**6.3 Quantum dot**

Quantum dots (QD) are zero-dimensional memristors. Semiconducting quantum dots which are small particles with clearly defined energy levels, exhibit electrical and optical features based on quantum mechanics. Josephson junctions are the foundation for how a QD functions as a memristor. The phase difference between quasi-particles is employed ss a state variable [211]. Here, a hybrid construction made of QDs and a memristor is used. In [212], Lv et al. demonstrate that RRAM devices with QD-film as their insulator can be switched in response to an external signal. The memristive characteristic of QD-RRAMs is catalysed by ion migration, charge trapping, or redox reaction. Qi et al. show how to fabricate

RRAM with Carbon QD for usage as a LED [213]. In [214], Roychowdhury et al. use QD arrays to show quantum neuromorphic computing. There are a lot of potential opportunities that are yet to be explored.

### **6.4 Carbon nanotube**

A carbon nanotube (CNT) is a cylindrical rolled up, often single-walled carbon in a tube shape of nanometre diameter. They have a metallic or semiconducting character because of their achiral connections. These fall within the category of one-dimensional materials that resemble axons structurally. Due to their great charge mobility, semiconductor CNTs can be employed as conducting channels in FETs. CNTFET is a CNT replacing semiconductor channel between the source and drain. With voltage applied, a Schottky barrier that has formed at the metal-CNT contact is alleviated. The ON/OFF state of memory cells is determined by the interaction between CNTs. The gate and source of the single-walled CNT matrix network are respectively coupled to presynaptic and integrate-and-fire (IF) postsynaptic neurons by Feldmann et al. [215]. The channel conduct anceto store synaptic weights is controlled by varying voltage pulses at the pre- and postneuron. All of the post synaptic neuron spikes are gathered to fire back the CNT if the output hits a threshold level. In order to choose the sign and magnitude of the weight update for an STDP implementation, the channel conductance change when the gate and source voltages are correlated. Kim et al. describe p-type CNTFETbased models of excitatory and inhibitory neurons [158], where the neurons exhibit STP accumulative current. The very lateral geometry of CNTFETs is not viable for larger integration, though. CNT TFTs have therefore become a popular substitute for the same.

The materials science community is doing a lot of intriguing work to create devices for neuromorphic systems out of novel materials in order to create smaller, faster, and more effective neuromorphic devices. Diverse materials can have radically different properties, even when used in the same device. These variations will have an impact on the rest of the community, up through the device, high-level hardware, supporting software, models, and algorithms levels of neuromorphic systems. Therefore, it is crucial that we as a community comprehend the potential effects that various materials may have on functionality. Going forward, tight partnerships with the materials science community will undoubtedly be necessary.
