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Laser beam powder bed fusion (LB-PBF) is a widely-used metal additive manufacturing process due to its high potential for fabrication flexibility and quality. Its process and performance optimization are key to improving product quality and promote further adoption of LB-PBF. In this article, the state-of-the-art machine learning (ML) applications for process and performance optimization in LB-PBF are reviewed. In these applications, ML is used to model the process-structure–property relationships in a data-driven way and optimize process parameters for high-quality fabrication. We review these applications in terms of their modeled relationships by ML (e.g., process—structure, process—property, or structure—property) and categorize the ML algorithms into interpretable ML, conventional ML, and deep ML according to interpretability and accuracy. This way may be particularly useful for practitioners as a comprehensive reference for selecting the ML algorithms according to the particular needs. It is observed that of the three types of ML above, conventional ML has been applied in process and performance optimization the most due to its balanced performance in terms of model accuracy and interpretability. To explore the power of ML in discovering new knowledge and insights, interpretation with additional steps is often needed for complex models arising from conventional ML and deepmore »ML, such as model-agnostic methods or sensitivity analysis. In the future, enhancing the interpretability of ML, standardizing a systemic procedure for ML, and developing a collaborative platform to share data and findings will be critical to promote the integration of ML in LB-PBF applications on a large scale.« less

Volumetric defect types commonly observed in the additively manufactured parts differ in their morphologies ascribed to their formation mechanisms. Using high-resolution X-ray computed tomography, this study analyzes the morphological features of volumetric defects, and their statistical distribution, in laser powder bed fused Ti-6Al-4V. The geometries of three common types of volumetric defects; i.e., lack of fusions, gas-entrapped pores, and keyholes, are quantified by nine parameters including maximum dimension, roundness, sparseness, aspect ratio, and more. It is shown that the three defect types share overlaps of different degrees in the ranges of their morphological parameters; thus, employing only one or two parameters cannot uniquely determine a defect’s type. To overcome this challenge, a defect classification methodology incorporating multiple morphological parameters has been proposed. In this work, by employing the most discriminating parameters, this methodology has been shown effective when implemented into decision tree (>98% accuracy) and artificial neural network (>99% accuracy).

We study the connection between the correlation decay property (more precisely, strong spatial mixing) and the zero-freeness of the partition function of 2-spin systems on graphs of bounded degree. We show that for 2-spin systems on an entire family of graphs of a given bounded degree, thecontractionproperty that ensures correlation decay exists for certain real parameters implies the zero-freeness of the partition function and the existence of correlation decay for some corresponding complex neighborhoods. Based on this connection, we are able to extend any real parameter of which the 2-spin system on graphs of bounded degree exhibits correlation decay to its complex neighborhood where the partition function is zero-free and correlation decay still exists. We give new zero-free regions in which the edge interaction parameters and the uniform external field are all complex-valued, and we show the existence of correlation decay for such complex regions. As a consequence, we obtain approximation algorithms for computing the partition function of 2-spin systems on graphs of bounded degree for these complex parameter settings.

Expansion of an initial population of T cells is essential for cellular immunotherapy. In Chronic Lymphocytic Leukemia (CLL), expansion is often complicated by lack of T cell proliferation, as these cells frequently show signs of exhaustion. This report seeks to identify specific biomarkers or measures of cell function that capture the proliferative potential of a starting population of cells. Mixed CD4+/CD8+ T cells from healthy donors and individuals previously treated for CLL were characterized on the basis of proliferative potential and in vitro cellular functions. Single-factor analysis found little correlation between the number of populations doublings reached during expansion and either Rai stage (a clinical measure of CLL spread) or PD-1 expression. However, inclusion of in vitro IL-2 secretion and the propensity of cells to align onto micropatterned features of activating proteins as factors identified three distinct groups of donors. Notably, these group assignments provided an elegant separation of donors with regards to proliferative potential. Furthermore, these groups exhibited different motility characteristics, suggesting a mechanism that underlies changes in proliferative potential. This study describes a new set of functional readouts that augment surface marker panels to better predict expansion outcomes and clinical prognosis.

Human papillomavirus (HPV) is a globally prevalent sexually-transmitted pathogen, responsible for most cases of cervical cancer. HPV vaccination rates remain suboptimal, partly due to the need for multiple doses, leading to a lack of compliance and incomplete protection. To address the drawbacks of current HPV vaccines, we used a scalable manufacturing process to prepare implantable polymer–protein blends for single-administration with sustained delivery. Peptide epitopes from HPV16 capsid protein L2 were conjugated to the virus-like particles derived from bacteriophage Qβ, to enhance their immunogenicity. The HPV-Qβ particles were then encapsulated into poly(lactic-co-glycolic acid) (PLGA) implants, using a benchtop melt-processing system. The implants facilitated the slow and sustained release of HPV-Qβ particles without the loss of nanoparticle integrity, during high temperature melt processing. Mice vaccinated with the implants generated IgG titers comparable to the traditional soluble injections and achieved protection in a pseudovirus neutralization assay. HPV-Qβ implants offer a new vaccination platform; because the melt-processing is so versatile, the technology offers the opportunity for massive upscale into any geometric form factor. Notably, microneedle patches would allow for self-administration in the absence of a healthcare professional, within the developing world. The Qβ technology is highly adaptable, allowing the production of vaccine candidates andmore »their delivery devices for multiple strains or types of viruses.« less