# Electrospun Nanofibers for Integrated Sensing, Storage, and Computing Applications
## 6 Artificial Synapses and Other Electronic Devices Prepared by Electrospinning  
In addition to the electrospun nanofiber applications including transistors, memories, and sensors, mentioned above, electrospinning has been involved in many other fields, such as optoelectrical and biological devices. In particular, brain-inspired electronic devices have emerged as efficient approaches to reform traditional computing. With the scaling down of the critical channel length of the transistor in integrated circuits, the number of transistors per unit chip is growing exponentially following Moore's Law, triggering many quantum effects by the small size of the FET and leading the improvement of integrated circuit performance into a bottleneck. Further, traditional von Neuman computers with separate storage and computing blocks could not effectively deal with the massive amount of information. Neuromorphic electronic devices as creative components with brand new architecture appear to be comprehensive innovations of the common computer chips, with advantages of extremely high efficiency, ultra-low power consumption, and flexible adaptive capability. For the neural network in the human brain, neurons are the basic units for cognition and computation, and synapses that connect neurons and transmit information are also important elements for the formal function of nerve cells. Solid-state synaptic devices represent the underlying foundation for the implementation of brain-like computing systems and are as important as transistors for modern circuits. To successfully fabricate synaptic devices, careful attention should be paid to the basic functions and principles of biological synapses in neural networks. The action potential of a synapse is a process for generating impulses by a neuron, and the signal transmission between neurons utilizing synapses is the basis for information flow and data processing in the human brain. When an action potential is transmitted to an axon terminal, the presynaptic membrane will send out a pulse, and a change in the cell membrane potential on the postsynaptic membrane will follow. If the pulse on the presynaptic membrane causes positive ion channels on the postsynaptic membrane to open, such as Na+ ion channels, the cell membrane potential will rise and prompt the release of an action potential. Consequently, the potential is referred to as the excitatory postsynaptic potential (EPSP), and the corresponding rise in current is referred to as the excitatory postsynaptic current (EPSC). Conversely, while a pulse on the presynaptic membrane causes the opening of a negative ion channel, such as the Cl- ion channel, the post-synaptic cell membrane potential is referred to as the inhibitory postsynaptic potential (IPSP) and the corresponding decrease in current is referred to as the inhibitory postsynaptic current (IPSC) (Figure 19a,b). In this case, the most representative artificial electronic synapses, synaptic transistors, utilize the gate as the presynaptic pulse applied terminal while source and drain are combined to detect the postsynaptic current (I\({}_{\text{ds}}\)) (Figure 19c). As a result, nearly all synaptic behaviors could be imitated by the simple structure of synaptic transistors for the further construction of complicated neuromorphic networks. Due to the enormous specific surface area, 1D electrospun nanofibers for artificial synapse applications can be in full contact with the surrounding dielectric, which significantly improves the device's operating sensitivity and reduces power consumption. However, electrospun nanofiber-based FETs have not been deeply explored and few studies have been conducted to introduce 1D-nanostructure materials into brain-like computing.