Characterization of integrated nanomaterials using deep learning method-based Mantis search algorithm

IF 2.2 4区工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Journal of Computational Electronics Pub Date : 2025-02-16 DOI:10.1007/s10825-025-02284-8

L. Gowrisankar, J. Ganesh Murali, Y. Dominic Ravichandiran

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引用次数: 0

Abstract

The characterization of silver nanoparticles is vital for understanding unique properties and potential applications in various fields. This research aims to explore and evaluate characterization techniques to assess the quality and behavior of silver nanoparticles. Understanding characteristics is crucial for optimizing synthesis methods and ensuring safe and effective use in nanotechnology applications. In this research, bidirectional long short-term memory-Mantis search algorithm is deployed to characterizations of silver nanoparticle and also evaluates the characteristics of silver nanoparticle such as the accuracy, precision, recall, and f1-score values are recorded. The outcome of the recommended technique is implemented in MATLAB and benchmarked against existing approaches, demonstrating its effectiveness in achieving the proper characterization. The results indicate that the given approach outperforms existing techniques, demonstrating its effectiveness and also reduces the weighted square error by 0.6 and enhances the precession by 98.8%. This signifies not only the effectiveness, but also the efficiency of the given approach, indicating its potential for streamlining characterization processes and enhancing productivity in nanotechnology research and development.

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来源期刊

Journal of Computational Electronics ENGINEERING, ELECTRICAL & ELECTRONIC-PHYSICS, APPLIED

CiteScore

4.50

自引率

4.80%

发文量

142

审稿时长

>12 weeks

期刊介绍： he Journal of Computational Electronics brings together research on all aspects of modeling and simulation of modern electronics. This includes optical, electronic, mechanical, and quantum mechanical aspects, as well as research on the underlying mathematical algorithms and computational details. The related areas of energy conversion/storage and of molecular and biological systems, in which the thrust is on the charge transport, electronic, mechanical, and optical properties, are also covered. In particular, we encourage manuscripts dealing with device simulation; with optical and optoelectronic systems and photonics; with energy storage (e.g. batteries, fuel cells) and harvesting (e.g. photovoltaic), with simulation of circuits, VLSI layout, logic and architecture (based on, for example, CMOS devices, quantum-cellular automata, QBITs, or single-electron transistors); with electromagnetic simulations (such as microwave electronics and components); or with molecular and biological systems. However, in all these cases, the submitted manuscripts should explicitly address the electronic properties of the relevant systems, materials, or devices and/or present novel contributions to the physical models, computational strategies, or numerical algorithms.