Collective Dipole‐Dominated Doping of Monolayer MoS2: Orientation and Magnitude Control via the Supramolecular Approach

Molecular doping is a powerful, tuneable, and versatile method to modify the electronic properties of 2D transition metal dichalcogenides (TMDCs). While electron transfer is an isotropic process, dipole‐induced doping is a collective phenomenon in which the orientation of the molecular dipoles interfaced to the 2D material is key to modulate and boost this electronic effect, despite it is not yet demonstrated. A novel method toward the molecular functionalization of monolayer MoS₂ relying on the molecular self‐assembly of metal phthalocyanine and the orientation‐controlled coordination chemistry of axial ligands is reported here. It is demonstrated that the subtle variation of position and type of functional groups exposed on the pyridinic ligand, yields a molecular dipole with programed magnitude and orientation which is capable to strongly influence the opto‐electronic properties of monolayer MoS₂. In particular, experimental results revealed that both p‐ and n‐type doping can be achieved by modulating the charge carrier density up to 4.8 10¹² cm^?2. Density functional theory calculations showed that the doping mechanism is primarily resulting from the effect of dipole‐induced doping rather than charge transfer. The strategy to dope TMDCs is a highly modulable and robust, and it enables to enrich the functionality of 2D materials‐based devices for high‐performance applications in optoelectronics.     

Instances selection algorithm by ensemble margin

Abstract

The main limit of data mining algorithms is their inability to deal with the huge amount of available data in a reasonable processing time. A solution of producing fast and accurate results is instances and features selection. This process eliminates noisy or redundant data in order to reduce the storage and computational cost without performances degradation. In this paper, a new instance selection approach called Ensemble Margin Instance Selection (EMIS) algorithm is proposed. This approach is based on the ensemble margin. To evaluate our approach, we have conducted several experiments on different real-world classification problems from UCI Machine learning repository. The pixel-based image segmentation is a field where the storage requirement and computational cost of applied model become higher. To solve these limitations we conduct a study based on the application of EMIS and other instance selection techniques for the segmentation and automatic recognition of white blood cells WBC (nucleus and cytoplasm) in cytological images.     

Improving kriging surrogates of high-dimensional design models by Partial Least Squares dimension reduction

Engineering computer codes are often computationally expensive. To lighten this load, we exploit new covariance kernels to replace computationally expensive codes with surrogate models. For input spaces with large dimensions, using the kriging model in the standard way is computationally expensive because a large covariance matrix must be inverted several times to estimate the parameters of the model. We address this issue herein by constructing a covariance kernel that depends on only a few parameters. The new kernel is constructed based on information obtained from the Partial Least Squares method. Promising results are obtained for numerical examples with up to 100 dimensions, and significant computational gain is obtained while maintaining sufficient accuracy.     

Fast mode decision algorithm for H.264/SVC enhancement layer

Scalable video coding (SVC) has been standardized to extend the capabilities of the H.264 advanced video coding (AVC). The SVC can compress several video sequences of various resolutions as a single bit-stream. In the SVC enhancement layer, for Joint Scalable Video Model (JSVM) software implementation, an exhaustive mode decision process based on the base layer mode predictions is performed to obtain the best mode for each macroblock (MB). This technique may achieve a higher coding efficiency; however, it induces a significant computational complexity in the encoding engine. In order to speedup the SVC encoder, a fast mode decision algorithm was proposed in this paper. In other words, our aim was to decrease the number of candidate modes to reduce the computational complexity and maintain the same level of coding efficiency, this approach used the spatial and temporal correlation between MB situated at the enhancement layer and its co-located MB at the base layer. Our statistical analyses were made using several HD sequences with different motion characteristics. Experimental results show a significant improvement in terms of time encoding which is a major constraint for any real-time implementation. However, this gain is accompanied with an acceptable loss in video quality and a tolerable bit rate increase for most media supports. In fact, our proposed algorithm permits a major improvement that can reach up to 64.9 % in terms of computational effort. This gain will induce an average loss yield to 10.5 or 13.87 % that is comparable to the 13.12 % of the He Li’s algorithm with an acceptable loss in terms of subjective video quality.     

Hybrid intelligent method for fuzzy reliability analysis of corroded X100 steel pipelines

Epistemic uncertainties are critical for reliable design of corroded pipes made of high-strength grade steel. In this work, corrosion defects geometries and operating pressure are provided as the epistemic uncertainties in reliability analysis. A framework of an iterative approach-based bi-loop is presented for fuzzy reliability analysis (FRA) of corroded pipelines to evaluate the fuzzy reliability index-based various fuzzy-random variables (FRVs). In the inner loop, the conjugate first-order reliability method using adaptive finite-step size is applied for carried out the reliability analysis. The outer loop is structured based on the fuzzy analysis corresponding to a modified particle swarm optimization as an intelligent tool. The adaptive conjugate fine step size is dynamically computed to adjust the conjugate sensitivity vector in the reliability loop. The sufficient descent condition is satisfied based on three-term conjugate first-order reliability method. The performance function of corroded pipelines is defined based on average shear stress yield-based plastic flow theory, remaining strength factor, and operating pressure. Two applicable examples as corroded pipelines made from X100 high-strength steel are given to illustrate the effects of epistemic uncertainties under corrosion defects. Investigation the results has shown that modeling of epistemic uncertainty in the reliability analysis of high-grade steel pipelines could result more reasonable reliability indexes. In addition, results indicate that FRVs have significant influence on fuzzy reliability index calculations, especially corrosion defect depth and operating pressure (as FRVs). The sensitivity measure of FRA demonstrated that fuzzy reliability index of corroded X100 steel pipelines is more sensitive to the FRVs means.

     

A hybrid sufficient performance measure approach to improve robustness and efficiency of reliability-based design optimization

The stable convergence and efficiency of reliability-based design optimization (RBDO) using performance measure approach (PMA) are the major issue to develop the reliability methods based on modified chaos control (MCC), hybrid chaos control (HCC) and finite-step length adjustment (FSL). However, these methods may be inefficient for RBDO problems with convex and concave probabilistic constraints. In this paper, an adaptive modified chaos control (AMC) is proposed to provide the robust and efficient results in RBDO. The proposed AMC is adjusted using dynamical chaos control factor, which is extracted using sufficient descent condition for PMA. Using sufficient criterion, the proposed AMC is adaptively combined with advanced mean value (AMV) to improve the performance of PMA, named as hybrid adaptive modified chaos control (HAMC). Considering the robustness and efficiency, the proposed HAMC is compared with several existing reliability methods by three nonlinear structural/mathematical performance functions and two RBDO problems. The results indicate that the proposed HAMC with sufficient descent condition provides superior convergences in terms of both robustness and efficiency, compared to existing PMA methods using AMV, MCC, HCC and FSL.

     

Tolerance design of datum systems

A majority of mechanical products and devices can be viewed as a collection of parts engineered to assemble so that mating parts and features satisfy some predetermined spatial relationships. Designers typically satisfy the constraints that arise from these relationships by using a set of specific physical features to create on each mating part an accurate reference frame from which all other relevant geometric elements are located. The accuracy and precision with which two mating parts assemble and influence subsequent alignment of other features are controlled by the nominal dimensioning and tolerancing scheme imposed on the geometric elements used to create the two coincident reference frames. The paper presents the development and implementation of a computer aid to assist designers in the allocation of design sizes and tolerances that satisfy functional translation, rotation and assembly constraints imposed on four datum systems commonly used in design.     

Erratum to: An improved multimodal signal-image compression scheme with application to natural images and biomedical data

Multimedia Tools and Applications -     

Ring opening polymerization of oxetane by the use of a montmorillonite clay as catalyst

Maghnite-H⁺ was found to be an effective solid catalyst for the ring opening polymerization of oxetane. Maghnite-H⁺ is a proton exchanged montmorillonite clay. Effect of weight ratio of initiator/monomer and reaction time on the conversion of monomer and the molecular weight is investigated. Increasing maghnite-H⁺ proportion produced an increase in oxetane conversion and a decrease in Mn. A cationic mechanism for the reaction was proposed.