Downloads provided by UsageCountsEpitaxial ferroelectric memristors integrated with silicon
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Miguel Rengifo; Miguel Rengifo; Miguel Rengifo; Myriam H. Aguirre; Myriam H. Aguirre; Myriam H. Aguirre; Martín Sirena; +4 Authors
Miguel Rengifo; Miguel Rengifo; Miguel Rengifo; Myriam H. Aguirre; Myriam H. Aguirre; Myriam H. Aguirre; Martín Sirena; Martín Sirena; Ulrike Lüders; Diego Rubi; Diego Rubi;
Epitaxial ferroelectric memristors integrated with silicon
Neuromorphic computing requires the development of solid-state units able to electrically mimic the behavior of biological neurons and synapses. This can be achieved by developing memristive systems based on ferroelectric oxides. In this work we fabricate and characterize high quality epitaxial BaTiO3-based memristors integrated with silicon. After proving the ferroelectric character of BaTiO3 we tested the memristive response of LaNiO3/BaTiO3/Pt microstructures and found a complex behavior which includes the co-existence of volatile and non-volatile effects, arising from the modulation of the BaTiO3/Pt Schottky interface by the direction of the polarization coupled to oxygen vacancy electromigration to/from the interface. This produces remanent resistance loops with tunable ON/OFF ratio and asymmetric resistance relaxations. These properties might be harnessed for the development of neuromorphic hardware compatible with existing silicon-based technology.
Argentina, Spain
Artificial neural network, Silicon, Artificial intelligence, Dielectric, INTEGRATION WITH SILICON, Ferroelectricity, Memristive Devices for Neuromorphic Computing, Ferroelectric Devices for Low-Power Nanoscale Applications, perovskites, TP1-1185, Cellular and Molecular Neuroscience, Layer (electronics), Engineering, https://purl.org/becyt/ford/1.3, FOS: Electrical engineering, electronic engineering, information engineering, Nanotechnology, Electrical and Electronic Engineering, Optoelectronics, https://purl.org/becyt/ford/1, Neuromorphic Computing, FERROELECTRICS, FOS: Nanotechnology, MEMRISTORS, Electronic engineering, Chemical technology, ferroelectrics, Life Sciences, Neural Interface Technology, integration with silicon, Memristor, neuromorphic computing, Computer science, Neuromorphic engineering, Materials science, Chemistry, memristors, PEROVSKITES, Physical chemistry, Physical Sciences, NEUROMORPHIC COMPUTING, Non-Volatile Memory, Polarization (electrochemistry), Neuroscience, Epitaxy
Artificial neural network, Silicon, Artificial intelligence, Dielectric, INTEGRATION WITH SILICON, Ferroelectricity, Memristive Devices for Neuromorphic Computing, Ferroelectric Devices for Low-Power Nanoscale Applications, perovskites, TP1-1185, Cellular and Molecular Neuroscience, Layer (electronics), Engineering, https://purl.org/becyt/ford/1.3, FOS: Electrical engineering, electronic engineering, information engineering, Nanotechnology, Electrical and Electronic Engineering, Optoelectronics, https://purl.org/becyt/ford/1, Neuromorphic Computing, FERROELECTRICS, FOS: Nanotechnology, MEMRISTORS, Electronic engineering, Chemical technology, ferroelectrics, Life Sciences, Neural Interface Technology, integration with silicon, Memristor, neuromorphic computing, Computer science, Neuromorphic engineering, Materials science, Chemistry, memristors, PEROVSKITES, Physical chemistry, Physical Sciences, NEUROMORPHIC COMPUTING, Non-Volatile Memory, Polarization (electrochemistry), Neuroscience, Epitaxy
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