Publications by authors named "Argyros A"

Article Synopsis
  • The study focused on using silicon nitride (SiN) as an additive to improve the properties of high-density polyethylene (HDPE) through material extrusion (MEX) 3D printing, testing various concentrations of SiN from 0.0 to 10.0 wt. %.
  • Following the preparation of six composite types, a series of comprehensive tests were conducted, including thermal, mechanical, and morphological analyses, to evaluate the performance of the composites.
  • The results showed that the HDPE/SiN composite with 6.0 wt. % exhibited the best enhancements in mechanical properties, proving SiN to be a promising reinforcing additive for industrial 3D printing applications. *
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Robust materials in medical applications are sought after and researched, especially for 3D printing in bone tissue engineering. Poly[ε-caprolactone] (PCL) is a commonly used polymer for scaffolding and other medical uses. Its strength is a drawback compared to other polymers.

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This study aimed to investigate the potential of antimony-doped tin oxide (ATO) as a reinforcing agent for polyamide 12 (PA12) in 3D printing by examining four mixtures with varying ATO concentrations (2.0 to 8.0 wt.

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In this study, titanium nitride (TiN) was selected as an additive to a high-density polyethylene (HDPE) matrix material, and four different nanocomposites were created with TiN loadings of 2.0-8.0 wt.

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Acrylonitrile butadiene styrene (ABS) composites were prepared in filament form compatible with the material extrusion (MEX) 3D printing method, using biochar as a filler at various loadings of up to 10.0 wt %. Samples were fabricated to experimentally investigate their mechanical performance.

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Glass was introduced as an additive to filaments used for the manufacturing of composite materials, employed by Additive Manufacturing applications. Glass accounts for a large waste electric and electronic equipment (WEEE) percentage, and its recovery and recycling can lead to the production of sustainable composite materials. In this work, poly(lactic acid) (PLA)/commercially available silicon oxide composite filaments were manufactured and their structural, thermal, rheological, and mechanical properties were assessed.

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In this study, poly (ethylene terephthalate) (PETG) was combined with Antimony-doped Tin Oxide (ATO) to create five different composites (2.0-10.0 wt.

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Polyethylene terephthalate glycol (PETG) and silicon nitride (SiN) were combined to create five composite materials with SiN loadings ranging from 2.0 wt.% to 10.

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High-density polyethylene polymer (HDPE) and carbon black (CB) were utilized to create HDPE/CB composites with different filler concentrations (0.0, 2.0, 4.

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The goal of this paper is to investigate tungsten carbide (WC) as a reinforcement in the popular material extrusion (MEX) additive manufacturing (AM) procedure. The impressive characteristics of WC demonstrate its potential as a valuable additive for commonly used polymeric matrices in MEX 3D printing, offering reinforcement and stabilization properties. The mechanical properties of hybrid polymer/ceramic nanocomposites made up of various filler loadings (0-10 wt.

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The current research aimed to examine the thermomechanical properties of new nanocomposites in additive manufacturing (AM). Material extrusion (MEX) 3D printing was utilized to evolve acrylonitrile butadiene styrene (ABS) nanocomposites with silicon nitride nano-inclusions. Regarding the mechanical and thermal response, the fabricated 3D-printed samples were subjected to a course of standard tests, in view to evaluate the influence of the SiN nanofiller content in the polymer matrix.

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The effect of Cellulose NanoFiber (CNF) addition to a medical-grade resin in Stereolithography (SLA) Additive Manufacturing (AM) technology is reported, aiming to elaborate an easily processable, highly stiff bio-compound. CNFs were shear stir blended at various weight ratios with liquid resin. The fabricated nanocomposite materials were introduced in an SLA 3D printer for specimens manufacturing.

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This study introduced binary nanoparticle (NP) inclusions into a biomedical-grade photosensitive resin (Biomed Clear-BC). Multi-functional, three-dimensional (3D) printed objects were manufactured via the vat photopolymerization additive manufacturing (AM) technique. Cellulose nanofibers (CNFs) as one dimensional (1D) nanomaterial have been utilized for the mechanical reinforcement of the resin, while three different spherical NPs, namely copper NPs (nCu), copper oxide NPs (nCuO), and a commercial antimicrobial powder (nAP), endowed the antimicrobial character.

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In the current study, nanocomposites of medical-grade polyamide 12 (PA12) with incorporated copper (I) oxide (cuprous oxide-CuO) were prepared and fully characterized for their mechanical, thermal, and antibacterial properties. The investigation was performed on specimens manufactured by fused filament fabrication (FFF) and aimed to produce multi-purpose geometrically complex nanocomposite materials that could be employed in medical, food, and other sectors. Tensile, flexural, impact and Vickers microhardness measurements were conducted on the 3D-printed specimens.

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Most people touch their faces unconsciously, for instance to scratch an itch or to rest one's chin in their hands. To reduce the spread of the novel coronavirus (COVID-19), public health officials recommend against touching one's face, as the virus is transmitted through mucous membranes in the mouth, nose and eyes. Students, office workers, medical personnel and people on trains were found to touch their faces between 9 and 23 times per hour.

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Background And Objective: The study of small vessels allows for the analysis and diagnosis of diseases with strong vasculopathy. This type of vessels can be observed non-invasively in the retina via fundoscopy. The analysis of these vessels can be facilitated by applications built upon Retinal Image Registration (RIR), such as mosaicing, Super Resolution (SR) or eye shape estimation.

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The ability to predict, anticipate and reason about future outcomes is a key component of intelligent decision-making systems. In light of the success of deep learning in computer vision, deep-learning-based video prediction emerged as a promising research direction. Defined as a self-supervised learning task, video prediction represents a suitable framework for representation learning, as it demonstrated potential capabilities for extracting meaningful representations of the underlying patterns in natural videos.

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Objective: In-vivo assessment of small vessels can promote accurate diagnosis and monitoring of diseases related to vasculopathy, such as hypertension and diabetes. The eye provides a unique, open, and accessible window for directly imaging small vessels in the retina with non-invasive techniques, such as fundoscopy. In this context, accurate registration of retinal images is of paramount importance in the comparison of vessel measurements from original and follow-up examinations, which is required for monitoring the disease and its treatment.

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We present a sensor-fusion method that exploits a depth camera and a gyroscope to track the articulation of a hand in the presence of excessive motion blur. In case of slow and smooth hand motions, the existing methods estimate the hand pose fairly accurately and robustly, despite challenges due to the high dimensionality of the problem, self-occlusions, uniform appearance of hand parts, etc. However, the accuracy of hand pose estimation drops considerably for fast-moving hands because the depth image is severely distorted due to motion blur.

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We describe the fabrication of metamaterial magnifying hyperlenses with subwavelength wire array structures for operation in the mid-infrared (around 3 μm). The metadevices are composed of approximately 500 tin wires embedded in soda-lime glass, where the metallic wires vary in diameter from 500 nm to 1.2 μm along the tapered structure.

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We consider the problem of estimating realistic contact forces during manipulation, backed with ground-truth measurements, using vision alone. Interaction forces are usually measured by mounting force transducers onto the manipulated objects or the hands. Those are costly, cumbersome, and alter the objects' physical properties and their perception by the human sense of touch.

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Luminescent solar concentrators (LSCs) utilizing stimulated emission by a seed laser are a promising approach to overcome the limitations of conventional LSCs, with a significant reduction of the photovoltaic material. In our previous work, we demonstrated the principle of a stimulated LSC (s-LSC) and correspondingly developed a model for quantifying the output power of such a system, taking into account different important physical parameters. The model suggested Perylene Red (PR) dye as a potential candidate for s-LSCs.

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This work regards an investigation of the accuracy of a state-of-the-art, keypoint-based retinal image registration approach, as to the type of keypoint features used to guide the registration process. The employed registration approach is a local method that incorporates the notion of a 3D retinal surface imaged from different viewpoints and has been shown, experimentally, to be more accurate than competing approaches. The correspondences obtained between SIFT, SURF, Harris-PIIFD and vessel bifurcations are studied, either individually or in combinations.

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In this paper, a retinal image registration method is proposed. The approach utilizes keypoint correspondences and assumes that the human eye has a spherical or ellipsoidal shape. The image registration problem amounts to solving a camera 3D pose estimation problem and, simultaneously, an eye 3D shape estimation problem.

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The efficiency improvement of luminescent solar concentrators (LSCs) necessary for practical realization is currently hindered by one major loss mechanism: reabsorption of emitted photons by the luminophores. Recently, we explored a promising technique for reducing reabsorption and also improving directional emission in LSCs utilizing stimulated emission, rather than only spontaneous emission, with an inexpensive seed laser. In this work, a model is developed to quantify the gain (i.

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