All-Group IV Transferable Membrane Mid-Infrared Photodetectors

Semiconductor membranes emerged as a versatile class of nanomaterials to control lattice strain and engineer complex heterostructures enabling a variety of innovative applications. With this perspective, herein this platform is exploited to tune simultaneously the lattice parameter and bandgap energy in group IV GeSn semiconductor alloys. As Sn content is increased to reach a direct bandgap, these semiconductors become metastable and typically compressively strained. It is shown that the relaxation in released membranes extends the absorption wavelength range deeper in the mid-infrared. Fully released Ge_0.83Sn_0.17 membranes are integrated on silicon and used in the fabrication of broadband photodetectors operating at room temperature with a record wavelength cutoff of 4.6  µ m, without compromising the performance at shorter wavelengths down to 2.3  µ m. These membrane devices are characterized by two orders of magnitude reduction in dark current as compared to as-grown strained epitaxial layers. A variety of experimental tools and optimized calculations are used to discuss the crystalline quality, composition uniformity, lattice strain, and the electronic band structure of the investigated materials and devices. The ability to engineer all-group IV transferable mid-infrared photodetectors lays the groundwork to implement scalable and flexible sensing and imaging technologies exploiting these integrative, silicon-compatible strained-relaxed GeSn membranes.     

An efficient artificial bee colony algorithm with application to nonlinear predictive control

In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.     

Phase transformations in nickel sulphide: Microstructures and mechanisms

Nickel sulphide inclusions are known to be responsible for delayed fracture in tempered glasses due to phase transformation within the inclusion. Microstructural identification of the phase transformation mechanisms in the Ni–S system close to the NiS composition were carried out on a series of partially transformed states. Observations allow to investigate the morphological evolution during transformation, the phase orientation relationships and the first stages of the transformation were investigated by optical microscopy, electron backscatter diffraction, and scanning and transmission electron microscopy. The transformation mechanisms change significantly with the change in sulphur content of the α-NiS phase. Massive transformation is observed for near-stoichiometric composition. For overstoichiometric composition, the transformation is controlled by a long-range diffusion mechanism. The influence of stoichiometry and impurities (Fe) on the microstructural evolution and transformation mechanisms has also been studied.     

Robust Chaotic Communication Based on Indirect Coupling Synchronization

This paper proposes a chaotic communication approach using indirect coupled synchronization scheme with high power encrypted signals. The proposed scheme is carefully designed so that the encrypted signal does not deteriorate the synchronization unlike in traditional communication methods. The synchronization problem is solved using observer-based controller. The advantages of this approach are the general and systematic feedback observer design methodology suitable for convergence rate of synchronization; flexibility in selection of chaotic signals for cryptosystem secure key generator; and improvement of the frequency-domain characteristics of the transmitted message. Computer simulations show that the synchronization between the transmitter and the receiver is more robust for different amplitude values of the information signal, even in the presence of external disturbances.     

Optimizing Resource Utilization during the Recovery of Civil Infrastructure Systems

Postdisaster recovery efforts of damaged civil infrastructure systems need to be optimized in order to alleviate the adverse impacts of natural disasters on local societies and economies. This paper presents an innovative framework that integrates two newly developed models for resource utilization and multiobjective optimization that are designed to optimize these recovery efforts. The developed models provide new and unique capabilities, including (1) allocating limited reconstruction resources to competing recovery projects, (2) estimating the reconstruction duration and cost associated with implementing specific recovery plans, and (3) generating optimal trade-offs between minimizing the reconstruction duration and cost. An application example is analyzed to evaluate the performance of the developed models and demonstrate their capabilities in identifying a wide spectrum of optimal reconstruction plans, where each provides a unique and nondominated trade-off between minimizing the recovery duration and cost. This allows decision makers in emergency management agencies to select and implement reconstruction plans that address various societal and economical needs in the aftermath of natural disasters.     

A temporal-based SVM approach for the detection and identification of pollutant gases in a gas mixture

Applied Intelligence - Air toxicity and pollution phenomena are on the rise across the planet. Thus, the detection and control of gas pollution are nowadays major economic and environmental...     

Linseed oil and mixture with maleic anhydride: <Superscript>1</Superscript>H and <Superscript>13</Superscript>C NMR

It was shown that ¹H NMR allowed a rapid determination of the ratio of the linolenic residues over all the others (linoleic + oleic + saturated) and ¹³C NMR allowed a rapid determination of the ratio of linolenic over (linoleic + oleic) residues as well as the linoleic/oleic ratio in a few minutes on less than 20 mg of crude LO. After thermal treatment (220°C for 2 h, followed by cooling to room temperature), a 1∶1 mixture of linseed oil (LO) and maleic anhydride (MA), which was a suspension, became limpid and remained limpid. Moreover, the viscosity of the mixture was higher than that of pure LO treated in the same way. It was shown by ¹³C NMR and quantitative recovery of the constituents (LO and MA) through solvent separation that no reaction occurred between LO and MA during this thermal treatment. This result is in accord with DSC analysis of such a 1∶1 LO/MA mixture that exhibited an exothermic effect too small (about 34 kcal/mol) to correspond to formation of a C−C bond.