Peer Fischer, Editorial Board

Max Planck Institute for Intelligent Systems and Univ. of Stuttgart

Inspired by Richard Feynman’s famous 1959 lecture “There’s plenty of room at the bottom,” researchers are striving to build synthetic motors, machines, and robots at the micro- and nanoscale. The 2016 Nobel Prize in chemistry honors three pioneers in this field who have designed and built some of the first molecular machines (see Fig. 1A). Despite the progress in crafting structures of increasing complexity at such a small scale, truly functional dynamic nanorobots that are autonomous and that can undertake useful tasks are still in their infancy. This is in contrast to any living organism, where dynamic biological nanomachines are ubiquitous and where they accomplish functions that are readily observed at the macro scale. A beautiful example is the flagellar motor of a bacterial cell—a fully functioning rotary motor that is only 45 nm tall but that self-assembles, runs with high efficiency, and propels a bacterial cell through liquid. The challenges faced in realizing synthetic autonomous nanorobots that can rival their biological counterparts, and perhaps ultimately lead to medically useful applications, are manifold. They require the combination of basic Science and Robotics to develop suitable fabrication and assembly strategies, to address questions of control and communication, and to solve the difficulty of power transfer to small scales.

Fig. 1. The 2016 Nobel Prize in Chemistry was awarded to J.-P. Sauvage, J. F. Stoddard, and B. L. Feringa, who showed how to synthesize small organic molecules that can act as an axle, a lift, and a molecular muscle. (A) Such a molecule that functions as a molecular rotor driven by chemical energy [1]. (B) It is also possible to use DNA molecules that self-assemble into larger nanostructures [2, 3]. (C) The design of a DNA nanorotor that has recently been demonstrated [4]. The cylinder elements represent double-helical DNA domains.

Although the undertaking proposed by Feynman 50 years ago has largely remained unfulfilled, there are recent developments that suggest that this may change. Most systems so far have been based on conventional materials. Since these are governed by equilibrium statistical mechanics, conventional materials are unable to exhibit autonomous motion, organize, or perform work. In contrast, living systems contain energy-consuming building blocks, which give rise to complex behavior. Such “active” phenomena hold the key to understanding how, for instance, a micron-sized bacterial cell is able to incorporate perception, learning, and action in the absence of a neuronal system. Active matter is therefore also expected to transform the field of micro- and nanorobotics. A case in point is the field of chemical nanomotors [5], where a synthetic micro- or nanostructure immersed in a chemical fuel can self-propel and even show chemotaxis (see Fig. 2).

Fig. 2. Schematic depicts how chemical gradients that arise at an asymmetric nano- or microstructure can cause a chemical nanomotor to self-propel. The nanorobot swims in the chemical fuel. A catalytic reaction (blue arrow) leads to a local concentration gradient, which causes self-propulsion. The black arrow indicates the locomotion toward the target molecules (green). Molecular systems engineering may lead to more complex nanorobots that use internal feedback mechanisms (red arrows) as control circuits.

A modern approach to creating function in nanorobots can thus benefit from such fundamental research. While there is still plenty of room at the bottom, the integration of active phenomena into the design of micro- and nanosystems is expected to generate exciting new robotic systems. Science Robotics will report on the development of the next generation of micro- and nanorobots as well as their potential applications including in the biomedical field.


1. S. P. Fletcher, F. Dumur, M. M. Pollard, B. L. Feringa, Science 310, 80 (2005).

2. N. C. Seeman, Nature 421, 427 (2003).

3. P. W. K. Rothemund, Nature 440, 297 (2006).

4. P. Ketterer, E. M. Willner, H. Dietz, Sci. Adv2, e1501209 (2016).

5. W. F. Paxton et al.J. Am. Chem. Soc126, 13424 (2004).