Acta Energiae Solaris Sinica•2026•DOI: 10.19912/j.0254-0096.tynxb.202608_9734
This study addresses the motion response of a taut-moored wind turbine supported by a four-bucket foundation under wave loading. A 1:100 scale physical model was tested in a wave flume to systematically investigate the effects of water depth, draft, and anchor distance on the motion response of the four-bucket foundation. The model consists of four buckets (diameter 0.1 m, height 0.2 m) arranged in a square pattern with a center-to-center spacing of 0.25 m, connected by rigid members, with a total mass of 3.4 kg. Mooring lines are steel strands (diameter 2 mm, breaking force 1670 N, elastic modulus 12.04 GPa, tensile stiffness 0.378 MN). Regular waves with a height of 0.02 m (unit wave amplitude 0.01 m) were generated. Results indicate that increasing water depth suppresses the oscillatory motion response. Increasing draft amplifies surge and pitch responses while reducing heave response. Increasing anchor distance enhances heave and pitch motions but reduces surge motion during the slow-drift phase. These findings provide empirical data for optimizing taut mooring configurations for deep-sea floating wind turbine foundations, highlighting the trade-offs between stability and motion attenuation under varying environmental and geometric parameters.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4502-1
Near-infrared-II (NIR-II, 1000-1700 nm) luminescent materials are pivotal for deep-tissue bioimaging and optical communication, yet their performance is often limited by low quantum yields and thermal quenching. Here, we report a thermal-enhanced NIR-II luminescence in Sb3+/Er3+ co-doped Cs3GdCl6 microcrystals synthesized via a modified Bridgman method. Under ultraviolet excitation, the co-doped microcrystals exhibit intense NIR-II emission centered at 1532 nm corresponding to Er3+: 4I13/2 → 4I15/2 transition, with a maximum relative sensitivity of 1.2% K−1 at 303 K. Notably, the integrated NIR-II emission intensity increases by 2.3-fold from 298 K to 373 K, demonstrating anomalous thermal enhancement. This behavior is attributed to the thermally activated energy transfer from Sb3+ sensitizers to Er3+ activators, as confirmed by temperature-dependent photoluminescence spectra and decay kinetics. The energy transfer efficiency reaches 86% at room temperature and further improves with rising temperature. The microcrystals also show excellent photostability, retaining 95% of initial intensity after 120 min continuous UV irradiation. Furthermore, we demonstrate a proof-of-concept wireless optical communication link using the microcrystals as a NIR-II phosphor, achieving a signal-to-noise ratio of 30 dB at 400 Hz modulation frequency. These findings provide a new strategy for designing thermal-enhanced NIR-II luminescent materials and expand their potential in temperature sensing and optical communication.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4322-4
Ultrafast scintillators with low-nanosecond emission are essential for next-generation high-rate X-ray and particle imaging. Although Ce3+-activated scintillators inherently exhibit fast response characteristics, conventional Ce3+-doped hosts rarely achieve low-nanosecond ultrafast decay. Here, we report a high-entropy fluoride scintillator (HEFS), Ce:LaGdCaSrBaF12 (Ce:LGCSB), in the form of bulk single crystals. The severe lattice distortion arising from multi-cation disorder induces exciton localization and effectively suppresses exciton diffusion. Through the rapid relaxation of localized excitons, the high-entropy Ce:LGCSB single crystals deliver a decay time of 1.23 ns with a 94.6% fast-component contribution and without any noticeable slow component. Through first-principles calculations, spectroscopic characterization, and transient dynamics analysis, we reveal that the ultrafast response originates from accelerated Frenkel exciton (FE) recombination enabled by the high-entropy environment. This work establishes entropy-engineered fluorides as promising ultrafast scintillator platforms and proposes a general strategy for extending sluggish diffusion effects to the excitonic scale, offering new opportunities for improving scintillation timing performance.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202509036
Algal-derived phosphorus (P) constitutes a significant fraction in eutrophic lakes, with particulate phosphorus (PP) serving as both a major internal P reservoir and a potential target for P resource recovery. This study proposed a chitosan-coupled electroflotation (CEF) technology for efficient enrichment and recovery of algal-derived P from high-algal water. Using Taihu Lake algae-laden water as the test medium, the effects of chitosan dosage and voltage on the enrichment of different P fractions were systematically evaluated. Results showed that the optimal P enrichment was achieved at a chitosan dosage of 15 mg·L−1, and higher voltages further enhanced the enrichment efficiency. Under optimal conditions, PP accounted for 83.57% of the enriched P, indicating a strong capability for particulate P capture. The mechanism involved chitosan-induced flocculation via charge neutralization and sweep flocculation, while higher voltages increased the positive charge density of chitosan molecules, enhancing charge neutralization and electroflotation. In P release experiments, open conditions significantly promoted the transformation of PP to dissolved P, whereas closed conditions inhibited this process. Additionally, chitosan's antibacterial action and physical retention effectively limited P release. Compared with conventional metal salt coagulants, this method avoids metal ion residues, offering high environmental safety and providing a green and feasible approach for the harmless disposal and resource utilization of algal-derived P in eutrophic lakes.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-4084-1
Alkali metal halides such as KCl are typical insulators with broad bandgaps, exhibiting poor luminescence. Ion doping can enhance their luminescence, but the mechanism of ultrafast diffusion and structural evolution remains unclear. Here, Sb3+ was doped into a KCl matrix via a room-temperature grinding route. Varying Sb3+ concentration induces a structural evolution from KCl:Sb3+ to 0D inorganic metal halides (IMHs) K3SbCl6. The resulting K3SbCl6 exhibits broad-spectrum yellow emission with near-unity photoluminescence quantum yield (PLQY). The luminescence mechanism is attributed to the 3P1→1S0 transition of Sb3+ ions. Furthermore, a room-temperature solid-liquid interface diffusion method enables ultrafast single-crystal growth of K3SbCl6 in only 20 seconds, with stable luminescence. The material demonstrates excellent temperature sensing performance in the 50–310 K range, achieving a maximum relative sensitivity of 9.99%/K. Additionally, K3SbCl6 shows application potential in information encryption, flexible composite fluorescent films, and white light-emitting diodes. This study provides new insights into ultrafast synthesis of high-performance luminescent materials.
SCIENCE CHINA Materials•2025•DOI: 10.1007/s40843-025-3701-1
Organic field-effect transistors (OFETs) based on N2200 donor-acceptor copolymer were fabricated with top-gate bottom-contact architecture. Parametric optimization revealed that a channel length of 150 μm enhances current density while maintaining leakage control. Optimal N2200/poly(methyl methacrylate) (PMMA) concentration ratio of 7/100 mg/mL and annealing at 80 °C for 3 h improved crystallinity and interfacial properties, yielding stable electrical performance. A dataset of 719 experimental data points, surpassing typical TCAD-generated datasets, was used to train convolutional neural network (CNN), back propagation neural network (BPNN), and random forest (RF) models. The CNN achieved R² > 0.9 for all metrics, with R² Vth = 0.95 and R² SS = 0.96. A novel CNN-particle swarm optimization (PSO)-BP hybrid architecture further reduced mean absolute error (MAE) and root mean square error (RMSE) by 15.7% and 14.9% for Vth, 10% and 9% for lg(Ion/Ioff), and 13.5% and 9.5% for SS, respectively. Residual analysis showed that the CNN-PSO-BP model produced the most compact residual distribution, effectively mitigating overfitting and underfitting. This machine learning framework enables autonomous extraction of physical characteristics without predefined formulas, offering a robust pathway for high-throughput device performance tuning.