Advances in Urethane

Science & Technology, Volume XIV

Kurt C. Frisch, Daniel Klempner

• Publisher: CRC Press
• Year: 2020
• ISBN:
  9781000725490
• Edition: 1
• Topic: Physical Sciences
• Subtopic: Physics
• Index: Physics

Flexible polyurenthane foams of all types are a unique group of plastics materials, characterized by the fact that a multitude of different sets of properties can be obtained by varying the levels of a relatively small number of base components in the formulations. Different foam grades, primarily characterized by density and hardness, can be obtained by changing the ratio between base polyol, polymer polyol, water, blowing agent, isocyanate and other components. It is not uncommon for foam producers in industrialized countries to manufacture more than one hundred different foam grades based on these basic chemicals, plus the ancillary chemicals needed for optimized processing. This has always made flexible polyurethane foams a highly suitable candidate for correlating these variations in the formulations with the resulting properties in a mathematical way, aimed at predicting the properties as accurately as possible, fine-tuning existing grades or designing new foam grades. This book discusses the methodology for obtaining meaningful equations for correlating properties with formulation variables and other influencing factors

Mathematical Property Prediction Models for Flexible Polyurethane Foams

REINHART SCHIFFAUER

ARCO Chemical Company

3200-3300 Kanawha Turnpike

South Charleston, WV 25303, U.S.A.

INTRODUCTION

FLEXIBLE POLYURETHANE FOAMS OF ALL TYPES ARE A UNIQUE GROUP OF plastics materials, characterized by the fact that a multitude of different sets of properties can be obtained by varying the levels of a relatively small number of base components in the formulations. Different foam grades, primarily characterized by density and hardness, can be obtained by changing the ratio between base polyol, polymer polyol, water, blowing agent, isocyanate and other components. It is not uncommon for foam producers in industrialized countries to manufacture more than one hundred different foam grades based on these basic chemicals, plus the ancillary chemicals needed for optimized processing. This has always made flexible polyurethane foams a highly suitable candidate for correlating these variations in the formulations with the resulting properties in a mathematical way, aimed at predicting the properties as accurately as possible, fine-tuning existing grades or designing new foam grades. Severed publications addressing such correlations have been reported in the literature [1, 2, 3].

In the following sections we will discuss the methodology for obtaining meaningful equations for correlating properties with formulation variables and other influencing factors. The currently available equations for the most important properties will be discussed in detail, followed by individual emphasis on the various influencing variables and their importance on specific properties. Finally some thoughts will be presented on a purposeful use of these models, on some further influencing variables which have not been addressed to date, and suggestions for further investigations seeking continuous improvements as well as tailoring to individual needs.

METHODS FOR OBTAINING MATHEMATICAL PROPERTY PREDICTION MODELS

Data Collection and Preparation

The compilation of meaningful data banks, prior to mathematical analysis, is of extreme importance. For obtaining good correlations between formulation variables and properties which may include interaction terms, every variable has to be present at three levels or higher. In an ideal case, starting such an analysis without any prior history, one would design a set of experiments with the desired levels of the chosen variables, prepare the foams, measure the properties and analyze the results. In such a case, however, one might experience an undesired side effect: not all foams are at or around the middle of the processing range to be suitable for analysis: some may be too tight, others may be too open celled, even contain splits. This would lead to a logical next step: to evaluate every variation over a range of stannous octoate levels, to make sure that at least one of the individual foams for a given set of other variables is of good enough quality for testing. It becomes apparent that the generation of good, meaningful data could become quite a big task. For example, the evaluation of four major variables (levels of water, blowing agent, polymer polyol and isocyanate index), plus stannous octoate as outlined earlier, all at three levels, would need the preparation of a large number of foams, namely 3⁵ or 243 individual experiments. Even by applying statistical techniques to reduce the number of experiments, e.g., using fractional factorial designs, the numbers are still quite large. Furthermore, in some cases three levels of a particular variable may not be enough as will be discussed later. Finally, the four formulation variables mentioned earlier do not represent the full spectrum of variables which influence properties. For these reasons some of the early modeling work was done with existing data banks, either from laboratory sources or from actual production. This may sound like the ideal appr...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Mathematical Property Prediction Models for Flexible Polyurethane Foams
• The Effective Diffusivity of Cyclopentane and n-Pentane in PU and PUIR Foams by Thin-Slice Gravimetric Analysis
• Scorch Inhibitors for Polyurethane Slabstock Foams
• A Novel Architecture for Electro-optic Polyurethanes: Alternating Charge Transporting and Nonlinear Optical Chromophores
• Advances in Moisture-Curable Siloxane-Urethane Polymers
• New Synthetic Pathways to Polyether Polyols for Rigid Polyurethane Foams
• PU Based Structural RIM Composites for a Complete Car Floor Pan
• Effect of Crosslink Variation on Physical Properties of Polyurethanes
• Structure-Property Relationships of Polyurethane Elastomers Based on New Saturated Hydrocarbon Diols
• Polyurethane Elastomers Based on Novel Hydrocarbon-Based Diols
• Polyurethane Structural Adhesives for Automotive Applications