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Water reduces the stability and safety of paving material, and this has been extensively studied in traditional asphalt pavement. However, the influence of water on emerging cold-mixed epoxy asphalt (CEA) has not yet been acknowledged. In addition, the microstructure composed of epoxy resin (ER) and asphalt determines the performance of the CEA binder, and the influence of water entering this structure should be focused on. Here, CEA interfacial water models were established based on experimental and molecular dynamics (MD) simulations. The distribution and motion of the interfacial water and their influence on the energy, compatibility, and mechanical properties of CEA were explored. The results showed that CEA had desirable water stability when the water content was less than 5%. Water moved and was rearranged at the interface of the CEA and tended to move toward the ER. The water diffusion coefficient increased proportionally to the quadratic of the water content, and the structure of the CEA changed from an ordered short-range arrangement to a disordered one. Water reduced the interaction between the ER and asphalt by a maximum of 41.7% but had little effect on the compatibility of the CEA. Water plasticized CEA because the glass transition temperature of the CEA decreased, and less than 3% of water decreased the modulus of the CEA by a maximum of 27.0%. Simultaneously, water also destroyed the isotropy of the properties of the CEA. The gyration radius of the CEA dropped to approximately half of the value without water. This study is positive for promoting the performance improvement of CEA and provides a framework for studying CEA modeling and evaluation with MD simulations. [ABSTRACT FROM AUTHOR]

In environmental conditions, the ultraviolet (UV) light from sunshine will trigger epoxy asphalt (EA) paving materials aging and performance reduction. This work studied the influence of UV aging on the structure and mechanical performance of cold‐mixed epoxy asphalt (CEA) to evaluate its aging mechanism. The chemical structure of CEA was tested by Fourier transform infrared spectra, X‐ray photoelectron spectroscopy, and micromorphology was observed through fluorescence microscopy. The mechanical properties of CEA were studied by tensile tests and dynamic mechanical analysis. The results indicated that the toughness of CEA went down due to UV aging, and the elongation at break and glass transition temperature decreased by 35.5% and 6.0°C, respectively. Based on structural analysis, the UV aging mechanism of CEA was summarized as follows: (1) the curing network of epoxy resin was partially broken, and the asphalt particle aggregated; (2) the asphalt and epoxy resin in UV aging‐CEA were oxidized and formed carbonyl group and sulfonic group. Highlights: Both asphalt and ER components in CEA underwent oxidation reactions and formed more CO, SO, and CO groups.UV‐CEA showed a decrease in toughness due to destruction of the cured ER cross‐linked network and shortening of the asphalt molecular chainE' and Tg of UV‐CEA was decreased, resulting from a decrease in ER crosslink density and an increase in molecular chain segment mobility of ER and asphalt. [ABSTRACT FROM AUTHOR]

Biobased cold-mix epoxy asphalt (BCEA) was prepared by adopting biodiesel and epoxy soybean oil as asphalt solvent and compatibilizer. The strength and toughness attenuation laws under freeze–thaw (FT) cycles of BCEA were studied through tensile tests, flexural tests, and dynamic mechanical analysis. The attenuation mechanism was explored through scanning electron microscopy, Fourier transform infrared spectroscopy and water absorption tests. The results showed that the first FT cycle significantly weakened the strength and toughness of BCEA. After the third cycle, the attenuation rate of storage modulus, loss tangent, and glass transition temperature of BCEA declined. The attenuation mechanism of BCEA is as follows: (1) post-curing and destruction of the cross-linking network, (2) agglomeration and aging of asphalt, and (3) diffusion and reaction of water. This research provided a theoretical basis for the application of BCEA. [ABSTRACT FROM AUTHOR]

Cold-mixed epoxy asphalt (CEA) is an emerging energy-saving and environment-friendly material for steel bridge decks, overload roads, and airfield pavement. Occasionally, CEA suffers from impact with high strain rates, which will be extremely detrimental to the pavement's safety and stability. Since little research deals with this dynamic mechanical behavior, this study aims to clarify the dynamic mechanical performance of CEA mixtures (CEAM) under high strain rates. First, this study evaluated the quasi-static strength evolution by Marshall stability tests. The Marshall stability of CEAM more than quadrupled within the first 20 h and 1.6 times up again when exposed at 60°C, while its flow value showed the opposite trend. Then, the dynamic mechanical behavior under different high strain rates and temperatures was investigated by split Hopkinson pressure bar tests. Results showed that the peak strain rate (146–316 s−1) was 1.7–2.0 times greater than the average strain rate (84–162 s−1). The strain–stress curves became steep as the temperature and the pressure ascended. Under the same test conditions, the peak stress and the peak dynamic modulus of CEAM were 1.7 times larger than that of cement concrete. CEAM absorbed more energy below 25°C than 60°C. All the CEAM had binder failure, and the crushed specimens had aggregates broken. The constitutive model of CEAM was established based on the statistical damage theory and the modified Weibull distribution function. Besides, multiparametric regression analysis proved a demarcation point during the impact. [ABSTRACT FROM AUTHOR]

As a green material for high‐performance paving, cold‐mixed epoxy asphalt (CEA) should be improved in compatibility, mechanical performance, and thermal stability. This work is going to estimate the potential of graphene oxide (GO) as an additive for preparing GO/CEA composites with different GO content from 0 to 0.2 wt%. The influences of GO on the structure and performances of CEA were evaluated by Fourier transform‐infrared spectrum, fluorescence microscopy, viscosity, thermogravimetric analysis, tensile test, and dynamic mechanical analysis. Results showed that the functional groups on GO reacted with CEA and improved the compatibility of epoxy resin and asphalt. The viscosity of the GO/CEA composites increased slightly and the pot life decreased significantly, with GO loading increasing. The cured GO/CEA composite with 0.1 wt% GO had the best heat resistance and showed a gentle thermal decomposition. GO improved the toughness of the cured CEA and had a certain weakening effect on its strength. The introduction of GO lowered the glass transition temperature of the cured CEA from 51.4 to 47.1 °C and decreased its storage modulus. The preliminary exploration of this study shows that the modification of GO for CEA is feasible, and it is expected to prolong the service life of CEA. [ABSTRACT FROM AUTHOR]

The graphene oxide (GO) was used to improve the mechanical performances of epoxy asphalt (EA) by preparing GO/EA composite. The influence of the GO dosage on the micro-structure, curing rheology, mechanical and thermal properties of GO/EA was investigated. According to the XRD and Fourier transform infrared spectra, the GO was exfoliated in the EA matrix and modified EA by non-covalent strategy. GO decreased the rotational viscosity of EA and increased the pot life. The GO/EA with 0.1 wt.% GO showed excellent toughness that the elongation at break was increased by 164%, and the tensile and pull-off adhesion strength were nearly equal to that of EA. The addition of GO improved the original thermal decomposition temperature (T5%), glass transition temperature (Tg), compatibility and stiffness of the EA. The improved mechanical and thermal properties of GO/EA may be attributed to (1) excellent performances of GO and (2) inhibiting effect of GO on the EA curing process. [ABSTRACT FROM AUTHOR]

The Drosophila lymph gland is an ideal model for studying hematopoiesis, and unraveling the mechanisms of Drosophila hematopoiesis can improve our understanding of the pathogenesis of human hematopoietic malignancies. Bone morphogenetic protein (BMP) signaling is involved in a variety of biological processes and is highly conserved between Drosophila and mammals. Decapentaplegic (Dpp)/BMP signaling is known to limit posterior signaling center (PSC) cell proliferation by repressing the protooncogene dmyc. However, the role of two other TGF-β family ligands, Glass bottom boat (Gbb) and Screw (Scw), in Drosophila hematopoiesis is currently largely unknown. Here, we showed that the loss of Gbb in the cortical zone (CZ) induced lamellocyte differentiation by overactivation of the EGFR and JNK pathways and caused excessive differentiation of plasmatocytes, mainly by the hyperactivation of EGFR. Furthermore, we found that Gbb was also required for preventing the hyperproliferation of the lymph glands by inhibiting the overactivation of the Epidermal Growth Factor Receptor (EGFR) and c-Jun N-terminal Kinase (JNK) pathways. These results further advance our understanding of the roles of Gbb protein and the BMP signaling in Drosophila hematopoiesis and the regulatory relationship between the BMP, EGFR, and JNK pathways in the proliferation and differentiation of lymph gland hemocytes. [ABSTRACT FROM AUTHOR]

This paper develops a size-adaptive hybrid meshing scheme for Chemical Species Tomography (CST) that is driven by the customized spatial resolution of the sensing region. Traditionally, the entire sensing region in CST is uniformly discretized with the empirically determined density of the meshes. Such a discretization results in a) waste of computational efforts on the less spatially resolved location; and b) much severer rank deficiency. To solve the above-mentioned issues, we introduce, for the first time, a size-adaptive hybrid meshing scheme for CST. Driven by the spatial resolution, dense meshes are deployed in the region of interest (RoI) to detail the target flow field while sparse ones are deployed out of the RoI to fully consider the physically existing laser absorption. The proposed scheme is numerically validated using a CST sensor with 128 laser beams. The visual and quantitative metric comparisons show that the proposed hybrid-size meshing scheme outperforms the traditionally uniform-size meshing scheme, giving 35% lower image error and 38% less significant dislocation at a typical 35 dB signal-to-noise ratio in the RoI. The proposed hybrid-size meshing scheme significantly facilitates the reconstruction of the industrial combustion processes where the combustion zone is bypassed by cooling flows. In these scenarios, the proposed scheme can adapt a finer resolution to detail the combustion zone, while maintaining the integrity of the physical model by less resolved reconstruction of the bypass flows. [ABSTRACT FROM AUTHOR]

Tunable diode laser absorption spectroscopy (TDLAS) tomography is a well-established combustion diagnostic technique for imaging 2-D cross-sectional distributions of critical flow-field parameters. As two key metrics in TDLAS tomography, reconstruction accuracy and efficiency are generally traded off to satisfy either the requirement of high-fidelity image retrieval or rapid tomographic data inversion. In this article, a novel quality-hierarchical temperature imaging network for TDLAS tomography is developed based on stacked long short-term memory (LSTM). From limited line-of-sight TDLAS measurements, this network outputs two reconstructed temperature images, i.e., a coarse-quality image and a fine-quality image, with different numbers of network layers and consequently different computational costs. The coarse-quality image provides more timely temperature reconstruction, which can satisfy real-time dynamic monitoring of turbulence–chemistry interactions with a temporal resolution of tens of kilo frames per second. In contrast, the fine-quality image, which can be stored and utilized for offline analysis and diagnosis, further details the temperature reconstruction with more accurate features. Both numerical stimulation and lab-scale experiment validated the accuracy-efficiency tradeoff achieved by the proposed quality-hierarchical temperature imaging network. [ABSTRACT FROM AUTHOR]

Chemical species tomography (CST) has been widely used for in situ imaging of critical parameters, e.g., species concentration and temperature, in reactive flows. However, even with state-of-the-art computational algorithms, the method is limited due to the inherently ill-posed and rank-deficient tomographic data inversion and by high computational cost. These issues hinder its application for real-time flow diagnosis. To address them, we present here a novel convolutional neural network, namely CSTNet, for high-fidelity, rapid, and simultaneous imaging of species concentration and temperature using CST. CSTNet introduces a shared feature extractor that incorporates the CST measurements and sensor layout into the learning network. In addition, a dual-branch decoder with internal crosstalk, which automatically learns the naturally correlated distributions of species concentration and temperature, is proposed for image reconstructions. The proposed CSTNet is validated both with simulated datasets and with measured data from real flames in experiments using an industry-oriented sensor. Superior performance is found relative to previous approaches in terms of reconstruction accuracy and robustness to measurement noise. This is the first time, to the best of our knowledge, that a deep learning-based method for CST has been experimentally validated for simultaneous imaging of multiple critical parameters in reactive flows using a low-complexity optical sensor with a severely limited number of laser beams.

MXenes, two-dimensional nanomaterials, are gaining traction in catalysis and biomedicine. Yet, their oxidation instability poses significant functional constraints. Gaining insight into this oxidation dynamic is pivotal for designing MXenes with tailored functionalities. Herein, we crafted VO x C nanosheets by oxidatively engineering V 4 C 3 MXene. Interestingly, while pristine V 4 C 3 displays pronounced antioxidant behavior, its derived VO x C showcases enhanced peroxidase-like activity, suggesting the crossover between antioxidant and pro-oxidant capability. The mixed valence states and balanced composition of V in VO x C drive the Fenton reaction through multiple pathways to continually generate hydroxyl radicals, which was proposed as the mechanism underlying the peroxidase-like activity. Furthermore, this unique activity rendered VO x C effective in dopamine and glutathione detection. These findings underscore the potential of modulating MXenes' oxidation state to elicit varied catalytic attributes, providing an avenue for the judicious design of MXenes and derivatives for bespoke applications., Competing Interests: The authors declare no conflict of interest., (This journal is © The Royal Society of Chemistry.)

Two-dimensional (2D) transition-metal borides (TMBs) are especially expected to exhibit excellent performance in various fields among electricity, superconductivity, magnetism, mechanics, biotechnology, battery, and catalysis. However, the synthesis of ultrathin TMB single crystals with ultrahigh phase purity was deemed extremely challenging and has not been realized till date. That is because TMBs have the most kinds of crystal structures among inorganic compounds, which possess generous phase structures with similar formation energies compared with other transition-metal compounds, attributing to the metalloid and electron-deficient characteristics of boron. Herein, for the first time, we demonstrate a chemical potential-modulated strategy to realize the precise synthesis of various ultrahigh-phase-purity (approximately 100%) ultrathin TMB single crystals, and the precision in the phase formation energy can reach as low as 0.01 eV per atom. The ultrathin MoB 2 single crystals exhibit an ultrahigh Young's modulus of 517 GPa compared to other 2D materials. Our work establishes a chemical potential-modulated strategy to synthesize ultrathin single crystals with ultrahigh phase purity, especially those with similar formation energies, and undoubtedly provides excellent platforms for their extensive research and applications.