Xuanhe Zhao

Coal-fired power plants represent a major anthropogenic source of nanoscale particulate matter, yet conventional mass-based regulations overlook the distinct and potent health risks posed by specific components. Here we combine single-particle elemental profiles (169 plants across China) with cellular toxicity (human lung cells). Using interpretable machine learning, we reveal iron-rich nanoparticles as key toxic driver, explaining 27.4% of the observed oxidative stress and 16.9% of cytotoxicity. We then develop a high-resolution national inventory of iron-rich nanoparticles, estimating total emissions of 236 tons in 2020, with Eastern China as a hotspot contributing 38.2%. Tailored regional strategies could achieve a 77.5% reduction in national emission, with electrostatic precipitator upgrades identified as the most cost-effective measure. Our findings provide an actionable framework to advance air pollution policy beyond total emissions control toward component-specific reduction of the most toxic nanoparticles, ultimately mitigating their associated public health impacts. Iron rich nanoscale particles from coal plants are identified as the main toxic component, revealed through single particle chemical profiling and cell-based toxicity analysis combined with interpretable machine learning.

Lead-containing fine particles (Pb-FPs) from industrial emissions pose significant health risks, but their source-specific characteristics and traceability remain significant knowledge gaps. This study constructed a nationwide Pb-FP multi-metal fingerprint dataset and developed a machine learning–based source apportionment approach for efficient and accurate source attribution of atmospheric Pb-containing particles. Specifically, we presented a comprehensive investigation of Pb-FPs derived from four major industrial sectors in China, i.e. coal-fired power (CFP), iron and steel smelting (ISS), waste incineration power (WIP), and biomass power generation (BP), through systematic analysis of 134 PM samples collected nationwide using single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOF-MS). Our results showed that WIP (5 ×107 particles/mg) and ISS (3.9 ×107 particles/mg) activities emitted significantly higher number concentrations of Pb-FPs compared to CFP and BP sources. Across all sources, Pb–multi-metal FPs accounted for 66.7–81.2 % of total Pb-FPs number concentrations, with the mass fraction of Pb was predominantly ≤ 10 %.Hierarchical clustering resolved 36 elemental fingerprint clusters with distinct source signatures (e.g., Fe/Mn/Zn-enriched ISS particles versus Si/Al-dominated CFP particles). Building on these fingerprints, we evaluated five machine learning algorithms for source apportionment, with XGBoost emerging as the optimal classifier (F1 score = 0.76, accuracy = 0.77) after intra-fold parameter optimization and cross-validation strategies. Application of the model to PM2.5 samples from Beijing and Shanghai revealed persistent and substantial contributions from ISS-derived Pb-FPs (6.7–38.1 % in Beijing, 10.5–33.7 % in Shanghai), with additional average inputs from CFP (7.4 %), WIP (5.8 %), and BP (12.1 %). These results highlight the dominant role of ISS in atmospheric Pb pollution across industrialized regions of China and provide a basis for explainable source-attribution analysis and future transfer-learning applications.

The failure resistance of polymer networks dictates their utility as material candidates across industries. However, relating the key length scales driving crack growth to molecular mechanisms remains a key bottleneck in predicting and designing against fracture. The fractocohesive length—defined in terms of the ratio of fracture energy to the specific work to rupture—of a material correlates with the length scale of energy dissipation and controls fracture resistance. Although the Lake–Thomas model predicts the fractocohesive length of a perfect polymer network to match the undeformed mesh size, real soft materials exhibit values that far exceed this prediction. Here, we report extraordinarily high fractocohesive lengths in polymer-like networks with and without defects. We find that even perfect networks can have fractocohesive lengths orders of magnitude higher than the undeformed mesh size due to highly nonlinear chain behavior giving rise to nonlocal effects during fracture. Introducing defects further increases the fractocohesive length. We identify quantitative relations between nonlinear chain mechanics, defect length, defect density, and fractocohesive length. Overall, strain-stiffening chain behavior, defect density, and defect size independently correlate with larger fractocohesive lengths in polymer-like networks, and their individual effects can be collapsed into a single power law scaling. These outcomes point the way towards improved physics-informed design of soft yet tough polymers and metamaterials.

Coal-derived fine particles (FPs, <1 μm) are highly reactive and compositionally heterogeneous, yet their toxicity mechanisms remain poorly understood. Using single-particle ICP-TOF-MS, we profiled metal(loid)s in FPs from ten representative coal-fired power plants across China. Quantification showed that 57 ± 9% of FPs were multimetal(loid) (mmFPs), 84 ± 9% of which were Al/Si/Fe-rich and carried most toxic metals. Toxicology assays identified that Fe-rich FPs and associated toxic metals (Cr, Mn, and Pb) could be important contributors to cellular injury, accompanied by oxidative stress and in vitro transcriptomic enrichment of ferroptosis, inflammation, and small-cell lung cancer-related signaling pathways. As an easily separable Fe-rich FP fraction, magnetic FPs comprised only 15.8% of the mass yet contributed 74.2% of oxidative stress and 88.5% of the cytotoxicity. In vitro and in vivo experiments revealed their transferrin receptor (TFRC)-mediated uptake induced ferroptosis and pulmonary injury, which could be attenuated by a TFRC inhibitor. These results suggest Fe-rich FPs (together with associated toxic metals) as the significant contributor of coal-combustion FP toxicity and provide the mechanistic evidence pinpointing Fe-rich particles as key determinants.

Airborne particulate matter (PM) pollution has long been a major threat to human health worldwide, often ignored, but now coming into focus. Specifically in China, two atmosphere-polluting industrial sectors, coal-fired power plants (CFPPs) and iron-steel plants (ISPs), were taken as examples to decipher and estimate the emission of key toxic components of fine particles (FPs; < 1 μm). In vitro tests revealed ISP-emitted FPs induced 12.4 times higher oxidative stress and 4.4 times higher cytotoxicity on human bronchial epithelial cells than CFPP-emitted FPs. Single-particle ICP time-of-flight MS analysis showed that 60 ± 4 % of the CFPP-emitted metal(loid)-containing FPs were multi-metal(loid)s FPs (mmFPs), mostly Si-rich mmFPs (∼80 %). In contrast, Fe-rich mmFPs dominated the ISP-emitted mmFPs, with their number concentrations 8.5 − 35.6 times higher than those from CFPPs. Random forest model and SHapley Additive exPlanation analysis identified Fe-rich mmFPs (especially Fe-sole fingerprinted FPs) as the top regulator of intracellular oxidative stress, while toxic metal(loid)s associated with Fe-rich mmFPs controlled cytotoxicity. Fe-rich FPs, including Fe-rich mmFPs and Fe-single-metal(loid) FPs, contributed over 30 % of the total toxic potency induced by FPs, exceeding any other chemical component. Based on the latest available emission data of PMs in 2019, Fe-rich FPs emitted from CFPPs and ISPs in China were estimated to be about 1.7 × 10 23 particles (ca. 5217 tons), annually. Among these emissions, ISPs contributed over 97 %, with sintering and ironmaking being the major contributors. Therefore, developing advanced filtration technologies and enhancing the monitoring of ISP emissions is strongly encouraged.

Bioelectronic devices implanted on peripheral nerves offer potential for the treatment and rehabilitation of clinical diseases. However, the foreign body reaction and the subsequent fibrous capsule formation at the device-peripheral nerve interface severely limit their efficacy and longevity in vivo. Here, we describe a robust bioadhesive strategy that can establish nonfibrotic bioelectronic interfaces on diverse peripheral nerves-occipital, vagus, deep peroneal, sciatic, tibial, and common peroneal nerves-for up to 12 weeks. Our approach inhibits the infiltration of immune cells into the interface, thereby preventing the formation of fibrous capsules in the inflammatory microenvironment. We demonstrate that our adhesive bioelectronic device with nonfibrotic interfaces maintains long-term blood pressure regulation in a spontaneously hypertensive rat model over 4 weeks. Furthermore, we confirm minimal accumulation of macrophages, smooth muscle actin, and collagen at nonfibrotic bioelectronic interfaces after 12 weeks of device implantation with nerve stimulation, supporting long-lasting neuromodulation without fibrosis.

The genetic diversity of HIV-1, driven by mutation and recombination, poses significant challenges to prevention and control efforts, particularly in regions like China where multiple subtypes and circulating recombinant forms co-circulate. Men who have sex with men (MSM) represent a key population for the emergence of novel recombinants. This study characterizes two novel unique recombinant forms (URFs) identified within the MSM population in Hebei, China. Viral RNA extraction, amplification, and near full-length genome (NFLG) sequencing were performed. Phylogenetic analysis based on NFLG alignments was conducted in MEGA 6 under the Kimura 2-parameter model with 1,000 bootstrap replicates. Recombination was assessed using the Recombinant Identification Program and SimPlot v3.5.1. Breakpoint-defined regions were phylogenetically analyzed, and recombination maps were generated. Phylogenetic and recombinant analysis based on NFLG sequences (designated BDL061 and BDL071) revealed that they originated from subtypes B and C. BDL061 exhibited a predominantly subtype B backbone with interspersed subtype C segments, while BDL071 displayed a predominantly subtype C backbone with subtype B segments. Phylogenetic analysis of recombinant segments strongly supported (bootstrap >90%) subtype B and C parental origins for the respective fragments. We report the identification and characterization of two phylogenetically distinct, novel HIV-1B/C URFs (BDL061 and BDL071) among MSM in Hebei, China. Their unique mosaic structures, differing predominant backbones, and confirmation as novel recombinants underscore the ongoing evolution and increasing complexity of the HIV-1 epidemic within this high-risk population in China. These findings highlight the critical need for NFLG-based surveillance to accurately track viral diversity and inform public health strategies.

Lead-containing fine particles (Pb-FPs) from industrial emissions pose significant health risks, but their source-specific characteristics remain poorly characterized. This study presents a comprehensive investigation of Pb-FPs derived from four major industrial sectors in China, i.e. coal-fired power (CFP), iron and steel smelting (ISS), waste incineration power (WIP), and biomass power generation (BP), through systematic analysis of 134 PM samples collected nationwide using single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOF-MS). Our results showed that WIP (5 ×107 particles/mg) and ISS (3.9 ×107 particles/mg) activities emitted significantly higher number concentrations of Pb-FPs compared to CFP and BP sources. Pb-multi-metal FPs accounted for 66.7-81.2 % of total Pb-FPs number concentrations across all sources, with the mass fraction of Pb was predominantly ≤ 10 %. Distinct elemental fingerprints were identified for each source type, particularly metal-rich matrices associated with Pb. We developed a source apportionment approach by evaluating five machine learning algorithms, with XGBoost emerging as the optimal classifier (F1 score = 0.76, accuracy = 0.77) after Bayesian optimization and 10-fold cross-validation. Application of the model to PM2.5 samples from Beijing and Shanghai revealed persistent and substantial contributions from ISS-derived Pb-FPs (6.7-38.1 % in Beijing, 10.5-33.7 % in Shanghai), with additional average inputs from CFP (7.4 %), WIP (5.8 %), and BP (12.1 %). These results highlight the dominant role of ISS in atmospheric Pb pollution across industrialized regions of China and emphasize the need for targeted mitigation strategies.

Abstract Mitigating adverse tissue remodeling after a heart attack or myocardial infarction (MI) is critical to prevent the development of heart failure. Among various post-MI treatment strategies, mechanical reinforcement of the infarcted region with epicardial patches has promise due to its consistent improvement of chronic cardiac function and its drug- or biologic-free nature. However, despite the variety of patch materials studied to date, the lack of a programmable platform that predictably modifies early-stage cardiac biomechanics to different degrees has prevented further optimization of this strategy. Here, we introduce the matrix-mimicking bioadhesive epicardium (MMBE), a platform that can be rationally designed to achieve a wide range of anisotropic mechanical properties to offer quantifiable mechanical reinforcement of the heart upon application. The platform synergistically combines fully programmable direct-ink-writing of extracellular matrix-inspired crimped fibers and a bioadhesive for sutureless integration to the epicardium. The MMBE platform achieves an array of matrix-mimicking mechanical properties and acute modulation of cardiac biomechanics using numerical analysis, in silico studies and experimental characterizations. Furthermore, the feasibility of the MMBE platform in an in vivo rat model of MI is demonstrated. The MMBE platform can be used to systematically identify patch design parameters that alter post-MI remodeling without introducing confounding biological variables.

Abstract Biohybrid robots powered by tissue engineered skeletal muscle have historically relied on architectures in which muscle actuators are placed directly on skeletons, thus limiting the accessible design space for such machines. By contrast, native musculoskeletal architecture relies on tendons to bridge the interface between muscles and skeletons, enabling precise, space-efficient, and energy-efficient force transmission. In this study, we use a mathematical model of the muscle-tendon-skeleton interface to design a biohybrid muscle-tendon unit composed of tissue engineered muscle coupled to adhesive tough hydrogel tendons. We show how tuning tendon stiffness and pre-tension modulates actuator performance, measure fatigue characteristics of our actuators over &gt;7000 cycles, and tune skeleton stiffness to increase force transmission muscles to skeletons by ∼29X. Furthermore, we demonstrate an ∼11X improvement in power-to-weight ratio of muscle-tendon units as compared to previous demonstrations of robots powered by muscles alone. This work validates a robust approach for designing, manufacturing, and deploying muscle-tendon actuators that promises to enhance the modularity and efficiency of biohybrid robots.

In the version of the article initially published, in Fig. 3d, the immunofluorescence staining image for vimentin on day 7 post-implantation was inadvertently sourced from the immunofluorescence staining image for vimentin on day 14 post-implantation. The image has now been corrected in the HTML and PDF versions of the article, as seen in Fig. 1 , below. The change does not alter the results or conclusions of the paper. Fig. 1: Original and corrected Fig. 3d . Full size image

The intrinsic fracture energy of elastomers is a key factor in determining the mechanical durability of products such as rubber and tires. Historically, the intrinsic fracture energy has been described by the Lake–Thomas model, despite its known limitations. A loop-opening model has been proposed to describe the intrinsic fracture energy of gels prepared at semidilute conditions. In this work, we performed fatigue experiments on highly elastic end-linked polydimethylsiloxane (PDMS) elastomers and further combined these results with existing data from various elastomers to validate the applicability of the loop-opening model to elastomers. Our findings show that the intrinsic fracture energy per chain scales with the product of the fracture force and the contour length of the bridging chains between constraints, suggesting that unentangled and slightly entangled elastomers also follow the loop-opening model. However, in elastomers, overlapping chains constrain the opened loops and prevent them from fully extending. This result is supported by both experimental data and molecular dynamics simulations. This study extends the applicability of the loop-opening framework from gels to elastomers, providing a more quantitative and predictive description of intrinsic fracture energy across diverse polymer networks.

RecommendationsB iological systems are capable of dexterous and adaptable behaviors across length scales.Replicating these behaviors in human-made machines thus requires drawing inspiration from nature.In recent years, roboticists have identified compliance as a key design feature of biological sensors and actuators, enabling closed-loop control of complex behaviors such as locomotion, feeding, and manipulation that are central to life.Integrating compliance into the functional components of autonomous machines has inspired and accelerated the growth of "soft robotics" as a discipline.In this special issue on Soft Robotics, we highlight emerging frontiers in compliant sensing and actuation, novel materials and manufacturing techniques for fabricating soft bioinspired and biohybrid systems, and real-world applications of compliant machines.The featured reviews outline an exciting vision for the future of soft robotics that promises to advance the safety, reliability, and sustainability of autonomous machines.Despite rapid progress in soft materials, sensors, and actuators, achieving seamless sensorimotor integration in soft robots remains a challenge.A comprehensive review from Xiaodong Chen and colleagues explores this emerging topic by examining the foundations of sensorimotor functions. 1The authors first outline the current state-of-the-art in soft sensing mechanisms (pressure, strain, temperature, optical, chemical, acoustic, and electromagnetic) and actuation mechanisms (fluidic, electroactive, magnetic, optical, thermal, chemical) and then highlight efforts to combine these into sensorimotor control architectures, drawing inspiration from biological systems.In particular, this review considers how artificial intelligence (AI) integrated with soft robotics can enable adaptive and responsive control in dynamic environments, enabling high-level functional behaviors such as decision making and autonomous learning.Adaptive and responsive control requires improvements in stretchable electronics, motivating a review by Michael Dickey and colleagues on methods to manufacture flexible conductors via sintering of liquid metal particles. 2The review surveys the benefits and limitations of ten sintering methods (mechanical, thermal, laser, sonication, electrochemical, Ag flake bridges, chemical, evaporation-induced, field-based alignment, and freezing-activated) for forming soft, stretchable, and conductive materials for functional use in soft robotics.The authors also highlight key technical challenges, including the development of practical manufacturing and processing methods, that need to be addressed to enable scalable fabrication of high-performance soft electronics for real-world applications.

Abstract Fibrotic encapsulation around medical implants affects millions of patients annually. Current approaches targeting inflammation or implant material properties have failed clinically, but the mechanical origins of implant-induced fibrosis remain unexplored. Here, we demonstrate that directional imbalance of mechanical forces (“tension anisotropy”) is the primary driver of fibroblast activation at implant-tissue interfaces, and that it can be eliminated through adhesive bonding strategies. Computational modeling reveals a mechanistic basis for successful adhesive anti-fibrotic interfaces: conventional sutured implants generate highly anisotropic stress fields between discrete suture anchor points that activate fibroblasts, while adhesive interfaces distribute forces isotropically, maintaining a mechanical environment that does not activate fibroblasts. In vivo experiments from the literature across multiple animal models confirm these predictions: as predicted, adhesive interfaces completely prevent fibrotic capsule formation for up to 12 weeks across diverse organs, while maintaining identical implant composition and geometry compared to sutured controls. Results establish tension anisotropy as a mechanical regulator of implant fibrosis and provide a mechanistic foundation explaining why adhesive interfaces succeed where all previous anti-fibrotic strategies have failed. By addressing the root mechanical cause of fibrosis, this mechanobiology-driven approach may enable a universal approach for preventing fibrosis across all categories of implantable medical devices. Significance statement Millions of patients suffer from medical device failure due to fibrotic encapsulation, in which a surgically implanted item such as pacemaker leads or a vascular graft loses function by becoming covered with scar tissue. Implants affixed to soft tissues by sutures are especially prone to this form of failure, but implants affixed with a recently invented adhesive are not. We present the discovery that directional imbalance of forces (“tension anisotropy”) drives conversion of healing tissue into scar tissue. Conventional sutured implants create highly anisotropic stress fields between anchor points that activate fibroblasts, while adhesive interfaces distribute forces isotropically, attenuating scarring. This mechanistic insight explains why adhesive implant-tissue interfaces successfully prevent fibrotic capsule formation across multiple animal models and organ systems, where all previous anti-fibrotic approaches have failed. By addressing root mechanical causes of fibrotic remodeling, this discovery provides a pathway for clinical remediation of fibrotic encapsulation.

Networks of interconnected materials permeate throughout nature, biology, and technology due to exceptional mechanical performance. Despite the importance of failure resistance in network design and utility, no existing physical model effectively links strand mechanics and connectivity to predict bulk fracture. Here, we reveal a scaling law that bridges these levels to predict the intrinsic fracture energy of diverse stretchable networks. Simulations and experiments demonstrate its remarkable applicability to a breadth of strand constitutive behaviors, topologies, dimensionalities, and length scales. We show that local strand rupture and nonlocal energy release contribute synergistically to the measured intrinsic fracture energy in networks. These effects coordinate such that the intrinsic fracture energy scales independent of the energy to rupture a strand; it instead depends on the strand rupture force, breaking length, and connectivity. Our scaling law establishes a physical basis for fracture of homogeneous networks with uniform strand mechanics and lattice connectivity throughout. The scaling also extends generally for fabricating tough materials from homogeneous networks across multiple length scales.

The design and functionality of polymeric materials hinge on failure resistance. While molecular-level details drive crack evolution in polymer networks, the connection between individual chain scission and bulk failure remains unclear and difficult to probe. In this work, we systematically study the fracture mechanics of polymer-like networks with hybrid bond strengths. We reveal that varying the ratio of strong and weak strands within otherwise identical networks gives a non-monotonic relationship between intrinsic fracture energy and strong strand fraction. Networks with some weak strands can counterintuitively outperform those with exclusively strong strands. Experiments on poly(ethylene glycol) gels and architected polymer-like lattices together with simulations unveil these properties. We show through computational visualization that strand type concentrations impact crack growth patterns and fracture energy trends. Cracks propagate through weak layers at low strong strand fractions. Aggregate clusters deflect or pin cracks at similar concentrations of strong and weak strands. Cracks blunt due to dispersed weak strand failure at high strong strand fractions. The sacrificial weak strands can notably deconcentrate stress near the crack tip, which toughens by delaying crack advancement. The interplay between concentration and clustering of strand types in networks with hybrid bond strengths, combined with crack growth phenomena and nonlocal energy release, provides insights into unusual fracture characteristics. Results shed light on fracture in polymer networks and percolated lattices.

The original version of the Supplementary Information associated with this Article contained an error in author list. The correct version of author list is: Chase M. Hartquist, Buxuan Li, James H. Zhang, Zhaohan Yu, Guangxin Lv, Jungwoo Shin, Svetlana V. Boriskina, Gang Chen, Xuanhe Zhao & Shaoting Lin, which replaces the previous incorrect version: Shaoting Lin, Chase Hartquist, Buxuan Li, James H. Zhang, Zhaohan Yu, Guangxin Lv, Jungwoo Shin, Svetlana V. Boriskina, Gang Chen, Xuanhe Zhao. The HTML has been updated to include a corrected version of the Supplementary Information .

Abstract Polymeric thermal switches that can reversibly tune and significantly enhance their thermal conductivities are desirable for diverse applications in electronics, aerospace, automotives, and medicine; however, they are rarely achieved. Here, we report a polymer-based thermal switch consisting of an end-linked star-shaped thermoset with two independent thermal conductivity tuning mechanisms—strain and temperature modulation—that rapidly, reversibly, and cyclically modulate thermal conductivity. The end-linked star-shaped thermoset exhibits a strain-modulated thermal conductivity enhancement up to 11.5 at a fixed temperature of 60 °C (increasing from 0.15 to 2.1 W m −1 K −1 ). Additionally, it demonstrates a temperature-modulated thermal conductivity tuning ratio up to 2.3 at a fixed stretch of 2.5 (increasing from 0.17 to 0.39 W m −1 K −1 ). When combined, these two effects collectively enable the end-linked star-shaped thermoset to achieve a thermal conductivity tuning ratio up to 14.2. Moreover, the end-linked star-shaped thermoset demonstrates reversible tuning for over 1000 cycles. The reversible two-way tuning of thermal conductivity is attributed to the synergy of aligned amorphous chains, oriented crystalline domains, and increased crystallinity by elastically deforming the end-linked star-shaped thermoset.

Current clinically used electronic implants, including cardiac pacing leads for epicardial monitoring and stimulation of the heart, rely on surgical suturing or direct insertion of electrodes to the heart tissue. These approaches can cause tissue trauma during the implantation and retrieval of the pacing leads, with the potential for bleeding, tissue damage, and device failure. Here, we report a bioadhesive pacing lead that can directly interface with cardiac tissue through physical and covalent interactions to support minimally invasive adhesive implantation and gentle on-demand removal of the device with a detachment solution. We developed 3D-printable bioadhesive materials for customized fabrication of the device by graft-polymerizing polyacrylic acid on hydrophilic polyurethane and mixing with poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) to obtain electrical conductivity. The bioadhesive construct exhibited mechanical properties similar to cardiac tissue and strong tissue adhesion, supporting stable electrical interfacing. Infusion of a detachment solution to cleave physical and covalent cross-links between the adhesive interface and the tissue allowed retrieval of the bioadhesive pacing leads in rat and porcine models without apparent tissue damage. Continuous and reliable cardiac monitoring and pacing of rodent and porcine hearts were demonstrated for 2 weeks with consistent capture threshold and sensing amplitude, in contrast to a commercially available alternative. Pacing and continuous telemetric monitoring were achieved in a porcine model. These findings may offer a promising platform for adhesive bioelectronic devices for cardiac monitoring and treatment.

Epicardial drug delivery offers the potential to increase drug concentration at the target site, decrease systemic side effects, and reduce overall drug usage and cost. However, controlled drug delivery to the epicardium remains challenging, limiting exploration as a feasible administration route. Existing epicardial delivery systems lack precise control over drug dosing and responsiveness to local physiological cues. To address these limitations, we present SmartSleeve, a sutureless, soft robotic drug-delivery device that enables switchable on-off drug delivery in response to epicardial electrocardiogram (ECG) sensing. SmartSleeve is composed of an elastomeric soft robotic actuator with self-sealing therapy reservoirs, coupled to an adhesive bioelectronic interface. With SmartSleeve, we demonstrate controlled epicardial delivery of therapeutic agents in response to real-time ECG changes in animal models. SmartSleeve provides a sophisticated platform for studying epicardial drug delivery, with the potential to transform cardiac therapy delivery in clinical applications, including postoperative arrhythmia management and chronic inotropic support.

We present a loop-opening model that accounts for the molecular details of the intrinsic fracture energy for fracturing polymer networks. This model includes not only the energy released from the scission of bridging chains but also the subsequent energy released from the network continuum. Scission of a bridging chain releases the cross-links and opens the corresponding topological loop. The released cross-links will be caught by the opened loop to reach a new force-balanced state. The amount of energy released from the network continuum is limited by the stretchability of the opened loop. Based on this loop-opening process, we suggest that the intrinsic fracture energy per broken chain approximately scales with the product of the fracture force and the contour length of the opened loop. This model predicts an intrinsic fracture energy that aligns well with various experimental data on the fracture of polymer networks.

Abstract Implanted biomaterials and devices face compromised functionality and efficacy in the long term owing to foreign body reactions and subsequent formation of fibrous capsules at the implant–tissue interfaces 1–4 . Here we demonstrate that an adhesive implant–tissue interface can mitigate fibrous capsule formation in diverse animal models, including rats, mice, humanized mice and pigs, by reducing the level of infiltration of inflammatory cells into the adhesive implant–tissue interface compared to the non-adhesive implant–tissue interface. Histological analysis shows that the adhesive implant–tissue interface does not form observable fibrous capsules on diverse organs, including the abdominal wall, colon, stomach, lung and heart, over 12 weeks in vivo. In vitro protein adsorption, multiplex Luminex assays, quantitative PCR, immunofluorescence analysis and RNA sequencing are additionally carried out to validate the hypothesis. We further demonstrate long-term bidirectional electrical communication enabled by implantable electrodes with an adhesive interface over 12 weeks in a rat model in vivo. These findings may offer a promising strategy for long-term anti-fibrotic implant–tissue interfaces.

People have realized that the mechanical properties of circular nanoplate structures exhibit strong surface effects. In this article, we introduce Gurtin-Murdoch surface theory into von Karman’s plate theory to examine the nonlinear post-buckling behaviors of graded porous circular nano-plates with surface effects, subjected to follower force. The bulk structure is a porous graded material and pores are embedded in the board in both symmetrical and asymmetrical ways along the thickness direction. The post-buckling equilibrium equations governing axi-symmetric deformation of the graded porous circular nanoplate are derived, and then a shooting method combined with analytical continuation is used to numerically solve the control equation. Characteristic curves of the post-buckling equilibrium path and equilibrium configuration relate to the performances were plotted. Finally, a detailed analysis was conducted on the effects of important parameters such as surface elastic modulus, residual surface stress, scale parameters, pore distribution patterns, and even boundary conditions on the buckling and post-buckling of nanocircular plates. Overall, the results show that surface elastic modulus, and residual surface stress play a great role in the analyzing nonlinear post-buckling of circular nanoplate under follower forces. The surface elastic parameters and residual surface stress have important effects on the yield strength and post-buckling behaviors of porous nano-material sturctures. These new findings can provide theoretical basis for the precise design and manufacturing of aerospace nanodevices.

Automated delivery of insulin based on continuous glucose monitoring is revolutionizing the way insulin-dependent diabetes is treated. However, challenges remain for the widespread adoption of these systems, including the requirement of a separate glucose sensor, sophisticated electronics and algorithms, and the need for significant user input to operate these costly therapies. Herein, a user-centric glucose-responsive cannula is reported for electronics-free insulin delivery. The cannula-made from a tough, elastomer-hydrogel hybrid membrane formed through a one-pot solvent exchange method-changes permeability to release insulin rapidly upon physiologically relevant varying glucose levels, providing simple and automated insulin delivery with no additional hardware or software. Two prototypes of the cannula are evaluated in insulin-deficient diabetic mice. The first cannula-an ends-sealed, subcutaneously inserted prototype-normalizes blood glucose levels for 3 d and controls postprandial glucose levels. The second, more translational version-a cannula with the distal end sealed and the proximal end connected to a transcutaneous injection port-likewise demonstrates tight, 3-d regulation of blood glucose levels when refilled twice daily. This proof-of-concept study may aid in the development of "smart" cannulas and next-generation insulin therapies at a reduced burden-of-care toll and cost to end-users.

Abstract Marine animals equipped with sensors provide vital information for understanding their ecophysiology and collect oceanographic data on climate change and for resource management. Existing methods for attaching sensors to marine animals mostly rely on invasive physical anchors, suction cups, and rigid glues. These methods can suffer from limitations, particularly for adhering to soft fragile marine species such as squid and jellyfish, including slow complex operations, unreliable fixation, tissue trauma, and behavior changes of the animals. However, soft fragile marine species constitute a significant portion of ocean biomass (&gt;38.3 teragrams of carbon) and global commercial fisheries. Here we introduce a soft hydrogel-based bioadhesive interface for marine sensors that can provide rapid (time &lt;22 s), robust (interfacial toughness &gt;160 J m −2 ), and non-invasive adhesion on various marine animals. Reliable and rapid adhesion enables large-scale, multi-animal sensor deployments to study biomechanics, collective behaviors, interspecific interactions, and concurrent multi-species activity. These findings provide a promising method to expand a burgeoning research field of marine bio-sensing from large marine mammals and fishes to small, soft, and fragile marine animals.

Acute liver failure (ALF) is a critical medical condition defined as the rapid development of hepatic dysfunction. Conventional ultrasound elastography cannot continuously monitor liver stiffness over the course of rapidly changing diseases for early detection due to the requirement of a handheld probe. In this study, we introduce wearable bioadhesive ultrasound elastography (BAUS-E), which can generate acoustic radiation force impulse (ARFI) to induce shear waves for the continuous monitoring of modulus changes. BAUS-E contains 128 channels with a compact design with only 24 mm in the azimuth direction for comfortable wearability. We further used BAUS-E to continuously monitor the stiffness of in vivo rat livers with ALF induced by d-galactosamine over 48 hours, and the stiffness change was observed within the first 6 hours. BAUS-E holds promise for clinical applications, particularly in patients after organ transplantation or postoperative care in the intensive care unit (ICU).

Tissue adhesives are promising alternatives to sutures and staples for joining tissues, sealing defects, and immobilizing devices. However, existing adhesives mostly take the forms of glues or hydrogels, which offer limited versatility. We report a direct-ink-write 3D printable tissue adhesive which can be used to fabricate bioadhesive patches and devices with programmable architectures, unlocking new potential for application-specific designs. The adhesive is conformable and stretchable, achieves robust adhesion with wet tissues within seconds, and exhibits favorable biocompatibility. In vivo rat trachea and colon defect models demonstrate the fluid-tight tissue sealing capability of the printed patches, which maintained adhesion over 4 weeks. Moreover, incorporation of a blood-repelling hydrophobic matrix enables the printed patches to seal actively bleeding tissues. Beyond wound closure, the 3D printable adhesive has broad applicability across various tissue-interfacing devices, highlighted through representative proof-of-concept designs. Together, this platform offers a promising strategy toward developing advanced tissue adhesive technologies.

We present a loop-opening model that accounts for the molecular details of the intrinsic fracture energy for fracturing polymer networks. This model includes not only the energy released from the scission of bridging chains but also the subsequent energy released from the network continuum. Scission of a bridging chain releases the crosslinks and opens the corresponding topological loop. The released crosslinks will be caught by the opened loop to reach a new force-balanced state. The amount of energy released from the network continuum is limited by the stretchability of the opened loop. Based on this loop-opening process, we suggest that the intrinsics fracture energy per broken chain approximately scales with the product of the fracture force and the contour length of the opened loop. This model predicts an intrinsic fracture energy that aligns well with various experimental data on the fracture of polymer networks.

Networks of interconnected materials permeate throughout nature, biology, and technology due to exceptional mechanical performance. Despite the importance of failure resistance in network design and utility, no existing physical model effectively links strand mechanics and connectivity to predict bulk fracture. Here, we reveal a universal scaling law that bridges these levels to predict the intrinsic fracture energy of diverse networks. Simulations and experiments demonstrate its remarkable applicability to a breadth of strand constitutive behaviors, topologies, dimensionalities, and length scales. We show that local strand rupture and nonlocal energy release contribute synergistically to the measured intrinsic fracture energy in networks. These effects coordinate such that the intrinsic fracture energy scales independent of the energy to rupture a strand; it instead depends on the strand rupture force, breaking length, and connectivity. Our scaling law establishes a physical basis for understanding network fracture and a framework for fabricating tough materials from networks across multiple length scales.

Bioadhesives In article number 2307288, Ellen T. Roche and co-workers introduce a silicone-based bioadhesive tailored for robust, durable adhesion between silicone devices and biological tissues. The strategy addresses the challenges of wet tissue adhesion and long-term integration by blending soft silicone oligomers, siloxane coupling agents, and absorbents. The adhesive undergoes controlled degradation, transitioning from nonpermeable to permeable, fostering cell migration and ensuring effective adhesion in diverse medical device applications.

Strain-induced crystallization (SIC) prevalently strengthens, toughens, and enables an elastocaloric effect in elastomers. However, the crystallinity induced by mechanical stretching in common elastomers (e.g., natural rubber) is typically below 20%, and the stretchability plateaus due to trapped entanglements. We report a class of elastomers formed by end-linking and then deswelling star polymers with low defects and no trapped entanglements, which achieve strain-induced crystallinity of up to 50%. The deswollen end-linked star elastomer (DELSE) reaches an ultrahigh stretchability of 12.4 to 33.3, scaling beyond the saturated limit of common elastomers. The DELSE also exhibits a high fracture energy of 4.2 to 4.5 kJ m −2 while maintaining low hysteresis. The heightened SIC and stretchability synergistically promote a high elastocaloric effect with an adiabatic temperature change of 9.3°C.

Connecting polymer network fracture to molecular-level chain scission remains a quandary. While the Lake-Thomas model predicts the intrinsic fracture energy of a polymer network is the energy to rupture a layer of chains, it underestimates recent experiments by ∼1-2 orders of magnitude. Here we show that the intrinsic fracture energy of polymerlike networks stems from nonlocal energy dissipation by relaxing chains far from the crack tip using experiments and simulations of 2D and 3D networks with varying defects, dispersity, topologies, and length scales. Our findings not only provide physical insights into polymer network fracture but offer design principles for tough architected materials.

Bioadhesives have emerged as transformative and versatile tools in healthcare, offering the ability to attach tissues with ease and minimal damage. These materials present numerous opportunities for tissue repair and biomedical device integration, creating a broad landscape of applications that have captivated clinical and scientific interest alike. However, fully unlocking their potential requires multifaceted design strategies involving optimal adhesion, suitable biological interactions, and efficient signal communication. In this Review, we delve into these pivotal aspects of bioadhesive design, highlight the latest advances in their biomedical applications, and identify potential opportunities that lie ahead for bioadhesives as multifunctional technology platforms.

We report in this work several unexpected experimental observations on evaporation from hydrogels under visible light illumination. 1) Partially wetted hydrogels become absorbing in the visible spectral range, where the absorption by both the water and the hydrogel materials is negligible. 2) Illumination of hydrogel under solar or visible-spectrum light-emitting diode leads to evaporation rates exceeding the thermal evaporation limit, even in hydrogels without additional absorbers. 3) The evaporation rates are wavelength dependent, peaking at 520 nm. 4) Temperature of the vapor phase becomes cooler under light illumination and shows a flat region due to breaking-up of the clusters that saturates air. And 5) vapor phase transmission spectra under light show new features and peak shifts. We interpret these observations by introducing the hypothesis that photons in the visible spectrum can cleave water clusters off surfaces due to large electrical field gradients and quadrupole force on molecular clusters. We call the light-induced evaporation process the photomolecular effect. The photomolecular evaporation might be happening widely in nature, potentially impacting climate and plants' growth, and can be exploited for clean water and energy technologies.