Pub Date : 2026-01-24DOI: 10.1016/j.nancom.2026.100613
Mohammad Zoofaghari , Liv Cornelia Middelthon , Mladen Veletić , Ilangko Balasingham
Directing extracellular vesicles (EVs), such as exosomes and microvesicles, toward specific cells is an emerging focus in nanomedicine, owing to their natural role as carriers of proteins, RNAs, and drugs. EVs can be manipulated by external electric fields due to their intrinsic surface charge and biophysical properties. This study investigates the feasibility of using extremely low-frequency electromagnetic fields to guide EV transport. A theoretical framework based on the Fokker–Planck equation was developed and numerically solved to model vesicle trajectories under time-harmonic drift. Computational simulations were conducted to systematically assess the influence of key electric field parameters—including phase, frequency, and intensity—on vesicle displacement and trajectory. The findings demonstrate that frequencies below combined with field strengths of 200–2000 V/m can induce substantial directional control of EV motion. Moreover, enhanced directivity was achieved through the application of multi-component electric fields. Overall, this work establishes a theoretical foundation for the external-field-based beam steering of nanoparticles within the framework of MC.
{"title":"Electrophoretic beam steering in molecular communication: Toward targeted extracellular vesicle delivery","authors":"Mohammad Zoofaghari , Liv Cornelia Middelthon , Mladen Veletić , Ilangko Balasingham","doi":"10.1016/j.nancom.2026.100613","DOIUrl":"10.1016/j.nancom.2026.100613","url":null,"abstract":"<div><div>Directing extracellular vesicles (EVs), such as exosomes and microvesicles, toward specific cells is an emerging focus in nanomedicine, owing to their natural role as carriers of proteins, RNAs, and drugs. EVs can be manipulated by external electric fields due to their intrinsic surface charge and biophysical properties. This study investigates the feasibility of using extremely low-frequency electromagnetic fields to guide EV transport. A theoretical framework based on the Fokker–Planck equation was developed and numerically solved to model vesicle trajectories under time-harmonic drift. Computational simulations were conducted to systematically assess the influence of key electric field parameters—including phase, frequency, and intensity—on vesicle displacement and trajectory. The findings demonstrate that frequencies below <span><math><mrow><mn>5</mn><mi>H</mi><mi>z</mi></mrow></math></span> combined with field strengths of 200–2000 V/m can induce substantial directional control of EV motion. Moreover, enhanced directivity was achieved through the application of multi-component electric fields. Overall, this work establishes a theoretical foundation for the external-field-based beam steering of nanoparticles within the framework of MC.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"47 ","pages":"Article 100613"},"PeriodicalIF":4.7,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.nancom.2026.100612
Yesenia Cevallos , Tadashi Nakano , Paola G. Vinueza-Naranjo , Luis Tello-Oquendo , Navinkumar Patil , Santiago Armas , Cristian Vacacela Gomez , Talia Tene , Deysi Inca , Jiri Svozilik
Molecular Communications (MCs) systems exist in nature and have evolved over billions of years. These systems can be found all around and within us. MCs represent a new communication paradigm that plays a crucial role in science, particularly in medical science, by facilitating the diagnosis and treatment of diseases. Emulation of biological processes occurring at the nanoscale has enabled personalized predictions of disease progression. In this context, simulations are useful in MCs due to their unique ability to bridge the gap between theoretical models (that often rely on simplifications and assumptions that may not fully capture the complexities of real-world scenarios) and practical experiments (that are too complex and expensive). Currently, there exists a large number of programming Extensible Markup Language (XML) and simulators for MCs systems that are generally not interoperable with each other, and consequently, simulations cannot be reused, hindering reproducibility of results. To address this challenge, the Institute of Electrical and Electronics Engineers (IEEE) has propelled 1906.1 and 1906.1.1 standards to establish a common framework to simulate and subsequently to use the programming code for other simulations by other researchers, thereby eliminating the heterogeneity and programming code incompatibility. These standards establish Network Simulator-3 (NS-3) as the simulation tool and provide an MC example that considers a MCs system using On–Off Keying (OOK) modulation, where molecules displacement are modeled by Brownian motion. In this paper, we extend this example to various MCs scenarios using diverse types of modulation at the transmitter, different physical propagation characteristics in communications channels, and various ways to decode information at the destination in end-to-end systems. The results are compared with analytical expressions to establish the efficacy and fidelity of the simulator.
{"title":"End-to-End Molecular Communications Systems: Simulation and analysis following IEEE 1906.1 and 1906.1.1 standards","authors":"Yesenia Cevallos , Tadashi Nakano , Paola G. Vinueza-Naranjo , Luis Tello-Oquendo , Navinkumar Patil , Santiago Armas , Cristian Vacacela Gomez , Talia Tene , Deysi Inca , Jiri Svozilik","doi":"10.1016/j.nancom.2026.100612","DOIUrl":"10.1016/j.nancom.2026.100612","url":null,"abstract":"<div><div>Molecular Communications (MCs) systems exist in nature and have evolved over billions of years. These systems can be found all around and within us. MCs represent a new communication paradigm that plays a crucial role in science, particularly in medical science, by facilitating the diagnosis and treatment of diseases. Emulation of biological processes occurring at the nanoscale has enabled personalized predictions of disease progression. In this context, simulations are useful in MCs due to their unique ability to bridge the gap between theoretical models (that often rely on simplifications and assumptions that may not fully capture the complexities of real-world scenarios) and practical experiments (that are too complex and expensive). Currently, there exists a large number of programming Extensible Markup Language (XML) and simulators for MCs systems that are generally not interoperable with each other, and consequently, simulations cannot be reused, hindering reproducibility of results. To address this challenge, the Institute of Electrical and Electronics Engineers (IEEE) has propelled 1906.1 and 1906.1.1 standards to establish a common framework to simulate and subsequently to use the programming code for other simulations by other researchers, thereby eliminating the heterogeneity and programming code incompatibility. These standards establish Network Simulator-3 (NS-3) as the simulation tool and provide an MC example that considers a MCs system using On–Off Keying (OOK) modulation, where molecules displacement are modeled by Brownian motion. In this paper, we extend this example to various MCs scenarios using diverse types of modulation at the transmitter, different physical propagation characteristics in communications channels, and various ways to decode information at the destination in end-to-end systems. The results are compared with analytical expressions to establish the efficacy and fidelity of the simulator.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"47 ","pages":"Article 100612"},"PeriodicalIF":4.7,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-05DOI: 10.1016/j.nancom.2026.100611
S. Divya , S. Anila
Wireless technology of the fifth generation has made great strides and thereby increased the need for compact antennas with better electromagnetic performance and less complex design. In this aspect, the midband spectrum (1–6 GHz) is particularly attractive due to its trade-off between bandwidth and area covered. However, in traditional approaches, parametric design is limited by overload of computation and design inefficiency. This research introduces a Multi-notch Metasurface Fractal Antenna (MMFA) based on an optimized iterative neural network for midband applications of the fifth generation. The suggested design uses a hybrid geometry of forward and inverted pyramidal patches combined with a modified ground plane and a metasurface superstrate with Rectangular Split-Ring Resonators (RSRRs). The Reinforced Iterative Neural network-based function System (RINS) is employed to physically optimize the parameters of the antenna for improved return loss, gain, voltage standing wave ratio, and efficiency throughout the UNII-1 band. The RINS framework leverages surrogate modeling with gorilla troops optimization and puma hiking optimization for hyperparameter tuning, which results in a significant cut in simulation burden. Simulations and measured data reveal excellent performance with a peak return loss of –55.6 dB and a gain over 7.12 dBi. The assessment of RINS predictions compared to target values proves a high prediction accuracy with errors of less than 3%. The incorporation of machine learning into the antenna design process has led to a remarkable performance improvement, shortened design time, and faster arrival at the best configurations.
{"title":"Optimized iterative neural network-based notch fractal metasurface antenna for 5th generation midband applications","authors":"S. Divya , S. Anila","doi":"10.1016/j.nancom.2026.100611","DOIUrl":"10.1016/j.nancom.2026.100611","url":null,"abstract":"<div><div>Wireless technology of the fifth generation has made great strides and thereby increased the need for compact antennas with better electromagnetic performance and less complex design. In this aspect, the midband spectrum (1–6 GHz) is particularly attractive due to its trade-off between bandwidth and area covered. However, in traditional approaches, parametric design is limited by overload of computation and design inefficiency. This research introduces a Multi-notch Metasurface Fractal Antenna (MMFA) based on an optimized iterative neural network for midband applications of the fifth generation. The suggested design uses a hybrid geometry of forward and inverted pyramidal patches combined with a modified ground plane and a metasurface superstrate with Rectangular Split-Ring Resonators (RSRRs). The Reinforced Iterative Neural network-based function System (RINS) is employed to physically optimize the parameters of the antenna for improved return loss, gain, voltage standing wave ratio, and efficiency throughout the UNII-1 band. The RINS framework leverages surrogate modeling with gorilla troops optimization and puma hiking optimization for hyperparameter tuning, which results in a significant cut in simulation burden. Simulations and measured data reveal excellent performance with a peak return loss of –55.6 dB and a gain over 7.12 dBi. The assessment of RINS predictions compared to target values proves a high prediction accuracy with errors of less than 3%. The incorporation of machine learning into the antenna design process has led to a remarkable performance improvement, shortened design time, and faster arrival at the best configurations.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"47 ","pages":"Article 100611"},"PeriodicalIF":4.7,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The field of nanotechnology has experienced rapid growth in recent years, leading to new applications in biomedicine, electronics, energy and the military industry, thus making it one of the most promising interdisciplinary fields. However, significant challenges must be overcome to fully exploit the enormous potential of nanocommunication systems. In this work, we focus on molecular communications based on diffusion, where the physical channel is governed by Fick’s laws of diffusion and the channel-memory effect, leading to destructive interference between past inputs and current signals. To overcome this effect, we initially propose a new mathematical formulation for modeling message reception with particular emphasis on the receiver. As a complementary aspect of the proposed model, we propose a twofold method to enhance the performance of the nanonetwork by increasing the achieved transmission rate. The proposed framework aims to mitigate the channel memory effect on diffusion-based molecular nanonetworks. It does so, by scheduling pulse releases and deactivating information molecules after a certain time interval, rendering them unable to interact with the receiver via the Ligand–Receptor model, extracted from the proposed mathematical formulation. Both methods handle intersymbol interference, allowing the system to exchange messages at higher rates and with a higher reception rate. A number of simulation scenarios were devised to evaluate the performance of the framework in terms of message delivery rate and message error rate. The results demonstrate an almost 33% improvement in the message delivery rate compared to the theoretical limit imposed by the typical pulse width. This offers new prospects to design new communication protocols and improve existing ones, tailored to the Internet of Bio-Nano Things application domain.
{"title":"Intersymbol interference mitigation in biological nanonetworks based on polynomial regression","authors":"Charalampos Metallinos , Grigorios Karagiannakis , Konstantinos Kantelis , Petros Nicopolitidis , Georgios Papadimitriou","doi":"10.1016/j.nancom.2025.100610","DOIUrl":"10.1016/j.nancom.2025.100610","url":null,"abstract":"<div><div>The field of nanotechnology has experienced rapid growth in recent years, leading to new applications in biomedicine, electronics, energy and the military industry, thus making it one of the most promising interdisciplinary fields. However, significant challenges must be overcome to fully exploit the enormous potential of nanocommunication systems. In this work, we focus on molecular communications based on diffusion, where the physical channel is governed by Fick’s laws of diffusion and the channel-memory effect, leading to destructive interference between past inputs and current signals. To overcome this effect, we initially propose a new mathematical formulation for modeling message reception with particular emphasis on the receiver. As a complementary aspect of the proposed model, we propose a twofold method to enhance the performance of the nanonetwork by increasing the achieved transmission rate. The proposed framework aims to mitigate the channel memory effect on diffusion-based molecular nanonetworks. It does so, by scheduling pulse releases and deactivating information molecules after a certain time interval, rendering them unable to interact with the receiver via the Ligand–Receptor model, extracted from the proposed mathematical formulation. Both methods handle intersymbol interference, allowing the system to exchange messages at higher rates and with a higher reception rate. A number of simulation scenarios were devised to evaluate the performance of the framework in terms of message delivery rate and message error rate. The results demonstrate an almost 33% improvement in the message delivery rate compared to the theoretical limit imposed by the typical pulse width. This offers new prospects to design new communication protocols and improve existing ones, tailored to the Internet of Bio-Nano Things application domain.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"47 ","pages":"Article 100610"},"PeriodicalIF":4.7,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1016/j.nancom.2025.100609
Wenxuan Hui , Pengfeng Hou , Xiufang Ren
In the biological world, signal transduction plays a crucial role in coordinating cellular activities, maintaining homeostasis, and responding to the environment. In this paper, we first introduce the channel modeling of the intensity-driven signal transduction. We then show how to obtain the independent and identically distributed capacity and the feedback capacity for the Channel-Rhodopsin-2 receptor. We reveal that the non-feedback capacity of this channel equals its feedback capacity. Moreover, we give the upper bound of the capacity and provide a general method to maximize the directed information rate to obtain the optimal input distribution. Finally, simulation results are presented to confirm our analysis.
{"title":"Capacity of the intensity-driven signal transduction channel with and without feedback","authors":"Wenxuan Hui , Pengfeng Hou , Xiufang Ren","doi":"10.1016/j.nancom.2025.100609","DOIUrl":"10.1016/j.nancom.2025.100609","url":null,"abstract":"<div><div>In the biological world, signal transduction plays a crucial role in coordinating cellular activities, maintaining homeostasis, and responding to the environment. In this paper, we first introduce the channel modeling of the intensity-driven signal transduction. We then show how to obtain the independent and identically distributed capacity and the feedback capacity for the Channel-Rhodopsin-2 receptor. We reveal that the non-feedback capacity of this channel equals its feedback capacity. Moreover, we give the upper bound of the capacity and provide a general method to maximize the directed information rate to obtain the optimal input distribution. Finally, simulation results are presented to confirm our analysis.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"47 ","pages":"Article 100609"},"PeriodicalIF":4.7,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145750054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-07DOI: 10.1016/j.nancom.2025.100608
Md. Siam Uddin , Joheb Muhammad Tanzeer Sayeed , Md Abu Talha , Shameem Ahmad , Md. Mehedi Hasan Monna
Long-distance quantum communication faces significant challenges due to the decay of quantum entanglement over distance and the limitations of direct quantum transmission. Traditional quantum repeater systems struggle with scalability, and resource demands. This paper presents an optimized quantum repeater system for entanglement distribution, utilizing Grover’s algorithm to enhance qubit probability amplitudes and increase entanglement probability. Most importantly, the system can automatically select a qubit state using an oracle and boost its probability through the diffusion process, thereby improving communication performance. The system initializes qubits in superposition using Hadamard gates, followed by entanglement through controlled-X (CNOT) gates. Grover’s Oracle and diffusion functions are employed to amplify the probability of target qubit states and optimize entanglement swapping via Bell State Measurements (BSM) for long-distance communication. Simulation results using the Qiskit library show a 93 % increase in target qubit probability amplitude and a 0.46 increase in entanglement probability for the state α|00,101⟩ + β|11,010⟩. Comparative analysis reveals that the proposed design outperforms existing quantum repeaters by achieving higher entanglement probability while addressing scalability and efficiency concerns in long-distance quantum communication.
{"title":"Grover enhanced quantum repeater system with 8-qubit optimization","authors":"Md. Siam Uddin , Joheb Muhammad Tanzeer Sayeed , Md Abu Talha , Shameem Ahmad , Md. Mehedi Hasan Monna","doi":"10.1016/j.nancom.2025.100608","DOIUrl":"10.1016/j.nancom.2025.100608","url":null,"abstract":"<div><div>Long-distance quantum communication faces significant challenges due to the decay of quantum entanglement over distance and the limitations of direct quantum transmission. Traditional quantum repeater systems struggle with scalability, and resource demands. This paper presents an optimized quantum repeater system for entanglement distribution, utilizing Grover’s algorithm to enhance qubit probability amplitudes and increase entanglement probability. Most importantly, the system can automatically select a qubit state using an oracle and boost its probability through the diffusion process, thereby improving communication performance. The system initializes qubits in superposition using Hadamard gates, followed by entanglement through controlled-X (CNOT) gates. Grover’s Oracle and diffusion functions are employed to amplify the probability of target qubit states and optimize entanglement swapping via Bell State Measurements (BSM) for long-distance communication. Simulation results using the Qiskit library show a 93 % increase in target qubit probability amplitude and a 0.46 increase in entanglement probability for the state α|00,101⟩ + β|11,010⟩. Comparative analysis reveals that the proposed design outperforms existing quantum repeaters by achieving higher entanglement probability while addressing scalability and efficiency concerns in long-distance quantum communication.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"47 ","pages":"Article 100608"},"PeriodicalIF":4.7,"publicationDate":"2025-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-09DOI: 10.1016/j.nancom.2025.100598
Anshu Mala, Sanjoy Mandal
This study introduces a novel micro-optical ring resonator (MORR) structure designed to enhance filtering efficiency and channel capacity in dense wavelength-division multiplexing (DWDM) systems. The proposed design integrates two asymmetrical triple-ring multibus systems, effectively cascading three asymmetric ring-based MORRs with multiple output ports (1 × 2) to form a (1 × 4) bus configuration. The performance of the proposed MORR structures is mathematically modelled using the delay line approach in the Z-domain, with frequency response characteristics analyzed in MATLAB. The system is further designed and simulated using OptiFDTD software, where directional coupler design and field distribution analysis are also conducted. The frequency response of the designed MORRs is analyzed using OptiFDTD software and cross-verified with MATLAB simulations. The computed FSR from both methods shows a strong correlation, indicating high accuracy. Additionally, OptiSystem 18 is employed to simulate the system using an eye diagram analyzer, ensuring a noise-free model. The results demonstrate a high-quality signal with a low bit error rate (BER) and a Q-factor exceeding 20 at each output bus. This cascading approach significantly enhances signal processing efficiency, reduces crosstalk, and increases the number of output channels, thereby boosting data capacity in communication networks.
{"title":"Cascaded asymmetrical triple-ring multibus system: Modelling and performance analysis","authors":"Anshu Mala, Sanjoy Mandal","doi":"10.1016/j.nancom.2025.100598","DOIUrl":"10.1016/j.nancom.2025.100598","url":null,"abstract":"<div><div>This study introduces a novel micro-optical ring resonator (MORR) structure designed to enhance filtering efficiency and channel capacity in dense wavelength-division multiplexing (DWDM) systems. The proposed design integrates two asymmetrical triple-ring multibus systems, effectively cascading three asymmetric ring-based MORRs with multiple output ports (1 × 2) to form a (1 × 4) bus configuration. The performance of the proposed MORR structures is mathematically modelled using the delay line approach in the Z-domain, with frequency response characteristics analyzed in MATLAB. The system is further designed and simulated using OptiFDTD software, where directional coupler design and field distribution analysis are also conducted. The frequency response of the designed MORRs is analyzed using OptiFDTD software and cross-verified with MATLAB simulations. The computed FSR from both methods shows a strong correlation, indicating high accuracy. Additionally, OptiSystem 18 is employed to simulate the system using an eye diagram analyzer, ensuring a noise-free model. The results demonstrate a high-quality signal with a low bit error rate (BER) and a Q-factor exceeding 20 at each output bus. This cascading approach significantly enhances signal processing efficiency, reduces crosstalk, and increases the number of output channels, thereby boosting data capacity in communication networks.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"46 ","pages":"Article 100598"},"PeriodicalIF":4.7,"publicationDate":"2025-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-17DOI: 10.1016/j.nancom.2025.100597
Ritika Sharma, Mayank Kumar Rai, Rajesh Khanna
This paper presents a more accurate diameter-dependent model based on a Log-Normal (Log-N) distribution, addressing the limitations of previous normal distribution models that can produce unrealistic negative CNT diameters. The model aligns closely with experimental data, with only a 1.1 % deviation. The study explores the circuit parameters and the performance of CNT bundles and CuCNT composite interconnects specifically within the subthreshold regime, where ultra-low-power operation is essential. Design optimizations enhance the electrical performance of CNT bundle interconnects by taking into account the effects of dielectric surface roughness and structural defects. Results indicate that optimized CuCNT composites reduce average crosstalk delay by 79.36 % and 45.41 % on rough and smooth substrates, respectively. The study further examines the impact of CNT count and aspect ratio scaling, showing that both optimized CNT bundles and CuCNT composites significantly improve subthreshold performance metrics. The optimized CuCNT composite interconnect achieves superior crosstalk delay reduction, bandwidth, power delay product, and stability, making it ideal for future low-power VLSI applications.
{"title":"Enhancing subthreshold interconnect performance with log-normal distribution model: A study of CNT bundles and CuCNT composites","authors":"Ritika Sharma, Mayank Kumar Rai, Rajesh Khanna","doi":"10.1016/j.nancom.2025.100597","DOIUrl":"10.1016/j.nancom.2025.100597","url":null,"abstract":"<div><div>This paper presents a more accurate diameter-dependent model based on a Log-Normal (Log-N) distribution, addressing the limitations of previous normal distribution models that can produce unrealistic negative CNT diameters. The model aligns closely with experimental data, with only a 1.1 % deviation. The study explores the circuit parameters and the performance of CNT bundles and CuCNT composite interconnects specifically within the subthreshold regime, where ultra-low-power operation is essential. Design optimizations enhance the electrical performance of CNT bundle interconnects by taking into account the effects of dielectric surface roughness and structural defects. Results indicate that optimized CuCNT composites reduce average crosstalk delay by 79.36 % and 45.41 % on rough and smooth substrates, respectively. The study further examines the impact of CNT count and aspect ratio scaling, showing that both optimized CNT bundles and CuCNT composites significantly improve subthreshold performance metrics. The optimized CuCNT composite interconnect achieves superior crosstalk delay reduction, bandwidth, power delay product, and stability, making it ideal for future low-power VLSI applications.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"46 ","pages":"Article 100597"},"PeriodicalIF":4.7,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-16DOI: 10.1016/j.nancom.2025.100596
S.R. Preethi , P. Chinniah , P. Ezhilarasi , T.R. Vijaya Lakshmi
Tongue characteristics reflect health conditions. In the context of emerging IoT healthcare, automated tongue image analysis is essential for accurate disease classification and diagnosis. Existing challenges include imaging variations, preprocessing issues, poor multiclass accuracy, IoT integration challenges and security concerns. To overcome these complications, Biomedical Tongue Colour Image Analysis using Optimized Quantum Self-Attention Neural Network for Disease Diagnosis and Classification in Internet of Things (BM-TCIA-QS-ANN) is proposed. Here, the input images are taken from tongue image dataset and type 2 diabetes mellitus tongue dataset. The gathered input images are pre-processed using Maximum Correntropy Quaternion Kalman Filtering (MCQ-KF) is employed to decrease noise and enhance the image quality. After preprocessing, the images are fed into Synchro-Transient-Extracting Transform (STET) to extract geometric and texture features like smaller half distance, center distance, circle area, square area, triangle area, energy, entropy, contrast, and homogeneity. Then the extracted features are fed into Quantum Self-Attention Neural Network (QS-ANN) for classifying the tongue images as healthy, Erosive Gastritis (EG), Chronic Gastritis (CG), Nephrotic Syndrome (NS), Diabetes Mellitus (DM), Nephritis (NT), Gastritis Verrucosa (GV), and Coronary Heart disease (CH) in the tongue image dataset and diabetes and non-diabetes in the type 2 diabetes mellitus tongue database. To enhance accuracy, the Pelican Optimization Algorithm (POA) is utilized to optimize QS-ANN parameters, ensuring precise tongue colour image analysis disease classification. The proposed BM-TCIA-QS-ANN technique is implemented in Python. The BM-TCIA-QS-ANN method achieves superior performance with 99.42 % accuracy, 98.34 % precision, and 98.12 % recall, outperforming existing techniques such as TDM-SE-ResNet50-GD, TD-CTLNTI-DCNN, and TRTS-DenseNet-IC respectively.
{"title":"Optimized quantum self-attention neural network for biomedical tongue colour image analysis disease diagnosis and classification in Internet of Things","authors":"S.R. Preethi , P. Chinniah , P. Ezhilarasi , T.R. Vijaya Lakshmi","doi":"10.1016/j.nancom.2025.100596","DOIUrl":"10.1016/j.nancom.2025.100596","url":null,"abstract":"<div><div>Tongue characteristics reflect health conditions. In the context of emerging IoT healthcare, automated tongue image analysis is essential for accurate disease classification and diagnosis. Existing challenges include imaging variations, preprocessing issues, poor multiclass accuracy, IoT integration challenges and security concerns. To overcome these complications, Biomedical Tongue Colour Image Analysis using Optimized Quantum Self-Attention Neural Network for Disease Diagnosis and Classification in Internet of Things (BM-TCIA-QS-ANN) is proposed. Here, the input images are taken from tongue image dataset and type 2 diabetes mellitus tongue dataset. The gathered input images are pre-processed using Maximum Correntropy Quaternion Kalman Filtering (MCQ-KF) is employed to decrease noise and enhance the image quality. After preprocessing, the images are fed into Synchro-Transient-Extracting Transform (STET) to extract geometric and texture features like smaller half distance, center distance, circle area, square area, triangle area, energy, entropy, contrast, and homogeneity. Then the extracted features are fed into Quantum Self-Attention Neural Network (QS-ANN) for classifying the tongue images as healthy, Erosive Gastritis (EG), Chronic Gastritis (CG), Nephrotic Syndrome (NS), Diabetes Mellitus (DM), Nephritis (NT), Gastritis Verrucosa (GV), and Coronary Heart disease (CH) in the tongue image dataset and diabetes and non-diabetes in the type 2 diabetes mellitus tongue database. To enhance accuracy, the Pelican Optimization Algorithm (POA) is utilized to optimize QS-ANN parameters, ensuring precise tongue colour image analysis disease classification. The proposed BM-TCIA-QS-ANN technique is implemented in Python. The BM-TCIA-QS-ANN method achieves superior performance with 99.42 % accuracy, 98.34 % precision, and 98.12 % recall, outperforming existing techniques such as TDM-SE-ResNet50-GD, TD-CTLNTI-DCNN, and TRTS-DenseNet-IC respectively.</div></div>","PeriodicalId":54336,"journal":{"name":"Nano Communication Networks","volume":"46 ","pages":"Article 100596"},"PeriodicalIF":4.7,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1016/j.nancom.2025.100595
Nuriddin Safoev , Madjit Karimov , Seyed-Sajad Ahmadpour , Muhammad Zohaib , Komil Tashev , Suhaib Ahmed
The Internet of Things (IoT) is a propelling technological shift that enables seamless networking between billions of physical devices across healthcare sectors, agriculture, smart cities, and industrial production lines. By integrating embedded sensors, actuators, and communication modules, IoT systems can gather real-time data, leading to better operational decisions and improved efficiency in healthcare systems. The rapid growth of IoT devices creates three main operational challenges related to power usage, efficiency, and thermal management requirements. The demand for more efficient, compact, high-speed, and energy-efficient devices poses significant challenges for these systems. Traditional complementary metal-oxide-semiconductor (CMOS)-based architectures struggle to meet these demanding requirements, representing a major barrier to the development of reliable and scalable next-generation IoT systems. This research demonstrates Quantum-Dot Cellular Automata (QCA) nanotechnology as an alternative solution because it performs logical operations through electron positioning rather than conventional current flow. This paper proposes a modified version of a QCA-based multiplexer design (MUX) since digital logic systems require these signal routing elements for operation. The fundamental 2:1 MUX is established using QCA cell-interaction principles, and then 4:1 and 8:1 QCA MUXs are designed through hierarchical expansion. The suggested modified MUX devices operate on a compact scale with minimal cells to reduce the occupied area compared to current MUX designs. The research outcomes demonstrate that QCA circuits hold promising potential for creating energy-saving, powerful, and scalable computational platforms for future IoT healthcare systems.
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