Nanostructure and mechanical properties of aromatic polyamide and reactive organoclay nanocomposites

Aromatic polyamide/organoclay nanocomposites were synthesized using the solution blending technique. Treatment of montmorillonite clay with p-phenylenediamine produced reactive organophilic clay for good compatibility with the matrix. Polyamide chains were prepared by condensing a mixture of 1,4-phenylenediamine and 4-4′-oxydianiline with isophthaloyl chloride under anhydrous conditions. These chains were end capped with carbonyl chloride using 1% extra acid chloride near the end of reaction to develop the interactions with organoclay. The dispersion and structure–property relationship were monitored using FTIR, XRD, FE-SEM, TEM, DSC and tensile testing of the thin films. The structural investigations confirmed the formation of delaminated and disordered intercalated morphology with nanoclay loadings. This morphology of the nanocomposites resulted in their enhanced mechanical properties. The tensile behavior and glass transition temperature significantly augmented with increasing organoclay content showing a greater interaction between the two disparate phases.     

Evolutionary Intelligence and Deep Learning Enabled Diabetic Retinopathy Classification Model

Diabetic Retinopathy (DR) has become a widespread illness among diabetics across the globe. Retinal fundus images are generally used by physicians to detect and classify the stages of DR. Since manual examination of DR images is a time-consuming process with the risks of biased results, automated tools using Artificial Intelligence (AI) to diagnose the disease have become essential. In this view, the current study develops an Optimal Deep Learning-enabled Fusion-based Diabetic Retinopathy Detection and Classification (ODL-FDRDC) technique. The intention of the proposed ODL-FDRDC technique is to identify DR and categorize its different grades using retinal fundus images. In addition, ODL-FDRDC technique involves region growing segmentation technique to determine the infected regions. Moreover, the fusion of two DL models namely, CapsNet and MobileNet is used for feature extraction. Further, the hyperparameter tuning of these models is also performed via Coyote Optimization Algorithm (COA). Gated Recurrent Unit (GRU) is also utilized to identify DR. The experimental results of the analysis, accomplished by ODL-FDRDC technique against benchmark DR dataset, established the supremacy of the technique over existing methodologies under different measures.     

Nanoheterostructure by Liquid Metal Sandwich-Based Interfacial Galvanic Replacement for Cancer Targeted Theranostics

Nanoheterostructures with exquisite interface and heterostructure design find numerous applications in catalysis, plasmonics, electronics, and biomedicine. In the current study, series core–shell metal or metal oxide-based heterogeneous nanocomposite have been successfully fabricated by employing sandwiched liquid metal (LM) layer (i.e., LM oxide/LM/LM oxide) as interfacial galvanic replacement reaction environment. A self-limiting thin oxide layer, which would naturally occur at the metal–air interface under ambient conditions, could be readily delaminated onto the surface of core metal (Fe, Bi, carbonyl iron, Zn, Mo) or metal oxide (Fe₃O₄, Fe₂O₃, MoO₃, ZrO₂, TiO₂) nano- or micro-particles by van der Waals (vdW) exfoliation. Further on, the sandwiched LM layer could be formed immediately and acted as the reaction site of galvanic replacement where metals (Au, Ag, and Cu) or metal oxide (MnO₂) with higher reduction potential could be deposited as shell structure. Such strategy provides facile and versatile approaches to design and fabricate nanoheterostructures. As a model, nanocomposite of Fe@Sandwiched-GaIn-Au (Fe@SW-GaIn-Au) is constructed and their application in targeted magnetic resonance imaging (MRI) guided photothermal tumor ablation and chemodynamic therapy (CDT), as well as the enhanced radiotherapy (RT) against tumors, have been systematically investigated.     

Assessment and Improvement of IDF Generation Algorithms Used in the IDF_CC Tool

Water Resources Management - Climate change will modify the spatio-temporal variation of hydrological variables worldwide, potentially leading to more extreme events and hydraulic infrastructure...     

Ternary adsorbent photocatalyst hybrid (APH) nanomaterials for improved abstraction of tetracycline from water

ABSTRACT

Current health situations have instigated increased frequency of taking antibiotics for cure of infections but this amplified use is posing threats to environment. This research is focused to remove Tetracycline (TC), an antibiotic from water, using an advanced nanohybrid that compact the properties of adsorbent and photocatalyst. Compared to conventional methods for remediation of TC, large surface area (452 m²g^?1) adsorbent photocatalyst hybrid (APH) g-C₃N₄/α-MoO₃/ZIF-67 (CMZ) have found much effective as 97% degradation of TC is observed in 110 min with 0.1 g of APH. Increasing g-C₃N₄ in the hybrids has improved percent degradation of TC molecules. CMZ-3 is found as a potential candidate for water treatment.     

6D direct-drive technology for planar motion stages

Achieving 6D direct drive motion control over long planar strokes on a single mover can greatly improve machine performance. Existing solutions are either limited to small-stroke applications (a fraction of the stage size) or require a large number of coils with enormous control complexity. This paper presents a novel 6D direct drive technology for planar stages with many advantages: (1) stroke can be on the order of several meters; (2) the number of coils increases linearly with motion range; (3) no end effects or force coupling between axes; and (4) ease of control and superior force linearity.