Enhanced Linear Conductance Modulation by La‐Doping in HfO ₂ ‐Based Memristors for Neuromorphic Applications

Abstract Efficient computing systems require low‐power and high‐density memory technologies capable of supporting advanced applications such as neuromorphic computing and artificial intelligence. Hafnium oxide (HfO 2 ) based resistive random‐access memory (RRAM) is a promising candidate to this end because of its Complementary Metal‐Oxide‐Semiconductor (CMOS) compatibility and reliable switching behavior. In this work, the effects of lanthanum (La) doping in hafnium oxide are assessed in connection with the memristor performance for neuromorphic applications. It shows that substitution of La stabilizes the cubic phase of (Hf,La)O 2 lowering the oxygen vacancies formation energy and, thereby, favoring their migration properties. La‐doped HfO 2 ‐based memristors show reduced forming and operating voltages, improved switching uniformity, and increased endurance. These memristors exhibit electric field‐driven resistive switching with low voltage variability and most important linear conductance modulation under ultra‐fast pulsed stimulation. These improvements indicate that La‐doped HfO 2 memristors offer significant advantages for energy efficient and reliable analog computing as compared to undoped devices. These findings suggest that La‐doped HfO 2 RRAM has the potential to be a key technology for future analog neuromorphic applications in next‐generation computing architectures.