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Microwave fracturing and assisted mechanical breakage of rocks has been demonstrated to be efficient and cost-effective, holding great potential in rock excavation. However, the size effect on the fracturing process using open-ended microwave antennas has not been well studied or understood. To address this issue, a dielectric-loaded converging antenna is used to heat and fracture diorite specimens of different dimensions. The study investigates the effect of specimen plane size and thickness, as well as microwave energy, on the crack characteristics. The results show that as specimen plane size increases, fracturing becomes more localized with shorter and narrower cracks. Conversely, specimen thickness is negatively correlated with crack characteristics on the microwave-treated surface. The study also defines and examines the representative elementary volume (REV) of microwave fracturing using the antenna. Regression models are developed and validated to predict crack characteristics such as number, density, total length, and maximum width. The paper concludes by discussing the arrangement of microwave radiations on rock masses with different joint spacings using the antenna.HighlightsThe effect of specimen plane size and thickness, as well as microwave energy, on the crack characteristics is comprehensively studied.The representative elementary volume (REV) of microwave fracturing using the DLCWA is defined and studied.Regression models are developed to predict crack characteristics such as number, density, total length, and maximum width.The arrangement of microwave radiation points of rock masses with different joint spacings using the DLCWA is proposed.

The Microwave Radiation Imager (MWRI) onboard the FengYun satellite plays a crucial role in global change monitoring and numerical weather prediction. Estimating and correcting geolocation errors are important to retrieving accurate geophysical variables. However, the instantaneous field of view (IFOV) inter-channel deviation, which is mainly caused by the structure mounting error and measurement error of feedhorns, is less studied. In this present study, we constructed a general theoretical model to automatically estimate the IFOV inter-channel deviations suitable for conical-scanning instruments. The model can automatically detect the along-track and across-track vectors that pass through the land–sea boundary points and are perpendicular to the actual coastlines. Regarding the midpoints of the vectors as the brightness temperature (Tb) inflection points, the IFOV inter-channel deviation is the pixel offset or distance of the maximum gradients of the Tb near the inflection points for each channel relative to the 89-GHz V-pol channel. We tested the model’s operational performance using the FY-3G/MWRI-Rainfall Mission (MWRI-RM) observations. Considering that parameter uploading adjusted the IFOV inter-channel deviations, the model’s validity was verified by comparing the adjustments calculated by the model with the theoretical changes caused by parameter uploading. The result shows that the differences between them for all window channels are less than 100 m, indicating the model’s effectiveness in evaluating the IFOV inter-channel deviation for the MWRI-RM. Furthermore, the estimated on-orbit IFOV inter-channel deviations for the MWRI-RM show that all channel deviations are less than 1 km, meeting the instrument’s design requirement of 2 km. We believe this study will provide a foundation for IFOV inter-channel registration of passive microwave payloads and spatial matching of multiple payloads.

This study addresses the challenge of radio‐frequency interference (RFI) in brightness temperature (BT) observations from China's FY‐3G satellite, a low‐inclination‐orbit platform equipped with a Microwave Radiation Imager (MWRI) designed for precipitation monitoring. To mitigate RFI contamination, we propose a deep neural network (DNN) framework that integrates multidimensional features, including interchannel correlations, topographic variables, and principal components, with particular emphasis on the complex conditions near land–sea boundaries. Validation using FY‐3G seasonal orbital data demonstrates outstanding performance, with simulated BTs achieving correlation coefficients greater than 0.999 and standard deviations below 0.5 K. An RFI index derived from residual analysis enables effective identification and correction of contamination, and results further show that in snow‐ and ice‐covered regions during winter, the proposed method significantly outperforms conventional techniques. The corrected BT dataset improves spatial and temporal consistency and provides reliable input for geophysical retrievals, including land surface temperature estimation, thereby confirming the practical applicability of the framework. Compared with existing approaches, the proposed method enhances generalization capability, improves detection accuracy, and reduces false alarms, ultimately establishing a robust quality control mechanism for the low‐frequency channels of FY‐3G MWRI. This study proposes a DNN‐based framework for RFI detection and correction in FY‐3G MWRI observations. The approach outperforms conventional methods, achieving superior accuracy in brightness temperature reconstruction. Enhanced datasets support downstream geophysical applications, establishing a robust quality‐control solution for operational satellite missions.

We investigated how different doses of microwave irradiation (MR) affect seed germination in Sorghum, including the level of remediation against textile and surgical wastewater (WW) by modulating biochemical and morpho-physiological mechanisms under glutamic acid (GA) application. The experiment was conducted to determine the impact of foliar-applied GA on Sorghum under wastewater conditions. Plants were treated with or without microwave irradiation (30 s, 2.45 GHz), GA (5 and 10 mM), and wastewater (0, 25, 50, and 100). Growth and photosynthetic pigments were significantly decreased in plants only treated with various concentrations of WW. GA significantly improved the plant growth characteristics both in MR-treated and -untreated plants compared with respective controls. HMs stress increased electrolyte leakage (EL), hydrogen peroxide (H2O2), and malondialdehyde (MDA) content; however, the GA chelation significantly improved the antioxidant enzymes activities such as ascorbate oxidase (APX), superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) both in MR-treated and -untreated plants under WW stress compared with respective controls. The results suggested that the MR-treated plants accumulate higher levels of HMs under GA addition in comparison to the WW-only-treated and MR-untreated plants. The maximum increase in Cd accumulation was observed in the range of 14–629% in the roots, 15–2964% in the stems, and 26–4020% in the leaves; the accumulation of Cu was 18–2757% in the roots, 15–4506% in the stems, and 23–4605% in the leaves; and the accumulation of Pb was 13–4122% in the roots, 21–3588% in the stems, and 21–4990% in the leaves under 10 mM GA and MR-treated plants. These findings confirmed that MR-treated sorghum plants had a higher capacity for HMs uptake under GA and could be used as a potential candidate for wastewater treatment.

Modern processes require innovative technological solutions meeting the requirements set forth to the environmental safety, lean production combined with efficiency. The results of studying the polymer composite materials in the form of fiberglass rebar cured inside a microwave unit are reported. The electromagnetic field oscillating at a frequency of 2450 MHz is capable of curing polymer composite materials. The thermosetting epoxy resins and glass fibers are used as binders and fillers. A uniform temperature profile is made inside the polymer composite material having a rod shape (with a diameter of 20 and 40 mm) using the microwave electrodynamic installation. It is confirmed that the microwave radiation energy as a heat source allows mastering a new level of producing polymer composite materials. The new materials feature better physics and mechanical properties. In addition, the use of microwave installations dramatically reduces the consumption of energy compared to regular techniques in making fiberglass rebar. The design parameters of microwave installations are presented, and estimates are given for fiberglass rebar heat treatment regimes. The temperature distribution profiles across the rods’ cross-section are obtained. The results can be applied in making polymer composite rods exposed to heat treatment.

The paper describes an original setup for studying the contribution of capillary waves in the range of wave numbers k = 100–1200 rad/m to the microwave radiation of the surface. A feature of the technical solution is the generation of an almost monochromatic capillary grid of waves on the surface of a flat vessel, which allows for a “pure” study of critical phenomena occurring in the microwave radiation of the surface at certain observation angles. The generation of capillary waves of a given frequency and amplitude was carried out by a thin bar on the surface and its oscillations were set by the author’s device located under the water surface. The shape of the resulting wave was recorded with the accuracy of 0.03 mm by an original method based on reflections from the surface. The vertical observation angle varied from 8° to 70° and the azimuthal rotation angles of the capillary grating changed by 360°. The microwave radiometer made it possible to measure variations in brightness temperature in four polarizations with the sensitivity of 0.1 K and with the accumulation time of 1 s. It was found that capillary waves with the amplitude of only 0.15–0.20 mm cause a resonant increase in the radiation intensity, reaching 5–6.5 K. Both the amplitude and the position of the resonant peak, which shifted to smaller elevation angles as the capillary wave length tended to the radiation wavelength, are consistent with the theory.

Passive multi-frequency microwave sensors are indispensable instruments for worldwide environmental monitoring. However, they often suffer from the issues of poor spatial resolution and the original land–sea transition zone data are contaminated severely. Conventional analytical deconvolution methods enhance the spatial resolution at the expense of noise amplification and Gibbs fluctuations in the land–sea transition zone. In order to enhance the spatial resolution as well as simultaneously enhance the integrity of the Microwave Radiometer data, a method based on Total Variation deconvolution, Bilateral Filter, and data fusion (TVBF+) is proposed. Our method substantially improves data integrity and obtains similar enhanced resolution compared to existing methods. Experiments performed using both simulated and actual microwave radiation Imager (MWRI) data demonstrate the method’s robustness and effectiveness.

Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination. This paper focuses on the newly launched Chinese FY-3G satellite’s Microwave Radiation Imager-Rainfall Mission (MWRI-RM) instrument, aiming to detect sun glint contamination and set a critical angle for data quality control. The model regression difference method is employed to simulate uncontaminated brightness temperatures at 10.65 GHz. By comparing the observed and simulated values, this study finds that sun glint contamination, which causes a 0–5 K increase in brightness temperature, is strongly related to sun glint angle. Based on the statistical analysis of contaminated pixels from November 2023 to July 2024, it is recommended that a critical angle of 25° be used to flag contaminated areas. The method also identifies persistent television frequency interference along the U.S. coastline at 18.7 GHz, which the radio frequency interference (RFI) Flag in Level 1 data failed to detect. Through the utilization of the model regression difference method, the warm biases in the MWRI-RM observations can be corrected. This research offers a practical way to enhance the accuracy of the MWRI-RM data and can be applied to other microwave radiometry missions.

Passive multi-frequency microwave remote sensing is often plagued with the problems of low- and non-uniform spatial resolution. In order to adaptively enhance and match the spatial resolution, an accommodative spatial resolution matching (ASRM) framework, composed of the flexible degradation model, the deep residual convolutional neural network (CNN), and the adaptive feature modification (AdaFM) layers, is proposed in this paper. More specifically, a flexible degradation model, based on the imaging process of the microwave radiometer, is firstly proposed to generate suitable datasets for various levels of matching tasks. Secondly, a deep residual CNN is introduced to jointly learn the complicated degradation factors of the data, so that the resolution can be matched up to fixed levels with state of the art quality. Finally, the AdaFM layers are added to the network in order to handle arbitrary and continuous resolution matching problems between a start and an end level. Both the simulated and the microwave radiation imager (MWRI) data from the Fengyun-3C (FY-3C) satellite have been used to demonstrate the validity and the effectiveness of the method.

Reconfigurable radio‐frequency components are in high demand for modern communication systems as they can be involved in multiband and multistandard electronic devices. The key part of such components is an active switching element. This work offers a way to obtain an efficient microwave switch using vanadium dioxide‐poly (methyl methacrylate) composite. Differential scanning calorimetry, SQUID magnetometery, and impedance spectroscopy measurements were used to characterize the phase transition in the proposed composite. Temperature induced metal‐insulator transition occurs at technologically attractive 341 K. The transition leads to a change of microwave transmission trough VO2‐PMMA composite from −4.9 dB for low‐temperature monoclinic form to −5.8 dB for high‐temperature rutile form. This provides an ability to tune the material's transparency in the microwave range, while the shaping polymer matrix provides the proper mechanical processability of the switching element. A route towards microwave radiation switching using a composite material, which consists of vanadium dioxide and poly (methyl methacrylate) matrix is reported in this work. VO2 displays a temperature induced metal‐insulator phase transition which provides an ability to tune the material's transparency in the microwave range, while the presence of polymer matrix allows to give necessary shape to the switching element.