Review

The nanoscale circuitry of battery electrodes

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Science  15 Dec 2017:
Vol. 358, Issue 6369, eaao2808
DOI: 10.1126/science.aao2808

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Although overall battery performance is limited by the electrochemistry of the component materials, the actual performance can be limited by a number of factors. Zhu et al. review different electrode architectures for lithium-ion batteries. In particular, they look at the relations between the kinetics and dimensionality of the different electrode constituents. Making things smaller can improve transport of electrons and ions, but at the cost of making the overall architecture more complex. The authors discuss the overall design rules and criteria to guide battery design.

Science, this issue p. eaao2808

Structured Abstract

BACKGROUND

Developing high-performance, affordable, and durable batteries is one of the decisive technological tasks of our generation. Designing such batteries requires more than just the identification of electroactive storage materials with desirable properties such as high voltage, high capacity, and sufficient stability. These materials must also be assembled with ion- and electron-conducting phases into a composite electrode architecture, and this step is of equal significance; the size, shape, and spatial distribution of the various phases have a decisive influence on the charging and discharging rate capability of the electrode. Because the combined motion of ions and electrons within the solid is notoriously sluggish at room temperature, reduction of the transport length by downsizing the storage particles is indispensable. However, this necessity shifts the transport problems to the electrode’s internal circuitry. That is, every electroactive particle must be part of a network that rapidly provides both ions from an electrolyte and electrons from an electronic current collector. If nanosized particles are used, then a myriad of particles and connections are required, resulting in a network with a degree of nanoscale intricacy comparable to that of electronic circuits in information technology or bioelectrochemical networks in living systems (see the figure). While electronic circuits are based on electron transport and bioelectrochemistry relies on ion motion, battery electrodes require a combination of electron-conducting, ion-conducting, and mixed-conducting phases.

ADVANCES

Criteria for rational electrode design are based on transport and dimensional parameters. The optimal size of the storage particles can be estimated from the chemical diffusivity and the (dis)charging rate needed in the application. An important strategy is to implement two different length scales over which ions and electrons must diffuse within the storage phase to reach the ionic (electrolyte) and electronic current collector phases. The optimal values of these two “wiring lengths” depend on the ionic and electronic conductivities of the storage material. Nanoscale structures with different dimensionalities such as dots, fibers, and sheets are often useful for various reasons. If the current-collecting phases exhibit appreciable resistance due to tiny feature sizes, a hierarchical structure is helpful. Such considerations help to optimize the morphology and simplify the circuitry. They also provide a conceptual framework for organizing the vast literature on nanostructured battery materials and for reviewing characteristic topologies in a systematic way. To realize the targeted electrode architectures, substantial progress has been achieved by adapting various chemical and physical preparation methods. The figure shows lithium-storing tin particles embedded in a 2-μm-diameter carbon fiber prepared by electrospinning. Often a synthesized structure must deviate from the general design criteria to address material-specific stability issues such as interfacial reactivity, crack formation, agglomeration, and dendrite growth. Structural evolution during battery cycling is being elucidated by new methods based on x-ray absorption, electron microscopy, and other nondestructive probes that can provide in operando analysis at a variety of length scales.

OUTLOOK

More powerful multiscale computational approaches are needed to adequately model the mixed-conducting electrode networks. Such numerical treatments will be helpful in optimizing electrode structures beyond the semiquantitative design rules reviewed here. The further development of synthetic methods is also vital, so that the desired complex and hierarchical architectures can be systematically reduced into practice. Whether or not even self-organized networks may be realized—as is the case in bioelectrochemical systems—remains to be seen. Finally, continued development of in operando characterization methods will surely boost our still-limited understanding of combined ion and electron transport in the presence of complicating factors such as mechanical strain, slow interfacial reactions, crystallographic anisotropy, phase transformations, and morphological instability.

Battery electrodes, integrated electronic circuits, and bioelectrochemical networks all exhibiting intricate connections and nanoscale charge transport, although for different reasons.MICROGRAPH IS REPRODUCED FROM Y. YU ET AL., J. AM. CHEM. SOC. 131, 15984–15985 (2009) WITH PERMISSION; OTHER IMAGES COPYRIGHT SERGEY NIVENS, ROMAN SAKHNO/123RF.COM

Abstract

Developing high-performance, affordable, and durable batteries is one of the decisive technological tasks of our generation. Here, we review recent progress in understanding how to optimally arrange the various necessary phases to form the nanoscale structure of a battery electrode. The discussion begins with design principles for optimizing electrode kinetics based on the transport parameters and dimensionality of the phases involved. These principles are then used to review and classify various nanostructured architectures that have been synthesized. Connections are drawn to the necessary fabrication methods, and results from in operando experiments are highlighted that give insight into how electrodes evolve during battery cycling.

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