With the advancement of flexible electronics and machine learning (ML), the collection and analysis of athletic big data using self-powered sensors have become increasingly important in intelligent sports. However, accurate quantification of the rotation direction, a critical parameter in ball games, remains largely underexplored. This study proposes an ML-assisted, intelligent motion-feedback table tennis paddle integrated with a triboelectric nanogenerator (TENG) for simultaneous velocity and rotation direction sensing. By leveraging a well-intercalated MXene/bacterial cellulose (MXBC) composite thin film, the developed sensor exhibits improved tensile strength, excellent conductivity, good processability, and lightweight characteristics. Consequently, the MXBC-based TENG generates distinct and rich feature signals corresponding to rotational motions, enabling its use as a self-powered intelligent feedback sensor. To enhance detection sensitivity and accuracy, a hybrid long short-term memory network–support vector machine (LSTM–SVM) model is constructed, coupled with effective denoising technique. Using the optimized LSTM–SVM modal, the proposed sensor achieves table tennis ball rotation direction and velocity recognition with an accuracy of 99.8%, representing a 48.5% improvement over the conventional SVM method. This study is the first to achieve self-powered rotation direction detection in table tennis, demonstrating significant potential for ball sports training and opening new avenues for the advancement of intelligent sports.

Technologies for evaporation-driven electricity generation and solar-driven steam generation exhibit significant potential for addressing energy crises and freshwater shortages. Nevertheless, it is still a challenge to develop multifunctional materials for efficient energy generation and seawater desalination via economical and simple methods. Here, we propose a Chinese ink-coated viscose fiber composite (Ink@VF), suitable for direct applications in evaporation-driven electricity generators (EEGs) and solar-driven steam generators (SSGs). The Ink@VF prepared by a simple dip-dyeing method exhibits excellent mechanical properties (Young’s modulus of 18.1 GPa), hydrophilicity, electrical conductivity (36.51 Ω/sq), and photothermal conversion properties. Based on the synergy of water evaporation, capillary effect, and electric double layer (EDL) electrokinetic effect, the Ink@VF-based EEG can achieve a maximum open-circuit voltage (V_oc) of 0.65 V and an optimal power density of 43.72 mW/m² with 1 mol/L NaCl solution. It can also be integrated in series to develop a self-powered bracelet. Simultaneously, the evaporation rate and solar energy conversion efficiency of the Ink@VF-based SSG can reach 1.32 kg/(m²·h) and 84.9% under 1 sun irradiation, respectively. Through utilizing the evaporation-condensation mechanism, it can achieve freshwater generation at a rate of 1.49 kg/(m²·h) and metal ion removal in excess of 99.9%. This study provides a low-cost and efficient solution to the energy crisis and freshwater shortage in resource-poor remote areas by utilizing inexhaustible natural resources.