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The rise of Na‐storage devices has put forward higher requirements for Na‐storage anode materials with large capacity, long service life, and fast rate capability. Mesoporous carbons, either as active materials or as hosts for guest active nanoparticles, are considered as promising electrode materials. However, addressing the issues of their short lifespan resulting from volume variation and the low coulombic efficiency caused by large surface area via a facile porous structure design still remains a challenge. Herein, a versatile phosphorus‐doped mesoporous carbon (PMC) armed is developed by graphene aerogel (GA) (GA@PMC) for hosting Na‐storage active nanoparticles. As a case study, FeSe2 nanoparticles are selectively supported onto this GA@PMC matrix, creating the FeSe2/GA@PMC composite. When employed in typical Na‐storage devices, such as Na‐ion batteries, Na‐ion hybrid capacitors, and Na‐ion based dual‐ion batteries, the FeSe2/GA@PMC electrode consistently demonstrates superior electrochemical performance. In such GA@PMC, the conformal GA can improve the entire conductivity while decreasing the specific surface area that is directly contacting with electrolyte. The interconnected macroporous structure can not only promote the diffusion of Na+ but also buffers the volume change of the guest active nanoparticles. This bespoke carbon platform synergistically endows the electrode material with enhanced rate capability, cyclic stability, and coulombic efficiency, which are being expected in advanced Na‐storage devices. [ABSTRACT FROM AUTHOR]

Collapsibility significantly impacts the bearing capacity of pile foundations in loess areas. To improve the load-bearing capacity of piles, the pile-base postgrouting technique is widely used worldwide. However, there are still several related issues to be solved: the impact of loess collapsibility on the bearing capacity; the effectiveness of the pile-base postgrouting technique in enhancing the bearing capacity; and the diffusion pattern of the grout during the grouting process. To investigate these issues, this experiment utilizes a visual static pressure device combined with numerical simulation. According to the experiment, the maximum axial force and neutral point appeared to shift downward after grouting, resulting in a 17.5% increase in the bearing capacity of the pile foundation. Additionally, an increase in grouting pressure leads to a rise in both the number of shear cracks and the diffusion radius. As the permeability of the grout improves, the number of shear cracks and diffusion radii tend to stabilize after an initial increase. These discoveries enable a thorough analysis of the changes in side friction and base resistance of postgrouted piles in collapsible loess. Furthermore, they provide valuable references and guidance for the implementation of the pile-base postgrouting technique in loess areas. [ABSTRACT FROM AUTHOR]

Machine learning is becoming a preferred method for the virtual screening of organic materials due to its cost-effectiveness over traditional computationally demanding techniques. However, the scarcity of labeled data for organic materials poses a significant challenge for training advanced machine learning models. This study showcases the potential of utilizing databases of drug-like small molecules and chemical reactions to pretrain the BERT model, enhancing its performance in the virtual screening of organic materials. By fine-tuning the BERT models with data from five virtual screening tasks, the version pretrained with the USPTO–SMILES dataset achieved R2 scores exceeding 0.94 for three tasks and over 0.81 for two others. This performance surpasses that of models pretrained on the small molecule or organic materials databases and outperforms three traditional machine learning models trained directly on virtual screening data. The success of the USPTO–SMILES pretrained BERT model can be attributed to the diverse array of organic building blocks in the USPTO database, offering a broader exploration of the chemical space. The study further suggests that accessing a reaction database with a wider range of reactions than the USPTO could further enhance model performance. Overall, this research validates the feasibility of applying transfer learning across different chemical domains for the efficient virtual screening of organic materials. Scientific contribution This study verifies the feasibility of applying transfer learning to large language models in different chemical fields to help organic materials perform virtual screening. Through the comparison of transfer learning from different chemical fields to a variety of organic material molecules, the high precision virtual screening of organic materials is realized. [ABSTRACT FROM AUTHOR]

The present paper aims to study the influence of pore-scale fiber structure on the Cassie-Baxter contact angle of droplets on PTFE fibrous hydrophobic membranes. The fiber structure is obtained by the Confocal Laser Scanning Microscope (CLSM), and an optical test bench is built to measure the Cassie-Baxter contact angles of a droplet on a PTFE membrane. The free energy of the solid-liquid interface is measured by the surface tension integral on the droplet profile. An iterative algorithm for liquid-vapor interface shrinking is brought forward to analyze the liquid-vapor interface area between the droplet and the membrane, and the interface parameters of the Cassie-Baxter model are recognized. The experiment shows that the Cassie-Baxter contact angles and the contact line radii along the droplet circumference are in a normal distribution due to random fiber structures, and the variance of the normal distribution increases with the membrane pore diameter. The normal distribution of Cassie-Baxter's contact angle indicates the constraint of the solid-liquid interface to the liquid-vapor interface. On the same normal contact pressure condition, the liquid-vapor area ratio of the droplet and membrane interface changes little, and Cassie-Baxter's contact angle increases with the solid-liquid interface area ratio. [ABSTRACT FROM AUTHOR]

Environment perception technology is the most important part of driverless technology, and driverless vehicles need to realize decision planning and control by virtue of perception feedback. This paper summarizes the most promising technology methods in the field of perception, namely visual perception technology, radar perception technology, state perception technology, and information fusion technology. Regarding the current development status in the field, the development of the main perception technology is mainly the innovation of information fusion technology and the optimization of algorithms. Multimodal perception and deep learning are becoming popular. The future of the field can be transformed by intelligent sensors, promote edge computing and cloud collaboration, improve system data processing capacity, and reduce the burden of data transmission. Regarding driverless vehicles as a future development trend, the corresponding technology will become a research hotspot. [ABSTRACT FROM AUTHOR]

Widespread integration of carbon‐based membranes into prevailing fields like energy storage and material engineering is thwarted by a lack of functionality, customization, and compatibility, making the development of such carbon‐based membranes urgency yet challenging. Herein, a "graphene bubble bridging" strategy is adopted to fabricate the multifunctional carbon fiber membrane, in which graphene bubbles with optimized assembling not only endow the carbon fiber with superior flexibility and integrity by embedded bridging function, but also enhance the fast electron transport capability and electrolyte wettability. Few‐layer MoSSe nanosheets with expanded interlayer spacing as a typical energy storage material contribute to plentiful ion intercalation/deintercalation that can be well buffered within the robust fibers. The interlaced carbon fibers enable a self‐supporting framework that ensures good conductivity and mechanical stability as well. Such functional, customized, and compatible membranes with synergies can boost the attributes of advanced K+ storage devices, such as flexible K‐ion capacitors and K‐based dual‐ion batteries. This work can afford new insights for designing flexible electrode in the energy storage field, as well as various types of conformations that can bring more opportunities on developing flexible functional membranes for other fields (e.g., catalysts, electromagnetic shielding). [ABSTRACT FROM AUTHOR]