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  • 1
    Online Resource
    Online Resource
    Activation and Disproportionation of Zr2Fe Alloy as Hydrogen Storage Material
    MDPI AG ; 2019
    In:  Molecules Vol. 24, No. 8 ( 2019-04-19), p. 1542-
    Details
    In: Molecules, MDPI AG, Vol. 24, No. 8 ( 2019-04-19), p. 1542-
    Abstract: As a hydrogen storage material, Zr2Fe alloy has many advantages such as fast hydrogen absorption speed, high tritium recovery efficiency, strong anti-pulverization ability, and difficulty self-igniting in air. Zr2Fe alloy has lower hydrogen absorption pressure at room temperature than LaNi5 alloy. Compared with the ZrVFe alloy, the hydrogen release temperature of Zr2Fe is lower so that the material can recover hydrogen isotopes at lower hydrogen concentration efficiently. Unfortunately, the main problem of Zr2Fe alloy in application is that a disproportionation reaction is easy to occur after hydrogen absorption at high temperature. At present, there is little research on the generation and influencing factors of a disproportionation reaction in Zr2Fe alloy. In this paper, the effects of temperature and hydrogen pressure on the disproportionation of Zr2Fe alloy were studied systematically. The specific activation conditions and experimental parameters for reducing alloy disproportionation are given, which provide a reference for the specific application of Zr2Fe alloy.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules24081542
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2008644-1
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  • 2
    Online Resource
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    Association between Antidepressants and Dementia Risk in Older Adults with Depression: A Systematic Review and Meta-Analysis
    MDPI AG ; 2023
    In:  Journal of Clinical Medicine Vol. 12, No. 19 ( 2023-10-03), p. 6342-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 12, No. 19 ( 2023-10-03), p. 6342-
    Abstract: Depression, commonly treated with antidepressants, is associated with an increased risk of dementia, especially in older adults. However, the association between antidepressant use and dementia risk is unclear. We searched for randomized controlled trials and observational studies from PubMed, Embase, and Cochrane on 1 February 2022, restricting to full texts in English. Since dementia is a chronic disease requiring a long induction time, we restricted studies with ≥1 year follow-up. We extracted the relative risk (RR) adjusted for the most variables from each study and evaluated the heterogeneity using I square (I2). The protocol was registered in the PROSPERO International Register of Systematic Reviews (CRD42022338038). We included six articles in the systematic review, of which the sample size ranged from 716 to 141,740, and the median length of follow-up was 5 years. The pooled RR was 1.21 (95% CI = 1.12–1.29) with an I2 of 71%. Our findings suggest that antidepressant use was associated with an increased risk of dementia in older adults with depression, yet moderate to high heterogeneity existed across studies. Future work accounting for the depression progression is needed to differentiate the effect of depression and antidepressants on dementia risk.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm12196342
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662592-1
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  • 3
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    Deciphering Gut Microbiome Responses upon Microplastic Exposure via Integrating Metagenomics and Activity-Based Metabolomics
    MDPI AG ; 2023
    In:  Metabolites Vol. 13, No. 4 ( 2023-04-07), p. 530-
    Details
    In: Metabolites, MDPI AG, Vol. 13, No. 4 ( 2023-04-07), p. 530-
    Abstract: Perturbations of the gut microbiome are often intertwined with the onset and development of diverse metabolic diseases. It has been suggested that gut microbiome perturbation could be a potential mechanism through which environmental chemical exposure induces or exacerbates human diseases. Microplastic pollution, an emerging environmental issue, has received ever increasing attention in recent years. However, interactions between microplastic exposure and the gut microbiota remain elusive. This study aimed to decipher the responses of the gut microbiome upon microplastic polystyrene (MP) exposure by integrating 16S rRNA high-throughput sequencing with metabolomic profiling techniques using a C57BL/6 mouse model. The results indicated that MP exposure significantly perturbed aspects of the gut microbiota, including its composition, diversity, and functional pathways that are involved in xenobiotic metabolism. A distinct metabolite profile was observed in mice with MP exposure, which probably resulted from changes in gut bacterial composition. Specifically, untargeted metabolomics revealed that levels of metabolites associated with cholesterol metabolism, primary and secondary bile acid biosynthesis, and taurine and hypotaurine metabolism were changed significantly. Targeted approaches indicated significant perturbation with respect to the levels of short-chain fatty acids derived from the gut microbiota. This study can provide evidence for the missing link in understanding the mechanisms behind the toxic effects of microplastics.
    Type of Medium: Online Resource
    ISSN: 2218-1989
    URL: Article
    DOI: 10.3390/metabo13040530
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662251-8
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  • 4
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    Numerical Simulation for Elasto-Plastic Contact of Novel Ti-(SiCf/Al3Ti)-Laminated Composite with Double-Layered SiC Fiber Reinforcements
    MDPI AG ; 2019
    In:  Metals Vol. 9, No. 2 ( 2019-02-01), p. 165-
    Details
    In: Metals, MDPI AG, Vol. 9, No. 2 ( 2019-02-01), p. 165-
    Abstract: An innovative, high-strength metal–intermetallic-laminate (MIL) composite Ti-(SiCf/Al3Ti), reinforced by double or even several SiC fiber rows, was fabricated. A high-efficiency, semi-analytical model with a numerical equivalent inclusion method (NEIM) was employed to investigate the deformation behaviors, microscopic strengthening, and failure mechanisms of the composite during elasto-plastic sphere–plane contact. The microstructure and interface features were characterized by scanning electron microscopy (SEM) and energy dispersive spectrometer (EDS). The contact model for the Ti-(SiCf/Al3Ti) composite was validated via quasi-static compressive indentation tests with a spherical indenter. A series of in-depth parametric studies were conducted to quantify the effect of the microstructure. The results indicate that the as-fabricated laminated composite has a well-organized microstructure and a higher volume fraction of fibers. The SiC fiber rows effectively enhance the strength and toughness of the composite. The optimal diameter of the SiC fibers is 32 μm when the horizontal center distance between the adjacent fibers is 2.5 times that of the fiber diameter. The hole defects occurring above the fibers would damage the material strength most compared with those occurring in other positions. The optimal quantity of the SiC fiber rows is four when the thickness of the SiCf/Al3Ti layer is 400 μm and the fiber diameter is 8 μm.
    Type of Medium: Online Resource
    ISSN: 2075-4701
    URL: Article
    DOI: 10.3390/met9020165
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2662252-X
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  • 5
    Online Resource
    Online Resource
    Development, Characterization, and Validation of a Cold Stage-Based Ice Nucleation Array (PKU-INA)
    MDPI AG ; 2018
    In:  Atmosphere Vol. 9, No. 9 ( 2018-09-17), p. 357-
    Details
    In: Atmosphere, MDPI AG, Vol. 9, No. 9 ( 2018-09-17), p. 357-
    Abstract: A drop-freeze array (PeKing University Ice Nucleation Array, PKU-INA) was developed based on the cold-stage method to investigate heterogeneous ice nucleation properties of atmospheric particles in the immersion freezing mode from −30 to 0 °C. The instrumental details as well as characterization and performance evaluation are described in this paper. A careful temperature calibration protocol was developed in our work. The uncertainties in the reported temperatures were found to be less than 0.4 °C at various cooling rates after calibration. We also measured the ice nucleation activities of droplets containing different mass concentrations of illite NX, and the results obtained in our work show good agreement with those reported previously using other instruments with similar principles. Overall, we show that our newly developed PKU-INA is a robust and reliable instrument for investigation of heterogeneous ice nucleation in the immersion freezing mode.
    Type of Medium: Online Resource
    ISSN: 2073-4433
    URL: Article
    DOI: 10.3390/atmos9090357
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2605928-9
    SSG: 23
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  • 6
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    Curve-Localizability-SVM Active Localization Research for Mobile Robots in Outdoor Environments
    MDPI AG ; 2021
    In:  Applied Sciences Vol. 11, No. 10 ( 2021-05-11), p. 4362-
    Details
    In: Applied Sciences, MDPI AG, Vol. 11, No. 10 ( 2021-05-11), p. 4362-
    Abstract: Working environment of mobile robots has gradually expanded from indoor structured scenes to outdoor scenes such as wild areas in recent years. The expansion of application scene, change of sensors and the diversity of working tasks bring greater challenges and higher demands to active localization for mobile robots. The efficiency and stability of traditional localization strategies in wild environments are significantly reduced. On the basis of considering features of the environment and the robot motion curved surface, this paper proposes a curve-localizability-SVM active localization algorithm. Firstly, we present a curve-localizability-index based on 3D observation model, and then based on this index, a curve-localizability-SVM path planning strategy and an improved active localization method are proposed. Obtained by setting the constraint space and objective function of the planning algorithm, where curve-localizability is the main constraint, the path helps improve the convergence speed and stability in complex environments of the active localization algorithm. Helped by SVM, the path is smoother and safer for large robots. The algorithm was tested by comparative experiments and analysis in real environment and robot platform, which verified the improvement of efficiency and stability of the new strategy.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app11104362
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704225-X
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  • 7
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    Effects of Cr Content on Microstructure and Mechanical Properties of Co-Free FeCryNiAl0.8 High-Entropy Alloys
    MDPI AG ; 2023
    In:  Materials Vol. 16, No. 9 ( 2023-04-25), p. 3348-
    Details
    In: Materials, MDPI AG, Vol. 16, No. 9 ( 2023-04-25), p. 3348-
    Abstract: High-entropy alloys have gained widespread concern in response to the increased requirements for future high-temperature structural superalloys. By combining phase-diagram calculations with microhardness, compression behavior measurements at room temperature, and elevated temperature conditions, the very important role of the Cr element on the microstructure and properties is deeply revealed, which provides candidates materials for future high-temperature alloy applications. The increment of Cr favors the regulation of the two-phase fraction and distribution. The thermodynamic calculations illustrate that the density and melting point of the HEAs showed an increasing trend with the increase of the Cr content. The typical worm-like microstructure of the Cr0.6 alloy with a dual BCC structure was detected. Meanwhile, on the one hand, the increment of the Cr elements results in a considerable optimization of the mechanical properties of the alloy in terms of strength and ductility at room temperature. The corresponding compressive strength and plasticity of Cr0.6 alloy at room temperature are 3524 MPa and 43.3%. On the other hand, the high-temperature mechanical properties of the alloy are greatly enhanced. At 1000 °C, the yield strength of the Cr0.6 alloy is about 25 MPa higher than that of the Cr0.4 alloy. The superior mechanical properties are attributed to the pronounced work-hardening response, and the work-hardening behavior of Cr-containing HEAs was systematically analyzed by employing the modified Ludwik model. The higher content of Cr helps the resistance of the local deformation response, improving the nonuniform strain and promoting the balance of strength and ductility of the alloys.
    Type of Medium: Online Resource
    ISSN: 1996-1944
    URL: Article
    DOI: 10.3390/ma16093348
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2487261-1
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  • 8
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    Characterization of the Complete Mitochondrial Genome Sequences of Three Croakers (Perciformes, Sciaenidae) and Novel Insights into the Phylogenetics
    MDPI AG ; 2018
    In:  International Journal of Molecular Sciences Vol. 19, No. 6 ( 2018-06-12), p. 1741-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 19, No. 6 ( 2018-06-12), p. 1741-
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms19061741
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 9
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    Earth-Mover-Distance-Based Detection of False Data Injection Attacks in Smart Grids
    MDPI AG ; 2022
    In:  Energies Vol. 15, No. 5 ( 2022-02-25), p. 1733-
    Details
    In: Energies, MDPI AG, Vol. 15, No. 5 ( 2022-02-25), p. 1733-
    Abstract: The high integration of power information physical system improves the efficiency of power transmission, but it also brings new threats to power grid. False data injection attacks can use traditional bad data to detect vulnerabilities and maliciously tamper with measurement data to affect the state estimation results. In order to achieve a higher security level for power systems, we propose an earth mover distance method to detect false data injection attacks in smart grids. The proposed method is built on the dynamic correlation of measurement data between adjacent moments. Firstly, a joint-image-transformation-based scheme is proposed to preprocess the measurement data variation, so that the distribution characteristics of measurement data variation are more significant. Secondly, the deviation between the probability distribution of measurement data variation and the histogram are obtained based on the earth’s mover distance. Finally, a reasonable detection threshold is selected to judge whether there are false data injection attacks. The proposed method is tested using IEEE 14 bus system considering the state variable attacks on different nodes. The results verified that the proposed method has a high detection accuracy against false data injection attacks.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en15051733
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2437446-5
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  • 10
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    Prediction of High-Temperature Creep Life of Austenitic Heat-Resistant Steels Based on Data Fusion
    MDPI AG ; 2023
    In:  Metals Vol. 13, No. 9 ( 2023-09-21), p. 1630-
    Details
    In: Metals, MDPI AG, Vol. 13, No. 9 ( 2023-09-21), p. 1630-
    Abstract: The creep life prediction of austenitic heat-resistant steel is necessary to guarantee the safe operation of the high-temperature components in thermal power plants. This work presents a machine learning model that can be applied to predict the creep life of austenitic steels, offering a novel method and approach for such predictions. In this paper, creep life data from six typical austenitic heat-resistant steels are used to predict their creep life using various machine learning models. Moreover, the dissimilarities between the machine learning model and the conventional lifetime prediction method are compared. Finally, the influence of different input characteristics on creep life is discussed. The results demonstrate that the prediction accuracy of machine learning depends on both the model and the dataset used. The Gaussian model based on the second dataset achieves the highest level of prediction accuracy. Additionally, the accuracy and the generalization ability of the machine learning model prediction are significantly better than those of the traditional model. Lastly, the effect of the input characteristics on creep life is generally consistent with experimental observations and theoretical analyses.
    Type of Medium: Online Resource
    ISSN: 2075-4701
    URL: Article
    DOI: 10.3390/met13091630
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662252-X
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