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While robotic tactile sensors have been developed to help robots to perceive and interact effectively with their surrounding environment by mimicking the structure and function of human skin, most of them overlook the role of near-contact behavior and data structure modeling in robotic perception, which limits robotic exploration capabilities. To address this problem, this article presents a novel proximity-tactile fingertip (PT-TIP) sensor, and a new multireceptive graph convolutional network (MR-GCN) that seamlessly integrates near-contact behavior and tactile perception in rich sensory data. Moreover, MR-GCN utilizes two graph structures, including topology graph and affinity graph, to capture temporal and spatial connections and differences among sensing units on PT-TIP, and it learns a robust feature representation from different receptive fields with attention mechanisms. The performance of MR-GCN was evaluated in two common robotic tasks, namely, object recognition and grasp stability detection, and the results show that the presented method outperforms state-of-the-art work in both tasks.

In order to achieve natural tactile sensation and satisfactory perception for robots in complex environments, this article presents a novel human-inspired robotic tactile sensing system for fluid. Specifically, a biomimetic fluid-sensitive handlike sensor (BFHS) is designed by mimicking the perception mechanism of human skin. A deep learning model is then developed to establish a mapping between tactile sensor offset and two key properties of fluid, namely, fluid flow direction and velocity. Furthermore, a feature correlation reconstruction (FCR) method is proposed to derive a new feature to improve the interpretability among features. Finally, an experimental system is constructed to validate the proposed BFHS. The experimental results demonstrate that its average accuracy in sensing fluid direction and velocity significantly outperforming human tactile perception. This can be viewed as a breakthrough finding in the field of robotic tactile perception.

In order to help robots understand and perceive an object's properties during noncontact robot-object interaction, this article proposes a deeply supervised subspace learning method. In contrast to previous work, it takes the advantages of low noise and fast response of noncontact sensors and extracts novel contactless feature information to retrieve cross-modal information, so as to estimate and infer material properties of known as well as unknown objects. Specifically, a depth-supervised subspace cross-modal material retrieval model is trained to learn a common low-dimensional feature representation to capture the clustering structure among different modal features of the same class of objects. Meanwhile, all of unknown objects are accurately perceived by an energy-based model, which forces an unlabeled novel object's features to be mapped beyond the common low-dimensional features. The experimental results show that our approach is effective in comparison with other advanced methods.

Elasticity and stability play a crucial role in phase change fibers (PCFs), ensuring both comfort and effective thermal management in fabrics. In this study, we present the development of an elastic and shape-stable phase change fiber through coaxial wet spinning. The fiber consists of a paraffin wax (PW) core encapsulated in a thermoplastic polyurethane (TPU) sheath, providing reliable protection against leakage during use. The obtained PCFs exhibit a PW loading capacity of up to 64.9 wt% and a heating enthalpy of 117.0 J/g. Notably, these fibers maintain their morphological and thermal stability even after undergoing 50 cycles of heating and cooling treatments. By integrating the PCFs into a fabric and coating the surface with CNTs, the PCFs-based fabric achieves an outstanding photothermal conversion efficiency of 95.1 % under a light intensity of 250 mW/cm2and an electrothermal conversion efficiency of 73.2 % at a power level of 0.9 W. Furthermore, the fabric, woven with uniformly broken PW core, exhibits excellent tensile resilience in various conditions, including room temperature and during photothermal and electrothermal conversion processes. This study introduces a promising avenue for the development of innovative PCFs, offering significant potential for their application in the realm of personal smart fabrics, particularly in the field of advanced thermal management.

Drying behaviors of brown coal are affected by internal water diffusion, which is controlled by pore structures. To diminish the effect of functional groups on drying, drying behaviors and pore structures of only one kind of coal dried at different heating rates and atmospheres were investigated. The final drying temperature was kept constant. The relationships between pore structures, including specific surface area (SBET), volume of mesopores (Vmeso), volume of macropores (Vmacro), volume of total pores (Vtotal), and two fractal dimensions (DIand DII), and drying characteristics, including maximum drying rate (vmax), activation energy of drying surface water (E1), activation energy of drying pore water (E2), apparent diffusion coefficient surface water (Deff-1), and apparent diffusion coefficient pore water (Deff-2), were correlated. The relationship between basic pore parameters and fractal dimensions was examined. For coals dried in N2, the SBETwas confirmed as one of the key factors influencing DI. The vmaxincreased with heating rates, resulting from the higher temperature at the same drying time and larger SBETand Vmacro. The E1was higher at faster heating rates, because of the higher temperature gradient and the bigger DI. The E2increased as heating rates increased from 3 to 20 °C/min and then decreased for flash drying (directly dried at 200 °C). The increase could be also due to the higher temperature gradient at higher heating rates. The decrease could be because of the effect of Vmacroon Deff-2. For coals dried in different atmospheres, the higher E1and E2in air were due to oxidation reaction. The relatively large heat conductivity of N2led to the lower E1. The small molecular diameter of CO2led to the lower E2. There was no consistent relationship between SBETand DIand between pore structures and drying characteristics for coals dried in different atmospheres.

The Inner Mongolia lignite was selected as the feedstock and dewatered by hydrothermal, fixed-bed, and microwave upgrading techniques. The physicochemical structures of the raw coal and dewatered coal samples were determined by N2adsorption, Fourier transform infrared, and chemical titration methods. The combustion behavior of coals was investigated by thermogravimetric analyzer, and the results demonstrated that the combustion reactivity of the dewatered coals was enhanced. The apparent activation energies of the coal samples were obtained from nonisothermal single heating rate method, and the results illuminated that the combustion process of these coals could be divided into three stages according to the variations of their apparent activation energies. Those variations were used as the medium to investigate the correlations between combustion reactivity parameters and physicochemical structures. It was found that at stage I of the combustion process, the ignition temperature of the coal was mainly affected by intrinsic chemical reactivity; at stage II, the maximum combustion reaction rate of the coal was affected by intrinsic chemical reactivity and specific area diffusion, and the temperature corresponding to the maximum combustion reaction rate was mainly affected by intrinsic chemical reactivity; and at stage III, the burnout temperature was affected by intrinsic chemical reactivity, and the overall reaction rate was controlled by gas diffusion rate.

Series of HY sorbents with different amounts and strength of Brønsted and Lewis acidic sites were prepared. Their adsorption performance in thiophene–benzene solution, pure benzene, and pure thiophene were evaluated, and the desulfurization mechanisms were studied. The results show that both thiophene and benzene could be effectively adsorbed through the interaction between Lewis acid sites and the conjugated π bond in these two molecules, and thus thiophene adsorption could be obviously competed by benzene on Lewis acidic sites. By contrast, on Brønsted acidic sites, thiophene can be efficiently adsorbed via H–S bond, which is stronger than the former interaction. Moreover, the middle strong Brønsted acid could cause thiophene oligomerization. Hence, for the desulfurization purpose by NaY zeolite in aromatic free system, its weak and middle strong Lewis acid should be increased, and for that in aromatic existing system, the Brønsted acid site with relative low strength should be promoted.

The effective treatment of industrial pollutant N, N-dimethylformamide (DMF) containing wastewater is a matter of worldwide concern. This study investigated the performance and microecology of anaerobic granular sludge (AGS) and aerobic sludge (AS) in treating DMF wastewater. It was also explored the degradation pathways of DMF in an anaerobic sequencing batch reactor series aerobic sequencing batch reactor (AnSBR-ASBR). Results showed that 5 mg/L DMF facilitated the degradation of chemical oxygen demand (COD) by AGS with AS, while 100 mg/L DMF reduced the efficiency of AS. The physicochemical properties of the sludge showed that the polysaccharide and protein levels in extracellular polymeric substances and key enzyme activity (acetate kinase, coenzyme F420) deteriorated when DMF increased from 25 to 100 mg/L. As the DMF dose increased (0–100 mg/L), the Euryarchaeota abundance in the AGS decreased from 28.41% to 11.06%, and the predominant methanogenic pathway shifted from a combination of aceticlastic methanogenesis (AM) and hydrogenotrophic methanogenesis (HM) to HM. The metabolic pathway to effectively remove DMF was as follows: hydrolysis of DMF to dimethylamine, methylamine, and finally mineralisation to CO2. The abundance of dmd-tmd, a functional gene encoding dimethylamine/trimethylamine dehydrogenase, increased as the DMF increased in the AS. This study systematically examined the operating efficiency and stability of the AnSBR-ASBR, and summarized the AGS and AS stress response, microbial community evolution, key metabolic pathways to DMF, also provided useful information for the treatment of industrial wastewater containing DMF.

The oxygen-containing functional groups and pore structure of lignite are the main factors controlling its moisture readsorption and drying behaviors. However, the effects of these two factors were not separated in former studies. To minimize the effect of differences in surface chemical properties, several partially gasified lignite char samples with different pore structure but similar surface functional groups were used. The surface areas and volumes of micro-, meso-, and macro-pores of samples were determined by CO2adsorption, helium pycnometry, and mercury intrusion porosimetry. The concentrations of different forms of water in moisturized char samples were determined from the equilibrium moisture contents at constant humidity and temperature and from the results of dewatering experiments analyzed by thermogravimetry coupled with differential scanning calorimetry (TGA-DSC). The congelation characteristics of water in moisturized char samples were studied by low-temperature DSC. The relationship between pore structure and the content of different forms of water was analyzed by individual linear regression. The results showed that three forms of water were distinguished, free water, capillary water, and molecular water. The free water and capillary water were frozen at −12 °C and −40 °C, respectively. The dewatering heat per gram of water was in the order: molecular water > capillary water > free water. The concentrations of free-, capillary-, and molecular water were strongly correlated with the macropore volume, mesopore volume, and surface area, respectively.

Abstract