The Role of Hydrogen in ReRAM.

Previous research on transistor gate oxides reveals a clear link between hydrogen content and oxide breakdown. This has implications for redox-based resistive random access memory (ReRAM) devices, which exploit soft, reversible, dielectric breakdown, as hydrogen is often not considered in modeling or measured experimentally. Here quantitative measurements, corroborated across multiple techniques are reported, that reveal ReRAM devices, whether manufactured in a university setting or research foundry, contain concentrations of hydrogen at levels likely to impact resistance switching behavior.

Thin-film design of amorphous hafnium oxide nanocomposites enabling strong interfacial resistive switching uniformity.

A design concept of phase-separated amorphous nanocomposite thin films is presented that realizes interfacial resistive switching (RS) in hafnium oxide-based devices. The films are formed by incorporating an average of 7% Ba into hafnium oxide during pulsed laser deposition at temperatures ≤400°C. The added Ba prevents the films from crystallizing and leads to ∼20-nm-thin films consisting of an amorphous HfO host matrix interspersed with ∼2-nm-wide, ∼5-to-10-nm-pitch Ba-rich amorphous nanocolumns penetrating approximately two-thirds through the films.

Nonideality-Aware Training for Accurate and Robust Low-Power Memristive Neural Networks.

Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever-increasing computing requirements of these structures have contributed to a desire for novel technologies and paradigms, including memristor-based hardware accelerators. Solutions based on memristive crossbars and analog data processing promise to improve the overall energy efficiency.

Brain-inspired computing needs a master plan.

New computing technologies inspired by the brain promise fundamentally different ways to process information with extreme energy efficiency and the ability to handle the avalanche of unstructured and noisy data that we are generating at an ever-increasing rate. To realize this promise requires a brave and coordinated plan to bring together disparate research communities and to provide them with the funding, focus and support needed. We have done this in the past with digital technologies; we are in the process of doing it with quantum technologies; can we now do it for brain-inspired computing?