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    <responseDate>2026-10-13T13:37:59Z</responseDate>
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    <identifier>10.57760/sciencedb.34750</identifier>
    <datestamp>2026-01-08T17:14:01Z</datestamp>
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  <dc:date>2026-01-08</dc:date>
  <dc:title>Hybrid multicomponent UNIFAC density model of unsymmetrical dimethylhydrazine enhanced by machine learning and microscopic mechanism analysis</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.34750</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This study developed a machine learning bias-correction scheme for the UNIFAC model, incorporating temperature and key impurities to significantly improve UDMH density prediction accuracy within &amp;plusmn;0.5 mg/cm&amp;sup3; error while maintaining interpretability. This dataset contains the machine-learing data and the quantum-chemical calculation data, if you need to obtain our data, please provide the user's name, institutional information, and a statement of purpose, and send it to the email address l1ming@foxmail.com or xuzl@0912@163.com.</dc:description>
  <dc:subject>machine learning; mixed liquid density; quantum-chemical calculation; 1 1-dimethylhydrazine</dc:subject>
  <dc:creator>Zelong Xu</dc:creator>
  <dc:creator>Ming Li</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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