Developing a small, smart, and sensitive pressure sensor array is necessary for establishing a comfortable and safe environment in daily life. Herein, the miniaturization effects of $1\times 1$ poly (3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) piezoresistive pressure sensors with a cross-point electrode (CPE) structure have been investigated and found to suffer from response delays owing to the serious current crowding effect. To eliminate the adverse effects caused by the device scaling, polypyrrole (PPy) was blended into PEDOT:PSS to obtain a high piezoresistive sensitivity of 0.58 kPa−1 and a fast relaxation time of 0.74 s for the miniaturized PEDOT:PSS/PPy piezoresistive pressure sensors with a PPy concentration of 60 ppm. Subsequently, the optimized PEDOT:PSS/PPy composites were implemented to fabricate $3\times 3$ CPE piezoresistive sensor arrays with an electrode size of 0.2 mm, and a readout circuit was designed to instantaneously measure the resistance of each pixel of the sensor arrays under the application of pressure. Using the $3\times 3$ PEDOT:PSS/PPy piezoresistive sensor arrays with a readout circuit, the pressure distribution of the finger pressing and an occlusal pressure monitoring of a molar before and after the dental filling process were successfully demonstrated, suitable for prospective applications in biomedicine.

Heat generation in integrated circuits (ICs) has become a severe issue, which limits the utilization of miniaturized semiconductor devices in high-density 3-D IC technologies. Herein, Al2O3 was doped in ZrO2 thin films by plasma-enhanced atomic layer deposition (PEALD) to enhance their antiferroelectric (AFE) characteristics for highly reliable electrocaloric (EC) cooling applications. The cycling endurance in AFE behaviors of the Al:ZrO2 thin films under a high electric field of 5 MV/cm was significantly improved because of the enlargement of the energy bandgap with high resistance in trap-induced leakage current. Hence, the reliability of the EC effect of the 1% Al:ZrO2 thin film was examined with a negligible change in adiabatic temperature change ( $\Delta {T}$ ) of 2.6% after a cycling endurance test of $10^{{6}}$ cycles. With the competitive cycling reliabilities in AFE and EC behaviors, devices with optimized Al2O3-incorporated ZrO2 thin films show significant potential for future nanoscale cooling systems in chip-level ICs.

Solar-to-fuel conversion is an innovative concept for green energy, attracting many researchers to explore them. Solar-driven photocatalysts have become an essential solution to provide valuable chemicals like hydrogen, hydrocarbon, and ammonia. For sustainable stability under solar irradiation, titanium dioxide is regarded as an acceptable candidate, further showing excellent photocatalytic activity. Incorporating the photo-sensitizers, including noble metal nanoparticles and polymeric carbon-based material, can improve its photoresponse and facilitate the electron transfer and collection. In this study, we synthesized the graphitic carbon nitride (g-C3N4) nanosheet incorporated with high crystalline TiO2 nanofibers (NF) as 1D/2D heterostructure catalyst for photocatalytic water splitting. The microstructure, optical absorption, crystal structure, charge carrier dynamics, and specific surface area were characterized systematically. The low bandgap of 2D g-C3N4 nanosheets (NS) as a sensitizer improves the specific surface area and photo-response in the visible region as the incorporated amount increases. Because of the band structure difference between TiO2 and g-C3N4, constructing the heterojunction formation, the superior separation of electron-hole is observed. The detection of reactive oxygen species and photo-assisted Kelvin probe microscopy are conducted to investigates the possible charge migration. The highest photocatalytic hydrogen production rate of Pd/TiO2/g-C3N4 achieves 11.62 mmol·h−1·g−1 under xenon lamp irradiation.

Traditional physical-based models have generally been used to model the resistive-switching behavior of resistive-switching memory (RSM). Recently, vacancy-based conduction-filament (CF) growth models have been used to model device characteristics of a wide range of RSM devices. However, few have focused on learning the other-device-parameter values (e.g., low-resistance state, high-resistance state, set voltage, and reset voltage) to compute the compliance-current (CC) value that controls the size of CF, which can influence the behavior of RSM devices. Additionally, traditional CF growth models are typically physical-based models, which can show accuracy limitations. Machine learning holds the promise of modeling vacancy-based CF growth by learning other-device-parameter values to compute the CC value with excellent accuracy via examples, bypassing the need to solve traditional physical-based equations. Here, we sidestep the accuracy issues by directly learning the relationship between other-device-parameter values to compute the CC values via a data-driven approach with high accuracy for test devices and various device types using machine learning. We perform the first modeling with machine-learned device parameters on aluminum-nitride-based RSM devices and are able to compute the CC values for nitrogen-vacancy-based CF growth using only a few RSM device parameters. This model may now allow the computation of accurate RSM device parameters for realistic device modeling.

CF4 plasma treatment on n(+)-Si wafers as bottom electrodes (BEs) of poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) metal-ferroelectric-metal (MFM) capacitors has been investigated in this study. Prior to the fabrication of MFM capacitors, comprehensive material analyses are administered to identify the incorporation of fluorine atoms into P(VDF-TrFE) copolymers, revealing an enrichment in C2HF3 (trifluoroethylene) bonds and an improvement in the crystallinity of the film. The P(VDF-TrFE) MFM capacitors with CF4-plasma-treated n(+)-Si wafers show a shallower charge trapping level of 0.154-0.226 eV extracted from the Frenkel-Poole (F-P) emission at 213-273 K for the BE injection compared to that for the top electrode (TE) injection, which is ascribed to the passivation of deep traps by the fluorine atoms that diffused from the n(+)-Si wafers. Thus, asymmetric remanent polarization and a negative internal bias field are obtained because of the significant increase in the beta-phase at the bottom of the P(VDF-TrFE) films. With the CF4 plasma treatment for 1 min. the P(VDF-TrFE) MFM capacitors demonstrate a remanent polarization (2P(r)) of 6.58 mu C/cm(2), a coercive electric field (E-c) of 0.47 MV/cm and stability for more than 3 x 10(4) cycles with negligible fatigue, making the fluorine-incorporated P(VDF-TrFE) copolymers suitable for future high-performance nonvolatile memory applications. (C) 2019 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Resistive-switching memory (RSM) is one of the most promising candidates for next-generation edge computing devices due to its excellent device performance. Currently, a number of experimental and modeling studies have been reported to understand the conduction behaviors. However, a complete physical picture that can describe the conduction behavior is still missing. Here, we present a conduction model that not only fully accounts for the rich conduction behaviors of RSM devices by harnessing a combination of electronic and thermal considerations via electron mobility and trap-depth and with excellent accuracy but also provides critical insight for continued design, optimization, and application. A physical model that is able to describe both the conduction and switching behaviors using only a single set of expressions is achieved. The proposed model reveals the role of temperature, mobility of electrons, and depth of traps, and allows accurate prediction of various set and reset processes obtained by an entirely new set of general current-limiting parameters.

Memristors with rich interior dynamics of ion migration are promising for mimicking various biological synaptic functions in neuromorphic hardware systems. A graphene-based memristor shows an extremely low energy consumption of less than a femtojoule per spike, by taking advantage of weak surface van der Waals interaction of graphene. The device also shows an intriguing programmable metaplasticity property in which the synaptic plasticity depends on the history of the stimuli and yet allows rapid reconfiguration via an immediate stimulus. This graphene-based memristor could be a promising building block toward designing highly versatile and extremely energy efficient neuromorphic computing systems.

Graphene nanodiscs (GNDs), functionalized using NH3 plasma, as charge trapping sites (CTSs) for nonvolatile memory applications have been investigated in this study. The fabrication process relies on the patterning of Au nanoparticles (Au-NPs), whose thicknesses are tuned to adjust the GND density and size upon etching. A GND density as high as 8 x 10(11) cm(-2) and a diameter of approximately 20 nm are achieved. The functionalization of GNDs by NH3 plasma creates N-H+ functional groups that act as CTSs, as observed by Raman and Fourier transform infrared spectroscopy. This inherently enhances the density of CTSs in the GNDs, as a result, the memory window becomes more than 2.4 V and remains stable after 10(4) operating cycles. The charge loss is less than 10% for a 10-year data retention testing, making this low-temperature process suitable for low-cost non-volatile memory applications on flexible substrates. (C) 2016 Elsevier Ltd. All rights reserved.

In this study, the cross-talk effects and the basic piezoresistive characteristics of gold nanoparticle (Au-NP) incorporated poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) pressure sensing 2 × 2 arrays are investigated using a cross-point electrode (CPE) structure. Transmission electron microscopy (TEM), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) mappings were carried out to confirm the incorporation of Au-NPs in the PEDOT:PSS films. A solution mixing process was employed to incorporate the nanoparticles. When the diameter of the Au-NPs incorporated in the PEDOT:PSS films (Au-NPs/PEDOT:PSS) was 20 nm, the piezoresistive pressure sensing 2 × 2 arrays were almost immune to cross-talk effects, which enhances the pressure sensing accuracy of the array. The Au-NPs render the PEDOT:PSS films more resilient. This is confirmed by the high plastic resistance values using a nanoindenter, which reduce the interference between the active and passive cells. When the size of the Au-NPs is more than 20 nm, a significant cross-talk effect is observed in the pressure sensing arrays as a result of the high conductivity of the Au-NPs/PEDOT:PSS films with large Au-NPs. With the incorporation of optimally sized Au-NPs, the PEDOT:PSS piezoresistive pressure sensing arrays can be promising candidates for future high-resolution fingerprint identification system with multiple-electrode array structures.

Characteristics of chemically-synthesized (CS) gold nanoparticle (Au-NP) nonvolatile memories (NVMs) with low-damage NH3 plasma treatment on a tunneling oxide (TO) layer have been investigated. Although the dot density of CS Au-NPs is decreased, the programming efficiency of memories with optimized NH3 plasma treatment condition is enhanced due to the formation of a trapezoid-like energy band diagram of the TO layer by nitrogen incorporation. With the extraction of relative permittivity and electron affinity of the TO layer, the capacitance-voltage (C-V) and programming behaviors of CS Au-NP memories with low-damage NH3 plasma treatment on the TO layer are well-fitted by the TCAD (Technology Computer-Aided-Design) simulation. Further, the built-in electric field induced by the trapezoid-like energy band diagram of the TO layer can suppress the leakage current of the TO layer, thereby improving the data retention properties. The low-damage NH3 plasma treatment that results in no plasma damage to the TO layer has been proposed to be the probable candidate for future NVM applications.

This study investigated the effects of the bottom electrode (BE) on the resistive switching (RS) of silver programmable metallization cells (Ag-PMCs) with gadolinium oxide and aluminum oxide (GdxOy/AlxOy) solid electrolytes (SEs). The RS mechanisms of memories with different bottom electrodes were proposed based on the temperature dependence of the resistance at low resistance state (LRS) and current voltage (I-V) fitting at high resistance state (HRS). The Schottky emission was dominant in the resistive switching of the memory with an iridium bottom electrode (Ir-BE), whereas in the memories with n(+)-Si and nickel (Ni) bottom electrodes, silver and both silver and nickel ions dominated the resistive switching, respectively. Additionally, the Ag-PMC with Ni-BE had a high resistance ratio of more than 107 as a result of the extremely low resistance of roughly 50 Omega at LRS. The Ag-PMCs with GdxOy/AlxOy SEs and Ni-BE exhibited a retention behavior of more than 10(4) s and an endurance of more than 500 cycles with a resistance ratio of at least four orders of magnitude, which is promising for future high-density nonvolatile memory applications. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract The piezoresistive and cross-talk properties of gold nanoparticle (Au-NPs) incorporated PEDOT:PSS pressure sensors with 22 cross-point array structure have been investigated. With the Au-NPs incorporation, the PEDOT:PSS pressure sensors present a fast response and cross-talk immunity as compared with the pure PEDOT:PSS one. The improved piezoresistive response and cross-talk properties can be explained by the Au-NP assisted electron hopping and fast relaxation of PSS chain by the Au-NPs respectively, suitable for future high-density pressure sensing applications.

Display Omitted Study of Gd2O3-NC memories with Al2O3/HfO2/Al2O3 (AHA) stacked tunnelling layers.Superior P/E properties achieved by Gd2O3-NC memories with optimized AHA layers.Improved retention properties obtained by Gd2O3-NC memories with AHA layers.Gd2O3-NC memories with stable VFB after a P/E cycling test of 104 times realized. Characteristics of Gd2O3-NC memories with multiple tunneling layers of Al2O3/HfO2/Al2O3 (AHA) have been investigated. It can be found that the Gd2O3-NC memory with thin bottom and thin top Al2O3 film of AHA stacked tunneling layers exhibits superior programming and erasing (P/E) properties, respectively. Compared with the memory with SiO2 tunneling layer, the retention characteristics of Gd2O3-NC memories with AHA stacked tunneling layers are significantly improved. In addition, for the memories with AHA stacked tunneling layers, the trapping energy level (Et) of shallow-trap (ST) electron loss is decreased but that of deep-trap (DT) electron loss is increased due to some shallow traps within HfO2 film and the midgap interface states at HfO2/Si interface respectively. Further, the dependence of AHA stacked layer thickness on memory characteristics can be explained by the band engineering of tunneling layer. The Gd2O3-NC memories with AHA stacked tunneling layers can sustain a stable memory window of more than 1.6V after a P/E cycling test of 104 times.

In-Ga-Zn-O (IGZO) was widely applied in the substrate of TFT to replace alpha-Si in recent years. In this study, IGZO layer with thickness of 70 nm is firstly proposed as a pH-sensing membrane directly deposited on P-type Si substrate acting as an extended gate of conventional extended-gate field-effect transistor (EGFET). Post-deposition rapid thermal anneal (RTA) was performed to improve pH sensing performance of IGZO layer sputtered with Ar/O-2 flow rate of 20/5 in sccm. Sensitivity could be increased from 41.5 mV/pH to 53.3 mV/pH by RTA in N-2 ambience at 700 degrees C in pH application range between pH 2 and 10. XRD analysis supports the orientation changes of IGZO layer after RTA at different temperature. Ar/O-2 ratio was also modified in the RF sputtering. IGZO-EGFET prepared by Ar/O-2 ambience of 24/1 in sputtering can have the highest sensitivity and linearity of 59.5 mV/pH and 99.7%, respectively. After 7 months, sensitivity and linearity are 51.4 mV/pH and 92%, respectively. Etch rate and drift coefficient in standard buffer solution are higher than in other sensing material for EGFET and ISFET. More studies on enlargement of pH application range and minimisation of non-ideal effect still need to be investigated before real applications.

Ambipolar carrier injection and charge retention phenomenon of gold-nanocrystal (Au-NC) memories with different tunneling oxide (TO) thickness were investigated. For the samples with thin TO (∼3 nm), the electrons were injected from the substrate at positive gate bias. With the increase of TO thickness, the holes injected from the gate became more significant. Compared with the gate injected holes in the sample with thick TO, the substrate injected electrons in the sample with thin TO show a higher charge loss. The poor charge retention can be ascribed to the direct tunneling leakage current through the thin TO. Further, the Au-NC memories with electrons exhibit lower activation energy of charge loss than that with holes, which is due to the lower electron barrier height of the Au-NC memory.

The paper reports samarium oxide as pH. sensing membrane on polysilicon combined with proper post deposition annealing for the extended-gate field-effect transistor (EGFET) application at the first time. It can be found that the high-k samarium oxide membrane annealed at 700 ºC could obtain high sensitivity, high linearity, low hysteresis voltage, and low drift rate due to improvements ofcrystalline structures. The high-k Sm2O3 sensing membrane shows great promise for future bio-medical device applications.