Soft matter roadmap

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 CerbinoYilong 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

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations


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.

Original languageEnglish
Article number012501
JournalJPhys Materials
Issue number1
StatePublished - 1 Jan 2024

Bibliographical note

Publisher Copyright:
© 2023 The Author(s). Published by IOP Publishing Ltd.


R G thanks Jawaharlal Nehru Centre for Advanced Scientific Research and the Department of Science and Technology (DST), Govt. of India (Swarna Jayanti Fellowship Grant and DST-Nanomission Grant) for financial support. R G also thanks members of the Experimental Soft Matter Research group at JNCASR for many discussions over the years. A K S thanks the DST, Govt of India for support under the Year of Science Professorship. A K S acknowledges gratefully the contributions of his group members over the years and Professor Sriram Ramaswamy for most enjoyable collaboration over the last 30 years. C M P gratefully acknowledges Deutsche Forschungsgemeinschaft for funding (PA 771/19-1). C M P and C T thank DAAD and IKY for funding within the IKYDA program. The Flatiron Institute is a division of the Simons Foundation, which also supported this work through the collaboration ‘Cracking the glass problem’ via Grant No. 454945 (S A R and A J L) and Simons Investigator Grant No. 327939 (A J L). This work was also supported by the U. S. Department of Energy, Office of Science, DE- DE-SC0020963 (A J L), and the National Science Foundation via NSF-DMR-2005749 (M S and I T), and the UPenn MRSEC NSF-DMR-1720530 (G Z). This publication is part of the project How cytoskeletal teamwork makes cells strong (with project number VI.C.182.004 of the NWO Talent Programme which is financed by the Dutch Research Council (NWO)), and the project Light-responsive microalgal living materials (ERC starting Grant No. 101042612). Images are created with . This material is based upon work supported by the National Science Foundation under Grant No. CBET- 1637991. This work was supported by the NSF Center for the Chemistry of Molecularly Optimised Networks (MONET), CHE-2116298. We thank X Mao and S Wang for providing the graphics in figures and , respectively. This work was supported by NSF CBET Award Nos. 2010118, 1804963 and 1509308, and an NSF DMR Award No. 1507607 D J P acknowledges support from the US Army Research Office (Award No. W911NF-17-1-0328) and the US Department of Energy (Award No. DE-SC0007991). Financial support from ERC Advanced Grant No. 884902 ‘SoftML’ is acknowledged. Contributions to this article have been made possible due to research funded by the Australian Government through the Australian Research Council (ARC) Grants DP180101919 and LP160100239. This material is based upon work supported by the National Science Foundation under Grant Nos. CMMI-2035122 and CMMI-1435920, and Convergence RAISE program IOS-1848671. S S acknowledges support through the JC Bose Fellowship (JBR/2020/000015) SERB, DST (India). M M was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Projektnummer 398962893, Projektnummer 21150405, and Projektnummer 390685813. I acknowledge the support from MIUR PRIN 2017 (Project 2017Z55KCW). The authors gratefully acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG), the German Ministry for Education and Research (BMBF), the Crafoord Foundation as well as various large-scale research facilities (in particular Diamond Light Source, the ISIS Neutron and Muon Source, the European Synchrotron Radiation Facility, the Forschungsreaktor München II, the Julich Center for Neutron Science, the Institut Laue-Langevin and Oak Ridge Neutron Laboratory) for beamtime allocation and excellent on-site support. C O O acknowledges financial support from NSF through DMR-1945966 and DMR- 2223705 M M thanks the Centre Interdisciplinaire de Nanoscience de Marseille (CINaM) for providing office space. M M, P R and J-F R received funding from the «Investissements d’Avenir» French Government program managed by the French National Research Agency (ANR-16-CONV-0001) and from the Excellence Initiative of Aix-Marseille University—A*MIDEX.

FundersFunder number
Flatiron Institute
Julich Center for Neutron Science
NSF DMR1507607
Oak Ridge Neutron Laboratory
UPenn MRSEC NSF-DMR-1720530
National Science FoundationDMR- 2223705, 2010118, CMMI-2035122, 1804963, CBET- 1637991, CMMI-1435920, IOS-1848671, CHE-2116298, NSF-DMR-2005749, DMR-1945966, 1509308
U.S. Department of EnergyDE-SC0007991
Army Research OfficeW911NF-17-1-0328
Simons Foundation327939, 454945
Office of ScienceDE- DE-SC0020963
Aix-Marseille Université
European Research Council101042612, 884902
Australian Research CouncilLP160100239, DP180101919
Department of Science and Technology, Ministry of Science and Technology, India
Deutscher Akademischer Austauschdienst
Deutsche Forschungsgemeinschaft390685813, PA 771/19-1, 21150405, 398962893
Agence Nationale de la RechercheANR-16-CONV-0001
Science and Engineering Research Board
Bundesministerium für Bildung und Forschung
Crafoordska Stiftelsen
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Ministero dell’Istruzione, dell’Università e della Ricerca
State Scholarships Foundation
Jawaharlal Nehru Centre for Advanced Scientific Research
ISIS Neutron and Muon Source


    • colloid
    • complex
    • materials
    • matter
    • polymer
    • soft


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