Despite huge potential, automation of synthetic chemistry has only made incremental progress over the past few decades. We present an automatically executable chemical reaction database of 100 molecules representative of the range of reactions found in contemporary organic synthesis. These reactions include transition metal–catalyzed coupling reactions, heterocycle formations, functional group interconversions, and multicomponent reactions. The chemical reaction codes or χDLs for the reactions have been stored in a database for version control, validation, collaboration, and data mining. Of these syntheses, more than 50 entries from the database have been downloaded and robotically run in seven modular ChemPU’s with yields and purities comparable to those achieved by an expert chemist. We also demonstrate the automatic purification of a range of compounds using a chromatography module seamlessly coupled to the platform and programmed with the same language.

Remote photogrammetric inspection is a Non-Destructive Testing method used to quantify surface integrity and detect external discontinuities. The mobility and size of an unmanned aerial vehicle (UAV) offer the flexibility to quickly deploy remote photogrammetric inspections for large-scale assets. In this paper, the results of a photogrammetric inspection are presented as a 3D profile, reconstructed from UAV captured images. Experiments were conducted indoors using a wind turbine blade section obtained from a recently decommissioned asset. The naturally occurring surface features representative of environmental wear were augmented with a small number of artificial features to aid in the visualisation of inspection quality. An autonomous UAV system for photogrammetric inspections is demonstrated and the influence of image parameters such as environmental light levels, motion blur and focal blur quantified in terms of their impact on the inspection accuracy. Over the range of parameter values studied, the poorest scenario was observed to cause a degradation in reconstruction error by a factor of 13 versus the optimal. Reconstruction quality when employing a laser range scanner to maintain standoff distance relative to the object during flight was also investigated. In this schema, the controller automatically generated a real-time adaptive flight path to follow the outer profile of the wind turbine blade and, consequently, demonstrated improved image quality during close-range inspection of an object with complex geometry. Inspection accuracy was quantified using the error of the photogrammetric reconstruction as compared to a model acquired using independent metrology equipment. While utilising the laser-based adaptive path, error in the reconstructed geometry was reduced by a factor of 2.7 versus a precomputed circular path. In the best case, the mean deviation was below 0.25 mm. Instances of wind turbine blade damage such as edge crushing, surface imperfections, early stage leading edge erosion were clearly observed in the textured 3D reconstruction profiles, indicating the utility of the successful inspection process. The results of this paper evaluate the impact of optical environmental effects on photogrammetric inspection accuracy, offering practical insight towards mitigation of negative effects.

Environmental and commercial drivers are leading to a circular economy, where systems and components are routinely recycled or remanufactured. Unlike traditional manufacturing, where components typically have a high degree of tolerance, components in the remanufacturing process may have seen decades of wear, resulting in a wider variation of geometries. This makes it difficult to translate existing automation techniques to perform Non-Destructive Testing (NDT) for such components autonomously. The challenge of performing automated inspections, with off-line tool-paths developed from Computer Aided Design (CAD) models, typically arises from the fact that those paths do not have the required level of accuracy. Beside the fact that CAD models are less available for old parts, these parts often differ from their respective virtual models. This paper considers flexible automation by combining part geometry reconstruction with ultrasonic tool-path generation, to perform Ultrasonic NDT. This paper presents an approach to perform custom vision-guided ultrasonic inspection of components, which is achieved through integrating an automated vision system and a purposely developed graphic user interface with a robotic work-cell. The vision system, based on structure from motion, allows creating 3D models of the parts. Also, this work compares four different tool-paths for optimum image capture. The resulting optimum 3D models are used in a virtual twin environment of the robotic inspection cell, to enable the user to select any points of interest for ultrasonic inspection. This removes the need of offline robot path-planning and part orientation for assessing specific locations on a part, which is typically a very time-consuming phase.

Imaging technologies have made a significant improvement in the past few decades and their application made a great impact on accelerating the process of drug discovery and development. The ability to non-invasively image an animal model or co-cultured live cells and validate potential drug target, biomarkers of drug efficacy and assess a pharmacological drug interaction significantly contributes to the process of translating molecules into medicines. This paper summarizes current trends in bio-imaging technologies and their application on the process of drug discovery. In particular, High Content Screening (HCS) and Virtual Screening (VS) are reviewed, and their respective examples are discussed to gain insight into state-of-the-art bio-imaging methodologies used for extracting knowledge and its application to drug discovery. This paper argues the need to reduce the gap between experimental (e.g. HCS based assays) and theoretical (e.g. VS based assays) assays. Although HCS and VS are leading drug discovery choices for the pharmaceutical industry and such investigations have been carried out in their respective campaign, the potential effects of these approaches together to facilitate the process of drug discovery has rarely been reported. Further, the prevalent research trends on developing hybrid approaches such as VS complementing HCS implies substantial enhancement to the goal of reliable drug candidate identification.

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