Apr 24, 2024
9:30am - 9:45am
Room 436, Level 4, Summit
Yan Liu1,Franz Fischer2,Hongrong Hu1,Hartmut Gliemann1,Carsten Natzeck1,Christof Wöll1,Ben Breitung1,Jasmin Aghassi-Hagmann1
KIT1,RWTH Aachen University2
Yan Liu1,Franz Fischer2,Hongrong Hu1,Hartmut Gliemann1,Carsten Natzeck1,Christof Wöll1,Ben Breitung1,Jasmin Aghassi-Hagmann1
KIT1,RWTH Aachen University2
Memristors, as fundamental electronic components, have the unique ability to retain a memory of its past electrical resistance state based on the charge that has flown through it. They have generated considerable interest in the field of electronics due to their potential to revolutionize memory and computing technology. Moreover, they offer a combination of non-volatile storage, high-speed operation, and the ability to perform analog computation, which can be advantageous in certain computing tasks and artificial intelligence applications.<br/>Metal Organic Frameworks (MOFs) consist of metal ions connected by organic linkers, resulting in intricate structures with well-defined porosities, which leave spaces for ions, vacancies or guest molecules to immigration and provides an excellent environment for electrochemical metallization (ECM) memristors.<br/>Integrating MOFs into additive manufacturing techniques like inkjet printing can revolutionize their applicability, opening doors to large-scale production of patterned MOF devices. In this talk, the first demonstration of inkjet printed HKUST-1 directly integrated into a printed electronic device, particularly a memristor, will be presented, marking a significant advancement in the field of printed electronics. Furthermore, the inkjet printed memristors can serve as both, non-volatile memories and artificial synapses, for neuromorphic computing. Additionally, the ability of inkjet-printed memristors to act as artificial synapses for neuromorphic applications under different forms of synaptic short-term plasticity was investigated. This study showcases the potential of inkjet printed MOF memristors and will pave the way for high performance memristors in the field of neuromorphic computing, thus, it will further advance the development of artificial intelligence.