The rapid development of information technology has led to urgent requirements for high efficiency and ultralow power consumption. In the past few decades, neuromorphic computing has drawn extensive attention due to its promising capability in processing massive data with extremely low power consumption. Here, we offer a comprehensive review on emerging artificial neuromorphic devices and their applications. In light of the inner physical processes, we classify the devices into nine major categories and discuss their respective strengths and weaknesses. We will show that anion/cation migration-based memristive devices, phase change, and spintronic synapses have been quite mature and possess excellent stability as a memory device, yet they still suffer from challenges in weight updating linearity and symmetry. Meanwhile, the recently developed electrolyte-gated synaptic transistors have demonstrated outstanding energy efficiency, linearity, and symmetry, but their stability and scalability still need to be optimized. Other emerging synaptic structures, such as ferroelectric, metal–insulator transition based, photonic, and purely electronic devices also have limitations in some aspects, therefore leading to the need for further developing high-performance synaptic devices. Additional efforts are also demanded to enhance the functionality of artificial neurons while maintaining a relatively low cost in area and power, and it will be of significance to explore the intrinsic neuronal stochasticity in computing and optimize their driving capability, etc. Finally, by looking into the correlations between the operation mechanisms, material systems, device structures, and performance, we provide clues to future material selections, device designs, and integrations for artificial synapses and neurons.

A comprehensive review on emerging artificial neuromorphic devices

Detection and quantification of hydrogen sulfide (H2S) gas is important as it influences directly human health, our environment, and operations of several industries including food and beverages, oil, construction, and medicine. It also acts as biomarker in diagnosis of halitosis at early stage. We report herein liquid exfoliated MoSe2 nanoflakes based stable chemiresistive H2S gas sensor which operate at moderate temperature of 200℃. The response of p-type MoSe2 gas sensor device (when operated in ambient environment) was found to be varying between 15.87%–53.04% when the concentration of H2S was varied between 50 ppb – 5.45 ppm. The response of the device decreases when the measurements were done in synthetic air environment and it varies between 7.13%–19.87% for the concentration range of 500 ppb - 5.45 ppm. The response (%), recovery rate (%), hysteresis, experimental lowest detection limit etc. of the device suggest that the device performs better when operated in ambient than in synthetic air which suggest its real time device application. The response time and recovery time of the sensor are 15 s and 43 s respectively for 100 ppb of H2S. The sensor performance was found to be highly repeatable with sensitivity of 5.57%/ppm of H2S. The theoretical limit of detection and limit of quantization of the device were found to be 6.73 ppb and 22.44 ppb respectively. Based on chemical analysis, a plausible mechanism based on charge transfer phenomenon has been proposed for this sensor.

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MoSe2 nanoflakes based chemiresistive sensors for ppb-level hydrogen sulfide gas detection

1D Metal Oxide Semiconductor Materials for Chemiresistive Gas Sensors: A Review

New criterion for finite-time synchronization of fractional order memristor-based neural networks with time delay

As a typical n-type semiconductor, MoO3 has been widely applied in the gas-detection field due to its competitive physicochemical properties and ecofriendly characteristics. Volatile organic compounds (VOCs) are harmful to the atmospheric environment and human life, so it is necessary to quickly identify the presence of VOCs in the air. This review briefly introduced the application progress of an MoO3-based sensor in VOCs detection. We mainly emphasized the optimization strategies of a high performance MoO3, which consists of morphology-controlled synthesis and electronic properties functional modification. Besides the general synthesis methods, its gas-sensing properties and mechanism were briefly discussed. In conclusion, the application status of MoO3 in gas-sensing and the challenges still to be solved were summarized.

/pdf/volatile-organic-compounds-gas-sensors-based-on-molybdenum-2uso1tk723.pdf

Volatile Organic Compounds Gas Sensors Based on Molybdenum Oxides: A Mini Review.

Transformation of Moo3nanobelts into Moo3 nanofibers with high surface defect has been achieved by the application of pulsed temperature during hydrothermal growth. Moo3nanobelts and nanofibers are characterized by field emission scanning electron microscopy (FESEM), x-ray diffraction (XRD), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HR-TEM), and surface area analysis by nitrogen adsorption-desorption technique. Results clearly revealed that high crystalline, lower thickness, high surface area, and high surface defects are present in the Moo3 nanofibers as compare to Moo3 nanobelts. Furthermore, ethanol sensing properties of these M003 nanobelts and Moo3 nanofibers were examined, where Moo3 nanofibers show superior ethanol sensing properties due to the above mention advantages in Moo3 nanofibers.

Defect Control in MoO 3 Nanostructures as Ethanol Sensor

This paper presents the design of a Memristor based startup circuit for self biased circuits. Memristor has many advantages over conventional CMOS devices such as low leakage current at nanometer scale, easy to manufacture. In this work the switching characteristics of memristor is utilized. First the theoretical equations describing the switching behavior of memristor are investigated. To prove the switching capability of Memristor, a startup circuit based on memristor is proposed which uses series combination of Memristor and capacitor. Proposed circuit is compared with the previously reported MOSFET based startup circuits. Comparison of different circuits was done to validate the results. Simulation results show that memristor based circuit can attain on (I = 12.94 µA) to off state (I = 1 .2 µA) in 25 ns while the MOSFET based startup circuits take on (I = 14.19 µA) to off state (I = 1.4 µA) in more than 90 ns. The benefit comes in terms of area because the number of components used in the circuit are lesser than the conventional startup circuits.

Memristor based startup circuit for self biased circuits

In order to keep aquatic ecosystems safe and healthy, it is imperative that cleaning be done frequently. This research suggests the use of autonomous underwater rovers for effective underwater cleaning as a novel approach to this issue. The enhanced sensing and navigational capabilities of the autonomous rovers enable them to independently navigate underwater environments and find and remove underwater garbage and uneaten fish feed which can be recycled. The suggested solution not only does away with the requirement for human divers, but also provides a more effective and affordable technique for underwater cleaning. The paper also examines the creation, testing, and potential of the autonomous underwater rovers.

Underwater Autonomous Tank Cleaning Rover

AbstractA rapid rise in the complexity of designs and shrinking device dimensions has recently led to multimillion gate systems run with numerous asynchronous clocks. Traditional digital design testing and verification methods in many cases are unable to detect clock domain crossing (CDC) issues. At structural and functional level, existing methods provide an ad hoc partial verification which are erroneous and take huge time to analyze. If these source of potential error are not addressed and verified early in the design cycle, then the designs may go to silicon with functional errors. Detection of these errors in post-silicon verification is very costly in terms of time and money. Automatic tools can warrant that these multi-clock designs are corrected prior to final tape out of design. But, these tools give errors in the range of thousands if not used properly. Analysis of these reports can be very time-consuming as the number of false errors and warnings (noise) is generally huge. Manual CDC verification techniques only work well for verification but not for detection of issues. In this paper, the key optimization techniques have been reviewed which when used with the automatic tools will reduce the no of noise in analysis report. Reduction in false issues speed up verification cycle thus saving the overall cost.KeywordsMulti-clock designCDC analysis toolAsynchronous designSoCMissing clock informationReal CDC issue 

Mangal Das

Papers

Defect Control in MoO 3 Nanostructures as Ethanol Sensor

Memristor based startup circuit for self biased circuits

Underwater Autonomous Tank Cleaning Rover

Productivity Enhancement in Clock Domain Crossings Verification

Synthesis of C-V2O3 composite for electrode materials of rechargeable batteries