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At least 505 records · Page 28

Enhancing nanoscale charged colloid crystallization near a metastable liquid binodal

Achieving predictive control over crystallization using non-classical nucleation while avoiding kinetic traps would be a step towards designing materials with new functionalities. We address these challenges by inducing the bottom-up assembly of nanocrystals into ordered arrays, or superlattices. Using electrostatics—rather than density—to tune the interactions between particles, we watch self-assembly proceed through a metastable liquid phase. Here, we systematically investigate the phase behaviour as a function of quench conditions in situ and in real time using small-angle X-ray scattering. By fitting to colloid, liquid and superlattice models, we extract the time evolution of each phase and the system phase diagram, which we find to be consistent with short-range attractive interactions. Using the predictive power of the phase diagram, we establish control of the self-assembly rate over three orders of magnitude, and we identify one- and two-step self-assembly regimes, with only the latter implicating the metastable liquid as an intermediate. The presence of the metastable liquid increases the superlattice formation rate relative to the equivalent one-step pathway, and the superlattice order increases with the rate, revealing a generalizable kinetic strategy for promoting and enhancing ordered assembly.

Tanner, Christian P. N. [University of California,↗

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coherence-Induced Deep Thermalization Transition in Random Permutation Quantum Dynamics

We report a phase transition in the projected ensemble—the collection of postmeasurement wave functions of a local subsystem obtained by measuring its complement. The transition emerges in systems undergoing random permutation dynamics, a type of quantum time evolution wherein computational basis states are shuffled without creating superpositions. It separates a phase exhibiting deep thermalization, where the projected ensemble is distributed over Hilbert space in a maximally entropic fashion (Haar random), from a phase where it is minimally entropic (“classical bit-string ensemble”). Crucially, this deep thermalization transition is invisible to the subsystem’s density matrix, which always exhibits thermalization to infinite temperature across the phase diagram. Through a combination of analytical arguments and numerical simulations, we show that the transition is tuned by the total amount of injected by the input state and the measurement basis, and is exhibited robustly across different microscopic models. Our findings represent a novel form of ergodicity-breaking universality in quantum many-body dynamics, characterized not by a failure of regular thermalization, but rather by a failure of deep thermalization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Inhomogeneous magnetic ordered state and evolution of magnetic fluctuations in Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 revealed by 31 P NMR

SrCo 2 ⁢P 2 with a tetragonal structure is known to be a Stoner-enhanced Pauli paramagnetic metal being nearly ferromagnetic. Recently J. Schmidt et al. [Phys. Rev. B 108, 174415 (2023)] reported that a ferromagnetic ordered state is actually induced by a small Ni substitution for Co of x = 0.02 in Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 where an antiferromagnetic ordered phase also appears by further Ni substitution with x = 0.06–0.35. Here, in this work, using nuclear magnetic resonance (NMR) measurements on 31 P nuclei, we have investigated how the magnetic properties change by the Ni substitution in Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 from a microscopic point of view, especially focusing on the evolution of magnetic fluctuations with the Ni substitution and the characterization of the magnetically ordered states. The temperature dependencies of the 31 P spin-lattice relaxation rate divided by temperature (1/T 1 ⁢T) and Knight shift (K) for SrCo 2 ⁢P 2 are reasonably explained by a model where a double-peak structure for the density of states near the Fermi energy is assumed. Based on a Korringa ratio analysis using the T 1 and K data, ferromagnetic spin fluctuations are found to dominate in the ferromagnetic Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 as well as the antiferromagnets where no clear antiferromagnetic fluctuations are observed. We also found the distribution of the ordered Co moments in the magnetically ordered states from the analysis of the 31 P-NMR spectra exhibiting a characteristic rectangular-like shape.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Ab Initio Molecular Dynamics Insights into Stress Corrosion Cracking and Dissolution of Metal Oxides

Oxide phases such as α-Fe2O3 (hematite) and α-Al2O3 (corundum) are highly insoluble in water; however, subcritical crack growth has been observed in humidity nonetheless. Chemically induced bond breaking at the crack tip appears unlikely due to sterically hindered molecular transport. The molecular mechanics of a crack in corundum with a reactive force field reveal minimal lattice trapping, leading to bond breaking before sufficient space opens for water transport. To address this, we model a pre-built blunt crack with space for H2O molecule adsorption at the tip and show that it reduces fracture toughness by lowering the critical J-integral. Then, we explore stress-enhanced dissolution to understand the mechanism of crack tip blunting in the oxide/water system. Density functional theory combined with metadynamics was employed to describe atomic dissolution from flat hematite and corundum surfaces in pure water. Strain accelerates dissolution, stabilizing intermediate states with broken bonds before full atom detachment, while the free energy profile of unstrained surfaces is almost monotonic. The atomistic calculations provided input for a kinetic model, predicting the shape evolution of a blunt crack tip, which displays three distinct regimes: (i) dissolution primarily away from the tip, (ii) enhanced blunting near but not at the apex, and (iii) sharpening near the apex. The transition between regimes occurs at a low strain, highlighting the critical role of water in the subcritical crack growth of oxide scales, with dissolution as the fundamental microscopic mechanism behind this process.

Chemistry↗

Ultra-stable trimetallic phosphide heterostructure with regulated electronic structure for overall water splitting at high current densities

Developing ultra-stable electrocatalysts for highly efficient overall water splitting at high current density (HCD) is critical for renewable hydrogen/oxygen production in the industry. However, the most active electrocatalysts for large current-driven water splitting are seriously handicapped by insufficient electrical contact kinetics due to the intensive bubble overflow. Herein, we demonstrate the ultra-stable trimetallic phosphides of NiFeP/NiCoP catalysts on a hydrophilic Ni foam skeleton via a corrosion-hydrothermal-phosphating strategy. The optimized NiFeP/NiCoP catalyst stabilizes for 600 h at -1 A cm -2 for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline solution, and it only needs low overpotentials of 237 and 314 mV to drive HER and OER at 1 A cm -2 , respectively. As expected, the optimized NiFeP/NiCoP electrode maintains 1000 h at 0.5 A cm -2 for water splitting, ranking among the top performers among reported catalysts. Such excellent performance could be attributed to the fast electron transfer for electrochemical reactions, the electron-deficient Fe/Ni sites contribute to forming robust metal oxyhydroxide during OER, and electron-rich Co sites facilitate H adsorption during HER. In conclusion, the findings present a highly promising candidate for ultra-stable non-noble metal electrocatalysts, offering a viable option for hydrogen/oxygen supply for fuel cells and metal-air batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Field-Coupled Water Splitting with Metal-Free Donor–Acceptor Covalent Organic-Framework Junctions

Advancing metal-free electrocatalysts for hydrogen and oxygen evolution reactions (HER/OER) across acidic and alkaline media requires coordinated control of intermediate binding thermodynamics, interfacial charge delivery, and near-electrode transport dynamics. Here, we design amide-linked benzene–triazine covalent organic frameworks (BTA/TzTA-Hz COFs) and integrate them with carbon nanotubes (CNTs) to form COF–CNT junctions that establish a built-in interfacial electric field. Density functional theory (DFT) and electrostatic potential maps indicate complementary active motifs, with benzene-proximal fragments associated with HER and triazine-proximal motifs associated with OER. CNT integration shifts the contact-potential difference by ≈0.20 V, while operando electrochemical impedance spectroscopy suggests partially separable high-frequency junction-charging and lower-frequency Faradaic/transport responses. A 300 mT static magnetic field lowers the HER and OER overpotentials by tens of millivolts. Under anodic bias, the effective interfacial charging capacitance increases, and Mott–Schottky analysis shows an apparent ∼0.15 V flat-band shift with an essentially unchanged slope. Together, these observations are consistent with field-perturbed interfacial charging and altered bias partitioning. Field-dependent impedance and bubble imaging are consistent with magnetohydrodynamic convection that promotes bubble detachment and near-electrode mass transport for both half-reactions, and they reveal an OER-specific high-frequency perturbation under anodic bias. Under field, the heterostructure reaches an OER onset overpotential of ∼261 mV and requires an overpotential of 366 mV at 10 mA cm –2 in alkaline electrolyte. These results illustrate how reticular-framework chemistry, junction engineering, and both built-in and applied fields can program reactivity through interfacial electrostatics and near-electrode transport in organic-framework electrocatalysts.

Garcia-Enriquez, Lissette [Univ. of Texas at El Pa↗

Evolved Gas Analysis–Mass Spectrometry Exposes Polymer Network Structures

Polymer network structures in epoxy thermosets play an important role in the final thermoset material properties. However, analytical characterization of these network structures is difficult due to their amorphous nature. In this work, the application of evolved gas analysis–mass spectrometry (EGA-MS) to characterize the polymer network structures of bisphenol A (BPA)-based thermosets is demonstrated. Analytical characterization of the polymer network structures is accomplished by monitoring the Product-Specific Kinetics (PSK) of BPA monomer formation during thermal degradation investigations. We relate observed differences in the activation energy (E a ) of BPA monomer formation to the local packing environment around the BPA monomer units within the polymer network. Variations in the local environment related to the polymer networks manifest qualitatively as broadening in the thermal profile of the BPA monomer evolution and quantitatively as changes in the activation energy (E a ). Three BPA thermoset formulations were investigated; two amine-cured thermoset with 4,4′-diaminodiphenylmethane (DDM) or poly(propylene glycol) bis(2-amino-propyl ether) (PPG400) and a homopolymerized thermoset via curing with Epikure 3253 catalyst (3253). Results revealed that the 3253 thermoset contained two distinct packing densities in the polymer network, while DDM and PPG400 thermosets had uniform distributions of packing densities. Results from the DDM thermoset revealed a gradually decreasing E a , while the apparent E a of PPG400 was consistent over the entire degradation. Furthermore, these differences in E a were concluded to stem from the flexibility of the corresponding polymer networks and the ability of the network components to rearrange and occupy formed voids. Due to the minimal sample required for analysis (100–200 μg), this EGA-MS technique has great potential for postproduction evaluation of composite parts to identify changes in the polymer networks from use and aging, which could signal compromised performance.

Degradation↗

Automation of Nanoparticle Synthesis Processes in a Plasma Environment Using LabVIEW

This work presents an automated control system for the synthesis of nanomaterials by plasma-enhanced chemical vapor deposition (PECVD), implemented using the LabVIEW software environment. The main objective of the study is to develop an integrated hardware-software platform that enables sequential control of the key stages of the PECVD process, including vacuum chamber preparation, pressure monitoring, working gas supply, plasma ignition, power matching, cyclic nanomaterial growth, and optical monitoring of nanoparticles in the plasma environment. The use of LabVIEW made it possible to integrate actuator control, experimental parameter acquisition, and realtime process visualization within a single automated system. The automated cycle begins with evacuation of the reaction chamber to a predefined base pressure. Transition to the next stage is permitted only after the specified pressure threshold has been reached, ensuring reproducible initial conditions for each experiment. The program then controls the supply of the working gas through mass flow controllers (MFCs). In this work, two gas-flow control modes were considered: analog control using a 0-5 V voltage signal and digital communication via RS-232 interface. It was shown that the analog approach requires accurate scaling of the control voltage, since applying 5 V corresponds to full-scale opening of the controller and results in the maximum gas flow. In contrast, the RS232 interface enables the gas flow rate to be specified directly in sccm, improving the accuracy, flexibility, and convenience of gas-environment control. After pressure stabilization, LabVIEW initiates RF plasma ignition and executes the RF matching algorithm aimed at minimizing reflected power and improving the stability of the plasma process. A separate software module implements the cyclic nanomaterial growth mode, in which the plasma-on time, plasma duration, and total number of synthesis cycles are predefined. This approach makes it possible to control material accumulation on the substrate and to correlate the process parameters with the morphological characteristics of the resulting nanostructures. The final module of the system is designed for optical monitoring of the nanoparticle cloud density in dusty plasma. For this purpose, the change in the intensity of laser radiation passing through the plasma region is recorded using a photodetector and a Keithley 2401 measuring unit connected to LabVIEW via RS-232 interface. The difference between the initial and modified optical signal intensity is used as a diagnostic parameter characterizing the formation and temporal evolution of nanoparticles. The developed system demonstrates that LabVIEW can be effectively applied not only for the automation of individual instruments, but also for the implementation of a complete digital control cycle for PECVD-based nanomaterial synthesis.

PECVD↗

Atomate2: modular workflows for materials science

High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.

97 MATHEMATICS AND COMPUTING↗

Two-Dimensional Tantalum Carbo-Selenide for Hydrogen Evolution

Herein, we report the synthesis of two-dimensional Ta 2 Se 2 C (2D-Ta 2 Se 2 C) nanosheets using electrochemical lithiation in multilayer Ta 2 Se 2 C followed by sonication in deionized water. Multilayer Ta 2 Se 2 C was obtained via solid-state synthesis of Fe x Ta 2 Se 2 C followed by chemical etching of Fe. 2D-Ta 2 Se 2 C exhibited promising electrocatalytic activity for the hydrogen evolution reaction from water compared to multilayer Ta 2 Se 2 C and 2D-TaSe 2 . 2D-Ta 2 Se 2 C showed an overpotential at 10 mA·cm -2 (η 10 ) of 264 mV, a Tafel slope of 91 mV·dec -1 , and an electrochemically active surface area of 17.61 m ECSA 2 ·g catalyst -1 . The high performance could be attributed to the large surface area of single sheets which hence maximizes the number of exposed catalytic sites and increased density of vacancies, observed with transmission electron microscopy, during synthesis and processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermal Regulation of CO 2 Activation Pathways via Interfacial Water Restructuring Enables Ampere-Level, Near-Unity CO Electrosynthesis

Electrochemical reduction of CO 2 to CO is a key step in carbon utilization technologies, yet maintaining high CO selectivity under elevated temperatures relevant to industrial membrane-electrode-assembly (MEA) electrolyzers remains challenging due to the competing hydrogen evolution reaction (HER). Additionally, the temperature dependence of CO selectivity on Cu-based catalysts has remained largely unexplored. Here, we demonstrate that incorporating atomic In or Sn into Cu fundamentally reshapes the selectivity of Cu catalysts at elevated temperatures. Dilute alloy catalysts, In 1 Cu and Sn 1 Cu, achieve >95% FE of CO over a broad current-density window (0.1−1.1 A cm −2 ) at 60 °C in MEA electrolyzers, far exceeding their performance at ambient temperature. In situ attenuated total reflection surface-enhanced infrared absorption spectroscopy suggests that elevating temperature depletes interfacial water activity, which favors a shift in CO 2 activation from a proton-coupled *COOH pathway toward an electron-driven *COO − -associated pathway, while also suppressing HER and CO hydrogenation. In contrast, benchmark CO-selective catalysts such as Ag exhibit minimal temperature-induced changes in CO production at 20−60 °C. These findings identify temperature as an unavoidable yet previously underutilized operating parameter in MEA electrolyzers for high-rate, selective CO production on Cubased catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Illuminating the mechanistic impacts of an Fe-quaterpyridine functionalized crystalline poly(triazine imide) semiconductor for photocatalytic CO 2 reduction

The strategy of incorporating earth-abundant catalytic centers into light-absorbing architectures is desirable from the viewpoint of low cost, low toxicity, and versatility for activating small molecules to produce solar-based fuels. Herein, we show that an Fe-quaterpyridine molecular catalyst can be anchored to a light-absorbing, crystalline, carbon nitride (PTI), to yield a molecular-catalyst/material hybrid, Fe-qpy-PTI, capable of facilitating CO 2 reduction to CO selectively (up to ∼97–98%) in aqueous solution under low-intensity light irradiation. This hybrid material leverages the ability of the Fe-qpy catalyst to bind CO 2 upon a one-electron reduction, as achieved by transfer of excited electrons from the carbon-nitride semiconductor. At a low incident power density of only 50 mW cm −2 , the catalytic activity of the hybrid material was measured across a range of catalyst loadings from 0.1–3.8 wt%, yielding CO rates of up to 596 μmol g −1 h −1 for a 3.8 wt% loading during a 3 h experiment. Over the course of 8 h, the hybrid material attained a CO evolution rate of 608 μmol g −1 h −1 and 305 turnovers for a TOF of ∼38 h −1 and an apparent quantum yield of 2.6%. Higher light intensities provided an initial increase in activity but negatively impacted photocatalytic rates with time, with an AQY of 0.6% at 150 mW cm −2 and 0.4% at 250 mW cm −2 . Transient absorption spectroscopy results showed electron survival probabilities consistent with the trends in observed product rates. Computational modeling was also used to evaluate and understand the mechanistic pathway of the high product selectivity for CO versus H 2 . These results thus help unveil key factors for leveraging the mechanistic understanding of molecular catalysts for CO 2 reduction for pairing with light absorbing semiconductors and establishing optimal conditions to attain maximal rates in aqueous solution.

McGuigan, Scott [Baylor University, Waco, TX (Unit↗

Single-shot ultrafast dynamics of nanosecond pulsed plasmas: Transition from ps–ns nonequilibrium to near-full ionization

The ultrafast multi-stage evolution of state-defining properties in atmospheric-pressure nanosecond pulsed plasmas is quantified using single-discharge, jitter-free, continuous streak-sweep spectroscopy of N 2 (C → B) molecular and N + /O + ionic species with a single-shot time resolution as short as ∼160 ps. An early period of extreme nonequilibrium is observed with vibrational temperatures [T V (C)] dropping from ∼8000 K at <200 ps after plasma breakdown to <4000 K within ∼1 ns, with near-ambient rotational temperatures [T R (C)] ∼ 300 K due to limited collisional energy transfer. This early-time T V (C) trend is representative of a direct and unquenched look into the high-energy tail of the electron energy distribution function; thus, it tracks real-time changes in the mean electron energy via the N2(C) emission signatures. This is followed by the rapid onset of N + /O + ionic emission after a distinct time delay of ∼14.9 ns due to multistep chemical kinetics. The ionic emission enables determination of electron densities (n e ) >2 × 10 19 cm −3 and electron temperatures (T e ) >36 000 K, indicating the transition to a nearly fully ionized regime. The ps–ns temporal dynamics are also compared between air and N 2 plasmas to assess the influence of collisional partners, as well as across the anode, cathode, and central gap regions to identify spatial variations in plasma behavior. Finally, this work demonstrates versatile continuously probing approach capable of spectro-temporal and spatially resolved single-shot measurements of key state variables in the ps–ns evolution of atmospheric-pressure nanosecond pulsed plasmas.

Electric discharges↗

Bidirectional Ultrafast Control of Charge Density Waves via Phase Competition

The intricate competition between coexisting charge density waves (CDWs) can lead to rich phenomena, offering unique opportunities for phase manipulation through electromagnetic stimuli. Here, leveraging time-resolved x-ray diffraction, we demonstrate ultrafast control of a CDW in EuTe 4 upon optical excitation. At low excitation intensities, the amplitude of one of the coexisting CDW orders increases at the expense of the competing CDW, whereas at high intensities, it exhibits a nonmonotonic temporal evolution characterized by both enhancement and reduction. This transient bidirectional controllability, tunable by adjusting photoexcitation intensity, arises from the interplay between optical quenching and phase-competition-induced enhancement. Our findings, supported by phenomenological time-dependent Ginzburg-Landau theory simulations, not only clarify the relationship between the two CDWs in EuTe 4 , but also highlight the versatility of optical control over order parameters enabled by phase competition.

charge density waves↗

Iridium Nanocrystals Enriched with Defects and Atomic Steps to Enhance Oxygen Evolution Reaction Performance

The presence of defects can significantly improve catalytic activity and stability, as they influence the binding of the reactants, intermediates, and products to the catalyst. Controlling defects in the structures of nanocrystal catalysts is synthetically challenging. In this study, we demonstrate the ability to control the growth of Ir nanocrystals, enabling the tuning of both structural and surface defects. The Ir nanocrystals have unique structures that range from single crystals of a few nanometers to twinned nanoparticles and multiply twinned crystallites with a high density of atomic steps. Further, this approach of defect engineering enables us to understand their roles in enhancing the performance of the OER and producing an Ir catalyst with both high activity and stability. Our results show the importance of the concept of using synthetic control of structural and surface defects in metal nanoparticles as a strategy to improve catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonlinear evolution, propagation, electron-trapping, and damping effects of ion-acoustic solitons using fully kinetic PIC simulations

We investigate ion acoustic solitary waves (solitons) of varying amplitudes in a one-dimensional plasma using fully kinetic particle-in-cell simulations. The initial soliton conditions are based on the Korteweg–de Vries (KdV) equation, treating ions as a cold species and electrons with finite temperature. Our findings reveal that KdV solitons evolve nonlinearly to a saturated state at higher amplitude, deviating from KdV predictions for ion density and electric potential, and from the Boltzmann relation for electron density. At this saturated state, the KdV model cannot accurately describe the soliton behavior. For small amplitudes, Sagdeev's model describes the saturated state, but not the soliton width; for larger amplitudes, it models the width accurately, but not the amplitude. These discrepancies arise from assuming a Boltzmann relation for electron density, while electron trapping creates non-Boltzmann densities—a deviation that increases with soliton amplitude. Additionally, we observe that the soliton amplitude oscillates roughly at the electron bounce frequency. The soliton is better described by Schamel's electron density formulation and a modified KdV equation incorporating electron trapping. The soliton velocity matches best with predictions from Sagdeev's and Schamel's models. Moreover, the soliton speed–amplitude relationship differs from existing theoretical predictions. Finally, we find minimal ion and electron Landau damping effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Defect Chemistry in High‐Voltage Cathode Materials for Lithium‐Ion Batteries

High-voltage cathodes (HVCs) have emerged as a paramount role for the next-generation high-energy-density lithium-ion batteries (LIBs). However, the pursuit of HVCs comes with inherent challenges related to defective structures, which significantly impact the electrochemical performance of LIBs. The current obstacle lies in the lack of a comprehensive understanding of defects and their precise effects. This perspective aims to provide insights into defect chemistry for governing HVCs. The classifications, formation mechanisms, and evolution of defects are outlined to explore the intricate relationship between defects and electrochemical behavior. The pressing need for cutting-edge characterization techniques that comprehensively investigate defects across various temporal and spatial scales is emphasized. Building on these fundamental understandings, engineering strategies such as composition tailoring, morphology design, interface modification, and structural control to mitigate or utilize defects are thoroughly discussed for enhanced HVCs performance. Furthermore, these insights are expected to provide vital guidelines for developing high-performance HVCs for next-generation high-energy lithium-ion batteries.

cross-scale characterization↗