Traditional approaches to materials synthesis have largely relied on uniform, equilibrated phases leading to static “condensed-matter” structures (e.g., monolithic single crystals). Departures from these modes of materials design are pervasive in biology. From the folding of proteins to the reorganization of self-regulating cytoskeletal networks, biological materials reflect a major shift in emphasis from equilibrium thermodynamic regimes to out-of-equilibrium regimes. Here, equilibrium structures, determined by global free-energy minima, are replaced by highly structured dynamical states that are out of equilibrium, calling into question the utility of global thermodynamic energy minimization as a first-principles approach. Thus, the creation of new materials capable of performing life-like functions such as complex and cooperative processes, self-replication, and self-repair, will ultimately rely upon incorporating biological principles of spatiotemporal modes of self-assembly. Elucidating fundamental principles for the design of such out-of-equilibrium dynamic self-assembling materials systems is the focus of this issue of MRS Bulletin.

Searching for materials with improved or perhaps completely novel properties involves an iterative process intended to successively narrow the gap between some initial starting point and the desired design target. This can be viewed as an optimization problem in a high-dimensional search space, often with many dozens of material parameters that need to be tuned. To tackle this, the evolutionary process in biology has been a source of inspiration in developing effective search algorithms. However, reaping the full benefits of bioinspired searches for materials design requires some thought. Here, we go beyond traditional black box algorithms and take a broader view of computational evolution strategies. We discuss recent strategies that exploit knowledge about the material configuration statistics and we highlight the advantages when time-varying environments are considered. Throughout, we emphasize that the search strategies themselves can be viewed as a nonequilibrium dynamical process in design space.

Nature’s optical nanomaterials are poised to form the platform for future optical devices with unprecedented functionality. The brilliant colors of many animals arise from the physical interaction of light with nanostructured, multifunctional materials. While their length scale is typically in the 100-nm range, the morphology of these structures can vary strongly. These biological nanostructures are obtained in a controlled manner, using biomaterials under ambient conditions. The formation processes nature employs use elements of both equilibrium self-assembly and far-from-equilibrium and growth processes. This renders not only the colors themselves, but also the formation processes technologically and ecologically highly relevant. Yet, for many biological nanostructured materials, little is known about the formation mechanisms—partially due to a lack of in vivo imaging methods. Here, we present the toolbox of natural multifunctional nanostructures and the current knowledge about the understanding of their far-from-equilibrium assembly processes.

Materials can be endowed with unique properties by the integration of molecular motors. Molecular motors can have a biological origin or can be chemically synthesized and produce work from chemical energy or light. Their ability to access large internal or external reservoirs of energy enables a wide range of nonequilibrium behaviors, including the production of force, changes in shape, internal reorganization, and dynamic changes in mechanical properties—muscle tissue is one illustration of the possibilities. Current research efforts advance our experimental capabilities to create such “active matter” by using either biomolecular or synthetic motors, and also advance our theoretical understanding of these materials systems. Here, we introduce this exciting research field and highlight a few of the recent advances as well as open questions.

Biological entities are capable of amazing material feats, such as self-organization, self-repair, self-replication, and self-immolation. Indeed, the most intriguing feature of living biomaterials, whether they are tissues, cells, or intracellular structures, is their ability to autonomously sense, decide, and perform work without the need of a project manager. The effect is multiscale—from enzymes to full organisms, each level is capable of such autonomous activities. Further, each scale has similar energy-using units that work together to compose the larger-scale material. For instance, autonomous cells work together to create tissues. In this article, we will discuss some of the outstanding and desirable properties of active biological materials that we might consider mimicking in future materials. We will discuss how such active materials are powered and explore some fundamental lessons we can learn to direct future fundamental scientific inquiries to begin to understand and use these properties to make synthetic, autonomous materials of the future.

This article addresses why biomaterials are a growing part of materials science. We consider two areas at two different scales. At the nanometer scale, enzymes are heterogeneous nanoparticles of extraordinary deformability; this property allows us to view biomolecules informed by concepts of materials science and nonlinear physics. A degree of universality in the mechanical behavior of the molecules appears in the ubiquitous softening transitions; some results obtained dynamically by nanorheology, and others obtained in equilibrium experiments through the method of the DNA springs are summarized. These soft molecules represent an opportunity for studies of dissipation at the atomic scale. At the mesoscopic scale, composite functional materials with biological components hold promise for applications such as low power, chemically driven, biodegradable devices. A concrete example, and a program for the future, is the artificial axon. It is a synthetic structure that supports action potentials based on the same physical mechanism as the voltage spikes in nerve cells. A network of such axons, which is yet to come, would constitute an artificial brain. Beyond device applications, the focus here is on the basic science, namely, a constructivist approach to cybernetics, algorithmic mathematics, and the brain.

Far-from-equilibrium systems are ubiquitous in nature. They are also rich in terms of diversity and complexity. Therefore, it is an intellectual challenge to be able to understand the physics of far-from-equilibrium phenomena. In this article, we revisit a standard tabletop experiment, the Rayleigh–Bénard convection, to explore some fundamental questions and present a new perspective from a first-principles point of view. We address how nonequilibrium fluctuations differ from equilibrium fluctuations, how emergence of order out of equilibrium breaks symmetries in the system, and how free energy of a system gets locally bifurcated to operate a Carnot-like engine to maintain order. The exploration and investigation of these nontrivial questions are the focus of this article.