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10.1038/nature21419

http://scihub22266oqcxt.onion/10.1038/nature21419
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C5458805!5458805!28329756
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suck abstract from ncbi


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pmid28329756      Nature 2017 ; 543 (7647): 657-64
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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): 657-64 PMID28329756show ga
  • Molecular crystals cannot be designed like macroscopic objects because they do not assemble according to simple, intuitive rules. Their structure results from the balance of many weak interactions, unlike 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 describing the possible structures and properties available to a candidate molecule. Using these maps, we identify a highly porous solid with the lowest density reported for a molecular crystal. Both crystal structure and physical properties, such as the methane storage capacity and guest selectivity, are predicted using the molecular diagram 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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