Answers are grounded in this paper and cite their sources.
The continued scaling of silicon-based dynamic random-access memory (DRAM) slows down due to increased process complexity and reduced storage capacitance. Oxide semiconductors (OS), represented by InGaZnOx (IGZO), offer an attractive alternative owing to their ultralow leakage and low thermal budget, making them promising candidates for next-generation DRAM as well as monolithic three-dimensional (M3D) architectures. However, realizing IGZO devices with well-balanced overall performance, including high performance and high reliability under ultrascaled dimensions, remains challenging. Here, we report ultrascaled IGZO field-effect transistors (FETs) fabricated using an optimized O2 plasma-enhanced atomic-layer deposition (PE-ALD) process. The IGZO FETs deliver state-of-the-art performance, including an on-state current (Ion) of 785 μA/μm at a drain voltage of 0.5 V and a transconductance (gm) of 620 μS/μm at a drain voltage of 1.0 V alongside a contact resistance (Rc) of 164.5 Ω·μm with positive threshold voltage (Vth). Reliability degradation is effectively suppressed, with bias-temperature instability (BTI) down to 8 mV even at extremely scaled contact length (Lc) of 50 nm. Leveraging these optimized devices, we further demonstrated a scaled two-transistor-zero-capacitor (2T0C) DRAM capable of up to 6-bit per cell, long data retention over 4000 s, and write time down to 10 ns. We proposed an M3D-DRAM architecture with vertically stacked multilayer embedded memory for artificial intelligence (AI) accelerators, achieving 77× faster weight loading and 9.6× lower energy consumption compared with mature high-bandwidth memory (HBM) counterpart, while maintaining graphics processing units (GPU)-equivalent inference accuracy of 92.25%. This work demonstrates an effective approach for the co-optimization of performance and reliability in ultrascaled IGZO FETs, providing critical foundation for next-generation DRAM and M3D applications.
No takes yet. Share an insight, caveat, or question.
Wang et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: