http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113689918-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_4c0ed78c4d5c4951a22374d61ea1f178 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C60-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-10 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-70 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C60-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-10 |
| filingDate | 2021-06-24-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_acd2fd4e2e02932493e24b03f55e4dcb http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_6af3a226296f7bc8482ec30d5baf5bb4 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8b1e8a13b2a58b346e66766f9fbc27a1 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_e8877050ad6dd40b8ce8bf89b55bc23d http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_805d4c43f2a5af4bcabaa9395f7e71f5 |
| publicationDate | 2021-11-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-113689918-A |
| titleOfInvention | Method for predicting performance of metal organic framework material in catalyzing carbon dioxide |
| abstract | The invention discloses a method for predicting the performance of a metal organic framework material catalyzing carbon dioxide, which comprises the steps of firstly determining characteristic parameters for predicting the catalyzing and fixing carbon dioxide of the metal organic framework material, collecting data, and establishing a machine learning prediction data set; secondly, data preprocessing is carried out on the data; establishing a machine learning model; inputting the characteristics of the metal organic framework and the characteristic parameters of the reactant in the sample as models, outputting the performance of the metal organic framework to be predicted as a model, and training a machine learning model; inputting the characteristic parameters of the new metal organic framework to be predicted into a machine learning model, and outputting the catalytic performance of the new material to be predicted; and analyzing the result to find the relationship between the structure and the performance of the metal organic framework material. The invention can screen out the catalyst material with excellent performance in a large scale so as to solve the problems of obstruction in the development of the existing material, high time and cost of material design and the like. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114957695-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114907571-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114907571-B |
| priorityDate | 2021-06-24-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 155.