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model of reaction barriers. This will enable the development of more accurate and advanced high-throughput reaction network discovery and by-product prediction. Background Typical drug molecules can
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net zero goals and the future of our planet. During their lifetime, those energy storage systems can experience complex electrochemical-thermomechanical phenomena that can result in their volumetric
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materials, and lattice fluctuations which drive phase changes in these systems that dictate their durability. One bottleneck however is the complexity of the design and interpretation of XFEL experiments
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of the project is to understand the drying process in commercial driers from a continuum perspective. Starting from established models of granular flows and complex fluid flows that incorporate plasticity
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electron microscopy image simulations Development of a machine learning model capable of inferring 3D atomic structure from two-dimensional TEM projection images Application of the new approach
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. Setting-up enzymatic reactions between sub-compartments to model and understand eukaryotic cellular metabolism. Developing new microfluidic tools to construct multi-compartment synthetic cells for drug
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objective of this research project is to unravel the complex dynamics of iron-dominated, nickel-dominated, and mixed Fe-Ni corrosion products on zircaloy surfaces. By exploring boiling, flow conditions, and
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. There is good theoretical and observational evidence that the accretion disc will likely be misaligned with the spin axis of the black hole although this is presently hard to pin down due to a lack of models
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memorisation capabilities of deep learning models. Such vulnerabilities expose FL systems to various privacy attacks, making the study of privacy in distributed settings increasingly complex and vital
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where