Multiple H-Bonding Cross-Linked Supramolecular Solid-Solid Phase Change Materials for Thermal Energy Storage and Management.

Solid-solid phase change materials (SSPCMs) are considered among the most promising candidates for thermal energy storage and management. However, the application of SSPCMs is consistently hindered by the canonical trade-off between high TES capacity and mechanical robustness. In addition, they suffer from poor recyclability due to chemical cross-linking. Herein, a straightforward but effective strategy for fabricating supramolecular SSPCMs with high latent heat and mechanical strength is proposed. The supramolecular polymer employs multiple H-bonding interactions as robust physical cross-links. This enables SSPCM with a high enthalpy of phase transition (142.5 J g-1 ), strong mechanical strength (36.9 MPa), and sound shape stability (maintaining shape integrity at 120 °C) even with a high content of phase change component (97 wt%). When SSPCM is utilized to regulate the operating temperature of lithium-ion batteries, it significantly diminishes the battery working temperature by 23 °C at a discharge rate of 3 C. The robust thermal management capability enabled through solid-solid phase change provides practical opportunities for applications in fast discharging and high-power batteries. Overall, this study presents a feasible strategy for designing linear SSPCMs with high latent heat and exceptional mechanical strength for thermal management.

A deep learning model adjusting for infant gender, age, height, and weight to determine whether the individual infant suit ultrasound examination of developmental dysplasia of the hip (DDH).

Objective: To examine the correlation between specific indicators and the quality of hip joint ultrasound images in infants and determine whether the individual infant suit ultrasound examination for developmental dysplasia of the hip (DDH). Method: We retrospectively selected infants aged 0-6 months, undergone ultrasound imaging of the left hip joint between September 2021 and March 2022 at Shenzhen Children's Hospital. Using the entropy weighting method, weights were assigned to anatomical structures. Moreover, prospective data was collected from infants aged 5-11 months. The left hip joint was imaged, scored and weighted as before. The correlation between the weighted image quality scores and individual indicators were studied, with the last weighted image quality score used as the dependent variable and the individual indicators used as independent variables. A Long-short term memory (LSTM) model was used to fit the data and evaluate its effectiveness. Finally, The randomly selected images were manually measured and compared to measurements made using artificial intelligence (AI). Results: According to the entropy weight method, the weights of each anatomical structure as follows: bony rim point 0.29, lower iliac limb point 0.41, and glenoid labrum 0.30. The final weighted score for ultrasound image quality is calculated by multiplying each score by its respective weight. Infant gender, age, height, and weight were found to be significantly correlated with the final weighted score of image quality (P < 0.05). The LSTM fitting model had a coefficient of determination (R2) of 0.95. The intra-class correlation coefficient (ICC) for the α and ß angles between manual measurement and AI measurement was 0.98 and 0.93, respectively. Conclusion: The quality of ultrasound images for infants can be influenced by the individual indicators (gender, age, height, and weight). The LSTM model showed good fitting efficiency and can help clinicians select whether the individual infant suit ultrasound examination of DDH.

Artificial Intelligence-Assisted Ultrasound Diagnosis on Infant Developmental Dysplasia of the Hip Under Constrained Computational Resources.

OBJECTIVES: Ultrasound (US) is important for diagnosing infant developmental dysplasia of the hip (DDH). However, the accuracy of the diagnosis depends heavily on expertise. We aimed to develop a novel automatic system (DDHnet) for accurate, fast, and robust diagnosis of DDH. METHODS: An automatic system, DDHnet, was proposed to diagnose DDH by analyzing static ultrasound images. A five-fold cross-validation experiment was conducted using a dataset containing 881 patients to verify the performance of DDHnet. In addition, a blind test was conducted on 209 patients (158 normal and 51 abnormal cases). The feasibility and performance of DDHnet were investigated by embedding it into ultrasound machines at low computational cost. RESULTS: DDHnet obtained reliable measurements and accurate diagnosis predictions. It reported an intra-class correlation coefficient (ICC) on α angle of 0.96 (95% CI: 0.93-0.97), ß angle of 0.97 (95% CI: 0.95-0.98), FHC of 0.98 (95% CI: 0.96-0.99) and PFD of 0.94 (95% CI: 0.90-0.96) in abnormal cases. DDHnet achieved a sensitivity of 90.56%, specificity of 100%, accuracy of 98.64%, positive predictive value (PPV) of 100%, and negative predictive value (NPV) of 98.44% for the diagnosis of DDH. For the measurement task on the US device, DDHnet took only 1.1 seconds to operate and complete, whereas the experienced senior expert required an average 41.4 seconds. CONCLUSIONS: The proposed DDHnet demonstrate state-of-the-art performance for all four indicators of DDH diagnosis. Fast and highly accurate DDH diagnosis is achievable through DDHnet, and is accessible under constrained computational resources.

Solvothermal preparation of Ti3+ self-doped TiO2-x nanotube arrays for enhanced photoelectrochemical performance.

Ti3+ self-doped TiO2-x nanotube arrays (TiO2-x NTs) were prepared by solvothermal treatment in KBH4 ethanol solution followed by calcination, and were characterized by field-emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and UV-vis diffusion reflection spectroscopy (DRS). The photoelectrochemical properties of TiO2-x NTs prepared in different KBH4 concentrations were investigated. The TiO2-x NTs exhibited high visible light response, visible light photocurrent and photoelectrocatalytic activities. The active species and photocatalytic mechanism for the dye degradation were proposed, and the improved photoelectrochemical performance was attributed to the synergistic effect of the narrowed energy gap and enhanced electron transportation. The ability to improve the photoelectrochemical properties of TiO2-x electrode materials should open up new opportunities for high-performance solar cells and photocatalysts.