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  • MDPI AG  (42)
  • 1
    Online Resource
    Online Resource
    Effects of Raw Material Source on the Properties of CMC Composite Films
    MDPI AG ; 2021
    In:  Polymers Vol. 14, No. 1 ( 2021-12-22), p. 32-
    Details
    In: Polymers, MDPI AG, Vol. 14, No. 1 ( 2021-12-22), p. 32-
    Abstract: Sodium carboxymethyl cellulose (CMC) can be derived from a variety of cellulosic materials and is widely used in petroleum mining, construction, paper making, and packaging. CMCs can be derived from many sources with the final properties reflecting the characteristics of the original lignocellulosic matrix as well as the subsequent separation steps that affect the degree of carboxy methyl substitution on the cellulose hydroxyls. While a large percentage of CMCs is derived from wood pulp, many other plant sources may produce more attractive properties for specific applications. The effects of five plant sources on the resulting properties of CMC and CMC/sodium alginate/glycerol composite films were studied. The degree of substitution and resulting tensile strength in leaf-derived CMC was from 0.87 to 0.89 and from 15.81 to 16.35 MPa, respectively, while the degree of substitution and resulting tensile strength in wooden materials-derived CMC were from 1.08 to 1.17 and from 26.08 to 28.97 MPa, respectively. Thus, the degree of substitution and resulting tensile strength tended to be 20% lower in leaf-derived CMCs compared to those prepared from wood or bamboo. Microstructures of bamboo cellulose, bamboo CMC powder, and bamboo leaf CMC composites’ films all differed from pine-derived material, but plant source had no noticeable effect on the X-ray diffraction characteristics, Fourier transform infrared spectroscopy spectra, or pyrolysis properties of CMC or composites films. The results highlighted the potential for using plant source as a tool for varying CMC properties for specific applications.
    Type of Medium: Online Resource
    ISSN: 2073-4360
    URL: Article
    DOI: 10.3390/polym14010032
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2527146-5
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  • 2
    Online Resource
    Online Resource
    Antibacterial Films Made of Bacterial Cellulose
    MDPI AG ; 2022
    In:  Polymers Vol. 14, No. 16 ( 2022-08-13), p. 3306-
    Details
    In: Polymers, MDPI AG, Vol. 14, No. 16 ( 2022-08-13), p. 3306-
    Abstract: Bacterial cellulose (BC) is naturally degradable, highly biocompatible, hydrophilic, and essentially non-toxic, making it potentially useful as a base for creating more sophisticated bio-based materials. BC is similar to plant-derived cellulose in terms of chemical composition and structure but has a number of important differences in microstructure that could provide some unique opportunities for use as a scaffold for other functions. In this study, bacterial cellulose was alkylated and then esterified to produce a carboxymethyl bacterial cellulose (CMBC) that was then used to produce six different composite films with potential antibacterial properties. The films were assessed for antibacterial activity against Staphylococcus aureus and Escherichia coli, pyrolysis characteristics using thermogravimetric analysis (TGA), microstructure using scanning electron microscopy (SEM), and mechanical properties. The addition of nano-silver (nano-Ag) markedly improved the antimicrobial activity of the films while also enhancing the physical and mechanical properties. The results indicate that the three-dimensional reticulated structure of the bacterial cellulose provides an excellent substrate for scaffolding other bioactive materials. Thus, the nano-BC was added into the CMBC/nano-Ag composites furthermore, and then the antibacterial and mechanical properties were improved 44% for E. coli, 59% for S. aureus, and 20% for tensile strength, respectively.
    Type of Medium: Online Resource
    ISSN: 2073-4360
    URL: Article
    DOI: 10.3390/polym14163306
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527146-5
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  • 3
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    Online Resource
    The Improved Properties of Carboxymethyl Bacterial Cellulose Films with Thickening and Plasticizing
    MDPI AG ; 2022
    In:  Polymers Vol. 14, No. 16 ( 2022-08-12), p. 3286-
    Details
    In: Polymers, MDPI AG, Vol. 14, No. 16 ( 2022-08-12), p. 3286-
    Abstract: This study aims to improve the thermal stability and mechanical properties of carboxymethyl bacterial cellulose (CMBC) composite films. Experiments were conducted by preparing bacterial cellulose (BC) into CMBC, then parametrically mixing sodium alginate/starch/xanthan gum/gelatin and glycerin/sorbitol/PEG 400/PEG 6000 with CMBC to form the film. Scanning electron microscopy, X-ray diffractometry, infrared spectroscopy, mechanical tests, and thermogravimetric analysis showed that the composite films had better mechanical properties and thermal stability with the addition of 1.5% CMBC (% v/v), 1% sodium alginate, and 0.4% glycerin. Tensile strength was 38.13 MPa, the elongation at break was 13.4%, the kinematic viscosity of the film solution was 257.3 mm2/s, the opacity was 4.76 A/mm, the water vapor permeability was 11.85%, and the pyrolysis residue was 45%. The potential causes for the differences in the performance of the composite films were discussed and compared, leading to the conclusion that CMBC/Sodium alginate (SA)/glycerin (GL) had the best thermal stability and mechanical properties.
    Type of Medium: Online Resource
    ISSN: 2073-4360
    URL: Article
    DOI: 10.3390/polym14163286
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 4
    Online Resource
    Online Resource
    Preparation of Cellulose Nanoparticles from Foliage by Bio-Enzyme Methods
    MDPI AG ; 2021
    In:  Materials Vol. 14, No. 16 ( 2021-08-13), p. 4557-
    Details
    In: Materials, MDPI AG, Vol. 14, No. 16 ( 2021-08-13), p. 4557-
    Abstract: There are vast reserves of foliage in nature, which is an inexhaustible precious resource. In this study, the chemical components of five foliage types (pine needles, black locust tree leaves, bamboo leaves, elm leaves and poplar leaves) were analyzed, including cellulose content, hemicellulose content, and lignin content. The bio-enzymatic method was then used to prepare cellulose nanoparticles (CNPs) from these five kinds of leaves, and the prepared CNPs were analyzed using TEM, FTIR, FESEM, and XRD. The results showed that the content of hemicellulose in bamboo leaves was the highest, and the lignin content in the other four leaves was the highest. The cellulose content in the five kinds of foliage was arranged from large to small as pine needles (20.5%), bamboo leaves (19.5%), black locust leaves (18.0%), elm leaves (17.6%), and poplar leaves (15.5%). TEM images showed that the CNPs prepared by the five kinds of foliage reached the nanometer level in width and the micrometer level in length; therefore, the CNPs prepared in this study belonged to cellulose nanofibers (CNFs). The results of FTIR and XRD showed that CNFs prepared by the enzyme treatment exhibited a typical crystalline structure of cellulose II. The degree of crystallinity (DOC) of CNFs prepared from pine needle, poplar leaves, and bamboo leaves are 78.46%, 77.39%, and 81.51%, respectively. FESEM results showed that the CNFs prepared from pine needles, poplar leaves and bamboo leaves by enzymatic method presents a three-dimensional (3D) network structure, and their widths are 31 nm, 36 nm, and 37 nm, respectively. This study provides a meaningful reference for broadening the use of foliage types and improving their added value.
    Type of Medium: Online Resource
    ISSN: 1996-1944
    URL: Article
    DOI: 10.3390/ma14164557
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2487261-1
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  • 5
    Online Resource
    Online Resource
    Preliminary Study on Rapid and Simultaneous Detection of Viable Escherichia coli O157:H7, Staphylococcus aureus, and Salmonella by PMA-mPCR in Food
    MDPI AG ; 2023
    In:  Molecules Vol. 28, No. 15 ( 2023-08-03), p. 5835-
    Details
    In: Molecules, MDPI AG, Vol. 28, No. 15 ( 2023-08-03), p. 5835-
    Abstract: Escherichia coli O157:H7, Staphylococcus aureus, and Salmonella are major foodborne pathogens that are widespread in nature and responsible for several outbreaks of food safety accidents. Thus, a rapid and practical technique (PMA-mPCR) was developed for the simultaneous detection of viable E. coli O157:H7, S. aureus, and Salmonella in pure culture and in a food matrix. To eliminate false positive results, propidium monoazide (PMA) was applied to selectively suppress the DNA amplification of dead cells. The results showed the optimum concentration of PMA is 5.0 µg/mL. The detection limit of this assay by mPCR was 103 CFU/mL in the culture broth, and by PMA-mPCR was 104 CFU/mL both in pure culture and a food matrix (milk and ground beef). In addition, the detection of mixed viable and dead cells was also explored in this study. The detection sensitivity ratio of viable and dead counts was less than 1:10. Therefore, the PMA-mPCR assay proposed here might provide an efficient detection tool for the simultaneous detection of viable E. coli O157:H7, S. aureus, and Salmonella and also have great potential for the detection and concentration assessment of VBNC cells.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules28155835
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2008644-1
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  • 6
    Online Resource
    Online Resource
    Effect of SnO2 Colloidal Dispersion Solution Concentration on the Quality of Perovskite Layer of Solar Cells
    MDPI AG ; 2021
    In:  Coatings Vol. 11, No. 5 ( 2021-05-18), p. 591-
    Details
    In: Coatings, MDPI AG, Vol. 11, No. 5 ( 2021-05-18), p. 591-
    Abstract: The electron transport layer (ETL) is critical to carrier extraction for perovskite solar cells (PSCs). Moreover, the morphology and surface condition of the ETL could influence the topography of the perovskite layer. ZnO, TiO2, and SnO2 were widely investigated as ETL materials. However, TiO2 requires a sintering process under high temperature and ZnO has the trouble of chemical instability. SnO2 possesses the advantages of low-temperature fabrication and high conductivity, which is critical to the performance of PSCs prepared under low temperature. Here, we optimized the morphology and property of SnO2 by modulating the concentration of a SnO2 colloidal dispersion solution. When adjusting the concentration of SnO2 colloidal dispersion solution to 5 wt.% (in water), SnO2 film indicated better performance and the perovskite film has a large grain size and smooth surface. Based on high efficiency (16.82%), the device keeps a low hysteresis index (0.23).
    Type of Medium: Online Resource
    ISSN: 2079-6412
    URL: Article
    DOI: 10.3390/coatings11050591
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662314-6
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  • 7
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    Online Resource
    Distributed Non-Communicating Multi-Robot Collision Avoidance via Map-Based Deep Reinforcement Learning
    MDPI AG ; 2020
    In:  Sensors Vol. 20, No. 17 ( 2020-08-27), p. 4836-
    Details
    In: Sensors, MDPI AG, Vol. 20, No. 17 ( 2020-08-27), p. 4836-
    Abstract: It is challenging to avoid obstacles safely and efficiently for multiple robots of different shapes in distributed and communication-free scenarios, where robots do not communicate with each other and only sense other robots’ positions and obstacles around them. Most existing multi-robot collision avoidance systems either require communication between robots or require expensive movement data of other robots, like velocities, accelerations and paths. In this paper, we propose a map-based deep reinforcement learning approach for multi-robot collision avoidance in a distributed and communication-free environment. We use the egocentric local grid map of a robot to represent the environmental information around it including its shape and observable appearances of other robots and obstacles, which can be easily generated by using multiple sensors or sensor fusion. Then we apply the distributed proximal policy optimization (DPPO) algorithm to train a convolutional neural network that directly maps three frames of egocentric local grid maps and the robot’s relative local goal positions into low-level robot control commands. Compared to other methods, the map-based approach is more robust to noisy sensor data, does not require robots’ movement data and considers sizes and shapes of related robots, which make it to be more efficient and easier to be deployed to real robots. We first train the neural network in a specified simulator of multiple mobile robots using DPPO, where a multi-stage curriculum learning strategy for multiple scenarios is used to improve the performance. Then we deploy the trained model to real robots to perform collision avoidance in their navigation without tedious parameter tuning. We evaluate the approach with multiple scenarios both in the simulator and on four differential-drive mobile robots in the real world. Both qualitative and quantitative experiments show that our approach is efficient and outperforms existing DRL-based approaches in many indicators. We also conduct ablation studies showing the positive effects of using egocentric grid maps and multi-stage curriculum learning.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s20174836
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2052857-7
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  • 8
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    Online Resource
    Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles
    MDPI AG ; 2021
    In:  Energies Vol. 14, No. 22 ( 2021-11-10), p. 7505-
    Details
    In: Energies, MDPI AG, Vol. 14, No. 22 ( 2021-11-10), p. 7505-
    Abstract: To simultaneously achieve high fuel efficiency and low emissions in a diesel hybrid electric vehicle (DHEV), it is necessary to optimize not only power split but also exhaust thermal management for emission aftertreatment systems. However, how to coordinate the power split and the exhaust thermal management to balance fuel economy improvement and emissions reduction remains a formidable challenge. In this paper, a hierarchical model predictive control (MPC) framework is proposed to coordinate the power split and the exhaust thermal management. The method consists of two parts: a fuel and thermal optimized controller (FTOC) combining the rule-based and the optimization-based methods for power split simultaneously considering fuel consumption and exhaust temperature, and a fuel post-injection thermal controller (FPTC) for exhaust thermal management with a separate fuel injection system added to the exhaust pipe. Additionally, preview information about the road grade is introduced to improve the power split by a fuel and thermal on slope forecast optimized controller (FTSFOC). Simulation results show that the hierarchical method (FTOC + FPTC) can reach the optimal exhaust temperature nearly 40 s earlier, and its total fuel consumption is also reduced by 8.9%, as compared to the sequential method under a world light test cycle (WLTC) driving cycle. Moreover, the total fuel consumption of the FTSFOC is reduced by 5.2%, as compared to the fuel and thermal on sensor-information optimized controller (FTSOC) working with real-time road grade information.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en14227505
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2437446-5
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  • 9
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    Online Resource
    Simulation of Radiation Damage for Silicon Drift Detector
    MDPI AG ; 2019
    In:  Sensors Vol. 19, No. 8 ( 2019-04-13), p. 1767-
    Details
    In: Sensors, MDPI AG, Vol. 19, No. 8 ( 2019-04-13), p. 1767-
    Abstract: Silicon drift detector with high sensitivity and energy resolution is an advanced detector which is suitable to be used in deep space detection. To study and reveal the radiation damage of the silicon drift detector (SDD) in a deep-space environment, which will degrade the detector performance, in this paper, the SDD radiation damage effects and mechanics, including displacement damage and ionization damage, for irradiations of different energy of neutrons and gammas are investigated using Geant4 simulation. The results indicate the recoil atoms distribution generated by neutrons in SDD is uniform, and recoil atoms’ energy is mainly in the low energy region. For secondary particles produced by neutron irradiation, a large energy loss in inelastic scattering and fission reactions occur, and neutron has a significant nuclear reaction. The energy deposition caused by gammas irradiation is linear with the thickness of SDD; the secondary electron energy distribution produced by gamma irradiation is from several eV to incident particle energy. As the scattering angle of secondary electron increases, the number of secondary electrons decreases. Therefore, a reasonable detector epitaxial thickness should be set in the anti-irradiation design of SDD.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s19081767
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
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  • 10
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    Integrating the Textural and Spectral Information of UAV Hyperspectral Images for the Improved Estimation of Rice Aboveground Biomass
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 11 ( 2022-05-25), p. 2534-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 11 ( 2022-05-25), p. 2534-
    Abstract: The accurate and rapid estimation of the aboveground biomass (AGB) of rice is crucial to food security. Unmanned aerial vehicles (UAVs) mounted with hyperspectral sensors can obtain images of high spectral and spatial resolution in a quick and effective manner. Integrating UAV-based spatial and spectral information has substantial potential for improving crop AGB estimation. Hyperspectral remote-sensing data with more continuous reflectance information on ground objects provide more possibilities for band selection. The use of band selection for the spectral vegetation index (VI) has been discussed in many studies, but few studies have paid attention to the band selection of texture features in rice AGB estimation. In this study, UAV-based hyperspectral images of four rice varieties in five nitrogen treatments (N0, N1, N2, N3, and N4) were obtained. First, multiple spectral bands were used to identify the optimal bands of the spectral vegetation indices, as well as the texture features; next, the vegetation index model (VI model), the vegetation index combined with the corresponding-band textures model (VI+CBT model), and the vegetation index combined with the full-band textures model (VI+FBT model) were established to compare their respective rice AGB estimation abilities. The results showed that the optimal bands of the spectral and textural information for AGB monitoring were inconsistent. The red-edge and near-infrared bands demonstrated a strong correlation with the rice AGB in the spectral dimension, while the green and red bands exhibited a high correlation with the rice AGB in the spatial dimension. The ranking of the monitoring accuracies of the three models, from highest to lowest, was: the VI+FBT model, then the VI+CBT model, and then the VI model. Compared with the VI model, the R2 of the VI+FBT model and the VI+CBT model increased by 1.319% and 9.763%, respectively. The RMSE decreased by 2.070% and 16.718%, respectively, while the rRMSE decreased by 2.166% and 16.606%, respectively. The results indicated that the integration of vegetation indices and textures can significantly improve the accuracy of rice AGB estimation. The full-band textures contained richer information that was highly related to rice AGB. The VI model at the tillering stage presented the greatest sensitivity to the integration of textures, and the models in the N3 treatment (1.5 times the normal nitrogen level) gave the best AGB estimation compared with the other nitrogen treatments. This research proposes a reliable modeling framework for monitoring rice AGB and provides scientific support for rice-field management.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14112534
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
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