“…The temperatures reached by the Nb metal wire are comparable to those reported for the growth of niobium oxide nanowires on metal foils by thermal treatment [11][12][13], but the times are clearly shorter. Thus, the rapid growth of the nanowires could be related to an increase in the diffusion rate of oxygen and niobium mobility due to electromigration [27].…”
Section: Resultsmentioning
confidence: 99%
“…Crystals 2024, 14, x FOR PEER REVIEW 5 of 12 niobium oxide nanowires on metal foils by thermal treatment [11][12][13], but the times are clearly shorter. Thus, the rapid growth of the nanowires could be related to an increase in the diffusion rate of oxygen and niobium mobility due to electromigration [27]. Then, we study the evolution of the nanowires with time for a fixed current value of 4.8 A (Figure 4).…”
Joule heating of niobium (Nb) metal wires by running a high electric current density through them has been used to grow Nb2O5 nanowires. The formation of a micrometric oxide layer on the Nb wires has also been observed. The size and density of the nanowires are related to the current values applied, as well as the thickness of the oxide layer formed. Characterization of both nanowires and oxide layer has been performed using X-ray diffraction, scanning electron microscopy, energy dispersive X-ray microanalysis, and micro-Raman spectroscopy. It has been observed that this method allows the growth of Nb2O5 nanowires in times as short as tens of seconds.
“…The temperatures reached by the Nb metal wire are comparable to those reported for the growth of niobium oxide nanowires on metal foils by thermal treatment [11][12][13], but the times are clearly shorter. Thus, the rapid growth of the nanowires could be related to an increase in the diffusion rate of oxygen and niobium mobility due to electromigration [27].…”
Section: Resultsmentioning
confidence: 99%
“…Crystals 2024, 14, x FOR PEER REVIEW 5 of 12 niobium oxide nanowires on metal foils by thermal treatment [11][12][13], but the times are clearly shorter. Thus, the rapid growth of the nanowires could be related to an increase in the diffusion rate of oxygen and niobium mobility due to electromigration [27]. Then, we study the evolution of the nanowires with time for a fixed current value of 4.8 A (Figure 4).…”
Joule heating of niobium (Nb) metal wires by running a high electric current density through them has been used to grow Nb2O5 nanowires. The formation of a micrometric oxide layer on the Nb wires has also been observed. The size and density of the nanowires are related to the current values applied, as well as the thickness of the oxide layer formed. Characterization of both nanowires and oxide layer has been performed using X-ray diffraction, scanning electron microscopy, energy dispersive X-ray microanalysis, and micro-Raman spectroscopy. It has been observed that this method allows the growth of Nb2O5 nanowires in times as short as tens of seconds.
“…The interaction of the laser beam with a stream of powder particles and the substrate is depicted schematically in Figure 1 (Mahmood et al , 2020c; Mahmood et al , 2020c). When the laser beam coincides with the substrate surface, a portion of it is absorbed by the powder elements and substrate, resulting in melt pool formation (Yang et al , 2023; Zhang et al , 2022d; Zhang et al , 2023). Three powder jets combine to form a single conical stream of powder particles fed directly into the melt pool created by the high-power focused laser spot, resulting in layer formation (Guo et al , 2023; Tian et al , 2022; Wang et al , 2020).…”
Purpose
Porosity is a commonly analyzed defect in the laser-based additive manufacturing processes owing to the enormous thermal gradient caused by repeated melting and solidification. Currently, the porosity estimation is limited to powder bed fusion. The porosity estimation needs to be explored in the laser melting deposition (LMD) process, particularly analytical models that provide cost- and time-effective solutions compared to finite element analysis. For this purpose, this study aims to formulate two mathematical models for deposited layer dimensions and corresponding porosity in the LMD process.
Design/methodology/approach
In this study, analytical models have been proposed. Initially, deposited layer dimensions, including layer height, width and depth, were calculated based on the operating parameters. These outputs were introduced in the second model to estimate the part porosity. The models were validated with experimental data for Ti6Al4V depositions on Ti6Al4V substrate. A calibration curve (CC) was also developed for Ti6Al4V material and characterized using X-ray computed tomography. The models were also validated with the experimental results adopted from literature. The validated models were linked with the deep neural network (DNN) for its training and testing using a total of 6,703 computations with 1,500 iterations. Here, laser power, laser scanning speed and powder feeding rate were selected inputs, whereas porosity was set as an output.
Findings
The computations indicate that owing to the simultaneous inclusion of powder particulates, the powder elements use a substantial percentage of the laser beam energy for their melting, resulting in laser beam energy attenuation and reducing thermal value at the substrate. The primary operating parameters are directly correlated with the number of layers and total height in CC. Through X-ray computed tomography analyses, the number of layers showed a straightforward correlation with mean sphericity, while a converse relation was identified with the number, mean volume and mean diameter of pores. DNN and analytical models showed 2%–3% and 7%–9% mean absolute deviations, respectively, compared to the experimental results.
Originality/value
This research provides a unique solution for LMD porosity estimation by linking the developed analytical computational models with artificial neural networking. The presented framework predicts the porosity in the LMD-ed parts efficiently.
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