# Neuromorphic Spatiotemporal Information Processing Using Neuro-Photodetector Systems
## 3 Results and Discussion  
The biological neuron receives one or more inputs (e.g., A1, A2, etc.) and usually each input is separately weighed to produce an output (C1A1 + C2A2,... CnAn), as depicted schematically in Figure 1a [1; 2; 5; 10]. Where, C1, C2,... Cn are the coefficients of weight of each input, containing the values from 0 to 1. We proposed a simple photodetector--termed neuro-photodetector--that could be used to mimic the basic functions of bio-neuron in which light (ultraviolet, UV) pulses work as inputs, and measured photocurrent between two terminals is termed the response form the neuron; see Figure 1b. In fact, the respective photocurrent (\(I\)1, \(I\)2,... \(I\)n) generated by different inputs (e.g., P1, \(P2,\)... \(P\)n) can be summed to produce the resultant output, where \(I\)1, \(I\)2,... In is the magnitude of the resultant photocurrent (e.g., weighed sum) produced by the \(P1,P2,\)... \(P\)n inputs, respectively. Particularly, the current transport across a photoconductive material can be altered easily by a series of optical pulses, which provide a unique opportunity to mimic the neuron and synapse. In contrast to the conventional photodetectors, a neuro-photodetector must exhibit a time-dependent output current,which in turn allows mimicking the neuron-like behavior. Such a neuro-photodetector is capable to integrate the photocurrent (\(I_{\text{p}}\)) over time, resulting in the \(I_{\text{p}}\) increasing gradually by applying multiple optical inputs, and once the \(I_{\text{p}}\) is above the threshold, the device fires the output like bio-neuron; see Figure 1c [9]. The threshold can be defined for specific application in which this artificial neuron is supposed to use. In fact, the output \(I_{\text{p}}\) behavior from the neuro-photodetector with applied pulse intensity/duration could show similar behavior, as is by the bio-neuron. On the other hand, the \(I_{\text{p}}\) decreases gradually during the UV, which is very similar to the leaky behavior of the bio-neuron. The increasing of \(I_{\text{p}}\) with UV illumination, and decreasing after that, are attributed to the UV induced electron-hole pair generation and recombination processes, respectively. To prepare the neuro-photodetector, we used ZnO materials, in which the transducer is considered the determinant factor of charge transport. Therefore, these defects can be filled out by the photogenerated electron-hole (_e-h_) pairs, resulting in a smooth charge transport or higher photocurrent [4, 15, 20]. In fact, as illuminating time and/or intensity increases, the defects within the used ZnO layer can be filled out, as shown sequentially from (1) to (4), which in turn increases the \(I_{\text{p}}\) as a fixed measuring voltage, as depicted schematically in Figure 1d. On the other hand, a slow decay of the \(I_{\text{p}}\) originated from well-known persistent photoconductivity (PPC) due to absorption and desorption of oxygen vacancies [2, 6, 21]. The schematic of the device is depicted in Figure 2a, which contains atomic layer deposited ZnO \"nanofin\" sandwiched between Al and Ag electrodes. More detail of the nanofin-based device fabrication is presented in the Experimental Section and Figure S1 (Supporting Information). Such kind of arrangements of nanofin provide a unique opportunity to design large-scale and well controlled patterns of devices, which, in fact, could be used for several other neuromorphic applications [4, 14, 22, 23]. To confirm the effectiveness of our approach of device fabrication, various type of symmetric and asymmetric electrodes, such as Al/ZnO/Al, Ag/ZnO/Ag, Al/ZnO/Ag, and ITO/ZnO/ITO were used;  
Figure 1: The operation of a bio-neuron and its analogue in the present photodetector. (**a**) Schematic of bio-neuron. Neuron works as an adder and sum all individual inputs (A\({}_{1}\), A\({}_{2}\),... A\({}_{n}\)) with its respective weight (C\({}_{1}\), C\({}_{2}\),... C\({}_{n}\)).