Institute of Microelectronics

Phosphor-converted light-emitting diodes (LEDs) were fabricated by precoating blue/green/red phosphors onto near ultraviolate (n-UV) LED chips prior to package into LED lamps. With a 20-mA injection current, it was found that the color temperature T/sub c/ was around 5900 K and the color-rendering index R/sub a/ was around 75 for the "n-UV+blue/green/red" white LED lamps. It was also found that no changes in color temperature T/sub c/ and color-rendering index R/sub a/ could be observed when we increased the injection from 20 to 60 mA. These results indicate that such "n-UV+blue/green/red" white LEDs are much more optically stable than the conventional "blue+yellow" LEDs.

Complex-valued neural networks have many advantages over their real-valued counterparts. Conventional digital electronic computing platforms are incapable of executing truly complex-valued representations and operations. In contrast, optical computing platforms that encode information in both phase and magnitude can execute complex arithmetic by optical interference, offering significantly enhanced computational speed and energy efficiency. However, to date, most demonstrations of optical neural networks still only utilize conventional real-valued frameworks that are designed for digital computers, forfeiting many of the advantages of optical computing such as efficient complex-valued operations. In this article, we highlight an optical neural chip (ONC) that implements truly complex-valued neural networks. We benchmark the performance of our complex-valued ONC in four settings: simple Boolean tasks, species classification of an Iris dataset, classifying nonlinear datasets (Circle and Spiral), and handwriting recognition. Strong learning capabilities (i.e., high accuracy, fast convergence and the capability to construct nonlinear decision boundaries) are achieved by our complex-valued ONC compared to its real-valued counterpart.

Abstract Resistive switching (RS) is an interesting property shown by some materials systems that, especially during the last decade, has gained a lot of interest for the fabrication of electronic devices, with electronic nonvolatile memories being those that have received the most attention. The presence and quality of the RS phenomenon in a materials system can be studied using different prototype cells, performing different experiments, displaying different figures of merit, and developing different computational analyses. Therefore, the real usefulness and impact of the findings presented in each study for the RS technology will be also different. This manuscript describes the most recommendable methodologies for the fabrication, characterization, and simulation of RS devices, as well as the proper methods to display the data obtained. The idea is to help the scientific community to evaluate the real usefulness and impact of an RS study for the development of RS technology.

This paper demonstrates gate-all-around (GAA) n- and p-FETs on a silicon-on-insulator with /spl les/ 5-nm-diameter laterally formed Si nanowire channel. Alternating phase shift mask lithography and self-limiting oxidation techniques were utilized to form 140- to 1000-nm-long nanowires, followed by FET fabrication. The devices exhibit excellent electrostatic control, e.g., near ideal subthreshold slope (/spl sim/ 63 mV/dec), low drain-induced barrier lowering (/spl sim/ 10 mV/V), and with I/sub ON//I/sub OFF/ ratio of /spl sim/10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> . High drive currents of /spl sim/ 1.5 and /spl sim/1.0 mA/μm were achieved for 180-nm-long nand p-FETs, respectively. It is verified that the threshold voltage of GAA FETs is independent of substrate bias due to the complete electrostatic shielding of the channel body.

Evolution of growth/dissolution conductive filaments (CFs) in oxide-electrolyte-based resistive switching memories are studied by in situ transmission electron microscopy. Contrary to what is commonly believed, CFs are found to start growing from the anode (Ag or Cu) rather than having to reach the cathode (Pt) and grow backwards. A new mechanism based on local redox reactions inside the oxide-electrolyte is proposed. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

We reported an efficient inverted bulk-heterojunction [regioregular of poly(3-hexylthiophene): (6,6)-phenyl C61 butyric acid methyl ester] solar cell with a highly transparent sol-gel derived ZnO film as electron selective layer and MoO3 as hole selective layer. By modifying the precursor concentration of sol from 0.75 to 0.1M, the optical transmittance of ZnO film increases from 75% to 95%. This improvement in transmittance increases the short-circuit density of inverted solar cell from 5.986 to 8.858 mA/cm2 without sacrificing the open-circuit voltage and fill factor of the device. We also demonstrated that the device incorporated with MoO3 has a larger open-circuit voltage and fill factor than the device without MoO3. Power conversion efficiency of 3.09% was achieved under simulated AM 1.5G illumination of 100 mW/cm2.

Surmounting the inhomogeniety issue of gas sensors and realizing their reproducible ppb-level gas sensing are highly desirable for widespread deployments of sensors to build networks in applications of industrial safety and indoor/outdoor air quality monitoring. Herein, a strategy is proposed to substantially improve the surface homogeneity of sensing materials and gas sensing performance via chip-level pyrolysis of as-grown ZIF-L (ZIF stands for zeolitic imidazolate framework) films to porous and hierarchical zinc oxide (ZnO) nanosheets. A novel approach to generate adjustable oxygen vacancies is demonstrated, through which the electronic structure of sensing materials can be fine-tuned. Their presence is thoroughly verified by various techniques. The sensing results demonstrate that the resultant oxygen vacancy-abundant ZnO nanosheets exhibit significantly enhanced sensitivity and shortened response time toward ppb-level carbon monoxide (CO) and volatile organic compounds encompassing 1,3-butadiene, toluene, and tetrachloroethylene, which can be ascribed to several reasons including unpaired electrons, consequent bandgap narrowing, increased specific surface area, and hierarchical micro-mesoporous structures. This facile approach sheds light on the rational design of sensing materials via defect engineering, and can facilitate the mass production, commercialization, and large-scale deployments of sensors with controllable morphology and superior sensing performance targeted for ultratrace gas detection.

In this letter, the authors report a dye-sensitized solar cell (DSSC) using a ZnO-nanoflower film photoanode, which was grown by a hydrothermal method at 95°C. The dye used was cis-bis(isothiocyanato)bis(2,2′-bipyridyl-4,4′-dicarboxylato)-ruthenium(II) bis-tetrabutylam-monium (N-719). At AM1.5G irradiation with 100mW∕cm2 light intensity, the DSSC based on ZnO-nanoflower film showed an energy conversion efficiency of 1.9%, which is much higher compared to that (1.0%) of the control device constructed using a photoanode of upstanding ZnO-nanorod array fabricated by hydrothermal method as well. The better performance of ZnO-nanoflower DSSC was due to a better dye loading and light harvesting of the ZnO-nanoflower film. The results demonstrate potential application of ZnO-nanoflower array for efficient dye-sensitized solar cells.

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Neuromorphic computing is an emerging computing paradigm beyond the conventional digital von Neumann computation. An oxide-based resistive switching memory is engineered to emulate synaptic devices. At the device level, the gradual resistance modulation is characterized by hundreds of identical pulses, achieving a low energy consumption of less than 1 pJ per spike. Furthermore, a stochastic compact model is developed to quantify the device switching dynamics and variation. At system level, the performance of an artificial visual system on the image orientation or edge detection with 16 348 oxide-based synaptic devices is simulated, successfully demonstrating a key feature of neuromorphic computing: tolerance to device variation. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Neuromorphic computing represents an innovative technology that can perform intelligent and energy-efficient computation, whereas construction of neuromorphic systems requires biorealistic synaptic elements with rich dynamics that can be tuned based on a robust mechanism. Here, an ionic-gating-modulated synaptic transistor based on layered crystals of transitional metal dichalcogenides and phosphorus trichalcogenides is demonstrated, which produce a diversity of short-term and long-term plasticity including excitatory postsynaptic current, paired pulse facilitation, spiking-rate-dependent plasticity, dynamic filtering, etc., with remarkable linearity and ultralow energy consumption of ≈30 fJ per spike. Detailed transmission electron microscopy characterization and ab initio calculation reveal two-stage ionic gating effects, namely, surface adsorption and internal intercalation in the channel medium, causing different poststimulation diffusive dynamics and thus accounting for the observed short-term and long-term plasticity, respectively. The synaptic activity can therefore be effectively manipulated by tailoring the ionic gating and consequent diffusion dynamics with varied thickness and structure of the van der Waals material as well as the number, duration, rate, and polarity of gate stimulations, making the present synaptic transistors intriguing candidates for low-power neuromorphic systems.

The ever-increasing concerns over indoor/outdoor air quality, industrial gas leakage, food freshness, and medical diagnosis require miniaturized gas sensors with excellent sensitivity, selectivity, stability, low power consumption, cost-effectiveness, and long lifetime. Metal-organic frameworks (MOFs), featuring structural diversity, large specific surface area, controllable pore size/geometry, and host-guest interactions, hold great promises for fabricating various MOF-based devices for diverse applications including gas sensing. Tremendous progress has been made in the past decade on the fabrication of MOF-based sensors with elevated sensitivity and selectivity toward various analytes due to their preconcentrating and molecule-sieving effects. Although several reviews have recently summarized different aspects of this field, a comprehensive review focusing on MOF-based gas sensors is absent. In this review, the latest advance of MOF-based gas sensors relying on different transduction mechanisms, for example, chemiresistive, capacitive/impedimetric, field-effect transistor or Kelvin probe-based, mass-sensitive, and optical ones are comprehensively summarized. The latest progress for making large-area MOF films essential to the mass-production of relevant gas sensors is also included. The structural and compositional features of MOFs are intentionally correlated with the sensing performance. Challenges and opportunities for the further development and practical applications of MOF-based gas sensors are also given.

We report herein a glucose biosensor based on glucose oxidase (GOx) immobilized on ZnO nanorod array grown by hydrothermal decomposition. In a phosphate buffer solution with a pH value of 7.4, negatively charged GOx was immobilized on positively charged ZnO nanorods through electrostatic interaction. At an applied potential of +0.8V versus Ag∕AgCl reference electrode, ZnO nanorods based biosensor presented a high and reproducible sensitivity of 23.1μAcm−2mM−1 with a response time of less than 5s. The biosensor shows a linear range from 0.01to3.45mM and an experiment limit of detection of 0.01mM. An apparent Michaelis-Menten constant of 2.9mM shows a high affinity between glucose and GOx immobilized on ZnO nanorods.

The ability to detect small amounts of materials, especially pathogenic bacteria, is important for medical diagnostics and for monitoring the food supply. Engineered micro- and nanomechanical systems can serve as multifunctional, highly sensitive, immunospecific biological detectors. We present a resonant frequency-based mass sensor, comprised of low-stress silicon nitride cantilever beams for the detection of Escherichia coli (E. coli)-cell-antibody binding events with detection sensitivity down to a single cell. The binding events involved the interaction between anti-E. coli O157:H7 antibodies immobilized on a cantilever beam and the O157 antigen present on the surface of pathogenic E. coli O157:H7. Additional mass loading from the specific binding of the E. coli cells was detected by measuring a resonant frequency shift of the micromechanical oscillator. In air, where considerable damping occurs, our device mass sensitivities for a 15 μm and 25 μm long beam were 1.1 Hz/fg and 7.1 Hz/fg, respectively. In both cases, utilizing thermal and ambient noise as a driving mechanism, the sensor was highly effective in detecting immobilized anti-E. coli antibody monolayer assemblies, as well as single E. coli cells. Our results suggest that tailoring of oscillator dimensions is a feasible approach for sensitivity enhancement of resonant mass sensors.

Rapid prototyping of polydimethylsiloxane (PDMS) is often used to build microfluidic devices. However, the inherent hydrophobic nature of the material limits the use of PDMS in many applications. While different methods have been developed to transform the hydrophobic PDMS surface to a hydrophilic surface, the actual implementation proved to be time consuming due to differences in equipment and the need for characterization. This paper reports a simple and easy protocol combining a second extended oxygen plasma treatments and proper storage to produce usable hydrophilic PDMS devices. The results show that at a plasma power of 70 W, an extended treatment of over 5 min would allow the PDMS surface to remain hydrophilic for more than 6 h. Storing the treated PDMS devices in de-ionized water would allow them to maintain their hydrophilicity for weeks. Atomic force microscopy analysis shows that a longer oxygen plasma time produces a smoother surface.

In this paper we review the subject of oxide breakdown (BD), focusing our attention on the case of the gate dielectrics of interest for current Si microelectronics, i.e., Si oxides or oxynitrides of thickness ranging from some tens of nanometers down to about 1nm. The first part of the paper is devoted to a concise description of the subject concerning the kinetics of oxide degradation under high-voltage stress and the statistics of the time to BD. It is shown that, according to the present understanding, the BD event is due to a buildup in the oxide bulk of defects produced by the stress at high voltage. Defect concentration increases up to a critical value corresponding to the onset of one percolation path joining the gate and substrate across the oxide. This triggers the BD, which is therefore believed to be an intrinsic effect, not due to preexisting, extrinsic defects or processing errors. We next focus our attention on experimental studies concerning the kinetics of the final event of BD, during which the gate leakage increases above acceptable levels. In conditions of intrinsic BD, the leakage increase is due to the growth of damage within the oxide in localized regions. Observations concerning this damage are reviewed and discussed. The measurement of the current, voltage, and power dissipated during the BD transient are also reported and discussed in comparison with the data of structural damage. We then describe the current understanding concerning the dependence of the BD current transient on the conditions of electric field and voltage. In particular, as the oxide thickness and, as a consequence, the voltage levels used for accelerated reliability tests have decreased, the BD transient exhibits a marked change in behavior. As the stress voltage is decreased below a threshold value, the BD transient becomes slower. This recently discovered phenomenon has been termed progressive BD, i.e., a gradual growth of the BD spot and of the gate leakage, with a time scale that under operation conditions can be a large fraction of the total time to BD. We review the literature on this phenomenon, describing the current understanding concerning the dependence of the effect on voltage, temperature, oxide thickness, sample geometry, and its physical structure. We also discuss the possible relation to the so-called soft oxide BD mode and propose a simpler, more consistent terminology to describe different BD regimes. The last part of the paper is dedicated to exploratory studies, still at the early stages given the very recent subject, concerning the impact on the BD of materials for the metal-oxide-semiconductor gate stack and, in particular, metal gates.

Abstract Memristor, based on the principle of biological synapse, is recognized as one of the key devices in confronting the bottleneck of classical von Neumann computers. However, conventional memristors are difficult to continuously adjust the conduction and dutifully mimic the biosynapse function. Here, TiO 2 films with self‐assembled Ag nanoclusters implemented by gradient Ag dopant are employed to achieve enhanced memristor performance. The memristors exhibit gradual both potentiating and depressing conduction under positive and negative pulse trains, which can fully emulate excitation and inhibition of biosynapse. Moreover, comprehensive biosynaptic functions and plasticity, including the transition from short‐term memory to long‐term memory, long‐term potentiation and depression, spike‐timing‐dependent plasticity, and paired‐pulse facilitation, are implemented with the fabricated memristors in this work. The applied pulses with a width of hundreds of nanoseconds timescale are beneficial to realize fast learning and computing. High‐resolution transmission electron microscopy observations clearly demonstrate that Ag clusters redistribute to form Ag conductive filaments between Ag and Pt electrode under electrical field at ON‐state device. The experimental data confirm that the oxides doped with Ag clusters have the potential for mimicking biosynaptic behavior, which is essential for the further creation of artificial neural systems.

Arrays of highly ordered n-type silicon nanowires (SiNW) are fabricated using complementary metal-oxide semiconductor (CMOS) compatible technology, and their applications in biosensors are investigated. Peptide nucleic acid (PNA) capture probe-functionalized SiNW arrays show a concentration-dependent resistance change upon hybridization to complementary target DNA that is linear over a large dynamic range with a detection limit of 10 fM. As with other SiNW biosensing devices, the sensing mechanism can be understood in terms of the change in charge density at the SiNW surface after hybridization, the so-called "field effect". The SiNW array biosensor discriminates satisfactorily against mismatched target DNA. It is also able to monitor directly the DNA hybridization event in situ and in real time. The SiNW array biosensor described here is ultrasensitive, non-radioactive, and more importantly, label-free, and is of particular importance to the development of gene expression profiling tools and point-of-care applications.

We have demonstrated high-sensitivity detection of bacteria using an array of bulk micromachined resonant cantilevers. The biological sensor is a micromechanical oscillator that consists of an array of silicon-nitride cantilevers with an immobilized antibody layer on the surface of the resonator. Measured resonant frequency shift as a function of the additional cell loading was observed and correlated to the mass of the specifically bound Escherichia coli O157:H7 cells. Deposition and subsequent detection of E. coli cells was achieved under ambient conditions.

Abstract Memristors with nonvolatile memory characteristics have been expected to open a new era for neuromorphic computing and digital logic. However, existing memristor devices based on oxygen vacancy or metal‐ion conductive filament mechanisms generally have large operating currents, which are difficult to meet low‐power consumption requirements. Therefore, it is very necessary to develop new materials to realize memristor devices that are different from the mechanisms of oxygen vacancy or metal‐ion conductive filaments to realize low‐power operation. Herein, high‐performance and low‐power consumption memristors based on 2D WS 2 with 2H phase are demonstrated, which show fast ON (OFF) switching times of 13 ns (14 ns), low program current of 1 µA in the ON state, and SET (RESET) energy reaching the level of femtojoules. Moreover, the memristor can mimic basic biological synaptic functions. Importantly, it is proposed that the generation of sulfur and tungsten vacancies and electron hopping between vacancies are dominantly responsible for the resistance switching performance. Density functional theory calculations show that the defect states formed by sulfur and tungsten vacancies are at deep levels, which prevent charge leakage and facilitate the realization of low‐power consumption for neuromorphic computing application.