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Wafer-Scale Single-Crystal WSe<sub>2 </sub>Monolayers Using Substrate-Passivation-Driven Epitaxy
No full textTwo-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) offer a promising materials platform for next-generation electronic devices, providing ultimate subnanometer thickness control and various functionalities for advanced optoelectronics. Among 2D TMDs, p-type TMDs such as WSe2 are essential for fabricating fully complementary metal-oxide-semiconductor (CMOS) 2D circuits. Nonetheless, achieving wafer-scale, single-orientation p-type WSe2 monolayers is notably elusive compared with n-type MoS2 monolayers. Herein, we report a substrate-passivation-driven epitaxy strategy that produces a 98.44% single-orientation WSe2 monolayer on two-inch C-plane sapphire, surpassing previous benchmarks of around 82–87% ratios for single-orientation large-area p-type TMDs. By precisely tailoring the introduction sequence of H2 gas and Se vapor for in situ substrate treatment, we engineered an AlOSe2–Se-passivated sapphire surface that stabilizes the as-grown WSe2 monolayer with a predominantly 30° single orientation. Optical and electrical characterization results corroborate the structural uniformity of the WSe2 monolayers and the consistency of their device performance across wafer-scale transistor arrays. By advancing the epitaxial growth mechanism of oriented WSe2 monolayer on sapphire, we establish this passivation-driven epitaxy strategy that can be used as a robust materials platform for scalable, single-orientation p-type TMD monolayers, bridging the performance gap between n-type and p-type 2D semiconductors for next-generation electronic and optoelectronic devices.</p
3D-printed low-voltage-driven ciliary hydrogel microactuators
No full textMicrometre-sized, densely packed natural cilia that perform non-reciprocal 3D motions with dynamically tunable collective patterns are crucial for biological processes such as microscale locomotion1, nutrient acquisition2, cell trafficking3, 4–5 and embryonic and neurological development6, 7–8. However, replicating these motions in artificial systems remains challenging given the limits of scalable, locally controllable soft-bodied actuation at the micrometre scale. Overcoming this challenge would enhance our understanding of ciliary dynamics, clarify their biological importance and enable new microscale devices and bioinspired technologies. Here we show a previously unrecognized fast electrical response of micrometre-scale hydrogels, induced by voltages down to 1.5 V without hydrolysis, with bending motions driven by ion migration across a nanometre-scale hydrogel network 3D-printed by two-photon polymerization, occurring within milliseconds. On the basis of these findings, we print gel microcilia arrays composed of a soft acrylic acid-co-acrylamide (AAc-co-AAm) hydrogel (modulus of approximately 1,000 Pa) that respond to electrical stimuli within milliseconds. Each microcilium measures 2–10 µm in diameter and 18–90 µm in height, achieving 3D rotational bending motion at up to 40 Hz, mirroring the geometry and dynamics of natural cilia. These gel microcilia maintain functionality after 330,000 continuous actuation cycles with less than 30% performance degradation. The gel microcilia arrays can be integrated on flexible polyimide substrates and fabricated at large scale using conventional lithography techniques. They also offer individual dynamic control by means of microelectrode arrays and enable fluid manipulation and particle transport at the micrometre scale.</p
Analysis of Chlorinated Microbially Derived Dissolved Organic Nitrogen: Linking Molecular Structure to Toxicological Risk
No full textDissolved organic nitrogen (DON) is an important precursor of nitrogenous disinfection byproducts (N-DBPs) during chlorination. As soluble microbial products (SMP) and extracellular polymeric substances (EPS) constitute important sources of DON in the water environment, understanding how their distinct compositional profiles influence DBP formation is critical for water safety assessment. This study systematically explored the chlorination reaction network of SMP and EPS, elucidating the structure and toxicological profiles of generated N-DBPs. The results showed that SMP, characterized by elevated aromaticity and humification, preferentially formed aromatic chlorinated DBPs (Cl-DBPs) through electrophilic aromatic substitution pathways. In contrast, EPS contained more labile protein with less ordered secondary structure, promoting N-DBP generation. Molecular network analysis showed that SMP primarily formed aromatic Cl-DBPs via lignin/tannin chlorination, whereas EPS generated more N-DBPs from proteins and lipids. Structural characterization via ultrahigh performance liquid chromatography-high resolution mass spectrometry proposed two predominant N-DBP classes: heterocyclic aromatic amines (high mammalian oral toxicity and developmental effects) and long-chain aliphatic amines (pronounced aquatic toxicity but minimal mammalian effects). This study provides critical insights into differential DBP formation pathways in chlorinated DON-rich water and highlights the necessity of multiend point toxicity assessment for water quality evaluation.</p
Mechanochemical Acceptor Engineering for NIR-I and NIR-II Fluorophores Enabling Orthogonal Ureter-Vascular Image-Guided Surgery
No full textAccurate intraoperative identification of the ureters and surrounding vasculature is essential for preventing iatrogenic injuries during laparoscopic surgery. While fluorescence imaging (FLI) offers a promising solution, conventional single-channel systems lack the capacity for multistructure anatomical differentiation. Here, we present a dual-channel near-infrared (NIR) FLI strategy facilitated by mechanochemistry-assisted acceptor engineering, which allows the subsequent screening of spectrally orthogonal fluorophores. Two of the resulting NIR fluorophores, TQx-FTA (NIR-I, λem = 755 nm) and TPzCl-FTA (NIR-II, λem = 1122 nm), exhibit large Stokes shifts of up to 280 nm, minimal spectral overlap, and high photostability. When formulated into nanoparticles, they enable high signal-to-background ratios and crosstalk-free imaging under white-light and 980 nm excitation. In rabbit models, both antegrade and retrograde infusion workflows provided high-contrast visualization of the ureters and vasculature. The system accurately detected ureteral pathologies, including strictures, obstructions, and injury-induced leakage, with quantitative fluorescence profiles confirming the anatomical precision. Compared to single-channel imaging, the dual-channel system offered a superior ability for structural differentiation. This integrated chemical and imaging platform overcomes key limitations in conventional FLI and offers a clinically translatable approach for high-resolution surgical navigation.</p
Coupling LED-Irradiated Photocatalyst-Embedded Hierarchically Porous Polymeric Optical Fibers with Residual Chlorine for Enhanced Emerging Contaminants Degradation in Decentralized Water Treatment System
No full textAddressing global water scarcity requires the development of efficient decentralized water treatment technologies. This study presents novel hierarchically porous TiO2-embedded polymeric optical fibers (TiO2-POFs) with a lotus-leaf-like bionic and micro/mesoporous structure for the removal of emerging contaminants (ECs). When coupled with UV-A LEDs and trace chlorine (5.0 mg/L), the system achieved a carbamazepine degradation rate constant of 0.0302 min-1 (1.167 cm2/μeinstein or 0.0143 cm2/mJ), which was 8.4 times that without chlorine, and a order of magnitude lower electrical energy per order (EE/O) of CBZ degradation (0.001 kWh/m3/order) compared to the median EE/O of the existing UVC-based AOPs. The enhancement was attributed to chlorine activation by photoinduced holes, electrons, and superoxide radicals, ultimately generating hydroxyl radicals (HO•), which were responsible for 99.4% of the degradation. The unique hydrophobic interface of TiO2-POFs confers a high affinity for hydrophobic pollutants and superior resistance to matrix quenching by hydrophilic natural organic matter. This enables the rapid degradation (within 2-5 min) of ECs at environmentally relevant (ng/L) levels in complex matrices like real tap water. The system maintained high activity after treating ∼454 L of tap water and exhibited excellent structural stability under an accumulated HO• exposure of ∼1.04 × 10-8 M·s. A 40% decrease was observed after high Cu2+ exposure, i.e., equivalent to treating 19,800 L of water due to copper oxide/hydroxide deposition. Simple acid washing using household vinegar or dilute nitric acid readily restores their activity. Furthermore, the process yielded less disinfection byproduct (DBP) compared to UV-C/chlorine due to the in situ adsorption and degradation of DBPs and their precursors. With its high selectivity, efficiency, safety, and stability, the UV-A-irradiated TiO2-POF chlorine process represents a highly promising strategy for safe and effective decentralized water purification.</p
Revealing the acoustic wave behaviour of lithium-ion batteries with a binder-connected poromechanical model
No full textUltrasonic non-destructive evaluation (NDE) of lithium-ion batteries (LIBs) has attracted increasing attention, yet the underlying wave propagation in porous, fluid-saturated electrodes remains insufficiently understood for accurate diagnostics. In this work, we develop the Binder-Spring-Biot (BSB) theory as an analytical model for ultrasonic wave propagation in LIB electrodes, a representative multiphase porous medium. By explicitly incorporating binder-mediated particle contacts into a spring–mass framework, the theory addresses the limitations of homogenized approaches such as Biot’s poroelasticity and slurry-based models. It predicts two distinct compressional modes whose velocities are governed by binder stiffness, thereby establishing a mechanistic link between microscale connectivity and measurable acoustic response. The theoretical predictions are rigorously validated through experiments across diverse electrode chemistries and architectures, showing strong agreement with measured wave velocities. Notably, the framework enables the clear experimental observation of the slow compressional wave in porous, fluid-saturated composites—a complex wave phenomenon. Together, these findings establish the BSB theory as a robust acoustics-based foundation for interpreting ultrasonic measurements in LIB electrodes and advance non-destructive methodologies for probing the internal state of batteries.</p
RBFOX2-dependent alternative splicing of Numb regulates Notch signaling during muscle stem cell activation
No full textSatellite cells (SCs) are somatic stem cells essential for skeletal muscle regeneration. Most SCs remain quiescent in resting muscle, but they rapidly activate in response to stimuli. Although post-transcriptional regulation has been implicated in SC functions, the role of alternative splicing (AS) during SC activation remains unclear. Using in vivo fixation to preserve quiescent SCs, we uncovered rapid and extensive AS changes upon activation, affecting genes involved in fundamental pathways. We identified RBFOX2 as a key AS regulator in SCs; its loss delayed both SC activation and muscle regeneration. Particularly, RBFOX2 promotes the inclusion of exon 6 in Numb , a Notch pathway regulator. This exon is required for SC activation, and its skipping delays activation while upregulating Notch signaling. Altogether, our study provides the AS landscape during SC activation and demonstrates that a single-gene splicing change can significantly influence SC activation and essential pathways such as Notch signaling.</p
Genetic programming control of self-excited thermoacoustic oscillations in a turbulent hydrogen–methane combustor
No full textThermoacoustic instabilities are a key challenge in developing sustainable combustion systems. In this experimental study, we present the first application of a data-driven machine learning algorithm based on genetic programming (GP) to suppress self-excited thermoacoustic oscillations in a turbulent premixed combustor operating with hydrogen-enriched fuels. The GP algorithm evolves model-free control laws via genetic operations such as replication, mutation, and crossover. Its performance is optimized through a cost function that balances the thermoacoustic amplitude reduction against the actuator power consumption. We evaluate GP in both closed-loop and open-loop configurations, benchmarking these against traditional open-loop time-periodic actuation. We find that GP closed-loop control proves superior in every metric evaluated, achieving the highest amplitude reduction with the lowest power consumption. This efficient suppression is physically achieved via synchronous quenching without resonant amplification, where GP actuation synchronizes the acoustic field and disrupts its coupling with the heat-release-rate (HRR) fluctuations of the flame. This disruption inhibits the formation of large-scale coherent vortices, resulting in a steadier HRR field decoupled from the acoustics, as evidenced by phase drifting and reduced Rayleigh index values. We also find that the GP algorithm is robust across varying reactant flow velocities, combustor lengths, and hydrogen concentrations, consistently yielding thermoacoustic amplitude reductions of 80%–94%. These findings establish GP as an effective, efficient and robust data-driven strategy for controlling thermoacoustic instabilities in turbulent combustion systems, including those fueled with hydrogen-enriched mixtures, advancing the development of sustainable energy technology. Novelty and significance statement: This experimental study is the first to apply genetic programming (GP) in both closed-loop and open-loop forms to suppress self-excited thermoacoustic oscillations in a turbulent combustor fueled by hydrogen- enriched mixtures. The GP algorithm discovers model-free control laws that achieve synchronous quenching (SQ) of the thermoacoustic mode by disrupting the flame–acoustic coupling, without resonant amplification of the actuation signal. GP closed-loop control outperforms both GP open-loop and conventional time-periodic forcing, achieving 80%–94% amplitude reduction across a range of Reynolds numbers, combustor lengths, and hydrogen power fractions while minimizing the actuation power. These results establish GP as an effective, efficient and robust strategy for active control of thermoacoustic instabilities in turbulent combustion systems, advancing sustainable energy technology.</p
Orchestrating Multi‑Agent Systems for End‑to‑End Climate Data Science Workflows
No full textClimate science relies on automated workflows to transform comprehensive research questions into data-driven insights over massive, heterogeneous datasets distributed across multiple data repositories. With the rise of large language models, automated workflow generation has become increasingly feasible. However, existing approaches face significant challenges: generic LLM agents lack domain-specific knowledge of climate data sources and analysis conventions, while static scripting pipelines cannot adapt to diverse task requirements or recover from execution failures. Consequently, existing methods struggle to reliably complete complex, multi-step climate analysis workflows. The CLIMATEAGENT framework is proposed to address these limitations through specialized multi-agent orchestration. The architecture decomposes high-level user questions into executable subtasks coordinated by a PLAN-AGENT, acquires data via specialized DATA-AGENTs that dynamically introspect API metadata to synthesize valid download scripts, and completes analysis with a CODING-AGENT that generates Python code, visualizations, and scientific reports through iterative self-correction. This design enables the system to maintain workflow coherence across dependent steps while adapting to execution failures without human intervention. To enable systematic evaluation, the CLIMATE-AGENT-BENCH-85 benchmark is introduced, comprising real-world tasks spanning six climate phenomena: atmospheric rivers, drought, extreme precipitation, heat waves, sea surface temperature, and tropical cyclones. Experiments demonstrate that CLIMATEAGENT substantially outperforms strong baselines including GitHub Copilot and direct GPT-5 synthesis across all evaluation dimensions, with particularly pronounced improvements in tasks requiring multi-step reasoning, heterogeneous data integration, and external tool coordination. These results establish that structured multi-agent orchestration with domain-specific knowledge integration and adaptive error recovery provides a viable path toward reliable, end-to-end automation of complex scientific workflows.</p
Applying semantic model for easy and fast deployment of chiller sequencing algorithm
No full textThough model predictive control (MPC) has demonstrated promising energy saving and load shifting potentials, however its widespread adoption in real buildings is limited, majorly because of the high engineering costs and lack of reusability of the current site-specific deployments. The high cost stems from cross-building data and system heterogeneity and the tight coupling of building-specific information with the MPC controller. This paper presents a semantic model based framework that is designed to address this deployment bottleneck. The framework achieves a smooth decoupling of control logic from building description, which is represented by Brick Schema to formally encode hardware topology, data points, and operational constraints as queryable metadata. This allows a generic controller to discover its entire operational context at runtime. The approach is made more accessible through a structured, template-driven workflow that streamlines the creation of the semantic model. The framework was evaluated through a simulation study and a field test on two large-scale, operationally distinct chiller plants. By deploying an identical controller codebase to both sites, an 80-85 % reduction in engineering effort was achieved compared to traditional deployment methods, providing a quantitative solution to the deployment challenge. A two-week field test further confirmed the framework’s effectiveness, demonstrating a 5.28 % system energy saving rate, which translates to an estimated annual electricity saving of 897,600 kWh, while maintaining a 99 % compliance rate for the chilled water supply temperature. This work provides a replicable, model-centric pathway for scalable building control. By lowering the marginal deployment cost and shifting the required expertise from custom programming to building systems knowledge, the proposed approach addresses key economic and talent-related barriers to the widespread adoption of advanced control technologies.</p