Nanoparticles are defined as an organic or non-organic structure of matter in at least one of its dimensions less than 100 nm. Nanoparticles proved their effectiveness in different fields because of their unique physicochemical properties. Using nanoparticles in the power field contributes to cleaning and decreasing environmental pollution, which means it is an environmentally friendly material. It could be used in many different parts of batteries, including an anode, cathode, and electrolyte. This study reviews different types of nanoparticles used in Lithium-ion batteries by collecting the advanced techniques for applying nanotechnology in batteries. In addition, this review presents an idea about the advantages and disadvantages of using nanoparticles in batteries to harness energy without harming the environment. This review showed that applying nanotechnology and using nanoparticles in the production technique of batteries open the field for developing energy storage in Nano sized batteries. This, in turn, is important in the new era of technology in the industries of electronic devices and precision electrical appliances such as mobile phones, digital cameras, etc.
This comprehensive review examines the efficacy and safety of tumor necrosis factor-alpha (TNF-α) inhibitors in treating various autoimmune diseases, and focuses on their application in Iraqi patients. Elevated TNF-α levels are linked to autoimmune disorders, leading to the development of anti-TNF-α therapies such as infliximab, etanercept, adalimumab, certolizumab pegol, and golimumab, which have gained FDA approval for conditions like psoriasis, in¬flammatory bowel disease, ankylosing spondylitis, and rheumatoid arthritis. While these therapies demonstrate sig¬nificant therapeutic benefits, including improved quality of life and disease management, they also carry risks, such as increased susceptibility to infections and pote
... Show MoreOptical losses represent one of the primary obstacles to increasing the efficiency of silicon solar cells. The recommended solution to minimize optical losses is the use of plasmonic metal nanoparticles; however, they act as recombination centers within the solar cell construction, leading to a decrease in performance. The goal of this article is to introduce cobalt/graphene nanoparticles into the solar cell to minimize the optical losses. An ultra-thin film silicon PIN solar cell of dimensions (400 ×400 ×900) nm3 with ring metal contact shape was designed and numerically investigated using COMSOL Multiphysics software version 6.2 by the finite element method (FEM). Core/shell cobalt-graphene (Co/Gr) nanoparticles are periodically int
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Background: Polymethylmethacrylate (PMMA) is the most ‎commonly used mâ€aterial in denture construction. This material is ‎far from ideal in fulfilling the‎ mechanical requirements, like low impact and transverse strength and poor thermal conductivity are present in this material. The purpose of this study was to study the effect of addition a composite which include 1%wt silanized silicone dioxide nano fillers (SiO2) and 1wt% oxygen plasma treated polypropylene fiber (PP) on some properties of heat cured acrylic resin denture base material (PMMA). Materials and methods: One hundâ€red (100) prepared specimens were divided into five groups according to the tests, each group consisted of 20 specimens and t
Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c
... Show MoreWe report a new theranostic device based on lead sulfide quantum dots (PbS QDs) with optical emission in the near infrared wavelength range decorated with affibodies (small 6.5 kDa protein-based antibody replacements) specific to the cancer biomarker human epidermal growth factor receptor 2 (HER2), and zinc(II) protoporphyrin IX (ZnPP) to combine imaging, targeting and therapy within one nanostructure. Colloidal PbS QDs were synthesized in aqueous solution with a nanocrystal diameter of ∼5 nm and photoluminescence emission in the near infrared wavelength range. The ZHER2:432 affibody, mutated through the introduction of two cysteine residues at the C-terminus (
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
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