Answers are grounded in this paper and cite their sources.
The relentless demand for data‐intensive computing has exposed the fundamental bottlenecks of the conventional von Neumann architecture, driving the search for alternative processing paradigms. Memristors have emerged as compelling building blocks for next‐generation in‐memory and neuromorphic computing. Within this domain, heterojunction‐based memristors stand out as highly promising candidates, leveraging interfacial engineering to deliver exceptional device performance and multifunctional capabilities. This review provides a comprehensive and critical overview of recent advancements in heterojunction memristors. We systematically examine the material systems, structural classifications, and fabrication strategies that underpin these devices, followed by an in‐depth analysis of their underlying resistive switching (RS) mechanisms. Furthermore, we highlight their transformative potential across diverse application domains, spanning data storage, artificial synapses, neuromorphic biomimetic sensory perception, and advanced logic circuits. Finally, we address the prevailing technical challenges and propose viable strategies, offering a strategic roadmap for the rational design of high‐performance heterojunction memristors to power the future of neuromorphic hardware.
No takes yet. Share an insight, caveat, or question.
Yin et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: