The distribution of substrate temperature plays a decisive role on the uniformity of polycrystalline diamond films on cemented carbide tools with a long flute, prepared by a hot filament chemical vapor deposition (HFCVD). In this work, the heat dissipation mode at the bottom of tools is a focal point, and the finite volume method (FVM) is conducted to simulate and predict the temperature field of tools, with the various materials of the holder placed under the tools. The simulation results show that the thermal conductivity of the holder affects the temperature difference of the individual tools greatly, but only affects the temperature of different tools at the same XY plane slightly. Moreover, the ceramic holder can reduce the difference in temperature of an individual tool by 54%, compared to a copper one. Afterwards, the experiments of the deposition of diamond films is performed using the preferred ceramic holder. The diamond coatings on the different positions present a highly uniform distribution on their grain size, thickness, and quality.

Nafion, a widely used proton exchange membrane in fuel cells, is a representative perfluorosulfonic acid membrane consisting of a hydrophobic Teflon backbone and hydrophilic sulfonic acid side chains. Its thermal conductivity (k) is critical to fuel cell's thermal management. During fuel cell operation, water molecules inevitably enter Nafion and could strongly affect its k. In this work, we measure the k of Nafion of different water content (λ). Findings reveal that k is significantly low in a vacuum environment characterized as 0.110 W m−1 K−1, but at λ ∼1, a notable increase is observed, reaching 0.162 W m−1 K−1. Moreover, k at λ ≈ 6 is 60% higher than that of λ ∼1. This exceptional k increase is far beyond the theoretical prediction by the effective medium theory that only considers simply physical mixing. Rather this k increase is attributed to the formation of water clusters and channels with increased λ, creating thermal pathways through hydrogen bonding, thereby improving chemical connections within the Nafion structure and augmenting its k. Furthermore, it is observed that Nafion's k reaches the maximum value of 0.256 W m−1 K−1 at λ ≈ 6, with no further increase up to λ ≈ 10.5. This phenomenon is explained by the coalescence of water clusters at λ ≈ 6, forming channels that optimize heat transfer pathways and connections within the Nafion structure. Moreover, the free movement of water molecules within water channels (λ > 6) shows physical alterations in Nafion structure (significant volume increase), which have a lesser impact on k.

Microcrystalline diamond powders are deposited directly by a HFCVD apparatus with adding amounts of trimethyl borate in gas mixture. The study establishes the relationship between the boron...

In biomass estimation based on size-related features, regression models are commonly used to predict fish mass. However, in real-world scenarios, fish are often partially occluded by others, resulting in missing or corrupted features. To address this issue, we propose a robust framework that integrates feature imputation with regression. Missing features are first reconstructed through imputation, followed by regression for biomass prediction. We evaluated various imputation and regression methods and found that the autoencoder achieved the best performance in imputation. Among regression models, SVR, Extra Trees, and MLP performed best in their respective categories. These three models, combined with the autoencoder, were selected to construct the final framework. Experimental results demonstrate that the proposed framework significantly improves performance. For instance, the RMSE of SVR, Extra Trees, and MLP decreased from 21.10 g, 2.49 g, and 18.40 g to 6.53 g, 1.95 g, and 5.09 g, respectively.

Underwater image enhancement (UIE) technology plays a vital role in marine resource exploration, environmental monitoring, and underwater archaeology. However, due to the absorption and scattering of light in underwater environments, images often suffer from blurred details, color distortion, and low contrast, which seriously affect the usability of underwater images. To address the above limitations, a lightweight transformer-based model (LITM) is proposed for improving underwater degraded images. Firstly, our proposed method utilizes a lightweight RGB transformer enhancer (LRTE) that uses efficient channel attention blocks to capture local detail features in the RGB domain. Subsequently, a lightweight HSV transformer encoder (LHTE) is utilized to extract global brightness, color, and saturation from the hue–saturation–value (HSV) domain. Finally, we propose a multi-modal integration block (MMIB) to effectively fuse enhanced information from the RGB and HSV pathways, as well as the input image. Our proposed LITM method significantly outperforms state-of-the-art methods, achieving a peak signal-to-noise ratio (PSNR) of 26.70 and a structural similarity index (SSIM) of 0.9405 on the LSUI dataset. Furthermore, the designed method also exhibits good generality and adaptability on unpaired datasets.