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arXiv2019

Negative Capacitance Ion-Sensitive Field-Effect Transistors with improved current sensitivity

Ion-Sensitive Field-Effect Transistors (ISFETs) form a wide-spread technology for sensing, thanks to their label-free detection and intrinsic CMOS compatibility. Their current sensitivity, ΔID/ID, for a given ΔpH, however, is limited by the thermionic limit for the Subthreshold Slope (SS) of Metal-Oxide-Semiconductor Field-Effect Transistors(MOSFET) and by the Nernst limit. Obtaining ISFETs with a steep slope transfer characteristics is extremely challenging. In this paper we combine the merits of traditional ISFETs with the performance boosts offered by the insertion of a Negative Capacitor in series with the Gate contact. In the proposed tests with NC PZT capacitors, we demonstrate experimentally a reduction of the SS by 44%, combined with a current efficiency improvement of more than two times. As a consequence of the steeper SS, the current sensitivity to pH is improved by 78%.

physics.ins-det↗

arXiv2019

Broadband ultra-thin acoustic metasurface absorber

We theoretically and experimentally propose two designs of broadband low-frequency acoustic metasurface absorbers (Sample I/Sample II) for the frequency ranges of 458Hz~968Hz and 231Hz~491Hz (larger than 1 octave), with absorption larger than 0.8, and having the ultra-thin thickness of 5.2cm and 10.4cm respectively (λ/15 for the lowest working frequency and λ/7.5 for the highest frequency). The designed supercell consists of 16 different unit cells corresponding to 16 eigen frequencies for resonant absorptions. The coupling of multiple resonances leads to broadband absorption effect in the full range of the targeted frequency spectrum. In particular, we propose to combine gradient-change channel and coiled structure to achieve simultaneous impedance matching and minimal occupied space, leading to the ultra-thin thickness of the metasurface absorbers. Our conceived ultra-thin low-frequency broadband absorbers may lead to pragmatic implementations and applications in noise control field.

physics.app-ph↗

arXiv2019

Apparent Spatial Memory Register and Oscillating Shape Transformations in Gold Nanostructures

Nano structures, namely, nano rings and nanoparticles, comprising two dimensional, crystalline gold atomic discs were produced on a sapphire substrate. Nano rings revealed several remarkable properties, namely, an apparent spatial orientation memory register, an apparent programmed homing instinct and action based on that instinct, usually observed only in living, biological systems. Momentary application of 100 nN force on a nanostructure, mother led every mother within the entire scanner area to increase its volume and create several daughter replicas. Over time, without the influence of any applied external force or stimulus, each daughter, of its own volition, transported itself back to its mother and recreated its original form. The results strongly implied temporal and spatial synchronization between the daughters and their respective mothers. The targeted movement of the daughters towards their mothers implied the existence of a special, yet unidentified new force. Momentary application of a weak force on a gold nanoparticle resulted in the spontaneous transformation of each nanoparticle into a complex and robot like Dalek 3dimensional form. Without the application of any additional external force or stimulus, we observed a remarkable display of oscillatory transformation between the robot-like forms and their mother nanoparticles lasting over 26 hours. The robot-like structures seem to replicate identical copies of themselves.

physics.app-ph↗

arXiv2019

Demonstration of a-Si metalenses on a 12-inch glass wafer by CMOS-compatible technology

Metalenses built up by artificial sub-wavelength nanostructures have shown the capability of realizing light focusing with miniature lens size. To date, most of the reported metalenses were patterned using electron beam lithography (EBL), which requires long processing time and is not suitable for mass production. Here, we demonstrate an amorphous silicon (a-Si) metalens on a 12-inch glass wafer via the 193 nm ArF deep UV immersion lithography, with critical dimension (CD) as small as 100 nm. The layer transfer technology is developed to solve the glass wafer handling issue in complementary metal-oxide-semiconductor (CMOS) fabrication line. The measured numerical aperture (NA) is 0.494 with a beam spot size of 1.26 μm, which agrees well with the simulation results. The focusing efficiency of 29.2% is observed at the designed wavelength of 940 nm. In addition, the metalens is applied in an imaging system, which further verifies its focusing functionality.

physics.app-ph↗

arXiv2019

Ultra-Compact Coupling Structures for Heterogeneously Integrated Silicon Lasers

Due to the inherent in-direct bandgap nature of Silicon, heterogeneous integration of semiconductor lasers on Silicon on Insulator (SOI) is crucial for next-generation on-chip optical interconnects. Compact, high-efficient and high-tolerant couplers between III-V light source and silicon chips have been the challenge for photonic integrated circuit (PIC). Here, we redesign the taper adiabatic coupler with the total coupling length of only 4 μm, and propose another two novel slot coupler and bridge-SWG coupler with both coupling length of 7 μm, to heterogeneously integrate III-V lasers and silicon chips. We study theoretically the optical mode coupling process through the redesigned taper coupler, the final coupling results match well with the simulation in 3D-FDTD. The three compact couplers represent fundamental TE mode coupling efficiencies all over 90%, even 95.7% for bridge-SWG coupler, to the best of our knowledge, are also the shortest coupling structures (7 um). Moreover, these coupling structures also possess excellent fabrication tolerance.

physics.optics↗

arXiv2019

4K-Memristor Analog-Grade Passive Crossbar Circuit

The superior density of passive analog-grade memristive crossbars may enable storing large synaptic weight matrices directly on specialized neuromorphic chips, thus avoiding costly off-chip communication. To ensure efficient use of such crossbars in neuromorphic computing circuits, variations of current-voltage characteristics of crosspoint devices must be substantially lower than those of memory cells with select transistors. Apparently, this requirement explains why there were so few demonstrations of neuromorphic system prototypes using passive crossbars. Here we report a 64x64 passive metal-oxide memristor crossbar circuit with ~99% device yield, based on a foundry-compatible fabrication process featuring etch-down patterning and low-temperature budget, conducive to vertical integration. The achieved ~26% variations of switching voltages of our devices were sufficient for programming 4K-pixel gray-scale patterns with an average tuning error smaller than 4%. The analog properties were further verified by experimentally demonstrating MNIST pattern classification with a fidelity close to the software-modeled limit for a network of this size, with an ~1% average error of import of ex-situ-calculated synaptic weights. We believe that our work is a significant improvement over the state-of-the-art passive crossbar memories in both complexity and analog properties.

cs.ET↗

arXiv2019

Fano-like spectral features in nanodiamond solutions for biometric applications

Fano resonance is a unique feature of interacting quantum systems, exhibiting resonance shapes distinctively different from conventional symmetric resonance curves. Recently, Fano resonances have been found in plasmonic nanoparticles, photonic crystals, and electromagnetic metamaterials. Here we report Fano-like photoluminiscence curves in nanodiamond solutions as a result of incoherent combination of two or more scattering and fluorescence processes. We argue that, analogously to Fano resonances, the steep asymmetric dispersion of the photoluminiscence profile in nanodiamond solutions, in combination with biologically-compatible spectral features characterizing nanodiamond fluorescence, can find promising biometric applications in several areas such as bio-sensors, bio-switches and bio-filters.

physics.app-ph↗

arXiv2019

Modeling the Generic Breakthrough Curve for Adsorption Process

This work is aimed at understanding the basic principles of adsorption process in great details as adsorptive separation process has broad applications in the industry. To this end, a simple mathematical model has been used to describe transient fixed bed physical adsorption process. Governing equations are solved numerically to obtain breakthrough curves for single component and multi-component monolayer adsorption. Desorption of a saturated bed by an inert fluid is also considered. A full parametric study is performed to analyze the effects of different parameters such as bed length, velocity, diffusivity, particle radius and isotherm properties on the nature of the breakthrough curve. Analysis of these results led to the development of the generic breakthrough curve for a single component monolayer adsorption which will enable us to tell the nature of breakthrough curve for different process parameters without recourse to the numerical simulation or experiment. Thus this study will be of great interest in the industrial separation process.

physics.app-ph↗

arXiv2019

Process Verification of Magnetic Ion Embedded Nanodiamonds Using Secondary Ion Mass Spectroscopy

Ion implantation is used to create magnetic ion embedded nanodiamonds for use in a wide range of biological and medical applications; however, the effectiveness of this process depends heavily on separating magnetic nanodiamonds from non-magnetic ones. In this study, we use secondary ion mass spectrometry to assess the distribution of magnetic ions and verify the success of separation. When applied to a series of iron/manganese embedded nanodiamonds, the sorting tool used in this study proved highly effective in selecting magnetic nanodiamonds. This paper also discusses the major challenges involved in the further development of this technology.

physics.app-ph↗

arXiv2019

Mapping electromagnetic fields structure in plasma using a spin polarized electron beam

We propose a scheme to mapping electromagnetic fields structure in plasma by using a spin polarized relativistic electron beam. Especially by using Particle-in-Cell (PIC) and electron spin tracing simulations, we have successfully reconstructed a plasma wakefield from the spin evolution of a transmitted electron beam. Electron trajectories of the probe beam are obtained from PIC simulations, and the spin evolutions during the beam propagating through the fields are calculated by a spin tracing code. The reconstructed fields illustrate the main characters of the original fields, which demonstrates the feasibility of fields detection by use of spin polarized relativistic electron beams.

physics.plasm-ph↗

arXiv2019

Cryogenic Memory Architecture Integrating Spin Hall Effect based Magnetic Memory and Superconductive Cryotron Devices

One of the most challenging obstacles to realizing exascale computing is minimizing the energy consumption of L2 cache, main memory, and interconnects to that memory. For promising cryogenic computing schemes utilizing Josephson junction superconducting logic, this obstacle is exacerbated by the cryogenic system requirements that expose the technology's lack of high-density, high-speed and power-efficient memory. Here we demonstrate an array of cryogenic memory cells consisting of a non-volatile three-terminal magnetic tunnel junction element driven by the spin Hall effect, combined with a superconducting heater-cryotron bit-select element. The write energy of these memory elements is roughly 8 pJ with a bit-select element, designed to achieve a minimum overhead power consumption of about 30%. Individual magnetic memory cells measured at 4 K show reliable switching with write error rates below $10^{-6}$, and a 4x4 array can be fully addressed with bit select error rates of $10^{-6}$. This demonstration is a first step towards a full cryogenic memory architecture targeting energy and performance specifications appropriate for applications in superconducting high performance and quantum computing control systems, which require significant memory resources operating at 4 K.

physics.app-ph↗

arXiv2019

Continuous Fourier Transform: A practical approach for truncated signals and suggestions for improvements in thermography

The fundamentals of Fourier Transform are presented, with analytical solutions derived for Continuous Fourier Transform (CFT) of truncated signals, to benchmark against Fast Fourier Transform (FFT). Certain artifacts from FFT were identified for decay curves. An existing method for Infrared Thermography, Pulse Phase Thermography (PPT), was benchmarked against a proposed method using polynomial fitting with CFT, to analyse cooling curves for defect identification in Non-Destructive Testing (NDT). Existing FFT methods used in PPT were shown to be dependent on sampling rates, with inherent artifacts and inconsistencies in both amplitude and phase. It was shown that the proposed method produced consistent amplitude and phase, with no artifacts, as long as the start of the cooling curves are sufficiently represented. It is hoped that a collaborative approach will be adopted to unify data in Thermography for machine learning models to thrive, in order to facilitate automated geometry and defect recognition and move the field forward.

physics.app-ph↗

arXiv2019

Enhanced low-flux sensitivity (ELFS) effect of neutron-induced displacement damage in bipolar devices: physical mechanism and parametric model

Similar to the enhanced low-dose-rate sensitivity (ELDRS) effect of ionization damage, an enhanced low-flux senstivity (ELFS) effect has been reported in ions/neutron irradiation on n-type silicon or PNP transistors. However, the existing mechanism and simulation dominated by the diffusion dynamics give much higher transition flux than the experimental observations. In this work, we develop a new model based on the annealing of defect clusters for the ELFS effect. Simulations considering Si-interstitial-mediated inter-cluster interactions during their annealing processes successfully reproduce the ELFS effect. The ratio of Si interstitials captured by defect clusters to those dissipating off on the sample edges or re-merging into the bulk is found as the key parameter dominating the enhancement factor (EF) of the ELFS effect. We also establish a compact parametric model based on the mechanism, which is found to provide a good quantitative description of the experimental results. The model predicts the existence of nonsensitive regions at sufficiently low and high fluxes as well as a non-trivial fluence and temperature dependence of the enhancement factor.

physics.space-ph↗

arXiv2019

High-flux dual-phase percolation membrane for oxygen separation

A series of composites based on (100-x)wt.%Ce0.9Pr0.1O2-δ-xwt.%Pr0.6Ca0.4FeO3-δ (x = 25, 40 and 50) doped with the cheap and abundant alkaline earth metal Ca2+ at the A-site has been successfully designed and fabricated. The crystal structure, oxygen permeability, phase and CO2 stability were evaluated. The composition of 60wt.%Ce0.9Pr0.1O2-δ-40wt.%Pr0.6Ca0.4FeO3-δ(60CPO-40PCFO) possesses the highest oxygen permeability among three studied composites. At 1000 oC, the oxygen permeation fluxes through the 0.3 mm-thickness 60CPO-40PCFO membranes after porous La0.6Sr0.4CoO3-δ each to 1.00 mL cm-2 min-1 and 0.62 mL cm-2 min-1 under air/He and air/CO2 gradients, respectively. In situ XRD results demonstrated that the 60CPO-40PCFO sample displayed a perfect structural stability in air as well as CO2-containing atmosphere. Thus, low-cost, Co-free and Sr-free 60CPO-40PCFO has high CO2 stability and is economical and environmental friendly since the expensive and volatile element Co was replaced by Fe and Sr was waived since it easily forms carbonates.

physics.app-ph↗

arXiv2019

Equivalent Circuit Model Recognition of Electrochemical Impedance Spectroscopy via Machine Learning

Electrochemical impedance spectroscopy (EIS) is an effective method for studying the electrochemical systems. The interpretation of EIS is the biggest challenge in this technology, which requires reasonable modeling. However, the modeling of EIS is of great subjectivity, meaning that there may be several models to fit the same set of data. In order to overcome the uncertainty and triviality of human analysis, this research uses machine learning to carry out EIS pattern recognition. Raw EIS data and their equivalent circuit models were collected from the literature, and the support vector machine (SVM) was used to analyze these data. As the result, we addresses the classification of EIS and recognizing their equivalent circuit models with accuracies of up to 78%. This study demonstrates the great potential of machine learning in electrochemical researches.

physics.data-an↗

arXiv2019

Thick adherent diamond films on AlN with low thermal barrier resistance

Growth of $>$100 $μ$m thick diamond layer adherent on aluminium nitride is presented in this work. While thick films failed to adhere on untreated AlN films, hydrogen/nitrogen plasma treated AlN films retained the thick diamond layers. Clear differences in zeta potential measurement confirms the surface modification due to hydrogen/nitrogen plasma treatment. Areal Raman maps showed an increase in non-diamond carbon in the initial layers of diamond grown on pre-treated AlN. The presence of non-diamond carbon has minimal effect on the interface between diamond and AlN. The surfaces studied with x-ray photoelectron spectroscopy (XPS) revealed a clear distinction between pre-treated and untreated samples. The surface aluminium goes from nitrogen rich environment to an oxygen rich environment after pre-treatment. Cross section transmission electron microscopy shows a clean interface between diamond and AlN. Thermal barrier resistance between diamond and AlN was found to be in the range of 16 m$^2$K/GW which is a large improvement on the current state-of-the-art.

physics.app-ph↗

arXiv2019

Asymptotic reduction, solution, and homogenisation of a thermo-electrochemical model for a lithium-ion battery

We study two thermo-electrochemical models for lithium-ion batteries. The first is based on volume averaging the electrode microstructure whereas the second is based on the pseudo-two-dimensional (P2D) approach which treats the electrode as a collection of spherical particles. A scaling analysis is used to reduce the volume-averaged model and show that the electrochemical reactions are the dominant source of heat. Matched asymptotic expansions are used to compute solutions of the volume-averaged model for the cases of constant applied current, oscillating applied current, and constant cell potential. The asymptotic and numerical solutions of the volume-averaged model are in remarkable agreement with numerical solutions of the thermal P2D model for (dis)charge rates up to 2C, and reasonable agreement is found at 4C. Homogenisation is then used to derive a thermal model for a battery consisting of several connected lithium-ion cells. Despite accounting for the Arrhenius dependence of the reaction coefficients, we show that thermal runaway does not occur in the model. Instead, the cell potential is simply pushed closer to the open-circuit potential. We also show that in many cases, the homogenised battery model can be solved analytically, making it ideal for use in on-board thermal management systems.

physics.app-ph↗

arXiv2019

Double Input Boost/Y-Source DC-DC Converter for Renewable Energy Sources

With the increasing adoption of renewable energy sources by domestic users, decentralisation of the grid is fast becoming a reality. Distributed generation is an important part of a decentralised grid. This approach employs several small-scale technologies to produce electrical energy close to the end users or consumers. The higher reliability of these systems proves to be of advantage when compared to traditional generation systems. Multi-Input Converters (MICs) perform a decisive function in Distributed Energy Resources (DERs). Making use of such MICs prove to be beneficial in terms of size, cost, number of components used, efficiency and reliability as compared to using several independent converters. This thesis proposes a double input DC-DC converter which makes use of a quasi Y-source converter in tandem with a boost converter. The quasi Y-source converter has the advantage of having a very high gain for low duty cycles. The associated operating modes are analysed and the operation of the MIC is verified using simulation result. A hardware prototype is built for large signal analysis in open loop. Different loads are applied and the efficiency of the MIC as a whole as well as the load sharing between the different sources is investigated.

eess.SY↗