[article-cris] Sähkötekniikan korkeakoulu / ELEC

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  • Impact of Grid Characteristics on the Damping of Converter-Driven Subsynchronous Oscillation Modes
    (2025) Perttula, Tomi; Sikder, Md Pabel; Seppänen, Janne; Kasmaei, Mahdi Pourakbari
    A4 Artikkeli konferenssijulkaisussa
    This paper studies whether and how grid strength and grid impedance characteristics affect the damping of a critical oscillation mode caused by a large-scale wind farm. Damping can be regarded as one of the most significant grid properties, in terms of power system stability. It is well known that grid strength has a significant impact on the slow converter-driven stability. However, to the best of our knowledge, it is not well documented if grid strength and grid impedance characteristics affect the damping of converter-driven oscillatory modes. The topic is studied using a PSCAD model of a wind farm consisting of average model of grid-following (GFL) Type-4 wind turbines. The main findings provide insight into the impact a wind farm operation point and grid characteristics has on the damping of a converter-driven SSO (subsynchronous oscillation) mode, especially in weak grid conditions. The findings indicate that in weak grid conditions a small change in SCR could result in a rather large change in the damping of critical oscillation mode. This behaviour may cause challenges with power system operation regarding weaker grids with high penetration of IBRs. The findings also suggests that despite the grid impedance characteristics, the wind farm model is more exposed to low-damped SSO events when operated at high capacity. On the contrary, results show that the wind farm is able to operate in really weak grid conditions with decreased capacity while retaining a sufficient damping level.
  • Analysis of Capacity Credit of Wind Power and the Influence of Hydrogen Energy Storage
    (2025) Agostini, Andrea; Jokinen, Ilkka; Lehtonen, Matti; Coppo, Massimiliano
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    With an increasing share of wind power generation, it is crucial to analyze its availability and effect on the reliability of power systems, to maintain a high level of security of supply. Moreover, since the annual generation can vary greatly, long term analysis is required. Thus, this study examined two independent methods for determining the capacity credit of wind power, considering a long period of 18 years. The first method was a time-period-based capacity credit which only considered wind power generation, and the second one a risk-based method, which analyzed the complete power system and its level of reliability. Moreover, with the risk-based method, the analysis considered different installed capacities for wind power and possible hydrogen storage coupled to the wind power. The results from the time-period-based capacity credit determined, that 8.8% and 3.1% of wind power capacity can be expected the be available with 90% and 98% confidence levels, respectively. In addition, with the risk-based method, the ratio between additional load that a system can supply by including wind power and installed wind capacity, decreased from 14.5% to 4.3% when the wind capacity was increased from 5.68 GW to 30 GW. Moreover, coupling an energy storage to the wind power generation improved its utilization and simultaneously the capacity credit by 2.6-4.6 percentage points. Furthermore, to obtain these results, wind power generation was modeled from 2004 to 2021.
  • Nested smoothing algorithms for inference and tracking of heterogeneous multi-scale state-space systems
    (2026) Pérez-Vieites, Sara; Molina-Bulla, Harold; Míguez, Joaquín
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Multi-scale problems, where variables of interest evolve in different time-scales and live in different state-spaces, can be found in many fields of science. Here, we introduce a new recursive methodology for Bayesian inference that aims at estimating the static parameters and tracking the dynamic variables of these kind of systems. Although the proposed approach works in rather general setups, for clarity we analyze the case of a heterogeneous multi-scale model with 3 time-scales (static parameters, slow dynamic state variables and fast dynamic state variables). The proposed scheme, based on a nested filtering methodology of [27], combines three intertwined layers of filtering techniques that approximate recursively the joint posterior probability distribution of the parameters and both sets of dynamic state variables given a sequence of partial and noisy observations. We explore the use of both sequential Monte Carlo schemes and several Kalman filtering techniques in the different layers of the methodology to obtain approximations of the posterior probability distributions of interest. Some numerical results are presented for a stochastic two-scale Lorenz 96 model with unknown parameters.
  • Robotic AI-based Fiber Threading
    (2024) Bettahar, Houari; Zhou, Quan
    A4 Artikkeli konferenssijulkaisussa
    This paper presents our research on robotic AI-fiber threading, offering a comprehensive overview of our findings. We introduce a novel robotic device and innovative approaches for fiber threading, enabling precise fiber pulling with real-time force measurement during both pulling and tensile testing. Our proposed approaches exhibit enhanced consistency, as well as superior strength and toughness when compared to traditional dry and wet spinning approaches. We explore fiber threading across a range of materials with varying viscosities, including high-viscosity materials like solvent-based polychloroprene rubber, and low viscosity materials such as dextran, recombinant spider silk, and regenerated silk fibroin. Additionally, we introduce a novel approach for rapidly improving artificial fiber tensile properties using our robotic fiber-pulling device and Bayesian Optimization (BO) algorithm.
  • Optimal design and modeling of hydrogen-based multi-energy system with solid oxide electrolyzer technology considering efficiency degradation
    (2026-01-15) Hassan, Abubakr; Al-Awami, Ali T.; Li, Zhengmao
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The integration of solid oxide electrolyzer cells (SOECs) in hydrogen-based multi-energy systems offers a promising pathway for efficient and low-emission hydrogen production. However, optimizing system-level economic performance requires a careful balance between electricity imports, waste heat recovery, and on-site generation. This study presents a mixed-integer linear programming (MILP) model for the optimal design and operation of key system components, including the SOEC stack, combined heat and power (CHP) unit, battery energy storage system (BESS), and hydrogen storage. A novel three-state SOEC operation model is introduced to represent thermal inertia and ramp-up limitations, enabling more realistic system-level scheduling and scenario evaluation. Based on this formulation, three scenarios are investigated: (S1) the SOEC’s heat requirement is met entirely by external waste heat, and recovered SOEC heat is reused to meet system thermal demand; (S2) the SOEC receives heat from a CHP unit, but recovered heat still contributes to overall demand; and (S3) all thermal needs are met solely by the CHP unit without heat recovery. Results show that thermal integration significantly enhances profitability, with S1 and S2 outperforming S3 by 19.5% and 15.7%, respectively. To assess environmental performance, the model is evaluated under different grid carbon intensities. Results show that electricity-related emissions play a decisive role, with France’s low-carbon grid enabling up to 87% lower CO2 emissions compared to steam methane reforming (SMR). Furthermore, sensitivity analysis demonstrates that hydrogen and heat prices dominate revenue composition, with hydrogen contributing up to 92% of total revenue under favorable market conditions. Meanwhile, electricity and gas prices significantly influence system profitability, leading to as much as 60% variation in profit. These findings highlight the combined impact of thermal integration, market volatility, and carbon intensity in designing efficient, low-emission, and economically resilient hydrogen-based energy systems.
  • Open-ended coordination for multi-agent systems using modular open policies
    (2025-12) Rother, David; Pajarinen, Joni; Peters, Jan; Weisswange, Thomas H.
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Significant multi-agent advances addressing the challenge of learning policies for acting in ad hoc teamwork have been made. In ad hoc teamwork, a team of agents must cooperate effectively without prior coordination or communication. Many existing approaches, however, struggle to perform well in open environments where the setting can change significantly during deployment. This paper presents a new reinforcement learning approach to tackle collaboration in open environments controlling one agent with a changing number of distinct other agents, each with an individual task. The approach uses policy blending based on an online goal inference module and a collection of learned policies modeling the individual interaction impact between the agent and populations of partners with different tasks. Blending is done using the estimated goals of others and a posterior-based action blending with entropy adjustment and regularization. Our approach addresses issues of existing policy blending mechanisms, such as handling conflicting modes in action distributions leading to oscillation and instability and adapting to uncertain states dynamically. In experiments in two collaborative open environments based on Overcooked and Level-based Foraging, our approach outperforms a baseline learner, trained with the joint reward of all agents, across changes to both agents and tasks. Ablation studies further highlight the importance of our posterior-based blending mechanism to achieve high rewards as well as the provided goal weighting. The proposed approach provides an important step towards the application of reinforcement learning to AI assistance beyond strictly closed worlds and towards more realistic scenarios.
  • Leveraging Maps of Spatial Motion Patterns to Enhance Long-Term Adaptive Trajectory Prediction with Diffusion Models
    (2025) Shi, Junyi; Kucner, Tomasz Piotr
    A4 Artikkeli konferenssijulkaisussa
    Pedestrian trajectory prediction is crucial for human-robot interaction applications. In this paper, we employ maps of spatial motion patterns combined with diffusion models to improve prediction accuracy. Our method projects both input and output trajectories into an embedding space, leveraging spatial motion patterns to bias anchors that represent the general motion flow within corresponding environments. These place-dependent spatial motion patterns are previously learned from prior environmental observations, enabling better adaptation to new surroundings. Diffusion models are then applied to generate multi-modal trajectory predictions based on the anchors. Experimental results demonstrate that our method outperforms existing models in domain adaptation and long-term trajectory prediction, showcasing the effectiveness of maps of spatial motion patterns in adapting to new environments and improving trajectory prediction performance.
  • Front-End Parameter Identification for Performance Optimization and Load Voltage Regulation of Detuned Wireless Power Transfer Systems
    (2025) Zakerian, Ali; Abbasian, Sohrab; Jayathurathnage, Prasad; Roinila, Tomi; Simoes, Marcelo Godoy; Rasilo, Paavo
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The technology of wireless power transfer (WPT) has been in accelerated adoption for charging battery-powered devices, particularly in electric vehicles. The variable coupling coefficient between the transmitter and receiver coils and variable equivalent load resistance are the factors affecting the system’s operation. In addition, it is not feasible in practice to perfectly match the resonance frequencies of transmitter and receiver circuits due to parameter variation, rated component tolerances, and manufacturing mismatches. The authors investigated a new system identification method based on nonlinear fitting in order to improve the issues related to parameter uncertainty. The operation is enhanced by employing a frequency control methodology to regulate the load voltage. The system is optimized for zero voltage switching (ZVS) and low conduction loss by the frequency control algorithm to keep the operation efficient. This article shows a very cost-effective and simple measurement of the transmitter’s current magnitude and detection of parameter changes to achieve the new optimum operating point under the dynamic operating conditions. The effectiveness of the proposed method has been validated in the laboratory with experimental results from a prototype, confirming the theoretical analysis and design.
  • Carrier mobility in crystalline germanium at high injection: experimental characterization of carrier-carrier scattering
    (2026-01-15) Garín, Moisés; Gamel, Mansur; Yli-Koski, Marko; Vähänissi, Ville; Rivera, Gerard; Savin, Hele; Martín, Isidro
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The decay of the sum of electron and hole mobilities, μs = μn+μp, due to carrier-carrier scattering was experimentally investigated in crystalline germanium (Ge) at high-injection conditions. Contactless measurements of the mobility sum as a function of the excess carrier density (Δn) in Ge were obtained using photoconductance decay methods. First, the measurement method was revised and improvements were introduced to ensure that μs(Δn) could be obtained for independent samples with improved accuracy. This method is successfully validated with crystalline silicon and, then, applied to Ge samples of different doping types and resistivity. The analysis of the data suggests that the mobility decay at high injection levels cannot be properly explained with the usual assumption of equal cross section for carrier-carrier and carrier-ion scattering events. Instead, we find the mobility sum due to carrier-carrier scattering to be inversely proportional to Δn according to the expression 8 × 1020·Δn−1 cm2V−1s−1. The limitations and potential error sources of the measurement method are discussed and, finally, the mobility model is used to improve lifetime analysis at high injection, allowing to estimate the ambipolar Auger recombination coefficient at Camb = 7 × 10−31 cm6s−1.
  • Long term multi-wavelength analysis of the flat spectrum radio quasar OP 313
    (2025) Lähteenmäki, A.; Tornikoski, M.; , Fermi Large Area Telescope Collaboration
    A4 Artikkeli konferenssijulkaisussa
    The Flat Spectrum Radio Quasar (FSRQ) OP 313 showed intense γ-ray activity from November 2023 to March 2024, as observed by the Fermi Large Area Telescope (Fermi-LAT). We present a multi-wavelength analysis covering 15 years of Fermi-LAT observations, from August 2008 to March 2024. From the γ-ray light-curve study, we identified different periods of high-state activity, called flaring states. These are compared with the data available from other facilities. The long-term multi-wavelength activity of the source was investigated using a wide dataset extending from radio to the γ-ray bands. We investigated the kinematics of the radio jet to probe the mechanisms producing the galaxy’s flaring activity. This approach helps us to understand the mechanisms involved in particle acceleration inside the jet, and how radiation in different wavelengths is connected.
  • Phase-angle-free harmonic coupling analysis and injection sites identification approach via data-driven regression model of harmonic voltage versus current
    (2025-11) Yao, Jieyu; Yu, Hao; Püvi, Verner; Merlin, Michael; Judge, Paul; Djokic, Sasa
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Harmonic coupling analysis and injection site identification are essential for maintaining reliable power system operation. Conventional approaches rely on detailed system models and synchronised multi-site phase-angle measurements, which are seldom publicly available, and deploying such metering network-wide is impractical. This paper introduces a data-driven approach for harmonic coupling analysis and injection site identification, maintaining high reliability while requiring only limited measurements. The method involves two main steps. First, a Multi-Compression Refined Self-Attention Network (MCReSANet) is used to model the relationship between harmonic voltages and currents in low-voltage (LV) grids. This model does not require phase angle information and supports both deterministic and probabilistic analyses. Second, SHapley Additive exPlanations (SHAP) values are applied to interpret the trained regression model, enabling qualitative assessment of correlation strengths across different harmonic components. The method is validated using two real-world LV datasets. Compared to benchmark models (Convolutional Neural Network (CNN) and Multi-Layer Perceptron (MLP)), the MCReSANet-based model improves accuracy by 10%–20% in both deterministic and probabilistic analysis. In addition, SHAP-based harmonic coupling and injection site analysis using MCReSANet shows more stable and interpretable results with lower noise levels than CNN and MLP, across both single and multiple site applications.
  • STeF-LSTM: A Hybrid Framework Integrating Periodic and Sequential Modeling for Mapping Motion Patterns
    (2025) Yan, Zhibin; Shi, Junyi; Kucner, Tomasz Piotr
    A4 Artikkeli konferenssijulkaisussa
    Human awareness is crucial for autonomous robotic systems to safely and efficiently interact with people in shared environments. However, reliably modeling human movements over extended periods poses substantial challenges due to human behavior's inherent complexity. This paper introduces STeF-LSTM, a novel hybrid predictive framework that integrates the strengths of Frequency Map Enhancement (FreMEn) for periodic pattern modeling and Long Short-Term Memory (LSTM) networks for capturing sequential dependencies. By combining FreMEn's frequency-domain representation to encode long-term rhythmic patterns and LSTM's robust short-term sequential learning capabilities, the proposed method addresses the limitations of each standalone approach. Evaluations with real-world pedestrian datasets demonstrate significant improvements in prediction accuracy and generalization. STeF-LSTM reduces pattern prediction divergence error by approximately 50%. Further, if the model is applied for motion prediction, the displacement errors decrease by around 7% compared to state-of-the-art methods like CLiFF-LHMP. These results highlight the value of integrating periodic and sequential modeling for robust long-term human motion pattern forecasting, improving navigation, planning, and collaboration in autonomous robotic deployments.
  • Unmanned Aerial Vehicle-Based Cyberattacks on Microgrids
    (2025) Zhao, Alexis P.; Li, Shuangqi; Li, Zhengmao; Ma, Zixiao; Huo, Da; Hernando-Gil, Ignacio; Alhazmi, Mohannad
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The increasing reliance on Networked Microgrids (NMGs) for decentralized energy management introduces unprecedented cybersecurity risks, particularly in the context of False Data Injection Attacks (FDIA). While traditional FDIA studies have primarily focused on network-based intrusions, this work explores a novel cyber-physical attack vector leveraging Unmanned Aerial Vehicles (UAVs) to execute sophisticated cyberattacks on microgrid operations. UAVs, equipped with communication jamming and data spoofing capabilities, can dynamically infiltrate microgrid communication networks, manipulate sensor data, and compromise power system stability. This paper presents a multi-objective optimization framework for UAV-assisted FDIA, incorporating Non-dominated Sorting Genetic Algorithm III (NSGA-III) to maximize attack duration, disruption impact, stealth, and energy efficiency. A comprehensive mathematical model is formulated to capture the intricate interplay between UAV operational constraints, cyberattack execution, and microgrid vulnerabilities. The model integrates flight path optimization, energy consumption constraints, signal interference effects, and adaptive attack strategies, ensuring that UAVs can sustain long-duration cyberattacks while minimizing detection risk. Results indicate that UAV-assisted cyberattacks can induce power imbalances of up to 15%, increase operational costs by 30%, and cause voltage deviations exceeding 0.10 p.u.. Furthermore, analysis of attack success rates vs. detection mechanisms highlights the limitations of conventional rule-based anomaly detection, reinforcing the need for adaptive AI-driven cybersecurity defenses. The findings underscore the urgent necessity for advanced intrusion detection systems, UAV tracking technologies, and resilient microgrid architectures to mitigate the risks posed by airborne cyber threats.
  • The EnVisS fish-eye camera for the Comet Interceptor ESA mission: design and performance
    (2025) Deppo, Vania Da; Senter, Lara; Corte, Vincenzo Della; Zuppella, Paola; Lara, Luisa M.; Castro, José M.; Gutierrez, Pedro J.; Fiocco, Lorenzo G.; Alimenti, Alessandro; Tofani, Beatrice; Gabrieli, Riccardo; Impiccichè, Giuseppe; Dami, Michele; Tommasi, Leonardo; Verzegnassi, Fulvia; Martinez-Navajas, Ignacio; Naletto, Carmen; Chioetto, Paolo; Cocola, Lorenzo; Frassetto, Fabio; Moualla, Lama; Jimenez, Jaime; Mazuecos, Alvaro; Bertini, Ivano; Fulle, Marco; Tubiana, Cecilia; Rotundi, Alessandra; Gomez, Juan Carlos; Guirado, Daniel; Moreno, Fernando; Muñoz, Olga; Bagnulo, Stefano; Jones, Geraint; Praks, Jaan
    A4 Artikkeli konferenssijulkaisussa
    EnVisS (Entire Visible Sky) is a fish-eye camera designed to fly on the first European Space Agency Fast mission, i.e. Comet Interceptor. The Comet Interceptor spacecraft suite consists of a mother spacecraft (A) plus two probes (B1 and B2), and it is expected to be launched by the end of 2029. The mission aims to explore a long-period comet, possibly entering the inner Solar System for the first time. The scientific goal of this mission is to study the composition, shape and morphology of both the nucleus and the surrounding coma of the target. Comet Interceptor will provide new insights into the formation and evolution of the Solar System in its early age [1]. The EnVisS camera will be placed on the B2 spinning probe designed to venture near the comet through a 20-hour fly-by. The task of the camera is to image, in push-frame mode, the whole comet coma in the visible spectrum (wavelength range 550-800 nm) and characterize the comet dust environment, including its polarimetric properties. This work will begin by presenting the scientific requirements for the instrument and the technical solutions adopted to meet them, providing an overall view of the design of the instrument and its sub-systems. A discussion will follow on the current status of the instrument development and on the test campaign performed on a laboratory breadboard of EnVisS, particularly focusing on the detector characterization.
  • Design of Aperture-coupled Vivaldi-antenna Array with Scan-range-improving Parasitic Resonators for Ka-band
    (2025) Bergman, Jan H.S.; Heino, Mikko; Ala-Laurinaho, Juha; Riihonen, Taneli; Valkama, Mikko; Viikari, Ville
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    We present a linear Vivaldi-antenna array with a misalignment-robust non-galvanic transition and scan-range-improvingparasitic resonators for 5G FR2-1 base-station applications. The array covers most of the Ka-band (26.5–40 GHz) on a scan range of ±60◦ with a total active reflection coefficient of below −10 dB and a scan gain of above 10 dBi. Furthermore, the parasitic resonators increase the scan range to ±85◦ between 30 and 35 GHz. A prototype of the array is measured and the performance is confirmed to coincide well with the simulations.
  • Meta Distribution of the SIR in a Narrow-Beam LEO Uplink
    (2025) Angervuori, Ilari; Haenggi, Martin; Wichman, Risto
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    We focus on stochastic geometry analysis of a low Earth orbit (LEO) narrowband terrestrial-satellite uplink with satellite base stations (SBSs) in a uniform constellation equipped with narrow Gaussian beams. The served and interfering omnidirectional user equipments (UEs) are distributed on the Earth’s surface according to a homogeneous Poisson point process (HPPP) with Nakagami faded signals. This study presents a detailed but comprehensive mathematical analysis of several key metrics: the signal-to-interference ratio (SIR), the SIR meta distribution (MD), the signal-to-interference-plus-noise ratio (SINR), and the average throughput. Many results are presented in simple analytical and closed forms containing more insight than the expressions proposed in prior works. The results indicate an optimal UE density depending on the altitude, elevation angle, and the width of the antenna gain, maximizing the average throughput. However, this optimal density leads to a significant variance in the user experience regarding link quality (i.e., the users are not treated fairly).
  • Shared-optical-path VLBI frequency phase transfer from 86 to 258 GHz on an 8600km baseline: Demonstrated with the APEX and IRAM 30m telescopes
    (2025-09-01) Zhao, G. Y.; Roy, A. L.; Wagner, J. F.; Donoso, E.; Torne, P.; Ros, E.; Lindqvist, M.; Lobanov, A. P.; Ramakrishnan, V.; Krichbaum, T. P.; Rottmann, H.; Zensus, J. A.; Pérez-Beaupuits, J. P.; Klein, B.; Menten, K. M.; Ricken, O.; Reyes, N.; Sánchez, S.; Ruiz, I.; Durán, C.; John, D.; Santaren, J. L.; Sánchez-Portal, M.; Bremer, M.; Kramer, C.; Schuster, K. F.; Rioja, M. J.; Dodson, R.
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Context. The receiver N3AR operating at a frequency range between 67 and 116 GHz was commissioned at the APEX telescope in October 2024. It adds a new low-frequency band for APEX, with the capability of simultaneous dual-frequency observations using a dichroic beamsplitter. The 3 mm receiver also allows APEX to join the existing 3 mm global very long baseline interferometry (VLBI) network. Aims. One of our commissioning goals was to perform simultaneous dual-band VLBI observations at 86 and 258 GHz using receivers with shared optical paths (SOPs) to correct the atmospheric phase fluctuations using the frequency phase transfer (FPT) technique. This was possible together with the IRAM 30 m telescope, which has already developed such a capability. We aimed to verify the expected phase coherence and sensitivity improvement at the higher frequency achievable by applying FPT. Methods. With the dual-band, single baseline data, we applied the FPT method, which uses the lower-frequency data to correct the simultaneously observed higher-frequency data. We evaluated the improvement compared to the conventional single-band observing mode by analyzing the coherence factor in the higher-frequency data. Results. Our results show that the phase fluctuations at the two bands correlate well. After applying FPT, the interferometric phases at the higher frequency vary much less, and the coherence factor is significantly improved. Conclusions. Our analysis confirms the feasibility of applying FPT to frequencies above 250 GHz with SOP receivers. Future observations in this mode could dramatically improve the sensitivity and imaging fidelity of high-frequency VLBI.
  • Vertically Stacked Boron Nitride/Graphene Heterostructure for Tunable Antiresonant Hollow-Core Fiber
    (2025-09-17) Cheng, Yi; Cheng, Xu; Xie, Jin; Cui, Guang; Cheng, Shuting; Li, Xiao; Gan, Jiajie; Dong, Han; Yang, Yuyao; Yu, Wentao; Chen, Ke; Hong, Hao; Zhou, Xu; Pang, Meng; Jiang, Xin; Sun, Zhipei; Liu, Kaihui; Liu, Zhongfan
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Incorporating atomically thin two-dimensional (2D) materials with optical fibers expands their potential for optoelectronic applications. Recent advancements in chemical vapor deposition have enabled the batch production of these hybrid fibers, paving the way for practical implementation. However, their functionality remains constrained by the integration of a single 2D material, restricting their versatile performance. Here, we introduce a boron nitride/graphene (BN/Gr) heterostructure in the antiresonant hollow-core fiber (ARF) to modulate its optical resonance and thus enhance graphene nonlinearity by controlling the BN thickness. Hydroxyl-rich methanol is employed to improve the flatness and crystallinity of graphene, promoting the vertical epitaxy of BN with a controllable thickness ranging from 5 to 50 nm. The engineered optical resonance notably tunes the light-graphene interaction within the BN/Gr-ARF, increasing the depth of nonlinear optical modulation from 4% to 10% and enhancing all-optical modulation performance by 75%. Our methodology opens possibilities for tunable optical waveguides via the direct growth of functional 2D material-based heterostructures, offering a robust platform for the development of highly integrated photonic devices.
  • Electrically-Driven Polarized Nano-Light Sources Based on Suspended Graphene Nanoscrolls
    (2025-08-26) Han, Xu; Dai, Yun Yun; Xie, Yong Zhi; Ge, Li Xin; Miao, Tai Min; Fu, Qiang; Xue, Tong Tong; Yang, Long Long; Sun, Zhen Yu; Duan, Zhe Xing; Yan, Jia Hao; Yang, Shi Qi; Fan, Xiao Yue; Zhao, Jing Han; Guo, Zi Hao; Wang, Jia Kai; Shen, Zi Ling; Liu, Xia; Wang, Gang; Du, Luo Jun; Gao, Yu Nan; Chai, Yang; Sun, Zhi Pei; Huang, Yuan; Wang, Ye Liang
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Low-dimensional nanomaterials hold great promise for on-chip light-emitting applications and are expected to profoundly influence the evolution of next-generation photonic chips. Currently, microlasers and light-emitting diodes represent the predominant on-chip integrated light sources. Exploring how to employ low-dimensional materials to realize more miniaturized and controllable light sources remains a key research focus over the past decade. In this work, we demonstrate a high-efficiency nanolight source (NLS) based on graphene nanoscrolls (GNSs), with its emission modulated via an external electric field and device structural design. The GNS NLS features a widely tunable emission spectrum, covering wavelengths from the infrared to the visible range. Besides, we investigated the super-Planckian radiation effect in GNSs, which arises from enhanced absorption in the low-dimensional nanostructure. The theoretical calculations reveal that the absorption coefficient of GNSs in the normal direction is larger than 1, thereby indicating their strong radiative emission according to Kirchhoff's Law of thermal radiation. Furthermore, the emission from GNSs can exhibit fast switching behavior (response time ∼ 75 ms), with the degree of polarization reaching 20% in the visible light range. This work provides important support for the study of the emission characteristics of GNSs and holds profound significance for promoting the development of on-chip integrated NLS technology.
  • Understanding Subterahertz Radio Channels: The Impact of Beamforming on Wireless System Design
    (2025) Zhang, Peize; De Guzman, Mar Francis; Li, Xuhong; Cai, Xuesong; Haneda, Katsuyuki; Tervo, Nuutti; Parssinen, Aarno; Tufvesson, Fredrik; Kyosti, Pekka
    A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Wireless connectivity in the subterahertz (sub-THz) band, spanning from 100 GHz to 300 GHz, is envisioned as an enhanced feature of 6G and beyond. Due to significant propagation losses at these frequencies, the transmission of sub-THz signals relies heavily on high antenna directivity, realized by beamforming. In this article, we present a newly developed sub-THz stored channel model, and perform a realistic evaluation of the impact of beamforming on sub-THz link establishment and data transmission. Unlike the propagation channel between the transmitting and receiving antennas, the radio channel is observed by a pair of beams. Incorporating the impact of beamforming into measured sub-THz propagation channel data enables to gain insights into the key factors that determine, among others, sub-THz beam alignment strategy and waveform design, ultimately enhancing spectral efficiency.