Yonezawa Rheology Workshop 2004: “Reconstruction of Polymer Rheology”
held during
The IRIS Platform for Visualizing Experimental Data and Theoretical Predictions in Rheology
By H. Henning Winter, Dpt. Chemical Engineering and Dpt of Polymer Science and Engineering, University of Massachusetts, Amherst, MA 01003, USA; winter@ecs.umass.edu
and
Marian Mours, Weisenheim am
Rheology is still difficult to access. This is its biggest unsolved problem. The full use of rheology is limited to a small group of highly trained scientists. If there is widespread use of rheology today, it has been achieved mostly by simplifications of rheological concepts, sometimes over-simplification. In spite of this, rheology has still proven to be useful to a certain extent, but simplified methods fall way short of revealing the full potential of the rheological information of a specific material of interest. Rheology will gain by the development of user-friendly methods that express rheology in its full complexity. This includes methods of freely communicating rheological data and theory as discussed here.
User-friendly methods are essential not only for research and application, but also for the teaching of rheology. New teaching methods will potentially generate broad access to rheological concepts. This will lead to an appreciation of the significance that rheology has in technical applications. In-depth data analysis and evaluation of theory should become easy enough to be performed by non-rheologists after reasonable training (one week of training seems acceptable) and without relying on over-simplifications.
To make rheology more accessible, we have started to develop a computer platform that allows a detailed analysis of experimental data and allows predictions from the newest theories in rheology (https://rheology.tripod.com/). The IRIS computer platform gives experts in specialized topics of rheology the opportunity to write modules that will seamlessly merge into a general code so that it can be used by a wide range of engineers and scientists.
Current Capabilities
While IRIS is an established tool for experimental rheology (used in about 50 laboratories worldwide), the access to rheological theory has been opened only recently. Theory groups were invited to work with us on the implementation of their theory so that they become available to a wide community in rheology and beyond.
Theory: Theoretical predictions of linear viscoelastic material functions can be made directly in IRIS. Available are classical theories of polymer melts and solutions (Maxwell, Rouse, Doi-Edwards) and empirical models. Theory groups began to write modules for the IRIS platform. A common goal of these theories is to find a relation between molecular architecture (topology) and molecular dynamics as expressed in rheology. The theoretical part of IRIS also extends into non-linear rheology. The most common transient flows of polymer melts and solutions can be modeled with classical theories (Lodge rubberlike liquid, Doi-Edwards independent alignment), with empirical models, and with recent theory. The molecular stress function theory (M. Wagner, see reference) has been fully implemented for predicting shear flow, uniaxial extension, planar extension and equi-biaxial extension of polymer melts. The tube-dilation theory (McLeish and coworkers, see references) is established for linear viscoelastic predictions; it is in testing for non-linear flows. More theory modules are in progress.
Experiment: For complex materials, the understanding of rheological behavior can be greatly advanced through careful experiments that are followed by a detailed data analysis. Our initial focus was solely on the data analysis. There, we used and still use a comprehensive and efficient code that is designed to analyze data to the fullest extent and at high rate. Take mechanical spectroscopy data G’(w),G”(w) as example, where a typical 5-to-10 minutes analysis provides time-temperature superposition, spectrum calculation, and plotting of the main material functions. The most commonly found rheological experiments are included in IRIS:
Dynamic mechanical spectroscopy,
Steady shear,
Start-up of shear and extension,
Step strain,
Creep experiment.
Research
The IRIS platform and the associated tools generate a research environment that focuses on rheological concepts and their application while minimizing the time that is spent with repetitive tasks. For experimental work, it helps to validate data, explore their limits, search for patterns, and connect into theory. For researching theory, it helps to validate theoretical predictions and to compare one theory with another.
Theory has advanced rapidly in recent years, but these advances have gone different ways for different research groups. In contrast to the well established analysis of rheometry data, theory is far from being consolidated. Because of this exciting diversity and novelty of ideas, it is important to have several theories represented. It is now possible to plot predictions from theory in the same graph as experiments. Predictions of one theory can be plotted against predictions of another theory. This will allow critical evaluation of theory. Beyond this practical aspect, theory describes the underlying molecular dynamics to a level that exceeds the realm of current experimentation. The gained insight in molecular details produces new challenges for experimentalists and for the practice of rheology.
Rheological instruments have reached a high level of sophistication and, as a consequence, an abundance of high quality rheological data have become available for a wide variety of material classes. The high data volume in rheology has three main aspects: (1) the actual measurement and all its complications, (2) the analysis of the experimental data, and (3) the seamless communication of the results to larger user groups. Seamless communication in combination with detailed analysis is achieved with unified data structure and unified methods of applying these data as attempted with the IRIS platform. Questions can be addressed such as: How can we cope with myriads of rheological data? How can we extract useful information in a reasonably short time? Are the data self-consistent? What are the dominating experimental parameters?
Education
The meaningful use of rheology requires a deeper understanding of the underlying principles. Such understanding is critically needed both in industry and in academia. The interactive graphics approach to rheology, as proposed here, makes it a great teaching tool for introducing rheology to a wide audience. Graphics has the advantage that it can explain complex concepts to students at an early state of their education. The interactive graphics also helps non-rheologists (post graduates or the sales engineer of the above example) to develop rheological skills that are necessary for understanding experiments or applications. At the same time, they will explore the molecular origin of their observed flow phenomena. Predictive tools allow calculating flow induced molecular stretch and orientation in polymer melts as function of molecular topology (linear, short-chain branched, stars, pom-pom; size).
Applications
Applications can reach from the very fundamental (development of a new polymer with specific molecular topology) to the very practical. Here is an example where the IRIS approach can add value to the service a company gives to its customers: A sales engineer, for instance, will be able to address specific questions of a customer by providing quantitative rheological information without delay. Consider a sales engineer with a customer that requests creep data of a specific polymer ABC at 150oC. However, the only data available for ABC are omega, G’, G” at 120 oC, 140 oC, 160 oC, 180 oC, and the sales engineer is far away from her/his office. A meaningful response to the customer will require additional work and will cause delay. This is where IRIS can add value. Instead of promising the delivery of 150 oC creep data in a week or two, (s)he accesses the central server, downloads the data (omega, G’, G” at 120 oC, 140 oC, 160 oC, 180 oC), applies time-temperature superposition to merge these data into a master curve, calculates the retardation time spectrum, calculates the creep function, transfers the resulting plot to a word processor, and prints the 150 oC creep graph for the customer. With the theory modules, the engineer can predict effects of varied molecular topology and suggest a suitable polymer for the application at hand. All of these actions can be performed while continuing the interactions with the customer. The sales engineer has to be trained for the interactive rheology work, but the training is not extensive.
Conclusions
The basic framework for interactive theory and experiment in rheology is now defined. The unified platform adds value to rheological research, education, and industrial application. Theories and experimental data can be shared and explored by large groups of experimentalists, theoreticians, and applied engineers (seamless communication). The necessary tools are established and tested. Several theories are implemented. Further modules will be added in the near future.
Acknowledgement
The IRIS platform has emerged from many years of work experience with rheology, mostly at the University of Massachusetts (UMass) Amherst. It has also benefited from suggestions of many rheologists (worldwide) during its entire development process. The code itself was written by Marian Mours. Theory modules were written by Richard J. Blackwell (Tube Dilation Theory) and Manfred H. Wagner (Molecular Stress Function Theory). HHW is especially grateful for the 2004 Conti Faculty Fellowship that UMass awarded to him for establishing an interactive rheology course that utilizes the IRIS tools in the classroom.
References
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Baumgärtel M, Winter HH (1992) J Non-Newtonian Fluid Mech 44:15-36
Blackwell RJ, Harlen OG, McLeish TCB (2001) Macromolecules 34:2579-2596
McLeish TCB, Allgaier J, Bick DK, Bishko G, Biswas P, Blackwell R, Blottiere B, Clarke N, Gibbs B, Groves DJ, Hakiki A, Hoenan RK, Johnson JM, Kant R, Read DJ, Young RN (1999) Macromolecules 32:6734-6758
McLeish TCB, Larson RG (1998) J Rheology 42: 81-110
Milner ST. McLeish TCB (1997) Macromolecules 30:2159-2166
Milner ST; McLeish, TCB (1998) Phys Rev Lett 81:725-728.
Mours M, Winter HH (1994) Rheol Acta 33:385-397
Mours M, Winter HH (2000) Mechanical spectroscopy. Tanaka T, Ed, Experimental Methods in Polymer Science: Modern Methods in Polymer Research and Technology, Academic Press, San Diego CA. p. 495-546
Mours M, Winter HH (2004) https://rheology.tripod.com/
Pryke A, Blackwell R J, McLeish TCB, Young RN (2002) Macromolecules 35:467-472
Wagner MH, Yamaguchi M, Takahashi M (2003) J Rheol 47:779-793
Winter HH (1997) J Non-Newtonian Fluid Mech 68:225-239