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10.1038/nature21419

http://scihub22266oqcxt.onion/10.1038/nature21419
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suck abstract from ncbi


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pmid28329756
      Nature 2017 ; 543 (7647 ): 657-664
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  • Functional materials discovery using energy-structure-function maps #MMPMID28329756
  • Pulido A ; Chen L ; Kaczorowski T ; Holden D ; Little MA ; Chong SY ; Slater BJ ; McMahon DP ; Bonillo B ; Stackhouse CJ ; Stephenson A ; Kane CM ; Clowes R ; Hasell T ; Cooper AI ; Day GM
  • Nature 2017[Mar]; 543 (7647 ): 657-664 PMID28329756 show ga
  • Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.
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