Two-dimensional pure isotropic proton solid state NMR

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{
  "metadata": {
    "is_last": true, 
    "version": 1, 
    "title": "Two-dimensional pure isotropic proton solid state NMR", 
    "keywords": [
      "MARVEL/DD1", 
      "machine learning", 
      "NMR", 
      "resolution"
    ], 
    "description": "One key bottleneck of solid-state NMR spectroscopy is that \u00b9H NMR spectra of organic solids are often very broad due to the presence of a strong network of dipolar couplings. We have recently suggested a new approach to tackle this problem. More specifically, we parametrically mapped errors leading to residual dipolar broadening into a second dimension and removed them in a correlation experiment. In this way pure isotropic proton (PIP) spectra were obtained that contain only isotropic shifts and provide the highest \u00b9H NMR resolution available today in rigid solids. Here, using a deep-learning method, we extend the PIP approach to a second dimension, and for samples of L-tyrosine hydrochloride and ampicillin we obtain high resolution \u00b9H-\u00b9H double-quantum/single-quantum dipolar correlation and spin-diffusion spectra with significantly higher resolution than the corresponding spectra at 100 kHz MAS, allowing the identification of previously overlapped isotropic correlation peaks.", 
    "license": "Creative Commons Attribution 4.0 International", 
    "references": [
      {
        "url": "https://doi.org/10.1002/anie.202301963", 
        "type": "Journal reference", 
        "citation": "P. Moutzouri, M. Cordova, B. Sim\u00f5es de Almeida, D. Torodii, L. Emsley, Angew. Chem. Int. Ed. 2023, e202301963", 
        "comment": "Paper in which the method is described", 
        "doi": "10.1002/anie.202301963"
      }
    ], 
    "doi": "10.24435/materialscloud:xj-5f", 
    "conceptrecid": "1686", 
    "publication_date": "Mar 10, 2023, 16:35:51", 
    "edited_by": 339, 
    "_oai": {
      "id": "oai:materialscloud.org:1687"
    }, 
    "contributors": [
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Moutzouri", 
        "givennames": "Pinelopi"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "email": "manuel.cordova@epfl.ch", 
        "familyname": "Cordova", 
        "givennames": "Manuel"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Sim\u00f5es de Almeida", 
        "givennames": "Bruno"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Torodii", 
        "givennames": "Daria"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "email": "lyndon.emsley@epfl.ch", 
        "familyname": "Emsley", 
        "givennames": "Lyndon"
      }
    ], 
    "owner": 339, 
    "license_addendum": null, 
    "mcid": "2023.41", 
    "_files": [
      {
        "size": 50642358, 
        "checksum": "md5:5c30816b8ac9b873259b62dcff1bd991", 
        "description": "Python code used to train and use the model and pre-trained model", 
        "key": "code.zip"
      }, 
      {
        "size": 4269643067, 
        "checksum": "md5:b3daa989fb87d227a24b741be038f675", 
        "description": "Experimental datasets on which the model is applied", 
        "key": "experiments.zip"
      }
    ], 
    "id": "1687", 
    "status": "published"
  }, 
  "revision": 5, 
  "updated": "2023-03-20T08:10:21.272933+00:00", 
  "created": "2023-03-10T14:12:08.516018+00:00", 
  "id": "1687"
}