- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
The Average Grain Size and Grain Aspect Ratio in Metal Laser Powder Bed Fusion: Modeling and Experiment
摘要： The additive manufacturing (AM) process induces high uncertainty in the mechanical properties of 3D-printed parts, which represents one of the main barriers for a wider AM processes adoption. To address this problem, a new time-efficient microstructure prediction algorithm was proposed in this study for the laser powder bed fusion (LPBF) process. Based on a combination of the melt pool modeling and the design of experiment approaches, this algorithm was used to predict the microstructure (grain size/aspect ratio) of materials processed by an EOS M280 LPBF system, including Iron and IN625 alloys. This approach was successfully validated using experimental and literature data, thus demonstrating its potential efficiency for the optimization of different LPBF powders and systems.
关键词： laser powder bed fusion,additive manufacturing,microstructure,process optimization,analytical model
更新于2025-09-23 15:21:01
-
Laser joining of titanium alloy to polyamide: influence of process parameters on the joint strength and quality
摘要： Laser-assisted metal–polymer joining (LAMP) is a novel assembly process for the development of miniaturized joints in hybrid lightweight products. This work adopts a design of experiments (DoE) approach to investigate the influence of several laser welding parameters on the strength and quality of titanium alloy (Ti-6Al-4V)–polyamide (PA6.6) assembly. Significant parameters were highlighted using the Plackett Burmann design, and process window was outlined using the Response Surface Method (RSM). A statistically reliable mathematical model was generated to describe the relation between highlighted welding parameters and joint strength. The analysis of variance (ANOVA) method was implemented to identify significant parametric interactions. Results show the prominence of focal position and laser power, as well as significant interaction between laser power and beam speed, on the joint strength. The evolution of weld defects (bubbles, excessive penetration, flashing, titanium coloring, weld pool cavities, and welding-induced deflection) along the process window was investigated using optical microscopy. The resulted deflection in titanium was quantified, and its relationship with welding parameters was mathematically modeled. Robust process window was outlined to maintain insignificant deflection in the welded joints. Results showed that the growth of weld defects correlates with a decline in joint strength. Optimal parameters demonstrated a defect-free joint, maximizing joint strength.
关键词： Hybrid joining,Metal–polymer assemblies,Laser beam joining,Process optimization
更新于2025-09-23 15:19:57
-
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics
摘要： Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.
关键词： Bayesian network,GaAs solar cells,photovoltaics,neural network surrogate model,process optimization
更新于2025-09-23 15:19:57
-
The influence of the pyramidal texture uniformity and process optimization on monocrystalline silicon solar cells
摘要： To improve the photoelectric conversion efficiency of monocrystalline silicon solar cells, the influence of the pyramidal texture uniformity on the defects in the monocrystalline silicon cells was analyzed by simulation, and the uniformity of the pyramidal texture was quantitatively characterized with the uniformity coefficient. The texturing process parameters were optimized by fitting and optimizing the uniformity coefficient. In the experiments herein, four groups of textured monocrystalline silicon wafers were obtained by treating them with a 1.2% sodium hydroxide (NaOH) solution for four different times. The uniformity coefficient of each monocrystalline silicon wafer group was obtained. By fitting the uniformity coefficient, we obtained the texturing process parameters corresponding to the maximum uniformity coefficient. The experimental results show that the optimized monocrystalline silicon cell achieved a pyramidal texture with a maximum uniformity coefficient. In addition, the reflectivity of the monocrystalline silicon cell reached a minimum value, and the photoelectric conversion efficiency reached a maximum value. The uniformity coefficient can not only effectively quantify the uniformity of the pyramidal texture but also effectively optimize the texturing process parameters to improve the photoelectric conversion efficiency of monocrystalline silicon cells.
关键词： pyramidal texture uniformity,texturing process optimization,uniformity coefficient,photoelectric conversion efficiency,monocrystalline silicon solar cells
更新于2025-09-19 17:13:59
-
Research on the Effects of Process Parameters on Surface Roughness in Wet-Activated Silicon Direct Bonding Base on Orthogonal Experiments
摘要： Surface roughness is a very important index in silicon direct bonding and it is affected by processing parameters in the wet-activated process. These parameters include the concentration of activation solution, holding time and treatment temperature. The effects of these parameters were investigated by means of orthogonal experiments. In order to analyze the wafer roughness more accurately, the bear ratio of the surface was used as the evaluation index. From the results of the experiments, it could be concluded that the concentration of the activation solution affected the roughness directly and the higher the concentration, the lower the roughness. Holding time did not affect the roughness as acutely as that of the concentration, but a reduced activation time decreased the roughness perceptibly. It was also discovered that the treatment temperature had a weak correlation with the surface roughness. Based on these conclusions, the parameters of concentration, temperature and holding time were optimized respectively as NH4OH:H2O2=1:1 (without water), 70 °C and 5 min. The results of bonding experiments proved the validity of the conclusions of orthogonal experiments.
关键词： wet activation,process optimization,wafer bonding,surface hydrophilicity
更新于2025-09-09 09:28:46
-
Estudo das propriedades ópticas de vidros borosilicatos dopados com íons de Itérbio em fun??o da concentra??o
摘要： Rare Earth elements have been studied for different scientific areas due to its excellent spectroscopic and magnetic properties with possible application for construction of different optical and electric devices (MARTINS, 2005; LOUREN?O et al., 2011). In this work, it is studied the optical properties of Ytterbium (Yb3+) ions embedded in a lead-borosilicate glass matrix synthesized by the melting method, using the optical absorption and photoluminescence techniques. The Yb3+ ions were chosen to dope the glass matrix because it has an energy level scheme more simplified compared with other Rare-Earth ions, with only two energy levels, making it very attractive for the construction of high efficiency optical devices. Increasing the annealing temperature as well as the ion concentration in the matrix leads to a shift of the optical band gap of the matrix to higher energies. We believe that this shift (blue-shift) can be associated with the nanocrystallization process of the glass matrix SBP (SiO2, B2O3, PbO2). The reduction of radiative lifetime with increasing ion concentration in matrix was studied using the Stokowski empirical relation, in which, it studies processes of energy transfer as a function of Rare-Earth concentration.
关键词： LiCoO2 extraction,Recycling,Process optimization,Lithium-ion batteries
更新于2025-09-04 15:30:14