Li-Chung Shih

• Doctor of Engineering
• Ph.D. candidate at National Cheng Kung University

Spiking Neural Networks (SNNs) have gained attention due to their potential to improve computational efficiency compared to traditional artificial neural networks. This study investigates the use of dynamic memristors Ta/IGZO/TaOx/Pt combined with peripheral circuits to emulate the leaky integrate‐and‐fire behavior of neurons, focusing on incorpora...

Components needed in Artificial Intelligence with a higher information capacity are critically needed and have garnered significant attention at the forefront of information technology. This study utilizes solution-processed zinc–tin oxide (ZTO) thin-film phototransistors and modulates the values of VG, which allows for the regulation of electron t...

To enhance the efficiency of machine vision system, physical hardware capable of sensing and encoding is essential. However, sensing and encoding color information has been overlooked. Therefore, this work utilizes an indium‐gallium‐zinc oxide (IGZO) phototransistor to detect varying densities of red, green, and blue (RGB) light, converting them in...

Memory devices with sensitivity, selectivity, and operation voltage towards the gases are rarely reported for artificial olfactory sensors. Additionally, there are no reports available on the atomistic aspects of artificial olfactory sensors. This study reports an atomistic simulation of monoclinic‐ZrO2 (m‐ZrO2). The impact of external electric fie...

Neuromorphic computers promise to enhance computing efficiency by eliminating conventional von Neumann architecture bottlenecks. Bio‐inspired artificial neural networks, such as feedforward neural networks and reservoir computing (RC), face challenges due to the unique memristor requirements. In this study, a dual‐gate ferroelectric polymer P(VDF–T...

Memristor devices offer an alternative route to transistor scaling and the exponential growth of computational resources. Numerous memristors have the potential to be used in neuromorphic computing or to complement the von Neumann architecture-based digital computation. However, most of the available reports on memristor are based on the first-orde...

Using light signals for computation and communication is a vital approach for advanced neuromorphic designs. In this study, an all‐optical‐controlled IGZO/ZrOx phototransistor is demonstrated to emulate synaptic functions via both positive and negative photoresponse arisen from the ionization of neutral oxygen vacancies (VO) and metalmetal bonding...

In contrast to the conventional voltage-gated channels of thin-film transistors (TFTs), the photo-induced gating effect provides a promising approach to control the carrier concentration in the channels and benefits the advanced application in a remote operation mode. In this work, the zinc-tin oxide TFT (ZTO TFT) is revealed the feasibility of bei...

The core integration and cooperation of the retina, neurons, and synapses in the visual systems enable humans to effectively sense and process visual information with low power consumption. To mimic the human visual system, an artificial sensory nerve, along with optical sensing─a paired-pulse ratio (PPR) of the light pulse stimulated currents─and...

Neuromorphic computing, inspired by the biological neuronal system, is a high potential approach to substantially alleviate the cost of computational latency and energy for massive data processing. Artificial synapses with regulable synaptic weights are the basis of neuromorphic computation, providing an efficient and low-power system to overcome t...

A ZTO/Au NPs heterostructure optosynaptic device proving the super-additivity of homo- and heterosynaptic plasticity is offered for visual and logical functions based on the light-bias coupling effect and hot electron transfer.

Metal oxide ZrO2 has been widely explored for resistive switching application due to excellent properties like high ON/OFF ratio, superior data retention, and low operating voltage. However, the conduction mechanism at the atomistic level is still under debate. Therefore, we have performed comprehensive insights into the role of neutral and charged...

Optical data processing and storage have become a promising stage for next-generation communication and computation technologies. Rather than using electrical bias in traditional memories, photomemories driven by optical signals have the ability to store light information directly, which is advantageous for the improvement of the power efficiency o...

The rapid emergency of data science, information technology, and artificial intelligence (AI) relies on massive data processing with high computing efficiency and low power consumption. However, the current von‐Neumann architecture system requires high‐energy budget to process data computing and storage between central computing unit and memory. To...

In contrast to the commonly present UV light-stimulated synaptic oxide thin-film transistors, this study demonstrates a violet light (wavelength of 405 nm) stimulated zinc–tin oxide (ZTO) photoelectric transistor for potential application in optical neuromorphic computation. Owing to the light-induced oxygen vacancy ionization and persistent photoc...

In this study, a charge trapping thin film transistor (TFT) is demonstrated based on a zinc-tin oxide (ZTO) semiconductor channel layer and a stack of AlOx/AZO nanoparticles/SiO2 as the gate dielectrics. This device can be switched from the pristine state to charge trapping state via the application of a positive gate voltage pulse (VG=40 V for 1 s...