Anbarasu Manivannan

Bio: Anbarasu Manivannan is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Phase-change memory & Amorphous solid. The author has an hindex of 8, co-authored 35 publications receiving 182 citations. Previous affiliations of Anbarasu Manivannan include Indian Institute of Technology Indore.

Redefining the Speed Limit of Phase Change Memory Revealed by Time-resolved Steep Threshold-Switching Dynamics of AgInSbTe Devices.

Abstract: Although phase-change memory (PCM) offers promising features for a ‘universal memory’ owing to high-speed and non-volatility, achieving fast electrical switching remains a key challenge. In this work, a correlation between the rate of applied voltage and the dynamics of threshold-switching is investigated at picosecond-timescale. A distinct characteristic feature of enabling a rapid threshold-switching at a critical voltage known as the threshold voltage as validated by an instantaneous response of steep current rise from an amorphous off to on state is achieved within 250 picoseconds and this is followed by a slower current rise leading to crystallization. Also, we demonstrate that the extraordinary nature of threshold-switching dynamics in AgInSbTe cells is independent to the rate of applied voltage unlike other chalcogenide-based phase change materials exhibiting the voltage dependent transient switching characteristics. Furthermore, numerical solutions of time-dependent conduction process validate the experimental results, which reveal the electronic nature of threshold-switching. These findings of steep threshold-switching of ‘sub-50 ps delay time’, opens up a new way for achieving high-speed non-volatile memory for mainstream computing.

Low power ovonic threshold switching characteristics of thin GeTe6 films using conductive atomic force microscopy

Abstract: Minimizing the dimensions of the electrode could directly impact the energy-efficient threshold switching and programming characteristics of phase change memory devices. A ∼12–15 nm AFM probe-tip was employed as one of the electrodes for a systematic study of threshold switching of as-deposited amorphous GeTe6 thin films. This configuration enables low power threshold switching with an extremely low steady state current in the on state of 6–8 nA. Analysis of over 48 different probe locations on the sample reveals a stable Ovonic threshold switching behavior at threshold voltage, VTH of 2.4 ± 0.5 V and the off state was retained below a holding voltage, VH of 0.6 ± 0.1 V. All these probe locations exhibit repeatable on-off transitions for more than 175 pulses at each location. Furthermore, by utilizing longer biasing voltages while scanning, a plausible nano-scale control over the phase change behavior from as-deposited amorphous to crystalline phase was studied.

Exploring ultrafast threshold switching in In3SbTe2 phase change memory devices.

Abstract: Phase change memory (PCM) offers remarkable features such as high-speed and non-volatility for universal memory. Yet, simultaneously achieving better thermal stability and fast switching remains a key challenge. Thus, exploring novel materials with improved characteristics is of utmost importance. We report here, a unique property-portfolio of high thermal stability and picosecond threshold switching characteristics in In3SbTe2 (IST) PCM devices. Our experimental findings reveal an improved thermal stability of amorphous IST compared to most other phase change materials. Furthermore, voltage dependent threshold switching and current-voltage characteristics corroborate an extremely fast, yet low electric field threshold switching operation within an exceptionally small delay time of less than 50 picoseconds. The combination of low electric field and high speed switching with improved thermal stability of IST makes the material attractive for next-generation high-speed, non-volatile memory applications.

Local structure of amorphous Ag5In5Sb60Te30 and In3SbTe2 phase change materials revealed by X-ray photoelectron and Raman spectroscopic studies

Abstract: Reversible switching between highly resistive (binary “0”) amorphous phase and low resistive (binary “1”) crystalline phase of chalcogenide-based Phase Change Materials is accredited for the development of next generation high-speed, non-volatile, data storage applications. The doped Sb-Te based materials have shown enhanced electrical/optical properties, compared to Ge-Sb-Te family for high-speed memory devices. We report here the local atomic structure of as-deposited amorphous Ag5In5Sb60Te30 (AIST) and In3SbTe2 (IST) phase change materials using X-ray photoelectron and Raman spectroscopic studies. Although AIST and IST materials show identical crystallization behavior, they differ distinctly in their crystallization temperatures. Our experimental results demonstrate that the local environment of In remains identical in the amorphous phase of both AIST and IST material, irrespective of its atomic fraction. In bonds with Sb (∼44%) and Te (∼56%), thereby forming the primary matrix in IST with a very few Sb-Te bonds. Sb2Te constructs the base matrix for AIST (∼63%) along with few Sb-Sb bonds. Furthermore, an interesting assimilation of the role of small-scale dopants such as Ag and In in AIST, reveals rare bonds between themselves, while showing selective substitution in the vicinity of Sb and Te. This results in increased electronegativity difference, and consequently, the bond strength is recognized as the factor rendering stability in amorphous AIST.

Classification of epileptic seizures in EEG signals based on phase space representation of intrinsic mode functions

Abstract: We propose new features for classification of epileptic seizure EEG signals.Features were extracted from PSR of IMFs of EEG signals.We define ellipse area of 2D PSR and IQR of Euclidian distance of 3D PSR as features.LS-SVM classifier has been used for classification with the proposed features.Results were compared with other existing methods studied on the same EEG dataset. Epileptic seizure is the most common disorder of human brain, which is generally detected from electroencephalogram (EEG) signals. In this paper, we have proposed the new features based on the phase space representation (PSR) for classification of epileptic seizure and seizure-free EEG signals. The EEG signals are firstly decomposed using empirical mode decomposition (EMD) and phase space has been reconstructed for obtained intrinsic mode functions (IMFs). For the purpose of classification of epileptic seizure and seizure-free EEG signals, two-dimensional (2D) and three-dimensional (3D) PSRs have been used. New features based on the 2D and 3D PSRs of IMFs have been proposed for classification of epileptic seizure and seizure-free EEG signals. Two measures have been defined namely, 95% confidence ellipse area for 2D PSR and interquartile range (IQR) of the Euclidian distances for 3D PSR of IMFs of EEG signals. These measured parameters show significant difference between epileptic seizure and seizure-free EEG signals. The combination of these measured parameters for different IMFs has been utilized to form the feature set for classification of epileptic seizure EEG signals. Least squares support vector machine (LS-SVM) has been employed for classification of epileptic seizure and seizure-free EEG signals, and its classification performance has been evaluated using different kernels namely, radial basis function (RBF), Mexican hat wavelet and Morlet wavelet kernels. Simulation results with various performance parameters of classifier, have been included to show the effectiveness of the proposed method for classification of epileptic seizure and seizure-free EEG signals.

Te-based chalcogenide materials for selector applications.

Abstract: The implementation of dense, one-selector one-resistor (1S1R), resistive switching memory arrays, can be achieved with an appropriate selector for correct information storage and retrieval. Ovonic threshold switches (OTS) based on chalcogenide materials are a strong candidate, but their low thermal stability is one of the key factors that prevents rapid adoption by emerging resistive switching memory technologies. A previously developed map for phase change materials is expanded and improved for OTS materials. Selected materials from different areas of the map, belonging to binary Ge-Te and Si-Te systems, are explored. Several routes, including Si doping and reduction of Te amount, are used to increase the crystallization temperature. Selector devices, with areas as small as 55 × 55 nm2, were electrically assessed. Sub-threshold conduction models, based on Poole-Frenkel conduction mechanism, are applied to fresh samples in order to extract as-processed material parameters, such as trap height and density of defects, tailoring of which could be an important element for designing a suitable OTS material. Finally, a glass transition temperature estimation model is applied to Te-based materials in order to predict materials that might have the required thermal stability. A lower average number of p-electrons is correlated with a good thermal stability.

Enhancing CexZr1–xO2 Activity for Methane Dry Reforming Using Subsurface Ni Dopants

Abstract: CeO2–ZrO2 (CZO) nanoparticles (NPs) have applications in many catalytic reactions, such as methane dry reforming, due to their oxygen cycling ability. Ni doping has been shown to improve the cataly...