ART: A machine learning Automated Recommendation Tool for synthetic biology

Biology has changed radically in the last two decades, transitioning from a descriptive science into a design science. Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, and fatty acids. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing

Influence of spray technology on ionic conductivity of yttria stabilized zirconia

International audienceIn this paper the influence of plasma spray parameters of both Vacuum Plasma Spraying (VPS) and Air Plasma Spraying (APS) processes onto Yttria Stabilized Zirconia (YSZ) coating microstructures were studied in order to establish a correlation with the ionic conductivity. Investigations of the relationships between spraying conditions and the spreading of particles were carried out thanks to a study of in-flight particle properties. The in-flight properties were determined using the DPV 2000 and the lamellae were studied by optical microscopy and 3D analyzes. Coatings were then elaborated. Coating microstructures were evaluated by Scanning Electron Microscopy (SEM) and their electrical properties by Impedance Spectroscopy (IS) in order to establish a relationship between interlamellar contacts and ionic conductivity. It has been shown that with these results, it has been possible to increase the ionic conductivity of YSZ coatings by improving their interlamellar contacts

Reliability of plasma-sprayed coatings: monitoring the plasma spray process and improving the quality of coatings

International audienceAs for every coating technology, the reliability and reproducibility of coatings are essential for the development of the plasma spraying technology in industrial manufacturing. They mainly depend on the process reliability, equipment and spray booth maintenance, operator training and certification, implementation and use of consistent production practices and standardization of coating testing. This paper deals with the first issue, that is the monitoring and control of the plasma spray process; it does not tackle the coating characterization and testing methods. It begins with a short history of coating quality improvement under plasma spray conditions over the last few decades, details the plasma spray torches used in the industry, the development of the measurements of in-flight and impacting particle parameters and then of sensors. It concludes with the process maps that describe the interrelations between the operating parameters of the spray process, in-flight particle characteristics and coating properties and with the potential of in situ monitoring of the process by artificial neural networks and fuzzy logic method