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Dynamic moisture-responsive textiles are highly desirable for smart clothing that adapts to physiological and environmental changes to enhance the wearer's comfort. Unfortunately, many moisture-responsive fabrics suffer from slow response times, poor reversibility, and insufficient durability. Moreover, these fabrics frequently fail to satisfy requirements such as tactile softness, appearance retention, and integration compatibility with existing clothing systems. This research reports a commercial strategy to engineer artificial leaf stomata into knitted fabrics by using screen-printed polyacrylamide (PAAm) hydrogel coatings followed by laser cutting. Inspired by natural stomatal function, our design enables the fabric to autonomously open and close moisture-responsive slits without altering its surface appearance or tactile properties. By investigating the hydrogel formulation, coating and cutting direction, and aspect ratio of the pattern, we optimized the actuation performance. Fabrics coated with 0.12 wt % cross-linked PAAm showed rapid and reversible opening behavior: slits cut along the weft direction at an 8:9 aspect ratio reached a maximum width of 1.07 ± 0.01 mm, while those at the warp direction at 7:9 reached 0.80 ± 0.04 mm. Upon absorbing moisture equivalent to 95% of their dry weight, slits opened within 10 s, increasing air permeability by 63.3% compared to control fabrics. The pores remained stable after repeated laundering. Under wet conditions, the slits enhanced heat and moisture dissipation, keeping the skin drier. This bioinspired integration of moisture actuation into textiles offers a promising route toward high-performance, moisture-responsive garments with durability.
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http://dx.doi.org/10.1021/acsami.5c03087 | DOI Listing |
Environ Sci Technol
September 2025
Department of Physics and Chemistry, Daegu Gyeongbuk Institute of Science and Technology (DGIST), 333 Techno Jungang-daero, Dalseong-gun, Daegu 42988, Korea.
Cesium ions (Cs) are notable radioactive contaminants hazardous to humans and the environment. Among various remediation methods, adsorption is a practical way to remove Cs from water, and Prussian blue (PB) is well-known as an efficient Cs adsorbent. Although various PB derivatives have been proposed to treat Cs-contaminated water, soil remediation is still challenging due to the limited mobility of pollutants in soil.
View Article and Find Full Text PDFBioresour Technol
September 2025
College of Engineering, Huazhong Agricultural University, Wuhan 430070, China. Electronic address:
In response to the challenges of nutrient limitations and low efficiency in synthesizing artificial humic acid (AHA) during the resource utilization of agricultural wastes, this study innovatively developed a process that integrates biogas slurry (BS) impregnation pretreatment with hydrothermal humification (HTH). Using steam-exploded corn straw (SES) as the raw material, the impregnation parameters were optimized (40 °C, liquid-to-solid ratio of 15:1, 18 h, 3 cycles), achieving an AHA yield of 40.61 %, which was over 15 % higher than that of the untreated group.
View Article and Find Full Text PDFNew Phytol
September 2025
Horticulture and Product Physiology, Department of Plant Sciences, Wageningen University & Research, Wageningen, 6708 PB, the Netherlands.
Thermal imaging is a key plant phenotyping and monitoring technique but faces major bottlenecks in accurately and efficiently inferring stomatal conductance (g) from leaf temperature. The conductance index (I) was previously proposed to estimate g from thermography by linking temperature differences between real and artificial leaves (ALs) based on the leaf energy balance. However, I is highly sensitive to environmental fluctuations, hampering interpretation and reducing reproducibility.
View Article and Find Full Text PDFFront Plant Sci
August 2025
School of Computer and Data Science, Henan University of Urban Construction, Pingdingshan, China.
Plant leaf disease control is crucial given the prevalence of plant leaf diseases around the world. The most crucial aspect of controlling plant leaf diseases is appropriately identifying them. Deep learning-based plant leaf disease recognition is a viable alternative to artificial methods that are useless and inaccurate.
View Article and Find Full Text PDFBiology (Basel)
August 2025
State Key Laboratory of Agricultural and Forestry Biosecurity, College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China.
Natural enemies commonly probe larval bodies and frass with their antennae for prey hunting. However, the attractants to natural enemies emitted directly from hosts and host-associated tissues remained largely unknown. Here, we used two generalist noctuid species, (Hübner) and (JE Smith), along with the larval endoparasitoid (Haliday) to address the question.
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