Enhanced Resistive Switching and Synaptic Characteristics of ALD Deposited AlN-Based RRAM by Positive Soft Breakdown Process.

Nitride film played an essential role as an excellent diffusion barrier in the semiconductor field for several decades. In addition, interest in next-generation memories induced researchers' attention to nitride film as a new storage medium. A Pt/AlN/TaN device was investigated for resistive random-access memory (RRAM) application in this work. Resistive switching properties were examined in the AlN thin film formed by atomic layer deposition (ALD). The unique switching feature conducted under the positive voltage was investigated, while the typical bipolar switching was conducted under the application of negative voltage. Good retention and DC, and pulse endurances were achieved in both conditions and compared to the memory performances. Finally, the electronic behaviors based on the unique switching feature were analyzed through X-ray photoelectron spectroscopy (XPS) and the current-voltage (I-V) linear fitting model.

Programming Escherichia coli to function as a digital display.

Synthetic genetic circuits offer the potential to wield computational control over biology, but their complexity is limited by the accuracy of mathematical models. Here, we present advances that enable the complete encoding of an electronic chip in the DNA carried by Escherichia coli (E. coli). The chip is a binary-coded digit (BCD) to 7-segment decoder, associated with clocks and calculators, to turn on segments to visualize 0-9. Design automation is used to build seven strains, each of which contains a circuit with up to 12 repressors and two activators (totaling 63 regulators and 76,000 bp DNA). The inputs to each circuit represent the digit to be displayed (encoded in binary by four molecules), and output is the segment state, reported as fluorescence. Implementation requires an advanced gate model that captures dynamics, promoter interference, and a measure of total power usage (RNAP flux). This project is an exemplar of design automation pushing engineering beyond that achievable "by hand", essential for realizing the potential of biology.

Organic-Inorganic Nanocomposite Film for High-Performance Stretchable Resistive Memory Device.

A compatible organic/inorganic nanocomposite film for a stretchable resistive memory device with high performance is demonstrated using poly(4-vinylpyridine)-block-poly(propyl methacrylate) (P4VP-b-PPMA) with zinc oxide (ZnO) nanoparticle. The PPMA soft segment is designed for reducing the rigidity of the active layer, while the P4VP block serves as a charge-trapping component to induce conductive filament and also a compatible moiety for inorganic nanoparticles through hydrogen bonding. The experimental results show that the P4VP-b-PPMA-based electrical memory device exhibits write-once-read-many-times memory behavior and an excellent ON/OFF current ratio of over 105 with a stable turn-on voltage (Vset ) around -2.0 V and stable memory behavior upon stretching up to 60% strain. On the other hand, P4VP-b-PPMA/ZnO nanocomposite film switches the memory characteristic to the dynamic random access memory behavior. The stretchable memory device prepared from the nanocomposite film can have a stretching durability over 40% strain and up to 1000 times cycling stretch-relaxation test. This work demonstrates a new strategy using nanocomposite films with tunable electrical characteristics and enhanced mechanical properties for stretchable electrical devices.

Non-Volatile Transistor Memory with a Polypeptide Dielectric.

Organic nonvolatile transistor memory with synthetic polypeptide derivatives as dielectric was fabricated by a solution process. When only poly (γ-benzyl-l-glutamate) (PBLG) was used as dielectric, the device did not show obvious hysteresis in transfer curves. However, PBLG blended with PMMA led to a remarkable increase in memory window up to 20 V. The device performance was observed to remarkably depend on the blend ratio. This study suggests the crystal structure and the molecular alignment significantly affect the electrical performance in transistor-type memory devices, thereby provides an alternative to prepare nonvolatile memory with polymer dielectrics.

Leaving us with fond memories, smiles, SMILES and, alas, tears: a tribute to David Weininger, 1952-2016.

David Weininger's career, accomplishments, genius, and friendship are warmly remembered by several of his colleagues, friends, and admirers.

A flexible organic resistance memory device for wearable biomedical applications.

Parylene is a Food and Drug Administration (FDA)-approved material which can be safely used within the human body and it is also offers chemically inert and flexible merits. Here, we present a flexible parylene-based organic resistive random access memory (RRAM) device suitable for wearable biomedical application. The proposed device is fabricated through standard lithography and pattern processes at room temperature, exhibiting the feasibility of integration with CMOS circuits. This organic RRAM device offers a high storage window (>10(4)), superior retention ability and immunity to disturbing. In addition, brilliant mechanical and electrical stabilities of this device are demonstrated when under harsh bending (bending cycle >500, bending radius <10 mm). Finally, the underlying mechanism for resistance switching of this kind of device is discussed, and metallic conducting filament formation and annihilation related to oxidization/redox of Al and Al anions migrating in the parylene layer can be attributed to resistance switching in this device. These advantages reveal the significant potential of parylene-based flexible RRAM devices for wearable biomedical applications.

Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity.

Memristors have been extensively studied for data storage and low-power computation applications. In this study, we show that memristors offer more than simple resistance change. Specifically, the dynamic evolutions of internal state variables allow an oxide-based memristor to exhibit Ca(2+)-like dynamics that natively encode timing information and regulate synaptic weights. Such a device can be modeled as a second-order memristor and allow the implementation of critical synaptic functions realistically using simple spike forms based solely on spike activity.

Using GBrowse 2.0 to visualize and share next-generation sequence data.

GBrowse is a mature web-based genome browser that is suitable for deployment on both public and private web sites. It supports most of genome browser features, including qualitative and quantitative (wiggle) tracks, track uploading, track sharing, interactive track configuration, semantic zooming and limited smooth track panning. As of version 2.0, GBrowse supports next-generation sequencing (NGS) data by providing for the direct display of SAM and BAM sequence alignment files. SAM/BAM tracks provide semantic zooming and support both local and remote data sources. This article provides step-by-step instructions for configuring GBrowse to display NGS data.

A novel method based on two cameras for accurate estimation of arterial oxygen saturation.

BACKGROUND: Photoplethysmographic imaging (PPGi) that is based on camera allows acquiring photoplethysmogram and measuring physiological parameters such as pulse rate, respiration rate and perfusion level. It has also shown potential for estimation of arterial oxygen saturation (SaO2). However, there are some technical limitations such as optical shunting, different camera sensitivity to different light spectra, different AC-to-DC ratios (the peak-to-peak amplitude to baseline ratio) of the PPGi signal for different portions of the sensor surface area, the low sampling rate and the inconsistency of contact force between the fingertip and camera lens. METHODS: In this paper, we take full account of the above-mentioned design challenges and present an accurate SaO2 estimation method based on two cameras. The hardware system we used consisted of an FPGA development board (XC6SLX150T-3FGG676 from Xilinx), with connected to it two commercial cameras and an SD card. The two cameras were placed back to back, one camera acquired PPGi signal from the right index fingertip under 660 nm light illumination while the other camera acquired PPGi signal from the thumb fingertip using an 800 nm light illumination. The both PPGi signals were captured simultaneously, recorded in a text file on the SD card and processed offline using MATLAB®. The calculation of SaO2 was based on the principle of pulse oximetry. The AC-to-DC ratio was acquired by the ratio of powers of AC and DC components of the PPGi signal in the time-frequency domain using the smoothed pseudo Wigner-Ville distribution. The calibration curve required for SaO2 measurement was obtained by linear regression analysis. RESULTS: The results of our estimation method from 12 subjects showed a high correlation and accuracy with those of conventional pulse oximetry for the range from 90 to 100%. CONCLUSIONS: Our method is suitable for mobile applications implemented in smartphones, which could allow SaO2 measurement in a pervasive environment.

A new bipolar RRAM selector based on anti-parallel connected diodes for crossbar applications.

Crossbar arrays are the most promising application of a resistive random access memory (RRAM) device for achieving high density memory. However, cross-talk interference in the crossbar array limits the increase in the integration density. In this paper, the combination of two anti-parallel connected diodes and a bipolar RRAM cell is proposed to suppress the sneak current in a crossbar array with anti-parallel connected diodes as the selector for the bipolar RRAM. By using the anti-parallel connected diodes as a selector, the sneak current can be effectively suppressed and the high density crossbar array of more than 1 Mb can be realized as estimated by the 1/2V read voltage scheme. These results indicate that anti-parallel connected diodes can be used as a bipolar selector and have great potential for high density bipolar RRAM crossbar array applications.

Temperature dependence of resistive switching behaviors in resistive random access memory based on graphene oxide film.

We reported resistive switching behaviors in the resistive random access memory (RRAM) devices based on the different annealing temperatures of graphene oxide (GO) film as active layers. It was found that the resistive switching characteristics of an indium tin oxide (ITO)/GO/Ag structure have a strong dependence on the annealing temperature of GO film. When the annealing temperature of the GO film was 20 °C, the devices showed typical write-once-read-many-times (WORM) type memory behaviors, which have good memory performance with a higher ON/OFF current ratio (∼10(4)), the higher the high resistance state (HRS)/low resistance state (LRS) ratio (∼10(5)) and stable retention characteristics (>10(3) s) under lower programming voltage (-1 V and -0.5 V). With the increasing annealing temperature of GO film, the resistive switching behavior of RRAM devices gradually weakened and eventually disappeared. This phenomenon could be understood by the different energy level distributions of the charge traps in GO film, and the different charge injection ability from the Ag electrode to GO film, which is caused by the different annealing temperatures of the GO film.

File formats commonly used in mass spectrometry proteomics.

The application of mass spectrometry (MS) to the analysis of proteomes has enabled the high-throughput identification and abundance measurement of hundreds to thousands of proteins per experiment. However, the formidable informatics challenge associated with analyzing MS data has required a wide variety of data file formats to encode the complex data types associated with MS workflows. These formats encompass the encoding of input instruction for instruments, output products of the instruments, and several levels of information and results used by and produced by the informatics analysis tools. A brief overview of the most common file formats in use today is presented here, along with a discussion of related topics.

The impact of tunnel oxide nitridation to reliability performance of charge storage non-volatile memory devices.

This paper is written to review the development of critical research on the overall impact of tunnel oxide nitridation (TON) with the aim to mitigate reliability issues due to incessant technology scaling of charge storage NVM devices. For more than 30 years, charge storage non-volatile memory (NVM) has been critical in the evolution of intelligent electronic devices and continuous development of integrated technologies. Technology scaling is the primary strategy implemented throughout the semiconductor industry to increase NVM density and drive down average cost per bit. In this paper, critical reliability challenges and key innovative technical mitigation methods are reviewed. TON is one of the major candidates to replace conventional oxide layer for its superior quality and reliability performance. Major advantages and caveats of key TON process techniques are discussed. The impact of TON on quality and reliability performance of charge storage NVM devices is carefully reviewed with emphasis on major advantages and drawbacks of top and bottom nitridation. Physical mechanisms attributed to charge retention and V(t) instability phenomenon are also reviewed in this paper.

Recombinant protein-based nanoscale biomemory devices.

Biomolecular computing devices that are based on the properties of biomolecular activities offer a unique possibility for constructing new computing structures. A new concept of using various biomolecules has been proposed in order to develop a protein-based memory device that is capable of switching physical properties when electrical input signals are applied to perform memory switching. To clarify the proposed concept, redox protein is immobilized on Au nanoelectrodes to catalyze reversible reactions of redox-active molecules, which is controlled electrochemically and reversibly converted between its ON/OFF states. In this review, we summarize recent research towards developing nanoscale biomemory devices including design, synthesis, fabrication, and functionalization based on the proposed concept. At first we analyze the memory function properties of the proposed device at bulk material level and then explain the WORM (write-once-read-many times) nature of the device, later we extend the analysis to multi-bit and multi-level storage functions, and then we focus the developments in nanoscale biomemory devices based on the electron transport of redox molecules to the underlying Au patterned surface. The developed device operates at very low voltages and has good stability and excellent reversibility, proving to be a promising platform for future memory devices.

Disordered self assembled monolayer dielectric induced hysteresis in organic field effect transistors.

A memory device using an organic field effect transistor (OFET) with copper phthalocyanine (CuPc) as active material was fabricated and studied. For this purpose, SiO2 dielectric surface was modified with a disordered self assembled monolayer (SAM) of octadecyltrichlorosilane (OTS) molecule which was found to induce large disorder in CuPc film thereby generating more traps for charge carriers. Drain current-drain voltage characteristics at zero gate voltage exhibited large hysteresis which was not observed in OFET devices with ordered OTS monolayer modified and unmodified SiO2 dielectrics. The extent of hysteresis and drain current on/off ratio, reading voltage etc. were found to be dependent on the sweep rate/step voltage employed during scanning. Highest hysteresis with on/off ratio of about 240 was obtained for an optimum step voltage of 2 V while it decreased with further reduction in the same. This was attributed to the longer scanning time leading to release of trapped carriers during forward scan itself. The OFET device was found to exhibit excellent memory retention capability where OFF and ON current measured for about 2 hours after stressing the device at write and erase voltages showed good retention of on/off ratio.

Resource management scheme based on ubiquitous data analysis.

Resource management of the main memory and process handler is critical to enhancing the system performance of a web server. Owing to the transaction delay time that affects incoming requests from web clients, web server systems utilize several web processes to anticipate future requests. This procedure is able to decrease the web generation time because there are enough processes to handle the incoming requests from web browsers. However, inefficient process management results in low service quality for the web server system. Proper pregenerated process mechanisms are required for dealing with the clients' requests. Unfortunately, it is difficult to predict how many requests a web server system is going to receive. If a web server system builds too many web processes, it wastes a considerable amount of memory space, and thus performance is reduced. We propose an adaptive web process manager scheme based on the analysis of web log mining. In the proposed scheme, the number of web processes is controlled through prediction of incoming requests, and accordingly, the web process management scheme consumes the least possible web transaction resources. In experiments, real web trace data were used to prove the improved performance of the proposed scheme.

Single-event-upset sensitivity analysis on low-swing drivers.

Technology scaling relies on reduced nodal capacitances and lower voltages in order to improve performance and power consumption, resulting in significant increase in layout density, thus making these submicron technologies more susceptible to soft errors. Previous analysis indicates a significant improvement in SEU tolerance of the driver when the bias current is injected into the circuit but results in increase of power dissipation. Subsequently, other alternatives are considered. The impact of transistor sizes and temperature on SEU tolerance is tested. Results indicate no significant changes in Q(crit) when the effective transistor length is increased by 10%, but there is an improvement when high temperature and high bias currents are applied. However, this is due to other process parameters that are temperature dependent, which contribute to the sharp increase in Q(crit). It is found that, with temperature, there is no clear factor that can justify the direct impact of temperature on the SEU tolerance. Thus, in order to improve the SEU tolerance, high bias currents are still considered to be the most effective method in improving the SEU sensitivity. However, good trade-off is required for the low-swing driver in order to meet the reliability target with minimal power overhead.

Ultra-low-voltage CMOS-based current bleeding mixer with high LO-RF isolation.

This journal presents an ultra-low-voltage current bleeding mixer with high LO-RF port-to-port isolation, implemented on 0.13 µm standard CMOS technology for ZigBee application. The architecture compliments a modified current bleeding topology, consisting of NMOS-based current bleeding transistor, PMOS-based switching stage, and integrated inductors achieving low-voltage operation and high LO-RF isolation. The mixer exhibits a conversion gain of 7.5 dB at the radio frequency (RF) of 2.4 GHz, an input third-order intercept point (IIP3) of 1 dBm, and a LO-RF isolation measured to 60 dB. The DC power consumption is 572 µW at supply voltage of 0.45 V, while consuming a chip area of 0.97 × 0.88 mm(2).

Evolving spiking networks with variable resistive memories.

Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in spiking neural networks. The evolutionary design process exploits parameter self-adaptation and allows the topology and synaptic weights to be evolved for each network in an autonomous manner. Variable resistive memories are the focus of this research; each synapse has its own conductance profile which modifies the plastic behaviour of the device and may be altered during evolution. These variable resistive networks are evaluated on a noisy robotic dynamic-reward scenario against two static resistive memories and a system containing standard connections only. The results indicate that the extra behavioural degrees of freedom available to the networks incorporating variable resistive memories enable them to outperform the comparative synapse types.