Foams with high damping capacity have high potential in noise reduction, vibration mitigation, and energy dissipation applications. However, integration of superior damping, strong mechanical properties, and effective sound absorption, into lightweight foams is still a serious challenge. Inspired by cicada wing structure, a new approach was developed to improve foam characteristics by establishing an in situ skeleton-GO network within the foam. This bioinspired network architecture partially spans the open regions defined by adjacent foam skeletons, rather than coating the skeleton or fully filling pores. This method remarkably improved the properties of the foam such that vibration attenuation time was decreased by about 83.3%, damping property was increased by about 179.3%, sound absorption was effectively enhanced, and compressive modulus was increased by about 924%, allowing the foam to tolerate 1000 times its own weight without noticeable deformation. The originally non-waterproof melamine foam becomes hydrophobic after modification, presenting contact angles of up to 114.2°. This research provided a new and versatile approach to improve synergistic multifunction of foam materials.
Microbes in natural environments often encounter diverse mixtures of organic compounds, yet how mixed substrate environments and their molecular composition shape microbial phenotypes remains understudied. Here, we examined how a defined fungal exudate mimic (FEM) mixture influences growth and metabolism in Pseudomonas putida KT2440 compared to individual substrates matched for total carbon and nitrogen. Growth on FEM initiated 2 h earlier than growth on glucose alone and exhibited both the lowest lag and shortest time to maximum biomass compared to individual substrates. Fructose was the only individual substrate that supported significantly higher maximum biomass than FEM, but exhibited a nearly 15-fold longer lag phase. Gas chromatography mass spectrometry analysis revealed dynamic temporal patterns of substrate utilization within the FEM mixture, with early preferential utilization of malate, followed by overlapping utilization of multiple substrates between 3 and 8 h. By integrating growth and substrate uptake kinetics with genome-scale metabolic modeling and validating model-predicted pathway activity using temporal proteomics, we show that experimentally constrained model predictions accurately captured substrate utilization dynamics across multiple FEM concentrations, and predicted temporal shifts in the dominant substrates supporting growth. Through this integrative experimental-modeling approach, we demonstrate that the mixed substrate FEM environment elicits an emergent growth phenotype characterized by the lowest lag, shortest time to maximum biomass, and relatively high maximum biomass in Pseudomonas putida, a combination of traits not simultaneously reproduced by any individual substrate. How mixed-nutrient substrate environments influence bacterial growth and metabolism is not well understood and is challenging to predictively model. Using Pseudomonas putida KT2440, we show that growth on a defined mixture of substrates inspired by mycorrhizal fungal hyphal exudates produces a distinct and emergent growth phenotype characterized by a lower lag, shorter time to maximum biomass, and relatively high biomass accumulation when compared to individual substrates alone. This combination of growth traits is not simultaneously reproduced by any individual substrate, even when total carbon and nitrogen are matched. By integrating growth measurements and temporal substrate uptake data with dynamic flux balance analysis and proteomics, we demonstrate that metabolic responses to mixed substrates can be quantitatively interpreted. These findings highlight the importance of studying microbes under chemically realistic conditions and suggest that learning from naturally occurring molecular environments may provide new strategies for engineering microbial growth conditions and improving bioprocess performance.
Engineering stable noncovalent conformational locks (NoCL) network at the aggregate level is essential for developing phototheranostic aggregates (PTAs) with enhanced rigidity and light-harvesting ability, but remains a challenge due to complex intermolecular interactions. Inspired by β-sheet proteins, where branched side chains act as steric directors to program backbones into interlocked architectures, a side-chain isomerization strategy is proposed to manipulate analogous NoCL networks for constructing planar-structured NIR-II multimodal PTAs. Two isomeric pairs with linear (l-series) and branched (b-series) alkyl side-chains are synthesized. Crystallographic analysis reveals that the b-series, driven by directional S···O/F interactions, adopts a fully planar conformation stabilized by a synergistic dual NoCL network, whereas l-series exhibits twisted conformations. Theoretical calculation and femtosecond transient absorption spectra confirm the dual NoCL network effectively narrows the energy gap and optimizes excited-state energy dissipation pathway, resulting in comprehensive enhancement in phototheranostic performance including superior ROS generation, higher NIR-II brightness and excellent photothermal properties compared to l-series NPs. Notably, the exceptional performance of b-3CPFIC NPs enables it to serve as an ideal candidate in multimodal NIR-II phototheranostics of tumors. This work establishes a novel design paradigm for multifunctional PTAs and elucidates aggregate-level structure-property relationships.
Solid-state sintering regeneration offers a promising strategy for repairing spent lithium iron phosphate (LFP) cathodes, yet conventional homogeneous-mixing (HM) sintering approaches neglect the intrinsic heterogeneity of FePO4 within LFP particles. This induces additional long-range Li+ solid-state migration from Li-rich to Li-deficient domains during regeneration, creating substantial solid-state diffusion barriers that necessitate extended high-temperature sintering duration while triggering local over-lithiation, ultimately degrading regeneration performance. Inspired by specific antigen-antibody-phagocyte interactions, we propose a novel mechanistic concept of site-specific atomic repair (SAR) for energy-efficient LFP regeneration. Through targeted-adsorption-enhanced evaporation-nucleation processes, lithium sources and reductants are selectively anchored onto heterogeneous FePO4 domains for localized repair, which shortens Li+ solid-state diffusion pathways, lowers migration barrier, and reduces FePO4 → LiFePO4 transition temperature from 300-400°C to 100-200°C. Consequently, the SAR-regenerated LFP cathodes deliver enhanced performance while requiring only half of the high-temperature sintering duration of conventional HM approaches, thereby achieving ∼20%-30% reduction in energy consumption & CO2 emissions with a markedly improved profit by ∼40%. With additional heteroatom doping, SAR demonstrates exceptional rate performance (73.0 mAh g-1 at 15 C) and long-term stability (90.0% after 600 cycles), ranking among the best reported to date, demonstrating cost-effective mechanistic advances for industrial-scale LFP recycling.
Developing photoelectrochemical synergistic catalysts for the oxygen evolution reaction (OER) that combine high activity and long-term stability is crucial for industrial hydrogen production, but simultaneously optimizing site utilization and bubble desorption kinetics remains extremely challenging. Inspired by the biomimetic logic of "soil-tree," this paper successfully developed a multi-scale synergistically enhanced F-NFA-LDH/MX photoelectrocatalyst by in situ constructing a vertical F-NiFeAl-LDH nanosheet array on a monolayer MXene conductive substrate and supplementing it with low-temperature gas-phase fluorination. In this system, MXene acts as a conductive "soil," constructing a continuous electron transport network that significantly reduces interfacial impedance; the vertical array, acting as a "tree," forms an open 3D mass transport channel, maximizing the active area while accelerating bubble desorption through excellent exhaust kinetics, ensuring the robustness of the system. At the atomic scale, fluorination modification reshapes the electronic structure of the metal center, inducing a high-valence electron-deficient environment and abundant oxygen vacancies, significantly enhancing intrinsic catalytic activity. Experimental results show that the F-NFA-LDH/MX exhibits an overpotential of only 204 mV at 10 mA cm-2 under illumination and operates stably for over 100 h at 20 mA cm-2. Furthermore, its unique architecture endows the system with superior light-harvesting capabilities and photoelectric synergy. This research, through comprehensive design from atomic-level electronic manipulation to macroscopic dynamics, provides a practical strategy for developing highly efficient energy conversion catalysts.
Erythrocyte-based drug delivery systems serve as an attractive strategy for cancer immunotherapy with improved biocompatibility, increased circulation time, and less immunogenicity. Due to their distinct physiological characteristics, erythrocytes can be developed as biomimetic carriers for targeted drug delivery, antigen presentation, and immune modulation. This review discusses the different strategies utilized to leverage erythrocytes in cancer immunotherapy, such as erythrocyte membrane-coated nanoparticles, antigen-hitchhiking systems, and immune-stimulatory erythrocyte-derived vesicles. Notably, we uniquely contextualizes erythrocyte-inspired platforms across each stage of the cancer-immunity cycle, highlighting their dual role as both drug delivery vehicles and active immunomodulators. We have explained how engineered erythrocyte-based systems enhance the cycle of cancer-immunity by increasing tumor antigen presentation and reshaping the tumor microenvironment for greater immune cell infiltration and cytotoxicity. In addition, recent advances in erythrocyte-based immunotherapeutic platforms, their advantages over conventional delivery platforms, and challenges in their clinical application are discussed. Overall, the integration of erythrocyte biomimetic technology into immunotherapy provides a novel approach to enhance cancer treatment efficacy and reduce systemic toxicity, paving the way for more targeted and effective therapies.
Burnout of nurses is a global occupational hazard characterized by emotional exhaustion, cynicism, and reduced care quality. Often framed as a nurse resilience issue, other evidence suggests organizational and systemic contributors such as workload, staffing shortages, and toxic leadership. This article introduces a holistic, tarot-informed framework for nurse self-reflection based on the Rider-Waite process organized around the Celtic Cross card-position structure. This framework uses card positions and symbolism as prompts to explore psychological, social, professional, and structural influences that inform nurses' experiences of burnout, rather than using tarot for prediction or divination. The 10-card position spread supports meaning-making, mindfulness, and professional identity to explore nurses' work experiences; tarot cards can be added for deeper symbolic meaning. This interconnected framework provides a pathway to nurse resilience and holistic insight. Individual reflection alone is insufficient; sustainable change also requires leadership accountability and organizational commitment to healthy work environments. Nursing is based on human caring, which also includes caring for ourselves.
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Insect locomotion exhibits remarkable adaptability and flexibility despite the limited scale of its nervous system. However, the underlying principles that govern leg coordination remain difficult to extract and model computationally. Understanding how insects achieve stable and adaptive locomotion has long provided important inspiration for the development of control strategies in bio-inspired robotics. Nevertheless, many existing approaches rely on predefined coordination rules, manually tuned parameters, or hand-crafted reward functions, which limit the flexibility and transferability of the resulting control strategies. To address this limitation, this study proposes a data-driven framework based on adversarial inverse reinforcement learning (AIRL), which directly learns continuous locomotion control policies from stick insect walking data and infers latent reward structures and control strategies from biological behavioral demonstrations. Experimental results show that even when trained using only a short segment of flat-terrain demonstration data, the learned policy can still be extracted to learn adaptive and flexible leg coordination patterns under different environmental conditions. Furthermore, the learned reward network can be transferred across different dynamic systems to guide policy learning for robot models with different morphologies. Compared with methods relying solely on reward shaping, the proposed approach achieves faster convergence and produces more biologically consistent gait coordination. A preliminary deployment on a physical bio-inspired robot further demonstrates the potential of the learned policy for sim-to-real application. The proposed method provides a transferable data-driven framework for extracting and learning locomotion control strategies from biological behavior, with potential applications to bio-inspired robotic systems.
In order to better understand medical students' decision-making to pursue ophthalmology, and inform efforts to recruit more diverse and inspired ophthalmologists, we aim to characterize values and experiences of medical students pursuing ophthalmology. Retrospective cross-sectional study. U.S. medical students who responded to American Association of Medical Colleges (AAMC) Matriculating Student and Graduation Questionnaires (MSQ & GQ) between 2013 and 2022. We examined survey responses pertaining to personal values, medical school experiences, and use of resources. Univariate analyses were performed to compare the odds of pursuing ophthalmology versus other specialties. Association of values and experiences with odds of pursuing ophthalmology versus another specialty. Among 134,723 matriculating students who completed the MSQ, those interested in ophthalmology (2425 students) were more likely to value high income (OR 1.46, p<0.001) and work-life balance (OR 1.44, p<0.001), and less likely to value social change (OR 0.76, p<0.001), leadership (OR 0.94, p=0.011), or creativity (OR 0.94, p=0.025). Of 98,628 graduates who completed the GQ, those pursuing ophthalmology (2150 students) valued salary (OR 1.73, p<0.001), family considerations (OR 1.31, p<0.001), and work-life balance (OR 2.40, p<0.001) more than those pursuing other specialties. Students pursuing ophthalmology rated their clerkships in neurology (OR 1.22 [1.16-1.29], p<0.001), internal medicine (OR 1.19 [1.12-1.28], p<0.001), surgery (OR 1.18 [1.12-1.25], p<0.001), psychiatry (OR 1.16 [1.09-1.23], p<0.001), and emergency medicine (OR 1.08 [1.01-1.16], p=0.02) more highly compared to other core clerkships. Students pursuing ophthalmology were more likely to perform research (OR 4.75, p<0.001) than those pursuing other fields. These students also more frequently relied on web-based resources (OR 1.58, p<0.001), group panels (OR 1.39, p<0.001), and extra electives (OR 1.30, p<0.001) for specialty information compared to other students, but not mentorship, school workshops, or AAMC-provided information. Medical students pursuing ophthalmology valued lifestyle factors rather than leadership, creativity, or social change and were also more likely to perform research. They were more likely to rely on non-mentorship resources for specialty information. Efforts are needed to refine the perception of ophthalmology, increase focus on creativity and innovation, and improve the recruitment of diverse and inspired future ophthalmologists.
Hypoxaemia occurs in intermittent forms, such as obstructive sleep apnoea, and in continuous forms, such as at high altitude, and is increasingly recognized as a modulator of cardiometabolic risk. Although hypoxaemia alters postprandial glucose and lipid metabolism, its effects on ketone bodies remain unclear. Using a randomized crossover design, we examined whether 6 h of normoxaemia or intermittent hypoxaemia (15 hypoxaemic cycles/h targeting ∼85% peripheral oxyhaemoglobin saturation with 100% medical-grade nitrogen) alters plasma β-hydroxybutyrate (BHB) concentrations in 12 young adult females (mean [SD]: 21 [3] years) following a high-fat meal (33% of estimated daily energy requirements; 59% of energy from fat). In a follow-up session, a subset (n = 8) completed 6 h of continuous hypoxaemia (fraction of inspired oxygen ∼12.0% in a normobaric chamber). Postprandial data were analysed using baseline-adjusted linear mixed-effects models, with Bonferroni post hoc tests. A time × condition interaction (P = 0.010) indicated that BHB concentrations at 360 min were higher during continuous hypoxaemia (0.247 mmol/L; 95% CI: 0.218-0.275) than normoxaemia (0.176 mmol/L; 95% CI: 0.153-0.200; PBonferroni = 0.029) and intermittent hypoxaemia (0.163 mmol/L; 95% CI: 0.139-0.186; PBonferroni = 0.002), representing increases of 13.0% and 14.2% in estimated marginal means, respectively. This response was accompanied by higher postprandial plasma glucose and triglyceride concentrations during continuous hypoxaemia than during normoxaemia and intermittent hypoxaemia (PBonferroni ≤ 0.002), despite similar plasma insulin and non-esterified fatty acid responses across conditions (P ≥ 0.081). These findings indicate that continuous hypoxaemia increases late postprandial plasma BHB concentrations in young adult females.
Obese patients are vulnerable to atelectasis, impaired oxygenation, and postoperative pulmonary complications (PPCs) during and after general anesthesia. Driving pressure-guided individualized positive end-expiratory pressure (PEEP) can improve intraoperative respiratory mechanics, but whether these physiological benefits translate into fewer PPCs in bariatric surgery remains uncertain. In this single-center, parallel-group randomized clinical trial, 116 adults with obesity scheduled for elective laparoscopic bariatric surgery were randomized 1:1 to a driving pressure-guided individualized PEEP strategy or a conventional fixed low-PEEP strategy. All patients received volume-controlled ventilation with a tidal volume of 7 ml/kg predicted body weight and an inspired oxygen fraction of 0.50. After a standardized recruitment maneuver, the driving pressure group underwent stepwise PEEP titration to identify the PEEP level associated with the lowest driving pressure; the conventional group received fixed PEEP of 5 cm H2O. The primary endpoint was the severity and incidence of PPCs within the first 5 postoperative days. Secondary endpoints included respiratory mechanics, oxygenation, hospital length of stay, postoperative nausea and vomiting, surgical site infection, and mortality. All 116 randomized patients completed the trial. Any PPC occurred in 41 of 58 patients (70.7%) in the driving pressure group and 44 of 58 patients (75.9%) in the conventional group (odds ratio, 0.77; 95% CI, 0.33 to 1.79; P = 0.68). PPC severity scores were 1.0 ± 0.9 and 1.1 ± 0.8, respectively (mean difference, -0.10; 95% CI, -0.41 to 0.21; P = 0.53). Severe PPCs (grade >  = 3) occurred in 3 patients (5.2%) in each group. Compared with conventional ventilation, driving pressure-guided ventilation produced lower intraoperative driving pressure, higher dynamic compliance, and a higher PaO2/FiO2 ratio 1 h after surgical start; these physiological improvements were not accompanied by shorter hospital stay or fewer postoperative adverse events. In obese patients undergoing laparoscopic bariatric surgery, a driving pressure-guided individualized PEEP strategy improved intraoperative respiratory mechanics and early oxygenation but did not reduce PPCs compared with conventional fixed low-PEEP ventilation. These findings suggest that optimizing respiratory-system driving pressure alone may be insufficient to improve short-term clinical pulmonary outcomes in this surgical population.
Inspired by motile cells in tissue formation, we find that active systems of self-aligning adhesive particles undergo ballistic aggregation through a flocking transition. This kinetic regime emerges when the cluster persistence length grows faster with cluster mass than the intercluster distance does. We also identify and explain distinct noncollective kinetic regimes, including biologically relevant long-lived transients. Our analytical and numerical results offer a framework explaining the broad range of experimentally observed aggregation exponents in cellular systems and reveal physical principles potentially critical for timely tissue organization.
Programmable metamaterials that exhibit prescribed mechanical responses and adaptive deformation under external loading are highly desirable for multifunctional engineering applications. However, most existing designs rely on multi-material systems, which pose significant fabrication challenges with conventional additive manufacturing. Inspired by the unique soft-hard heterogeneous architecture of nacre, this study introduces a novel class of dual-phase (DP) metamaterials where spatially encoded soft and hard phases are realized through bending-dominated and stretching-dominated lattice architectures, respectively. By systematically varying the spatial coding patterns of soft-hard phases, representative DP metamaterials are shown to exhibit programmable nonlinear mechanical responses and tailored failure processes, achieved through geometry-based mechanical encoding governed by phase interactions and internal stress redistribution. Notably, the engineered sequenced failure processes and phase-coupling-induced strengthening effects lead to significantly enhanced energy absorption compared with the constituent architectures, while enabling customizable plateau stress. To efficiently explore the vast design space of DP metamaterials, a data-driven framework is then developed to model the relationship between spatial encodings and nonlinear mechanical responses. The trained model enables rapid and accurate inverse design of DP metamaterials matching the complex target responses for multifunctional applications. Overall, this work establishes a new geometry-based strategy for achieving highly programmable mechanical responses in single-material metamaterials.
In today's climate of increasing health and social care needs and a declining workforce, most organisations and leaders are not only looking for strategies to recruit new staff but also ways of retaining the staff already in service. Retention, with its multiple factors and no single solution, is a wicked problem. Of the multiple factors influencing staff intent to stay, leadership and culture are two major areas where a significant impact can be made. Front-line leaders are in an ideal position for cultivating workplaces where staff want to work. As part of a two-nation project exploring the impact of various interventions on staff retention, we developed and evaluated a leadership development programme for front-line leaders in health and social care. Two cohorts followed a 12 month programme inspired by the co-operative inquiry process and adult, person-centred and transformative learning. Participants were facilitated in moving through continuous cycles of: identifying individual or group action, executing and observing the impact of their actions, sharing their observations and reflecting on the meaning of the observations for leadership intended to encourage staff retention. They creatively expressed their development narrative at the end of the programme. In this paper we share the participant faction (one fictive narrative based on fourteen participant narratives). The narrative reveals how participants started with feelings of fumbling around in darkness but then discovering one's own (and others') colour as conscious attentiveness to the ways they were leading grew. Alongside finding the authentic self, participants came to the realization that you don't have to travel alone and that using critical thinking and creativity they dared surf the dynamic waves of current health and social care oceans. We conclude that leadership development programmes based on adult, transformative and person-centred learning theory creates a learning climate and culture that enables front-line leaders to start to consciously cultivate workplaces where staff want to stay.
The sulfonamide moiety (-SO2NH-) is a structurally versatile motif in agrochemical discovery. It can engage in hydrogen bonding, modulate molecular polarity and acidity, and act as a bioisostere or linking fragment in ligand design. Inspired by the mechanism of sulfonamide antibiotics, researchers have developed a range of agrochemicals active against plant pathogens and weeds. However, the development of sulfonamide-based agrochemicals has been unbalanced: commercial products are mainly concentrated in herbicides and some fungicides, whereas research on insecticides, antiviral and plant-growth regulators remains largely at the greenhouse trial stage. In fungicide research, chesulfamide derivatives, triazole sulfonamide and sulfonamide-bearing succinate dehydrogenase inhibitor candidates exhibit diverse molecular optimization strategies. Acetolactate synthase and protoporphyrinogen IX oxidase inhibitors clearly demonstrate that structural modification can modulate the weed control spectrum and crop selectivity; nevertheless, single-target herbicides are constantly confronted with the challenge of weed resistance. In the insecticidal and antiviral fields, the sulfonamide group is commonly used as an activity-modulating linker or recognition motif. Multiple studies have reported sulfonamide compounds targeting vacuolar-type H+-ATPase, viral coat protein or plant defense pathways. Sulfonamide abscisic acid (ABA) analogs further validate the utility of this motif in plant-growth regulation and stress response research. This article systematically reviews sulfonamide compounds for their herbicidal, fungicidal, bactericidal, insecticidal and antiviral activities, and summarizes their roles as ABA functional analogs over the past 20 years. Particular attention is given to representative scaffolds, structure-activity relationship and proposed targets or mechanisms. © 2026 Society of Chemical Industry.
The intuitionistic fuzzy twin support vector machine (IFTSVM) utilizes the intuitionistic fuzzy set (IFS) to enhance the robustness of twin support vector machine (TSVM). While IFTSVM has successfully mitigated the impact of noise and outliers, significant room for improvement remains: (1) IFS cannot reduce resampling noise deviation; (2) TSVM is sensitive to noise features. To address these problems, we propose a novel intuitionistic proximity-consensus fuzzy (IPCF) geometric TSVM with l0-norm-based best subset selection to reduce the influence of outliers, resampling noise and noise features, simultaneously. The proposed IPCF is induced by the distance to the hyperplane obtained from the least squares one-class support vector machine, rather than considering the distance to the class center as in IFS. This strategy can effectively alleviate the effects of both outliers and resampling noise. Moreover, by incorporating the l0-norm penalty, we can achieve significant feature selection and noise feature reduction at the same time. Due to the non-convexity, non-smoothness and non-continuity of l0-norm penalty, it is difficult to solve the optimization problem. Inspired by the recently proposed variable sorted active set algorithm, we design an intuitionistic proximity-consensus fuzzy-optimized variable sorted active set algorithm (IPCF-VSAS) for optimizing the problem. On both simulating datasets and UCI datasets, it is the experimental results that validate the advantages of the proposed method. Specifically, compared with other state-of-the-art support vector classifiers, ours typically performs optimally on the datasets with redundant features and noise.
Smart fiber actuators with self-sensing and intelligent actuation have inspired great efforts toward perceiving environmental changes and responding real-time movements, showing great promise in the man-machine interaction and the Internet of Things. Organic ferroelectric species present an enticing prospect in flexible mechanical actuators, yet are rarely developed in smart fiber actuators. Herein, we proposed an organic charge-transfer ferroelectric cocrystal composed of 7H-Dibenzo[c,g]carbazole and tetracyanoquinodimethane, which demonstrated a non-centrosymmetric alignment of Pc space group with a low coercive field of 500 V/cm. Furthermore, the scalable piezoelectric nanofibers with a piezoelectric coefficient of 0.6744 nm/V were achieved after undergoing the location self-assembly of ferroelectric cocrystal in polyvinylidene fluoride (PVDF) matrix during electrospinning process. Significantly, these prepared nanofibers were purposefully employed to form the flexible piezoelectric nanogenerator, yielding an instantaneous peak voltage output of 60 V under 200 N, and a pressure sensitivity of 0.3060 V/N. We foresee application possibilities in accurately detecting physiological signals, such as finger bending and respiration. This work opens up avenues to the wonderful optoelectronic application for the cost-effective ferroelectric cocrystal.
Origami-inspired architectures offer a powerful route toward lightweight, reconfigurable, and programmable robotic systems. Yet, a unified mechanics framework capable of seamlessly bridging rigid folding, elastic deformation, and stability-driven transitions in compliant origami remains lacking. Here, we introduce a geometry-consistent modeling framework based on discrete differential geometry (DDG) that unifies panel elasticity and crease rotation within a single variational formulation. By embedding crease-panel coupling directly into a mid-edge geometric discretization, the framework naturally captures rigid-folding limits, distributed bending, multistability, and nonlinear dynamic snap-through within one mechanically consistent structure. This unified description enables programmable control of stability and deformation across rigid and compliant regimes, allowing origami structures to transition from static folding mechanisms to active robotic modules. An implicit dynamic formulation incorporating gravity, contact, friction, and magnetic actuation further supports strongly coupled multiphysics simulations. Through representative examples spanning single-fold bifurcation, deployable Miura membranes, bistable Waterbomb modules, and Kresling-based crawling robots, we demonstrate how geometry-driven mechanics directly informs robotic functionality. This work establishes discrete differential geometry as a foundational design language for intelligent origami robotics, enabling predictive modeling, stability programming, and mechanics-guided robotic actuation within a unified computational platform.
Direct ethanol fuel cells are hindered by the ethanol oxidation reaction (EOR) that favors the low-efficiency C2 pathway over the desirable C1 pathway. Here, we report a catalyst design integrating an ultrathin Turing-type nanonet with a Pd-based crystalline/amorphous (C/A) heterointerface, achieving a near-complete C1-pathway selectivity of 97.1% for alkaline EOR, which is the highest reported to date. Inspired by spatially decoupling C─C cleavage and CO oxidation, we engineer two intimately integrated phases: strained interstitial-carbon-doped PdO (Cint-PdO) enriched with oxygen vacancies and defective amorphous PdCx (a-PdCx). This heterostructure is realized via a "carbon engineering" strategy combining salt-melt templating with secondary annealing. Atomic-resolution studies confirm atomically sharp C/A interfaces and the highly unsaturated a-PdCx phase. In situ Fourier-transform infrared spectroscopy (FTIR) directly visualizes CO2 emergence at ultralow overpotentials, while high-performance liquid chromatography (HPLC) verifies the near-complete C1 pathway. Density functional theory (DFT) reveals a dual-cooperative mechanism: Cint-PdO steers the EOR toward C1 pathway by facilitating CH3CO* dehydrogenation and subsequent C─C cleavage via CH2CO*, thereby suppressing acetate formation; concurrently, a-PdCx dramatically accelerates CO oxidation and may also contribute to C─C cleavage via an alternative direct CH3CO* pathway. This work establishes carbon-engineered C/A heterointerfaces as a powerful platform for overcoming the EOR selectivity bottleneck.