Recent advancements of additive manufacturing technology have enabled the fabrication of complex geometries and fiber placement along customized paths. The proposed approach introduces a novel ...framework for the optimized topology and the fiber paths in order to create variable stiffness designs. The optimized distribution of the material is achieved by two different methods: a density-based method and a level-set method for orthotropic materials. The fiber orientation of each element or the fiber path is considered as the design variable. The optimized orientation is obtained using an energy-based method and a level-set based method. In addition to a fiber angle filtering scheme, three new approaches for the design of fiber infill pattern are introduced to enforce the fiber path continuity across the domain, ensure manufacturability, and achieve reduced compliance. The effects of fiber infill pattern techniques on the compliance is demonstrated in three benchmark case studies.
To take advantage of multi-material additive manufacturing technology using mixtures of metal alloys, a topology optimization framework is developed to synthesize high-strength spatially periodic ...metamaterials possessing unique thermoelastic properties. A thermal and mechanical stress analysis formulation based on homogenization theory is developed and is used in a regional scaled aggregation stress constraint method. Since specific load cases are not always known beforehand, a method of worst-case stress minimization is also included to efficiently address load uncertainty. It is shown that the two stress-based techniques lead to thermal expansion properties that are highly sensitive to small changes in material distribution and composition. To resolve this issue, a uniform manufacturing uncertainty method is utilized which considers variations in both geometry and material mixture. Test cases of high stiffness, zero thermal expansion, and negative thermal expansion microstructures are generated, and the stress-based and manufacturing uncertainty methods are applied to demonstrate how the techniques alter the optimized designs. Large reductions in stress are achieved while maintaining robust strength and thermal expansion properties.
•Development of homogenization-based, multi-material, thermoelastic stress analysis.•Formulations for worst-case loads and manufacturing uncertainties are discussed.•Low-stress robust microstructures with tailored thermal expansions are discussed.
Nanoparticles are often engineered as a scaffolding system to combine targeting, imaging and/or therapeutic moieties into a unitary agent. However, mostly overlooked, the nanomaterial itself ...interacts with biological systems exclusive of application-specific particle functionalization. This nanoparticle biointerface has been found to elicit specific biological effects, which we term 'ancillary effects'. In this Review, we describe the current state of knowledge of nanobiology gleaned from existing studies of ancillary effects with the objectives to describe the potential of nanoparticles to modulate biological effects independently of any engineered function; evaluate how these effects might be relevant for nanomedicine design and functional considerations, particularly how they might be useful to inform clinical decision-making; identify potential clinical harm that arises from adverse nanoparticle interactions with biology; and, finally, highlight the current lack of knowledge in this area as both a barrier and an incentive to the further development of nanomedicine.
•Simultaneous layout and compositional grading optimization.•Incorporation of failure constraint and its sensitivity in the optimization scheme.•Comparison of stiffness and strength-based designs for ...thermal and mechanical loads.•Comparison of single-material and multi-material optimized designs performance.
Gradient additive manufacturing techniques are capable of implementing multiple materials with graded compositions into the fabrication of a single component. This provides a unique opportunity to control the properties of materials, such as thermal expansion, Young’s modulus, and yield stress, and create a structure that otherwise would be infeasible. To utilize this capability, a density-based topology optimization framework is developed to optimize the spatial distribution of different materials, their interfaces, and the structural layout in order to enhance both the stiffness and the stress. Interpolation schemes to achieve these objectives are proposed, and the three levels of complexities, i.e., multi-material designs, design-dependent thermal loads, and stress constraints, are addressed. The framework is evaluated using three numerical examples, and the optimized stiffness and strength-based topology and material composition are demonstrated. Finally, the single-material and multi-material optimized designs are compared. The results show that the low compliance of the multi-material designs, while satisfying the failure constraint, was either infeasible or was achieved with a significantly higher weight for single-material structures.
This paper introduces a novel strength-based structural optimization technique capable of concurrent design of shape and fiber path in continuous fiber-reinforced composites. To this end, a higher ...order function, i.e., the level-set function, is employed to update both shape and fiber placement. The shape evolution relies on a shape sensitivity analysis based on the Tsai–Wu failure criterion. The fiber path evolution depends on the level-set function determined from the shape boundary. A scheme combining the classical level-set method using fixed mesh and a level-set-based mesh evolution method is developed to ensure the efficiency and accuracy of the process. A revision step over fiber orientations along the ridge of the level-set function is introduced to alleviate the local failure index singularity. Manufacturability of the design is further ensured by incorporating a thickness control term, avoiding the appearance of ultra-thin members in the optimized design. The developed scheme is applied to three benchmark examples, showing that the failure index concentration is largely reduced compared with the initial shape, the compliance-based optimized design, and the design with optimized shape but unidirectional fibers.
3D printing of high strength, lightweight, and relatively inexpensive parts can save engineers time and resources not possible otherwise. Continuous fiber reinforced polymer 3D printing has recently ...emerged to address this need. In contrast to conventional composites that consist of unidirectional or woven laminates, continuous fibers in 3D printed composites can be used to only partially reinforce each layer and/or be printed in curved patterns (infill patterns) to enhance mechanical performance. Understanding the mechanics of this new class of 3D printed (additively manufactured) composites is required for their optimal design and utilization in various applications. In this work, the thermo-mechanical response and failure mechanics of 3D printed composites are evaluated and correlated to their structure. We show that the strength of the 3D printed specimens depends strongly on the infill pattern and part geometry. Specifically, fiber curvatures and interfaces between reinforced and non-reinforced regions result in stress concentrations, multi-axial stress states, and pre-mature failure in parts. To better understand the failure in 3D printed composite structures, finite element analysis (FEA) was used. To this end, anisotropic properties were assigned to each element of the generated mesh based on the local fiber direction. FEA was able to capture experimental failure stresses and shed light on the failure mechanisms in tested specimens. Finally, we present rudimentary design rules that can be useful for designing 3D printed fiber reinforced parts.
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•The ‘ChemTrainer’ smartphone application was developed for colorimetric detection.•Hydrogen peroxide strip images were used to train for machine learning classifiers.•Over 90% ...classification accuracy was obtained for primary peroxide levels.•Color constancy algorithms positively affected classification accuracy.
A smartphone application based on machine learning classifier algorithms was developed for quantifying peroxide content on colorimetric test strips. The strip images were taken from five different Android based smartphones under seven different illumination conditions to train binary and multi-class classifiers and to extract the learning model. A custom app, “ChemTrainer”, was designed to capture, crop, and process the active region of the strip, and then to communicate with a remote server that contains the learning model through a Cloud hosted service. The application was able to detect the color change in peroxide strips with over 90% success rate for primary colors with inter-phone repeatability under versatile illumination. The utilization of a grey-world color constancy image processing algorithm positively affected the classification accuracy for binary classifiers. The developed app with a Cloud based learning model paves the way for better colorimetric detection for paper-based chemical assays.
Flower based nanoparticles has gained a special attention as a new sustainable eco-friendly avenue. Rosa floribunda charisma belongs to modern roses with bright yellow, red flowers with marvellous ...rose scent. Different methods were used for the extraction of its floral scent such as hexane, microwave, and solid-phase micro-extraction. The latter was the most efficient method for the extraction of phenyl ethyl alcohol, the unique scent of roses. In the current study, magnesium nanoparticles (RcNps) have been synthesized using Rosa floribunda charisma petals that have privileges beyond chemical and physical routs. RcNps formation was confirmed using UV-Visible (UV-Vis) Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), High Resolution-Transmission Electron Microscope (HR-TEM), Field Emission-Scanning Electron Microscope (FE-SEM), Energy dispersive X-ray (EDX), X-ray Diffractometer (XRD), and X-ray photoelectron spectroscopy (XPS). HR-TEM images detected the polyhedral shape of RcNps with a diverse size ranged within 35.25-55.14 nm. The resulting RcNps exhibited a high radical scavenging activity illustrated by inhibition of superoxide, nitric oxide, hydroxyl radical and xanthine oxidase by by IC
values 26.2, 52.9, 31.9 and 15.9 µg/ml respectively as compared to ascorbic acid. Furthermore, RcNps at concentration of 100 µg/ml significantly reduced xanthine oxidase activity (15.9 ± 0.61 µg/ml) compared with ascorbic acid (12.80 ± 0.32 µg/ml) with p < 0.05. Moreover, RcNps showed an excellent antiaging activity demonstrated by inhibition of collagenase, elastase, hyaluronidase and tyrosinase enzymes in a dose-dependent manner with IC
values of 58.7 ± 1.66 µg/ml, 82.5 ± 2.93 µg/ml, 191.4 ± 5.68 µg/ml and 158.6 ± 5.20 µg/ml as compared to EGCG respectively. RcNps also, exhibited a promising antibacterial activity against three skin pathogens delineate a significant threat to a public health, as Staphylococcus epidermidis, Streptococcus pyogenes, and Pseudomonas aeruginosa with MIC of 15.63, 7.81, 31.25 µg/ml as compared to ciprofloxacin (7.81, 3.9 and 15.63 µg/ml). Moreover, RcNps suppressed the formation of biofilms with minimum biofilm inhibitory concentrations 1.95, 1.95, 7.81 µg/ml against the fore mentioned strains, respectively. Overall, our findings indicate that Rosa floribunda nanoparticles could be used as a leading natural source in skin care cosmetic industry.
Overview of the updated literature on the classification of adhesives systems and CAD/CAM materials with clinical guidelines to condition various surfaces for bonding to the tooth structure.
Searches ...were conducted in MEDLINE, EMBASE, PubMed, Web of Science, Scopus, Cochrane Library, and Google Scholar using specific keywords.
240 papers were revised, 150 articles were excluded, and 90 were eligible for the review. Most studies concluded the essentiality of bonding E-max, zirconia, and hybrid materials to enhance fracture toughness and fatigue resistance. The success of ceramic bonding depends on the microstructure and surface treatment of the materials. The proper treatment of the intaglio starts with using alumina oxide or hydrofluoric acid. This initial treatment could be followed by monobond salinization, which improves the chemical adhesion. Zirconia-based ceramics have grown lately and become the most prescribed for posterior and anterior teeth. Zirconia can be bonded to the tooth structure using the APC concept and 10 MDP promoting primers. Three hundred adhesive resin systems are currently available in the market, and each is different in chemical composition and clinical bonding strength. Of the three hundred systems, the total-etch system remains the gold standard, especially on the enamel surface. The self-etch adhesive system is favorable on dentin due to lowering the postoperative sensitivity. A new generation of dentin adhesives, called universal or multi-mode adhesives. This system has become popular and can be used either as etch-and-rinse or self-etch adhesives.
The chemistry of adhesive systems has changed across generations. The variation of dental tissue is the decisive factor in selecting adhesive systems, resin cement, and ceramic materials. Moreover, a reliable bonding strength necessitates a perfect surface treatment and bonding promoter for tooth and CAD/CAM materials.
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