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Non-Newtonian viscous fluids such as yogurt, honey, etc., due to their extremely high viscosity and complex fluidity, remain on food containers after use, where adhesion and staining occurs, which is a great inconvenience and causes a lot of wasted resources. Hydrophobic coatings can be an excellent candidate for eliminating liquid waste. Inexpensive wollastonite nanoparticles were used to build rough micro- and nano-structures, and chitosan was used to emulsify rice bran wax to prepare green and low surface energy emulsions. The above two were mechanically mixed to obtain the hydrophobic emulsion, and coated on the paper surface and heat-treated to prepare the hydrophobic paper. Contact angles up to 157.3°. The coating exhibits good self-cleaning properties for a wide range of non-Newtonian viscous food liquids and shows excellent resistance to repeated machine bending and multiple abrasion damages, while maintaining its hydrophobicity. After 40 cycles of friction, the contact angle is 148.1°, which is still close to 150° and has good hydrophobicity. In addition, the coating has great potential for application to the interior surfaces of various food packages to reduce or even eliminate liquid food residues. [ABSTRACT FROM AUTHOR]

Objective: This study aims to evaluate the mental health of college students who have failed in entrepreneurship by analyzing their electroencephalogram (EEG) signals. Long-term negative emotions are closely related to mental health problems. This study explores how to evaluate the mental health of college students who have failed in entrepreneurship through EEG signals and the use of generative adversarial networks (GANs) to improve classification accuracy. Methods: We first collected EEG data from college students who have failed in entrepreneurship. These data were used to extract multiple features, including time domain features, frequency domain features, and nonlinear features. To improve the accuracy and robustness of the classification model, we introduced GAN. GAN enhances the diversity of the training data set by generating more samples, thereby improving the performance of the EEG signal classification model. This process includes training the generator to generate samples similar to real data and training the discriminator to distinguish between real and generated data. Through this adversarial process, the classification model is continuously optimized. Experimental results show that the EEG signal analysis method based on GAN can effectively classify the long-term emotional state of college students who have failed in entrepreneurship and accurately identify negative emotions such as depression and anxiety. The additional samples generated by GAN significantly improve the classification model's ability to identify emotional states, making the assessment of mental health status more accurate. Conclusion: This study successfully improved the accuracy of EEG signal classification by introducing GAN technology, thus providing an effective tool for evaluating the mental health status of college students who failed in entrepreneurship. This method not only enhances the ability to detect negative emotions of college students but also provides a novel and practical solution for mental health assessment and intervention in colleges and universities, which helps to detect and intervene in potential mental health problems of college students who failed in entrepreneurship as early as possible. [ABSTRACT FROM AUTHOR]

Metastable‐phase intermetallic compounds (IMCs) provide great flexibility to modify the electronic structure and surface coordination environment of metallic catalysts for various reactions. However, the synthesis of metastable‐phase IMCs with high catalytic performance remains a great challenge due to their thermodynamically unstable nature. Here, a wet‐chemical epitaxial growth strategy to synthesize metastable‐phase Pd‐Bi intermetallic nanocrystals (NCs) is reported. β‐Pd3Bi and γ‐Pd5Bi3 intermetallic NCs are epitaxially grown on the templates of face‐centered cubic Pd3Pb nanocubes and hexagonal close‐packed PtBi nanoplates, achieving Pd3Pb@Pd3Bi and PtBi@Pd5Bi3 core–shell NCs, respectively. The obtained Pd3Pb@Pd3Bi NCs possess a mass activity and specific activity of 8.52 A mg−1Pd and 11.59 mA cm−2 for ethanol oxidation reaction, which is 7.5 and 3.6 times as high as those of commercial Pd/C, respectively. Meanwhile, Pd3Pb@Pd3Bi NCs possess superior stability than commercial Pd/C. This work advances the design and synthesis of high‐performance metastable‐phase IMCs, opening an avenue for electrocatalytic ethanol oxidation and beyond. [ABSTRACT FROM AUTHOR]

Bismuth‐based materials have emerged as promising catalysts in the electrocatalytic reduction of CO2 to formate. However, the reasons for the reconstruction of Bi‐based precursors to form bismuth nanosheets are still puzzling, especially the formation of defective bismuth sites. Herein, we prepare bismuth nanosheets with vacancy‐rich defects (V‐Bi NS) by rapidly reconstructing Bi19Cl3S27 under negative potential. Theoretical analysis reveals that the introduction of chlorine induces the generation of intrinsic electric field in the precursor, thereby increasing the electron transfer rate and further promoting the metallization of trivalent bismuth. Meanwhile, experimental tests verify that Bi19Cl3S27 has a faster reconstruction rate than Bi2S3. The formed V‐Bi NS exhibits up to 96 % HCOO− Faraday efficiency and 400 mA cm−2 HCOO− partial current densities, and its electrochemical active surface area normalized formate current density and yield are 2.2 times higher than those of intact bismuth nanosheets (I‐Bi NS). Density functional theory calculations indicate that bismuth vacancies with electron‐rich aggregation reduce the activation energy of CO2 to *CO2− radicals and stabilize the adsorption of the key intermediate *OCHO, thus facilitating the reaction kinetics of formate production. [ABSTRACT FROM AUTHOR]