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At least 127 records · Page 7

Bio‐Imaging quorum sensing signal molecules in a soil‐mimic gel

Rhizosphere, the narrow region surrounding plant roots directly influenced by root exudates and the root associated microbiome, plays an important role in plant productivity and the rhizosphere is well known for stimulating microbial metabolic activities. How microbial communities interact to form stable, metabolically interconnected functional communities is an area of intense interest. The question remains on how microbially produced secreted molecules that function as intercellular communication signals shape the structure and function of microbial communities. Our goal is to detect and quantify signal molecules produced by microbes or plants in the root‐soil environment, spatially and temporarily. As a proof‐of‐concept, we are imaging diffusible extracellular microbial metabolites involved in a bacteria‐bacteria communication process called quorum‐sensing. Quorum‐sensing relies on the accumulation of high concentrations of signal molecules in the environment to control bacterial gene expression, influencing rhizosphere colonization and plant health. Local concentration of quorum sensing molecules are determined using aptamer based sensors. Aptamers that can specifically bind the desired signal molecules are selected through SELEX and immobilized on the surface of nano‐porous membranes. Binding of the signal molecules and aptamer covered surface results in changes in surface charge distribution and steric hinderance and thus modifying the transmembrane ionic transport. Changes in transmembrane impedance can be measured through electrochemical impedance spectroscopy methods to monitor local concentrations of signal molecules. Sensor responses were determined for different concentrations of signal molecules and results showed detection of C4‐HSL in a soil‐mimic solution with K D of 10 nM. We demonstrate that the quorum‐sensing signal molecule C4‐homoserine lactone and (C4‐HSL) can rapidly diffuse in a soil‐mimic gel, providing evidence for our use of a soil‐mimic for further aptasensor development and validation. The sensors were then inserted into soil mimic gel for monitoring C4‐HSL diffusion and the resulted impedance changes were used to determine the C4‐HSL concentration at different positions in the gel. Measurements of local C4‐HSL concentrations variation and numerical solution of diffusion equation were used to create 4D images of C4‐HSL molecule diffusion in the soil‐mimic gel.

Jiang, Nianyu↗

Squeezing-Enhanced Sensing at an Exceptional Point

Pushing the boundaries of measurement precision is central for sensing and metrology, pursued by nonclassical resources such as squeezing, as well as non-Hermitian degeneracies with distinct spectral response. Their convergence, however, remains challenging. We find extraordinary enhancement of sensitivity by unifying both effects in a general framework for quantum sensing in open systems. At the parametric oscillation threshold and an exceptional point, the sensing precision exhibits a unique quartic scaling with the perturbation strength. The result generalizes to multimode squeezed-state sensors with higher-order exceptional points catered to various quantum sensing platforms.

Wang, Changqing [Fermilab] (ORCID:0000000198073045↗

Passive Digital Sensing Method and Its Implementation on Passive RFID Temperature Sensors

Benefitting from the advancement of digital electronics in the 20 th century, sensors have also gradually evolved from analog to digital. As semiconductor components are required in digital sensors, a power supply is still needed for the sensor. To eliminate the need for a power supply a concept of passive digital sensing is proposed. Different from the semiconductor-based electrical digital sensing method, the parameter to be measured is first converted to a mechanical signal, then the mechanical signal is encoded to multiple digital bits by a passive digitizer, where each bit is identified as open or short state that is detectable by general IO ports. To demonstrate the proposed sensing concept, a passive RFID temperature sensor is implemented using a bimetallic coil as the temperature sensing unit. The 6-bit binary codes are acquired and transmitted by a passive RFID that is powered by an energy harvester. Furthermore, the test results show that the temperature sensor has a measurement sensitivity of 1.32 °C/bit and a working distance over 10 meters.

47 OTHER INSTRUMENTATION↗

DeepAndes: A Self-Supervised Vision Foundation Model for Multispectral Remote Sensing Imagery of the Andes

By mapping sites at large scales usingremotely sensed data, archaeologists can generate unique insights into long-term demographic trends, interregional social networks, and human adaptations in the past. Remote sensing surveys complement field-based approaches, and their reach can be especially great when combined with deep learning and computer vision techniques. However, conventional supervised deep learning methods face challenges in annotating fine-grained archaeological features at scale. In addition, while recent vision foundation models have shown remarkable success in learning large-scale remote sensing data with minimal annotations, most off-the-shelf solutions are designed for RGB images rather than multispectral satellite imagery, such as the eight-band data used in our study. In this article, we introduce DeepAndes, a transformer-based vision foundation model trained on three million multispectral satellite images, specifically tailored for Andean archaeology. DeepAndes incorporates a customized DINOv2 self-supervised learning algorithm optimized for eight-band multispectral imagery, marking the first foundation model designed explicitly for the Andes region. We evaluate its image understanding performance through imbalanced image classification, image instance retrieval, and pixel-level semantic segmentation tasks. Our experiments show that DeepAndes achieves superior F1 scores, mean average precision, and Dice scores in few-shot learning scenarios, significantly outperforming models trained from scratch or pretrained on smaller datasets. This underscores the effectiveness of large-scale self-supervised pretraining in archaeological remote sensing.

Guo, Junlin [Vanderbilt Univ., Nashville, TN (Unit↗

Passive sensing of a microparticle modified hybrid, fiber-reinforced composite

The widespread commercial adoption of high-performance, fiber-reinforced composites has pushed research interests toward the next generation of composites. These new composites are tasked with integrating additional functionalities into the structures without causing a trade-off in mechanical performance. One such functionality that has received significant interest is sensing. This is especially important for composites using high-performance fibers (e.g., carbon fiber) because their strain-to-failure is relatively low, resulting in brittle fracture. Besides, fiber damage can be hidden within the composite, potentially leading to premature catastrophic failure if not detected. In prior research, we demonstrated continuous feed-through deposition of ceramic nanoparticles on carbon fiber’s surface that simultaneously enhanced both the piezoresistive response and interlaminar shear strength. In this work, a similar continuous feed-through deposition process was used to demonstrate passive sensing and energy harvesting by integrating ferroelectric microparticles on the surface of electrically nonconductive fibers. The sensing and energy harvesting capabilities were characterized by mechanically straining composite beams and measuring the power generated. The improvements in mechanical properties are shown through interlaminar shear strength tests. Therefore, this research aims to demonstrate a high throughput, commercially scalable approach to coat fibers with ferroelectric microparticles that enable passive sensing as well as improved mechanical performance when fabricated into a fiber-reinforced composite.

Bowland, Christopher↗

2024 Workshop - Remote Sensing and Fluxes Upscaling for Real-world Impact - Tutorial v1

The software-tutorial was developed within the 2024 Remote Sensing and Fluxes Upscaling for Real-world Impact workshop as part of the hands-on session. The workshop was supported by AmeriFlux, National Ecological Observatory Network (NEON) and CarbonDew. The software provides basic tools to perform the following tasks: - gather remote sensing images using Google Earth Engine API; - gather flux data; - perform basic functions, such as plotting time-series, perform QA of the data, compute vegetation indices; - perform correlation analysis between flux data and remote sensing data; - perform flux predictions based on remote sensing data integrated in different modalities.

Falco, Nicola [Lawrence Berkeley National Laborato↗

Large-scale cascading of first-order FBG array in a highly multimode coreless fiber using femtosecond laser for distributed thermal sensing

This research focuses on the performance analysis and characterization of a fiber Bragg gratings (FBGs) array, consisting of 10 first-order FBGs inscribed by a femtosecond (FS) laser in a highly multimode coreless fiber. The study evaluates the FBG array's ability to function as a distributed thermal sensing (DTS) platform, with the coreless fiber chosen as the sensing element due to its immunity to dopant migration at high temperatures. The design of a large cascaded first-order FBG array effectively eliminates unwanted harmonic peaks across a wide spectrum range. In contrast, higher-order FBGs introduce limitations due to the overlapping of Bragg peaks with harmonics. The FBG array's performance is evaluated by measuring the reflection spectrum of each grating at different temperatures, showing a high temperature sensitivity of 15.05 pm/°C at a Bragg wavelength of 1606.3 nm, with a linear response in the temperature range of 24 - 1100 °C. The FBG array was designed for a spatial resolution of 5 mm. A mode scrambler in the sensing network is employed, which suppresses multimodal interference, characterizes FBG peak visibility, and stabilizes the interference spectrum. The stability of the FBG array is also assessed over 24 hrs at 1100 °C, and it is observed to be stable during thermal treatment. Heat treatment at 1100°C improves the signal to noise ratio of the FBG array, demonstrating the robustness and suitability of the proposed FBG array on highly multimode coreless fiber as a potential sensing platform for DTS applications in harsh environmental conditions, overcoming the issues of dopant migration presented by dopes silica optical fibers at high temperatures.

47 OTHER INSTRUMENTATION↗

Thin Film Hydrogen Sensor Development, Testing and Integration Into Low Cost Wireless Sensing Systems (SBIR Phase 1 Final Report)

Element One, Inc. is reporting on the results of its DOE SBIR Phase I project for the development and testing of low-cost thin film hydrogen sensors and their subsequent integration into wireless sensing systems and networks. This work is based on Element One’s chemo-chromic sensing technology which indicates hydrogen presence (leaks) colorimetrically and electronically with no power required. The lack of required power makes them particularly suitable for passive Radio Frequency Identification Device (RFID) technology which can be deployed affordably and abundantly to detect leaks in hazardous environments. Element One built upon its experience with chemochromic materials that change color in the presence of hydrogen. Both thin films and pigments have been used, but thin films have the ability to change conductivity by more than three orders of magnitude making them ideal for resistive sensors. Prototype sensors were fabricated, tested and characterized. For the wireless component, Element One partnered with Esensor, Inc. to construct and test a wireless sensing network. The network was tested and validated at the National Renewable Energy Laboratory (NREL) in February and March. The tests involved exposing the wireless system to hydrogen gas concentrations of 1% and 5%. There were no significant problems encountered, and the system is ready for commercial development. The system demonstrated the viability of wireless hydrogen sensing networks for hydrogen leak detection and other applications.

08 HYDROGEN↗

Second Annual Report on Development of Microwave Resonant Cavity Transducer for Fluid Flow Sensing

We are investigating a microwave resonant cavity transducer for flow sensing in the vessel of a high temperature fluid advanced reactor (AR), such as a molten salt cooled reactor (MSCR) or a sodium fast reactor (SFR). This transducer is a hollow metallic cylindrical cavity, with the flat wall of the cylinder flexible enough to undergo microscopic deflection due to dynamic fluid pressure. Membrane deflection leads to a shift in the resonant frequency, which can be detected with a spectrum analyzer. Because the transducer is intended for immersion in a high temperature corrosive fluid, understanding of material degradation is crucial for estimation of transducer performance lifetime, and development of measurement interpretation algorithms. We conducted a preliminary computational investigation of relevant damage mechanisms of a stainless steel 316 cylindrical resonator in FLiBe salt. The two main damage mechanisms, creep and corrosion, were modeled using multiphysics COMSOL software. Degradation was modeled for a temperature range 500°C to 700°C. Coupling of the damage mechanisms was not considered. These models predict significant inelastic deformation at most temperatures due to creep, and qualitatively predict chromium depletion both along the liquid/solid interface and along the grain boundaries. An algorithmic approach for compensation of these degradation effects during fluid flow measurements will be developed in the future work. To validate sensor physics, we have performed proof-of-principle test of flow sensing in water. For this test, we have developed a cylindrical resonator for K-band, which was machined from brass. The cavity was excited through WR-42 waveguide through a subwavelength hole on the side of the wall of the cylinder. To increase the spectral signal visibility, we developed a signal processing method for baseline subtraction. A flow loop for proof-of-principle test of transducer performance in water was assembled. A commercial flow meter was installed in the loop for reference measurements. Cylindrical cavity was excited in the TE 011 mode with resonant frequency f ≈ 17.8GHz. Frequency shift of cavity spectral response was obtained by gradually increasing water flow rate from 0 to 60gpm. Corresponding monotonic increase of resonant frequency shift by several MHz was observed. Approximate figure of merit of sensitivity to flow rate is 100KHz/GPM. In addition, we have identified an existing liquid sodium experimental setup for demonstration of flow sensing in environment similar to that of an advanced reactor. The setup consists of a cylindrical vessel and center feed line, where transducer inserted through the lid will measure velocity of the impinging liquid jet. As a calibration experiment, we have assembled a water vessel with center feed with the same dimensions as those of the liquid sodium setup. We have also developed and insertion probe consisting of a 50cm brass waveguide enclosed in protective SS316 tube. Using the water loop, we have demonstrated feasibility of sensing the impinging liquid jet in the vessel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Review: PFAS Adsorption, Sensing, and Remediation with Engineered Nanoporous Materials

Per- and polyfluoroalkyl substances (PFAS) are among the most abundant environmental contaminant species. They are widespread due to uncontrolled industrial and commercial use and have been linked to health risks such as cancer. With rising global concerns about the public health effects of PFAS, there is an incentive to develop strategies for reliable monitoring and effective PFAS removal, particularly in drinking water. Traditional PFAS sensing techniques are inefficient due to long measurement times, high labor input, high costs, and limitations to ex situ analysis. Current commercially available sorbents for PFAS removal generally lack the ability to capture PFAS components rapidly and quantitatively. Furthermore, existing sorbents are notably inefficient in removing the more toxic, smaller PFAS chemical chains. Large-scale applications of these methods tend to be costly and resource-intensive. Pacific Northwest National Laboratory has developed unique strategies for PFAS sensing and removal with capture probe technology that has an affinity for fluorocarbons, including PFAS. For both sensing and removal, the customizable capture probes can target specific PFAS compounds since they used a metal-organic framework (MOF)-based technology that can be fine-tuned and molecularly tailored. This tailoring of the materials enables high PFAS sensitivity, selectivity, and faster uptake. PNNL’s capture probe materials have been developed into a sensing technique based on the interactions of the capture probes with PFAS at the molecular level and further transduced that to a quantifiable electrochemical response. The materials have been integrated into a sensor platform developed by New Jersey Institute of Technology (NJIT). Tunable capture probes with a range of detection sensitivities allow for faster and more sensitive PFAS detection limits as low as what appears to be 0.5 ng/L (compared to the U.S. Environmental Protection Agency health advisory level of 70 ng/L). Customization of the capture probe results in improved sorption capacities (fast kinetics and high capacities) compared to commercial granular activated carbons. This research applied various experimental and modeling tools to improve understanding the molecular level interactions between the sorbents towards PFAS adsorption properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical aptamer-based sensors: leveraging the sensing platform for minimally-invasive microneedle measurements and fundamental exploration of sensor biofouling dynamics

The ability to track the concentrations of specific molecules in the body in real time would significantly improve our ability to study, monitor, and respond to diseases. To achieve this, we require sensors that can withstand the complex environment inside the body. Electrochemical aptamer-based sensors are particularly promising for in vivo sensing, as they are among the only generalizable sensing technologies that can achieve real-time molecular monitoring directly in blood and the living body. In this project, we first focused on extending the application space of aptamer sensors to support minimally-invasive wearable measurements. To achieve this, we developed individually-addressable sensors with commercial off-the-shelf microneedles. We demonstrated sensor function in buffer, blood, and porcine skin (a common proxy for human skin). In addition to the applied sensing project, we also worked to improve fundamental understanding of the aptamer sensing platform and how it responds to biomolecular interferents. Specifically, we explored the interfacial dynamics of biofouling – a process impacting sensors placed in complex fluids, such as blood.

59 BASIC BIOLOGICAL SCIENCES↗

Mercury Detection Utilizing an Aquatic Animal as a Remote-Sensing Platform

Mercury species in open water, especially the accumulated methylmercury ion, pose a threat to fish and environment. Therefore, it is important to develop a small sensor package that can be integrated into a biotelemetry sensor carried by an aquatic animal, enhancing the ability to detect mercury contamination in large water areas. A quartz crystal microbalance (QCM) sensor using metal-organic framework (MOF) as sensing material was developed to detect mercury and methylmercury ions in real time based on acoustic wave perturbation. Thiol groups were introduced into the MOF UiO-66 through the organic linker to prepare the UiO-66-SH which was confirmed by infrared spectroscopy results. Batch adsorption experiments were conducted for the Hg 2+ , CH 3 Hg + , and Ca 2+ ions adsorption in the UiO-66-SH. The adsorption capacities of the mercury ions were more than an order of magnitude higher than those of the competing Ca 2+ ions at the same concentration. The frequency changes of the QCM sensor with the UiO-66-SH sensing film were an order of magnitude higher than those of the controlled baseline QCM sensor without a sensing film. Additionally, the frequency change can be tailored by adjusting the thickness of the MOF film and the adsorption properties of the sensing material. The sensor frequency change correlates well with ion adsorption capacities.

47 OTHER INSTRUMENTATION↗

Functionalization of nitrogen vacancy-containing nanodiamonds with a metal-organic framework for quantum sensing applications

Nitrogen vacancy (NV)-containing nanodiamonds (NDs) are an important material in applications such as biological imaging, catalysis, and, in particular, quantum sensing. Careful manipulation of the surface coating on NV NDs is essential for both enhancing quantum sensor performance and for tuning selectivity towards specific sensing targets. Here, we demonstrate a simple synthetic approach for functionalizing NV NDs with the zeolitic imidazole framework-8 (ZIF-8) metal–organic framework (MOF), providing a well-ordered, porous scaffold for immobilizing target analytes near the NV ND surface. The composites were structurally characterized by x-ray diffraction, electron microscopy, and X-ray photoelectron spectroscopy, and these results were all consistent with NV NDs fully encapsulated by ZIF-8. Critically, the luminescent properties of the NV NDs, which are vital for quantum sensing experiments such as optically detected magnetic resonance (ODMR), are unchanged by the MOF coating. Moreover, spin relaxometry experiments indicate that the ZIF-8 coating significantly enhances the NV ND spin longitudinal relaxation time T1, a critical quantum parameter for sensing applications. Given the tremendous structural diversity of MOFs, the NV ND@MOF composites are an exciting material class with exciting implications for the development of high-performance quantum sensors.

Crawford, Scott↗

Remote Sensing and Fluxes Upscaling for Real-world Impact (Workshop Report)

The "Remote Sensing and Fluxes Upscaling for Real-world Impact" workshop, held on July 9-10, 2024, at Lawrence Berkeley National Lab, was a collaborative effort led by the AmeriFlux Management Project, NEON, and the Carbon Dew Community of Practice. The event brought together over 200 registrants and approximately 100 attendees each day, including leading experts, researchers, and practitioners. The primary focus was on bridging the gap between cutting-edge research and practical applications in environmental monitoring by integrating remote sensing and flux data. Key themes included the importance of site-level measurements for validating remote sensing products, providing nature-based climate solutions, and addressing challenges such as instrument costs and the need for standardized methods. At the regional scale, discussions centered on addressing spatial heterogeneity and using high-resolution remote sensing and machine learning methods to enhance data interpretation. Global scale challenges included data consistency, gap filling, and accurate emission source identification, with opportunities for international collaboration and standardized practices to improve global carbon budget assessments. The workshop emphasized the critical need for integrating data across local, regional, and global scales through explicit scale-matching and developed a workflow for scaling flux data using "straight shot" and "explicit nesting" approaches. The event highlighted the importance of connecting scientific research with real-world applications in carbon, energy, and water management, ensuring that advancements translate into tangible societal benefits. These insights will guide future research, technology transfer, and collaboration, maximizing the potential of environmental fluxes to address real-world challenges.

97 MATHEMATICS AND COMPUTING↗

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗

Best estimate of the planetary boundary layer height from multiple remote sensing measurements

Remote sensing measurements have been widely used to estimate the planetary boundary layer height (PBLHT). Each remote sensing approach offers unique strengths and faces different limitations. In this study, we use machine learning (ML) methods to produce a best-estimate PBLHT (PBLHT-BE-ML) by integrating four PBLHT estimates derived from remote sensing measurements at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory. Three ML models – random forest (RF) classifier, RF regressor, and light gradient-boosting machine (LightGBM) – were trained on a dataset from 2017 to 2023 that included radiosonde, various remote sensing PBLHT estimates, and atmospheric meteorological conditions. Evaluations indicated that PBLHT-BE-ML from all three models improved alignment with the PBLHT derived from radiosonde data (PBLHT-SONDE), with LightGBM demonstrating the highest accuracy under both stable and unstable boundary layer conditions. Feature analysis revealed that the most influential input features at the SGP site were the PBLHT estimates derived from (a) potential temperature profiles retrieved using Raman lidar (RL) and atmospheric emitted radiance interferometer (AERI) measurements (PBLHT-THERMO), (b) vertical velocity variance profiles from Doppler lidar (PBLHT-DL), and (c) aerosol backscatter profiles from micropulse lidar (PBLHT-MPL). The trained models were then used to predict PBLHT-BE-ML at a temporal resolution of 10 min, effectively capturing the diurnal evolution of PBLHT and its significant seasonal variations, with the largest diurnal variation observed over summer at the SGP site. We applied these trained models to data from the ARM Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) field campaign (EPC), where the PBLHT-BE-ML, particularly with the LightGBM model, demonstrated improved accuracy against PBLHT-SONDE. Analyses of model performance at both the SGP and EPC sites suggest that expanding the training dataset to include various surface types, such as ocean and ice-covered areas, could further enhance ML model performance for PBLHT estimation across varied geographic regions.

Zhang, Damao [Pacific Northwest National Laborator↗

COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

COVID-19, also known as SARS-CoV-2 is a novel, respiratory virus currently plaguing humanity. Genetically, at its core, it is a single-strand positive-sense RNA virus. It is a beta-type Coronavirus and is distinct in its structure and binding mechanism compared to other types of coronaviruses. Testing for the virus remains a challenge due to the small market available for at-home detection. Currently, there are three main types of tests for biomarker detection: viral, antigen and antibody. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) remains the gold standard for viral testing. However, the lack of quantitative detection and turnaround time for results are drawbacks. This manuscript focuses on recent advances in COVID-19 detection that have lower limits of detection and faster response times than RT-PCR testing. The advancements in sensing platforms have amplified the detection levels and provided real-time results for SARS-CoV-2 spike protein detection with limits as low as 1 fg/mL in the Graphene Field Effect Transistor (FET) sensor. Additionally, using multiple biomarkers, detection levels can achieve a specificity and sensitivity level comparable to that of PCR testing. Proper biomarker selection coupled with nano sensing detection platforms are key in the widespread use of Point of Care (POC) diagnosis in COVID-19 detection.

60 APPLIED LIFE SCIENCES↗

Template‐Directed Growth of Palladium Nanoparticles in Holey Single‐Layer Graphene for High‐Performance Room‐Temperature Hydrogen Sensing

Holey graphene (HG), formed by introducing nanoscale perforations into graphene sheets, combines the structural advantages of continuous sp 2 conjugation with the beneficial effects of high surface area and enhanced chemical reactivity associated with nanoscopic holes. Conventional HG fabrication methods often rely on harsh oxidative treatments that compromise graphene's intrinsic electronic properties by disrupting its sp 2 conjugation. A new approach is introduced to fabricate HG directly from single-layer graphene (SLG), using two-dimensional covalent organic frameworks (COFs) as a template followed by controlled oxygen plasma etching. This method preserves the integrity of the SLG's sp 2 network while producing well-defined holes with an average diameter of 2.7 nm. These hole edges act as reactive sites that facilitate the confined, autoreductive growth of palladium nanoparticles (PdNPs) without external reducing agents. The confined hole geometry prevents NP agglomeration and ensures a uniform size distribution. The resulting Pd@HG hybrid exhibits exceptional chemiresistive hydrogen sensing characteristics, including ultrahigh sensitivity, low detection limits, rapid response and recovery, and long-term stability under both dry and humid conditions. Mechanistic investigations reveal a two-step sensing process involving surface redox interactions and hydrogen absorption into the PdNP lattices. This strategy presents a scalable platform for integrating metal NPs within conductive carbon frameworks for advanced sensing applications.

chemical vapor deposition↗