Executive Summary : | The ability of a machine to mimic the capability of human brain such as recognizing objects, learning from past experience, processing and understanding different languages is termed as artificial intelligence (AI). Nowadays, it has become a part of our everyday life in each step which includes navigation applications, smart home devices, voice assistance, facial recognition, virus/spam prevention etc. The state-of-the-art artificial intelligence technologies are mainly based on von Neumann computing architectures in which the memory and processing units are separated. This leads to an enormous amount of energy and time usage during data transfer process. The human brain, which can be considered as an ultra-high efficient biological computer uses a highly parallel and event-driven scheme of computation while performing complicated learning and cognitive tasks. This is achieved by 10¹¹ neurons inter-linked by 10¹⁵ synapses, through which the brain signals travel. Neuromorphic computing technology which is inspired by the human brain implements and try to mimic the functioning of brain at the physical level so that advanced computation can be fast enough and high efficient. Artificial synapses are the main components of a neuromorphic computing system. Recently, this field of research is in the lime light and there are many studies which reported on brain-inspired neuromorphic computing. The literatures show that, different schemes can be used for artificial synapses, but the mechanism of the synaptic effect strongly depends on material under selection, synthesis method, device architecture and their interfacial properties. Hence, the overarching goal of the proposed project is to fabricate nano-transition metal oxide -which are promising materials for mimicking biological synapses- based synaptic devices to explore the possibility of achieving brain-inspired neuromorphic computing applications through an easy, simple and efficient synthesis and fabrication method. The solution based synthesis of nano-transition metal oxides, such as sol-gel and hydrothermal methods will be capable of overcoming the difficulties faced by the conventional vapour deposition techniques which are used for the synthesis of reported synaptic structures. The emphasis will be laid upon establishing a systematic understanding of the working mechanism of hierarchical structures of nanoparticle assemblies as artificial synapses to tailor the desired synaptic performance. In addition to that, another goal of the project is to achieve both electrical and optical tuning of these nano-hiearchical synapses which mimics complex human cognition employing micro/nano-structural engineering of the synaptic materials. This study will extend on the design and development of a novel, multi-level and high-performing synaptic device for neuromorphic applications. |