Efficient realization of infrared coherent radiation by the method of parametric light amplification in nonlinear photonic crystals

The process of parametric amplification of light from short laser pulses in nonlinear photonic crystals is analyzed numerically. The calculations were carried out taking into account the effects of the dispersion of the medium up to the third order and cubic nonlinearity of the Kerr type. It is shown that a change in the size of domains can significantly affect the formation of a signal wave pulse. On the basis of the results obtained, we analyzed the optimal values of the domain size at which the efficient energetic generation of the signal wave is observed.

Simple and Efficient Realization of Transverse Linear Dark Beams by Azimuthal Phase-Shifted Square Zone Plate

Herein, we are about to introduce a novel, reliable and straightforward method to create controllable dark lines employing an azimuthal square zone plate. As a matter of fact, this diffractive element is a square zone plate whose zones are phase-shifted azimuthally. As we illustrate, one way to construct it is combining a square zone plate and radial grating having period m. Considering its focusing behavior, we came to the result that a dark line surrounded by linear bright zones is generated for odd m, as well as a cross-like dark zone is produced when m is even. Furthermore, we illustrate that the length of the dark lines depends on the grating period. Finally, the simulation predictions are verified by experimental results.

Utilizing the Switching Stochasticity of HfO2/TiOx-Based ReRAM Devices and the Concept of Multiple Device Synapses for the Classification of Overlapping and Noisy Patterns

With the arrival of the Internet of Things (IoT) and the challenges arising from Big Data, neuromorphic chip concepts are seen as key solutions for coping with the massive amount of unstructured data streams by moving the computation closer to the sensors, the so-called “edge computing.” Augmenting these chips with emerging memory technologies enables these edge devices with non-volatile and adaptive properties which are desirable for low power and online learning operations. However, an energy- and area-efficient realization of these systems requires disruptive hardware changes. Memristor-based solutions for these concepts are in the focus of research and industry due to their low-power and high-density online learning potential. Specifically, the filamentary-type valence change mechanism (VCM memories) have shown to be a promising candidate In consequence, physical models capturing a broad spectrum of experimentally observed features such as the pronounced cycle-to-cycle (c2c) and device-to-device (d2d) variability are required for accurate evaluation of the proposed concepts. In this study, we present an in-depth experimental analysis of d2d and c2c variability of filamentary-type bipolar switching HfO2/TiOx nano-sized crossbar devices and match the experimentally observed variabilities to our physically motivated JART VCM compact model. Based on this approach, we evaluate the concept of parallel operation of devices as a synapse both experimentally and theoretically. These parallel synapses form a synaptic array which is at the core of neuromorphic chips. We exploit the c2c variability of these devices for stochastic online learning which has shown to increase the effective bit precision of the devices. Finally, we demonstrate that stochastic switching features for a pattern classification task that can be employed in an online learning neural network.

Additive Manufacturing: Post Processing Methods and Challenges

Additive Manufacturing (AM) has shown great potential for efficient realization of complicated microdevices fabricated with higher freedom of design and made from a wide variety of materials suiting to their specific target functionalities. Capability of generation of components with reduced weights, higher part consolidation, greater customization offered along with minimal waste generation are its advantages over conventional manufacturing processes. The AM built parts, however, need to undergo relevant post processing techniques to render them fit for their end product application. The paper attempts to classify the post processing techniques and emphasize their applicability to specific AM methods, generalized procedure as well as the recent improvements undergone. The post processing techniques have been categorised as methods for support material removal, surface texture improvements, thermal and non-thermal post processing and aesthetic improvements. The main challenges to the expansion of additive manufacturing have been discussed which highlight the future, scope of improvement and research required in the area of appropriate tool path development and product quality with regards to surface roughness, resolution and porosity levels in the built part.