Digital Chemistry as a robust tool for the design of heterogeneous catalysts for direct amination reactionsÔŅľ

Amines are important building blocks in the chemical industry, serving as intermediates in the manufacture of agrochemicals, surfactants, polymers, pharmaceuticals, solvents and dyes. Among the technologies for amine synthesis, the direct amination of alcohols with ammonia stands out as an atom-efficient and environmentally benign route, since water is generated as…

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Complexity in Pd‚ÄďCatalyzed Cross-Couplings: Uncovering Competing Catalytic Cycles Through High Throughput Experimentation and Rich Data Analysis of Reaction OutcomesÔŅľ

In this Webinar I will discuss the complexity associated with some Pd-catalyzed cross-coupling reactions (e.g. in terms of Pd catalyst speciation and reaction outcomes).  I will then describe how we have used the Chemspeed ISYNTH platform, in tandem with other techniques and methods, to examine a complicated Pd-catalyzed cross-coupling involving the reaction‚Ķ

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Automating Chemical HTE workflow and dataflow

This presentation will look at some of the challenges and progress made in automating Chemical HTE and associated flow of data between systems. Biography Simon gained his MChem in Chemistry from the University of York in 2002 and has spent the majority of his career in AstraZeneca’s Chemical Development department.…

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Flexible Automation: A New Approach to Meet Evolving Challenges

Automated executions of chemical synthesis and discovery has risen as a critical enabling technology. New tools combining advanced robotics with experiment planning by machine learning, known as self-driving labs, are now attainable. However, the optimal deployment of these technologies remains under development, requiring a recursive design-make-build cycle dedicated to tuning…

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Providing accurate chemical reactivity prediction with ML models

Numerous disciplines, such as image recognition and machine translation, have been revolutionized by using machine learning (ML) to leverage big data. In organic synthesis, providing accurate chemical reactivity prediction with ML models could assist chemists with reaction prediction, optimization, and mechanistic interrogation. This talk will cover the Doyle group’s efforts…

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Developing tools to discover and optimise complex chemical systems

The synthesis of molecular materials and supramolecular systems is challenging ‚Äď in part because their formation and self-assembly is strongly influenced by reaction environment. We use three approaches to control supramolecular synthesis and/or self-assembly: 1) tuning the building blocks;1 2) varying the interaction strength between building blocks,2and 3) controlling the reaction‚Ķ

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