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Controlling Light in Scattering Materials for Volumetric Additive Manufacturing

Antoine Vincent Boniface, Paul Delrot, Damien Claude-Marie Loterie, Jorge Andres Madrid Wolff, Christophe Moser

3D printing has revolutionized the manufacturing of volumetric components and structures in many areas. Several fully volumetric light-based techniques have been recently developed thanks to the advent of photocurable resins, promising to reach unprecedented short print time (down to a few tens of seconds) while keeping a good resolution (around 100 mu m). However, these new approaches only work with homogeneous and relatively transparent resins so that the light patterns used for photo-polymerization are not scrambled along their propagation. Herein, a method that takes into account light scattering in the resin prior to computing projection patterns is proposed. Using a tomographic volumetric printer, it is experimentally demonstrated that implementation of this correction is critical when printing objects whose size exceeds the scattering mean free path. To show the broad applicability of the technique, functional objects of high print fidelity are fabricated in hard organic scattering acrylates and soft cell-laden hydrogels (at 4 million cells mL(-1)). This opens up promising perspectives in printing inside turbid materials with particular interesting applications for bioprinting cell-laden constructs.

WILEY2022

Smart pooling: AI-powered COVID-19 informative group testing

Jorge Andres Madrid Wolff

Massive molecular testing for COVID-19 has been pointed out as fundamental to moderate the spread of the pandemic. Pooling methods can enhance testing efficiency, but they are viable only at low incidences of the disease. We propose Smart Pooling, a machine learning method that uses clinical and sociodemographic data from patients to increase the efficiency of informed Dorfman testing for COVID-19 by arranging samples into all-negative pools. To do this, we ran an automated method to train numerous machine learning models on a retrospective dataset from more than 8000 patients tested for SARS-CoV-2 from April to July 2020 in Bogota, Colombia. We estimated the efficiency gains of using the predictor to support Dorfman testing by simulating the outcome of tests. We also computed the attainable efficiency gains of non-adaptive pooling schemes mathematically. Moreover, we measured the false-negative error rates in detecting the ORF1ab and N genes of the virus in RT-qPCR dilutions. Finally, we presented the efficiency gains of using our proposed pooling scheme on proof-of-concept pooled tests. We believe Smart Pooling will be efficient for optimizing massive testing of SARS-CoV-2.

NATURE PORTFOLIO2022

Tomographic Volumetric Additive Manufacturing of Silicon Oxycarbide Ceramics

Antoine Vincent Boniface, Jürgen Brugger, Paul Delrot, Lorenz Hagelüken, Max Kollep, Georgia Konstantinou, Damien Claude-Marie Loterie, Jorge Andres Madrid Wolff, Christophe Moser

Ceramics are highly technical materials with properties of interest for multiple industries. Precisely because of their high chemical, thermal, and mechanical resistance, ceramics are difficult to mold into complex shapes. A possibility to make convoluted ceramic parts is to use preceramic polymers (PCP) in liquid form. The PCP resin is first solidified in a desired geometry and then transformed into ceramic compounds through a pyrolysis step that preserves the shape. Light-based additive manufacturing (AM) is a promising route to achieve solidification of the PCP resin. Different approaches, such as stereolithography, have already been proposed but they all rely on a layer-by-layer printing process which sets limitations on the printing speed and object geometry. Here, we report on the fabrication of complex 3D centimeter-scale ceramic parts by using tomographic volumetric printing, which is fast and offers a high resolution and geometrical design freedom. First, we formulated a photosensitive preceramic resin that was solidified by projecting light patterns from multiple angles. Then, the obtained 3D printed parts were converted into ceramics by pyrolysis. We demonstrate the strength of this approach through the fabrication of dense microcomponents exhibiting overhangs and hollow geometries without the need of supporting structures, and characterize their resistance to thermal stress and harsh chemical treatments.

2022