Soft matter roadmap
- Author(s)
- , Jean Louis Barrat, Emanuela Del Gado, Stefan U. Egelhaaf, Xiaoming Mao, Marjolein Dijkstra, David J. Pine, Sanat K. Kumar, Kyle Bishop, Oleg Gang, Allie Obermeyer, Christine M. Papadakis, Constantinos Tsitsilianis, Ivan I. Smalyukh, Aurelie Hourlier-Fargette, Sebastien Andrieux, Wiebke Drenckhan, Norman Wagner, Ryan P. Murphy, Eric R. Weeks, Roberto Cerbino, Yilong Han, Luca Cipelletti, Laurence Ramos, Wilson C.K. Poon, James A. Richards, Itai Cohen, Eric M. Furst, Alshakim Nelson, Stephen L. Craig, Rajesh Ganapathy, Ajay Kumar Sood, Francesco Sciortino, Muhittin Mungan, Srikanth Sastry, Colin Scheibner, Michel Fruchart, Vincenzo Vitelli, S. A. Ridout, M. Stern, I. Tah, G. Zhang, Andrea J. Liu, Chinedum O. Osuji, Yuan Xu, Heather M. Shewan, Jason R. Stokes, Matthias Merkel, Pierre Ronceray, Jean François Rupprecht, Olga Matsarskaia, Frank Schreiber, Felix Roosen-Runge, Marie-Eve Aubin-Tam, Gijsje H. Koenderink, Rosa M. Espinosa-Marzal, Joaquin Yus, Jiheon Kwon
- Abstract
Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts.
- Organisation(s)
- Computational and Soft Matter Physics
- External organisation(s)
- University of Grenoble Alpes, Georgetown University, Heinrich-Heine-Universität Düsseldorf, University of Michigan, Utrecht University, NYU Langone School of Medicine, Columbia University in the City of New York, Technische Universität München, University of Patras, University of Colorado, Boulder, Institut Charles Sadron, University of Delaware, NIST Center for Neutron Research, Emory University, Hong Kong University of Science and Technology, Laboratoire Charles Coulomb, Institut universitaire de France, University of Edinburgh, Cornell University, University of Washington, Duke University, Jawaharlal Nehru Centre for Advanced Scientific Research, Indian Institute of Science, Eberhard Karls Universität Tübingen, Malmö University, Delft University of Technology, University of Illinois at Urbana-Champaign
- Journal
- JPhys Materials
- Volume
- 7
- No. of pages
- 104
- DOI
- https://doi.org/10.1088/2515-7639/ad06cc
- Publication date
- 01-2024
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 103015 Condensed matter
- Keywords
- ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics, Materials Science(all), Condensed Matter Physics
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/soft-matter-roadmap(a00a9a48-d99b-4c1f-95ad-338e3a7180e1).html