Compositional effects on mechanical properties and viscosity in UDMA-MMA blends

Alabdali, Zinah N.; Reiter, Mary P.; Lynch-Branzoi, Jennifer; Mann, A.

doi:10.1080/01694243.2020.1816779

Cited by 5 publications

(3 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is seen in the FTIR spectra and our prior work has shown the importance of hydrogen bonds in these polymers. 38 The increased bonding between the polymer matrix and the additives is likely to be the origin of the increase in mechanical properties for the composites beyond the rule-of-mixtures values.…”

Section: Discussionmentioning

confidence: 99%

“…34,35 However, the main peaks associated with the polymer are mostly unchanged with the exception of very small shifts in the N H peak ≈ 1528 cm −1 and the C O double overlapping peaks ≈ 1701 and ≈ 1710 cm −1 . These are both affected by hydrogen bonding [36][37][38] and are slightly modified by the hydroxyl group of the HA.…”

Section: Vibrational Spectroscopymentioning

confidence: 99%

See 1 more Smart Citation

Low‐weight fractions of graphene and hydroxyapatite enhance mechanics in photocured methacrylate adhesives

Alabdali

Irizarry

Reiter

et al. 2021

J of Applied Polymer Sci

Self Cite

View full text Add to dashboard Cite

In many applications, it is desirable for photocured adhesives to have high‐mechanical strength in the cured state, but relatively low viscosity when liquid. This was achieved by adding less than 0.5 wt% hydroxyapatite and graphene to methyl methacrylate with diurethane dimethacrylate (UDMA‐MMA). Nanoindentation shows hardness increasing by 30–40% and indentation modulus by >30% compared to UDMA‐MMA on its own. Rheometry shows only a small increase in uncured viscosity for the liquid state. The additives affect the optical properties, mobility of free radicals, photocuring, and degree of conversion, the effects of which are seen in Fourier transform infrared and micro‐Raman spectra. Thermographic images taken during curing show that the additives impact the photocuring process. In addition, changes in intermolecular bonding are seen in the vibrational spectra when the additives are present. The enhanced mechanical properties are attributed to the observed changes in photocuring and bonding.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Vibrational Spectroscopymentioning

confidence: 99%

Low‐weight fractions of graphene and hydroxyapatite enhance mechanics in photocured methacrylate adhesives

Alabdali

Irizarry

Reiter

et al. 2021

J of Applied Polymer Sci

Self Cite

View full text Add to dashboard Cite

show abstract

“…Nanomaterials is a part of nanotechnology, which can be included organic and non-organic materials like silver, zinc, carbon nanotube, and graphene (7)(8)(9). One of the methods to characterize the nanoparticle size in the field of materials science (10) and engineering is scanning electron microscopy (SEM) (11,12). SEM imaging characterization was used to obtain the morphology of the samples as well as distinguish the particles.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Particle Size in Composite Materials Using Image Processing

Alabdali,

Alkalid

2024

IJE

View full text Add to dashboard Cite

Composite materials are the most important materials in materials science and engineering, which contain two or more materials. In materials engineering, the scanning electron microscopy (SEM) technique is an approach to measure the material's particle size. A new procedure was used instead of SEM is called Artificial Intelligence (AI). Artificial Intelligence (AI) is an interdisciplinary science and branch of computer science that involves solving problems that require human intelligence and capabilities. The computer vision is a subfield of AI, which uses some algorithms to detect the details of images by using computer called image processing. Detecting the particles and measuring the size of materials scanned by SEM is an essential task that helps to describe their feature, traditionally, the size is calculated manually by adding mesh to an SEM image or by drawing a diagonal line in an arbitrary particle. In this paper, a new model based on Artificial Intelligence (AI) is proposed using computer vision to analyze the size of all particles. This model is used to detect the particle size of additives in composite materials like graphene flakes and measure the size of them depending on the reference size fixed on the scanning electron microscope (SEM). The model was used based on the Open-source Computer Vision (OpenCV) library, utilizing multi-layers of canny edge detection, Sobel filter, Brightness and contrast algorithms, using Python 3. The results have achieved very satisfied indication with a very low process time = 0.2 mili-seconds.

show abstract