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Abstract Despite the advantages and emerging applications, broader adoption of powder bed fusion (PBF) additive manufacturing is challenged by insufficient reliability and in-process variations. Finite element modeling and control-oriented modeling have been shown to be effective for predicting and engineering part qualities in PBF. This paper first builds a finite element model (FEM) of the thermal fields to look into the convoluted thermal interactions during the PBF process. Using the FEM data, we identify a novel surrogate system model from the laser power to the melt pool width. Linking a linear model with a memoryless nonlinear submodel, we develop amore »physics-based Hammerstein model that captures the complex spatiotemporal thermomechanical dynamics. We verify the accuracy of the Hammerstein model using the FEM and prove that the linearized model is only a representation of the Hammerstein model around the equilibrium point. Along the way, we conduct the stability and robustness analyses and formalize the Hammerstein model to facilitate the subsequent control designs.« less

Abstract A high-precision additive manufacturing (AM) process, powder bed fusion (PBF) has enabled unmatched agile manufacturing of a wide range of products from engine components to medical implants. While finite element modeling and closed-loop control have been identified key for predicting and engineering part qualities in PBF, existing results in each realm are developed in opposite computational architectures wildly different in time scale. This paper builds a first-instance closed-loop simulation framework by integrating high-fidelity finite element modeling with feedback controls originally developed for general mechatronics systems. By utilizing the output signals (e.g., melt pool width) retrieved from the finite elementmore »model (FEM) to update directly the control signals (e.g., laser power) sent to the model, the proposed closed-loop framework enables testing the limits of advanced controls in PBF and surveying the parameter space fully to generate more predictable part qualities. Along the course of formulating the framework, we verify the FEM by comparing its results with experimental and analytical solutions and then use the FEM to understand the melt-pool evolution induced by the in- and cross-layer thermomechanical interactions. From there, we build a repetitive control (RC) algorithm to attenuate variations of the melt pool width.« less

Abstract Although laser-based additive manufacturing (AM) has enabled unprecedented fabrication of complex parts directly from digital models, broader adoption of the technology remains challenged by insufficient reliability and in-process variations. In pursuit of assuring quality in the selective laser sintering (SLS) AM, this paper builds a modeling and control framework of the key thermodynamic interactions between the laser source and the materials to be processed. First, we develop a three-dimensional finite element simulation to understand the important features of the melt pool evolution for designing sensing and feedback algorithms. We explore how the temperature field is affected by hatch spacingmore »and thermal properties that are temperature-dependent. Based on high-performance computer simulation and experimentation, we then validate the existence and effect of periodic disturbances induced by the repetitive in- and cross-layer thermomechanical interactions. From there, we identify the system model from the laser power to the melt pool width and build a repetitive control algorithm to greatly attenuate variations of the melt pool geometry.« less

Powder bed fusion (PBF) additive manufacturing has enabled unmatched agile manufacturing of a wide range of products from engine components to medical implants. While high-fidelity finite element modeling and feedback control have been identified key for predicting and engineering part qualities in PBF, existing results in each realm are developed in opposite computational architectures wildly different in time scale. Integrating both realms, this paper builds a first-instance closed-loop simulation framework by utilizing the output signals retrieved from the finite element model (FEM) to directly update the control signals sent to the model. The proposed closed-loop simulation enables testing themore »limits of advanced controls in PBF and surveying the parameter space fully to generate more predictable part qualities. Along the course of formulating the framework, we verify the FEM by comparing its results with experimental and analytical solutions and then use the FEM to understand the melt-pool evolution induced by the in-layer thermomechanical interactions. From there, we build a repetitive control algorithm to greatly attenuate variations of the melt pool width.

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Carbohydrate-based low molecular weight gelators (LMWGs) are interesting compounds with a variety of applications. In this research, a library of nineteen carbamate derivatives of N -acetyl- d -glucosamine were synthesized and characterized, and several derivatives were found to be effective LMWGs. They formed gels in pump oils as well as mixtures of water with ethanol or water with DMSO. The structures of the carbamoyl chains played an important role in the gelation properties, short chain aliphatic derivatives and phenyl carbamates formed gels in more solvents than certain aromatic and dimeric carbamates. The phenyl carbamate gelator was also selected for themore »encapsulation of naproxen sodium, and the drug slowly diffused from the gel to the aqueous phase as indicated by UV-vis spectroscopy. In addition, we also found that the p -methoxyl benzyl carbamate derivative showed interesting stimuli-responsive gelation properties in the presence of metal salts and tetrabutylammonium salts. The gels were characterized using optical microscopy, scanning electron microscopy, rheology and other methods. The self-assembling mechanisms of the gelators were studied using 1 H NMR spectroscopy. The preparation, characterization, and molecular assembling properties of these compounds are reported. The results obtained from this study are useful for the design of other LMWGs and the sugar derivatives can be explored for different biological applications. The formation of spontaneous ionic gels can be applicable for a plethora of applications including catalysis and environmental remediation.« less

P-selectin glycoprotein ligand-1 (PSGL-1) is a dimeric, mucin-like, 120-kDa glycoprotein that binds to P-, E-, and L-selectins. PSGL-1 is expressed primarily on the surface of lymphoid and myeloid cells and is up-regulated during inflammation to mediate leukocyte tethering and rolling on the surface of endothelium for migration into inflamed tissues. Although it has been reported that PSGL-1 expression inhibits HIV-1 replication, the mechanism of PSGL-1–mediated anti-HIV activity remains to be elucidated. Here we report that PSGL-1 in virions blocks the infectivity of HIV-1 particles by preventing the binding of particles to target cells. This inhibitory activity is independent of themore »viral glycoprotein present on the virus particle; the binding of particles bearing the HIV-1 envelope glycoprotein or vesicular stomatitis virus G glycoprotein or even lacking a viral glycoprotein is impaired by PSGL-1. Mapping studies show that the extracellular N-terminal domain of PSGL-1 is necessary for its anti–HIV-1 activity, and that the PSGL-1 cytoplasmic tail contributes to inhibition. In addition, we demonstrate that the PSGL-1–related monomeric E-selectin–binding glycoprotein CD43 also effectively blocks HIV-1 infectivity. HIV-1 infection, or expression of either Vpu or Nef, down-regulates PSGL-1 from the cell surface; expression of Vpu appears to be primarily responsible for enabling the virus to partially escape PSGL-1–mediated restriction. Finally, we show that PSGL-1 inhibits the infectivity of other viruses, such as murine leukemia virus and influenza A virus. These findings demonstrate that PSGL-1 is a broad-spectrum antiviral host factor with a unique mechanism of action.« less