Beyond Constant Current: Origin of Pulse-Induced Activation in Phase-Transforming Battery Electrodes.

Mechanistic understanding of phase transformation dynamics during battery charging and discharging is crucial toward rationally improving intercalation electrodes. Most studies focus on constant-current conditions. However, in real battery operation, such as in electric vehicles during discharge, the current is rarely constant. In this work we study current pulsing in LiXFePO4 (LFP), a model and technologically important phase-transforming electrode. A current-pulse activation effect has been observed in LFP, which decreases the overpotential by up to ∼70% after a short, high-rate pulse. This effect persists for hours or even days. Using scanning transmission X-ray microscopy and operando X-ray diffraction, we link this long-lived activation effect to a pulse-induced electrode homogenization on both the intra- and interparticle length scales, i.e., within and between particles. Many-particle phase-field simulations explain how such pulse-induced homogeneity contributes to the decreased electrode overpotential. Specifically, we correlate the extent and duration of this activation to lithium surface diffusivity and the magnitude of the current pulse. This work directly links the transient electrode-level electrochemistry to the underlying phase transformation and explains the critical effect of current pulses on phase separation, with significant implication on both battery round-trip efficiency and cycle life. More broadly, the mechanisms revealed here likely extend to other phase-separating electrodes, such as graphite.

Multiscale Analysis of Electrocatalytic Particle Activities: Linking Nanoscale Measurements and Ensemble Behavior.

Nanostructured electrocatalysts exhibit variations in electrochemical properties across different length scales, and the intrinsic catalytic characteristics measured at the nanoscale often differ from those at the macro-level due to complexity in electrode structure and/or composition. This aspect of electrocatalysis is addressed herein, where the oxygen evolution reaction (OER) activity of ß-Co(OH)2 platelet particles of well-defined structure is investigated in alkaline media using multiscale scanning electrochemical cell microscopy (SECCM). Microscale SECCM probes of ∼50 µm diameter provide voltammograms from small particle ensembles (ca. 40-250 particles) and reveal increasing dispersion in the OER rates for samples of the same size as the particle population within the sample decreases. This suggests the underlying significance of heterogeneous activity at the single-particle level that is confirmed through single-particle measurements with SECCM probes of ∼5 µm diameter. These measurements of multiple individual particles directly reveal significant variability in the OER activity at the single-particle level that do not simply correlate with the particle size, basal plane roughness, or exposed edge plane area. In combination, these measurements demarcate a transition from an "individual particle" to an "ensemble average" response at a population size of ca. 130 particles, above which the OER current density closely reflects that measured in bulk at conventional macroscopic particle-modified electrodes. Nanoscale SECCM probes (ca. 120 and 440 nm in diameter) enable measurements at the subparticle level, revealing that there is selective OER activity at the edges of particles and highlighting the importance of the three-phase boundary where the catalyst, electrolyte, and supporting carbon electrode meet, for efficient electrocatalysis. Furthermore, subparticle measurements unveil heterogeneity in the OER activity among particles that appear superficially similar, attributable to differences in defect density within the individual particles, as well as to variations in electrical and physical contact with the support material. Overall this study provides a roadmap for the multiscale analysis of nanostructured electrocatalysts, directly demonstrating the importance of multilength scale factors, including particle structure, particle-support interaction, presence of defects, etc., in governing the electrochemical activities of ß-Co(OH)2 platelet particles and ultimately guiding the rational design and optimization of these materials for alkaline water electrolysis.

Synergistic effects of mixing and strain in high entropy spinel oxides for oxygen evolution reaction.

Developing stable and efficient electrocatalysts is vital for boosting oxygen evolution reaction (OER) rates in sustainable hydrogen production. High-entropy oxides (HEOs) consist of five or more metal cations, providing opportunities to tune their catalytic properties toward high OER efficiency. This work combines theoretical and experimental studies to scrutinize the OER activity and stability for spinel-type HEOs. Density functional theory confirms that randomly mixed metal sites show thermodynamic stability, with intermediate adsorption energies displaying wider distributions due to mixing-induced equatorial strain in active metal-oxygen bonds. The rapid sol-flame method is employed to synthesize HEO, comprising five 3d-transition metal cations, which exhibits superior OER activity and durability under alkaline conditions, outperforming lower-entropy oxides, even with partial surface oxidations. The study highlights that the enhanced activity of HEO is primarily attributed to the mixing of multiple elements, leading to strain effects near the active site, as well as surface composition and coverage.

Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel.

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries1 and electrocatalysts2. Experimental characterizations of such materials by operando microscopy produce rich image datasets3-6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Large Decrease in the Melting Point of Benzoquinones via High-n Eutectic Mixing Predicted by a Regular Solution Model.

Decreasing the melting point (Tm) of a mixture is of interest in cryopreservatives, molten salts, and battery electrolytes. One general strategy to decrease Tm, exemplified by deep eutectic solvents, is to mix components with favorable (negative) enthalpic interactions. We demonstrate a complementary strategy to decrease Tm by mixing many components with neutral or slightly positive enthalpic interactions, using the number of components (n) to increase the entropy of mixing and decrease Tm. In theory, under certain conditions this approach could achieve an arbitrarily low Tm. Furthermore, if the components are small redox-active molecules, such as the benzoquinones studied here, this approach could lead to high energy density flow battery electrolytes. Finding the eutectic composition of a high-n mixture can be challenging due to the large compositional space yet is essential for ensuring the existence of a purely liquid phase. We reformulate and apply fundamental thermodynamic equations to describe high-n eutectic mixtures of small redox-active molecules (benzoquinones and hydroquinones). We illustrate a novel application of this theory by tuning the entropy of melting, rather than the enthalpy, in systems highly relevant to energy storage. We demonstrate with differential scanning calorimetry measurements that 1,4-benzoquinone derivatives exhibit eutectic mixing that decreases their Tm, despite slightly positive enthalpies of mixing (0-5 kJ/mol). By rigorously investigating all 21 binary mixtures of a set of seven 1,4-benzoquinone derivatives with alkyl substituents (Tm's between 44 and 120 °C), we find that the eutectic melting point of a mixture of all seven achieves a large decrease in Tm to -6 °C. We further determine that the regular solution model shows improvement over an ideal solution model in predicting the eutectic properties for this newly investigated type of mixture composed of many small redox-active organic molecules.

Selectivity of Electrochemical Ion Insertion into Manganese Dioxide Polymorphs.

The ion insertion redox chemistry of manganese dioxide has diverse applications in energy storage, catalysis, and chemical separations. Unique properties derive from the assembly of Mn-O octahedra into polymorphic structures that can host protons and nonprotonic cations in interstitial sites. Despite many reports on individual ion-polymorph couples, much less is known about the selectivity of electrochemical ion insertion in MnO2. In this work, we use density functional theory to holistically compare the electrochemistry of AxMnO2 (where A = H+, Li+, Na+, K+, Mg2+, Ca2+, Zn2+, Al3+) in aqueous and nonaqueous electrolytes. We develop an efficient computational scheme demonstrating that Hubbard-U correction has a greater impact on calculating accurate redox energetics than choice of exchange-correlation functional. Using PBE+U, we find that for nonprotonic cations, ion selectivity depends on the oxygen coordination environments inside a polymorph. When H+ is present, however, the driving force to form hydroxyl bonds is usually stronger. In aqueous electrolytes, only three ion-polymorph pairs are thermodynamically stable within water's voltage stability window (Na+ and K+ in α-MnO2, and Li+ in λ-MnO2), with all other ion insertion being metastable. We find Al3+ may insert into the δ, R, and λ polymorphs across the full 2-electron redox of MnO2 at high voltage; however, electrolytes for multivalent ions must be designed to impede the formation of insoluble precipitates and facilitate cation desolvation. We also show that small ions coinsert with water in α-MnO2 to achieve greater coordination by oxygen, while solvation energies and kinetic effects dictate water coinsertion in δ-MnO2. Taken together, these findings explain reports of mixed ion insertion mechanisms in aqueous electrolytes and highlight promising design strategies for safe, high energy density electrochemical energy storage, desalination batteries, and electrocatalysts.

Correlative image learning of chemo-mechanics in phase-transforming solids.

Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (for example, due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the chemo-mechanical expansion in solids. Here we developed a generalizable, physically constrained image-learning framework to algorithmically learn the chemo-mechanical constitutive law at the nanoscale from correlative four-dimensional scanning transmission electron microscopy and X-ray spectro-ptychography images. We demonstrated this approach on LiXFePO4, a technologically relevant battery positive electrode material. We uncovered the functional form of the composition-eigenstrain relation in this two-phase binary solid across the entire composition range (0 ≤ X ≤ 1), including inside the thermodynamically unstable miscibility gap. The learned relation directly validates Vegard's law of linear response at the nanoscale. Our physics-constrained data-driven approach directly visualizes the residual strain field (by removing the compositional and coherency strain), which is otherwise impossible to quantify. Heterogeneities in the residual strain arise from misfit dislocations and were independently verified by X-ray diffraction line profile analysis. Our work provides the means to simultaneously quantify chemical expansion, coherency strain and dislocations in battery electrodes, which has implications on rate capabilities and lifetime. Broadly, this work also highlights the potential of integrating correlative microscopy and image learning for extracting material properties and physics.

Electro-chemo-mechanical charge carrier equilibrium at interfaces.

Electrochemical interfaces involving solids enable charge transfer, electrical transport, and mass storage in energy devices. One central concept that determines the interfacial charge carrier concentration is the space-charge field. The classical theory accounts for electrochemical equilibrium in the absence of mechanical effects; such effects have recently been found critical in many solids, such as materials for lithium-ion and solid-state batteries, perovskite solar cells, and fuel cells. Towards elucidating the interplay between charge carriers and mechanics, we establish a generalized electro-chemo-mechanical space-charge model and categorize the carriers into physically-meaningful four types, based on the signs of the charge number (i.e., polarity) and the partial molar volume (i.e., expansion coefficient). Beyond the electrostatic effects discussed in the literature, our work reveals the importance of elastic effects, as demonstrated by simulations of a composite beam bending experiment. The analysis highlights opportunities to systematically tune the interfacial electrical conductivity and the reaction kinetics of solids through mechanics. Our treatment provides a rational basis for understanding stress-driven phenomena at interfaces in a wide range of solids.

Universal phase dynamics in VO2 switches revealed by ultrafast operando diffraction.

Understanding the pathways and time scales underlying electrically driven insulator-metal transitions is crucial for uncovering the fundamental limits of device operation. Using stroboscopic electron diffraction, we perform synchronized time-resolved measurements of atomic motions and electronic transport in operating vanadium dioxide (VO2) switches. We discover an electrically triggered, isostructural state that forms transiently on microsecond time scales, which is shown by phase-field simulations to be stabilized by local heterogeneities and interfacial interactions between the equilibrium phases. This metastable phase is similar to that formed under photoexcitation within picoseconds, suggesting a universal transformation pathway. Our results establish electrical excitation as a route for uncovering nonequilibrium and metastable phases in correlated materials, opening avenues for engineering dynamical behavior in nanoelectronics.

Highly Efficient Uniaxial In-Plane Stretching of a 2D Material via Ion Insertion.

On-chip dynamic strain engineering requires efficient micro-actuators that can generate large in-plane strains. Inorganic electrochemical actuators are unique in that they are driven by low voltages (≈1 V) and produce considerable strains (≈1%). However, actuation speed and efficiency are limited by mass transport of ions. Minimizing the number of ions required to actuate is thus key to enabling useful "straintronic" devices. Here, it is shown that the electrochemical intercalation of exceptionally few lithium ions into WTe2 causes large anisotropic in-plane strain: 5% in one in-plane direction and 0.1% in the other. This efficient stretching of the 2D WTe2 layers contrasts to intercalation-induced strains in related materials which are predominantly in the out-of-plane direction. The unusual actuation of Lix WTe2 is linked to the formation of a newly discovered crystallographic phase, referred to as Td', with an exotic atomic arrangement. On-chip low-voltage (<0.2 V) control is demonstrated over the transition to the novel phase and its composition. Within the Td'-Li0.5- δ WTe2 phase, a uniaxial in-plane strain of 1.4% is achieved with a change of δ of only 0.075. This makes the in-plane chemical expansion coefficient of Td'-Li0.5-δ WTe2 far greater than of any other single-phase material, enabling fast and efficient planar electrochemical actuation.

Correlative operando microscopy of oxygen evolution electrocatalysts.

Transition metal (oxy)hydroxides are promising electrocatalysts for the oxygen evolution reaction1-3. The properties of these materials evolve dynamically and heterogeneously4 with applied voltage through ion insertion redox reactions, converting materials that are inactive under open circuit conditions into active electrocatalysts during operation5. The catalytic state is thus inherently far from equilibrium, which complicates its direct observation. Here, using a suite of correlative operando scanning probe and X-ray microscopy techniques, we establish a link between the oxygen evolution activity and the local operational chemical, physical and electronic nanoscale structure of single-crystalline ß-Co(OH)2 platelet particles. At pre-catalytic voltages, the particles swell to form an α-CoO2H1.5·0.5H2O-like structure-produced through hydroxide intercalation-in which the oxidation state of cobalt is +2.5. Upon increasing the voltage to drive oxygen evolution, interlayer water and protons de-intercalate to form contracted ß-CoOOH particles that contain Co3+ species. Although these transformations manifest heterogeneously through the bulk of the particles, the electrochemical current is primarily restricted to their edge facets. The observed Tafel behaviour is correlated with the local concentration of Co3+ at these reactive edge sites, demonstrating the link between bulk ion-insertion and surface catalytic activity.

Fictitious phase separation in Li layered oxides driven by electro-autocatalysis.

Layered oxides widely used as lithium-ion battery electrodes are designed to be cycled under conditions that avoid phase transitions. Although the desired single-phase composition ranges are well established near equilibrium, operando diffraction studies on many-particle porous electrodes have suggested phase separation during delithiation. Notably, the separation is not always observed, and never during lithiation. These anomalies have been attributed to irreversible processes during the first delithiation or reversible concentration-dependent diffusion. However, these explanations are not consistent with all experimental observations such as rate and path dependencies and particle-by-particle lithium concentration changes. Here, we show that the apparent phase separation is a dynamical artefact occurring in a many-particle system driven by autocatalytic electrochemical reactions, that is, an interfacial exchange current that increases with the extent of delithiation. We experimentally validate this population-dynamics model using the single-phase material Lix(Ni1/3Mn1/3Co1/3)O2 (0.5 < x < 1) and demonstrate generality with other transition-metal compositions. Operando diffraction and nanoscale oxidation-state mapping unambiguously prove that this fictitious phase separation is a repeatable non-equilibrium effect. We quantitatively confirm the theory with multiple-datastream-driven model extraction. More generally, our study experimentally demonstrates the control of ensemble stability by electro-autocatalysis, highlighting the importance of population dynamics in battery electrodes (even non-phase-separating ones).

Tuning electrochemically driven surface transformation in atomically flat LaNiO3 thin films for enhanced water electrolysis.

Structure-activity relationships built on descriptors of bulk and bulk-terminated surfaces are the basis for the rational design of electrocatalysts. However, electrochemically driven surface transformations complicate the identification of such descriptors. Here we demonstrate how the as-prepared surface composition of (001)-terminated LaNiO3 epitaxial thin films dictates the surface transformation and the electrocatalytic activity for the oxygen evolution reaction. Specifically, the Ni termination (in the as-prepared state) is considerably more active than the La termination, with overpotential differences of up to 150 mV. A combined electrochemical, spectroscopic and density-functional theory investigation suggests that this activity trend originates from a thermodynamically stable, disordered NiO2 surface layer that forms during the operation of Ni-terminated surfaces, which is kinetically inaccessible when starting with a La termination. Our work thus demonstrates the tunability of surface transformation pathways by modifying a single atomic layer at the surface and that active surface phases only develop for select as-synthesized surface terminations.

Coulombically-stabilized oxygen hole polarons enable fully reversible oxygen redox.

Stabilizing high-valent redox couples and exotic electronic states necessitate an understanding of the stabilization mechanism. In oxides, whether they are being considered for energy storage or computing, highly oxidized oxide-anion species rehybridize to form short covalent bonds and are related to significant local structural distortions. In intercalation oxide electrodes for batteries, while such reorganization partially stabilizes oxygen redox, it also gives rise to substantial hysteresis. In this work, we investigate oxygen redox in layered Na2-XMn3O7, a positive electrode material with ordered Mn vacancies. We prove that coulombic interactions between oxidized oxideanions and the interlayer Na vacancies can disfavor rehybridization and stabilize hole polarons on oxygen (O-) at 4.2 V vs. Na/Na+. These coulombic interactions provide thermodynamic energy saving as large as O-O covalent bonding and enable ~ 40 mV voltage hysteresis over multiple electrochemical cycles with negligible voltage fade. Our results establish a complete picture of redox energetics by highlighting the role of coulombic interactions across several atomic distances and suggest avenues to stabilize highly oxidized oxygen for applications in energy storage and beyond.

The Role of Metal Substitution in Tuning Anion Redox in Sodium Metal Layered Oxides Revealed by X-Ray Spectroscopy and Theory.

We investigate high-valent oxygen redox in the positive Na-ion electrode P2-Na0.67-x [Fe0.5 Mn0.5 ]O2 (NMF) where Fe is partially substituted with Cu (P2-Na0.67-x [Mn0.66 Fe0.20 Cu0.14 ]O2 , NMFC) or Ni (P2-Na0.67-x [Mn0.65 Fe0.20 Ni0.15 ]O2 , NMFN). From combined analysis of resonant inelastic X-ray scattering and X-ray near-edge structure with electrochemical voltage hysteresis and X-ray pair distribution function profiles, we correlate structural disorder with high-valent oxygen redox and its improvement by Ni or Cu substitution. Density of states calculations elaborate considerable anionic redox in NMF and NMFC without the widely accepted requirement of an A-O-A' local configuration in the pristine materials (where A=Na and A'=Li, Mg, vacancy, etc.). We also show that the Jahn-Teller nature of Fe4+ and the stabilization mechanism of anionic redox could determine the extent of structural disorder in the materials. These findings shed light on the design principles in TM and anion redox for positive electrodes to improve the performance of Na-ion batteries.

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

Evolution of the Solid-Electrolyte Interphase on Carbonaceous Anodes Visualized by Atomic-Resolution Cryogenic Electron Microscopy.

The stability of modern lithium-ion batteries depends critically on an effective solid-electrolyte interphase (SEI), a passivation layer that forms on the carbonaceous negative electrode as a result of electrolyte reduction. However, a nanoscopic understanding of how the SEI evolves with battery aging remains limited due to the difficulty in characterizing the structural and chemical properties of this sensitive interphase. In this work, we image the SEI on carbon black negative electrodes using cryogenic transmission electron microscopy (cryo-TEM) and track its evolution during cycling. We find that a thin, primarily amorphous SEI nucleates on the first cycle, which further evolves into one of two distinct SEI morphologies upon further cycling: (1) a compact SEI, with a high concentration of inorganic components that effectively passivates the negative electrode; and (2) an extended SEI spanning hundreds of nanometers. This extended SEI grows on particles that lack a compact SEI and consists primarily of alkyl carbonates. The diversity in observed SEI morphologies suggests that SEI growth is a highly heterogeneous process. The simultaneous emergence of these distinct SEI morphologies highlights the necessity of effective passivation by the SEI, as large-scale extended SEI growths negatively impact lithium-ion transport, contribute to capacity loss, and may accelerate battery failure.