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Cite this: DOI: 10.1039/c4sm02344g
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Opportunities in theoretical and computational polymeric materials and soft matter Andrea J. Liu,a Gary S. Grest,b M. Cristina Marchetti,c Gregory M. Grason,d Mark O. Robbins,e Glenn H. Fredrickson,f Michael Rubinstein*g and Monica Olvera de la Cruz*h Soft materials are abundant in nature and ubiquitous in living systems. Elucidating their multi-faceted properties and underlying mechanisms is not only theoretically challenging and important in its own right, but also serves as the foundation for new materials and applications that will have wide-ranging impact on technology and the national economy. Recent initiatives in computation and data-driven materials discovery, such as the Materials Genome Initiative and the National Science Foundation Designing Materials to Revolutionize and Engineer our Future (NSF-DMREF) program, recognize and
Received 24th October 2014 Accepted 30th January 2015
highlight the many future opportunities in the field. Building upon similar past efforts, a workshop was held at the University of California, Santa Barbara in October 2013 to specifically identify the central
DOI: 10.1039/c4sm02344g
challenges and opportunities in theoretical and computational studies of polymeric as well as non-
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polymeric soft materials. This article presents a summary of the main findings of the workshop.
1. Introduction So materials constitute the basic components of living systems, are inextricably integrated into the fabric of modern society, and will be critical in future devices. Polymers are of vital importance in improving energy efficiency in the transportation sector, in fabricating consumer electronics, and in packaging food and personal care items. Supramolecular materials mimic biological bers and tissue, offering the possibility of fabricating materials with the properties of living systems. The gels, creams, and pastes that are common in health and personal care products and many processed foods are complex mixtures of colloidal particles, polymers, solvents, surfactants, avors, colorants, and fragrances. Granular matter is processed and transported in agriculture, food, mining, construction, and pharmaceutical industries. Additionally, ionic liquids, molecular electrolytes, and ion-containing a
Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19014, USA
b
Center for Integrated Nanotechnologies, Sandia National Laboratories, NM 87185, USA
c Department of Physics and Syracuse Biomaterials Institute, Syracuse University, Syracuse, NY 13244, USA d
Department of Polymer Science and Engineering, University of Massachusetts, Amherst, MA 01003, USA
e
Department of Physics & Astronomy, Johns Hopkins University, MD 21218, USA
f
Departments of Chemical Engineering and Materials and Materials Research Laboratory, University of California, Santa Barbara, CA 93106, USA
g
Department of Chemistry, University of North Carolina, Chapel Hill, NC 27599, USA
h
Department of Materials Science and Engineering, Northwestern University, IL 60208, USA
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polymers are the basis for products ranging from super-absorbents to separators and membranes for advanced energy devices such as batteries and fuel cells. So materials are integral to developments in organic electronics, such as energy harvesting organic photovoltaic devices (OPV), new display and lighting technologies (OTFT, OLED), and to advanced medical devices and therapies (implants, tissue engineering, drug delivery, personalized medicine). So materials also pose unique theoretical challenges. They are dubbed “so” because their structure is typically exquisitely sensitive to temperature, composition, external stimuli or other associated variables. This sensitivity arises from the competition among different interactions and between interactions and entropy. So materials are also highly correlated many-body systems, with complex structures and dynamics spanning a wide range of length and time scales. Many so systems are disordered, so tools derived from solid state physics do not apply. They may also be far from equilibrium, so that they cannot be understood using standard statistical mechanics. The report from a previous NSF workshop, “Interdisciplinary, Globally-Leading Polymer Science and Engineering” (IGLPSE) held in 2007 (ref. 1) elegantly assessed the current state of polymer science and engineering in the USA and the world. It identied future challenges and opportunities for research and education in polymers and so materials. While that study elaborated commercial and economic drivers for increased investment in polymer science, along with key research opportunities on the experimental side of the discipline (synthesis, characterization, and processing), the coverage of theory and simulation was limited and pre-dated recent
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initiatives in computation and data-driven materials discovery such as the Materials Genome Initiative (MGI)2 and the NSF DMREF Program.3 As a consequence, a second NSF workshop entitled “Opportunities in Theoretical and Computational Polymeric Materials and So Matter” (OTCPMSM) was held on October 20–22, 2013 at the University of California, Santa Barbara (UCSB).4 Major crosscutting challenges and opportunities identied at this workshop are summarized in the present article, while detailed and area-specic report can be found at http://www.nsfreport.polymericsomaterials.northwestern.edu/ nal_report.pdf. In the six years since the NSF-IGLPSE report, the rapid and widespread deployment of horizontal drilling and hydraulic fracturing technologies have opened up vast natural gas and oil reserves in previously inaccessible shale deposits. The resulting abundant supply of inexpensive “shale gas” has huge implications for many sectors of the US economy and is having unanticipated positive effects on both the environment and net carbon emissions (by substitution of gas for coal in electricity generation). While much of the shale oil is now directed to transportation fuels, the gas and associated natural gas liquids, largely ethane and propane, are being exploited by the US chemical industry as low-cost feedstock to produce ethylene and propylene, the basic C2 and C3 building blocks for the monomers, polymers, solvents and surfactants that comprise nearly all synthetic so materials. To fully exploit this new abundance, we must advance our theoretical understanding of polymer and so matter science and engineering to synthesize new materials by design in emerging areas such as medicine, energy, and electronics. Concurrent to the new abundance of natural gas liquids, remarkable changes have occurred in the eld of polymeric and so matter theory. New areas such as so origami and mechanical metamaterials have emerged, research on active matter is burgeoning and fundamental advances are being made on longstanding nonequilibrium problems such as the glass and jamming transitions (see Fig. 1 and 2). New colloidal materials and processes are emerging through advances in our understanding of shape, interactions, and entropy. New hardware platforms such as GPUs, high-throughput, data-centric approaches, and the application of machine-learning and evolutionary/genetic algorithms have begun to transform the computational landscape in the eld, bridging discovery and design. The remainder of this article outlines a number of theoretical challenges and opportunities motivated by these developments.
2.
Challenges and opportunities
Theory and simulation: so materials are “hard”. Theory and simulation are but one component of the science and engineering base necessary to support future developments in so materials, yet they are of vital importance to drive innovation and rapid, cost-effective deployment of solutions in an increasingly competitive world. In part, this is due to remarkable and continuing advances in the availability of low-cost, high-performance computing platforms. However, the need to
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dramatically accelerate the materials design process mandates increased deployment of predictive physics-based models, coupled via cyber-infrastructure to comprehensive property databases and high-throughput experimentation. Such motivations to advance theory and simulation science are not unique to so materials and are well articulated for broad classes of materials in the Materials Genome Initiative.3 Nonetheless, other material families present less formidable challenges to in silico design. While metals, ceramics, and inorganic semiconductors and oxides are largely crystalline materials with relatively small unit cells of 10 nm or less, polymers and so materials are for the most part amorphous uids or solids with embedded structures spanning nanometers to microns and even millimeters or more. Beyond this daunting range of length scales, so materials can possess an extraordinarily broad spectrum of time scales when assembling or responding to stimuli, oen covering more than ten orders of magnitude. Worse yet, in many cases the relaxation processes contributing to this broad spectrum involve nonequilibrium phenomena such as vitrication, jamming, or constrained crystallization, which are highly process-dependent and for which no comprehensive theoretical framework and understanding exist. Another distinguishing and complicating factor in the development of so materials, especially in the personal care product domain, is the large number, diversity in types, and variety in molecular architectures of components – oen ten or more distinct polymers, solvent/small molecules, surfactants, or particulate ingredients, all interacting in a complex way to balance a set of properties or performance metrics. In the following six subsections of this article, we highlight opportunities and challenges relating to polymer and so matter theory and simulation that were identied during the UCSB Workshop. The complete report, with the same titles as the following subsections, provides in-depth discussion and support for the summary points and recommendations provided here and can be downloaded at http://www.nsfreport. polymericsomaterials.northwestern.edu/nal_report.pdf.
2.1
Reversing the arrow: materials by design
In the forward problem, so material theorists and simulators build particle-level mathematical models for a specic system, such as a mixture of colloids and polymers of given composition. They then use theory or computation to predict the resulting structure and properties. The forward problem is oen solved repeatedly, because parameters such as composition are varied. This establishes a map between composition and materials properties. In the inverse problem, by contrast, one works backwards from a desired set of materials properties to design a system with those properties. While the forward problem has a unique solution, the inverse problem may not, so it is necessary to devise criteria for obtaining a “best solution.” Thus, the inverse problem requires global optimization with a feedback loop that adjusts composition or other system parameters, and with a forward prediction engine that calculates the desired properties for each system.
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Formulating reliable and efficient theoretical/computational methods for the forward problem. It is a formidable challenge to correlate combined macroscopic properties, such as capacitance, transparency, and stretchability, with the nano- and mesoscopic composition of a material. Studies to improve the understanding of separate physical processes and their underlying relationships would help to formulate connections between desired functionality and experimental control parameters. Developing practical and reliable solutions to the inverse problem. This could involve exploring genetic algorithms, metadynamics, or other techniques for identifying globally optimal solutions. It could be that a technique would work well for one class of so material problems but not for others, so it seems likely that a range of tools is required.
2.2
Exploiting geometry in form and function
Many traditional areas of so materials science combine molecular components to achieve morphology and material properties through molecular scale self-assembly, phase separation, or chemical reaction, e.g. crosslinking, to form gels or networks. Modern synthetic and fabrication methods now provide, however, a much broader palette of building blocks, whereby molecular-scale components (solvents, monomers, polymers, liquid crystals, chiral compounds, block copolymers, etc.) can be combined with nanoscale to microscale entities (nanoparticles, colloids, nanotubes) and even larger micro/ macro-scale units (complex shapes fabricated by sheet photolithography or other techniques), to create responsive so materials that are dynamic, complex, hierarchical, polymorphic, and profoundly recongurable. Such responsiveness is possible precisely because so matter is “so”—its structure is exquisitely sensitive to perturbations. While the inverse design problem is the ultimate target, even the forward problem remains challenging for many classes of responsive so materials that integrate components and geometrical information on multiple length scales. Potential applications abound in elds such as exible electronics, tissue repair, switchable photonic devices, and so robotics. Designing “so origami”. Here the challenge is to design the internal structure of exible lower-dimensional objects so that they fold, when perturbed, into desired three-dimensional shapes. The competition between the energy required to deform the order on the surface and the energy required to change the shape of the surface—in general nonlinearly coupled and hence frustrated—can lead to a rich variety of geometrical outcomes and material characteristics and function. The design principles connecting programmed two-dimensional fold patterns in so matter to targeted three-dimensional shapes are only now coming into focus. Equally critical, the nature of the exponentially-large “congurational landscape” between at and target shapes, as well as its inuence on emergent so origami dynamics and mechanics (not unlike the protein folding problem) remain to be understood. Developing new “mechanical metamaterials”. Geometric control of pores/holes has led to materials whose exotic properties are just beginning to be explored, from directed
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Soft Matter
“oppiness” to selective transmission of acoustic vibrations (i.e. “inaudibility cloaks”). Much more theoretical work is needed to understand the principles and limitations of “programming” a material's mechanical response through its geometry. Sculpting so matter via the boundary. So materials are extremely sensitive to the properties of enclosing boundaries. The ability to template bulk structure by controlling properties of a lower dimensional boundary is a powerful design strategy akin to setting a complex mechanical system in motion through initial conditions. The goal is to turn time into space and evolve systems boundaries to build target structures with full threedimensional order and requisite function. So materials formed in this way could be used to template reaction sites for catalysis or separations, to organize/optimize electronic or optical activity, or to control and guide phonons and photons. The design rules are virtually unexplored.
2.3
Harnessing nonequilibrium phenomena
With the exception of some so materials in the liquid state, virtually all so materials are deployed in a state that is not the equilibrium lowest-free-energy state. In some cases this is because the material has (partially) crystallized in the solid state, a familiar example being a semi-crystalline polymer such as polyethylene (PE) or polypropylene (PP). In other instances, such as polystyrene, a molten polymer vitries upon cooling into a glassy state. In these examples, it is clear that the structure/morphology of the material and its properties are highly dependent on the process used to produce it. The current lack of understanding of behavior far from equilibrium inhibits optimization of materials performance. For example, semi-crystalline conjugated polymers are used to create solution-processed organic electronic devices, such as bulk heterojunction solar cells and thin-lm transistors for advanced displays. Device performance and efficiency are closely linked to crystal morphology, but the task of nding process parameters (choice of solvent, temperature, additives, etc.) that lead to the optimal morphology is currently a black art. Nonequilibrium processing can lead to materials with far more desirable properties than are naturally attainable. A prime example are the ultra-high performance polyethylene bers manufactured using sophisticated “gel spinning” techniques that exploit diluted entanglements in a solvent-swollen, partially crystallized gel ber state to draw, anneal, and dry the material (ultrahigh molecular weight PE). The result is a ber with remarkably high crystallinity and exceptional modulus and tensile strength, suitable for applications ranging from sutures for spinal surgery to marine cables to ballistic protection (personal body armor). Living systems exploit nonequilibrium phenomena to produce materials with far more intricate structures and sophisticated, robust functions than synthetic materials. An important goal is therefore to rationally design the entire nonequilibrium process by which a material is made, to create new materials with functions that rival those of living systems. Understanding many-body behavior far from equilibrium. This challenge is particularly important for so and polymeric materials. The very sensitivity to perturbations that is a hallmark of
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so matter implies that virtually all so materials are out of equilibrium, with properties that depend on the kinetics of the process used to make them. More reliable and efficient theoretical and computational approaches are needed to understand what structure and properties result from a specied nonequilibrium process. This challenge can be viewed as the “forward problem” for nonequilibrium materials processing. Designing so materials processing. This is the related inverse problem, where the aim is to design a process, which could involve both equilibrium and nonequilibrium steps, that leads to a material with the desired set of properties. Controlling structure via kinetics. So materials typically have complex structure on a range of length scales due to competing interactions or forms of entropy. As a result, so materials are oen characterized by complex free energy landscapes with multiple metastable minima. A pervasive problem is that the systems can become kinetically trapped in metastable minima, unable to reach the equilibrium state. On the other hand, some of these minima might have desirable structures and properties. A key theoretical challenge is to understand how to avoid some kinetic traps and to exploit others to optimize function. Developing understanding of glass and jamming transitions and the glassy and jammed states. Many so materials have such complex free energy landscapes that they are glassy or jammed. This property is critical to applications such as membranes for purifying water or separating CO2, but can be disastrous in plants that process granular materials. Because the glass transition and jamming transitions are inherently nonequilibrium phenomena, and glassy and jammed states are nonequilibrium states, fundamental theoretical understanding is still lacking. Understanding friction and adhesion. These are also far from equilibrium processes. They are controlled by the complex chemistry and geometry of surfaces, which oen have bumps on top of bumps on scales from nanometers to millimeters.
Fig. 1 All solids flow via particle rearrangements at high enough applied stress and melt at high enough temperature. In this model glass, machine learning methods have been applied to the local structural geometry to identify “soft” particles that are susceptible to rearrangement. The degree of softness of each particle is indicated by color on a blue (hard) to red (soft) scale. Courtesy of E. D. Cubuk, S. Schoenholz, B. Malone, E. Kaxiras and A. J. Liu.
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Multiscale modeling is required to capture this structure while accurately describing bond breaking and formation between surface atoms. Optimizing adhesive performance and decreasing friction requires understanding dissipation mechanisms that operate at all scales, loading rates, and loading conditions. 2.4
New paradigms inspired by nature
The interface between the elds of biology and so matter has spawned exciting new strategies for designing biomimetic materials. Promising structural design motifs such as those found in abalone shell and spider silk point the way to designing materials of tightly-controlled and complex structure, with remarkable materials properties. This line of research, inspired by biological structures, remains a vibrant area of research in materials theory (see Fig. 3). A second related direction is to design materials inspired by biological functions such as self-replication, information processing, chemical and mechanical signaling, and motility. Many but not all of these functions are carried out far from equilibrium. Like the forward and inverse problems discussed in Section 2.1, two twin threads run through research on materials inspired by biological structure and function. Just as one must understand the forward problem in order to be able to solve the inverse problem, one must understand the physical basis of biological structure and/or function in order to design new synthetic materials inspired by them. Understanding active matter. Active matter differs from the familiar passive matter studied by materials theorists in that it is maintained out of equilibrium by injecting energy at a microscopic scale. This energy can then be transferred to larger scales via a “reverse energy cascade”. In contrast, passive matter is usually driven out of equilibrium by external forces applied either globally or at the macroscopic scale and then transferred to smaller scales. The materials theory
Fig. 2 Confined active particles organize in jammed glassy states with local correlated dynamical rearrangements typical of glasses and supercooled fluids. Similar fluctuations are seen in migrating cell layers and vibrated granular materials. (Reprinted with permission from ref. 5 Copyright 2011 by the American Physical Society.)
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Fig. 3 The measured spatial distribution of forces exerted by group of cells on substrates can be described by active matter theory. Cell groups behave like a cohesive material as cell–cell interaction increases (left to right).6 First row: time-course of traction stress (red arrows) produced by mouse keratinocytes following activation of intercellular adhesion via calcium. Second row: strain energy generated by above keratinocytes. Third row: active matter model's prediction of strain energy.
community is just beginning to develop theoretical understanding of the collective properties of active matter, including how to distinguish and classify different states of active matter. Developing a theoretical framework for understanding information out of equilibrium. The ability to transmit and acquire information through chemical and mechanical signaling is critical to many biological processes. In equilibrium, information can be understood in terms of entropy. For systems out of equilibrium, however, there is as yet no understanding of the fundamental principles of information processing. Understanding physical mechanisms underlying biological functions. Many biological functions involve sophisticated selfassembly and/or nonequilibrium processes. In most cases, energy must be supplied and converted from one form (for example, chemical energy) into another (such as mechanical energy). While biochemists and biologists have studied the chemical basis of biological processes for decades, the role of mechanics in biology remained relatively neglected and is a natural target of interest for so materials theorists. Designing new functional materials inspired by biological functions. This is the inverse problem to the forward problem of understanding the mechanisms underlying function. Designing specic functions is a very challenging problem that requires not only a detailed understanding of the mechanisms underlying these functions, but also the development of algorithms for function selection and optimization.
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2.5
Bridging scales in space and time
The development of a theoretical framework to seamlessly, continuously, and accurately model polymers and so matter across multiple time and length scales would signicantly accelerate the design and deployment of new so materials. Understanding so matter poses unique computational challenges where microscopic physical phenomena strongly couple to macroscopic time and length scales through multiple mechanisms. It requires: (1) new conceptual abilities, tools, and data infrastructure to describe systems at different time and length scales, (2) the knowledge to transfer information between different time and length scales, and (3) the development of feedback loops from macroscopic to atomistic to quantum. Advances are needed in models and simulation techniques at four key levels, rst-principles quantum, classical atomistic, mesoscopic, and continuum, but especially in interfacing the output from one class of model to the input of the next. In some cases, the theoretical constructs necessary to connect models between scales are missing, or are yet to be optimized and standardized among the community. Developing polarizable and reactive potentials at the quantum to atomistic interface. Many-body potentials that can accurately model bond breaking and formation are essential to describing equilibrium and non-equilibrium phenomena in many important and emerging so materials systems such as vitrimers,
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supramolecular polymers, networks, gels, and glasses. Polarizable potentials are key to the development of quantitative models for ion-containing polymers, useful in a variety of energy devices and polyelectrolytes common in consumer products. Developing a framework for mapping atomic congurations to coarse-grained models at the mesoscale. At present, there is no consensus on how to map from the atomic scale to the mesoscale, for example, to pseudo-atoms in particle models or collective elds in statistical eld theory models. Furthermore, a framework is needed to address transferability of coarse-grained model parameters to situations other than those for which they were derived, and to subsequent steps on the coarse-graining hierarchy. One difficulty of coarse-graining is that it inherently changes the local energy barriers and can destroy important topological characteristics such as entanglements. Another aspect of the challenge is therefore to accomplish the mapping in a way that preserves the dynamics of the underlying atomic systems. Developing a systematic strategy for concurrent modeling, i.e. treating different parts of a system simultaneously with different simulation techniques at different scales. An important part of this challenge is to standardize and validate the methods used to couple models at interfaces between different computational zones. Methods are also needed to address computational inefficiencies associated with the time-sampling requirements of the fastest components. Finally, new techniques are needed to address difficult materials phenomena that engage all length and time scales simultaneously, such as thermal transport of electronic degrees of freedom. Developing a culture of data sharing and propagation of standards for sharing in the computational so matter community. At present, there is redundancy of effort and lost opportunities for data usage and mining. An operating paradigm is needed for developing, maintaining, and funding soware platforms, as well as automated processes for archiving and curating data generated by a large and diverse community of modelers.
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modeling and simulations and sponsor external research or engage experts on theoretical topics, most predominantly practice and externally support experimental research. The limited industrial engagement in so matter theory and simulation is primarily due to the lack of quantitative, reliable tools that can capture multi-scale phenomena in complex systems and make accurate predictions of materials behavior/ properties using readily available computational resources on a timescale that can impact the design process. While the notion of “in silico” materials design is a compelling one, we are far from being able to realize it in virtually all so materials of commercial interest. It is critical that government agencies take the lead in supporting “in silico” design of so materials, since success is at least a decade away – well beyond the horizon of “long-term” research in even the most strategic of so materials companies. Signicantly more investment is needed to develop the theoretical constructs, soware tools, computational resources, and data infrastructure necessary to enable rstprinciples computational design. Developing in-depth course offerings covering a broad spectrum of so matter systems and both theoretical and experimental topics at more universities. Offerings are oen split between science (chemistry, physics, biology) and engineering (chemical, materials) departments, and at most institutions there is little effort to coordinate or integrate the available courses into a meaningful emphasis or specialty. Developing a suite of online courses to address the shortage of local offerings. Existing courses offered in a range of departments across the US could be professionally recorded and combined into comprehensive graduate or undergraduate programs on polymers and so matter. The recorded lectures can be indexed and made available to any student, scientist, or educator interested in this fascinating and rapidly growing eld by placing them on a polymer and so matter education website.
3. 2.6
Broader impacts and education
Polymers and so materials are integral to modern society. From sourcing raw materials to manufacture and deployment, so materials and their products represent a very signicant component of the U.S. and world economy. Industrial employers requiring technical expertise in so matter systems are numerous and span diverse business sectors, including resins, bers, apparel, molded plastics, home furnishings, elastomers, composites, pharmaceuticals, personal care products, electronics, medical devices, and processed foods, among others. There is a strong demand in industry for employees at the B.S., M.S., and Ph.D. levels that are broadly trained in so matter science, spanning synthesis, characterization, processing, and properties, and encompassing a wide spectrum of material systems from polymers to colloids, composites, foams, emulsions, and gels. Theoretical and computational so matter skills are currently less sought aer by the industrial sector than experimental training. While a few large companies in the so materials/chemicals sector have internal R&D experts in
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Concluding remarks
The challenges and opportunities highlighted in this article extend the scope of past efforts, which contained limited coverage of theory and simulation and pre-dated recent initiatives in computation and data-driven materials discovery such as the Materials Genome Initiative and the National Science Foundation Designing Materials to Revolutionize and Engineer our Future (NSF-DMREF) program, based on the premise that many future opportunities in the eld are expected at the interface of polymeric and other so materials. Moreover, there are many topics that have signicant overlap, and many fundamental concepts, such as gelation or glass transition, are common across different so materials. Considering opportunities in these areas from a broader prospective would contribute to their deeper understanding and overall progress in building new tools to bridge discovery and design in the so matter research community.
Acknowledgements This article summarizes the report that can be downloaded at http://www.nsfreport.polymericsomaterials.northwestern.edu/
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nal_report.pdf, which is the result of hard work by all workshop participants, and we would like to thank them for their cooperation and wisdom during the two and a half days of the workshop. We are especially grateful to Drs. Mark Bowick, Alexander Grosberg, Sanat Kumar, Sharon Glotzer, Fred MacKintosh, Murugappan Muthukumar, Kenneth Shull, Dvora Perahia and Thomas Witten who made an extra effort to write summaries of the discussions of the working groups and to edit the corresponding parts of the report, and to Ting Ge for designing the cover of the report. We thank William Kung at the NU-MRSEC for input in the organization and editing of both the article and the report and to Sara Bard and Naomi Recania of UCSB for their superb local orchestration of the workshop. Finally, we would like to thank NSF for funding the workshop and CMMT Program directors Drs. Daryl Hess and Andrey Dobrynin for their support and assistance throughout the whole process.
References 1 NSF workshop, Interdisciplinary, Globally-Leading Polymer Science and Engineering (IGLPSE), Arlington, VA, 15–17
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August 2007, http://people.ccmr.cornell.edu/cober/NSFPolymer Workshop/assets/NSF%20Polymer%20Workshop.pdf. Materials Genome Initiative (MGI), White House Office of Science & Technology Policy, http://www.whitehouse.gov/ mgi. Designing Materials to Revolutionize and Engineer our Future (DMREF), National Science Foundation, http://www.nsf.gov/ publications/pub_summ.jsp?ods_key¼nsf14591. NSF workshop, Opportunities in Theoretical and Computational Polymeric Materials and So Matter, University of California, Santa Barbara, CA, 20–22 October 2013. See report at http://www.nsfreport.polymericsomaterials. northwestern.edu/nal_report.pdf. S. Henkes, Y. Fily and M. C. Marchetti, Active jamming: selfpropelled so particles at high density, Phys. Rev. E: Stat., Nonlinear, So Matter Phys., 2011, 84, 040301(R). A. F. Mertz, Y. Che, S. Banerjee, J. M. Goldstein, K. A. Rosowski, S. F. Revilla, C. M. Niessen, M. C. Marchetti, E. R. Dufresne and V. Horsley, Cadherin-based intercellular adhesions organize epithelial cell-matrix traction forces, Proc. Natl. Acad. Sci. U. S. A., 2013, 110, 842.
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OPINION
Cite this: DOI: 10.1039/c4sm02344g
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Opportunities in theoretical and computational polymeric materials and soft matter Andrea J. Liu,a Gary S. Grest,b M. Cristina Marchetti,c Gregory M. Grason,d Mark O. Robbins,e Glenn H. Fredrickson,f Michael Rubinstein*g and Monica Olvera de la Cruz*h Soft materials are abundant in nature and ubiquitous in living systems. Elucidating their multi-faceted properties and underlying mechanisms is not only theoretically challenging and important in its own right, but also serves as the foundation for new materials and applications that will have wide-ranging impact on technology and the national economy. Recent initiatives in computation and data-driven materials discovery, such as the Materials Genome Initiative and the National Science Foundation Designing Materials to Revolutionize and Engineer our Future (NSF-DMREF) program, recognize and
Received 24th October 2014 Accepted 30th January 2015
highlight the many future opportunities in the field. Building upon similar past efforts, a workshop was held at the University of California, Santa Barbara in October 2013 to specifically identify the central
DOI: 10.1039/c4sm02344g
challenges and opportunities in theoretical and computational studies of polymeric as well as non-
www.rsc.org/softmatter
polymeric soft materials. This article presents a summary of the main findings of the workshop.
1. Introduction So materials constitute the basic components of living systems, are inextricably integrated into the fabric of modern society, and will be critical in future devices. Polymers are of vital importance in improving energy efficiency in the transportation sector, in fabricating consumer electronics, and in packaging food and personal care items. Supramolecular materials mimic biological bers and tissue, offering the possibility of fabricating materials with the properties of living systems. The gels, creams, and pastes that are common in health and personal care products and many processed foods are complex mixtures of colloidal particles, polymers, solvents, surfactants, avors, colorants, and fragrances. Granular matter is processed and transported in agriculture, food, mining, construction, and pharmaceutical industries. Additionally, ionic liquids, molecular electrolytes, and ion-containing a
Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19014, USA
b
Center for Integrated Nanotechnologies, Sandia National Laboratories, NM 87185, USA
c Department of Physics and Syracuse Biomaterials Institute, Syracuse University, Syracuse, NY 13244, USA d
Department of Polymer Science and Engineering, University of Massachusetts, Amherst, MA 01003, USA
e
Department of Physics & Astronomy, Johns Hopkins University, MD 21218, USA
f
Departments of Chemical Engineering and Materials and Materials Research Laboratory, University of California, Santa Barbara, CA 93106, USA
g
Department of Chemistry, University of North Carolina, Chapel Hill, NC 27599, USA
h
Department of Materials Science and Engineering, Northwestern University, IL 60208, USA
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polymers are the basis for products ranging from super-absorbents to separators and membranes for advanced energy devices such as batteries and fuel cells. So materials are integral to developments in organic electronics, such as energy harvesting organic photovoltaic devices (OPV), new display and lighting technologies (OTFT, OLED), and to advanced medical devices and therapies (implants, tissue engineering, drug delivery, personalized medicine). So materials also pose unique theoretical challenges. They are dubbed “so” because their structure is typically exquisitely sensitive to temperature, composition, external stimuli or other associated variables. This sensitivity arises from the competition among different interactions and between interactions and entropy. So materials are also highly correlated many-body systems, with complex structures and dynamics spanning a wide range of length and time scales. Many so systems are disordered, so tools derived from solid state physics do not apply. They may also be far from equilibrium, so that they cannot be understood using standard statistical mechanics. The report from a previous NSF workshop, “Interdisciplinary, Globally-Leading Polymer Science and Engineering” (IGLPSE) held in 2007 (ref. 1) elegantly assessed the current state of polymer science and engineering in the USA and the world. It identied future challenges and opportunities for research and education in polymers and so materials. While that study elaborated commercial and economic drivers for increased investment in polymer science, along with key research opportunities on the experimental side of the discipline (synthesis, characterization, and processing), the coverage of theory and simulation was limited and pre-dated recent
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initiatives in computation and data-driven materials discovery such as the Materials Genome Initiative (MGI)2 and the NSF DMREF Program.3 As a consequence, a second NSF workshop entitled “Opportunities in Theoretical and Computational Polymeric Materials and So Matter” (OTCPMSM) was held on October 20–22, 2013 at the University of California, Santa Barbara (UCSB).4 Major crosscutting challenges and opportunities identied at this workshop are summarized in the present article, while detailed and area-specic report can be found at http://www.nsfreport.polymericsomaterials.northwestern.edu/ nal_report.pdf. In the six years since the NSF-IGLPSE report, the rapid and widespread deployment of horizontal drilling and hydraulic fracturing technologies have opened up vast natural gas and oil reserves in previously inaccessible shale deposits. The resulting abundant supply of inexpensive “shale gas” has huge implications for many sectors of the US economy and is having unanticipated positive effects on both the environment and net carbon emissions (by substitution of gas for coal in electricity generation). While much of the shale oil is now directed to transportation fuels, the gas and associated natural gas liquids, largely ethane and propane, are being exploited by the US chemical industry as low-cost feedstock to produce ethylene and propylene, the basic C2 and C3 building blocks for the monomers, polymers, solvents and surfactants that comprise nearly all synthetic so materials. To fully exploit this new abundance, we must advance our theoretical understanding of polymer and so matter science and engineering to synthesize new materials by design in emerging areas such as medicine, energy, and electronics. Concurrent to the new abundance of natural gas liquids, remarkable changes have occurred in the eld of polymeric and so matter theory. New areas such as so origami and mechanical metamaterials have emerged, research on active matter is burgeoning and fundamental advances are being made on longstanding nonequilibrium problems such as the glass and jamming transitions (see Fig. 1 and 2). New colloidal materials and processes are emerging through advances in our understanding of shape, interactions, and entropy. New hardware platforms such as GPUs, high-throughput, data-centric approaches, and the application of machine-learning and evolutionary/genetic algorithms have begun to transform the computational landscape in the eld, bridging discovery and design. The remainder of this article outlines a number of theoretical challenges and opportunities motivated by these developments.
2.
Challenges and opportunities
Theory and simulation: so materials are “hard”. Theory and simulation are but one component of the science and engineering base necessary to support future developments in so materials, yet they are of vital importance to drive innovation and rapid, cost-effective deployment of solutions in an increasingly competitive world. In part, this is due to remarkable and continuing advances in the availability of low-cost, high-performance computing platforms. However, the need to
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dramatically accelerate the materials design process mandates increased deployment of predictive physics-based models, coupled via cyber-infrastructure to comprehensive property databases and high-throughput experimentation. Such motivations to advance theory and simulation science are not unique to so materials and are well articulated for broad classes of materials in the Materials Genome Initiative.3 Nonetheless, other material families present less formidable challenges to in silico design. While metals, ceramics, and inorganic semiconductors and oxides are largely crystalline materials with relatively small unit cells of 10 nm or less, polymers and so materials are for the most part amorphous uids or solids with embedded structures spanning nanometers to microns and even millimeters or more. Beyond this daunting range of length scales, so materials can possess an extraordinarily broad spectrum of time scales when assembling or responding to stimuli, oen covering more than ten orders of magnitude. Worse yet, in many cases the relaxation processes contributing to this broad spectrum involve nonequilibrium phenomena such as vitrication, jamming, or constrained crystallization, which are highly process-dependent and for which no comprehensive theoretical framework and understanding exist. Another distinguishing and complicating factor in the development of so materials, especially in the personal care product domain, is the large number, diversity in types, and variety in molecular architectures of components – oen ten or more distinct polymers, solvent/small molecules, surfactants, or particulate ingredients, all interacting in a complex way to balance a set of properties or performance metrics. In the following six subsections of this article, we highlight opportunities and challenges relating to polymer and so matter theory and simulation that were identied during the UCSB Workshop. The complete report, with the same titles as the following subsections, provides in-depth discussion and support for the summary points and recommendations provided here and can be downloaded at http://www.nsfreport. polymericsomaterials.northwestern.edu/nal_report.pdf.
2.1
Reversing the arrow: materials by design
In the forward problem, so material theorists and simulators build particle-level mathematical models for a specic system, such as a mixture of colloids and polymers of given composition. They then use theory or computation to predict the resulting structure and properties. The forward problem is oen solved repeatedly, because parameters such as composition are varied. This establishes a map between composition and materials properties. In the inverse problem, by contrast, one works backwards from a desired set of materials properties to design a system with those properties. While the forward problem has a unique solution, the inverse problem may not, so it is necessary to devise criteria for obtaining a “best solution.” Thus, the inverse problem requires global optimization with a feedback loop that adjusts composition or other system parameters, and with a forward prediction engine that calculates the desired properties for each system.
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Formulating reliable and efficient theoretical/computational methods for the forward problem. It is a formidable challenge to correlate combined macroscopic properties, such as capacitance, transparency, and stretchability, with the nano- and mesoscopic composition of a material. Studies to improve the understanding of separate physical processes and their underlying relationships would help to formulate connections between desired functionality and experimental control parameters. Developing practical and reliable solutions to the inverse problem. This could involve exploring genetic algorithms, metadynamics, or other techniques for identifying globally optimal solutions. It could be that a technique would work well for one class of so material problems but not for others, so it seems likely that a range of tools is required.
2.2
Exploiting geometry in form and function
Many traditional areas of so materials science combine molecular components to achieve morphology and material properties through molecular scale self-assembly, phase separation, or chemical reaction, e.g. crosslinking, to form gels or networks. Modern synthetic and fabrication methods now provide, however, a much broader palette of building blocks, whereby molecular-scale components (solvents, monomers, polymers, liquid crystals, chiral compounds, block copolymers, etc.) can be combined with nanoscale to microscale entities (nanoparticles, colloids, nanotubes) and even larger micro/ macro-scale units (complex shapes fabricated by sheet photolithography or other techniques), to create responsive so materials that are dynamic, complex, hierarchical, polymorphic, and profoundly recongurable. Such responsiveness is possible precisely because so matter is “so”—its structure is exquisitely sensitive to perturbations. While the inverse design problem is the ultimate target, even the forward problem remains challenging for many classes of responsive so materials that integrate components and geometrical information on multiple length scales. Potential applications abound in elds such as exible electronics, tissue repair, switchable photonic devices, and so robotics. Designing “so origami”. Here the challenge is to design the internal structure of exible lower-dimensional objects so that they fold, when perturbed, into desired three-dimensional shapes. The competition between the energy required to deform the order on the surface and the energy required to change the shape of the surface—in general nonlinearly coupled and hence frustrated—can lead to a rich variety of geometrical outcomes and material characteristics and function. The design principles connecting programmed two-dimensional fold patterns in so matter to targeted three-dimensional shapes are only now coming into focus. Equally critical, the nature of the exponentially-large “congurational landscape” between at and target shapes, as well as its inuence on emergent so origami dynamics and mechanics (not unlike the protein folding problem) remain to be understood. Developing new “mechanical metamaterials”. Geometric control of pores/holes has led to materials whose exotic properties are just beginning to be explored, from directed
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“oppiness” to selective transmission of acoustic vibrations (i.e. “inaudibility cloaks”). Much more theoretical work is needed to understand the principles and limitations of “programming” a material's mechanical response through its geometry. Sculpting so matter via the boundary. So materials are extremely sensitive to the properties of enclosing boundaries. The ability to template bulk structure by controlling properties of a lower dimensional boundary is a powerful design strategy akin to setting a complex mechanical system in motion through initial conditions. The goal is to turn time into space and evolve systems boundaries to build target structures with full threedimensional order and requisite function. So materials formed in this way could be used to template reaction sites for catalysis or separations, to organize/optimize electronic or optical activity, or to control and guide phonons and photons. The design rules are virtually unexplored.
2.3
Harnessing nonequilibrium phenomena
With the exception of some so materials in the liquid state, virtually all so materials are deployed in a state that is not the equilibrium lowest-free-energy state. In some cases this is because the material has (partially) crystallized in the solid state, a familiar example being a semi-crystalline polymer such as polyethylene (PE) or polypropylene (PP). In other instances, such as polystyrene, a molten polymer vitries upon cooling into a glassy state. In these examples, it is clear that the structure/morphology of the material and its properties are highly dependent on the process used to produce it. The current lack of understanding of behavior far from equilibrium inhibits optimization of materials performance. For example, semi-crystalline conjugated polymers are used to create solution-processed organic electronic devices, such as bulk heterojunction solar cells and thin-lm transistors for advanced displays. Device performance and efficiency are closely linked to crystal morphology, but the task of nding process parameters (choice of solvent, temperature, additives, etc.) that lead to the optimal morphology is currently a black art. Nonequilibrium processing can lead to materials with far more desirable properties than are naturally attainable. A prime example are the ultra-high performance polyethylene bers manufactured using sophisticated “gel spinning” techniques that exploit diluted entanglements in a solvent-swollen, partially crystallized gel ber state to draw, anneal, and dry the material (ultrahigh molecular weight PE). The result is a ber with remarkably high crystallinity and exceptional modulus and tensile strength, suitable for applications ranging from sutures for spinal surgery to marine cables to ballistic protection (personal body armor). Living systems exploit nonequilibrium phenomena to produce materials with far more intricate structures and sophisticated, robust functions than synthetic materials. An important goal is therefore to rationally design the entire nonequilibrium process by which a material is made, to create new materials with functions that rival those of living systems. Understanding many-body behavior far from equilibrium. This challenge is particularly important for so and polymeric materials. The very sensitivity to perturbations that is a hallmark of
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so matter implies that virtually all so materials are out of equilibrium, with properties that depend on the kinetics of the process used to make them. More reliable and efficient theoretical and computational approaches are needed to understand what structure and properties result from a specied nonequilibrium process. This challenge can be viewed as the “forward problem” for nonequilibrium materials processing. Designing so materials processing. This is the related inverse problem, where the aim is to design a process, which could involve both equilibrium and nonequilibrium steps, that leads to a material with the desired set of properties. Controlling structure via kinetics. So materials typically have complex structure on a range of length scales due to competing interactions or forms of entropy. As a result, so materials are oen characterized by complex free energy landscapes with multiple metastable minima. A pervasive problem is that the systems can become kinetically trapped in metastable minima, unable to reach the equilibrium state. On the other hand, some of these minima might have desirable structures and properties. A key theoretical challenge is to understand how to avoid some kinetic traps and to exploit others to optimize function. Developing understanding of glass and jamming transitions and the glassy and jammed states. Many so materials have such complex free energy landscapes that they are glassy or jammed. This property is critical to applications such as membranes for purifying water or separating CO2, but can be disastrous in plants that process granular materials. Because the glass transition and jamming transitions are inherently nonequilibrium phenomena, and glassy and jammed states are nonequilibrium states, fundamental theoretical understanding is still lacking. Understanding friction and adhesion. These are also far from equilibrium processes. They are controlled by the complex chemistry and geometry of surfaces, which oen have bumps on top of bumps on scales from nanometers to millimeters.
Fig. 1 All solids flow via particle rearrangements at high enough applied stress and melt at high enough temperature. In this model glass, machine learning methods have been applied to the local structural geometry to identify “soft” particles that are susceptible to rearrangement. The degree of softness of each particle is indicated by color on a blue (hard) to red (soft) scale. Courtesy of E. D. Cubuk, S. Schoenholz, B. Malone, E. Kaxiras and A. J. Liu.
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Multiscale modeling is required to capture this structure while accurately describing bond breaking and formation between surface atoms. Optimizing adhesive performance and decreasing friction requires understanding dissipation mechanisms that operate at all scales, loading rates, and loading conditions. 2.4
New paradigms inspired by nature
The interface between the elds of biology and so matter has spawned exciting new strategies for designing biomimetic materials. Promising structural design motifs such as those found in abalone shell and spider silk point the way to designing materials of tightly-controlled and complex structure, with remarkable materials properties. This line of research, inspired by biological structures, remains a vibrant area of research in materials theory (see Fig. 3). A second related direction is to design materials inspired by biological functions such as self-replication, information processing, chemical and mechanical signaling, and motility. Many but not all of these functions are carried out far from equilibrium. Like the forward and inverse problems discussed in Section 2.1, two twin threads run through research on materials inspired by biological structure and function. Just as one must understand the forward problem in order to be able to solve the inverse problem, one must understand the physical basis of biological structure and/or function in order to design new synthetic materials inspired by them. Understanding active matter. Active matter differs from the familiar passive matter studied by materials theorists in that it is maintained out of equilibrium by injecting energy at a microscopic scale. This energy can then be transferred to larger scales via a “reverse energy cascade”. In contrast, passive matter is usually driven out of equilibrium by external forces applied either globally or at the macroscopic scale and then transferred to smaller scales. The materials theory
Fig. 2 Confined active particles organize in jammed glassy states with local correlated dynamical rearrangements typical of glasses and supercooled fluids. Similar fluctuations are seen in migrating cell layers and vibrated granular materials. (Reprinted with permission from ref. 5 Copyright 2011 by the American Physical Society.)
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Fig. 3 The measured spatial distribution of forces exerted by group of cells on substrates can be described by active matter theory. Cell groups behave like a cohesive material as cell–cell interaction increases (left to right).6 First row: time-course of traction stress (red arrows) produced by mouse keratinocytes following activation of intercellular adhesion via calcium. Second row: strain energy generated by above keratinocytes. Third row: active matter model's prediction of strain energy.
community is just beginning to develop theoretical understanding of the collective properties of active matter, including how to distinguish and classify different states of active matter. Developing a theoretical framework for understanding information out of equilibrium. The ability to transmit and acquire information through chemical and mechanical signaling is critical to many biological processes. In equilibrium, information can be understood in terms of entropy. For systems out of equilibrium, however, there is as yet no understanding of the fundamental principles of information processing. Understanding physical mechanisms underlying biological functions. Many biological functions involve sophisticated selfassembly and/or nonequilibrium processes. In most cases, energy must be supplied and converted from one form (for example, chemical energy) into another (such as mechanical energy). While biochemists and biologists have studied the chemical basis of biological processes for decades, the role of mechanics in biology remained relatively neglected and is a natural target of interest for so materials theorists. Designing new functional materials inspired by biological functions. This is the inverse problem to the forward problem of understanding the mechanisms underlying function. Designing specic functions is a very challenging problem that requires not only a detailed understanding of the mechanisms underlying these functions, but also the development of algorithms for function selection and optimization.
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2.5
Bridging scales in space and time
The development of a theoretical framework to seamlessly, continuously, and accurately model polymers and so matter across multiple time and length scales would signicantly accelerate the design and deployment of new so materials. Understanding so matter poses unique computational challenges where microscopic physical phenomena strongly couple to macroscopic time and length scales through multiple mechanisms. It requires: (1) new conceptual abilities, tools, and data infrastructure to describe systems at different time and length scales, (2) the knowledge to transfer information between different time and length scales, and (3) the development of feedback loops from macroscopic to atomistic to quantum. Advances are needed in models and simulation techniques at four key levels, rst-principles quantum, classical atomistic, mesoscopic, and continuum, but especially in interfacing the output from one class of model to the input of the next. In some cases, the theoretical constructs necessary to connect models between scales are missing, or are yet to be optimized and standardized among the community. Developing polarizable and reactive potentials at the quantum to atomistic interface. Many-body potentials that can accurately model bond breaking and formation are essential to describing equilibrium and non-equilibrium phenomena in many important and emerging so materials systems such as vitrimers,
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supramolecular polymers, networks, gels, and glasses. Polarizable potentials are key to the development of quantitative models for ion-containing polymers, useful in a variety of energy devices and polyelectrolytes common in consumer products. Developing a framework for mapping atomic congurations to coarse-grained models at the mesoscale. At present, there is no consensus on how to map from the atomic scale to the mesoscale, for example, to pseudo-atoms in particle models or collective elds in statistical eld theory models. Furthermore, a framework is needed to address transferability of coarse-grained model parameters to situations other than those for which they were derived, and to subsequent steps on the coarse-graining hierarchy. One difficulty of coarse-graining is that it inherently changes the local energy barriers and can destroy important topological characteristics such as entanglements. Another aspect of the challenge is therefore to accomplish the mapping in a way that preserves the dynamics of the underlying atomic systems. Developing a systematic strategy for concurrent modeling, i.e. treating different parts of a system simultaneously with different simulation techniques at different scales. An important part of this challenge is to standardize and validate the methods used to couple models at interfaces between different computational zones. Methods are also needed to address computational inefficiencies associated with the time-sampling requirements of the fastest components. Finally, new techniques are needed to address difficult materials phenomena that engage all length and time scales simultaneously, such as thermal transport of electronic degrees of freedom. Developing a culture of data sharing and propagation of standards for sharing in the computational so matter community. At present, there is redundancy of effort and lost opportunities for data usage and mining. An operating paradigm is needed for developing, maintaining, and funding soware platforms, as well as automated processes for archiving and curating data generated by a large and diverse community of modelers.
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modeling and simulations and sponsor external research or engage experts on theoretical topics, most predominantly practice and externally support experimental research. The limited industrial engagement in so matter theory and simulation is primarily due to the lack of quantitative, reliable tools that can capture multi-scale phenomena in complex systems and make accurate predictions of materials behavior/ properties using readily available computational resources on a timescale that can impact the design process. While the notion of “in silico” materials design is a compelling one, we are far from being able to realize it in virtually all so materials of commercial interest. It is critical that government agencies take the lead in supporting “in silico” design of so materials, since success is at least a decade away – well beyond the horizon of “long-term” research in even the most strategic of so materials companies. Signicantly more investment is needed to develop the theoretical constructs, soware tools, computational resources, and data infrastructure necessary to enable rstprinciples computational design. Developing in-depth course offerings covering a broad spectrum of so matter systems and both theoretical and experimental topics at more universities. Offerings are oen split between science (chemistry, physics, biology) and engineering (chemical, materials) departments, and at most institutions there is little effort to coordinate or integrate the available courses into a meaningful emphasis or specialty. Developing a suite of online courses to address the shortage of local offerings. Existing courses offered in a range of departments across the US could be professionally recorded and combined into comprehensive graduate or undergraduate programs on polymers and so matter. The recorded lectures can be indexed and made available to any student, scientist, or educator interested in this fascinating and rapidly growing eld by placing them on a polymer and so matter education website.
3. 2.6
Broader impacts and education
Polymers and so materials are integral to modern society. From sourcing raw materials to manufacture and deployment, so materials and their products represent a very signicant component of the U.S. and world economy. Industrial employers requiring technical expertise in so matter systems are numerous and span diverse business sectors, including resins, bers, apparel, molded plastics, home furnishings, elastomers, composites, pharmaceuticals, personal care products, electronics, medical devices, and processed foods, among others. There is a strong demand in industry for employees at the B.S., M.S., and Ph.D. levels that are broadly trained in so matter science, spanning synthesis, characterization, processing, and properties, and encompassing a wide spectrum of material systems from polymers to colloids, composites, foams, emulsions, and gels. Theoretical and computational so matter skills are currently less sought aer by the industrial sector than experimental training. While a few large companies in the so materials/chemicals sector have internal R&D experts in
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Concluding remarks
The challenges and opportunities highlighted in this article extend the scope of past efforts, which contained limited coverage of theory and simulation and pre-dated recent initiatives in computation and data-driven materials discovery such as the Materials Genome Initiative and the National Science Foundation Designing Materials to Revolutionize and Engineer our Future (NSF-DMREF) program, based on the premise that many future opportunities in the eld are expected at the interface of polymeric and other so materials. Moreover, there are many topics that have signicant overlap, and many fundamental concepts, such as gelation or glass transition, are common across different so materials. Considering opportunities in these areas from a broader prospective would contribute to their deeper understanding and overall progress in building new tools to bridge discovery and design in the so matter research community.
Acknowledgements This article summarizes the report that can be downloaded at http://www.nsfreport.polymericsomaterials.northwestern.edu/
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nal_report.pdf, which is the result of hard work by all workshop participants, and we would like to thank them for their cooperation and wisdom during the two and a half days of the workshop. We are especially grateful to Drs. Mark Bowick, Alexander Grosberg, Sanat Kumar, Sharon Glotzer, Fred MacKintosh, Murugappan Muthukumar, Kenneth Shull, Dvora Perahia and Thomas Witten who made an extra effort to write summaries of the discussions of the working groups and to edit the corresponding parts of the report, and to Ting Ge for designing the cover of the report. We thank William Kung at the NU-MRSEC for input in the organization and editing of both the article and the report and to Sara Bard and Naomi Recania of UCSB for their superb local orchestration of the workshop. Finally, we would like to thank NSF for funding the workshop and CMMT Program directors Drs. Daryl Hess and Andrey Dobrynin for their support and assistance throughout the whole process.
References 1 NSF workshop, Interdisciplinary, Globally-Leading Polymer Science and Engineering (IGLPSE), Arlington, VA, 15–17
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August 2007, http://people.ccmr.cornell.edu/cober/NSFPolymer Workshop/assets/NSF%20Polymer%20Workshop.pdf. Materials Genome Initiative (MGI), White House Office of Science & Technology Policy, http://www.whitehouse.gov/ mgi. Designing Materials to Revolutionize and Engineer our Future (DMREF), National Science Foundation, http://www.nsf.gov/ publications/pub_summ.jsp?ods_key¼nsf14591. NSF workshop, Opportunities in Theoretical and Computational Polymeric Materials and So Matter, University of California, Santa Barbara, CA, 20–22 October 2013. See report at http://www.nsfreport.polymericsomaterials. northwestern.edu/nal_report.pdf. S. Henkes, Y. Fily and M. C. Marchetti, Active jamming: selfpropelled so particles at high density, Phys. Rev. E: Stat., Nonlinear, So Matter Phys., 2011, 84, 040301(R). A. F. Mertz, Y. Che, S. Banerjee, J. M. Goldstein, K. A. Rosowski, S. F. Revilla, C. M. Niessen, M. C. Marchetti, E. R. Dufresne and V. Horsley, Cadherin-based intercellular adhesions organize epithelial cell-matrix traction forces, Proc. Natl. Acad. Sci. U. S. A., 2013, 110, 842.
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