Soft matter roadmap<sup>*</sup>
Jean‐Louis Barrat, Emanuela Del Gado, Stefan U. Egelhaaf, Xiaoming Mao, Marjolein Dijkstra, David J. Pine, Sanat K. Kumar, Kyle J. M. Bishop, Oleg Gang, Allie C. Obermeyer, Christine M. Papadakis, Constantinos Tsitsilianis, Ivan I. Smalyukh, Aurélie Hourlier‐Fargette, Sébastien Andrieux, Wiebke Drenckhan, Norman J. 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, A. K. Sood, Francesco Sciortino, Muhittin Mungan, Srikanth Sastry, Colin Scheibner, Michel Fruchart, Vincenzo Vitelli, Sean A. Ridout, Menachem Stern, Indrajit Tah, Ge 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, Joaquín Yus, Jiheon Kwon
Abstract
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.