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Mining predicted crystal structure landscapes with high throughput crystallisation: Old molecules, new insights

Mining predicted crystal structure landscapes with high throughput crystallisation: Old molecules, new insights
Mining predicted crystal structure landscapes with high throughput crystallisation: Old molecules, new insights
Organic molecules tend to close pack to form dense structures when they are crystallised from organic solvents. Porous molecular crystals defy this rule: they contain open space, which is typically stabilised by inclusion of solvent in the interconnected pores during crystallisation. The design and discovery of such structures is often challenging and time consuming, in part because it is difficult to predict solvent effects on crystal form stability. Here, we combine crystal structure prediction (CSP) with a robotic crystallisation screen to accelerate the discovery of stable hydrogen-bonded frameworks. We exemplify this strategy by finding new phases of two well-studied molecules in a computationally targeted way. Specifically, we find a new ‘hidden’ porous polymorph of trimesic acid, δ-TMA, that has a guest-free hexagonal pore structure, as well as three new solvent-stabilized diamondoid frameworks of adamantane-1,3,5,7-tetracarboxylic acid (ADTA). Beyond porous solids, this hybrid computational-experimental approach could be applied to a wide range of materials problems, such as organic electronics and drug formulation.
1478-6524
9988-9997
Cui, Peng
5d181dda-0fe7-4046-b6ab-459302250484
Mcmahon, David P.
026a4184-d048-4a12-964e-5c6d9da81c68
Spackman, Peter
0b8d8f08-0b3b-45ce-8607-dafa10f28afe
Alston, Ben M.
dd98ba5d-f1bc-4467-8e6a-e9a44a1d9dcd
Little, Marc A.
2187f2c0-dfd5-4966-b65e-aa241150ee87
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Cooper, Andrew I.
f6374027-4856-4d3a-998d-2bfec79a7a42
Cui, Peng
5d181dda-0fe7-4046-b6ab-459302250484
Mcmahon, David P.
026a4184-d048-4a12-964e-5c6d9da81c68
Spackman, Peter
0b8d8f08-0b3b-45ce-8607-dafa10f28afe
Alston, Ben M.
dd98ba5d-f1bc-4467-8e6a-e9a44a1d9dcd
Little, Marc A.
2187f2c0-dfd5-4966-b65e-aa241150ee87
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Cooper, Andrew I.
f6374027-4856-4d3a-998d-2bfec79a7a42

Cui, Peng, Mcmahon, David P., Spackman, Peter, Alston, Ben M., Little, Marc A., Day, Graeme M. and Cooper, Andrew I. (2019) Mining predicted crystal structure landscapes with high throughput crystallisation: Old molecules, new insights. Chemical Science, 10 (43), 9988-9997. (doi:10.1039/C9SC02832C).

Record type: Article

Abstract

Organic molecules tend to close pack to form dense structures when they are crystallised from organic solvents. Porous molecular crystals defy this rule: they contain open space, which is typically stabilised by inclusion of solvent in the interconnected pores during crystallisation. The design and discovery of such structures is often challenging and time consuming, in part because it is difficult to predict solvent effects on crystal form stability. Here, we combine crystal structure prediction (CSP) with a robotic crystallisation screen to accelerate the discovery of stable hydrogen-bonded frameworks. We exemplify this strategy by finding new phases of two well-studied molecules in a computationally targeted way. Specifically, we find a new ‘hidden’ porous polymorph of trimesic acid, δ-TMA, that has a guest-free hexagonal pore structure, as well as three new solvent-stabilized diamondoid frameworks of adamantane-1,3,5,7-tetracarboxylic acid (ADTA). Beyond porous solids, this hybrid computational-experimental approach could be applied to a wide range of materials problems, such as organic electronics and drug formulation.

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Mining Predicted Crystal Structure Landscapes with High Throughput Crystallisation Old Molecules, New Insights_Revised - Accepted Manuscript
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Accepted/In Press date: 19 August 2019
e-pub ahead of print date: 17 September 2019

Identifiers

Local EPrints ID: 433549
URI: http://eprints.soton.ac.uk/id/eprint/433549
ISSN: 1478-6524
PURE UUID: a21c5035-5b23-4236-98c5-6771a32f9740
ORCID for Graeme M. Day: ORCID iD orcid.org/0000-0001-8396-2771

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Date deposited: 27 Aug 2019 16:30
Last modified: 04 Feb 2020 01:32

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