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, Costantinos 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, M 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 Stokes, Matthias Merkel, Pierre Ronceray, Jean-François Rupprecht, Olga Matsarskaia, Frank Schreiber, Felix Roosen-Runge, Marie-Eve Aubin-Tam, Gijsje Koenderink, Rosa M. Espinosa-Marzal, Joaquin Yus, Jiheon Kwon
{"title":"软物质路线图","authors":"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, Costantinos 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, M 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 Stokes, Matthias Merkel, Pierre Ronceray, Jean-François Rupprecht, Olga Matsarskaia, Frank Schreiber, Felix Roosen-Runge, Marie-Eve Aubin-Tam, Gijsje Koenderink, Rosa M. Espinosa-Marzal, Joaquin Yus, Jiheon Kwon","doi":"10.1088/2515-7639/ad06cc","DOIUrl":null,"url":null,"abstract":"Abstract 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.","PeriodicalId":36054,"journal":{"name":"JPhys Materials","volume":"8 ","pages":"0"},"PeriodicalIF":4.9000,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Soft Matter Roadmap\",\"authors\":\"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, Costantinos 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, M 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 Stokes, Matthias Merkel, Pierre Ronceray, Jean-François Rupprecht, Olga Matsarskaia, Frank Schreiber, Felix Roosen-Runge, Marie-Eve Aubin-Tam, Gijsje Koenderink, Rosa M. Espinosa-Marzal, Joaquin Yus, Jiheon Kwon\",\"doi\":\"10.1088/2515-7639/ad06cc\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract 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.\",\"PeriodicalId\":36054,\"journal\":{\"name\":\"JPhys Materials\",\"volume\":\"8 \",\"pages\":\"0\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2023-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JPhys Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1088/2515-7639/ad06cc\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JPhys Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2515-7639/ad06cc","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Abstract 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.