Angeliki Pantazi

Stochastic phase-change neurons

Artificial neuromorphic systems based on populations of spiking neurons are an indispensable tool in understanding the human brain and in constructing neuromimetic computational systems. To reach areal and power efficiencies comparable to those seen in biological systems, electroionics-based and phase-change-based memristive devices have been explored as nanoscale counterparts of synapses. However, progress on scalable realizations of neurons has so far been limited. Here, we show that chalcogenide-based phase-change materials can be used to create an artificial neuron in which the membrane potential is represented by the phase configuration of the nanoscale phase-change device. By exploiting the physics of reversible amorphous-to-crystal phase transitions, we show that the temporal integration of postsynaptic potentials can be achieved on a nanosecond timescale. Moreover, we show that this is inherently stochastic because of the melt-quench-induced reconfiguration of the atomic structure occurring when the neuron is reset. We demonstrate the use of these phase-change neurons, and their populations, in the detection of temporal correlations in parallel data streams and in sub-Nyquist representation of high-bandwidth signals.

High-speed multiresolution scanning probe microscopy based on Lissajous scan trajectories

A novel scan trajectory for high-speed scanning probe microscopy is presented in which the probe follows a two-dimensional Lissajous pattern. The Lissajous pattern is generated by actuating the scanner with two single-tone harmonic waveforms of constant frequency and amplitude. Owing to the extremely narrow frequency spectrum, high imaging speeds can be achieved without exciting the unwanted resonant modes of the scanner and without increasing the sensitivity of the feedback loop to the measurement noise. The trajectory also enables rapid multiresolution imaging, providing a preview of the scanned area in a fraction of the overall scan time. We present a procedure for tuning the spatial and the temporal resolution of Lissajous trajectories and show experimental results obtained on a custom-built atomic force microscope (AFM). Real-time AFM imaging with a frame rate of 1 frame s⁻¹ is demonstrated.

Control of MEMS-Based Scanning-Probe Data-Storage Devices

Micro-electro-mechanical-system (MEMS)-based scanning-probe data-storage devices are emerging as potential ultra-high-density, low-access-time, and low-power alternative to conventional data storage. Nanoscale accuracy and short latency in the navigation of the probes are the primary control challenges in probe-storage applications. This paper focuses on the control design to address these challenges in a probe-based storage prototype using a micro-scanner as the nanopositioner for the storage medium. Experimental results demonstrate remarkably short seek times on the order of 1 ms for the worst-case seek operations. Moreover, a thermal-sensor-based approach is compared with a two-sensor-control configuration employing both the global-position information from the thermal sensors and the medium-derived position information. Drift and low-frequency noise can affect the performance of the thermal-sensor-based control scheme over long periods of operation. This is addressed by the second scheme, a novel control architecture based on the Hinfin control framework that uses the best measurement in each of the frequency regions.

Achieving Subnanometer Precision in a MEMS-Based Storage Device During Self-Servo Write Process

In probe-based data storage devices, microelectromechanical system-based microscanners are typically used to position the storage medium relative to the read/write probes. Global position sensors are employed to provide position information across the full scan range of these microscanners. However, to achieve repeatable positioning, it is also necessary to have medium-derived position information. Dedicated storage fields known as servo fields are employed to obtain this medium-derived position information. The servo-patterns on these servo fields have to be written using the global position sensors prior to the regular operation of the storage device by employing a scheme known as ldquoself-servo writerdquo process. During this process, subnanometer positioning resolutions, well below that provided by the global position sensors, are desirable. Such precise positioning at acceptable bandwidth requires the directed design of the closed-loop noise sensitivity transfer function so as to minimize the impact of sensing noise. This paper describes control architectures in which the impact of measurement noise on positioning is minimal while providing satisfactory tracking performance. It is estimated that the positioning error due to sensing noise is a remarkably low 0.25 nm. Experimental results are also presented that show error-free operation of the device at high densities.

A servomechanism for a micro-electro-mechanical-system-based scanning-probe data storage device

Micro-electro-mechanical-system (MEMS)-based scanning-probe data storage devices are emerging as potential ultra-high-density, low-access-time, and low-power alternatives to conventional data storage. One implementation of probe-based storage uses thermomechanical means to store and retrieve information in thin polymer films. One of the challenges in building such devices is the extreme accuracy and the short latency required in the navigation of the probes over the polymer medium. This paper focuses on the design and characterization of a servomechanism to achieve such accurate positioning in a probe-based storage prototype. In our device, the polymer medium is positioned on a MEMS scanner with x/y-motion capabilities of about 100 µm. The device also includes thermal position sensors that provide x/y-position information to the servo controller. Based on a discrete state-space model of the scanner dynamics, a controller is designed using the linear quadratic Gaussian approach with state estimation. The random seek performance of this approach is evaluated and compared with that of the conventional proportional, integrator, and derivative (PID) approach. The results demonstrate the superiority of the state-space approach, which achieves seek times of about 4 ms in a ± 50 µm range. Finally, the experimental results show that closed-loop track following using the thermal position-sensor signals is feasible and yields a position-error standard deviation of approximately 2 nm.

Non-resistance-based cell-state metric for phase-change memory

In phase-change memory (PCM), low-field electrical resistance is typically used to quantify the programmed cell state. However, this metric has several disadvantages. First, it exhibits temporal drift, which is a significant challenge for realizing multilevel PCM. Moreover, because of cell-geometry effects, this metric saturates after a certain point and thus masks the fact that the amorphous size increases with increasing input power. Finally, the resistance is typically measured as the current for a fixed bias voltage, which adversely affects the signal-to-noise ratio at high resistance values. A new metric for the programmed state in a PCM cell is proposed that has significant advantages over the resistance metric in all these aspects and is more representative of the fundamental programmed entity, which is the amorphous/crystalline phase configuration in the PCM cell. Analytical and experimental results are presented that demonstrate the efficacy of the proposed metric.

Nanopositioning for probe-based data storage [Applications of Control]

Probe-based data-storage devices are being considered as an ultra-high-density, small- form-factor alternative to conventional data storage. The probe-based data-storage concept is derived from scanning-probe microscopy, where nanometer-sharp tips are used to interrogate and manipulate matter down to the atomic scale. One implementation of this concept is based on a thermomechanical principle for storing and retrieving data encoded as nanometer-scale indentations in thin polymer films. Ultra-high densities of more than 1 Tb/in2 have been achieved with this scheme. A small-scaleprototype system comprising all of the elements of a probe- based data storage device has been developed. One of the key challenges is the positioning of the storage medium relative to the read/write probes with nanometer-scale accuracy. A microscanner with X/Y motion capability is used to position the storage medium. Position information along both scan directions is provided by a pair of thermal position sensors. In addition, medium-derived position information provides a measure of the cross-track deviations in the Y-scan direction. Control architectures for both scan directions are presented. The X control architecture relies on thermal position sensors alone, whereas the Y control architecture relies on both the thermal position sensors and the medium-derived PES. Nanometer-scale positioning accuracies are achieved over a bandwidth of a few hundred hertz. Read/write demonstrations with sufficiently low error rates demonstrate the efficacy of the nanopositioning schemes employed.

Dual-Stage Nanopositioning for High-Speed Scanning Probe Microscopy

This paper presents a dual-stage approach to nanopositioning in which the tradeoff between the scanner speed and range is addressed by combining a slow, large-range scanner with a short-range scanner optimized for high-speed, high-resolution positioning. We present the design, finite-element simulations, and experimental characterization of a fast custom-built short-range scanner. The short-range scanner is based on electromagnetic actuation to provide high linearity, has a clean, high-bandwidth dynamical response and is equipped with a low-noise magnetoresistance-based sensor. By using advanced noise-resilient feedback controllers, the dual-stage system allows large-range positioning with subnanometer closed-loop resolution over a wide bandwidth. Experimental results are presented in which the dual-stage scanner system is used for imaging in a custom-built atomic force microscope.

All-memristive neuromorphic computing with level-tuned neurons

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

Servo-Pattern Design and Track-Following Control for Nanometer Head Positioning on Flexible Tape Media

Achieving multi-Terabyte capacity in tape cartridges requires a substantially higher track density than that available in present systems, and hence a significantly higher positioning accuracy is required of the track-following servo in tape drives. In this paper, advanced concepts are considered for several elements of a tape system that enhance the track-following servo performance to reach nanometer positioning accuracy. We introduce a novel method for optimizing the geometry of servo patterns in a timing-based servo system. The design criterion aims to minimize the measurement error in the position-error signal (PES) yielded by a digital synchronous servo channel. A flangeless tape path is adopted to mitigate high-frequency components of the lateral tape motion. The track-following servo controller, which is designed based on the H∞ approach, takes into account the measured plant transfer function, the disturbance characteristics of the tape path, and the properties of servo channel. These elements are combined to investigate the track-following performance achievable with a new high-SNR magnetic tape based on perpendicularly-oriented BaFe particles. With this setup, a record closed-loop track-following performance of less than 14 nm PES standard deviation is demonstrated.