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Despite their rapid emergence as the dominant paradigm for electrochemical energy storage, the full promise of lithium-ion batteries is yet to be fully realized, partly because of challenges in adequately resolving common degradation mechanisms. Positive electrodes of Li-ion batteries store ions in interstitial sites based on redox reactions throughout their interior volume. However, variations in the local concentration of inserted Li-ions and inhomogeneous intercalation-induced structural transformations beget substantial stress. Such stress can accumulate and ultimately engender substantial delamination and transgranular/intergranular fracture in typically brittle oxide materials upon continuous electrochemical cycling. This perspective highlights the coupling between electrochemistry, mechanics, and geometry spanning key electrochemical processes: surface reaction, solid-state diffusion, and phase nucleation/transformation in intercalating positive electrodes. In particular, we highlight recent findings on tunable material design parameters that can be used to modulate the kinetics and thermodynamics of intercalation phenomena, spanning the range from atomistic and crystallographic materials design principles (based on alloying, polymorphism, and pre-intercalation) to emergent mesoscale structuring of electrode architectures (through control of crystallite dimensions and geometry, curvature, and external strain). This framework enables intercalation chemistry design principles to be mapped to degradation phenomena based on consideration of mechanics coupling across decades of length scales. Scale-bridging characterization and modeling, along with materials design, holds promise for deciphering mechanistic understanding, modulating multiphysics couplings, and devising actionable strategies to substantially modify intercalation phase diagrams in a manner that unlocks greater useable capacity and enables alleviation of chemo-mechanical degradation mechanisms. 

Automated particle segmentation and feature analysis of experimental image data are indispensable for data-driven material science. Deep learning-based image segmentation algorithms are promising techniques to achieve this goal but are challenging to use due to the acquisition of a large number of training images. In the present work, synthetic images are applied, resembling the experimental images in terms of geometrical and visual features, to train the state-of-art Mask region-based convolutional neural networks to segment vanadium pentoxide nanowires, a cathode material within optical density-based images acquired using spectromicroscopy. The results demonstrate the instance segmentation power in real optical intensity-based spectromicroscopy images of complex nanowires in overlapped networks and provide reliable statistical information. The model can further be used to segment nanowires in scanning electron microscopy images, which are fundamentally different from the training dataset known to the model. The proposed methodology can be extended to any optical intensity-based images of variable particle morphology, material class, and beyond.

 

Substantial improvements in cycle life, rate performance, accessible voltage, and reversible capacity are required to realize the promise of Li-ion batteries in full measure. Here, we have examined insertion electrodes of the same composition (V 2 O 5 ) prepared according to the same electrode specifications and comprising particles with similar dimensions and geometries that differ only in terms of their atomic connectivity and crystal structure, specifically two-dimensional (2D) layered α-V 2 O 5 that crystallizes in an orthorhombic space group and one-dimensional (1D) tunnel-structured ζ-V 2 O 5 crystallized in a monoclinic space group. By using particles of similar dimensions, we have disentangled the role of specific structural motifs and atomistic diffusion pathways in affecting electrochemical performance by mapping the dynamical evolution of lithiation-induced structural modifications using ex situ scanning transmission X-ray microscopy, operando synchrotron X-ray diffraction measurements, and phase-field modeling. We find the operation of sharply divergent mechanisms to accommodate increasing concentrations of Li-ions: a series of distortive phase transformations that result in puckering and expansion of interlayer spacing in layered α-V 2 O 5 , as compared with cation reordering along interstitial sites in tunnel-structured ζ-V 2 O 5 . By alleviating distortive phase transformations, the ζ-V 2 O 5 cathode shows reduced voltage hysteresis, increased Li-ion diffusivity, alleviation of stress gradients, and improved capacity retention. The findings demonstrate that alternative lithiation mechanisms can be accessed in metastable compounds by dint of their reconfigured atomic connectivity and can unlock substantially improved electrochemical performance not accessible in the thermodynamically stable phase. 

The operation of a Li-ion battery involves a concerted sequence of mass and charge transport processes, which are underpinned by alternating dilation/contraction of the active electrode materials. Several Li-ion battery failure mechanisms can be directly traced to lattice-mismatch strain arising from local compositional heterogeneities. The mechanisms of chemo-mechanical coupling that effect phase separation and the resulting complex evolution of internal stress fields remain inadequately understood. This work employs X-ray microscopy techniques to image the evolution of composition and stress across individual bent V 2 O 5 particles. Experimental findings show that lattice strain imposed by the deformation of an individual cathode particle profoundly modifies phase separation patterns, yielding striated Li-rich domains ensconced within a Li-poor matrix. Particle-level inhomogeneities compound across scales resulting in fracture and capacity fade. Coupled phase field modeling of the evolution of domains reveals that the observed patterns minimize the energetic costs incurred by the geometrically imposed strain gradients during lithiation of the material and illustrate that phase separation motifs depend sensitively on the particle geometry, dimensions, interfacial energetics, and lattice incommensurability. Sharp differences in phase separation patterns are observed between lithiation and delithiation. This work demonstrates the promise of strain-engineering and particle geometry to deterministically control phase separation motifs such as to minimize accumulated stresses and mitigate important degradation mechanisms. 

Defects are essential to engineering the properties of functional materials ranging from semiconductors and superconductors to ferroics. Whereas point defects have been widely exploited, dislocations are commonly viewed as problematic for functional materials and not as a microstructural tool. We developed a method for mechanically imprinting dislocation networks that favorably skew the domain structure in bulk ferroelectrics and thereby tame the large switching polarization and make it available for functional harvesting. The resulting microstructure yields a strong mechanical restoring force to revert electric field–induced domain wall displacement on the macroscopic level and high pinning force on the local level. This induces a giant increase of the dielectric and electromechanical response at intermediate electric fields in barium titanate [electric field–dependent permittivity (ε₃₃) ≈ 5800 and large-signal piezoelectric coefficient (d₃₃*) ≈ 1890 picometers/volt]. Dislocation-based anisotropy delivers a different suite of tools with which to tailor functional materials.