Diffusion of Adhesion Layer Metals Controls Nanoscale Memristive Switching

Yang, J. Joshua; Strachan, John Paul; Xia, Qiangfei; Ohlberg, Douglas A. A.; Kuekes, Philip J.; Kelley, Ronald D.; Stickle, William F.; Stewart, Donald C.; Medeiros‐Ribeiro, G.; Williams, R. Stanley

doi:10.1002/adma.201000663

Cited by 112 publications

(88 citation statements)

References 46 publications

(31 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The bottom electrodes are patterned using conventional optical lithography on silicon substrates SiO 2 /Si (200 nm/500 mm). An anchoring layer of Ti (5 nm) and a Pt layer (25 nm) are deposited by e-beam evaporation before lift-off of the patterned resist 47 . Then, a 30-nm TiO 2 switching layer is fabricated by atomic layer deposition at 200°C using titanium isopropoxide (C 12 H 28 O 4 Ti) and water as the precursor and reactant, respectively.…”

Section: Methodsmentioning

confidence: 99%

Pattern classification by memristive crossbar circuits using ex situ and in situ training

2013

View full text Add to dashboard Cite

Memristors are memory resistors that promise the efficient implementation of synaptic weights in artificial neural networks. Whereas demonstrations of the synaptic operation of memristors already exist, the implementation of even simple networks is more challenging and has yet to be reported. Here we demonstrate pattern classification using a single-layer perceptron network implemented with a memrisitive crossbar circuit and trained using the perceptron learning rule by ex situ and in situ methods. In the first case, synaptic weights, which are realized as conductances of titanium dioxide memristors, are calculated on a precursor software-based network and then imported sequentially into the crossbar circuit. In the second case, training is implemented in situ, so the weights are adjusted in parallel. Both methods work satisfactorily despite significant variations in the switching behaviour of the memristors. These results give hope for the anticipated efficient implementation of artificial neuromorphic networks and pave the way for dense, high-performance information processing systems.

show abstract

Section: Methodsmentioning

confidence: 99%

Pattern classification by memristive crossbar circuits using ex situ and in situ training

2013

View full text Add to dashboard Cite

show abstract

“…2(a). In fact, Cr can chemically reduce TiO 2 and create oxygen vacancies in the TiO 2 layer [26]. The reason is that there are many other phases in the Ti-O system, such that Cr does not have to reduce the oxide all the way to Ti metal, and the full set of intermediate oxide phases are not shown in a normal Ellingham diagram.…”

mentioning

confidence: 99%

“…Then a blank TiO 2 layer of 25 nm was sputter deposited at a substrate temperature 270 • C. During the deposition of the TiO 2 layer, the Ti adhesion layer diffused through the bottom Pt electrode at the elevated deposition temperature, reached the Pt/TiO 2 interface, reacted with the TiO 2 layer and created a significant Fig. 1 (a)-(f) I -V [26]. This bottom interface remained conductive during all the electrical testing, and the more resistive top interfaces dominated the electronic transport in these devices.…”

mentioning

confidence: 99%

“…For example, an asymmetry between the two interfaces in the metal/oxide/metal structure is very helpful in obtaining a repeatable switching behavior with well-defined switching polarity [4,26], where the oxygen vacancy rich interface can serve as a reservoir of the mobile ions and the switching occurs at the relatively oxygen vacancy poor interface. Since the interface reactions between the top metal electrodes and the oxide essentially take place at ambient temperature (except for some heating caused by e-beam depositions), the thickness of the interfacial layer is expected to be comparable to or less than that of the native oxide on the surface of a metal.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Metal/TiO2 interfaces for memristive switches

et al. 2011

Self Cite

View full text Add to dashboard Cite

The interfaces between metal electrodes and the oxide in TiO 2 -based memristive switches play a key role in the switching as well as in the I -V characteristics of the devices in different resistance states. We demonstrate here that the work function of the metal electrode has a surprisingly minor effect in determining the electronic barrier at the interface. In contrast, Ti oxides can be readily reduced by most electrode metals. The amount of oxygen vacancies created by these chemical reactions essentially determines the electronic barrier at the device interfaces.The memristor, the fourth fundamental passive circuit element [1][2][3], has a wide variety of potential applications based on its promising device properties [1][2][3][4][5][6][7], including non-volatility, fast switching (<10 ns), low energy (∼1 pJ/operation), multiple-state operation, scalability and stackability. As suggested by the name, memristors can be used for information storage [8][9][10][11][12][13][14]. Moreover, memristors can function as stateful Boolean logic gates via the material implication operation [15]. In addition, memristors can also be used for neuromorphic computing [16,17] because of their analog switching, and some hybrid circuits due to their ease of stacking [18,19].Among all the kinds of switching materials that have been reported, oxides are the most extensively studied [4]. The interfaces between the metal electrodes and the oxide play a crucial role, especially for bipolar switches [5,6,20]. Under an applied electric field, oxygen vacancies can drift into the interface region, reducing the electronic barrier and resulting in a low-resistance state. Under an electric field with the opposite polarity, the oxygen vacancies are repelled away from the interface region, recovering the electronic barrier to regain the high resistance state [6,21,22]. A family of nanodevices with different switching and currentvoltage (I -V ) characteristics has been demonstrated by manipulating the elemental composition at the two interfaces of a simple metal/oxide/metal device stack [23]. For a crossbar array of memristors in a storage/memory circuit, sneak path currents [24] can be minimized by using memristors with a rectifying I -V characteristic, especially when they are in the low-resistance state. Therefore, interface engineering is critical to obtain the desired switching behavior and electrical properties for memristive devices.From a semiconductor physics point of view, the work function of the electrode metal might be an important factor in determining the electronic barrier at the metal/oxide interface [25]. This barrier in our thin film devices is not a traditional Schottky barrier because the oxide film is amorphous with a large concentration of defects and likely thinner than the depletion region of the semiconducting oxide. We prepared a set of 5 µm × 5 µm cross-point devices with six different top electrode metals (Au, Pt, Ag, Ni, W and Ti) to examine the effect of these contacts on the I -V characteristics, as show...

show abstract

“…An irreversible forming process under strong electric field is generally required to activate the memristive switching in oxides. 7,14,15,[20][21][22] Such process related to a soft breakdown brings more defects (oxygen vacancies) in the matrix according to the oxygen exchange reaction…”

Section: 21mentioning

confidence: 99%

Redox-controlled memristive switching in the junctions employing Ti reactive electrodes

Xia

et al. 2011

AIP Advances

View full text Add to dashboard Cite

We have proposed a kind of memristive device based on the junctions employing Ti as the reactive electrodes. The role of electrically-derived redox of Ti in such memristive switching is shown. The structural and chemical evidence of the electrically-derived oxidation is presented by TEM and XPS experiment, respectively. Due to the redox of the top electrode Ti and the consequent drift of oxygen vacancies, the device shows two distinct resistance states under a sweeping voltage loading. ON state is controlled by tunneling process, while OFF state is controlled by Schottky emission conductive mechanism. The failure behaviors of such memristive junctions are also discussed. In the light of the redox principle, we demonstrate that the devices could be recovered by loading a long electrical reduction treatment

show abstract

Diffusion of Adhesion Layer Metals Controls Nanoscale Memristive Switching

Cited by 112 publications

References 46 publications

Pattern classification by memristive crossbar circuits using ex situ and in situ training

Pattern classification by memristive crossbar circuits using ex situ and in situ training

Metal/TiO2 interfaces for memristive switches

Redox-controlled memristive switching in the junctions employing Ti reactive electrodes

Contact Info

Product

Resources

About