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Here we highlight recent work that used metal-organic framework structures in the Cambridge Structural Database (CSD) to train a machine learning model to predict guest accessibility with over 80% certainty. Part of our series highlighting the use of the CSD by scientists around the world.
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Here we highlight a paper by authors at Tianjin University who used the CSD MOF Subset to optimize materials for the recovery of volatile organic compound (VOC) emissions. This is part of our series highlighting examples of the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.
On 14 October, we hosted Dr Peyman Z. Moghadam from The University of Sheffield at our MOFs networking event. He presented his talk, High-throughput Computational Screening for MOF Materials Discovery. He spoke on how the analysis of MOFs data can support and guide the development of novel MOFs to suit specific applications like energy storage, catalysis, and CO2 sequestering. Here, you'll find materials from the event, including a recording of his presentation.
Here we highlight a paper by researchers at the University of Liverpool and Università di Siena who used the Cambridge Structural Database (CSD) to identify a set of promising compounds for use in semiconductors and a new tool for discovering materials with electronic properties. This is part of our series highlighting examples of the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.
Here we highlight a paper by researchers at the Material Engineering Division of Toyota Motor Europe and the University of Crete who used CCDC’s metal-organic framework (MOF) collection to investigate how ligand functionalization affects the hydrogen storage profile of MOFs. This is part of our series highlighting examples of the Cambridge Crystallographic Data Centre (CCDC) tools in action by scientists around the world.
To welcome the release of our CSD MOF collection, 10,636 structures available for free for academic research, we are answering some common questions on MOFs with the help of some of our team and collaborators.
The past year has pushed the importance and challenges of scientific discovery into the spotlight. What lessons can we learn, and what changes can scientific leaders make going forward? In a virtual "fireside chat" the leaders of the CCDC and the RCSB PDB explored this topic, and we share some key learnings from the discussion here.
The recent cover of Chemical Science (issue 32) showcased a paper by Moghadam et al. highlighting our new approach to classifying MOF structures for better searching and high-throughput screening.
