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Training samples for deep learning networks are typically obtained through various field experiments, which require significant manpower, resource and time consumption. However, it is possible to utilize simulated data to augment the training samples. In this paper, by comparing the actual experimental model with the simulated model generated by the gprMax [1] forward simulation method, the feasibility of obtaining simulated samples through gprMax simulation is validated. Subsequently, the samples generated by gprMax forward simulation are used for training the network to detect objects in existing real samples. At the same time, aiming at the detection and intelligent recognition of road sub-surface defects, the Swin-YOLOX algorithm is introduced, and the excellence of the detection network, which is improved by augmenting the simulated samples with real samples, is further verified. By comparing the prediction performance of the object detection models, it is observed that the model trained with mixed samples achieved a recall of 94.74% and a mean average precision (mAP) of 97.71%, surpassing the model trained only on real samples by 12.95% and 15.64%, respectively. The feasibility and excellence of training the model with mixed samples are confirmed. The potential of using a fusion of simulated and existing real samples instead of repeatedly acquiring new real samples by field experiment is demonstrated by this study, thereby improving detection efficiency, saving resources, and providing a new approach to the problem of multiple interpretations in ground penetrating radar (GPR) data.

Triplet photosensitizers have great potential in selective photooxidation by generating 1O2through triplet energy transfer. However, the heterogeneous bulk photosensitizers easily trap triplet excitons and inhibit photocatalysis efficiency. Previous work focused on controlling ultra-small size to reduce the transfer distance, but we propose a new strategy using triplet acceptor molecules (e.g., pyrenecarboxylic acid, PCA) with proper energy levels to modify the surface of heterogeneous photosensitizers (e.g., g-C3N4), facilitate the transfer of triplet excitons from the interior to the surface of the catalyst, and enhance catalytic reactions on its surface. In the photooxidation reaction of uric acid (UA), the conversion of UA catalyzed by pg-C3N4/PCA can reach 91.3% at 60 min, higher than that without modification (24.0%). DFT calculations and spectroscopic characterization show that the triplet acceptor in pg-C3N4/PCA could reduce the ΔESTvalue and grab triplet excitons in g-C3N4, thereby enhancing the 1O2generation. This work provides another approach for high-efficiency utilization of heterogeneous triplet photosensitizers in wide applications.

In response to the low detection efficiency and accuracy of traditional manual methods for detecting road underground defects, this paper proposes an intelligent detection method based on ground penetrating radar (GPR). This method integrates the detection, classification, and localization of road underground defects. The approach uses Swin Transformer as a feature extraction network and utilizes the YOLOX object detection algorithm as a road underground defect detection model. It enables the detection of defect regions in three types of defect images: voids, non-compact areas, and underground pipelines. In addition, the collected radar signals are processed by Fourier transformation to obtain time-domain spectra and frequency-domain spectra, which are further analyzed to generate signal classification data set to achieve the defect classification. Finally, based on the relative positional relationship between the detected defect images and the GPS information collected by the GPR, the real positions of the defects on the map are automatically determined using the APIs provided by Amap (AutoNavi map). Experimental results show that this method achieves a precision and recall rate of 94.2% and 99.1%, respectively, for the detection of road underground defects, with an average precision of 94% and an average classification accuracy of 90%. The method significantly improves the accuracy and speed of road underground defect detection while meeting engineering requirements, making it highly valuable for practical road underground defect detection tasks.

High energy consumption is required in traditional synthetic ammonia industry. The exploration of a novel environmentally sustainable approach for the artificial synthesis of ammonia is of urgency. Photocatalysis is regarded as a promising approach for nitrogen fixation under mild conditions and for converting inexhaustible solar energy into chemical energy. The selection and modification of the photocatalysts are important factors for enhancing the photocatalytic nitrogen fixation performance. In this review, we discuss the structure and preparation method of g-C3N4. In addition, modifications of g-C3N4-based photocatalysts, such as modification of morphology, defect engineering, element doping and construction of heterojunction structure, are discussed. Finally, the challenges and opportunities of developing advanced g-C3N4-based photocatalysts are summarized and prospected to bring some inspiration for designing g-C3N4-based photocatalysts in the field of photocatalytic nitrogen fixation.

Phase Change Materials (PCMs) serve as highly effective mediums for latent heat storage owing to their substantial heat storage capacity. However, their practical application encounters limitations stemming from low thermal conductivity (TC) and the potential leakage of the melt medium during phase transitions. Addressing these challenges, we devised a strategy to enhance the heat conduction paths in PCM composites. This involved fabricating a dual-aligned scaffold (D-AS) through the integration of both aligned carbon nanofibers (CNFs) in microscopic structures and directional microporous channels, achieved by combining magnetic alignment and conventional freeze-casting techniques. Furthermore, the D-AS functions as a supportive structure for PCMs, ensuring the phase change material maintains excellent shape stability. Experimental findings indicate that the TC of the D-AS and polyethylene glycol (PEG) composites reaches 5.48 W/(m·K) when the CNFs constitute 16.21 wt%, representing a remarkable 1857.1 % increase compared to pure PEG. The composites also exhibit outstanding shape stability, with PEG leakage effectively prevented by the pores in the scaffold. As a trade-off, the heat storage capacity and thermal storage efficiency of the composites is slightly reduced (146.85 J/g, 89.9 %) due to the increase of CNF weight fraction. This demonstrates that a promising direction was highlight for the preparation of high TC and shape stabilized PCMs in this work.

The pyrolysis process of Shendong coal (SD) was first studied by combining the characteristics of thermal gravimetric (TG), pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) and Gray-King assay (G-K). The results show that the order of coke yields is G-K (76.35% (mass))>TG (73.11% (mass))>Py (70.03% (mass)). G-K coke yield caused by condensation reaction and secondary reaction accounts for 3.08% (mass) and 3.24% (mass), respectively. Compared with slow pyrolysis, fast pyrolysis has stronger fracture ability to coal molecules and can obtain more O-compounds, mono-ring aromatics and aliphatics. Especially, the content of phenolics increases significantly from 15.49% to 35.17%, but the content of multi-ring aromatics decreases from 23.13% to 2.36%. By comparing the compositions of Py primary tar and G-K final tar, it is found that secondary reactions occurred during G-K pyrolysis process include the cleavage of alkane and esters, condensation of mono-ring aromatics with low carbon alkene, ring opening, isomerization of tri-ring aromatics, hydrogenation of aromatics and acids.

Coal has a highly complex chemical structure, similar to polymers, coal is a macromolecular structure composed of a large number of “similar compounds”, which is called the basic structural unit. Understanding coal structure is the basis of its transformation and utilization. Shendong (SD) coal was analyzed by FTIR, XRD, XPS, and NMR. The results show that SD coal normalized structure formula is C100H68.5O35.7N1.2S0.2and the average number of aromatic rings is 1.98. –CH2— content accounts for about 82% in aliphatic C–H region, and the ratio of ether bond C–O, aromatic ether C–O and CO is about 2:1:11 in oxygen-containing functional group region. The d002, LC, Laand NCof SD coal microcrystalline structure parameters are 0.1832 nm, 1.4688 nm, 2.0852 nm and 9.017, respectively. Aromatic carbon and aliphatic carbon ratios of SD coal are 55.67% and 29.97%, aromatic cluster size and average methylene chain length are 0.224 and 1.817. Based on these structural parameters, molecular model of SD coal was constructed with 13C SSNMR experimental spectra as a reference. The model was constructed with an atom composition of C214H214O49N2S.

This study was to investigate the therapeutic effects of silk fibroin/gelatin (SF/GT) electrospun nanofiber dressing loaded with astragaloside IV (AS) on acute trauma. SF/GT nanofiber dressing was prepared by electrospinning nanotechnology and loaded with AS. Four groups of rats inflicted with full-thickness wounds on the back were treated with saline, blank nanofiber dressing (blank control), AS solution and AS-loaded SF/GT nanofiber dressing, respectively. The results showed that AS-loaded SF/GT nanofiber dressing group had a significantly higher wound healing closure rate compared with control group on the 3rd, 6th, and 9th day after treatment. The VEGF content and the number of macrophages in the wound skin area of AS-loaded SF/GT nanofiber dressing group increased significantly compared to the blank control group 7 days after treatment (36 versus 4; 72 versus 38, p < 0.01, respectively). The expression level of Alpha smooth muscle actin (α-SMA) was inhibited by AS-loaded SF/GT nanofiber dressing treatment compared to the blank control, and the anti-scar effect was further demonstrated by scanning electron microscope and histological analyses. The conclusion of this study was that AS-loaded SF/GT nanofiber dressing with both healing accelerating ability and anti-scaring effect was proved to be a promising therapeutic for acute trauma treatment.

Herein, a water‐limited sol–gel method is applied to fabricate microencapsulated phase change materials (MEPCMs) which have a sodium nitrate (NaNO3) core and a titanium dioxide (TiO2) shell. The MEPCM has a high melting temperature of 306.5 °C and a solidification temperature of 296.7 °C, which shows a potential usage as a high‐temperature compatible thermal storage medium for industrial waste heat recovery and concentrated solar power (CSP). The MEPCM is demonstrated to be thermally stable for 200 thermal cycles with a high latent heat of 135.3 J g−1. The high‐temperature latent functional thermal fluid (HT‐LFTF) is prepared by dispersing the NaNO3@TiO2MEPCMs into thermal oil. The test results show that MEPCMs provide an 18.4% effective thermal conductivity enhancement and 131.7% effective specific heat enhancement compared with base thermal oil. The rheological test indicates that the MEPCMs added in the thermal oil enhance the viscosity of the suspension and it increases with the MEPCM concentration. This work provides a new type of thermal oil–based functional thermal fluid containing high‐temperature MEPCM and paves the way for the application of LFTF in high‐temperature heat storage and transfer. A new kind of molten salt microcapsule with NaNO3core and TiO2shell is synthesized successfully by a water‐limited sol–gel method. It is introduced to enhance the thermal performance of high‐temperature latent functional thermal fluid. It provides an 18.4% effective thermal conductivity enhancement and 131.7% effective specific heat enhancement compared with pure thermal oil.