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Cover Image, Volume 138, Issue 7
Author(s) -
Seidl Regina,
Weiss Stephanie,
ZikulnigRusch Edith M.,
Kandelbauer Andreas
Publication year - 2021
Publication title -
journal of applied polymer science
Language(s) - English
Resource type - Reports
SCImago Journal Rank - 0.575
H-Index - 166
eISSN - 1097-4628
pISSN - 0021-8995
DOI - 10.1002/app.50283
Subject(s) - yield (engineering) , cover (algebra) , materials science , volume (thermodynamics) , polymer , range (aeronautics) , process (computing) , composite material , molar ratio , image (mathematics) , process engineering , response surface methodology , computer science , chemical engineering , biological system , mechanical engineering , chemistry , artificial intelligence , thermodynamics , engineering , organic chemistry , machine learning , physics , catalysis , biology , operating system
The image created by Regina Seidl and co‐workers show how Statistical Design of Experiments and Response Surface Methodology can successfully be applied to very effectively and systematically tailor and optimize polymeric materials to very specialized target property profiles. MF resins of a wide range of M:F molar ratios were produced at different initial pH values and analyzed for properties relevant for impregnation resins. A causal linear regression model based on the identified factor effects was developed to derive suitable process windows that yield good impregnation resins suitable for high‐performance decorative laminates. The presented methodology is highly effective and transferable to other polymer systems. DOI: 10.1002/app.50181