Communications Engineering

Journal: Communications Engineering

Abbreviation

Commun Eng

Publisher

Nature

ISSN

2731-3395

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Publications 1 - 10 of 12

Spike frequency adaptation: bridging neural models and neuromorphic applications
Ganguly, Chittotosh; Bezugam, Sai Sukruth; Abs, Elisabeth; et al. (2024)
Communications Engineering
The human brain’s unparalleled efficiency in executing complex cognitive tasks stems from neurons communicating via short, intermittent bursts or spikes. This has inspired Spiking Neural Networks (SNNs), now incorporating neuron models with spike frequency adaptation (SFA). SFA adjusts these spikes’ frequency based on recent neuronal activity, much like an athlete’s varying sprint speed. SNNs with SFA demonstrate improved computational performance and energy efficiency. This review examines various adaptive neuron models in computational neuroscience, highlighting their relevance in artificial intelligence and hardware integration. It also discusses the challenges and potential of these models in driving the development of energy-efficient neuromorphic systems.
GEMTELLIGENCE: Accelerating gemstone classification with deep learning
Bendinelli, Tommaso; Biggio, Luca; Nyfeler, Daniel; et al. (2024)
Communications Engineering
The value of luxury goods, particularly investment-grade gemstones, is influenced by their origin and authenticity, often resulting in differences worth millions of dollars. Traditional methods for determining gemstone origin and detecting treatments involve subjective visual inspections and a range of advanced analytical techniques. However, these approaches can be time-consuming, prone to inconsistencies, and lack automation. Here, we propose GEMTELLIGENCE, a novel deep learning approach enabling streamlined and consistent origin determination of gemstone origin and detection of treatments. GEMTELLIGENCE leverages convolutional and attention-based neural networks that combine the multi-modal heterogeneous data collected from multiple instruments. The algorithm attains predictive performance comparable to expensive laser-ablation inductively-coupled-plasma mass-spectrometry analysis and expert visual examination, while using input data from relatively inexpensive analytical methods. Our methodology represents an advancement in gemstone analysis, greatly enhancing automation and robustness throughout the analytical process pipeline.
Additive manufacturing of a 3D-segmented plastic scintillator detector for tracking and calorimetry of elementary particles
Weber, Tim; Boyarintsev, Andrey; Kose, Umut; et al. (2025)
Communications Engineering
Plastic scintillators, segmented into small, optically isolated voxels, are used for detecting elementary particles and provide reliable particle identification with nanosecond time resolution. Building large detectors requires the production and precise alignment of millions of individual units, a process that is time-consuming, cost-intensive, and difficult to scale. Here, we introduce an additive manufacturing process chain capable of producing plastic-based scintillator detectors as a single, monolithic structure. Unlike previous manufacturing methods, this approach consolidates all production steps within one machine, creating a detector that integrates and precisely aligns its voxels into a unified structure. By combining fused deposition modeling with an injection process optimized for fabricating scintillation geometries, we produced an additively manufactured fine-granularity plastic scintillator detector with performance comparable to the state of the art, and demonstrated its capabilities for 3D tracking of elementary particles and energy-loss measurement. This work presents an efficient and economical production process for manufacturing plastic-based scintillator detectors, adaptable to various sizes and geometries.
Programming structural and magnetic anisotropy for tailored interaction and control of soft microrobots
Yan, Yimo; Song, Chao; Shen, Zaiyi; et al. (2024)
Communications Engineering
Swarms of soft microrobots controlled by minimally invasive magnetic fields show promise as biomedical agents. The collective behaviour of such swarms, governed by magnetic and hydrodynamic interactions, emerges from the properties of their individual constituents. The introduction of both magnetic and structural anisotropy into microrobots expands the possibilities for tailoring and predetermining interactions and collective behaviours that result. Unfortunately, current methods for large-scale production of soft microrobots, typically result in isotropic properties. Herein, by combining simulation-guided design and droplet-based microfluidics, we present a versatile, high-throughput technique for fabricating soft microrobots with programmable structural and magnetic anisotropy. Such microrobots consist of iron oxide nanoparticles organized into supra-domain structures and entrapped in a hydrogel matrix that can be elongated independently of its magnetic properties. By applying rotating magnetic fields to resulting swarms, distinct collective behaviours are produced, including gas-like formations, variable crystals, and heterogeneous motions.
Preserving privacy and video quality through remote physiological signal removal
Bhutani, Saksham; Elgendi, Mohamed; Menon, Carlo (2025)
Communications Engineering
The revolutionary remote photoplethysmography (rPPG) technique has enabled intelligent devices to estimate physiological parameters with remarkable accuracy. However, the continuous and surreptitious recording of individuals by these devices and the collecting of sensitive health data without users’ knowledge or consent raise serious privacy concerns. Here we explore frugal methods for modifying facial videos to conceal physiological signals while maintaining image quality. Eleven lightweight modification methods, including blurring operations, additive noises, and time-averaging techniques, were evaluated using five different rPPG techniques across four activities: rest, talking, head rotation, and gym. These rPPG methods require minimal computational resources, enabling real-time implementation on low-compute devices. Our results indicate that the time-averaging sliding frame method achieved the greatest balance between preserving the information within the frame and inducing a heart rate error, with an average error of 22 beats per minute (bpm). Further, the facial region of interest was found to be the most effective and to offer the best trade-off between bpm errors and information loss.
Active and integrated electronic metadevices for future telecommunication circuits
Samizadeh Nikoo, Mohammad; Chu, Chenhao; Lin, Boce; et al. (2025)
Communications Engineering
The rise of data-driven demands calls for terahertz-capable circuits, however, semiconductor devices still face performance limitations above 100 GHz, posing a challenge for wireless networks. Electronic metadevice is a concept inspired by optical metamaterials, which was first demonstrated in the form of switches that could challenge the limitations of traditional semiconductor devices. Here we unveil critical aspects of this technology and demonstrate three-terminal active metadevices, which show promise for the next generation of telecommunication circuits. We show near-ideal linear and nonlinear operation of electronic metadevices, approaching the material limits, and by monolithic integration of electronic metadevices, we demonstrate picosecond terahertz switches with low insertion loss and high isolation. We finally present three-terminal metadevices offering parametric amplification and active mixing, which show ultrawideband operation, supporting data-rates exceeding 40 Gbps. Our work provides a solution for future ultrafast electronics with applications in 6 G telecommunications, enabling the development of new functional devices based on the electronic metadevice concept.
Opportunities and challenges for sweat-based monitoring of metabolic syndrome via wearable technologies
Lyzwinski, Lynnette; Elgendi, Mohamed; Shokurov, Alexander V.; et al. (2023)
Communications Engineering
Metabolic syndrome is a prevalent condition in adults over the age of 65 and is a risk factor for developing cardiovascular disease and type II diabetes. Thus, methods to track the condition, prevent complications and assess symptoms and risk factors are needed. Here we discuss sweat-based wearable technologies as a potential monitoring tool for patients with metabolic syndrome. We describe several key symptoms that can be evaluated that could employ sweat patches to assess inflammatory markers, glucose, sodium, and cortisol. We then discuss the challenges with material property, sensor integration, and sensor placement and provide feasible solutions to optimize them. Together with a list of recommendations, we propose a pathway toward successfully developing and implementing reliable sweat-based technologies to monitor metabolic syndrome.
Radiative cooling sorbent towards all weather ambient water harvesting
Zhu, Wenkai; Zhang, Yun; Zhang, Chi; et al. (2023)
Communications Engineering
Emerging atmospheric water harvesting (AWH) technologies hold promise for water supply to underdeveloped regions with limited access to liquid water resources. The prevailing AWH systems, including condensation- or sorption-based, mostly rely on a single mechanism limited by working conditions and inferior performance. Here, we synergistically integrate multiple mechanisms, including thermosorption effect, radiative cooling, and multiscale cellulose-water interactions to improve the water harvesting performance with minimal active energy input over a relative humidity (RH) range between 8% to 100%. The proposed system consists of a scalable and sustainable cellulose scaffold impregnated with hygroscopic lithium chloride (LiCl). Cellulose scaffold and LiCl synergistically interact with water at molecular, nanometer, and micrometer scales, achieving a high yield (2.5–16 kg kg⁻¹ at 60–90% RH). The captured water in return facilitates radiative cooling due to its intrinsically high infrared emissivity. An outdoor batch-mode AWH device shows a water uptake up to 6.75 L kg⁻¹ day⁻¹ with a material cost as low as 3.15–5.86 USD kg⁻¹. A theoretical model is also proposed to elucidate the synergistic AWH mechanisms among cellulose-LiCl-water-energy interaction. This AWH strategy provides a potential solution to water scarcity problems in regions with larger seasonal and climate variations, especially arid areas.
Prediction and control of fracture paths in disordered architected materials using graph neural networks
Karapiperis, Konstantinos; Kochmann, Dennis M. (2023)
Communications Engineering
Architected materials typically rely on regular periodic patterns to achieve improved mechanical properties such as stiffness or fracture toughness. Here we introduce a class of irregular cellular materials with engineered topological and geometrical disorder, which represents a shift from conventional designs. We first develop a graph learning model for predicting the fracture path in these architected materials. The model employs a graph convolution for spatial message passing and a gated recurrent unit architecture for temporal dependence. Once trained on data gleaned from experimentally validated elastoplastic beam finite element analyses, the learned model produces accurate predictions overcoming the need for expensive finite element calculations. We finally leverage the trained model in combination with a downstream optimization scheme to generate optimal architectures that maximize the crack path length and, hence, the associated fracture energy.
Emitting and controlling ultra-low frequency underwater acoustic waves using a marine vibration system with time interfacing
Huang, Xingguo; Shang, Wenqing; Han, Li; et al. (2025)
Communications Engineering
The control and manipulation of waves in optical and/or acoustic science and engineering are widespread. Recently, despite reported studies on high frequency acoustic waves via time modulated media, none of these approaches has demonstrated success with broadband frequency exceeding that of the mechanical system, and all of them were not able to emit ultralow frequency waves. There are both fundamental and practical issues. Achieving ultra-low frequency underwater acoustic wave control via time interfaces remains a major challenge for integrated underwater acoustic devices. Here, we explore the design of a marine vibrator source system based on hydraulic-acoustic energy conversion. The system consists of a hydraulic servo system kept aboard a boat on one side while the other side comprises an underwater vibrator transducer. The transfer of wave energy is a fundamental mechanism for emitting acoustic waves, yet the rules of conventional reaction-mass force intrinsically limit the vibrator force based on the displacement and the acceleration of the reaction mass. We show that this intrinsic limit can be broken for acoustic waves, where the acoustics become controllable by the arrangement of the vibrator system. The marine vibrator acoustic waves open new frontiers in acoustic control and enables diverse focusing and imaging.

Publications 1 - 10 of 12

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