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Flexographic printed microwave-assisted grown zinc oxide nanostructures for sensing applications
Publication . Morais, Maria; Carlos, Emanuel; Rovisco, Ana; Calmeiro, Tomás; Gamboa, Hugo; Fortunato, Elvira; Martins, Rodrigo; Barquinha, Pedro; CENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N); DCM - Departamento de Ciência dos Materiais; UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias; LIBPhys-UNL; RSC - Royal Society of Chemistry
The development of flexible electronics has increased the demand for wearable pressure sensors that can be used to monitor various biomedical signals. In this context, pressure sensors based on zinc oxide (ZnO) have great potential since, besides the biocompatibility and biodegradability of this metal oxide, it also has piezoelectric properties. The common feature of these sensors is the alignment of the ZnO nanostructures in the strain direction. This alignment is achieved through a three-stage procedure: deposition of a ZnO nanoparticle layer (seed layer) followed by its patterning and the subsequent growth of nanostructures from the seed layer nanoparticles. Herein, a process compatible with industrial scale for depositing seed layers by flexographic printing is proposed, allowing seed layers to be deposited and patterned swiftly and efficiently in a single step on flexible indium tin oxide coated polyethylene terephthalate substrates, significantly decreasing the time and cost required to produce pressure sensors. The growth conditions of ZnO nanorods on these substrates were also studied to analyze their influence on the morphological and structural characteristics of the nanostructures. Nanorods with length of (0.27 ± 0.04) μm and density of (296 ± 6) nanorods per μm2 were obtained in microwave-assisted hydrothermal syntheses carried out at 100 °C for 30 min, with a 1 M zinc acetate seed layer and using an equimolar growth solution of zinc nitrate and hexamethylenetetramine. These conditions were used to produce ZnO-based pressure sensors with two patterns (one square and 16 individual squares). Although the single square sensors displayed a higher average output voltage ((12 ± 5) V for an impact pressure of 150 kPa), their response was considerably more variable than the patterned sensors (with 16 squares), which displayed an average output voltage of (8 ± 2) V under an applied pressure of 150 kPa and sensitivity values of (0.06 ± 0.01) V kPa−1, demonstrating their potential for wearables and portable electronics.
Gas tungsten arc welding of a multiphase CoCuxFeMnNi (x=20,30) high entropy alloy system
Publication . Lopes, J. G.; Varela, M.; Shim, S. H.; Schell, N.; Maawad, E.; Hong, S. I.; Baptista, A. C.; Oliveira, J. P.; UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial; DEMI - Departamento de Engenharia Mecânica e Industrial; DCM - Departamento de Ciência dos Materiais; CENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N); Elsevier Science B.V., Amsterdam.
With the current advancements in materials science, the development of high entropy alloys (HEAs) is progressively increasing. Hence, research on their processability is essential to make them competitive alternatives to common engineering alloys that are widely used in structural applications. One manufacturing technique commonly employed in this sector is gas tungsten arc welding (GTAW). This technique allows to obtain single monolithic parts from separate components, often at the cost of local microstructural and mechanical properties variation across the joint. As such, GTAW processing is capable of supplying relevant knowledge regarding the feasibility of joining new materials and their potential industry uptake. In this study, we present a comparative analysis on the use of GTAW on two distinct multiphase high entropy alloys: CoCu20FeMnNi and the CoCu30FeMnNi. Firstly, microstructural observations coupled with CalPhaD-based calculations and synchrotron X-ray diffraction analysis, allowed to delve, and compare, the microstructural evolution across both welds. It was possible to observe the dual phase nature of the microstructure throughout the welded joint alongside the nucleation of a B2 BCC phase in the heat affected zone (HAZ) of both HEAs. Considering the mechanical properties of the welded materials, results evidenced a poorer, yet still acceptable mechanical performance. The observed decrease in mechanical strength is attributed to the residual stress conditions and large grain size that developed owing to the process thermal cycle, which contrasted deeply with the microstructure of each base material.
Next-Generation Solar-Powering
Publication . Santos, Ivan M.; Alexandre, Miguel; Vicente, António T.; Teixeira, Cristina; Almeida, Eva; Fortunato, Elvira; Martins, Rodrigo; Águas, Hugo; Mendes, Manuel J.; CENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N); DCM - Departamento de Ciência dos Materiais; UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias; Wiley
Escalating environmental and energy supply concerns, coupled with an increasing interest in space exploration, are driving the development of advanced energy harvesting systems and the adoption of cutting-edge photovoltaic (PV) technologies. Photonics allows precise light manipulation in a multitude of ways, empowering PV with the means to tackle the multifaceted challenges inherent to the harsh space environment, with great potential to concomitantly spin off to on-Earth systems, prioritizing efficiency and reliability. This review thus synthesizes the key insights from the latest experimental and simulation R&D outcomes to inform the design and implementation of advanced photonic strategies for various PV applications. The state-of-the-art performance and foreground of photonic-managed thick- (single-junction crystalline silicon, c-Si, and perovskite-on-silicon tandem) and thin-film (hydrogenated amorphous silicon, a-Si:H, and perovskite) PV devices are assessed by comparison with theoretical ideal light-trapping scenarios (single-, double-pass, and Lambertian absorption models), looking also at the potential of photonic coolers as an emergent platform for effective thermal management. Finally, this work examines novel photonic approaches for spectrum modification, emphasizing the relevance of illumination-tailoring for outer space systems.
A review on physics-informed machine learning for process-structure-property modeling in additive manufacturing
Publication . Faegh, Meysam; Ghungrad, Suyog; Oliveira, João Pedro; Rao, Prahalada; Haghighi, Azadeh; CENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N); Elsevier BV
This article presents a state-of-the-art review of the emerging field of physics-informed machine learning (PIML) models in additive manufacturing for process-structure-property modeling. Additive manufacturing processes hold immense potential for fabricating intricate and complex geometries across diverse applications and material classes. From a quality assurance standpoint, appropriate modeling of process-structure-property relationships of additive manufacturing processes using either physics-based or machine learning (ML)-based approaches has been a topic of intensive research. As an example, ML of data acquired from in-situ sensors is related to flaw formation, e.g., porosity, cracking, or deformation. In recent years, the computational burden of pure physics-based models, the large data set requirement, and their black-box nature, i.e., the lack of interpretability of ML models, have prompted researchers to turn to PIML models. In PIML models, physical insights of the additive manufacturing process gained from various means are integrated with ML models, resulting in a more robust and interpretable framework for both process and microstructure evolution. A key delineator is the source of physical knowledge to be fused into PIML models, which can be obtained either from governing physical equations, data-centric feature extraction without implementing any physical equations, or a hybrid of the two foregoing. Within this review, we stratify PIML models based on the method used for the fusion of physical knowledge to ML models, into three categories, namely: (i) physics-based feature engineering, (ii) physics-based architecture shaping of ML models, and (iii) physics-based modification of the loss function of the ML models. For each of these categories, we further delineate the source of physical knowledge, ML models, integration approach, and data-set requirement, among others. A comparative analysis of the reviewed studies is presented and critically discussed, while the potential research gaps, along with future research directions on developing PIML models for different AM technologies are outlined.
Minimizing the maximum von Mises stress of elastic continuum structures using topology optimization and additively manufactured functionally graded materials
Publication . Silva, Rui F.; Coelho, Pedro G.; Conde, Fábio M.; Santos, Bernardo R.; Oliveira, João P.; UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial; DEMI - Departamento de Engenharia Mecânica e Industrial; DCM - Departamento de Ciência dos Materiais; CENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N); Elsevier Science B.V., Amsterdam.
The rising cost of natural resources and environmental concerns motivate systematic design and manufacture of more efficient structures. For that purpose, topology optimization has been appealing, as well as working on an enlarged design space to include multi-material solutions. The resulting optimal designs can be materialized using multi-material additive manufacturing. In the present framework, multi-material printed parts or layouts can be envisaged as having better strength properties than single-material counterparts. The maximum von Mises stress is minimized inside a design domain through topology changes and material selection. The selected composite material model encompasses either the classical arrange of two discrete materials with sharp interfaces, or their mixture controlled by the volume fraction of each base material to generate a Functionally Graded Material (FGM). An optimized continuous variation of properties makes the FGM appealing to mitigate stress concentrations. To adequately capture the physics of mixtures considering the FGM's mechanical properties, one uses the RAMP interpolation scheme within the Hashin-Shtrikman bounds. A set of plane stress benchmarks are proposed. It is shown that considerably lower stress peaks on the evaluated structures can be obtained on the account of introducing more than one solid phase, specifically in the case of FGM solutions.
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Fundação para a Ciência e a Tecnologia
Programa de financiamento
Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Programático
Número da atribuição
UIDP/50025/2020