Intrinsic program instability in HfO2 RRAM and consequences on program algorithms

Fantini, A.; Gorine, Georgi; Degraeve, R.; Goux, L.; Chen, C. Y.; Redolfi, A.; Clima, Sergiu; Cabrini, A.; Torelli, G.; Jurczak, M.

doi:10.1109/iedm.2015.7409648

Cited by 53 publications

(37 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar to [4], we observe large tails in the lower percentile of the High Resistance State (HRS) distribution that extend with time. However, we attribute these large initial tails to stochastic resistance state fluctuations which falsely trigger the verification mechanism and not rapid relaxation [4], [7] or other slowly changing mechanisms [8]–[10]. Recently it was shown that the occurrence of resistance fluctuations, or fluctuation probability, decays to a constant (non-zero) level within the first hundred microseconds after programming [11].…”

Section: Introductionsupporting

confidence: 83%

“…Spurning convention [4]–[6], the fast pulses are applied with a 50 Ω terminated probe with no current-limiting elements [12] as shown in Fig 1 (a). We rely on the ultra-short pulse timing to ensure that the energy delivered per pulse is small [13] and well controlled.…”

Section: Methodsmentioning

confidence: 99%

“…The stochasticity results in long resistance distribution tails which greatly limit the memory window. Subsequent efforts to control these distribution tails have relied heavily on “program-verification” methods [4]–[6]. It was recently shown that even careful implementation of “program-verify” can result in widely distributed HRS values whose distributions can broaden with time [4].…”

Section: Introductionmentioning

confidence: 99%

“…Subsequent efforts to control these distribution tails have relied heavily on “program-verification” methods [4]–[6]. It was recently shown that even careful implementation of “program-verify” can result in widely distributed HRS values whose distributions can broaden with time [4]. The broadening of the resistance distribution acts to close the memory window and effectively nullifies the efficiency of program-verify.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Impact of RRAM Read Fluctuations on the Program-Verify Approach

Nminibapiel

Veksler

Shrestha

et al. 2017

IEEE Electron Device Lett.

View full text Add to dashboard Cite

The stochastic nature of the conductive filaments in oxide-based resistive memory (RRAM) represents a sizeable impediment to commercialization. As such, program-verify methodologies are highly alluring. However, it was recently shown that program-verify methods are unworkable due to strong resistance state relaxation after SET/RESET programming. In this paper, we demonstrate that resistance state relaxation is not the main culprit. Instead, it is fluctuation-induced false-reading (triggering) that defeats the program-verify method, producing a large distribution tail immediately after programming. The fluctuation impact on the verify mechanism has serious implications on the overall write/erase speed of RRAM.

show abstract

Section: Introductionsupporting

confidence: 83%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impact of RRAM Read Fluctuations on the Program-Verify Approach

Nminibapiel

Veksler

Shrestha

et al. 2017

IEEE Electron Device Lett.

View full text Add to dashboard Cite

show abstract

“…4(a) shows the collected LRS distribution (>3σ ) with readout pulses placed each half decade. Due to the intrinsic variability [10] and resistance instability [13], [14], characteristic of filamentary RRAM, definition of failure criteria suitable for tail study is not trivial. For this reason failure is evaluated "globally" defining for each quantile a resistance threshold R th equal (for the LRS case) to two times the initial (t = 10μs) resistance R init as depicted in Fig.…”

Section: Failure Tail Predictionmentioning

confidence: 99%

Novel Flexible and Cost-Effective Retention Assessment Method for TMO-Based RRAM

Chen

Fantini

Goux

et al. 2016

IEEE Electron Device Lett.

Self Cite

View full text Add to dashboard Cite

In this letter, we propose a novel single-cell, cycle-to-cycle based retention testing method, enabling fast statistical retention assessment on oxide-based resistive random access memory (RRAM). Detailed comparison between cycle-tocycle and device-to-device retention testing methods is made on TiN\HfO 2 \Hf stack showing excellent agreement in terms of failure rate and extracted activation energy. Due to the unique properties of filamentary RRAM, this new retention testing method allows fast and cost effective retention benchmarking of different material stacks and is particularly versed in the study of the impact of programming algorithms.

show abstract

Theory and Technology of Memristive Devices

Tetzlaff

Ascoli

Wouters

2022

Wiley Encyclopedia of Electrical and Electronics Engineering

View full text Add to dashboard Cite

CMOS scaling is progressively and inevitably approaching atomic boundaries. The industry is thus exploring the potential of novel disruptive nanotechnologies, based on multifunctional materials, which may allow the development of integrated circuits keeping the trend predicted by Moore in 1965 in the years to come, despite further transistor shrinking being no longer possible. Memristors, originally postulated only theoretically out of a brilliant line of thought by Chua in 1971 and identified at the nanoscale almost 40 years later, back in 2008, by a team of engineers supervised by R.S. Williams at Hewlett Packard Labs, represent the key nanotechnology of the future, enabling novel forms of computation, which are closer to the principles underlying the functionalities of the human brain, given the extraordinarily peculiar capability of these devices to sense, store, and process data in the same physical miniaturized volume. Achieving progress in memristor circuit design crucially calls for the development of synergies among researchers with different academic backgrounds. In fact, only combining the technical knowledge, acquired by memristor theoreticians, with the practical know‐how of experimenters will enable to foster progress in memristor circuit and system development in the near future. In line with this necessity, the present article is the fruit of a joint cooperation between two leading memristor research units from Germany, one based at TU Dresden, which has contributed to establish solid theoretical foundations on resistance switching memories and their circuits since 2008, and the other one based at RWTH Aachen University, which has been the leading experimental research unit on nanostructures of this kind over the same time span. This article first presents a comprehensive overview of the theory of memristors, starting off from the early achievements in the pioneering studies of their father Chua, then classifies and analyses in depth the main physical mechanisms underlying the inherently nonlinear behavior of their physical realizations, and, finally, discusses their most promising applications, from the development of new nonvolatile memories based on resistance switching phenomena to the realization of novel neuromorphic circuits, capable to mimic the complex dynamics of biological entities closer than conventional purely CMOS hardware, without leaving aside an excursus on the potential to leverage the unique features of these devices for the circuit implementation of unconventional brain‐inspired time‐ and energy‐efficient sensing and memcomputing strategies, which is a great appeal for the realization of portable light‐weight technical systems for the Internet‐of‐Things industry, especially but not only to the benefit of healthcare, well‐being, and automotive market sectors.

show abstract

Intrinsic program instability in HfO2 RRAM and consequences on program algorithms

Cited by 53 publications

References 0 publications

Impact of RRAM Read Fluctuations on the Program-Verify Approach

Impact of RRAM Read Fluctuations on the Program-Verify Approach

Novel Flexible and Cost-Effective Retention Assessment Method for TMO-Based RRAM

Theory and Technology of Memristive Devices

Contact Info

Product

Resources

About