Artificial synapse having good linearity is crucial to achieve an efficient learning process in neuromorphic computing. It is found that the synaptic linearity can be enhanced by engineering the doping region across the switching layer. The nonlinearity of potentiation and depression of the pure device is 36% and 91%, respectively; meanwhile, the nonlinearity after doping can be suppressed to be 22% (potentiation) and 60% (depression). Henceforth, the learning accuracy of the doped device is 91% with only 13 iterations; meanwhile, the pure device is 78%. A detailed conduction mechanism to understand this phenomenon is proposed.

The synaptic plasticity of indium tin oxide (ITO)/ZnO/ITO highly transparent (more than 88%) analog switching resistive memory device is investigated. Highly stable analog switching behavior for more than 2500 cycles with a good memory window of approximately two orders makes it suitable for synapse application. The synaptic response is investigated by applying identical electrical pulses. The potentiation and depression of the device used the conventional identical single-pulse scheme to perform high nonlinearity (0.83) and decaying training epochs. However, the linearity and the training epochs are improved to 0.44 by implementing the identical double-pulse scheme. The proposed double-pulse scheme offers a broad dynamic range (200) having 320 conductance states. This invisible structure and double-pulse scheme can be highly suitable for the neuromorphic computing devices.

An oxidizable metal diffusion barrier inserted between the active metal electrode and the switching layer decreases the electroforming voltage and enhances the switching stability and synaptic performances in TaOx-based conducting bridge memristor devices. The TiW barrier layer avoids an excessive metal ion diffusion into the switching layer, while the TiWOx interfacial layer is formed between the barrier and the switching layer. It modulates the oxygen vacancy distribution at the top interface and contributes to the formation and rupture of the metal ion-oxygen vacancy hybrid conducting bridge. We observe that the device that relies upon non-hybrid (metal ions only) conducting bridge suffers from poor analogous performance. Meanwhile, the device made with the barrier layer is capable of providing 2-bit memory and robust 50 stable epochs. TaOx also acts as resistance for suppressing and a thermal enhancement layer, which helps to minimize overshooting current. The enhanced analog device with high linear weight update shows multilevel cell characteristics and stable 50 epochs. To validate the neuromorphic characteristic of the devices, a simulated neural network of 100 synapses is used to recognize 10 × 10 pixel images.

Printable electronics is emerging as one of the fast-growing engineering fields with a higher degree of customization and reliability. Ironically, sustainable printing technology is essential because of the minimal waste to the environment. To move forward, we need to harness the fabrication technology with the potential to support traditional process. In this review, we have systematically discussed in detail the various manufacturing materials and processing technologies. The selection criteria for the assessment are conducted systematically on the manuscript published in the last 10 years (2012–2022) in peer-reviewed journals. We have discussed the various kinds of printable ink which are used for fabrication based on nanoparticles, nanosheets, nanowires, molecular formulation, and resin. The printing methods and technologies used for printing for each technology are also reviewed in detail. Despite the major development in printing technology some critical challenges needed to be addressed and critically assessed. One such challenge is the coffee ring effect, the possible methods to reduce the effect on modulating the ink environmental condition are also indicated. Finally, a summary of printable electronics for various applications across the diverse industrial manufacturing sector is presented.

To move towards a new generation powerful computing system, brain-inspired neuromorphic computing is expected to transform the architecture of the conventional computer, where memristors are considered to be potential solutions for synapses part. We propose and demonstrate a novel approach to achieve remarkable improvement of analog switching linearity in TaN/Ta/TaOx/Al2O3/Pt/Si memristors by varying Al2O3 layer thickness. Presence of the Al2O3 layer is confirmed from the Auger Electron Spectroscopy study. Good analog switching ratio of about 100× and superior switching uniformity are observed for the 1 nm Al2O3 based device. Multilevel capability of the memristive devices is also explored for prospective use as a synapse. More than 104 and 4×104 cycles nondegradable dc and ac endurances, respectively, alongwith 104 second retention are achieved for the optimized device. Improved linearities of 2.41 and -2.77 for potentiation and depression, respectively are obtained for such 1 nm Al2O3-based devices. The property of gradual resistance changed by pulse amplitudes confirms that the TaOx memristors can be potentially used as an electronic synapse.

Hydrogen peroxide treatment induces the phase transformation of hexagonal ZnO to cubic ZnO₂ on the surface of the ZnO switching memory film; this oxidation process effectively reduces the concentration of n-type donor defects (oxygen vacancies and zinc interstitials) in the switching film. The chemically oxidized ZnO₂ layer not only lowers the operation current of the device but also can serve as an oxygen “bank” to improve the endurance of the memristor. The oxidation reaction of peroxide treatment can be easily controlled to achieve an analog behavior with good switching uniformity. The analog memristor device is able to perform two-bit per cell and synaptic operations. Based on the experimental synaptic data, an image processing of 7 × 9 pixels using a simulated artificial neural network comprises 63 synapses is evaluated to mimic the visual cortex function of the brain.