# Advances in Emerging Memory Technologies: From Data Storage to Artificial Intelligence
## 3 Overview of Emerging Memory Technologies  
### Emerging Memory Technologies  
#### 3.1.1 Filamentary Memory  
Filamentary memories (Figure 2), also known as resistive random access memories (RRAM) are based on the reversible formation and disruption of a conductive filament in an insulator sandwiched between two metal electrodes when an electric field is applied. This electrical behavior was first reported in the 1960s [41; 42] and was largely studied until the early 1980s for memory device applications. In the 2000s, new classes of RRAM appeared and the interest in this technology returned [43]. Two classes of filamentary memories can be distinguished: in oxide RAM (OxRAM, the filament comes from the formation of oxygen vacancies in the resistive layer, while in CBRAM (conductive bridging RAM), it results from the dissolution of an active electrode generally made of Cu or Ag. RRAM technology has many advantages. It is a low-cost two-terminal device and the number of integration steps is lower than in standard Flash. It also has a low voltage operation: typical RRAM operating voltages are 1-3 V, which is much lower than \(\sim\)20 V of Flash NAND memories. In addition, RRAM is a fast memory, with a typical programming time of 100 ns. Less than 10 ns programming times were also reported in the literature [46]. Resistive RAM underwent a strong improvement in its performance and maturity. Demonstrations of macros are now reported down to the 22 nm node. Bitcell area of less than 0.05 um\({}^{2}\)[47] was achieved by Intel, and 20 nm cell size functionality was demonstrated by Panasonic with high performances [48]. The endurance of macros of more than one megabyte now reach 10-100 kcycles, while the intrinsic endurance was demonstrated to be more than 10\({}^{10}\) cycles for single cells [49], showing the technology's reliability can be further improved. In particular, Panasonic demonstrated a limited resistance distribution shift up to 100 k with 10-ppm bitcell resolution [50], and [PERSON] showed no fail after 10\({}^{5}\) cycles on 16 kb arrays on a 28 nm node [44]. High-temperature operation is affected by oxygen vacancies (or metal) temperature assisted diffusion, limiting RRAM retention. In particular, device stability becomes critical when low programming currents are used [51]. [PERSON] demonstrated that it was possible  
Figure 2: TEM cross sections of an HfO\({}_{2}\) based OxRAM integrated in the BEOL of a 28 nm FDSOI technology, from [44] (top) and an OxRAM/OTS device integrated in the BEOL of a 130 nm CMOS process, from [45] (bottom). The OTS (Ovonic Threshold Switch) backend selector is composed of a C/GeSeSbN/C stack. to reach a \(-68\) margin (with a one bit ECC) after 40 min at 200 \({}^{\circ}\)C (equivalent to 10 years at 85 \({}^{\circ}\)C), which corresponds to a 0.1% chip failure of two-megabyte cells [52]. Finally, good scalability was shown: scaled memory devices include: 10 nm crossbar OxRAM [53] and 5 nm liner CBRAM [54]; further density improvements could be obtained with vertical RRAM architecture [43]. As filamentary switching can be observed in most integrated layers, many elements were investigated until some consensus finally appeared on transition metal oxides (Ta\({}_{2}\)O\({}_{5}\), HfO\({}_{2}\), Al\({}_{2}\)O\({}_{3}\), etc.). Depending on the integrated materials, various device performances are possible, enabling targeting of various applications. Today the main application of RRAM is in embedded products. For classical embedded technologies, chip cost reduction will be very difficult beyond 2\(\times\) nm nodes, due to their limited scalability and increasing complexity for integration in sub\(-\)28 nm CMOS nodes [20]. For that reason, RRAM is a strong candidate for future nodes due to its simple bitcell structure and low process complexity. RRAM is highly studied for IoT for its good density and low power consumption. Panasonic proposed the first commercially available implementation of RRAM.