## 3 Results
Additionally, since PGM was performed after full erase measurements, prior stress may have further degraded Vth reproducibility. Based on the transfer curves shown in Figure 4a,b, synaptic weights were extracted by analyzing the changes in I\({}_{\text{ds}}\) with respect to different read voltage (V\({}_{\text{read}}\)) values. The corresponding results are depicted as black curves in Figure 5. The V\({}_{\text{read}}\) is adjusted to ensure accurate data retrieval by setting a specific V\({}_{\text{gs}}\) as the reference voltage. In this study, specific values of V\({}_{\text{read}}\) values (0, 0.5, 1, and 1.5 V) were selected, and the synaptic weights were plotted based on the resulting changes in I\({}_{\text{ds}}\), as illustrated in Figure 4.  
The long-term objective of this research is to develop synaptic array devices. Achieving this requires not only sufficient I\({}_{\text{ds}}\) but also significant synaptic weight variation. Therefore, in this study, synaptic weights were analyzed under various conditions by incorporating V\({}_{\text{ds}}\) as an additional variable alongside V\({}_{\text{read}}\), with the results presented in Figure 5. Furthermore, to assess the reliability of the device, its repeatability was evaluated by performing three program/erase (P/E) cycles. To evaluate synaptic weight based on changes in I\({}_{\text{ds}}\), appropriate V\({}_{\text{ds}}\) and V\({}_{\text{read}}\) are selected [40]. V\({}_{\text{ds}}\) values were set to 0.1, 1, 3, and 5 V, taking into account the device characteristics, while V\({}_{\text{read}}\) values were set to 0, 0.5, 1, and 1.5 V to ensure stable signal acquisition under various conditions. A total of 484 repeated measurements (121 cycles \(\times\) 4) were conducted using the initial I\({}_{\text{ds}}\) as a baseline for each combination of V\({}_{\text{ds}}\) and V\({}_{\text{read}}\). These measurements confirmed that the device accurately represents synaptic potentiation and depression. During repeated measurements, the device demonstrated stable current changes and maintained synaptic connection strength, even after hundreds of cycles. This indicates high durability and reliability, making the device suitable for neuromorphic array designs. The subsequent goal of this study is to develop neuromorphic array devices capable of dynamically controlling signal transduction between neurons. To achieve this, the properties of a single synaptic device were examined. Under conditions where V\({}_{\text{ds}}\) = 1 V and V\({}_{\text{read}}\) = 0.5 V, the device exhibited stable signal transmission and reading characteristics  
Figure 4: (**a**) Synaptic potentiation and (**b**) synaptic depression at a drain voltage of 0.1 V. (**c**) Measurement of synaptic weights by threshold voltage. (**d**) Gaussian distribution in full erase states and full program states, based on threshold voltage. without degradation of synaptic connection strength. The results successfully demonstrated a synaptic current change of more than \(10^{3}\) times. Figure 5: Repeatability, a characteristic of device behavior. Synaptic weight analysis and repeatability evaluation based on drain voltage values (0.1, 1, 3, and 5 V) at read voltage (=V\({}_{\text{gs}}\)) values of (**a**) 0, (**b**) 0.5, (**c**) 1, and (**d**) 1.5 V, respectively. In neuromorphic array devices, the ability to perform parallel operations and respond to diverse input signals with multi-level synaptic connection strengths is critical. Therefore, stable and sufficiently high synaptic variation and current values are essential requirements. High synaptic variation precisely controls various signal strengths and effectively emulates the behavior between neurons and synapses. In addition, maintaining sufficiently high current prevents loss of synaptic connection strength, thereby improving signal transmission and ensuring device stability.