Soft electronic devices require durability to endure their inherent exposure to diverse mechanical deformations, including scratches, punctures, and repeated bending. Without intrinsic damage recovery mechanisms, such deformations inevitably compromise mechanical integrity and limit device lifetime. To address this issue, the strategic incorporation of reversible dynamic bonds enables autonomous self-healing while simultaneously achieving high mechanical toughness through energy dissipation during bond rupture. To this end, optimizing the glass transition temperature and bond exchange kinetics is essential to ensure sufficient chain mobility for rapid interfacial diffusion and autonomous mechanical recovery. Building on the reversible bond nature, this review presents emerging self-healable and tough soft electronics applications in three major areas: (1) Multimodal electronic skins capable of comprehensive physiological signal sensing; (2) modularly reconfigurable systems with adhesive-free interlayer bonding that enable user-on-demand device assembly; (3) optoelectronic devices that seamlessly integrate light-emitting and pressure-sensing capabilities. These applications demonstrate that dynamic bond engineering enables elastomeric devices to simultaneously achieve mechanical robustness, functional adaptability, and autonomous self-healing. Such advancements position them as durable platforms with extended operational lifetimes, paving the way for next-generation wearable and implantable bioelectronics in real-world applications.

Statistical mechanics of far-from-equilibrium systems requires trajectory-based ensembles rather than static configurations. Biasing fields conjugate to dynamical activity (s-field) and time-integrated trajectory energy (g-field) provide powerful tools for probing rare dynamical states. While s-ensemble studies have demonstrated first-order dynamical phase transitions in glass-forming models, it remains unclear whether energy-only biasing can induce transitions in kinetic observables to which it is not directly coupled. Here, we investigate this question in the Kob–Andersen binary Lennard–Jones model by constructing the two-dimensional (T, g) phase diagram using transition path sampling. We identify a first-order dynamical phase transition line separating active and inactive trajectory phases, confirmed by diverging dynamical susceptibilities and bimodal order parameter distributions. Binder cumulant analysis, enabled by Gaussian process regression and large-deviation relations, locates the upper critical point (Tuc, guc) ≃ (0.675, 1.9 × 10−3). We further demonstrate that g-ensemble glasses are structurally indistinguishable from conventionally quenched glasses, while intermediate scattering functions confirm that the active–inactive transition is purely dynamical in nature. Spatial analysis further reveals that mobile particles form a system-spanning cluster in the active phase but remain fragmented in the inactive phase, consistent with the dynamical facilitation picture. These results demonstrate that energy-landscape biasing alone is sufficient to drive first-order dynamical phase transitions in an atomistic glass-forming model, establishing the g-ensemble as a controlled framework that connects the thermodynamic potential energy landscape with dynamical arrest phenomena central to kinetic theories of the glass transition.

Precise modeling of the energetic landscape is a prerequisite for predicting the charge transport properties of organic light-emitting diodes (OLEDs). However, a significant gap remains between highly accurate but computationally prohibitive self-consistent field (SCF) calculations and efficient but often oversimplified models. In this work, we propose an accurate and effective electrostatic framework with high computational efficiency that encompasses these complex polarization effects through an anisotropically screened dielectric function augmented by a position-dependent background potential. Optimized for the archetypal host material 4,4′-Bis(N-carbazolyl)-1,1′-biphenyl (CBP), our model accurately reproduces the microscopic details, including the polarization-induced stabilization and the surface-reduced energetic disorder, while maintaining high transferability across independent morphological realizations and film thicknesses down to D ≈ 4 nm. Kinetic Monte Carlo (KMC) simulations further confirm that the model faithfully replicates the reference mean squared displacement (MSD) and current–voltage (JV) characteristics, whereas simple image charge models significantly underestimate the current density by failing to describe the downhill gradient at the interface. This framework offers a practical pathway for generating realistic energy distributions for large-scale device simulations, effectively bridging the tradeoff between physical accuracy and computational efficiency.

lycerol, a low-cost and abundant byproduct of biodiesel production, has attracted attention as a feedstock for conversion into value-added chemicals. To maximize the economic value of products, maintaining three carbons (C3) as the dominant product is important yet difficult to achieve at high potentials due to the favorable C–C bond scission. We demonstrate that an atomically dispersed Pt catalyst anchored on defect-rich ceria-carbon selectively controls the glycerol electrooxidation reaction (GEOR), favoring C3 products. The isolated Pt sites favored single-carbon adsorption, preventing multi-carbon binding and subsequent cleavage up until high potential of 1.2 VRHE. The catalyst maintained nearly 70% of C3 selectivity across various potentials with high glycerate productivity and selectivity. In contrast, catalysts with Pt nanoparticles rapidly shifted towards C2 and C1 products, especially glycolate and formate as potential increases. Moreover, Pt single atoms on the catalyst maintained high glycerate productivity without much Pt agglomeration under 48 h operation. Beyond batch operation, the Pt single atom catalyst was validated in a continuous flow-cell reactor. Glycerate remained as the major product, reaching a selectivity of 51.6% as potential increases and exhibited a productivity of 37.0 mmol L−1 mgPt−1 h−1 at 1.2 VRHE. This work highlights atomic dispersion on defect-engineered supports as a powerful strategy to control electrocatalytic pathways in the GEOR via suppressing C–C cleavage.

The electrochemical CO2 reduction reaction (CO2RR) relies heavily on the surrounding microenvironment to promote formation of desirable multicarbon (C2+) products. However, microenvironment control to achieve high C2+ yields at industrially relevant current densities remains a crucial challenge. We report that chitosan, cellulose and chitin biopolymer coatings on CO2RR electrocatalysts enhance the microenvironment by increasing local CO2/CO concentration, reducing local water activity and providing suitable ion conductivity and local pH. This facile approach achieves C2+ Faradaic efficiencies of 90 +/- 1.7% at 1.6 A cm-2 and C2+ Faradaic efficiency = 83 +/- 3.2% at 2.2 A cm-2 with a formation rate of 5,926 mu mol h-1 cm-2. Importantly, within the cathode, these ion-conductive hydrophilic biopolymers can fully substitute traditional hydrophobic ionomers/binders, such as Nafion, challenging previous assumptions about the non-viability of hydrophilic materials for selective CO2RR due to excess interfacial H2O. These findings unveil key insights into microenvironment design to enhance C-C coupling through a simple method.

Supramolecular assembly of biological materials into fibrous structures often provides exceptional functionalities. In the case of synthetic polymers, however, it is challenging to construct fibrous structures in the condensed matrix, primarily due to limited ordering and chain mobility for supramolecular assembly. We present a design strategy of using hydrogen bonding units to facilitate supramolecular assembly in self-healing PDMS-based polymer films, exploring how subtle changes in alkyl spacers affect dynamic mechanical responses. We observed that increasing structural flexibility in hydrogen bonding units enables long-range supramolecular assemblies, leading to the formation of fibrous structures. These structures endow the material with improved mechanical stability under tensile, compressive, and frictional stresses. Notably, the supramolecular assembly responds to molecular-level changes, allowing selective self-healing between corresponding polymers. This molecular-level recognition gave self-alignment in multilayer laminates, enabling autonomous healing and alignment of damaged and misaligned layers. Our findings provide new insights for designing mechanically robust, self-healable, and multi-functional polymers.

The electrocatalytic nitrate reduction reaction (NO3RR) provides a sustainable pathway to convert excess nitrate into ammonia, yet realizing high selectivity requires a fundamental understanding of dynamic structural changes occuring at active sites during reactions. Here, we investigate how in situ Cu clustering dynamically activates dual catalytic sites in Fe–Cu bimetallic single-atom catalysts (FeCu–N–C) during NO3RR, through combined density functional theory calculations and operando spectroscopy. Under reductive potentials, atomically dispersed Cu spontaneously aggregates into nanoclusters that efficiently activate NO3–. Concurrently, Cu clustering induces pronounced structural strain and electronic distortion in adjacent Fe–Nx moieties, triggering a spin-state transition in the Fe active site from low-spin to high-spin configuration. This spin modulation dramatically enhances the activity for subsequent NO2– conversion to NH3. The synergistic coupling between Cu clusters and spin-modulated Fe establishes a highly effective tandem pathway, yielding superior NO3RR activity and NH3 selectivity, compared to Cu–N–C and Fe–N–C counterparts. These findings provide new insights into the rational design of advanced multicomponent electrocatalysts with dynamically tunable active site properties.

Incorporating a secondary metal into a host material is an effective strategy to modulate its electronic structure and enhance electrocatalytic performance. Low-concentration doping, which minimizes perturbations to the host lattice and surface, enables precise material engineering while reducing synthesis complexity and costs. However, achieving stable low-concentration doping is challenging due to potential dopant leaching under dynamic electrochemical conditions. Here, we demonstrate that dilute incorporation of p-block elements (<= 2.50 wt %) into Cu2O significantly enhances its CO2-to-CO conversion efficiency and operational stability. The lowest effective doping concentrations were 0.37 wt % for tin and 2.03 wt % for indium, both exhibiting negligible leaching. Remarkably, these dopants decrease the work function of Cu2O even at such low concentrations, contributing to improved catalytic performance. Moreover, both tin and indium suppress the reduction of Cu2O to metallic copper, maintaining high CO conversion efficiency over extended operation. Our findings demonstrate that low-concentration doping with p-block metals can effectively tune the electronic structure and enhance the electrocatalytic performance of copper-based catalysts.

Plasmonic dimers are versatile platforms for manipulating light–matter interactions at the nanoscale, supporting hybridized modes such as capacitive plasmons (CPs) and charge transfer plasmons (CTPs), which are highly sensitive to the nature of the interparticle junction. However, these junctions have largely been restricted to noble metals, limiting fundamental understanding and design flexibility. Here, we report gold nanosphere dimers interconnected by a metal–semiconductor hybrid junction that enables selective regulation of plasmonic modes. Single-particle scattering measurements show that the hybrid junction, comprising metallic Ag pathways embedded within a high-permittivity AgI matrix, produces enhanced CPs and suppressed CTPs. Supported by electromagnetic simulations, we reveal that interfacial field localization driven by induced dipoles in AgI governs the mode selectivity by trapping oscillating surface plasmons and impeding long-range electronic conduction. This hybrid junction offers a tunable plasmonic platform, expanding opportunities in surface-enhanced Raman spectroscopy, optothermal therapeutics, nanophotonics, and optoelectronics that benefit from enhanced CP modes.

Zinc-halogen batteries (ZHBs) offer a safer, cost-effective alternative to lithium-ion batteries, leveraging abundant zinc resources and high energy density. Among ZHBs, dual-plating zinc bromine batteries (ZBBs) utilizing ionic liquid (IL)-forming bromine complexing agents (BCAs) exhibit enhanced performance by minimizing halogen crossover and enabling high conductivity via Grotthuss-type halide transport. In this study, the electrochemical impedance of the bromide redox reaction in the presence of 1-ethyl-1-methylpyrrolidinium bromide (MEPBr), an IL-forming BCA, was analyzed. Potentiodynamic operando impedance measurements revealed pronounced asymmetry in mass transport impedance between polybromide ionic liquid (PBIL) formation and dissolution. This asymmetry significantly influenced the potential and impedance trends during galvanostatic cycling of dual-plating ZBBs. During charging, facilitated Br− transport lowered the positive electrode impedance, resulting in minimal positive electrode overpotential even at high current densities. In contrast, during discharging, PBIL dissolution at the positive electrode exhibited large overpotential at high current densities due to the relatively sluggish internal mass transport of Br2n+1−. Furthermore, similar asymmetry was observed across various IL-forming BCAs, indicating that the mass transport disparity is an intrinsic property of PBIL rather than limited to MEPBr. These findings provide new insights into PBIL mass transport dynamics and their impact on high-current-density operation in dual-plating ZBBs.