Nanoglass–Nanocrystal Composite—a Novel Material Class for Enhanced Strength–Plasticity Synergy

The properties of a material can be engineered by manipulating its atomic and chemical architecture. Nanoglasses which have been recently invented and comprise nanosized glassy particles separated by amorphous interfaces, have shown promising properties. A potential way to exploit the structural benefits of nanoglasses and of nanocrystalline materials is to optimize the composition to obtain crystals forming within the glassy particles. Here, a metastable Fe‐10 at% Sc nanoglass is synthesized. A complex hierarchical microstructure is evidenced experimentally at the atomic scale. This bulk material comprises grains of a Fe₉₀Sc₁₀ amorphous matrix separated by an amorphous interfacial network enriched and likely stabilized by hydrogen, and property‐enhancing pure‐Fe nanocrystals self‐assembled within the matrix. This composite structure leads a yield strength above 2.5 GPa with an exceptional quasi‐homogeneous plastic flow of more than 60% in compression. This work opens new pathways to design materials with even superior properties.     

Multifamily malware models

When training a machine learning model, there is likely to be a tradeoff between accuracy and the diversity of the dataset. Previous research has shown that if we train a model to detect one specific malware family, we generally obtain stronger results as compared to a case where we train a single model on multiple diverse families. However, during the detection phase, it would be more efficient to have a single model that can reliably detect multiple families, rather than having to score each sample against multiple models. In this research, we conduct experiments based on byte n-gram features to quantify the relationship between the generality of the training dataset and the accuracy of the corresponding machine learning models, all within the context of the malware detection problem. We find that neighborhood-based algorithms generalize surprisingly well, far outperforming the other machine learning techniques considered.

     

ENGAGE compatibilized HDPE/EPDM blends: Modification of some industrially pertinent properties and morphology upon incorporation of Mg(OH)2 filler and electron beam crosslinked network

To observe the effect of ENGAGE (a poly‐olefin elastomer) on compatibilization of industrially important incompatible blend, high‐density polyethylene (HDPE)/ethylene‐propylene diene elastomer (EPDM), 15 wt % ENGAGE is incorporated into the system and the latter is found satisfactorily efficient as compatibilizer for the above system. To improve some industrially pertinent properties another strategies are also followed in addition, incorporation of magnesium hydroxide [Mg(OH)₂] and electron beam (EB) crosslinking into the system. The gel content was found to increase with radiation dose, EPDM content and Mg(OH)₂ dispersion. ENGAGE interestingly increases the gel content that is, promotes crosslinking. It is unique that filler dispersion and crosslinked network formation maintain the compatibility of the ternary system, which is confirmed by X‐ray diffraction, differential scanning calorimetry, mechanical properties, and scanning electron microscope. The compatibilization, Mg(OH)₂ dispersion, and EB crosslinking improve the mechanical, thermo mechanical, flame retardant properties, and phase morphology considerably. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44922.     

The Impact of Sequential Fluorination of π‐Conjugated Polymers on Charge Generation in All‐Polymer Solar Cells

The performance of all‐polymer solar cells (all‐PSCs) is often limited by the poor exciton dissociation process. Here, the design of a series of polymer donors ( P1 – P3 ) with different numbers of fluorine atoms on their backbone is presented and the influence of fluorination on charge generation in all‐PSCs is investigated. Sequential fluorination of the polymer backbones increases the dipole moment difference between the ground and excited states (Δµ_ge) from P1 (18.40 D) to P2 (25.11 D) and to P3 (28.47 D). The large Δµ_ge of P3 leads to efficient exciton dissociation with greatly suppressed charge recombination in P3 ‐based all‐PSCs. Additionally, the fluorination lowers the highest occupied molecular orbital energy level of P3 and P2 , leading to higher open‐circuit voltage (V_OC). The power conversion efficiency of the P3 ‐based all‐PSCs (6.42%) outperforms those of the P2 and P1 (5.00% and 2.65%)‐based devices. The reduced charge recombination and the enhanced polymer exciton lifetime in P3 ‐based all‐PSCs are confirmed by the measurements of light‐intensity dependent short‐circuit current density (J_SC) and V_OC, and time‐resolved photoluminescence. The results provide reciprocal understanding of the charge generation process associated with Δµ_ge in all‐PSCs and suggest an effective strategy for designing π‐conjugated polymers for high performance all‐PSCs.     

Large‐scale optimization strategies for pressure swing adsorption cycle synthesis

Pressure swing adsorption (PSA) is an efficient method for gas separation and is a potential candidate for carbon dioxide (CO₂) capture from power plants. However, few PSA cycles have been designed for this purpose; the optimal design and operation of PSA cycles for CO₂ capture, as well as other systems, remains a very challenging task. In this study, we present a systematic optimization‐based formulation for the synthesis and design of novel PSA cycles for CO₂ capture in IGCC power plants, which can simultaneously produce hydrogen (H₂) and CO₂ at high purity and high recovery. Here, we apply a superstructure‐based approach to simultaneously determine optimal cycle configurations and design parameters for PSA units. This approach combines automatic differentiation, efficient ODE solvers for the state and sensitivity equations of the PSA model, and state of the art nonlinear programming solvers. Three optimization models are proposed, and two PSA case studies are considered. The first case study considers a binary separation of H₂ and CO₂ at high purity, where specific energy is minimized, whereas the second case study considers a larger five component separation. © 2012 American Institute of Chemical Engineers AIChE J, 58: 3777–3791, 2012     

Electrical and magnetic properties of nanocrystalline BiFeO3 prepared by high energy ball milling and microwave sintering

A new synthesis route with high energy ball milling and microwave sintering is used to obtain nanocrystalline BiFeO3 with improved dielectric and magnetic properties. Electrical and magnetic properties are compared with a conventionally sintered microcrystalline BiFeO3. It is found that the dielectric constant is increased more than one order of magnitude, electrical resistivity by six orders of magnitude and remnant polarization value is increased by 4-5 times for nanocrystalline BiFeO3 in comparison to conventionally sintered microcrystalline BiFeO3. Nanocrystalline BiFeO3 is seen to have ferromagnetic behavior whereas microcrystalline BiFeO3 is known to be antiferromagnetic.     

Salt-and-pepper noise removal by adaptive median-based lifting filter using second-generation wavelets

In this paper, we propose a novel adaptive median-based lifting filter for image de-noising which has been corrupted by homogeneous salt and pepper noise. The median-based lifting filter removes the noise of the input image by calculating the median of the neighboring significant pixels. The algorithm for image noise removal uses the lifting scheme of the second-generation wavelets in conjunction with the proposed adaptive median-based lifting filter. The experimental results demonstrate the efficiency of the proposed method. The proposed algorithm is compared with all the basic filters, and it is found that our method outperforms many other algorithms and it can remove salt and pepper noise with a noise level as high as 90%. The algorithm works exceedingly well for all levels of noise, as illustrated in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) measures.     

On reducing the post-heat-treatment time of the weldment

Post heat treatment of weldments is one of the most extensively used techniques by the industrial community for relieving welding residual stresses. Such practice not only delays the manufacturing process, but also increases the cost of manufacturing. In this article, an idea of a new welding technique, which is a promising tool for relieving welding residual stresses, is presented. This method is anticipated to reduce the time and cost of the manufacturing process. The first part of the investigation focuses on simulation of an idea by using an auxiliary heat source for creating a weldment with a more uniform temperature distribution both spatially and temporally. A subroutine has been developed for optimizing the size of an auxiliary heat input (AHI). The details of the subroutine and the parameters considered for optimizing the AHI are presented. The results show that by increasing the stabilizing temperature and size of the AHI, the speed of cooling and spatial temperature gradient decreases. This may result in reducing the level of residual stresses.