Search

In this study, we present a novel approach to injection molding, focusing on the strength of weld lines in polyamide 6 (PA6) composite samples. By implementing a mold temperature significantly higher than the typical molding practice, which rarely exceeds 100°C, we assess the effects of advanced mold temperature management. The research introduces a newly engineered mold structure specifically designed for localized mold heating, distinguishing it as the 'novel cavity.' This innovative design is compared against traditional molding methods to highlight the improvements in weld line strength at elevated mold temperatures. To optimize the molding parameters, we apply an Artificial Neural Network (ANN) in conjunction with a Genetic Algorithm (GA). Our findings reveal that the optimal ultimate tensile strength (UTS) and elongation values are achieved with a filling time of 3.4 seconds, packing time of 0.8 seconds, melt temperature of 246°C, and a novel high mold temperature of 173°C. A specific sample demonstrated the best molding parameters at a filling time of 3.4 seconds, packing time of 0.4 seconds, melt temperature of 244°C, and mold temperature of 173°C, resulting in an elongation value of 582.6% and a UTS of 62.3 MPa. The most influential factor on the PA6 sample's UTS and elongation at the weld line was found to be the melt temperature, while the filling time had the least impact. SEM analysis of the fracture surfaces revealed ductile fractures with rough surfaces and grooves, indicative of the weld line areas' bonding quality. These insights pave the way for significant improvements in injection molding conditions, potentially revolutionizing the manufacturing process by enhancing the structural integrity of the weld lines in molded PA6 samples.

In this work, a photoelectrochemical reactor with an anode based on hybrid structure between conducting polymer polypyrrole (PPy) and porous silicon (PSi) was fabricated and utilized to evaluate the photocatalysis and electro‐assisted photocatalysis for degradation of rhodamine B (RhB) solution. The PSi was made of n‐type silicon single‐crystal wafer by the metal‐assisted chemical etching (MACE). The anode PPy/PSi formed following a polymerization of the PPy on the PSi from the vapour‐phase route using oxidant FeCl3. Typical material characterizations of the PPy, PSi and PPy/PSi were investigated via scanning electron microscope (SEM), and spectroscopies of Fourier‐transform infrared (FTIR), Raman scattering and UV‐vis. Under visible light radiation (halogen light with the wavelength region of 400–700 nm), photocatalytic and electro‐assisted photocatalytic processes of the reactor were conducted by degradation of the RhB solution. A heterojunction (p‐n) of the PPy/PSi was proposed to explain the efficient catalytic performance of the reactor. [ABSTRACT FROM AUTHOR]

Data transformation methods are utilized to convert datasets into non-integer formats, potentially altering their distribution patterns. This implies that the variance and standard deviation of the dataset may be altered after the dataset undergoes data transformation operations. Improving model accuracy is a primary application of these methods. This study compares the efficacy of three data transformation techniques: square root transformation, logarithmic transformation, and inverse transformation. The comparison is conducted within the context of developing a surface roughness model for a turning process. Eighteen experiments are performed using the Box-Behnken method, with surface roughness chosen as the response variable. The surface roughness dataset undergoes transformation using the mentioned methods. Four surface roughness regression models are then built: one without transformation, one with square root transformation, one with logarithmic transformation, and one with inverse transformation. Evaluation metrics include coefficient of determination (R-Sq), adjusted coefficient of determination (R-Sq(adj)), Mean Absolute Error (%MAE), and Mean Squared Error (%MSE). Results indicate logarithmic transformation as the most effective, followed by square root transformation, in enhancing model accuracy. The surface roughness model utilizing data transformation exhibits high R-Sq and R-Sq(adj) values, at 0.8792 and 0.7434 respectively. On the other hand, this model has %MAE and %MSE values of only 10.33 and 2.05 respectively. Conversely, inverse transformation exhibits the least effectiveness among the three methods. [ABSTRACT FROM AUTHOR]

Backgrounds/aims: Parenchymal-sparing anatomical hepatectomy (Ps-AH) based on portal ramification of the right anterior section (RAS) is a new technique to avoid unnecessarily transecting too much liver parenchyma, especially in cases of major anatomical hepatectomy., Methods: We prospectively assessed 26 patients with primary hepatic malignancies having undergone major Ps-AH based on portal ramification of the RAS from August 2018 to August 2022 (48 months). The perioperative indications, clinical data, intra-operative index, pathological postoperative specimens, postoperative complications, and follow-up results were retrospectively evaluated., Results: Among the 26 patients analyzed, there was just one case that had intrahepatic cholangiocarcinoma The preoperative level of α-Fetoprotein was 25.2 ng/mL. All cases (100%) had Child-Pugh A liver function preoperatively. The ventral/dorsal RAS was preserved in 19 and 7 patients, respectively. The mean surgical margin was 6.2 mm. The mean surgical time was 228.5 minutes, while the mean blood loss was 255 mL. In pathology, 5 cases (19.2%) had microvascular invasion, and in the group of HCC patients, 92% of all cases had moderate or poor tumor differentiation. Six cases (23.1%) of postoperative complications were graded over III according to the Clavien-Dindo system, including in three patients resistant ascites or intra-abdominal abscess that required intervention., Conclusions: Parenchymal-sparing anatomical hepatectomy based on portal ramification of the RAS to achieve R0-resection was safe and effective, with favorable short-term outcomes. This technique can be used widely in clinical practice.