflows guided by machine learning algorithms to optimize MOF thin film growth. Her landmark 2022 paper, "Fully Automated Optimization of Robot‐Based MOF Thin Film Growth via Machine Learning Approaches" (44 citations), established a paradigm for high-throughput experimentation in this domain. She further refined these methods in her 2024 study on HKUST-1 SURMOF optimization (14 citations), demonstrating how ML can enhance film quality for sensors and photodetectors. Most recently, her 2025 work (9 citations) achieved a breakthrough by using ML-driven robotic synthesis to fabricate Cu₃(HHTP)₂ thin films exhibiting Dirac-cone-induced metallic conductivity—a property previously elusive in MOFs. This finding opens the door to a new class of highly conductive, metallic MOFs for next-generation electronic devices. Dr. Pilz’s research is not only advancing fundamental materials science but also providing a scalable, intelligent platform for discovering functional MOF thin films.
Research Focus
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Top Papers
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