In this work, an extrusion-based 3D printing technique was employed for processing of biobased blends of Poly(Lactic Acid) (PLA) with low-cost kraft lignin. In Fused Filament Fabrication (FFF) 3D ...printing process, objects are built in a layer-by-layer fashion by melting, extruding and selectively depositing thermoplastic fibers on a platform. These fibers are used as building blocks for more complex structures with defined microarchitecture, in an automated, cost-effective process, with minimum material waste. A sustainable material consisting of lignin biopolymer blended with poly(lactic acid) was examined for its physical properties and for its melt processability during the FFF process. Samples with different PLA/lignin weight ratios were prepared and their mechanical (tensile testing), thermal (Differential Scanning Calorimetry analysis) and morphological (optical and scanning electron microscopy, SEM) properties were studied. The composition with optimum properties was selected for the production of 3D-printing filament. Three process parameters, which contribute to shear rate and stress imposed on the melt, were examined: extrusion temperature, printing speed and fiber’s width varied and their effect on extrudates’ morphology was evaluated. The mechanical properties of 3D printed specimens were assessed with tensile testing and SEM fractography.
Carbon fiber reinforced polymer manufacturing is emerging, with multiple studies to focus on the design of interfacial reinforcement to ensure the maximum of composite properties, but also ...respectively to be able to align with zero defect manufacturing. The controversy on the engineering approach is a data-driven task that can be efficiently tackled by involving Artificial Intelligence in order to establish unbiased structure-property relations. In the present study, nanoindentation mapping data were processed with Machine Learning classification models to identify the interfacial reinforcement. The data preparation included normalization and sorting out of highly similar data with k-means clustering, since nanoindentation on epoxy matrix does not enhance insight on the mechanism of reinforcement. The trained models included neural networks, classification trees, and support vector machines. Realization of models' performance was evaluated on the test dataset as screening to obtain best fitted models for each algorithm. Transfer learning potential was demonstrated by extrapolating the prediction of best trained models to a validation dataset at different indentation depth with support vector machines outperforming the other models. Overall accuracy was 67% on the test dataset, F1 Score was 65% in the prediction of reinforcement mechanism classes and 72% in case of pristine specimen, while accuracy on validation dataset was 72.7%. Prediction metrics were comparable to other case studies of real-world classification problems. Computational time-cost for tuning and training was sustainable and equal to 2.3 min.
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•Artificial Intelligence (AI) identified the interface reinforcement in CFRPs.•Support Vector Machines performed well in both testing and validation of the model.•Functionalization on CFs was predicted with F1-score equal to 65% and accuracy 67%.•Model was validated at different nanoindentation depth with accuracy 72.7%.•Feedback from AI could enhance materials design, decision-making, and quality control.
Manufacturing of nanomaterials is an interdisciplinary field covering physics, chemistry, biology, materials science and engineering. The interaction between scientists with different disciplines ...will undoubtedly lead to the production of novel materials with tailored properties. The success of nanomanufacturing depends on the strong cooperation between academia and industry in order to be informed about current needs and future challenges, to design products directly transferred into the industrial sector. It is of paramount importance the selection of the appropriate method combining synthesis of nanomaterials with required properties and limited impurities as well as scalability of the technique. Their industrial use faces many obstacles as there is no suitable regulatory framework and guidance on safety requirements; specific provisions have yet to be established in EU legislation. Moreover, regulations related to the right of intellectual properties as well as the absence of an appropriate framework for patent registration are issues delaying the process of products’ industrial application. The utilization of high-quality nanomaterials is now growing and coming to the industrial arena rendering them as the next generation attractive resources with promising applications. Undoubtedly, the existing gap between basic research relating nanomaterials and their application in real life will be overcome in the coming decade.
With an ever-increasing material and design space available for Fused Filament Fabrication (FFF) technology, fabrication of complex three-dimensional structures with functional performance offers ...unique opportunities for product customization and performance-driven design. However, ensuring the quality and functionality of FFF-printed parts remains a significant challenge, as material-, process-, and system-level factors introduce variability and potentially hinder the translation of bulk material properties in the respective FFF counterparts. To this end, the present study presents a methodological framework for assessing the influence of process parameters on FFF strand stability and functional performance through a systematic analysis of FFF structural elements (1D stacks of FFF strands and 3D blocks), in terms of dimensional deviation from nominal geometry and resistivity, corresponding to the printability and functionality attributes, respectively. The influence of printing parameters on strand stability was investigated in terms of dimensional accuracy and surface morphology, employing optical microscopy and micro-computed tomography (mCT) for dimensional deviation analysis. In parallel, electrical resistance measurements were carried out to assess the effect of different process parameter combinations and toolpath patterns on functional performance. In low-level structural elements, strand height (H) was found to induce the greatest influence on FFF strand dimensional accuracy and resistivity, with higher H values leading to a reduction in resistivity of up to 38% in comparison with filament feedstock; however, this occurred at the cost of increased dimensional deviation. At higher structural levels, the overall effect of process parameters was found to be less pronounced, indicating that the translation of 1D strand properties to 3D blocks is subject to a trade-off due to competing mechanisms that facilitate/hinder current flow. Overall, the proposed framework enables the quantification of the influence of process parameters on the selected response variables, contributing to the development of standard operating procedures and recommendations for selecting optimal process parameters to achieve the desired process stability and functional performance in FFF.
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•A new growth mechanism is proposed for the CVD of CNTs.•Model predictions are in good agreement with experimental measurements.•Up to 750 °C, the process is limited by the carbon ...diffusion through the catalyst.•Above 750 °C, the gas-phase acetylene reaction results in catalyst deactivation.•The catalyst lifetime is investigated for the first time computationally.
The mechanisms of carbon nanotube (CNT) growth by chemical vapor deposition of acetylene on Fe/SiO2:Al2O3 (zeolite Y) catalyst are unraveled through a combined computational and experimental study. CNTs are synthesized in a horizontal reactor under atmospheric pressure within the temperature range 650 °C–850 °C and characterized by SEM, TEM and Raman spectroscopy. A macroscopic computational fluid dynamics (CFD) model accounting for fluid flow, heat transfer and species transport is developed for the process, incorporating also kinetic expressions for acetylene surface decomposition, acetylene gas-phase reactions, carbon diffusion through the bulk of the catalyst, carbon surface accumulation on the catalyst surface and eventually, CNTs growth. The experimental behavior of the CNTs growth can be accurately described by the proposed macroscopic model. Most importantly, theoretical predictions suggest that there are two distinct temperature regimes for CNTs formation: at the low temperature regime, the process is dominated by the competition between carbon diffusion through the catalyst and carbon impurity layer formation on the catalyst surface, while at higher temperature, the gas-phase reactions of acetylene prevails, releasing byproducts that deposit on the catalyst surface in the form of carbon impurities. Finally, using the developed computational approach, the catalyst lifetime, which is directly affected by these mechanisms, is correlated with the CNTs growth process.
The widespread use of nano-biomaterials (NBMs) has increased the chance of human exposure. Although ingestion is one of the major routes of exposure to NBMs, it is not thoroughly studied to date. ...NBMs are expected to be dramatically modified following the transit into the oral-gastric-intestinal (OGI) tract. How these transformations affect their interaction with intestinal cells is still poorly understood. NBMs of different chemical nature--lipid-surfactant nanoparticles (LSNPs), carbon nanoparticles (CNPs), surface modified Fe.sub.3O.sub.4 nanoparticles (FNPs) and hydroxyapatite nanoparticles (HNPs)--were treated in a simulated human digestive system (SHDS) and then characterised. The biological effects of SHDS-treated and untreated NBMs were evaluated on primary (HCoEpiC) and immortalised (Caco-2, HCT116) epithelial intestinal cells and on an intestinal barrier model. The application of the in vitro SDHS modified the biocompatibility of NBMs on gastrointestinal cells. The differences between SHDS-treated and untreated NBMs could be attributed to the irreversible modification of the NBMs in the SHDS. Aggregation was detected for all NBMs regardless of their chemical nature, while pH- or enzyme-mediated partial degradation was detected for hydroxyapatite or polymer-coated iron oxide nanoparticles and lipid nanoparticles, respectively. The formation of a bio-corona, which contains proteases, was also demonstrated on all the analysed NBMs. In viability assays, undifferentiated primary cells were more sensitive than immortalised cells to digested NBMs, but neither pristine nor treated NBMs affected the intestinal barrier viability and permeability. SHDS-treated NBMs up-regulated the tight junction genes (claudin 3 and 5, occludin, zonula occludens 1) in intestinal barrier, with different patterns between each NBM, and increase the expression of both pro- and anti-inflammatory cytokines (IL-1beta, TNF-alpha, IL-22, IL-10). Notably, none of these NBMs showed any significant genotoxic effect. Overall, the results add a piece of evidence on the importance of applying validated in vitro SHDS models for the assessment of NBM intestinal toxicity/biocompatibility. We propose the association of chemical and microscopic characterization, SHDS and in vitro tests on both immortalised and primary cells as a robust screening pipeline useful to monitor the changes in the physico-chemical properties of ingested NBMs and their effects on intestinal cells.
The development of nanocomposites relies on structure–property relations, which necessitate multiscale modeling approaches. This study presents a modeling framework that exploits mesoscopic models to ...predict the thermal and mechanical properties of nanocomposites starting from their molecular structure. In detail, mesoscopic models of polypropylene (PP)- and graphene-based nanofillers (graphene (Gr), graphene oxide (GO), and reduced graphene oxide (rGO)) are considered. The newly developed mesoscopic model for the PP/Gr nanocomposite provides mechanistic information on the thermal and mechanical properties at the filler–matrix interface, which can then be exploited to enhance the prediction accuracy of traditional continuum simulations by calibrating the thermal and mechanical properties of the filler–matrix interface. Once validated through a dedicated experimental campaign, this multiscale model demonstrates that with the modest addition of nanofillers (up to 2 wt %), the Young’s modulus and thermal conductivity show up to 35 and 25% enhancement, respectively, whereas the Poisson’s ratio slightly decreases. Among the different combinations tested, the PP/Gr nanocomposite shows the best mechanical properties, whereas PP/rGO demonstrates the best thermal conductivity. This validated mesoscopic model can contribute to the development of smart materials with enhanced mechanical and thermal properties based on polypropylene, especially for mechanical, energy storage, and sensing applications.
Nanotechnology, as a mature enabling technology, has great potential to boost societal welfare. However, nanomaterials' current and foreseen applications raise serious concerns about their impact on ...human health and the environment. These concerns emerge because a reliable risk assessment in nanotechnology is yet to be achieved. The reasons for such a shortcoming are the inherent difficulties in characterizing nanomaterials properties. The interaction of characterization with modeling is an open issue and, due to overarching concerns about the reliability of research results, usually framed within the context of research integrity. This essay explores the connection between these different, but deeply intertwined concerns and the way they enable the production of responsible nanotechnology, i.e., nanotechnology devoted to societal welfare.
Potential substantial societal benefits of nanotechnology are being compromised by the fact that nanomaterials' impact on human health and the environment cannot yet be reliably assessed. Three causes for this shortcoming are described, namely, the inherent difficulty of characterizing nanomaterials, the insufficient interaction of characterization with modeling, and the concerns about the reliability of research results, while highlighting their interlinkage.
Various stakeholders in science have put research integrity high on their agenda. Among them, research funders are prominently placed to foster research integrity by requiring that the organizations ...and individual researchers they support make an explicit commitment to research integrity. Moreover, funders need to adopt appropriate research integrity practices themselves. To facilitate this, we recommend that funders develop and implement a Research Integrity Promotion Plan (RIPP). This Consensus View offers a range of examples of how funders are already promoting research integrity, distills 6 core topics that funders should cover in a RIPP, and provides guidelines on how to develop and implement a RIPP. We believe that the 6 core topics we put forward will guide funders towards strengthening research integrity policy in their organization and guide the researchers and research organizations they fund.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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