Keren Stern | Searcharxiv

arXiv2026

Energy and Scaling Limits of Phase-Change Memory

Phase change memory (PCM) relies on a reversible transition between amorphous and crystalline states of a material, and stands as a promising candidate for next-generation, energy-efficient data storage and neuromorphic hardware. Here, we review key innovations that have driven PCM technology to achieve energy consumption down to only tens of femtojoules per bit, and could further advance it closer to its fundamental limits. Because PCM switching is induced thermally, we highlight improvements in energy-efficiency through two primary strategies: by minimizing the active phase change material region to sub-10 nm dimensions, and by enhancing heat confinement within PCM devices to reduce thermal dissipation into the surrounding environment. While the theoretical limits could reach single attojoules per cubic nanometer of memory material, realizing these limits in practice is significantly constrained by electrical and thermal parasitics, particularly at contacts and interfaces.

cond-mat.mtrl-sci↗

arXiv2021

Uncovering Phase Change Memory Energy Limits by Sub-Nanosecond Probing of Power Dissipation Dynamics

Phase change memory (PCM) is one of the leading candidates for neuromorphic hardware and has recently matured as a storage class memory. Yet, energy and power consumption remain key challenges for this technology because part of the PCM device must be self-heated to its melting temperature during reset. Here, we show that this reset energy can be reduced by nearly two orders of magnitude by minimizing the pulse width. We utilize a high-speed measurement setup to probe the energy consumption in PCM cells with varying pulse width (0.3 to 40 nanoseconds) and uncover the power dissipation dynamics. A key finding is that the switching power (P) remains unchanged for pulses wider than a short thermal time constant of the PCM ($τ$$_t$$_h$ < 1 ns in 50 nm diameter device), resulting in a decrease of energy (E=P$τ$) as the pulse width $τ$ is reduced in that range. In other words, thermal confinement during short pulses is achieved by limiting the heat diffusion time. Our improved programming scheme reduces reset energy density below 0.1 nJ/$μ$m$^2$, over an order of magnitude lower than state-of-the-art PCM, potentially changing the roadmap of future data storage technology and paving the way towards energy-efficient neuromorphic hardware

cond-mat.mes-hall↗