Smart multifunctional memory devices capable of sensing: The role of responsive materials in advancing nonvolatile memories
Year: 2025
Type: article
Abstract: • Data-centric demands surpass von Neumann limits, driving new computing paradigms. • Next-gen devices unify sensing, computing, and storage in one platform. • Multifunctional memories adapt to diverse stimuli for smarter operation. • We review retention and sensing mechanisms across nonvolatile memory systems. • In-memory sensing harnesses light, humidity, gases, and chemical triggers. In-memory sensing represents a paradigm shift in the integrated device domain, offering a holistic approach to sensing, memory, and processing functionalities within a single unit. This review comprehensively explores nonvolatile memory devices, emphasizing their role as fundamental components for integrating diverse functionalities. The discussion encompasses various in-memory sensing approaches utilizing a range of memory technologies, including charge-trapping memory, memcapacitors, memristors, ferroelectric transistors, and phase-change memory. Such devices, constructed using different materials and operating through diverse mechanisms, offer versatility and efficiency in sensing applications. Furthermore, this review highlights the capability of such devices to respond to a broad spectrum of physical stimuli, including temperature variations, sound, and pressure; their utility in chemical sensing, including gas detection and quantification; and their application in humidity sensing. Furthermore, recent developments in multimodal sensing and integrated in-memory sensing and computing in artificial sensory systems are elucidated. The challenges and potential future trajectories in the rapidly evolving field are discussed, underscoring the transformative impact of the advancements in artificial intelligence and machine learning technologies.
Source: Materials Today
Authors: Bashayr Alqahtani, Dhananjay Kumbhar, Abdul Momin Syed, M.D. Hasan Raza Ansari, Hanrui Li, Kevin Dominguez, Pratibha Pal, Malak Albagami, Dayanand Kumar, Abril Alvarado, Nazek El-Atab
Institution: King Abdullah University of Science and Technology
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $6,070
OpenAlex ID: W4414090728
