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Leguizamon, Samuel

Publications and source records attributed to Leguizamon, Samuel.

Method of tuning physical properties of thermosets

Polymerization-induced phase separation enables fine control over thermoset network morphologies, yielding heterogeneous structures with domain sizes tunable over 1-100 nm. However, the controlled chain-growth polymerization techniques exclusively employed to regulate morphology at these length scales are unsuitable for most thermoset materials typically formed through step-growth mechanisms. By employing binary mixtures in place of the classic constituents of phase-separating thermosets—resin, curing agent, and secondary polymer—facile tunability over morphology can be achieved through a single compositional parameter. Indeed, this method yields morphologies spanning nano-scale to macro-scale, controlled by the relative reactivities and thermodynamic compatibility of the network components. Due to the connection between chain dynamics and microstructure in these materials, the tunable morphology enables exquisite control over glass transition and other physical and mechanical properties.

Jones, Brad Howard↗

Use of latent metathesis polymerization systems for additive manufacturing

The invention is directed to latent metathesis-active resin compositions and additive manufacturing approaches. The latent metathesis-active compositions comprise at least one latent metathesis catalyst, at least one curable metathesis-active monomer, and optional fillers, photosensitizers, and/or a secondary monomer resin system for dual-cure. A method comprises extruding a latent metathesis-active resin from a dispensing apparatus and spatially triggering a ring-opening metathesis polymerization by directed irradiation with light or directed application of a thermal stimuli for direct-ink write printing of objects. Another method uses a latent metathesis-active resin for vat photopolymerization and stereolithographic printing of objects.

Appelhans, Leah↗

Use of latent metathesis polymerization systems for photopolymerization-based additive manufacturing

Photolatent olefin metathesis catalysts can be used in combination with metathesis-active monomers or resins for photopolymerization-based additive manufacturing via ring-opening metathesis polymerization (ROMP). A variety of alternative catalysts and photosensitizers are commercially available that allows for tuning of thermomechanical properties, potlifes, activation rates, and irradiation wavelengths. As an example, two optimized catalyst/photosensitizer systems were demonstrated in the rapid stereolithographic printing of complex, multidimensional poly-dicyclopentadiene structures with microscale features under ambient conditions.

Leguizamon, Samuel↗

Invertible neural networks for real-time control of extrusion additive manufacturing

Material extrusion additive manufacturing (AM) has enabled an elegant fabrication pathway for a vast material library. Nonetheless, each material requires optimization of printing parameters generally determined through significant trial-and-error testing. To eliminate arduous, iteration-based optimization approaches, many researchers have used machine learning (ML) algorithms which provide opportunities for automated process optimization. Here, in this work, we demonstrate the use of an ML-driven approach for real-time material extrusion print-parameter optimization through in-situ monitoring of printed line geometry. To do this, we use deep invertible neural networks (INNs) which can solve both forward and inverse, or optimization, problems using a single network. By combining in-situ computer vision and deep INNs, the printing parameters can be autonomously optimized to print a target line width in 1.2 s. Furthermore, defects that occur during printing can be rapidly identified and corrected autonomously. The methods developed and presented in this work eliminate user-intensive, time-consuming, and iterative parameter discovery approaches that currently limit accelerated implementation of extrusion-based AM processes. Furthermore, the presented approach can be generalized to provide real-time monitoring and optimization pathways for increasingly complex AM environments.

36 MATERIALS SCIENCE↗