RESUMO
In this paper, we investigated the applicability of ChatGPT AI in electronics research and development via a case study of applied sensors in embedded electronic systems, a topic that is rarely mentioned in the recent literature, thus providing new insight for professionals and academics. The initial electronics-development tasks of a smart home project were prompted to the ChatGPT system to find out its capabilities and limitations. We wanted to obtain detailed information on the central processing controller units and the actual sensors usable for the specific project, their specifications and recommendations on the hardware and software design flow additionally. Furthermore, an extensive literature survey was requested to see if the bot could offer scientific papers covering the given topic. It was found that the ChatGPT responded with proper recommendations on controllers. However, the suggested sensor units, the hardware and software design were only partially acceptable, with occasional errors in specifications and generated code. The results of the literature survey showed that non-acceptable, fabricated citations (fake authors list, title, journal details and DOI-Digital Object identifier) were presented by the bot. The paper provides a detailed qualitative analysis, a performance analysis and critical discussion of the aforementioned aspects while providing the query set, the generated answers and codes as supplied data with the goal to give added value to electronics researchers and developers if trying to reach out for the tools in their profession.
RESUMO
Stencil printing is the most crucial process in reflow soldering for the mass assembly of electronic circuits. This paper investigates different machine learning-based methods to predict the essential process characteristics of stencil printing: the area, thickness, and volume of deposited solder paste. The training dataset was obtained experimentally by varying the printing speed (from 20 to 120 mm/s), the size (area ratio from 0.35 to 1.7) of stencil apertures, and the particle size (characterized by a log-normal distribution) in the solder paste. Various machine learning-based methods were assessed; ANFIS-adaptive neuro-fuzzy inference systems; ANN artificial neural networks (with different learning methods); boosted trees, regression trees, SVM-support vector machines. Each method was optimized and fine-tuned with hyperparameter optimization, and the overfitting phenomenon was also prevented with cross-validation. The regression tree was the best performing approach for modelling the stencil printing, while ANN with the Bayesian regularization learning method was only slightly worse. The presented methodology for fine-tuning, parameter optimization, and the comparison of different machine learning-based methods can easily be adapted to any application field in electronics manufacturing.
RESUMO
Flux contained in solder paste significantly affects the process of solder joint creation during reflow soldering, including the creation of an intermetallic layer (IML). This work investigates the dependence of intermetallic layer thickness on ROL0/ROL1 flux classification, glossy or matt solder mask, and OSP/HASL/ENIG soldering pad surface finish. Two original SAC305 solder pastes differing only in the used flux were chosen for the experiment. The influence of multiple reflows was also observed. The intermetallic layer thicknesses were obtained by the image analysis of micro-section images. The flux type proved to have a significant impact on the intermetallic layer thickness. The solder paste with ROL1 caused an increase in IML thickness by up to 40% in comparison to an identical paste with ROL0 flux. Furthermore, doubling the roughness of the solder mask has increased the resulting IML thickness by 37% at HASL surface finish and by an average of 22%.
RESUMO
The properties of Sn99Ag0.3Cu0.7 (SACX0307) solder alloy reinforced with ZnO nanoparticles were investigated. The primary ZnO particle sizes were 50, 100, and 200 nm. They were added to a solder paste at a ratio of 1.0 wt %. The wettability, the void formation, the mechanical strength, and the thermoelectric parameters of the composite solder alloys/joints were investigated. Furthermore, microstructural evaluations were performed using scanning electron and ion microscopy. ZnO nanoparticles decreased the composite solder alloys' wettability, which yielded increased void formation. Nonetheless, the shear strength and the thermoelectric parameters of the composite solder alloy were the same as those of the SACX0307 reference. This could be explained by the refinement effects of ZnO ceramics both on the Sn grains and on the Ag3Sn and Cu6Sn5 intermetallic grains. This could compensate for the adverse impact of lower wettability. After improving the wettability, using more active fluxes, ZnO composite solder alloys are promising for high-power applications.
RESUMO
Manganese can be an optimal alloying addition in lead-free SAC (SnAgCu) solder alloys because of its low price and harmless nature. In this research, the mechanical properties of the novel SAC0307 (Sn/Ag0.3/Cu0.7) alloyed with 0.7 wt.% Mn (designated as SAC0307-Mn07) and those of the traditionally used SAC305 (Sn96.5/Ag3/Cu0.5) solder alloys were investigated by analyzing the shear force and Vickers hardness of reflowed solder balls. During the preparation of the reflowed solder balls, different cooling rates were used in the range from 2.7 K/s to 14.7 K/s. After measuring the shear force and the Vickers hardness, the structures of the fracture surfaces and the intermetallic layer were investigated by SEM (Scanning Electron Microscopy). The mechanical property measurements showed lower shear force for the SAC0307-Mn07 alloy (20-25 N) compared with the SAC305 alloy (27-35 N), independent of the cooling rate. However, the SAC0307-Mn07 alloy was softer; its Vickers hardness was between 12 and 13 HV, whereas the Vickers hardness of the SAC305 alloy was between 19 and 20 HV. In addition, structural analyses revealed rougher intermetallic compound layers in the case of the SAC0307-Mn07 alloy, which can inhibit the propagation of cracks at the solder-substrate interface. These two properties of SAC0307-Mn07 alloy, the softer nature and the rougher intermetallic layer, might result in better thermomechanical behavior of the solder joints during the lifetime of electronic devices.
RESUMO
The effect of copper substrate roughness and tin layer thickness were investigated on whisker development in the case of Sn thin-films. Sn was vacuum-evaporated onto both unpolished and mechanically polished Cu substrates with 1 µm and 2 µm average layer thicknesses. The samples were stored in room conditions for 60 days. The considerable stress-developed by the rapid intermetallic layer formation-resulted in intensive whisker formation, even in some days after the layer deposition. The developed whiskers and the layer structure underneath them were investigated with both scanning electron microscopy and ion microscopy. The Sn thin-film deposited onto unpolished Cu substrate produced less but longer whiskers than that deposited onto polished Cu substrate. This phenomenon might be explained by the dependence of IML formation on the surface roughness of substrates. The formation of IML wedges is more likely on rougher Cu substrates than on polished ones. Furthermore, it was found that with the decrease of layer thickness, the development of nodule type whiskers increases due to the easier diffusion of other atoms into the whisker bodies.
