Flow, curing and mechanical properties of thermoset resins – wood-fiber blends for potential additive-manufacturing applications

Orji, Berlinda O.; McDonald, Armando G.

doi:10.1080/17480272.2022.2155873

Cited by 2 publications

(2 citation statements)

References 96 publications

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“…Besides, s-ZnO/PDA@TCN and s-ZnO/PDA@DOX exhibited similar absorption peaks at 474.6 and 477.1 cm –1 , respectively, indicating no structural changes in the s-ZnO nanostructure. The peaks located at 1486 cm –1 were ascribed to the aromatic C–H stretching vibration in ZnO/PDA@TCN and s-ZnO/PDA@DOX and were absent in bulk s-ZnO . Furthermore, the absorption peaks at approximately 1590 and 1576 cm –1 were attributed to the CN stretching vibrations of PDA in ZnO/PDA@TCN and s-ZnO/PDA@DOX.…”

Section: Resultsmentioning

confidence: 98%

“…The peaks located at 1486 cm −1 were ascribed to the aromatic C−H stretching vibration in ZnO/ PDA@TCN and s-ZnO/PDA@DOX and were absent in bulk s-ZnO. 33 Furthermore, the absorption peaks at approximately 1590 and 1576 cm −1 were attributed to the C�N stretching vibrations of PDA in ZnO/PDA@TCN and s-ZnO/PDA@ DOX. Notably, the peak at around 1303 cm −1 was associated with the C−O stretching and bending vibrations of TCN, indicating the successful binding of TCN onto the s-ZnO/PDA surface.…”

Section: Characterization Of the S-zno And R-znomentioning

confidence: 99%

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Sunflower Pollen-Morphology Mimicked Spiky Zinc Nanomotors as a Photosensitizer for Killing Bacteria and Cancer Cells

Dutta,

Luthfikasari,

Patil

et al. 2024

ACS Appl. Bio Mater.

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Photosensitizing agents have received increased attention from the medical community, owing to their higher photothermal efficiency, induction of hyperthermia, and sustained delivery of bioactive molecules to their targets. Micro/nanorobots can be used as ideal photosensitizing agents by utilizing various physical stimuli for the targeted killing of pathogens (e.g., bacteria) and cancer cells. Herein, we report sunflower-pollen-inspired spiky zinc oxide (s-ZnO)-based nanorobots that effectively kill bacteria and cancer cells under near-infrared (NIR) light irradiation. The as-fabricated s-ZnO was modified with a catechol-containing photothermal agent, polydopamine (PDA), to improve its NIR-responsive properties, followed by the addition of antimicrobial (e.g., tetracycline/TCN) and anticancer (e.g., doxorubicin/ DOX) drugs. The fabricated s-ZnO/PDA@Drug nanobots exhibited unique locomotory behavior with an average speed ranging from 13 to 14 μm/s under 2.0 W/cm 2 NIR light irradiation. Moreover, the s-ZnO/PDA@TCN nanobots exhibited superior antibacterial activity against E. coli and S. epidermidis under NIR irradiation. The s-ZnO/PDA@DOX nanobots also displayed sufficient reactive oxygen species (ROS) amplification in B16F10 melanoma cells and induced apoptosis under NIR light, indicating their therapeutic efficacy. We hope the sunflower pollen-inspired s-ZnO nanorobots have tremendous potential in biomedical engineering from the phototherapy perspective, with the hope to reduce pathogen infections.

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Section: Resultsmentioning

confidence: 98%

Section: Characterization Of the S-zno And R-znomentioning

confidence: 99%

Sunflower Pollen-Morphology Mimicked Spiky Zinc Nanomotors as a Photosensitizer for Killing Bacteria and Cancer Cells

Dutta,

Luthfikasari,

Patil

et al. 2024

ACS Appl. Bio Mater.

View full text Add to dashboard Cite

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Intelligent Detection Method for Surface Defects of Particleboard Based on Super-Resolution Reconstruction

Zhou,

Xia,

Fan

et al. 2024

Forests

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To improve the intelligence level of particleboard inspection lines, machine vision and artificial intelligence technologies are combined to replace manual inspection with automatic detection. Aiming at the problem of missed detection and false detection on small defects due to the large surface width, complex texture and different surface defect shapes of particleboard, this paper introduces image super-resolution technology and proposes a super-resolution reconstruction model for particleboard images. Based on the Transformer network, this model incorporates an improved SRResNet (Super-Resolution Residual Network) backbone network in the deep feature extraction module to extract deep texture information. The shallow features extracted by conv 3 × 3 are then fused with features extracted by the Transformer, considering both local texture features and global feature information. This enhances image quality and makes defect details clearer. Through comparison with the traditional bicubic B-spline interpolation method, ESRGAN (Enhanced Super-Resolution Generative Adversarial Network), and SwinIR (Image Restoration Using Swin Transformer), the effectiveness of the particleboard super-resolution reconstruction model is verified using objective evaluation metrics including PSNR, SSIM, and LPIPS, demonstrating its ability to produce higher-quality images with more details and better visual characteristics. Finally, using the YOLOv8 model to compare defect detection rates between super-resolution images and low-resolution images, the mAP can reach 96.5%, which is 25.6% higher than the low-resolution image recognition rate.

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Flow, curing and mechanical properties of thermoset resins – wood-fiber blends for potential additive-manufacturing applications

Cited by 2 publications

References 96 publications

Sunflower Pollen-Morphology Mimicked Spiky Zinc Nanomotors as a Photosensitizer for Killing Bacteria and Cancer Cells

Sunflower Pollen-Morphology Mimicked Spiky Zinc Nanomotors as a Photosensitizer for Killing Bacteria and Cancer Cells

Intelligent Detection Method for Surface Defects of Particleboard Based on Super-Resolution Reconstruction

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