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Abstract Hydrophobic surfaces have a wide range of applications, such as water harvesting, self-cleaning, and anti-biofouling. However, traditional methods of achieving hydrophobicity often involve the use of toxic materials such as fluoropolymers. This study aims to create controllable wettability surfaces with a three-dimensional geometry using a laser base powder bed fusion (PBF) process with commercially pure titanium (CP-Ti) and silicone oil as non-toxic materials. The optimal PBF process parameters for fabricating micropillar structures, which are critical for obtaining the surface roughness necessary for achieving hydrophobic properties, were investigated experimentally. After fabricating the micropillar structures using PBF, their surface energy was reduced by treatment with silicone oil. Silicone oil provides a low-surface-energy coating that contributes to the water-repellent nature of hydrophobic surfaces. The wettability of the treated CP-Ti surfaces was evaluated based on the diameter of the pillars and the space between them. The structure with the optimal diameter and spacing of micropillars exhibited a high contact angle (156.15°). A pronounced petal effect (sliding angle of 25.9°) was achieved because of the morphology of the pillars, indicating the controllability of wetting. The micropillar diameter, spacing, and silicone oil played crucial roles in determining the water contact and sliding angle, which are key metrics for surface wettability.

The direct energy deposition (DED) process requires proper interlayer cooling (IC) to avoid geometric failure caused by overheating of the midsection. This study suggests an optimum IC step based on a constitutive equation, instead of trial and error, to ensure the geometric stability of DED-processed 316 L stainless steel within a short period. The temperatures after cooling (TC) were acquired per layer of building and precisely measured using a constitutive model. Subsequently, a cooling period to maintain a target TC was calculated for the 30-layered DED specimen using the model. The optimum IC step varied with the number of deposited layers: (i) non-IC up to the fourth layer, (ii) IC step of 1.05 s for the fifth layer, and (iii) IC step of 2.21 s for the subsequent layers. The developed approach resulted in a remarkable improvement in geometric stability (geometric error of 5.9%) compared with the DED specimen fabricated without an IC step (error of 33.5%). Furthermore, the processing time was reduced by 30% compared with a conventional IC step with a fixed interval of 5 s. The developed approach also led to homogeneous grain refinement and a resulting increase in microhardness.

The deposition bead geometry in the arc strike zone is often abnormal compared with that in the middle deposition zone. The accumulation of these errors in the deposition process results in defects in the overall geometry of the deposition bead. To prevent the accumulation of such errors, this study aimed to address the irregular deposition bead shape and deviation of the deposition bead geometry in the arc strike zone without changing the deposition path or introducing external devices. A support vector machine classifier, which is a typical application of machine-learning classification models, was used to obtain the deposition condition ranges for a uniform deposition bead shape. The deposition conditions of the arc strike and middle deposition zones that could reduce the deviation of the deposition bead geometry in the arc strike zone were obtained using support vector machine regression. These conditions were applied in the form of variable conditions in single-path deposition. Five-layer deposition was conducted to validate the regression model. As a result of the validation experiment, the average height and width errors in the arc strike zone were 0.36% and 1.28%, respectively, and the average height and width errors in the middle deposition zone were 0.64% and 1.26%, respectively. Therefore, the regression model can be used for accurate deposition, thereby reducing the post-processing cost.

Abstract In the directed energy deposition (DED) process, significant empirical testing is required to select the optimal process parameters. In this study, single-track experiments were conducted using laser power and scan speed as parameters in the DED process for titanium alloys. The results of the experiment confirmed that the deposited surface color appeared differently depending on the process parameters. Cross-sectional view, hardness, microstructure, and component analyses were performed according to the color data, and a color suitable for additive manufacturing was selected. Random forest (RF) and support vector machine multi-classification models were constructed by collecting surface color data from a titanium alloy deposited on a single track; the accuracies of the multi-classification models were compared. Validation experiments were performed under conditions that each model predicted differently. According to the results of the validation experiments, the RF multi-classification model was the most accurate.

Astrocytes are the most abundant cells in the brain, playing vital roles in neuronal survival, growth, and function. Understanding the mechanism(s) regulating astrocyte proliferation will have important implications in brain development, response to injury, and tumorigenesis. Cyclin B1 is well known to be a critical regulator of mitotic entry via its interaction with cyclin-dependent kinase 1. In rat astrocytes, we now show that the mRNA binding protein cytoplasmic polyadenylation element binding protein 1 (CPEB1) is associated with cyclin B1 mRNA and that this interaction is enriched at the centrosome. In addition, if growth-arrested astrocytes are stimulated to divide, CPEB1 is phosphorylated and cyclin B1 mRNA is polyadenylated, both hallmarks of CPEB1 activation, resulting in an increase in cyclin B1 protein. CPEB1 binding to mRNA initially inhibits translation; therefore, removing CPEB1 from mRNA should result in an increase in translation due to derepression. Indeed, when we either knocked down CPEB1 protein with siRNA or sequestered it from endogenous mRNA by expressing RNA containing multiple CPEB1 binding sites, cyclin B1 protein was increased and cell proliferation was stimulated. Our data suggest a mechanism wherein CPEB1 is bound and represses cyclin B1 mRNA translation until a signal to proliferate phosphorylates CPEB1, resulting in an increase in cyclin B1 protein and progression into mitosis. Our results demonstrate for the first time a role for CPEB1 in regulating cell proliferation in the brain. [ABSTRACT FROM AUTHOR]