Effect of a Herringbone Mesostructure on the Electromechanical Properties of Piezofiber Composites for Energy Harvesting Applications

Piezoelectric materials are often used in energy harvesting devices that convert the waste mechanical energy into effective electrical energy. Polymer-based piezoelectric composites appear to be promising candidates for use in these devices, as they offer a number of advantages, such as sufficient flexibility and environmental compatibility. However, a major drawback associated with these composites may be that their effective electromechanical properties are usually weaker than those of the piezoelectric constituents used in them. In this paper, we propose a class of polymeric-based piezoelectric composites with a laminated mesostructure that offer improved electromechanical properties over unidirectional piezofiber composites and can even possess stronger electromechanical properties than their piezoelectric constituents for certain modes of operation. We present examples of enhanced properties of these composites including effective piezoelectric charge and voltage coefficients, as well as effective electromechanical coupling factors for two-dimensional operation modes. We conduct an optimization to identify the optimal microstructure for the highest values of the coupling coefficients within this class of composites. Our findings demonstrate the potential in designing piezoelectric composites with a hierarchical structure to achieve significantly amplified electromechanical properties for energy harvesting applications.Physic

Non-linear stress response of non-gap-spanning magnetic chains suspended in a Newtonian fluid under oscillatory shear test : A direct numerical simulation

The corresponding author wishes to express his sincerest thanks to the Iran National Science Foundation (INSF) for supporting this work under Contract Number 92021291.Peer reviewedPostprintPublisher PD

A SPH solver for simulating paramagnetic solid fluid interaction in the presence of an external magnetic field

Acknowledgment The first two authors wish to express their sincerest thanks to Iran National Science Foundation (INSF) for supporting this work under Contract Number 92021291.Peer reviewedPostprin

Local Semiconducting Transition in Armchair Carbon Nanotubes: The Effect of Periodic Bi-site Perturbation on Electronic and Transport Properties of Carbon Nanotubes

In carbon nanotubes, the most abundant defects, caused for example by irradiation or chemisorption treatments, are small perturbing clusters, i.e. bi-site defects, extending over both A and B sites. The relative positions of these perturbing clusters play a crucial role in determining the electronic properties of carbon nanotubes. Using bandstructure and electronic transport calculations, we find out that in the case of armchair metallic nanotubes a band gap opens up when the clusters fulfill a certain periodicity condition. This phenomenon might be used in future nanoelectronic devices in which certain regions of single metallic nanotubes could be turned to semiconducting ones. Although in this work we study specifically the effect of hydrogen adatom clusters, the phenomenon is general for different types of defects. Moreover, we study the influence of the length and randomness of the defected region on the electron transport through it.Comment: 5 Pages, 5 Figure

Phased Array Systems in Silicon

Phased array systems, a special case of MIMO systems, take advantage of spatial directivity and array gain to increase spectral efficiency. Implementing a phased array system at high frequency in a commercial silicon process technology presents several challenges. This article focuses on the architectural and circuit-level trade-offs involved in the design of the first silicon-based fully integrated phased array system operating at 24 GHz. The details of some of the important circuit building blocks are also discussed. The measured results demonstrate the feasibility of using integrated phased arrays for wireless communication and vehicular radar applications at 24 GHz

Training Curricula for Open Domain Answer Re-Ranking

In precision-oriented tasks like answer ranking, it is more important to rank many relevant answers highly than to retrieve all relevant answers. It follows that a good ranking strategy would be to learn how to identify the easiest correct answers first (i.e., assign a high ranking score to answers that have characteristics that usually indicate relevance, and a low ranking score to those with characteristics that do not), before incorporating more complex logic to handle difficult cases (e.g., semantic matching or reasoning). In this work, we apply this idea to the training of neural answer rankers using curriculum learning. We propose several heuristics to estimate the difficulty of a given training sample. We show that the proposed heuristics can be used to build a training curriculum that down-weights difficult samples early in the training process. As the training process progresses, our approach gradually shifts to weighting all samples equally, regardless of difficulty. We present a comprehensive evaluation of our proposed idea on three answer ranking datasets. Results show that our approach leads to superior performance of two leading neural ranking architectures, namely BERT and ConvKNRM, using both pointwise and pairwise losses. When applied to a BERT-based ranker, our method yields up to a 4% improvement in MRR and a 9% improvement in P@1 (compared to the model trained without a curriculum). This results in models that can achieve comparable performance to more expensive state-of-the-art techniques.Comment: Accepted at SIGIR 2020 (long