You are currently viewing a new version of our website. To view the old version click .

Electronics

Electronics is an international, peer-reviewed, open access journal on the science of electronics and its applications published semimonthly online by MDPI.
The Polish Society of Applied Electromagnetics (PTZE) is affiliated with Electronics and their members receive a discount on article processing charges.
Quartile Ranking JCR - Q2 (Engineering, Electrical and Electronic)

All Articles (27,028)

The rapid expansion and interdisciplinary nature of Physical Internet (PI) research have resulted in fragmented knowledge, limiting the ability of stakeholders to identify emerging trends, actionable insights and genuine research gaps. This study introduces a novel knowledge management approach that uses Graph Retrieval-Augmented Generation (GraphRAG) to systematically organize and integrate PI-related literature. A comprehensive knowledge graph was constructed by extracting and semantically modeling entities and relationships from 2835 academic papers, conference proceedings and international roadmaps. The developed system incorporates fuzzy semantic search and multiple retrieval strategies, including local, global and hybrid approaches, enabling nuanced, context-aware access to information. Stakeholder-specific prompts, tailored to the needs of industry, government and academia, demonstrate how GraphRAG can support the discovery of business model innovations, policy design and underexplored research areas. A comparative evaluation using cosine similarity and BERTScore confirms that graph-based strategies outperform standard LLM retrieval in providing relevant and comprehensive answers while also revealing connections that would be missed in manual reviews. The results demonstrate that the proposed GraphRAG model is a scalable and extensible framework for addressing knowledge gaps and promoting collaboration in PI research synthesis for sustainable logistics. The model also shows promise for application in other complex domains.

17 December 2025

Different methods using LLM.

In this article, the authors present an in-depth analysis of a PTAT sensor and its role as one of the analogue blocks in a test ASIC. The authors propose some modifications to the PTAT sensor to reduce output signal non-linearities observed following measurements that are more accurate than those in their previous article on a PTAT sensor. The obtained PTAT sensor linearity ranges from R2 = 0.9990 to R2 = 0.9999 in a temperature range from −40 °C to 150 °C for the entire set of measured specimens, and the details of these test sessions are discussed in this manuscript. Moreover, it is demonstrated that at least some of the implemented circuits may have a discernible impact on the operation of the others. This is particularly evident regarding the bandgap reference, whose operation is also presented and analysed. The integrated circuit specimens containing all analysed circuits were manufactured using custom 3 µm CMOS technology on an n-type wafer. Measurements showed that some circuits containing p-diff resistors behave differently compared to those consisting solely of MOS transistors in symmetrical and matched configurations. The spread of resistor values is approximately 20%, thus requiring their skilful operation in this technology. The likely cause of the bandgap reference’s operation modification has been identified, and promising results have been obtained by recreating its malfunction via simulation. The authors found that in this technology, analogue circuits should be designed with a large margin for component dimensions, especially those implanted in p-wells.

17 December 2025

Schematic of the proposed PTAT sensor [12] (simplified and detailed versions).

This paper focuses on FinFET transistors. The degradation characteristics of FinFET devices after total ionizing dose (TID) radiation in low-temperature environments were investigated by means of a combination of experiments and TCAD simulations. By analyzing the electronic properties of radiation-induced defects in FinFET transistors under low-temperature conditions, the formation and evolution mechanisms of these defects are studied. A physical model for the low-temperature total dose effects of FinFET transistors is established, providing support for the radiation hardening and space applications of FinFET devices.

17 December 2025

Physical Photograph and Layout of the FinFET Chip.

In open wireless communication channels, the combined effects of random pulse jamming and multipath-induced time-varying fading significantly degrade the reliability and efficiency of information transmission. Particularly in highly dynamic scenarios such as unmanned aerial vehicle (UAV) communications, existing Q-learning-based anti-jamming methods often rely on idealized channel assumptions, leading to mismatched “transmit/silence” decisions under fading conditions. To address this issue, this paper proposes a Q-learning and time-varying fading channel-aware anti-jamming method against random pulse jamming. In the proposed framework, a fading channel model is incorporated into Q-learning, where the state space jointly represents timeslot position, jamming history, and channel sensing results. Furthermore, a reward function is designed by jointly considering jamming power and channel quality, enabling dynamic strategy adaptation under rapidly varying channels. A moving average process is applied to smooth simulation fluctuations. The results demonstrate that the proposed method effectively suppresses jamming collisions, enhances the successful transmission rate, and improves communication robustness in fast-fading environments, showing strong potential for deployment in practical open-channel applications.

17 December 2025

UAV Communication Scenario Model.

News & Conferences

Issues

Open for Submission

Editor's Choice

Reprints of Collections

Biometric Recognition
Reprint

Biometric Recognition

Latest Advances and Prospects
Editors: Yunlong Wang, Zhaofeng He, Caiyong Wang, Jianze Wei, Min Ren
Computational Intelligence in Remote Sensing
Reprint

Computational Intelligence in Remote Sensing

2nd Edition
Editors: Yue Wu, Kai Qin, Maoguo Gong, Qiguang Miao

Get Alerted

Add your email address to receive forthcoming issues of this journal.

XFacebookLinkedIn
Electronics - ISSN 2079-9292