Ultra-low-density graphene aerogels (GAs) have attracted remarkable interests to solve the electromagnetic interference (EMI) issues for next-generation electronic devices. However, the practical EMI shielding application of ultralight GAs is still a great challenge owning to their structural instability when exposure to complex environmental conditions. Here we report an ultra-stable GA with superior and reliable EMI shielding ability. The ultralight GAs (ρ=3.7 mg/cm3) with face-to-face stacked structures possess excellent electrical conductivity and high shielding effectiveness (SE) of 64.1 dB at the thickness of 1 mm. The absolute EMI SE reaches up to 171000 dB·cm2/g, far beyond the previous ultralight carbon-based materials. The excellent structural robustness of GAs ensured the stable operation in mechanical deformation, extreme temperature, flame and underwater environment. Meanwhile, the intrinsic conflict of ultralow density and oversized volume was solved by vacuum encapsulation without structural damage. Our GAs paved the way to the practical EMI shielding application and greatly broadened the applied scenes, such as aerospace, warcraft and ocean fields.
With the rapid advancement of deepfake generation technologies, the demand for robust and accurate face forgery detection algorithms has become increasingly critical. Recent studies have demonstrated that wavelet analysis can uncover subtle forgery artifacts that remain imperceptible in the spatial domain. Wavelets effectively capture important facial contours, which are often slender, fine-grained, and global in nature. However, existing wavelet-based approaches fail to fully leverage these unique characteristics, resulting in sub-optimal feature extraction and limited generalizability. To address this challenge, we introduce WMamba, a novel wavelet-based feature extractor built upon the Mamba architecture. WMamba maximizes the utility of wavelet information through two key innovations. First, we propose Dynamic Contour Convolution (DCConv), which employs specially crafted deformable kernels to adaptively model slender facial contours. Second, by leveraging the Mamba architecture, our method captures long-range spatial relationships with linear computational complexity. This efficiency allows for the extraction of fine-grained, global forgery artifacts from small image patches. Extensive experimental results show that WMamba achieves state-of-the-art (SOTA) performance, highlighting its effectiveness and superiority in face forgery detection.
Making use of the cathodic electrolyte obtained from theelectroreduction of oxalic acid without separation,p-hydroxymandelic acid wassynthesized in 80% yield.The latter acid was subjected electrooxidation in anundivided cell affording p-hydroxybenzaldehyde in 90% yield.
<div class="section abstract"><div class="htmlview paragraph">Fossil fuel depletion and air pollution have accelerated the transformation and upgrading of the internal combustion engine industry. The argon-oxygen atmosphere engine has the advantages of “zero emission” and high thermal efficiency, but the knocking problem constrains the engine to operate at a lower compression ratio. In this paper, the effect of water spraying technology on the knocking combustion and combustion characteristics of a hydrogen-argon oxygen engine is investigated by numerical simulation. A one-dimensional thermodynamic model and a three-dimensional numerical model of the hydrogen-argon oxygen engine are established and validated by aligning the model with the data of the real engine. Firstly, investigate the effect of in-cylinder water spraying timing on knock suppression and combustion characteristics of hydrogen argon oxygen engines. 570 ° CA to 600 ° CA is the optimal water spraying timing range for suppressing knock. When 570 ° CA is sprayed, the atomization effect of droplets in the cylinder is good, and the combustion and power characteristics are significantly improved. At this time, the water spraying IMEP increases by 14.45%. Therefore, 570 ° CA is selected as the optimal spraying timing. On this basis, the effect of in-cylinder water spraying mass on the knock suppression and combustion characteristics of the hydrogen-argon oxygen engine is further investigated. When the water spraying mass reaches 24 mg, the knock intensity KI droppes to 0.170 MPa, and the knock phenomenon has been effectively suppressed. There is no obvious numerical change in KI when the water spraying mass continues to increase. In terms of power performance, IMEP increases with water spraying mass and then decreases, and the maximum value of 6.357 bar is achieved at 25 mg of water spraying mass, which proves that in-cylinder water spraying can effectively suppress the hydrogen-argon oxygen engine knock phenomenon while improving the engine power performance.</div></div>
The scheme demonstrates the sampling process and microstructure formation of GO/cellulose composite films, which have excellent ultraviolet-shielding and mechanical properties with optimal GO loading.
Surface acoustic wave (SAW) humidity sensors promise broad prospects for Internet of Things (IoT) applications due to the advantages of low cost, portability, and high sensitivity. However, previous researches mainly focused on developing SAW devices with higher resonant frequencies, or using new sensing materials to improve the performance of SAW humidity sensors. Few researches studied the specific response mechanism of SAW humidity sensors, which restricted further development of the sensors. In this paper, the sensing mechanism of a graphene oxide (GO) film-based SAW humidity sensor is thoroughly studied by investigating the mechanical and electrical parameters of the uniform GO membrane at different relative humidity (from 10% RH to 90% RH). After taking these parameters into consideration for the mechanism analysis, we quantitatively indicate that the mass loading (~800 ppm) and viscoelastic effects (~60 ppm) are the primary and secondary influence factors of the sensor's humidity response respectively, while the acoustoelectric interaction has little effect on the sensitivity.
Abstract A micro-nano structurized gold chip was developed and applied to a surface plasmon resonance imaging (SPRi) sensor with polarization contrast method. Compared with the planar gold film, a total sensitivity enhancement (SEF=287%) was obtained.
Multimaterial integration, such as soft elastic and stiff components, exhibits rich deformation and functional behaviors to meet complex needs. Integrating multimaterials in the level of individual fiber is poised to maximize the functional design capacity of smart wearable electronic textiles, but remains unfulfilled. Here, this work continuously integrates stiff and soft elastic components into single fiber to fabricate encoded mechano-metafiber by programmable microfluidic sequence spinning (MSS). The sequences with programmable modulus feature the controllable localization of strain along metafiber length. The mechano-metafibers feature two essential nonlinear deformation modes, which are local strain amplification and retardation. This work extends the sequence-encoded metafiber into fiber networks to exhibit greatly enhanced strain amplification and retardation capability in cascades. Local strain engineering enables the design of highly sensitive strain sensors, stretchable fiber devices to protect brittle components and the fabrication of high-voltage supercapacitors as well as axial electroluminescent arrays. The approach allows the scalably design of multimaterial metafibers with programmable localized mechanical properties for woven metamaterials, smart textiles, and wearable electronics.
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