Fluorescent patterns with multiple functions enable high-security anti-counterfeiting labels. Complex material synthesis and patterning processes limit the application of multifunctional fluorescent patterns, so the technology of in situ fluorescent patterning with tunable multimodal capabilities is becoming more necessary. In this work, an in situ fluorescent patterning technology was developed using laser direct writing on solid cellulose film at ambient conditions without masks. The fluorescent intensity and surface microstructure of the patterns could be adjusted by programmable varying of the laser parameters simultaneously. During laser direct writing, carbon dots are generated in situ in a cellulose ester polymer matrix, which significantly simplifies the fluorescent patterning process and reduces the manufacturing cost. Interestingly, the tunable fluorescent intensity empowers the fabrication of visual stereoscopic fluorescent patterns with excitation dependence, further improving its anti-counterfeiting performance. The obtained fluorescent patterns still show ultrahigh optical properties after being immersed in an acid/base solution (pH 5-12) over one month. In addition, the anti-UV performance of the obtained laser-patterned film with transmittance around 90% is comparable to that of commercial UV-resistant films. This work provided an advanced and feasible approach to fabricating programmable, performance-tunable, subtle fluorescent patterns in large-scale for industrial application.@en

Capturing the long-term performance of concrete must be underpinned by a detailed understanding of the pore structure. Mercury intrusion porosimetry (MIP) is a widely used technique for pore structure characterization. However, it has been proven inappropriate to measure the pore size distribution of cementitious materials due to the ink-bottle effect. MIP with cyclic pressurization-depressurization can overcome the ink-bottle effect and enables a distinction between large (ink-bottle) pores and small (throat) pores. In this paper, pressurization-depressurization cycling mercury intrusion porosimetry (PDC-MIP) is adopted to characterize the pore structure in a range of cementitious pastes cured from 28 to 370 days. The results indicate that PDC-MIP provides a more accurate estimation of the pore size distribution in cementitious pastes than the standard MIP. Bimodal pore size distributions can be obtained by performing PDC-MIP measurements on cementitious pastes, regardless of the age. Water-binder ratio, fly ash and limestone powder have considerable influences on the formation of capillary pores ranging from 0.01 to 0.5 μm.@en

The combination of photocatalyst with cementitious materials for air pollution abatement and self-cleaning has gained considerable attention. However, the most popularly used photocatalytic cementitious composites based on TiO2 achieve the purification function under ultraviolet sunlight, significantly impeding a broader application of photocatalytic cementitious composites. Here, the photocatalytic cementitious composites were prepared by incorporating g-C3N4 nanosheets (CNNs) in Portland cement. With the increase of CNNs content, the photocatalytic NOx abatement and self-cleaning performance was notably improved, while the micro-hardness of cementitious composites increased first and then decreased. Among the three mixing dosages (0.5%, 1% and 2% by weight of cement), the cementitious composite admixed with 2% CNNs showed the highest photocatalytic NOx abatement efficiency of 227.3 μmol m−2 h−1, and could degrade the rhodamine B within 40 min under visible light. Additionally, its microscopic hardness was 5.4% higher than the one without CNNs, suggesting that a moderate amount of CNNs (below 2%) in cementitious composites was effective in achieving an improved photocatalytic depollution performance.@en

The combination of photocatalyst with cementitious materials for air pollution abatement and self-cleaning has gained considerable attention. However, the most popularly used photocatalytic cementitious composites based on TiO2 achieve the purification function under ultraviolet sunlight, significantly impeding a broader application of photocatalytic cementitious composites. Here, the photocatalytic cementitious composites were prepared by incorporating g-C3N4 nanosheets (CNNs) in Portland cement. With the increase of CNNs content, the photocatalytic NOx abatement and self-cleaning performance was notably improved, while the micro-hardness of cementitious composites increased first and then decreased. Among the three mixing dosages (0.5%, 1% and 2% by weight of cement), the cementitious composite admixed with 2% CNNs showed the highest photocatalytic NOx abatement efficiency of 227.3 μmol m−2 h−1, and could degrade the rhodamine B within 40 min under visible light. Additionally, its microscopic hardness was 5.4% higher than the one without CNNs, suggesting that a moderate amount of CNNs (below 2%) in cementitious composites was effective in achieving an improved photocatalytic depollution performance.@en

Human–computer interaction (HCI) has received growing interest in both academic research and the design of information technological applications. Automated facial expression estimation of image is a difficult, yet crucial, problem in the design of HCI system. Although artificial neural network has achieved many remarkable results, few smart wearable devices can benefit from it. Most of these devices are constrained by limited computing and storage capacity. An effective solution is to allow servers to handle multiple tasks simultaneously. Toward this goal, we have been building an Efficient multitask scheme for facial expression estimation (EM-FEE). A multitask neural network is designed to enable the HCI system to accomplish different related tasks at the same time, that is, locating the user’s facial landmarks and estimating facial expressions. Experimental results demonstrate that our proposed scheme outperforms state-of-the-art. Finally, we review the remaining challenges and corresponding opportunities as well as future directions of the design of facial expression estimation systems for smart wearable devices.@en