Laser powder bed fusion (LPBF) is an additive manufacturing technique that is gaining popularity for producing metallic parts in various industries. However, parts produced by LPBF are prone to residual stress, deformation, cracks and other quality defects due to uneven temperature distribution during the LPBF process. To address this issue, in prior work, the authors have proposed SmartScan, a method for determining laser scan sequence in LPBF using a model-based and optimization-driven approach, rather than using heuristics, and applied it to simple 2D geometries. This paper presents a generalized SmartScan methodology that is applicable to arbitrary 3D geometries. This is achieved by: (1) expanding the thermal model and optimization approach used in SmartScan to multiple layers; (2) enabling SmartScan to process shapes with arbitrary contours and infill patterns within each layer and (3) providing SmartScan with global foresight to make it less myopic in its optimization. Sample 3D parts are printed using the proposed generalized SmartScan and compared to those printed using standard heuristic scan sequences. Reductions of up to 93% in temperature inhomogeneity, 87% in residual stress, and 26% in maximum deformation were observed, without significantly sacrificing print speed. However, SmartScan was found to cause minor (<5%) to significant (up to 20%) increases in surface roughness compared to the heuristic approaches, depending on the scan pattern used.

Parts produced by laser or electron-beam powder bed fusion (PBF) additive manufacturing are prone to residual stresses, deformations, and other defects linked to non-uniform temperature distribution during the manufacturing process. Several researchers have highlighted the important role scan sequence plays in achieving uniform temperature distribution in PBF. However, scan sequence continues to be determined offline based on trial-and-error or heuristics, which are neither optimal nor generalizable. To address these weaknesses, we have articulated a vision for an intelligent online scan sequence optimization approach to achieve uniform temperature distribution, hence reduced residual stresses and deformations, in PBF using physics-based and data-driven thermal models. This paper proposes SmartScan, our first attempt towards achieving our vision using a simplified physics-based thermal model. The conduction and convection dynamics of a single layer of the PBF process are modeled using the finite difference method and radial basis functions. Using the model, the next best feature (e.g., stripe or island) that minimizes a thermal uniformity metric is found using control theory. Simulations and experiments involving laser marking of a stainless steel plate are used to demonstrate the effectiveness of SmartScan in comparison to existing heuristic scan sequences for stripe and island scan patterns. In experiments, SmartScan yields up to 43% improvement in average thermal uniformity and 47% reduction in deformations (i.e., warpage) compared to existing heuristic approaches. It is also shown to be robust, and computationally efficient enough for online implementation.

Bromodomain (BRD)-containing proteins are involved in many biological processes, most notably epigenetic regulation of transcription, and BRD protein dysfunction has been linked to many diseases, including tumorigenesis. However, the role of BRD proteins in the pathogenesis of uterine fibroids (UFs) is entirely unknown. The present study aimed to determine the expression pattern of BRD9 protein in UFs and matching myometrium and further assess the impact of BRD9 inhibitors on UF phenotype and epigenetic/epitranscriptomic changes. Our studies demonstrated that the levels of BRD9 were significantly upregulated in UFs compared to matched myometrium, suggesting that the aberrant BRD protein expression may contribute to the pathogenesis of UFs. We then evaluated the potential roles of BRD9 using its specific inhibitor I-BRD9. Targeted inhibition of BRD9 suppressed the UF tumorigenesis with increased apoptosis and cell cycle arrest, decreased cell proliferation, and extracellular matrix deposition in UF cells. The latter is the key hallmark of UFs. Unbiased transcriptomic profiling coupled with downstream bioinformatics analysis further and extensively demonstrated that targeted inhibition of BRD9 impacted the cell cycle- and ECM-related biological pathways, reprogrammed the UF cell epigenome and epitranscriptome, and altered miRNA-mediated gene regulation in UFs. Taken together, our data support the critical role of BRD9 in UF cells and the strong interconnection between BRD9 and other pathways controlling the UF progression. Targeted inhibition of BRD proteins might provide a non-hormonal treatment option for this most common benign tumor in women of reproductive age.