•Analyze the thermal damage behavior of granite by optical microscopic observation.•Investigate the effect of temperature on the strength and deformation parameters of granite.•Explore the acoustic ...emission behavior of granite subjected to various high temperature treatment.•Discuss the internal crack mechanism of deformed granite specimens by X-ray micro CT system.
A detailed understanding of the thermal damage and failure mechanical behavior of granite at elevated temperatures is a key concern in nuclear waste disposal engineering, underground coal gasification, and heat mining in enhanced geothermal energy. In this research, uniaxial compression tests were first carried out to evaluate the effect of high temperature treatments (200, 300, 400, 500, 600, 700 and 800°C) on the crack damage, strength and deformation failure behavior of a granite. The results demonstrated that, in all cases, the crack damage threshold, the strength and static elastic modulus of granite were increased at 300°C, before decreasing up to our maximum temperature of 800°C. However, the static Poisson’s ratio of granite first decreased at 600°C, and then increased rapidly with the temperature. The crack damage and peak axial strain always showed an increase when the temperature was increased. However, the dynamic elastic modulus decreased with the temperature, whereas the dynamic Poisson’s ratio did not depend on the temperature. The gradual increase of temperature results in a more ductile failure of granite. Next, the thermal damage mechanism of uncompressed granite was analyzed by optical microscopic observation. At T=25–300°C, the mechanisms were favored by the thermal expansion of mineral grains but no microcracks were observed; at T=400–600°C, the mechanisms were contributed by boundary cracks and transgranular cracks in feldspar and quartz grains; and at T=700–800°C, the mechanisms were associated with the coalescence of boundary cracks and transgranular cracks. The internal crack evolution process was then monitored during deformation using acoustic emission (AE) monitoring. The results showed that the cracking process of granite depended on the heat treatment temperature. Finally, the deformation mechanism of failed granite at various temperatures was analyzed using X-ray micro CT. During loading, the uniaxial compression stress direction dominated the more brittle fracture process of granite at T=25–600°C, which led to splitting tensile main cracks induced along the axial stress, and thermal damage determined the larger ductile fracture process of granite at T=700–800°C, which resulted in a more ductile deformation after the peak strength.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•A graph learning framework, which captures both the global and local structure in data, is proposed.•Theoretical analysis builds the connections of our model to k-means, spectral clustering, and ...kernel k-means.•Extensions to semi-supervised classification and multiple kernel learning are presented.
Graphs have become increasingly popular in modeling structures and interactions in a wide variety of problems during the last decade. Graph-based clustering and semi-supervised classification techniques have shown impressive performance. This paper proposes a graph learning framework to preserve both the local and global structure of data. Specifically, our method uses the self-expressiveness of samples to capture the global structure and adaptive neighbor approach to respect the local structure. Furthermore, most existing graph-based methods conduct clustering and semi-supervised classification on the graph learned from the original data matrix, which doesn’t have explicit cluster structure, thus they might not achieve the optimal performance. By considering rank constraint, the achieved graph will have exactly c connected components if there are c clusters or classes. As a byproduct of this, graph learning and label inference are jointly and iteratively implemented in a principled way. Theoretically, we show that our model is equivalent to a combination of kernel k-means and k-means methods under certain condition. Extensive experiments on clustering and semi-supervised classification demonstrate that the proposed method outperforms other state-of-the-art methods.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Due to its excellent flexibility, graphene has an important application prospect in epidermal electronic sensors. However, there are drawbacks in current devices, such as sensitivity, range, ...lamination, and artistry. In this work, we have demonstrated a multilayer graphene epidermal electronic skin based on laser scribing graphene, whose patterns are programmable. A process has been developed to remove the unreduced graphene oxide. This method makes the epidermal electronic skin not only transferable to butterflies, human bodies, and any other objects inseparably and elegantly, merely with the assistance of water, but also have better sensitivity and stability. Therefore, pattern electronic skin could attach to every object like artwork. When packed in Ecoflex, electronic skin exhibits excellent performance, including ultrahigh sensitivity (gauge factor up to 673), large strain range (as high as 10%), and long-term stability. Therefore, many subtle physiological signals can be detected based on epidermal electronic skin with a single graphene line. Electronic skin with multiple graphene lines is employed to detect large-range human motion. To provide a deeper understanding of the resistance variation mechanism, a physical model is established to explain the relationship between the crack directions and electrical characteristics. These results show that graphene epidermal electronic skin has huge potential in health care and intelligent systems.
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IJS, KILJ, NUK, PNG, UL, UM
There is a growing demand for flexible electronic devices. In particular, strain sensors with high performance have attracted more and more attention, because they can be attached on clothing or ...human skin for applications in the real-time monitoring of human activities. However, monitoring human-body motions that include both subtle and intensive motions, and many strain sensors cannot meet the diverse demands simultaneously. In this work, a silver nanoparticles (Ag NPs) bridged graphene strain sensor is developed for simultaneously detecting subtle and intensive human motions. Ag NPs serve as many bridges to connect the self-overlapping graphene sheets, which endows the strain sensor with many excellent performances. Because of the high sensitivity, with a large gauge factor (GF) of 475 and a strain range of >14.5%, high durability of the sensor has been achieved. Besides, the excellent consistency and repeatability of the fabrication process is verified. Furthermore, the model for explaining the working mechanism of the strain sensor is proposed. Most importantly, the designed wearable strain sensor can be applied in human motion detection, including large-scale motions and small-scale motions.
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IJS, KILJ, NUK, PNG, UL, UM
A recent progress in new emerging two-dimensional (2D) materials has provided promising opportunity for gas sensing in ultra-low detectable concentration. In this work, we have demonstrated a ...flexible NO
2
gas sensor with porous structure graphene on polyethylene terephthalate substrates operating at room temperature. The gas sensor exhibited good performance with response of 1.2% and a fast response time within 30 s after exposure to 50 × 10
−9
NO
2
gas. As porous structure of graphene increased the surface area, the sensor showed high sensitivity of ppb level for NO
2
detection. Au nanoparticles were decorated on the surface of the porous structure graphene skeleton, resulting in an incensement of response compared with pristine graphene. Au nanoparticles-decorated graphene exhibits not only better sensitivity (1.5–1.6 times larger than pristine graphene) for NO
2
gas detection, but also fast response. The sensor was found to be robust and sensitive under the cycling bending test, which could also be ascribed to the merits of graphene. This porous structure graphene-based gas sensor is expected to enable a simple and inexpensive flexible gas sensing platform.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
A disposable electrochemical sensor based on ERGO/AuNPs composites via one-step electroreduction at the SPCE surface, showed the superior performances for the electrocatalytic analysis of nitrite in ...various foods.
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•A high-performance nitrite sensor was developed based on ERGO/AuNPs modified SPCE via one-step electroreduction at a low overpotential.•A possible formation mechanism of ERGO/AuNPs composite with unique 3D structures via cyclic voltammetric deposition was proposed.•The superior electrocatalysis of ERGO/AuNPs composite towards nitrite was attributed to synergistic effects of ERGO sheets and AuNPs.
Via a single-step electroreduction, the electrochemically reduced graphene oxide/gold nanoparticles (ERGO/AuNPs) composite was prepared on a disposable screen-printed carbon electrode (SPCE) for nitrite sensing. The AuNPs can be well dispersed in the stacked and wrinkled ERGO sheets. The possible mechanism for forming the unique structure of the hybrid composite was proposed. The electrochemical studies showed that AuNPs were efficient electrocatalysts towards the oxidation of nitrite, while the winkled ERGO sheets provide a 3D network scaffold for attachment of AuNPs and absorption of abundant nitrite, and promote the rapid heterogeneous electron transfer. The optimization of electrochemical reaction conditions also has been performed. The optimized electrode exhibited excellent properties for the detection of nitrite, including a low oxidation potential (0.65 V), wide linear range (1–6000 μM), high sensitivity (0.3048 μA μM−1 cm−2), low detection limit of 0.13 μM (S/N = 3), and great selectivity. Moreover, the good accuracy and recovery of ERGO/AuNPs based electrochemical sensor were achieved in the analysis of nitrite in various real food samples.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Lead halide perovskites have made remarkable progress in the field of radiation detection owing to the excellent and unique optoelectronic properties. However, the instability and the toxicity of ...lead‐based perovskites have greatly hindered its practical applications. Alternatively, lead‐free perovskites with high stability and environmental friendliness thus have fascinated significant research attention for direct X‐ray detection. In this review, the current research progress of X‐ray detectors based on lead‐free halide perovskites is focused. First, the synthesis methods of lead‐free perovskites including single crystals and films are discussed. In addition, the properties of these materials and the detectors, which can provide a better understanding and designing satisfactory devices are also presented. Finally, the challenge and outlook for developing high‐performance lead‐free perovskite X‐ray detectors are also provided.
Lead‐free perovskites have fascinated significant research attention for direct X‐ray detection. This review describes the current research progress in the synthesis methods of lead‐free perovskites, fundamental principles, and development of applications of X‐ray detectors. In addition, the challenge and outlook for developing high‐performance lead‐free perovskite X‐ray detectors are also discussed.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Conventional strain sensors rarely have both a high gauge factor and a large strain range simultaneously, so they can only be used in specific situations where only a high sensitivity or a large ...strain range is required. However, for detecting human motions that include both subtle and large motions, these strain sensors can't meet the diverse demands simultaneously. Here, we come up with laser patterned graphene strain sensors with self-adapted and tunable performance for the first time. A series of strain sensors with either an ultrahigh gauge factor or a preferable strain range can be fabricated simultaneously via one-step laser patterning, and are suitable for detecting all human motions. The strain sensors have a GF of up to 457 with a strain range of 35%, or have a strain range of up to 100% with a GF of 268. Most importantly, the performance of the strain sensors can be easily tuned by adjusting the patterns of the graphene, so that the sensors can meet diverse demands in both subtle and large motion situations. The graphene strain sensors show significant potential in applications such as wearable electronics, health monitoring and intelligent robots. Furthermore, the facile, fast and low-cost fabrication method will make them possible and practical to be used for commercial applications in the future.
An ultrasensitive strain sensor with a wide strain range based on graphene armour scales is demonstrated in this paper. The sensor shows an ultra-high gauge factor (GF, up to 1054) and a wide strain ...range (ε = 26%), both of which present an advantage compared to most other flexible sensors. Moreover, the sensor is developed by a simple fabrication process. Due to the excellent performance, this strain sensor can meet the demands of subtle, large and complex human motion monitoring, which indicates its tremendous application potential in health monitoring, mechanical control, real-time motion monitoring and so on.
Radiomics is an emerging field in oncological research. In this study, we aimed at developing a radiomics score (rad-score) to estimate postoperative recurrence and survival in patients with solitary ...hepatocellular carcinoma (HCC).
A total of 319 solitary HCC patients (training cohort: n = 212; validation cohort: n = 107) were enrolled. Radiomics features were extracted from the artery phase of preoperatively acquired computed tomography (CT) in all patients. A rad-score was generated by using the least absolute shrinkage and selection operator (lasso) logistic model. Kaplan-Meier and Cox's hazard regression analyses were used to evaluate the prognostic significance of the rad-score. Final nomograms predicting recurrence and survival of solitary HCC patients were established based on the rad-score and clinicopathological factors. C-index and calibration statistics were used to assess the performance of nomograms.
Six potential radiomics features were selected out of 110 texture features to formulate the rad-score. Low rad-score positively correlated with aggressive tumor phenotypes, like larger tumor size and vascular invasion. Meanwhile, low rad-score was significantly associated with increased recurrence and reduced survival. In addition, multivariate analysis identified the rad-score as an independent prognostic factor (recurrence: Hazard ratio (HR): 2.472, 95% confident interval (CI): 1.339-4.564, p = 0.004;survival: HR: 1.558, 95%CI: 1.022-2.375, p = 0.039). Notably, the nomogram integrating rad-score had a better prognostic performance as compared with traditional staging systems. These results were further confirmed in the validation cohort.
The preoperative CT image based rad-score was an independent prognostic factor for the postoperative outcome of solitary HCC patients. This score may be complementary to the current staging system and help to stratify individualized treatments for solitary HCC patients.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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