Partnerships for Emerging Technologies
The JTFI has awarded funding to the below research projects as part of the exciting new Partnerships for Emerging Technologies initiative. Through this support, the JTFI aims to deepen collaborative research opportunities among the University, Argonne, and Fermilab, position the projects to successfully scale and secure large-scale sponsored research funding, and accelerate the development of transformational research and technology that deliver high-impact results to society. The selected projects cut across four topic areas: Energy Technologies, Microelectronics, High-Throughput Autonomous Discovery, and AI-Microelectronics for Advanced Scientific Instrumentation.
| Project Name | Research Team |
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CMOS pixel sensors: enabling particle physics discoveries with advanced US microelectronics |
Karri DiPetrillo (UChicago), Farah Fahim and Pamela Klabbers (Fermilab), and Jinlong Zhang (Argonne) |
| Automated programmable fabrication of monodisperse sequence-defined conjugated polymers enabled by artificial intelligence-aided high-throughput robotic systems |
Guangbin Dong (UChicago) and Jie Xu (Argonne)
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| A high-performance multi-channel low-power ASIC with one pico- second resolution for emerging detector technologies | Henry Frisch and Eric Oberla (UChicago), and Troy England, Sudeshna Ganguly, Paul Rubinov, and Katsuya Yonehara (Fermilab) |
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Multi frame storage enabled by Direct Write techniques and circuit design for new multi-frame storage microelectronics hardware: Enablement for high speed, high dynamic range cameras
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Supratik Guha (UChicago), Farah Fahim and Hongzhi Sun (Fermilab)
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| Single-crystal silicon carbide membranes for heterogeneous microelectronics and quantum technologies | Alexander High (UChicago), Stephan Hruszkewycz and Katherine Harmon (Argonne) |
| Terahertz imaging spectroscopy for high-throughput non-contact charge transport mechanistic study and materials discovery | Po-Chun Hsu (UChicago) and Jie Xu (Argonne) |
| A mix-dopant strategy to achieve PGE-free OER catalysts for H2 production via water electrolysis | Chong Liu (UChicago) and Di-Jia Liu (Argonne) |
| Discovering new physics with autonomous data-processing and filtering at high-throughput physics facilities using real-time AI and embedded systems | David Miller, Yuxin Chen, and Cecilia Tosciri (UChicago), Christian Herwig, Jennifer Ngadiuba and Nhan Tran (Fermilab) |
| Characterizing, modeling and predicting degradation mechanisms in all-solid state batteries | Shirley Meng (UChicago) and Gary Hu, Bipul Barua and Eungje Lee (Argonne) |
| Enabling exascale discovery in neutrino science | David Schmitz (UChicago), Corey Adams (Argonne) |
| Leveraging integrated machine learning, simulation, and automation to enable solid-state mixed ion-electron conducting polymers | Sihong Wang and Paul Nealey (UChicago), and Jie Xu (Argonne) |
| Edge intelligence via compositional learning: Neuromorphic electrochemical transistor arrays | Fangfang Xia (Argonne) and Sihong Wang (UChicago) |
Funded in collaboration with the Big Idea Generator and divisions
| Project name | Research team |
| Bridging between communities and scientists: Developing a participatory artificial intelligence approach for addressing urban climate change | Marshini Chetty (UChicago) |
| An engineered enhanced weathering system for large-scale carbon sequestration from the atmosphere toward synergizing renewable energy and direct carbon removal | Cheng Wang (Argonne) |
| Self-driving laboratory for polymer discovery | Jie Xu (Argonne) |