Distribution Of Radiation Research Articles

Self-cooling in reverse biased p-InAsSbP/n-InAs0.9Sb0.1 heterostructures

2D thermal radiation distribution together with I–V and L–I characteristics has been measured and analyzed in forward and reverse biased p–n heterostructures based on InAs0.9Sb0.1 and grown onto n-InAs substrates. The measurements revealed a sufficient difference in the temperature distribution onto the sample surface at forward and reverse bias, which is explained by an impact of heat pump operation initiated by an electron–phonon interaction at the p–n junction and diode contacts at U < 0.

FLIP: a novel method for patient-specific dose quantification in circulating blood in large vessels during proton or photon external beam radiotherapy treatments

Purpose.To provide a novel and personalized method (FLIP, FLowand Irradiation Personalized) using patient-specific circulating blood flows and individualized time-dependent irradiation distributions, to quantify the dose delivered to blood in large vessels during proton or photon external beam radiotherapy.Methods.Patient-specific data were obtained from ten cancer patients undergoing radiotherapy, including the blood velocity field in large vessels and the temporal irradiation scheme using photons or protons. The large vessels and the corresponding blood flow velocities are obtained from phase-contrast MRI sequences. The blood dose is obtained discretizing the fluid into individual blood particles (BPs). A Lagrangian approach was applied to simulate the BPs trajectories along the vascular velocity field flowlines. Beam delivery dynamics was obtained from beam delivery machine measurements. The whole IS is split into a sequence of successive IEs, each one with its constant dose rate, as well as its corresponding initial and final time. Calculating the dose rate and knowing the spatiotemporal distribution of BPs, the dose is computed by accumulating the energy received by each BP as the time-dependent irradiation beams take place during the treatment.Results.Blood dose volume histograms from proton therapy and photon radiotherapy patients were assessed. The irradiation times distribution is obtained for BPs in both modalities. Two dosimetric parameters are presented: (i)D3%, representing the minimum dose received by the 3% of BPs receiving the highest doses, and (ii)V0.5 Gy, denoting the blood volume percentage that has received at least 0.5 Gy.Conclusion.A novel methodology is proposed for quantifying the circulating blood dose along large vessels. This methodology involves the use of patient-specific vasculature, blood flow velocity field, and dose delivery dynamics recovered from the irradiation machine. Relevant parameters that affect the dose received, as the distance between large vessels and CTV, are identified.

NEW APPROACHES TO CROSSLINKING IN COMBINATION WITH REFRACTIVE KERATOMODELING IN CORNEAL ECTASIA

Objective: To consider new approaches to crosslinking in combination with refractive keratomodeling in corneal ectasia of various etiologies.Methods: The work is based on clinical observations of the immediate and remote results of prophylactic and therapeutic corneal crosslinking with argon-fluorine excimer laser radiation (over 700 operations) over periods from 1 month to 13 years. Particular emphasis was placed on the formation of a Bowman-like membrane structure on the ablation surface and local exposure with a personalized gradient refractive profile of the total dose of radiation to achieve a greater keratomodeling effect. Rapid transition without additional calibrations to energy densities below the ablation threshold was carried out on the Russian excimer laser “Microscan Visum-500”.Results: Experimental and clinical studies have shown that excimer laser radiation on argon-fluorine can be used for corneal crosslinking, with energy densities in the pulse being below the ablation threshold. The advantage of excimer laser crosslinking was scanning with a narrow beam, which disrupts the oxygenation of the corneal stroma to a lesser extent and allows for the implementation of personalized local refractive keratomodeling based on keratotopography or aberrometry data. In this case, the induced secondary radiation covers all four peaks of maximum absorption by riboflavin. The use of subablative energy densities during irradiation of the cornea in the personalized PRK mode made it possible to locally affect the ectasia zone and enhance the refractive effect due to the gradient distribution of the total radiation dose.Conclusion: Radiation from an argon-fluorine excimer laser opens up new possibilities for refractive ablative and non-ablative refractive keratomodeling of the cornea in combination with laser-induced crosslinking in keratoconus and secondary keratoectasias of various etiologies.

CFD Analysis of UV-C Intensity Radiation Distribution and Inactivation of Foodborne Pathogens on Whole and Minimally Processed Mango

Ultraviolet shortwave (UV-C) is a technology for postharvest fruit disinfection. This study aimed to use computational fluid dynamics (CFD) based on the discrete ordinate (DO) radiation model to analyze the distribution of UV-C intensity on whole and minimally processed mangoes within a disinfection chamber and to predict treatments against foodborne pathogens. The mango spears were oriented both parallel and perpendicular to the lamp and positioned at varying distances from the radiation source (50, 75, and 100 mm for spears and 100 mm for whole fruit). CFD simulations integrated with in vitro kinetic parameters enabled predictions of the time and doses needed to inactivate one to three logarithmic units of pathogens on the fruit surface. The highest average radiation intensity values were recorded for the whole mango oriented parallel to the lamp at 100 mm and the spears oriented normally to the lamp at 50 mm. The estimated times to achieve inactivation of one to three logarithmic units of microorganisms ranged from approximately 15 to 6540 s, while the doses necessary for this inactivation were, on average, 1.854, 5.291, and 10.656 kJ/m2, respectively. CFD simulations are valuable for optimizing UV-C treatments in large-scale designing from both microbicide and sustainable perspectives.

Cherenkov radiation from relativistic heavy ions: interpretation in terms of diffraction

We demonstrate here the relationship between the diffraction theory and the theory of optical radiation in the vicinity of the Cherenkov cone from relativistic heavy ions taking account of the slowing-down in a radiator. We draw an analogy with the Huygens-Fresnel principle and demonstrate how the Cornu spiral, known in physical optics, is useful for qualitative and quantitative analysis of the shape and width of the non-trivial angular distributions of radiation.

PixPol: An In-Water Multispectral Polarized Upwelling Radiance Distribution Camera System

Abstract PixPol is an in-water multispectral polarized upwelling radiance distribution fisheye camera system. Its imaging sensors utilize a pixel-level polarizer structure allowing for polarimetric retrieval from one image capture, offering an advantage compared to other in-water polarimetric fisheye camera systems that require information from multiple images. When submerged, PixPol images a scene from which the first three Stokes parameters are derived at an angular resolution of 1° within a field of view that encompasses all azimuthal angles up to an elevation of 43° from nadir. For all viewing angles, Stokes parameter I and the linear polarization parameters, Q/I and U/I, are retrieved with an interpixel uncertainty of ±5%, ±0.02%, and ±0.02%, respectively. From these parameters, an uncertainty of ±0.01 is attained for the degree of linear polarization and ±0.9° for the angle of linear polarization. A description of the camera system, its radiometric and polarization calibration, and the associated uncertainties are described. Example images of the distribution of downwelling polarized light in the sky just above the ocean’s surface and upwelling polarized light just below the surface are provided.

External validation of a multimodality deep-learning normal tissue complication probability model for mandibular osteoradionecrosis trained on 3D radiation distribution maps and clinical variables

Background and purposeWhile the inclusion of spatial dose information in deep learning (DL)-based normal-tissue complication probability (NTCP) models has been the focus of recent research studies, external validation is still lacking. This study aimed to externally validate a DL-based NTCP model for mandibular osteoradionecrosis (ORN) trained on 3D radiation dose distribution maps and clinical variables. Methods and materialsA 3D DenseNet-40 convolutional neural network (3D-mDN40) was trained on clinical and radiation dose distribution maps on a retrospective class-balanced matched cohort of 184 subjects. A second model (3D-DN40) was trained on dose maps only and both DL models were compared to a logistic regression (LR) model trained on DVH metrics and clinical variables. All models were externally validated by means of their discriminative ability and calibration on an independent dataset of 82 subjects. ResultsNo significant difference in performance was observed between models. In internal validation, these exhibited similar Brier scores around 0.2, Log Loss values of 0.6–0.7 and ROC AUC values around 0.7 (internal) and 0.6 (external). Differences in clinical variable distributions and their effect sizes were observed between internal and external cohorts, such as smoking status (0.6 vs. 0.1) and chemotherapy (0.1 vs. −0.5), respectively. ConclusionTo our knowledge, this is the first study to externally validate a multimodality DL-based ORN NTCP model. Utilising mandible dose distribution maps, these models show promise for enhancing spatial risk assessment and guiding dental and oncological decision-making, though further research is essential to address overfitting and domain shift for reliable clinical use.

Incidence of malignant neoplasms and organizational aspects of cancer care in the Republic of Kazakhstan

BackgroundThis study aims to investigate the incidence and mortality rates of malignant neoplasms in Kazakhstan in 2022 and to analyze the organizational aspects of cancer care. MethodsData from 33,177 patients with malignant neoplasms registered in oncological institutions in 2022 were analyzed. The study focused on treatment completion rates and the distribution of treatment modalities, including surgical, radiation, medicinal, combined, comprehensive, and chemo-radiation therapies. Comparative analysis with international data was conducted to assess the effectiveness and adherence to global oncological standards. ResultsThe analysis revealed that 55.2 % of patients completed specialized treatment, with complex treatment being the most common modality (94.3 %). High completion rates were observed in breast cancer (65.9 %) and cervical cancer (68.8 %), reflecting the effectiveness of early detection and multidisciplinary approaches. However, lower completion rates were noted in liver cancer (26.2 %) and leukemia (23.0 %), highlighting the need for improved diagnostic and treatment strategies. Comparative international data indicated similar trends, with countries like the USA, UK, Japan, and Australia demonstrating the effectiveness of multidisciplinary and comprehensive treatment approaches. ConclusionThe study underscores the importance of a multidisciplinary approach in treating malignant neoplasms, with Kazakhstan's practices largely aligning with international standards. Nevertheless, there is a need to enhance early diagnosis and treatment completion rates for specific cancers such as liver cancer and leukemia. Strengthening screening programs, improving access to modern treatments, and integrating international best practices can further improve patient outcomes in Kazakhstan.

Spatial distribution of gamma rays produced by axially symmetric polarized and optical vortex lasers

The polarization properties and spatial distribution of electromagnetic radiation emitted from a high-energy electron can be calculated using the Lienard-Wiechert potentials. These properties are characterized by changes in electron orbitals. In Thomson or Compton scattering by relativistic electrons, which involves the interaction between electrons and a laser, the transverse motion of the electrons is induced by the laser's electric field. The polarization characteristics and spatial distribution of emitted radiation in linearly and circularly polarized laser fields have been extensively studied. In this paper, using a CdTe image sensor, the spatial distribution of MeV gamma rays generated by a 90-degree collision between a 750 MeV electron beam and an axially symmetric polarized laser was measured. The axially symmetric polarized laser, which includes radially and azimuthally polarized components, was created from a linearly polarized laser using a spatially variant retarder known as an s-waveplate. The spatial distribution of gamma rays exhibited a peak at the center, similar to linearly and circularly polarized gamma rays, but differed in overall contour from both. This result suggested that axially symmetric polarized lasers generated gamma rays with different polarization states. Moreover, the contour was observed to change with the polarization axis of the axially symmetric polarized laser, likely owing to the nonuniform distribution of the laser's polarization intensity. Additionally, the spatial distribution of gamma rays produced by circularly polarized optical vortex lasers was measured, showing that their contours corresponded to those of nonvortex circularly polarized lasers. Published by the American Physical Society 2024

Measurements of jet cross-section ratios in 13 TeV proton-proton collisions with ATLAS

Measurements of jet cross-section ratios between inclusive bins of jet multiplicity are performed in 140 fb−1 of proton-proton collisions with s=13 TeV center-of-mass energy, recorded with the ATLAS detector at CERN’s Large Hadron Collider. These ratios are constructed from double-differential cross-section measurements that are made in bins of jet multiplicity and other observables that are sensitive the energy scale and angular distribution of radiation due to the strong interaction in the final state. Additionally, the scalar sum of the two leading jets’ transverse momenta is measured triple differentially, in bins of the third jet’s transverse momentum and of jet multiplicity. These measurements are unfolded to account for acceptance and detector-related effects. The measured distributions are used to construct ratios of the inclusive jet-multiplicity bins, which have been shown to be sensitive to the strong coupling αS while being less sensitive than other observables to systematic uncertainties and parton distribution functions. The measured distributions are compared with state-of-the-art QCD calculations, including next-to-next-to-leading-order predictions for two- and three-jet events. These predictions are generally found to model the data well and perform best in bins with a modest requirement on the third jet’s transverse momentum. Significant differences between data and Monte Carlo predictions are observed in events with large rapidity gaps and invariant masses of the leading jet pair. Studies leading to reduced jet energy scale uncertainties significantly improve the precision of this work and are documented herein. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Radiation Limits the Yield Potential of Main Crops Under Selected Agrivoltaic Designs—A Case Study of a New Shading Simulation Method

Agrivoltaics (APVs) represent a growing technology in Europe that enables the co-location of energy and food production in the same field. Photosynthesis requires photosynthetic active radiation, which is reduced by the shadows cast on crops by APV panels. The design of the module rows, material, and field orientation significantly influences the radiation distribution on the ground. In this context, we introduce an innovative approach for the effective simulation of the shading effects of various APV designs. We performed an extensive sensitivity analysis of the photovoltaic (PV) geometry influence on the ground-incident radiation and crop growth of selected cultivars. Simulations (2013–2021) for three representative arable crops in eastern Austria (winter wheat, spring barley, and maize) and seven different APV designs that only limited to the shading effect showed that maize and spring barley experienced the greatest annual above-ground biomass and grain yield reduction (up to 25%), with significant differences between the APV design and the weather conditions. While spring barley had similar decreases within the years, maize was characterized by high variability. Winter wheat had only up to a 10% reduction due to shading and a reduced photosynthetic performance. Cold/humid/cloudy weather during the growing season had more negative yield effects under APVs than dry/hot periods, particularly for summer crops such as maize. The lowest grain yield decline was achieved for all three crops in the APV design in which the modules were oriented to the east at a height of 5 m and mounted on trackers with an inclination of +/−50°. This scenario also resulted in the highest land equivalent ratios (LERs), with values above 1.06. The correct use of a tracker on APV fields is crucial for optimizing agricultural yields and electricity production.

A 10 km daily-level ultraviolet-radiation-predicting dataset based on machine learning models in China from 2005 to 2020

Abstract. Ultraviolet (UV) radiation is closely related to health; however, limited measurements have hindered further investigation of its health effects in China. Machine learning algorithms have been widely used to predict environmental factors with high accuracy, but a limited number of studies have implemented it for UV radiation. The main aim of this study is to develop a UV radiation prediction model using the random forest approach and predict the UV radiation with a daily and 10 km resolution in mainland China from 2005 to 2020. The model was developed with multiple predictors, such as UV radiation data from satellites as independent variables and ground UV radiation measurements from monitoring stations as the dependent variable. Missing satellite-based UV radiation data were obtained using the 3 d moving average method. The model performance was evaluated using multiple cross-validation (CV) methods. The overall R2 and root mean square error between measured and predicted UV radiation from model development and model 10-fold CV were 0.97 and 15.64 W m−2 and 0.83 and 37.44 W m−2 at the daily level, respectively. The model that incorporated erythemal daily dose (EDD) retrieved from the Ozone Monitoring Instrument (OMI) had a higher prediction accuracy than that without it. Based on predictions of UV radiation at the daily level, 10 km spatial resolution, and nearly 100 % spatiotemporal coverage, we found that UV radiation increased by 4.20 %, PM2.5 levels decreased by 48.51 %, and O3 levels increased by 22.70 % from 2013–2020, suggesting a potential correlation among these environmental factors. The uneven spatial distribution of UV radiation was associated with factors such as latitude, elevation, meteorological factors, and season. The eastern areas of China pose a higher risk due to both high population density and high UV radiation intensity. Using a machine learning algorithm, this study generated a gridded UV radiation dataset with extensive spatiotemporal coverage, which can be utilized for future health-related research. This dataset is freely available at https://doi.org/10.5281/zenodo.10884591 (Jiang et al., 2024).

First experimental confirmation of island SOL geometry effects in a high radiation regime on W7-X

Abstract This work characterizes the detachment behavior and radiation characteristics of the low
iota configuration in the Wendelstein 7-X (W7-X) stellarator. The island scrape-off layer (SOL) of the
low iota has a poloidal mode number of 6 islands surrounding the last closed flux surface (LCFS).
The island geometry of the low iota configuration is significantly different to that of the standard
magnetic field configuration, whose detachment characteristics have already been described in previous
work[2, 3, 4]. Experimental results show that the radiation pattern in the low iota configuration
is starkly different to that of the standard magnetic field configuration, with radiation concentrated
at the island SOL O-points, rather than the X-points. Additionally, this O-point localized radiation
pattern is associated with unstable detachment, with both radiation oscillations in experiments and the
lack of a self-consistent plasma solution at high radiated power fraction in EMC3-Eirene simulations.
EMC3-Eirene simulations are used to understand the radiation distribution. It was found that the O-
point localized radiation arises first from local impurity accumulation near the parallel flow stagnation,
which is located close to the geometrical center of the island (”O-point”). The local cooling in this
region leads to plasma condensation in the islands in closest magnetic connection to the divertor target
plates. The heat source to this region of the island, which is thermally isolated from the upstream heat
source in terms of parallel transport, must arise via perpendicular heat transport. This heat source is
expected to be large for the low iota configuration due to its very small internal island field line pitch.
This work highlights the importance (complementary to previous work, e. g. [5, 6]) of the internal
island field line pitch not only on the radiation pattern, but also the detachment performance of the
island divertor.

Quantifying the effects of spectral and directional distribution of radiation on its propagation in saline water

The interactions of radiation with saline water facilitate various energy-related applications, such as radiative evaporation at the air–water interface, radiation-driven underwater vapor generation, and underwater photovoltaic systems. However, these applications require a comprehensive understanding of radiation propagation through saline water, considering both its spectral and directional characteristics, which are often inadequately explored. This study introduces a three-dimensional Monte Carlo radiative transfer model equipped with fine spectral resolution and detailed angular considerations. The model simulates the transfer of radiation from the air to the air–water interface and throughout the saline water body to thoroughly examine the effects of spectral and directional properties of incident radiation on its propagation across different depths of saline water. The findings reveal that within the solar spectrum, radiation entering the water at a 62.7-degree angle of incidence and completely diffuse radiation exhibit similar absorption effects in water layers less than 2 meters deep. In addition, the incident angle has little impact on the absorption rate of both the water surface and the water body when the angle is below 62.7°. Spectrally, radiation wavelengths longer than 1.4μm, 1.14μm, and 1μm are fully absorbed within the first 1, 8, and 50 centimeters of saline water, respectively, representing approximately 20%, 30%, and 50% of incident solar radiation. Additionally, radiation from blackbody sources below 1300 Kelvin is absorbed entirely within the top 1 centimeter of saline water. Empirical correlations are then developed to easily estimate the absorption rate based on the depth of the water and the temperature of the blackbody heat source. The findings elucidate the influence of the spectral and directional characteristics of incident radiation on its underwater propagation, offering essential guidance for the design and performance evaluation of various energy-centric applications.

Research on a three-dimensional radiation field reconstruction algorithm based on an improved 3D CNN

This article investigates the application of an improved three-dimensional convolutional neural network (3D CNN) for sparse data-based reconstruction of radiation fields. Sparse radiation data points are consolidated into structured three-dimensional matrices and fed into a self-attention integrated CNN, enabling the network to interpolate and produce complete radiation distribution grids. The model’s validity is assessed through experiments with randomly sourced radiation in scenarios both with and without shielding, as well as in refined grid configurations. Results indicate that in unshielded environments, a mere 5%(15 points) sampling yields an average relative error of 4%, while in shielded settings, a 7% (21 points) sampling maintains the error around 11%. In refined grid contexts, a 2% sampling rate suffices to limit the error to 6.58%. Thus, the improved 3D CNN is demonstrated to be highly effective for precise three-dimensional radiation field reconstruction in sparse data scenarios.

Analyzing the effects of shading on power output in curved photovoltaic array on airship

This study investigates the use of photovoltaic (PV) arrays on airships, focusing on challenges due to the curved structure that affects solar radiation distribution. A novel Photo-Thermal-Electric Model (PTEM), developed in MATLAB/Simulink, is introduced to simulate PV array behavior under various conditions, including the impact of solar altitude, laying angle, and airship flight attitude on power generation. PTEM's effectiveness is demonstrated through detailed power output graphs, revealing that radiation gradients significantly affect power generation, often leading to overestimations in the Photo-Thermal Model (PTM) model by 3 %–30 %. Comparative analysis shows that PTEM provides more accurate energy output estimates for individual PV modules, especially in areas with pronounced radiation gradients, differing from PTM estimates by hundreds of watts. These findings offer valuable insights for enhancing PV module lifespan and optimizing energy system designs, contributing to more efficient renewable energy solutions for long-endurance aircraft.

Investigating the radiative properties of large dust aggregate particles via the Monte Carlo ray tracing method

Understanding the radiative properties of particles is essential for interpreting and analyzing atmospheric remote sensing, target detection, combustion diagnostics, etc. At present, there is a relative lack of studies and understanding of the radiative properties of large aggregate particles. In this work, we comprehensively investigate the radiative properties of large dust aggregate particles via the developed Monte Carlo ray tracing method. Large dust aggregate models with monodisperse and polydisperse monomers are constructed, respectively. The effects of various factors on the radiative properties of large dust aggregate particles are analyzed. We find that the larger geometric standard deviation and the greater number of monomers lead to slightly larger backscattering and an increase of the overall radiative energy distribution on the receiving surface. With increasing the size parameter, the scattering phase function becomes smoother and the difference between the scattering phase function of spheres and aggregates diminishes. The absorptivity is proportional to the size parameter and inversely proportional to the number of monomers. At a size parameter of 100, the absorptivity and the peak of the radiative energy distribution of monodisperse monomer aggregates are higher than those of polydisperse monomer aggregates, and gradually converge with the increase of particle size parameter. Overall, this work helps to enhance the knowledge of the radiative properties of large aggregate particles.

Spatio-temporal Kriging for spatial irradiance estimation with short-term forecasting in a thermosolar power plant

This article proposes a method to improve the efficiency of solar power plants by estimating and forecasting the spatial distribution of direct normal irradiance (DNI) using a sensor network and anemometer data. For this purpose, the proposed approach employs spatio-temporal kriging with an anisotropic spatio-temporal variogram that depends on wind speed to accurately estimate the distribution of DNI in real-time, making it useful for short-term forecast and nowcast of DNI. Finally, the method is validated using synthetic data from varying sky conditions, outperforming another state-of-the-art technique.

Simulation model for electrical and agricultural productivity of an olive hedgerow Agrivoltaic system

Given the need to promote a more sustainable energy model that contributes to the fight against Climate Change and the consequent advancement of photovoltaics, Agrivoltaics is presented as a solution to the conflict over land use, since it makes it possible to reconcile agricultural production and photovoltaic power simultaneously on the same piece of land. However, it is a new production model and there are still many aspects to research. This work presents a mathematical model to simulate the spatial distribution of the solar radiation in the canopy of the crop of an agrivoltaic plant in which N-S solar trackers are alternately combined with olive groves in hedgerows. In this way, simulation has the advantage of predicting the expected behaviour of one or more configurations of agrivoltaic installations and, on the basis of this simulated behaviour, making decisions during the design phase to optimize their performance. To do this, various models have been integrated to simulate both the behaviour of irradiance on its way from the Sun to the crop, using geometric-vector analysis, and the irradiance absorption processes on its way through the canopy of the crop. Thus, the global model presented allows estimating the electrical and oil production of an agrivoltaic plant such as the one described. From this global model, electrical and oil productions have been systematically simulated for a set of agrivoltaic plants whose design parameters range around the intermediate values of an agrivoltaic facility with olive groves in hedgerows spaced 10 m apart and alternated with 3 m wide and 3 m hight N-S solar trackers. For this intermediate facility, the annual productions of oil and electricity are 789kg/year·ha and 891MWh/year·ha, respectively. Finally, the oil and energy productions of all the simulated agrivoltaic facilities and their design parameters have been interrelated obtaining mathematical equations to determine in a simple way the influence on the productions of the geometrical design variables of the agrivoltaic installation (height of the solar trackers, width of the collectors and distance between hedgerows). Therefore, the model presented makes it possible to advance in the evaluation of the possible integration of olive groves in agrivoltaic systems and their profitability, constituting an important benefit for the implementation of agrivoltaics in the Mediterranean regions where olive groves play a significant role in agricultural production systems.

Single-image SVBRDF estimation with auto-adaptive high-frequency feature extraction

In this paper, we address the task of estimating spatially-varying bi-directional reflectance distribution functions (SVBRDF) of a near-planar surface from a single flash-lit image. Disentangling SVBRDF from the material appearance by deep learning has proven a formidable challenge. This difficulty is particularly pronounced when dealing with images lit by a point light source because the uneven distribution of irradiance in the scene interacts with the surface, leading to significant global luminance variations across the image. These variations may be overemphasized by the network and wrongly baked into the material property space. To tackle this issue, we propose a high-frequency path that contains an auto-adaptive subband “knob”. This path aims to extract crucial image textures and details while eliminating global luminance variations present in the original image. Furthermore, recognizing that color information is ignored in this path, we design a two-path strategy to jointly estimate material reflectance from both the high-frequency path and the original image. Extensive experiments on a substantial dataset have confirmed the effectiveness of our method. Our method outperforms state-of-the-art methods across a wide range of materials.