TY - JOUR
T1 - Soft matter roadmap
AU - Barrat, Jean-Louis
AU - Del Gado, Emanuela
AU - Egelhaaf, Stefan U.
AU - Mao, Xiaoming
AU - Dijkstra, Marjolein
AU - Pine, David J.
AU - Kumar, Sanat K.
AU - Bishop, Kyle
AU - Gang, Oleg
AU - Obermeyer, Allie
AU - Papadakis, Christine M.
AU - Tsitsilianis, Constantinos
AU - Smalyukh, Ivan I.
AU - Hourlier-Fargette, Aurelie
AU - Andrieux, Sebastien
AU - Drenckhan, Wiebke
AU - Wagner, Norman
AU - Murphy, Ryan P.
AU - Weeks, Eric R.
AU - Cerbino, Roberto
AU - Han, Yilong
AU - Cipelletti, Luca
AU - Ramos, Laurence
AU - Poon, Wilson C. K.
AU - Richards, James A.
AU - Cohen, Itai
AU - Furst, Eric M.
AU - Nelson, Alshakim
AU - Craig, Stephen L.
AU - Ganapathy, Rajesh
AU - Sood, Ajay Kumar
AU - Sciortino, Francesco
AU - Mungan, Muhittin
AU - Sastry, Srikanth
AU - Scheibner, Colin
AU - Fruchart, Michel
AU - Vitelli, Vincenzo
AU - Ridout, S. A.
AU - Stern, M.
AU - Tah, null
AU - Zhang, G.
AU - Liu, Andrea J.
AU - Osuji, Chinedum O.
AU - Xu, Yuan
AU - Shewan, Heather M.
AU - Stokes, Jason R.
AU - Merkel, Matthias
AU - Ronceray, Pierre
AU - Rupprecht, Jean-Francois
AU - Matsarskaia, Olga
AU - Schreiber, Frank
AU - Roosen-Runge, Felix
AU - Aubin-Tam, Marie-Eve
AU - Koenderink, Gijsje H.
AU - Espinosa-Marzal, Rosa M.
AU - Yus, Joaquin
AU - Kwon, Jiheon
PY - 2024/1
Y1 - 2024/1
N2 - 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.
AB - 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.
KW - soft
KW - materials
KW - matter
KW - complex
KW - polymer
KW - colloid
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001124188100001
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85180149694&origin=recordpage
UR - http://www.scopus.com/inward/record.url?scp=85180149694&partnerID=8YFLogxK
U2 - 10.1088/2515-7639/ad06cc
DO - 10.1088/2515-7639/ad06cc
M3 - RGC 21 - Publication in refereed journal
SN - 2515-7639
VL - 7
JO - Journal of Physics: Materials
JF - Journal of Physics: Materials
IS - 1
ER -