Enhanced BSA Detection Precision: Leveraging High-Performance Dual-Gate Ion-Sensitive Field-Effect-Transistor Scheme and Surface-Treated Sensing Membranes.

Bovine serum albumin (BSA) is commonly incorporated in vaccines to improve stability. However, owing to potential allergic reactions in humans, the World Health Organization (WHO) mandates strict adherence to a BSA limit (≤50 ng/vaccine). BSA detection with conventional techniques is time-consuming and requires specialized equipment. Efficient alternatives such as the ion-sensitive field-effect transistor (ISFET), despite rapid detection, affordability, and portability, do not detect BSA at low concentrations because of inherent sensitivity limitations. This study proposes a silicon-on-insulator (SOI) substrate-based dual-gate (DG) ISFET platform to overcome these limitations. The capacitive coupling DG structure significantly enhances sensitivity without requiring external circuits, owing to its inherent amplification effect. The extended-gate (EG) structure separates the transducer unit for electrical signal processing from the sensing unit for biological detection, preventing chemical damage to the transducer, accommodating a variety of biological analytes, and affording easy replaceability. Vapor-phase surface treatment with (3-Aminopropyl) triethoxysilane (APTES) and the incorporation of a SnO2 sensing membrane ensure high BSA detection efficiency and sensitivity (144.19 mV/log [BSA]). This DG-FET-based biosensor possesses a simple structure and detects BSA at low concentrations rapidly. Envisioned as an effective on-site diagnostic tool for various analytes including BSA, this platform addresses prior limitations in biosensing and shows promise for practical applications.

Organic-Inorganic Hybrid Synaptic Transistors: Methyl-Silsesquioxanes-Based Electric Double Layer for Enhanced Synaptic Functionality and CMOS Compatibility.

Electrical double-layer (EDL) synaptic transistors based on organic materials exhibit low thermal and chemical stability and are thus incompatible with complementary metal oxide semiconductor (CMOS) processes involving high-temperature operations. This paper proposes organic-inorganic hybrid synaptic transistors using methyl silsesquioxane (MSQ) as the electrolyte. MSQ, derived from the combination of inorganic silsesquioxanes and the organic methyl (-CH3) group, exhibits exceptional thermal and chemical stability, thus ensuring compatibility with CMOS processes. We fabricated Al/MSQ electrolyte/Pt capacitors, exhibiting a substantial capacitance of 1.89 µF/cm2 at 10 Hz. MSQ-based EDL synaptic transistors demonstrated various synaptic behaviors, such as excitatory post-synaptic current, paired-pulse facilitation, signal pass filtering, and spike-number-dependent plasticity. Additionally, we validated synaptic functions such as information storage and synapse weight adjustment, simulating brain synaptic operations through potentiation and depression. Notably, these synaptic operations demonstrated stability over five continuous operation cycles. Lastly, we trained a multi-layer artificial deep neural network (DNN) using a handwritten Modified National Institute of Standards and Technology image dataset. The DNN achieved an impressive recognition rate of 92.28%. The prepared MSQ-based EDL synaptic transistors, with excellent thermal/chemical stability, synaptic functionality, and compatibility with CMOS processes, harbor tremendous potential as materials for next-generation artificial synapse components.

Smart pH Sensing: A Self-Sensitivity Programmable Platform with Multi-Functional Charge-Trap-Flash ISFET Technology.

This study presents a novel pH sensor platform utilizing charge-trap-flash-type metal oxide semiconductor field-effect transistors (CTF-type MOSFETs) for enhanced sensitivity and self-amplification. Traditional ion-sensitive field-effect transistors (ISFETs) face challenges in commercialization due to low sensitivity at room temperature, known as the Nernst limit. To overcome this limitation, we explore resistive coupling effects and CTF-type MOSFETs, allowing for flexible adjustment of the amplification ratio. The platform adopts a unique approach, employing CTF-type MOSFETs as both transducers and resistors, ensuring efficient sensitivity control. An extended-gate (EG) structure is implemented to enhance cost-effectiveness and increase the overall lifespan of the sensor platform by preventing direct contact between analytes and the transducer. The proposed pH sensor platform demonstrates effective sensitivity control at various amplification ratios. Stability and reliability are validated by investigating non-ideal effects, including hysteresis and drift. The CTF-type MOSFETs' electrical characteristics, energy band diagrams, and programmable resistance modulation are thoroughly characterized. The results showcase remarkable stability, even under prolonged and repetitive operations, indicating the platform's potential for accurate pH detection in diverse environments. This study contributes a robust and stable alternative for detecting micro-potential analytes, with promising applications in health management and point-of-care settings.

Synaptic Plasticity Modulation of Neuromorphic Transistors through Phosphorus Concentration in Phosphosilicate Glass Electrolyte Gate.

This study proposes a phosphosilicate glass (PSG)-based electrolyte gate synaptic transistor with varying phosphorus (P) concentrations. A metal oxide semiconductor capacitor structure device was employed to measure the frequency-dependent (C-f) capacitance curve, demonstrating that the PSG electric double-layer capacitance increased at 103 Hz with rising P concentration. Fourier transform infrared spectroscopy spectra analysis facilitated a theoretical understanding of the C-f curve results, examining peak differences in the P-OH structure based on P concentration. Using the proposed synaptic transistors with different P concentrations, changes in the hysteresis window were investigated by measuring the double-sweep transfer curves. Subsequently, alterations in proton movement within the PSG and charge characteristics at the channel/PSG electrolyte interface were observed through excitatory post-synaptic currents, paired-pulse facilitation, signal-filtering functions, resting current levels, and potentiation and depression characteristics. Finally, we demonstrated the proposed neuromorphic system's feasibility based on P concentration using the Modified National Institute of Standards and Technology learning simulations. The study findings suggest that, by adjusting the PSG film's P concentration for the same electrical stimulus, it is possible to selectively mimic the synaptic signal strength of human synapses. Therefore, this approach can positively contribute to the implementation of various neuromorphic systems.

Nanowire-Enhanced Fully Transparent and Flexible Indium Gallium Zinc Oxide Transistors with Chitosan Hydrogel Gate Dielectric: A Pathway to Improved Synaptic Properties.

In this study, a transparent and flexible synaptic transistor was fabricated based on a random-network nanowire (NW) channel made of indium gallium zinc oxide. This device employs a biocompatible chitosan-based hydrogel as an electrolytic gate dielectric. The NW structure, with its high surface-to-volume ratio, facilitated a more effective modulation of the channel conductance induced by protonic-ion polarization. A comparative analysis of the synaptic properties of NW- and film-type devices revealed the distinctive features of the NW-type configuration. In particular, the NW-type synaptic transistors exhibited a significantly larger hysteresis window under identical gate-bias conditions. Notably, these transistors demonstrated enhanced paired-pulse facilitation properties, synaptic weight modulation, and transition from short- to long-term memory. The NW-type devices displayed gradual potentiation and depression of the channel conductance and thus achieved a broader dynamic range, improved linearity, and reduced power consumption compared with their film-type counterparts. Remarkably, the NW-type synaptic transistors exhibited impressive recognition accuracy outcomes in Modified National Institute of Standards and Technology pattern-recognition simulations. This characteristic enhances the efficiency of practical artificial intelligence (AI) processes. Consequently, the proposed NW-type synaptic transistor is expected to emerge as a superior candidate for use in high-efficiency artificial neural network systems, thus making it a promising technology for next-generation AI semiconductor applications.

Light-Stimulated IGZO Transistors with Tunable Synaptic Plasticity Based on Casein Electrolyte Electric Double Layer for Neuromorphic Systems.

In this study, optoelectronic synaptic transistors based on indium-gallium-zinc oxide (IGZO) with a casein electrolyte-based electric double layer (EDL) were examined. The casein electrolyte played a crucial role in modulating synaptic plasticity through an internal proton-induced EDL effect. Thus, important synaptic behaviors, such as excitatory post-synaptic current, paired-pulse facilitation, and spike rate-dependent and spike number-dependent plasticity, were successfully implemented by utilizing the persistent photoconductivity effect of the IGZO channel stimulated by light. The synergy between the light stimulation and the EDL effect allowed the effective modulation of synaptic plasticity, enabling the control of memory levels, including the conversion of short-term memory to long-term memory. Furthermore, a Modified National Institute of Standards and Technology digit recognition simulation was performed using a three-layer artificial neural network model, achieving a high recognition rate of 90.5%. These results demonstrated a high application potential of the proposed optoelectronic synaptic transistors in neuromorphic visual systems.

Advancements in Complementary Metal-Oxide Semiconductor-Compatible Tunnel Barrier Engineered Charge-Trapping Synaptic Transistors for Bio-Inspired Neural Networks in Harsh Environments.

This study aimed to propose a silicon-on-insulator (SOI)-based charge-trapping synaptic transistor with engineered tunnel barriers using high-k dielectrics for artificial synapse electronics capable of operating at high temperatures. The transistor employed sequential electron trapping and de-trapping in the charge storage medium, facilitating gradual modulation of the silicon channel conductance. The engineered tunnel barrier structure (SiO2/Si3N4/SiO2), coupled with the high-k charge-trapping layer of HfO2 and high-k blocking layer of Al2O3, enabled reliable long-term potentiation/depression behaviors within a short gate stimulus time (100 µs), even under elevated temperatures (75 and 125 °C). Conductance variability was determined by the number of gate stimuli reflected in the maximum excitatory postsynaptic current (EPSC) and the residual EPSC ratio. Moreover, we analyzed the Arrhenius relationship between the EPSC as a function of the gate pulse number (N = 1-100) and the measured temperatures (25, 75, and 125 °C), allowing us to deduce the charge trap activation energy. A learning simulation was performed to assess the pattern recognition capabilities of the neuromorphic computing system using the modified National Institute of Standards and Technology datasheets. This study demonstrates high-reliability silicon channel conductance modulation and proposes in-memory computing capabilities for artificial neural networks using SOI-based charge-trapping synaptic transistors.

Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures.

In this study, we enhance the synaptic behavior of artificial synaptic transistors by utilizing nanowire (NW)-type polysilicon channel structures. The high surface-to-volume ratio of the NW channels enables efficient modulation of the channel conductance, which is interpreted as the synaptic weight. As a result, NW-type synaptic transistors exhibit a larger hysteresis window compared to film-type synaptic transistors, even within the same gate voltage sweeping range. Moreover, NW-type synaptic transistors demonstrate superior short-term facilitation and long-term memory transition compared with film-type ones, as evidenced by the measured paired-pulse facilitation and excitatory post-synaptic current characteristics at varying frequencies and pulse numbers. Additionally, we observed gradual potentiation/depression characteristics, making these artificial synapses applicable to artificial neural networks. Furthermore, the NW-type synaptic transistors exhibit improved Modified National Institute of Standards and Technology pattern recognition rate of 91.2%. In conclusion, NW structure channels are expected to be a promising technology for next-generation artificial intelligence (AI) semiconductors, and the integration of NW structure channels has significant potential to advance AI semiconductor technology.

Pushing the Limits of Biosensing: Selective Calcium Ion Detection with High Sensitivity via High-k Gate Dielectric Engineered Si Nanowire Random Network Channel Dual-Gate Field-Effect Transistors.

Calcium ions (Ca2+) are abundantly present in the human body; they perform essential roles in various biological functions. In this study, we propose a highly sensitive and selective biosensor platform for Ca2+ detection, which comprises a dual-gate (DG) field-effect transistor (FET) with a high-k engineered gate dielectric, silicon nanowire (SiNW) random network channel, and Ca2+-selective extended gate. The SiNW channel device, which was fabricated via the template transfer method, exhibits superior Ca2+ sensing characteristics compared to conventional film channel devices. An exceptionally high Ca2+ sensitivity of 208.25 mV/dec was achieved through the self-amplification of capacitively coupled DG operation and an enhanced amplification ratio resulting from the high surface-to-volume ratio of the SiNW channel. The SiNW channel device demonstrated stable and reliable sensing characteristics, as evidenced by minimal hysteresis and drift effects, with the hysteresis voltage and drift rate measuring less than 6.53% of the Ca2+ sensitivity. Furthermore, the Ca2+-selective characteristics of the biosensor platform were elucidated through experiments with pH buffer, NaCl, and KCl solutions, wherein the sensitivities of the interfering ions were below 7.82% compared to the Ca2+ sensitivity. The proposed Ca2+-selective biosensor platform exhibits exceptional performance and holds great potential in various biosensing fields.

Implementation of Highly Stable Memristive Characteristics in an Organic-Inorganic Hybrid Resistive Switching Layer of Chitosan-Titanium Oxide with Microwave-Assisted Oxidation.

This study proposes a high-performance organic-inorganic hybrid memristor for the development of neuromorphic devices in the memristor-based artificial synapse. The memristor consists of a solid polymer electrolyte (SPE) chitosan layer and a titanium oxide (TiOx) layer grown with a low-thermal-budget, microwave-assisted oxidation. The fabricated Ti/SPE-chitosan/TiOx/Pt-structured memristor exhibited steady bipolar resistive switching (BRS) characteristics and demonstrated excellent endurance in 100-cycle repetition tests. Compared to SPE-chitosan memristors without a TiOx layer, the proposed organic-inorganic hybrid memristor demonstrated a higher dynamic range and a higher response to pre-synaptic stimuli such as short-term plasticity via paired-pulse facilitation. The effect of adding the TiOx layer on the BRS properties was examined, and the results showed that the TiOx layer improved the chemical and electrical superiority of the proposed memristor synaptic device. The proposed SPE-chitosan organic-inorganic hybrid memristor also exhibited a stable spike-timing-dependent plasticity, which closely mimics long-term plasticity. The potentiation and depression behaviors that modulate synaptic weights operated stably via repeated spike cycle tests. Therefore, the proposed SPE-chitosan organic-inorganic hybrid memristor is a promising candidate for the development of neuromorphic devices in memristor-based artificial synapses owing to its excellent stability, high dynamic range, and superior response to pre-synaptic stimuli.

High-Performance FET-Based Dopamine-Sensitive Biosensor Platform Based on SOI Substrate.

Dopamine is a catecholamine neurotransmitter that plays a significant role in the human central nervous system, even at extremely low concentrations. Several studies have focused on rapid and accurate detection of dopamine levels using field-effect transistor (FET)-based sensors. However, conventional approaches have poor dopamine sensitivity with values <11 mV/log [DA]. Hence, it is necessary to increase the sensitivity of FET-based dopamine sensors. In the present study, we proposed a high-performance dopamine-sensitive biosensor platform based on dual-gate FET on a silicon-on-insulator substrate. This proposed biosensor overcame the limitations of conventional approaches. The biosensor platform consisted of a dual-gate FET transducer unit and a dopamine-sensitive extended gate sensing unit. The capacitive coupling between the top- and bottom-gate of the transducer unit allowed for self-amplification of the dopamine sensitivity, resulting in an increased sensitivity of 373.98 mV/log[DA] from concentrations 10 fM to 1 µM. Therefore, the proposed FET-based dopamine sensor is expected to be widely applied as a highly sensitive and reliable biosensor platform, enabling fast and accurate detection of dopamine levels in various applications such as medical diagnosis and drug development.

High-Performance Potassium-Selective Biosensor Platform Based on Resistive Coupling of a-IGZO Coplanar-Gate Thin-Film Transistor.

The potassium (K+) ion is an essential mineral for balancing body fluids and electrolytes in biological systems and regulating bodily function. It is associated with various disorders. Given that it exists at a low concentration in the human body and should be maintained at a precisely stable level, the development of highly efficient potassium-selective sensors is attracting considerable interest in the healthcare field. Herein, we developed a high-performance, potassium-selective field-effect transistor-type biosensor platform based on an amorphous indium gallium zinc oxide coplanar-gate thin-film transistor using a resistive coupling effect with an extended gate containing a potassium-selective membrane. The proposed sensor can detect potassium in KCl solutions with a high sensitivity of 51.9 mV/dec while showing a low sensitivity of <6.6 mV/dec for NaCl, CaCl2, and pH buffer solutions, indicating its high selectivity to potassium. Self-amplification through the resistive-coupling effect enabled an even greater potassium sensitivity of 597.1 mV/dec. Additionally, we ensured the stability and reliability of short- and long-term detection through the assessment of non-ideal behaviors, including hysteresis and drift effects. Therefore, the proposed potassium-sensitive biosensor platform is applicable to high-performance detection in a living body, with high sensitivity and selectivity for potassium.

Synaptic Transistors Based on PVA: Chitosan Biopolymer Blended Electric-Double-Layer with High Ionic Conductivity.

This study proposed a biocompatible polymeric organic material-based synaptic transistor gated with a biopolymer electrolyte. A polyvinyl alcohol (PVA):chitosan (CS) biopolymer blended electrolyte with high ionic conductivity was used as an electrical double layer (EDL). It served as a gate insulator with a key function as an artificial synaptic transistor. The frequency-dependent capacitance characteristics of PVA:CS-based biopolymer EDL were evaluated using an EDL capacitor (Al/PVA: CS blended electrolyte-based EDL/Pt configuration). Consequently, the PVA:CS blended electrolyte behaved as an EDL owing to high capacitance (1.53 µF/cm2) at 100 Hz and internal mobile protonic ions. Electronic synaptic transistors fabricated using the PVA:CS blended electrolyte-based EDL membrane demonstrated basic artificial synaptic behaviors such as excitatory post-synaptic current modulation, paired-pulse facilitation, and dynamic signal-filtering functions by pre-synaptic spikes. In addition, the spike-timing-dependent plasticity was evaluated using synaptic spikes. The synaptic weight modulation was stable during repetitive spike cycles for potentiation and depression. Pattern recognition was conducted through a learning simulation for artificial neural networks (ANNs) using Modified National Institute of Standards and Technology datasheets to examine the neuromorphic computing system capability (high recognition rate of 92%). Therefore, the proposed synaptic transistor is suitable for ANNs and shows potential for biological and eco-friendly neuromorphic systems.

Enhanced Synaptic Properties in Biocompatible Casein Electrolyte via Microwave-Assisted Efficient Solution Synthesis.

In this study, we fabricated an electric double-layer transistor (EDLT), a synaptic device, by preparing a casein biopolymer electrolyte solution using an efficient microwave-assisted synthesis to replace the conventional heating (heat stirrer) synthesis. Microwave irradiation (MWI) is more efficient in transferring energy to materials than heat stirrer, which significantly reduces the preparation time for casein electrolytes. The capacitance-frequency characteristics of metal-insulator-metal configurations applying the casein electrolyte prepared through MWI or a heat stirrer were measured. The capacitance of the MWI synthetic casein was 3.58 µF/cm2 at 1 Hz, which was higher than that of the heat stirrer (1.78 µF/cm2), confirming a stronger EDL gating effect. Electrolyte-gated EDLTs using two different casein electrolytes as gate-insulating films were fabricated. The MWI synthetic casein exhibited superior EDLT electrical characteristics compared to the heat stirrer. Meanwhile, essential synaptic functions, including excitatory post-synaptic current, paired-pulse facilitation, signal filtering, and potentiation/depression, were successfully demonstrated in both EDLTs. However, MWI synthetic casein electrolyte-gated EDLT showed higher synaptic facilitation than the heat stirrer. Furthermore, we performed an MNIST handwritten-digit-recognition task using a multilayer artificial neural network and MWI synthetic casein EDLT achieved a higher recognition rate of 91.24%. The results suggest that microwave-assisted casein solution synthesis is an effective method for realizing biocompatible neuromorphic systems.

Biocompatible Potato-Starch Electrolyte-Based Coplanar Gate-Type Artificial Synaptic Transistors on Paper Substrates.

In this study, we propose the use of artificial synaptic transistors with coplanar-gate structures fabricated on paper substrates comprising biocompatible and low-cost potato-starch electrolyte and indium-gallium-zinc oxide (IGZO) channels. The electrical double layer (EDL) gating effect of potato-starch electrolytes enabled the emulation of biological synaptic plasticity. Frequency dependence measurements of capacitance using a metal-insulator-metal capacitor configuration showed a 1.27 µF/cm2 at a frequency of 10 Hz. Therefore, strong capacitive coupling was confirmed within the potato-starch electrolyte/IGZO channel interface owing to EDL formation because of internal proton migration. An electrical characteristics evaluation of the potato-starch EDL transistors through transfer and output curve resulted in counterclockwise hysteresis caused by proton migration in the electrolyte; the hysteresis window linearly increased with maximum gate voltage. A synaptic functionality evaluation with single-spike excitatory post-synaptic current (EPSC), paired-pulse facilitation (PPF), and multi-spike EPSC resulted in mimicking short-term synaptic plasticity and signal transmission in the biological neural network. Further, channel conductance modulation by repetitive presynaptic stimuli, comprising potentiation and depression pulses, enabled stable modulation of synaptic weights, thereby validating the long-term plasticity. Finally, recognition simulations on the Modified National Institute of Standards and Technology (MNIST) handwritten digit database yielded a 92% recognition rate, thereby demonstrating the applicability of the proposed synaptic device to the neuromorphic system.

Milk-Ta2O5 Hybrid Memristors with Crossbar Array Structure for Bio-Organic Neuromorphic Chip Applications.

In this study, a high-performance bio-organic memristor with a crossbar array structure using milk as a resistive switching layer (RSL) is proposed. To ensure compatibility with the complementary metal oxide semiconductor process of milk RSL, a high-k Ta2O5 layer was deposited as a capping layer; this layer enables high-density, integration-capable, photolithography processes. The fabricated crossbar array memristors contain milk-Ta2O5 hybrid membranes, and they exhibit bipolar resistance switching behavior and uniform resistance distribution across hundreds of repeated test cycles. In terms of the artificial synaptic behavior and synaptic weight changes, milk-Ta2O5 hybrid crossbar array memristors have a stable analog RESET process, and the memristors are highly responsive to presynaptic stimulation via paired-pulse facilitation excitatory post-synaptic current. Moreover, spike-timing-dependent plasticity and potentiation and depression behaviors, which closely emulate long-term plasticity and modulate synaptic weights, were evaluated. Finally, an artificial neural network was designed and trained to recognize the pattern of the Modified National Institute of Standards and Technology (MNIST) digits to evaluate the capability of the neuromorphic computing system. Consequently, a high recognition rate of over 88% was achieved. Thus, the milk-Ta2O5 hybrid crossbar array memristor is a promising electronic platform for in-memory computing systems.

Binary-Synaptic Plasticity in Ambipolar Ni-Silicide Schottky Barrier Poly-Si Thin Film Transistors Using Chitosan Electric Double Layer.

We propose an ambipolar chitosan synaptic transistor that effectively responds to binary neuroplasticity. We fabricated the synaptic transistors by applying a chitosan electric double layer (EDL) to the gate insulator of the excimer laser annealed polycrystalline silicon (poly-Si) thin-film transistor (TFT) with Ni-silicide (NiSi) Schottky-barrier source/drain (S/D) junction. The undoped poly-Si channel and the NiSi S/D contact allowed conduction by electrons and holes, resulting in artificial synaptic behavior in both p-type and n-type regions. A slow polarization reaction by the mobile ions such as anions (CH3COO- and OH-) and cations (H+) in the chitosan EDL induced hysteresis window in the transfer characteristics of the ambipolar TFTs. We demonstrated the excitatory post-synaptic current modulations and stable conductance modulation through repetitive potentiation and depression pulse. We expect the proposed ambipolar chitosan synaptic transistor that responds effectively to both positive and negative stimulation signals to provide more complex information process versatility for bio-inspired neuromorphic computing systems.

Time-Dependent Sensitivity Tunable pH Sensors Based on the Organic-Inorganic Hybrid Electric-Double-Layer Transistor.

In this study, we propose tunable pH sensors based on the electric-double-layer transistor (EDLT) with time-dependent sensitivity characteristics. The EDLT is able to modulate the drain current by using the mobile ions inside the electrolytic gate dielectric. This property allows the implementation of a device with sensitivity characteristics that are simply adjusted according to the measurement time. An extended gate-type, ion-sensitive, field-effect transistor consisting of a chitosan/Ta2O5 hybrid dielectric EDLT transducer, and an SnO2 sensing membrane, were fabricated to evaluate the sensing behavior at different buffer pH levels. As a result, we were able to achieve tunable sensitivity by only adjusting the measurement time by using a single EDLT and without additional gate electrodes. In addition, to demonstrate the unique sensing behavior of the time-dependent tunable pH sensors based on organic−inorganic hybrid EDLT, comparative sensors consisting of a normal FET with a SiO2 gate dielectric were prepared. It was found that the proposed pH sensors exhibit repeatable and stable sensing operations with drain current deviations <1%. Therefore, pH sensors using a chitosan electrolytic EDLT are suitable for biosensor platforms, possessing tunable sensitivity and high-reliability characteristics.

Biocompatible Casein Electrolyte-Based Electric-Double-Layer for Artificial Synaptic Transistors.

In this study, we proposed a synaptic transistor using an emerging biocompatible organic material, namely, the casein electrolyte as an electric-double-layer (EDL) in the transistor. The frequency-dependent capacitance of the indium-tin-oxide (ITO)/casein electrolyte-based EDL/ITO capacitor was assessed. As a result, the casein electrolyte was identified to exhibit a large capacitance of ~1.74 µF/cm2 at 10 Hz and operate as an EDL owing to the internal proton charge. Subsequently, the implementation of synaptic functions was verified by fabricating the synaptic transistors using biocompatible casein electrolyte-based EDL. The excitatory post-synaptic current, paired-pulse facilitation, and signal-filtering functions of the transistors demonstrated significant synaptic behavior. Additionally, the spike-timing-dependent plasticity was emulated by applying the pre- and post-synaptic spikes to the gate and drain, respectively. Furthermore, the potentiation and depression characteristics modulating the synaptic weight operated stably in repeated cycle tests. Finally, the learning simulation was conducted using the Modified National Institute of Standards and Technology datasets to verify the neuromorphic computing capability; the results indicate a high recognition rate of 90%. Therefore, our results indicate that the casein electrolyte is a promising new EDL material that implements artificial synapses for building environmental and biologically friendly neuromorphic systems.

Artificial Synapses Based on Bovine Milk Biopolymer Electric-Double-Layer Transistors.

With the growing demand for bio- and eco-friendly artificial synapses, we propose a novel synaptic transistor using natural bovine-milk-based biocompatible polymers as an electrical double layer (EDL). A method for forming an EDL membrane, which plays a key role in synaptic devices, was established using a milk-based biocompatible polymer. The frequency-dependent capacitance of a milk-based polymer-EDL was evaluated by constructing an EDL capacitor (EDLC) with indium-tin-oxide (ITO) electrode. As a result, a significantly large capacitance (1.48 µF/cm2 at 1 Hz) was identified as an EDL effect due to the proton charge of the bovine-milk-based polymer, which is much more superior compared to conventional insulating materials such as SiO2. Subsequently, by using a milk-based polymer-EDL membrane in the fabrication of electronic synaptic transistors, we successfully implemented important synaptic functions, such as paired-pulse facilitation, dynamic filtering, and synaptic-weight-integration-based logic operations. Therefore, the proposed milk-based biocompatible polymer-EDL membrane offers new opportunities for building eco-friendly and biodegradable artificial synaptic systems.