Soft Matter Roadmap

Jean-Louis Barrat (1) , Emanuela del Gado (2) , Stefan Egelhaaf (3) , Xiaoming Mao (4) , Marjolein Dijkstra (5) , David Pine (6) , Sanat Kumar (7) , Kyle Bishop (7) , Oleg Gang (7) , Allie Obermeyer (7) , Christine Papadakis (8) , Costantinos Tsitsilianis (9) , Ivan Smalyukh (10) , Aurelie Hourlier-Fargette (11) , Sebastien Andrieux (11) , Wiebke Drenckhan (11) , Norman Wagner (12) , Ryan Murphy (13) , Eric Weeks (14) , Roberto Cerbino (15) , Yilong Han (16) , Luca Cipelletti (17, 18) , Laurence Ramos (18) , Wilson Poon (19) , James Richards (19) , Itai Cohen (20) , Eric Furst (12) , Alshakim Nelson (21) , Stephen Craig (22) , Rajesh Ganapathy (23) , Ajay Kumar Sood (24) , Francesco Sciortino (25) , Muhittin Mungan (26, 27) , Srikanth Sastry (23) , Colin Scheibner (28, 29) , Michel Fruchart (29, 28) , Vincenzo Vitelli (29, 28) , S. Ridout (30, 14) , M. Stern (30) , I. Tah (30, 31) , G. Zhang (30, 32) , Andrea Liu (30, 33) , Chinedum Osuji (30) , Yuan Xu (34) , Heather Shewan (34) , Jason Stokes (34) , Matthias Merkel (35, 36, 37) , Pierre Ronceray (38, 37) , Jean-François Rupprecht (35, 36, 37) , Olga Matsarskaia (39) , Frank Schreiber (40) , Felix Roosen-Runge (41) , Marie-Eve Aubin-Tam (42) , Gijsje Koenderink (42) , Rosa Espinosa-Marzal (43) , Joaquin Yus (43) , Jiheon Kwon (43)

1 LIPhy - Laboratoire Interdisciplinaire de Physique [Saint Martin d’Hères]
2 GU - Georgetown University [Washington]
3 Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf]
4 UMFlint - University of Michigan [Flint]
5 Universiteit Utrecht / Utrecht University [Utrecht]
6 SUNY - State University of New York
7 Columbia University [New York]
8 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
9 University of Patras
10 University of Colorado [Boulder]
11 ICS - Institut Charles Sadron
12 University of Delaware [Newark]
13 NIST - National Institute of Standards and Technology [Gaithersburg]
14 Emory University [Atlanta, GA]
15 University of Vienna [Vienna]
16 HKUST - Hong Kong University of Science and Technology
17 L2C - Laboratoire Charles Coulomb
18 IUF - Institut universitaire de France
19 Edin. - University of Edinburgh
20 Cornell University [New York]
21 University of Washington [Seattle]
22 Duke University [Durham]
23 JNCASR - Jawaharlal Nehru Centre for Advanced Scientific Research
24 IISc - Indian Institute of Science
25 UNIROMA - Università degli Studi di Roma "La Sapienza" = Sapienza University [Rome]
26 University of Cologne
27 Universität Bonn = University of Bonn
28 James Franck Institute
29 University of Chicago
30 University of Pennsylvania
31 IICB - CSIR Indian Institute of Chemical Biology Kolkata
32 CUHK - City University of Hong Kong [Hong Kong]
33 Flatiron Institute
34 UQ [All campuses : Brisbane, Dutton Park Gatton, Herston, St Lucia and other locations] - The University of Queensland
35 CPT - Centre de Physique Théorique - UMR 7332
36 CPT - E5 Physique statistique et systèmes complexes
37 TCLS - Turing Centre for Living Systems [Marseille]
38 CINaM - Centre Interdisciplinaire de Nanoscience de Marseille
39 ILL - Institut Laue-Langevin
40 University of Tübingen
41 Malmö Högskola = Malmö University
42 TU Delft - Delft University of Technology
43 UIUC - University of Illinois at Urbana-Champaign [Urbana]

Soft materials are usually defined as materials made of mesoscopic entities, often self-organized, 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 characterize 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 paper 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 characterization, instrumental, simulation and theoretical methods as well as general concepts.

Domaines: Physique [physics]

Jean-Louis Barrat, Emanuela del Gado, Stefan Egelhaaf, Xiaoming Mao, Marjolein Dijkstra, et al.. Soft Matter Roadmap. Journal of Physics: Materials, 2023, ⟨10.1088/2515-7639/ad06cc⟩. ⟨hal-04260533⟩