Structure-Process-Property Relations in Soft Matter – a Computational Physics Approach

MOLPROCOMP

Principal Investigator: Prof. Dr. Kurt Kremer
Project Coordinator: Dr. Kostas Daoulas

Duration: 5 years
Starting date: February 2014

From cell biology to polymer photovoltaics, (self-)assembly processes that give rise to morphology and functionality result from non-equilibrium processes, which are driven by both, external forces, such as flow due to pressure gradients, inserting energy, or manipulation on a local molecular level, or internal forces, such as relaxation into a state of lower free energy. The resulting material is arrested in a metastable state. Most previous work has focused on the relationship between structure and properties, while insight into the guiding principles governing the formation of a (new) material, has been lacking. However, a comprehensive molecular level understanding of non-equilibrium assembly would allow for control and manipulation of material processes and their resulting properties. This lag of knowledge can be traced to the formidable challenge in obtaining a molecular picture of non-equilibrium assembly. Non-equilibrium processes have been studied extensively on a macroscopic level by non-equilibrium thermodynamics. We take a novel route approaching the challenge from a molecular point of view. Recent advances in experimental, but especially computational modeling, now allow to follow (supra-) molecular structural evolution across the range of length and time scales necessary to comprehend, and ultimately control and manipulate macroscopic functional properties of soft matter at the molecular level. Soft matter is particularly suited for that approach, as it is “slow” and easy to manipulate. We take the computational physics route, based on simulations on different levels of resolution (all atom, coarse grained, continuum) in combination with recent multiscale and adaptive resolution techniques. This work will initiate the way towards a paradigm change from conventional Structure Property Relations (SPR) to molecularly based Structure Process Property Relations (SPPR).

Publications

2019

1.
Hsu, H.-P.; Kremer, K.: A coarse-grained polymer model for studying the glass transition. The Journal of Chemical Physics 150 (9), 091101 (2019)

2018

2.
Smrek, J.; Kremer, K.; Rosa, A.: Threading of Unconcatenated Ring Polymers at High Concentrations: Double-Folded vs Time-Equilibrated Structures. ACS Macro Letters 8 (2), pp. 155 - 160 (2019)
3.
Zhang, G.; Chazirakis, A.; Harmandaris, V. A.; Stühn, T.; Daoulas, K. C.; Kremer, K.: Hierarchical modelling of polystyrene melts: from soft blobs to atomistic resolution. Soft Matter 15 (2), pp. 289 - 302 (2019)
4.
Hsu, H.-P.; Kremer, K.: Chain Retraction in Highly Entangled Stretched Polymer Melts. Physical Review Letters 121 (16), 167801 (2018)
5.
Smrek, J.; Kremer, K.: Interfacial Properties of Active-Passive Polymer Mixtures. Entropy 20 (7), 520 (2018)
6.
Hsu, H.-P.; Kremer, K.: Primitive Path Analysis and Stress Distribution in Highly Strained Macromolecules. ACS Macro Letters 7 (1), pp. 107 - 111 (2018)

2017

7.
Fiorentini, R.; Kremer, K.; Potestio, R.; Fogarty, A. C.: Using force-based adaptive resolution simulations to calculate solvation free energies of amino acid sidechain analogues. The Journal of Chemical Physics 146 (24), 244113 (2017)
8.
Hsu, H.-P.; Kremer, K.: Detailed analysis of Rouse mode and dynamic scattering function of highly entangled polymer melts in equilibrium. European Physical Journal - Special Topics 226 (4), pp. 693 - 703 (2017)
9.
Smrek, J.; Kremer, K.: Small Activity Differences Drive Phase Separation in Active-Passive Polymer Mixtures. Physical Review Letters 118 (9), 098002 (2017)
10.
Radu, M.; Kremer, K.: Enhanced Crystal Growth in Binary Lennard-Jones Mixtures. Physical Review Letters 118 (5), 055702 (2017)

2016

11.
Fogarty, A. C.; Potestio, R.; Kremer, K.: A multi-resolution model to capture both global fluctuations of an enzyme and molecular recognition in the ligand-binding site. Proteins: Structure, Function, and Bioinformatics 84 (12), pp. 1902 - 1913 (2016)
12.
Kreis, K.; Potestio, R.; Kremer, K.; Fogarty, A. C.: Adaptive Resolution Simulations with Self-Adjusting High-Resolution Regions. Journal of Chemical Theory and Computation 12 (8), pp. 4067 - 4081 (2016)
13.
Hsu, H.-P.; Kremer, K.: Static and dynamic properties of large polymer melts in equilibrium. The Journal of Chemical Physics 144 (15), 154907 (2016)

2015

14.
Fogarty, A. C.; Potestio, R.; Kremer, K.: Adaptive resolution simulation of a biomolecule and its hydration shell: Structural and dynamical properties. The Journal of Chemical Physics 142 (19 ), 195101 (2015)
15.
Kreis, K.; Fogarty, A. C.; Kremer, K.; Potestio, R.: Advantages and challenges in coupling an ideal gas to atomistic models in adaptive resolution simulations. European Physical Journal 224 (12), pp. 2289 - 2304 (2015)
16.
Gemünden, P.; Poelking, C.; Kremer, K.; Daoulas, K.; Andrienko, D.: Effect of Mesoscale Ordering on the Density of States of Polymeric Semiconductors. Macromolecular Rapid Communications 36 (11), pp. 1047 - 1053 (2015)
17.
Espanol, P.; Delgado-Buscalioni, R.; Everaers, R.; Potestio, R.; Donadio, D.; Kremer, K.: Statistical mechanics of Hamiltonian adaptive resolution simulations. The Journal of Chemical Physics 142 (6 ), 064115 (2015)
18.
Zhang, G.; Stuehn, T.; Daoulas, K. C.; Kremer, K.: Communication: One size fits all: Equilibrating chemically different polymer liquids through universal long-wavelength description. The Journal of Chemical Physics 142 (22), 221102 (2015)
19.
Mukherji, D.; Marques, C. M.; Stuehn, T.; Kremer, K.: Co-non-solvency: Mean-field polymer theory does not describe polymer collapse transition in a mixture of two competing good solvents. The Journal of Chemical Physics 142 (11), 114903 (2015)

2014

20.
Kreis, K.; Donadio, D.; Kremer, K.; Potestio, R.: A unified framework for force-based and energy-based adaptive resolution simulations. EPL 108 (3), 30007 (2014)
21.
Potestio, R.; Peter, C.; Kremer, K.: Computer Simulations of Soft Matter: Linking the Scales. Entropy 16 (8), pp. 4199 - 4245 (2014)
22.
Mukherji, D.; Marques, C. M.; Kremer, K.: Polymer collapse in miscible good solvents is a generic phenomenon driven by preferential adsorption. Nature Communications 5, 4882 (2014)
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