Generate a solid form landscape of any single- or multi-component system. Quickly, easily, empirically.
Input any 2D or 3D system then quickly generate and visualize possible solid forms, including alternative polymorphs and stoichiometries.
Results are based on the empirical data in the Cambridge Structural Database (CSD) or your proprietary database, so you can quickly see how different forms were generated. And it's simple to use - just a few clicks to generate your solid form landscape, then visualize the results in the well-known Mercury interface, or access in the CSD Python API.
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Understand the packing preferences of your system from an early stage.
Identify risks such as solvate formation or polymorphism, and opportunities such as co-crystallization, from the earliest possible stage. Explore how changes to the components or system impact the solid form, without the need to do so experimentally.
Predict properties earlier
Understand stability and other solid form properties sooner than ever - before a system is even synthesized.
No expertise required
Generate the landscape in just a few clicks, then explore each structure in the well-established Mercury interface. Results are generated based on empirical data from the CSD, and no knowledge of predictive techniques is needed.
Explore any system
Pharmaceuticals, semiconductors, functional materials - generate a solid form landscape for any molecule type.
From empirical data
The generated structures are based on the experimentally confirmed structures in the Cambridge Structural Database (CSD). You can also generate based on your own in-house database. Using fingerprints and matching shapes the system evaluates molecular similarity to these known structures.
Incorporate the CSD Landscape Generator into workflows using the CSD Python API
Generate and visualize your solid form landscape in the established and well-known interface, Mercury. Take advantage of the extensive functionality to customize your view and analyse results further.
Do I need to know about CSP or computational chemistry?
No - the CSD Landscape Generator works in a few clicks within Mercury. It is also accessible in the CSD Python API for incorporating into workflows.
Can I use the generated structures in my CSD-Theory Web or CSD-Theory Python API?
Yes - the output includes standardized CSP meta-data, for direct use in other CSD-Theory applications.
How are the predictions generated?
Using fingerprints the CSD Landscape Generator evaluates molecular similarity to the CSD or your in-house database and places your molecule into their existing crystal structure.
What does the score mean?
The score correlates linearly with sublimation enthalpy from known structures in the CSD or your in-house database.
How does this compare to CSP or experimental screening?
The CSD Landscape Generator generates putative crystal structures based on empirical data, to illustrate possible polymorphs and stoichiometries in multi-component systems. This is intended to guide and complement experimental work not replace it.
Compared to CSP, this is preliminary analysis of the landscape - higher accuracy on energies can be obtained with full CSP.
How do I enter a molecule or system for analysis?
You can enter a 2D sketch, or a 1D representation like SMILES or SMARTS. This is converted to a 3D molecule using CSD-Discovery or CSD-Materials functionality, and then the 3D crystal structure is generated by the CSD landscape generator.