Multi-Laser Multi-Material powder bed fusion - vision and strategies

Multi-Laser Multi-Material powder bed fusion – vision and strategies - apresentação da tecnologia Powder Bed FusionThis work was supported by FCT national funds, under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020

Multi-material additive manufacturing for advanced high-tech components

Multi-Material Additive Manufacturing for Advanced High-Tech Components is a new open Special Issue of Materials, which aims to publish original and review papers regarding new scientific and applied research and make great contributions to finding, exploring and understanding novel multi-material components via additive manufacturing [...]Project Moedinov—New aesthetics for collection coins by using advanced technologies with the reference POCI-01-0247-FEDER-033361

Using multiple regression, neural networks and support vector machines to predict lamb carcasses composition

The objective of this work was to use a Data Mining (DM) approach to predict, using as predictors the car- cass measurements taken at slaughter line, the compo- sition of lamb carcasses. One hundred and twenty five lambs of Churra Galega Braganc ̧ana breed were slaugh- tered.During carcasses quartering, a caliper was used to perform subcutaneous fat measurements, over the max- imum depth of longissimus muscle (LM), between the 12th and 13th ribs (C12), and between the 1st and 2nd lumbar vertebrae (C1). The Muscle (MP), Bone (BP), Subcutaneous Fat (SFP), Inter-Muscular Fat (IFP), and Kidney Knob and Channel Fat (KKCF) proportions of lamb carcasses were computed. We used the rminer R library and compared three regression techniques: Mul- tiple Regression (MR), Neural Networks (NN) and Sup- port Vector Machines (SVM). The SVM model provided the lowest relative absolute error for the prediction of BP, SFP and KKCF, while MR presented the best pre- dictions for MP and IFP. Also, a sensitivity analysis procedure revealed the C12 measurement as the most relevant predictor for all five carcass tissues

A particle swarm-based algorithm for optimization of multi-layered and graded dental ceramics

The thermal residual stresses (TRSs) generated owing to the cooling down from the processing temperature in layered ceramic systems can lead to crack formation as well as influence the bending stress distribution and the strength of the structure. The purpose of this study is to minimize the thermal residual and bending stresses in dental ceramics to enhance their strength as well as to prevent the structure failure. Analytical parametric models are developed to evaluate thermal residual stresses in zirconia-porcelain multi-layered and graded discs and to simulate the piston-on-ring test. To identify optimal designs of zirconia-based dental restorations, a particle swarm optimizer is also developed. The thickness of each interlayer and compositional distribution are referred to as design variables. The effect of layers number constituting the interlayer between two based materials on the performance of graded prosthetic systems is also investigated. The developed methodology is validated against results available in literature and a finite element model constructed in the present study. Three different cases are considered to determine the optimal design of graded prosthesis based on minimizing (a) TRSs; (b) bending stresses; and (c) both TRS and bending stresses. It is demonstrated that each layer thickness and composition profile have important contributions into the resulting stress field and magnitude.info:eu-repo/semantics/publishedVersio

A superhydrophilic biomimicked ceramic-reinforced-polymer nanocomposite for enhanced slip resistance and adhesion

Slips and Falls (SFs) were not considered a major source of lethal injuries until recently. Two-third of SF accidents happen due to the presence of ice on the surface around countries with snowfall making it second prominent reason of fatal injuries. Nearly 70,000 serious SFs happen in Finland and Sweden every year, and about 17,000 people lose their lives in USA (annual 1 million cases). Approximately 83% of people in Russia and thousands of people fall during winter in the UK and die as per HSE-UK. WHO-2021 recorded 37.3 million SFs cases demanding medical attention including millions requiring intensive care which resulted into permanent injuries, trauma, loss of limbs, loss of jobs, and burden on insurance and healthcare. Huge monetary deficits were recorded in Finland as €2.4 billion, €280 million in Sweden, £42 million in the UK occurred due to SFs. USA and Canada spend more than $55 billions annually on healthcare due to SFs. An effective anti-slipping shoe-sole can prevent and avoid these mishaps. Shoe-sole design modifications like tread patterns, crampons, studs, spikes etc. or material variations to improve friction between the sole-ice interface have been utilised. Though crampons/spikes/studs are effective, they are unsuitable for indoor usages, physically challenged and children. Whereas material-based solutions lose their effectiveness due to quick wear or in the presence of wet ice with quasi-liquid layer. We introduce nano-powder based ceramic reinforced composite patterned with Laser Surface Texturing (LST). Patterns are nature-inspired and are adapted from gecko/frog toepad structures that offer excellent friction on dry and wet surfaces. This innovation is a combination of material and design modifications and is not limited to anti-slipping shoe-soles. E-skin, drug delivery, wound healing, and electronic sensor patches face severed adhesion due to handling of body fluid and perspiration at the interface. Silicone Rubber polymer and proven anti-bacterial nano powders of zirconia and/or titania were mixed, vulcanised and textured to produce microfibrillar structure. This composite is highly wettable, wear-resistant, and adhering to wet and dry surfaces by creating capillary bridges. The capillary bridges provide mechanical interlocking on icy surfaces and serve as suction locations for patches to absorb and evaporate the bodily exudations out. We used five zirconia compositions (1, 3, 5, 7, and 9% by weight) producing composite with three sizes of capillary cavities to obtain best capillary effect. The findings of the study include average Shore-A hardness (32 to 40), morphology and topography, parametric optimisation of LST parameters, and wettability analysis. Obtained nano composite has excellent physicochemical superhydrophilicity (absorption of water droplet within 50 milliseconds after contact) with high static and kinetic friction coefficients of 2.5 and 1.62, respectively on wet ice suitable for mentioned applications

Laser surface texturing of stainless-steel cutlery to integrate ceramic blocks: parametric optimization and patterning

Dynamic and fast-changing designs for cutleries or flatware are one important nature of this production business. Globalized hospitality merchandise, the demanding nature of modern customers, throat-to-throat competition of manufacturing industries, and the modernization of the manufacturing processes are some of the major challenges for the cutlery (silverware) manufacturing industry. So far, traditional methods of moulding and shaping are considered to be the best to provide static designs and trademark patterns of the organisation. Preparing a designed mould for a fixed blueprint of cutlery and then producing it in bulk is the sole purpose of existing methods. However, with the invention of laser engraving and design systems, the entire business of cutlery production has revolutionized. Allowing for different designs for different cutleries to set without changing the whole production line was the aim of this study. As shown in Figure 1, AISI-304 stainless steel, which is the general flatware material selected for laser engraving, was evaluated with three most vital input parameters (power, scanning speed and loops or number of passes) followed by the analysis of geometry, roughness, and volume removed/material removal (MR) as output variables. This study will provide insight into the know-how situation involving the processing of cutleries and introduction of different ceramic materials to the surface to define desired patterns. We produced different design patterns by laser and ingrained ceramic blocks on the silverware. This approach is much more flexible and adoptable for pattern changes. Besides that, there is no need to prepare a mould for each design. Belo Inox, Portugal supplied the silverware as per the collaborative project agreement.publishe

Nature inspired wet adhesive E-Skin patch for biosensing applications

Tree frogs are able to climb or stick to wet and rough surfaces. The hexagonal epithelial cells enclosed by profound passages which shield the surface of each toe pad and the array of nano-pillars on their surface are the main reason for their outstanding reversible adhesion in wet and rough environment. Inspired by the frog toe pad hexagonal hierarchical micro-pillars are developed by using Silicon rubber/ZrO2 nanocomposite. Due to the addition of oxide nanoparticles wettability properties of the rubber enhanced. The interlocking structures and hexagonal pattern helps to improve the capillary action and the sweat/water particles are drained easily, as a result surface adhesion increases. To design the hexagonal micro-pillars innovative laser engraving technique is adopted. The homogeneous distribution of nanoparticles and hierarchical hexagonal micro-patterns are confirmed through SEM analysis. This innovative design approach is helpful to design E-skin adhesive wearable devices for accurate monitoring of physiological signals.This work is supported by National Funds through the Portuguese Science Foundation (FCT) within project “FCT Reference No.: 030353 of IC&DT - AAC No. 02 / SAICT / 2017”, co-financed by the European Regional Development Fund (ERDF), through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Portugal 2020. Finally, this work was supported by FCT national funds, under the national support to R&D units grant, through the reference projects UIDB/04436/2020 and UIDP/04436/2020

Novo método de avaliação dinâmica da articulação patelo-femoral em RM

A patologia patelo-femoral é uma das mais frequentes causas de consulta do joelho. A problemática desta articulação é reconhecidamente multifactorial. Apesar de estabelecidos vários factores de risco, tem sido globalmente assumida a necessidade de uma avaliação dinâmica e objectiva desta “articulação”, face a recorrentes erros diagnósticos. Revela-se essencial, quer no âmbito do diagnóstico, orientando a triagem patológica (e por conseguinte a escolha das terapias mais adequadas); quer ao nível do “follow-up” do paciente, nomeadamente para avaliação dos novos métodos cirúrgicos incluindo reconstruções do ligamento patelo-femoral medial (LPFM) para instabilidades objectivas. A hipótese deste estudo é que, da avaliação funcional dinâmica combinada com os factores morfológicos clássicos pode resultar a detecção de novos factores de risco e de avaliação funcional pós operatória da patelo-femoral

Models for light propagation in the head: trends and implementation of Finite Element approaches

The simulation of light propagation in the head tissues has become of interest due to its applicability in transcranial photobiomodulation (tPBM). In silico studies appear as an effective way to research tPBM dosimetry and understand the light reach in the head tissues, as well as potential issues regarding tissue heating. Nonetheless, these computer models are still very simple and come with several limitations. Although Monte Carlo methods are still the most common models for the simulation of light propagation in the human head, deterministic models – mostly based on Finite Element Methods (FEM) – are becoming increasingly important and could offer a more computationally efficient solution for optical propagation modelling. Regarding tissues’ optical simulation, literature shows that the scalp, skull and brain are the most studied tissues, sometimes including the distinction between white and grey matter. These models show limitations, namely the complex geometry of the brain surface, which is usually not considered; and the oversight of the cerebrospinal fluid (CSF), which due to its low/non-scattering properties cannot be simulated using the diffusion approximation equation. One improvement that can be considered for future research is the standardization of the reduced scattering and absorption coefficients of the tissues, as studies report varying values. With this information, the skin, cranium and brain were simulated using FEM in COMSOL Multiphysics software. The scattering and absorption coefficients of the tissues were derived from values reported in literature. The simulations produced results closely aligned with the reviewed data, confirming that the selected parameters and approaches are adequate for reproducing expected outcomes in tPBM

Experimental and in silico models for studying light propagation in the head

Transcranial photobiomodulation (tPBM) is an alternative therapy to conventional approaches, with clinical studies that show promising results for the treatment of several neurological pathologies, such as stroke and dementia related conditions. Despite its potential, the optimal light parameters and dosimetry for effective tPBM therapy remain uncertain, with most literature on this topic highlighting the need for establishing optimal stimulation parameters. The efficiency of tPBM therapy is related to the propagation of light through the head tissues, which in turn depends on the tissues' optical properties. Therefore, the most accurate way to define optimal parameters for treatments is to first define how light interacts with the tissues involved. To this end, we aim to improve the understanding of tPBM by characterizing the propagation of light through the head tissues and develop tools for customized treatments. We approached the problem both experimentally and in silico. Experimentally, we developed optical mimicking phantoms for each of the head’s tissues. Agarose was used as a base, to which titanium dioxide, India ink, organometallic compounds, and laser-ablated gold and zinc nanoparticles were individually added. In parallel, we developed an in silico model for light propagation on those tissues, using the transmittance spectra obtained from the phantoms. The numerical simulation was implemented in COMSOL Multiphysics software, using Finite Element Methods. In the future, by using imaging data, such as Magnetic Resonance Imaging, we can construct patient-specific models, both with the phantoms and the numerical simulation, to provide the physicians with patient-specific treatment protocols. These advancements will improve outcomes for patients and thus further proving that light, a bioinspired therapy, can be the future for neurological treatments.This work was supported by the project PTDC/EME-EME/1681/2021—BrainStimMap, with DOI: 10.54499/PTDC/EME-EME/1681/202