Separation Parameters Research Articles

Angular-Spectral Characteristics of Acousto-Optic Tunable Filters Based on Mercurous Halide Crystals.

The angular and spectral properties crucial for the functionality of acousto-optic (AO) devices are determined by phase-matching geometries in AO interactions. In applications such as spectral imagers based on acousto-optic tunable filters (AOTFs), systematic throughput is constrained by the angle separating diffracted and transmitted light. This research introduces an analytical model that elucidates the angular-spectral properties of diffracted beams in mercurous halide crystals. These crystals possess a wide transmissive spectral range, from visible light to long-wave infrared light. The study computes and confirms correlations between the separation angle and parameters including incident angle, polarization, acoustic angle, and crystal birefringence. Experimental validation conducted on mercurous halide and tellurium dioxide crystals demonstrates that higher birefringence in crystals significantly amplifies the separation angle, augmenting the device's performance. The study contributes to the development of devices with large separation angles during the design phase, enhancing systematic throughput in spectral imaging applications.

Hybrid assessments of the progress of hybrid economic systems

Subject. The article addresses the development of enterprises of the Russian military-industrial complex, improvement of the combat capability of the Armed Forces. Objectives. The focus is on the analysis of military component as a separate parameter of the gross domestic product determining the probability of the country's survival. Methods. The study employs tools of economic and mathematical modeling. Results. We developed a probabilistic statistical model of the economic system, which will improve the feasibility of managerial decisions, taking into account the military component. Conclusions. The findings of the study can be taken into account in the implementation of Russia's defense capability strengthening programs.

Analysis of a Reiner–Rivlin liquid sphere enveloped by a permeable layer

The present article investigates the axisymmetric flow of a steady incompressible Reiner–Rivlin liquid sphere enveloped by a spherical porous layer using the cell model technique. The Brinkman-extended Darcy model is deployed for the porous medium hydrodynamics, and isotropic permeability is considered. The stream function solutions of the governing equations are obtained, which involves the Gegenbauer functions and the modified Bessel functions. An asymptotic series expansion in terms of the Reiner–Rivlin liquid parameter S has been employed to determine the expression of the flow field for the Reiner–Rivlin liquid. Boundary conditions on the cell surface corresponding to the Happel, Kuwabara, Kvashnin, and Cunningham models are considered. Analytical expressions are derived for dimensionless pressure, tangential stress, and the couple stress components using the method of separation of variables and Gegenbauer functions/polynomial. The integration constants are evaluated with appropriate boundary conditions on the inner and outer boundary of the porous zone with the aid of Mathematica symbolic software. Solutions for the drag force exerted by the Reiner–Rivlin fluid on the porous sphere are derived with corresponding expressions for the drag coefficient. Mathematical expression of the drag coefficient, pressure distribution, velocity profile, and separation parameter is established. On the basis of viscosity ratio, permeability parameter, dimensionless parameter, and the volume fraction, variations of the drag coefficient, velocity profiles, fluid pressure, and separation parameter (SEP) are investigated with their plots. The effects of the streamline pattern make the flow more significant for the Mehta–Morse when compared to the other models. Additionally, the mathematical expression of the separation parameter (SEP) is also calculated, which shows that no flow separation occurs for the considered flow configuration and is also validated by its pictorial depiction. This problem is motivated by emulsion hydrodynamics in chemical engineering where rheological behavior often arises in addition to porous media effects.

Multiplatform High-Definition Ion Mobility Separations of the Largest Epimeric Peptides.

Ion mobility spectrometry (IMS) coupled to mass spectrometry (MS) has become a versatile tool to fractionate complex mixtures, distinguish structural isomers, and elucidate molecular geometries. Along with the whole MS field, IMS/MS advances to ever larger species. A topical proteomic problem is the discovery and characterization of d-amino acid-containing peptides (DAACPs) that are critical to neurotransmission and toxicology. Both linear IMS and FAIMS previously disentangled d/l epimers with up to ∼30 residues. In the first study using all three most powerful IMS methodologies─trapped IMS, cyclic IMS, and FAIMS─we demonstrate baseline resolution of the largest known d/l peptides (CHH from Homarus americanus with 72 residues) with a dynamic range up to 100. This expands FAIMS analyses of isomeric modified peptides, especially using hydrogen-rich buffers, to the ∼50-100 residue range of small proteins. The spectra for d and l are unprecedentedly strikingly similar except for a uniform shift of the separation parameter, indicating the conserved epimer-specific structural elements across multiple charge states and conformers. As the interepimer resolution tracks the average for smaller DAACPs, the IMS approaches could help search for yet larger DAACPs. The a priori method to calibrate cyclic (including multipass) IMS developed here may be broadly useful.

Enlightening the Universe behind the Milky Way bulge

Context. The location of the Solar System complicates the detection extragalactic sources beyond the Milky Way plane. The optical observations are hampered in the so-called zone of avoidance (ZOA), where stellar crowding and Galactic absorption are severe. Observations at longer wavelengths are needed in order to discover new background galaxies and complete the census in the ZOA. Aims. The goal of this work is to identify galaxies behind the Milky Way bulge using near-infrared (NIR) data from the VISTA Variables in Vía Láctea (VVV) survey. Methods. To this end, we made use of different VISTA Science Archive (VSA) tools in order to extract relevant information from more than 32 billion catalogued sources in the VVV bulge region. We find that initial photometric restriction on sources from the VSA vvvSource table combined with restrictions on star–galaxy separation parameters obtained from Source Extractor is a successful strategy for achieving acceptable levels of contamination (60%) and high completeness (75%) in the construction of a galaxy target sample. To remove contaminating Galactic sources from the initial target sample, our methodology also incorporates a visual inspection of false-colour RGB images, a crucial quality control carried out following a specifically defined procedure. Results. Under this methodology, we find 14 480 galaxy candidates in the VVV bulge region, making this sample the largest catalogue to date in the ZOA. Moreover, these new sources provide a fresh picture of the Universe hidden behind the curtain of stars, dust, and gas in the unexplored Milky Way bulge region. Conclusions. The results from this work further demonstrate the potential of the VVV/VVVX survey to find and study a large number of galaxies and extragalactic structures obscured by the Milky Way, expanding our knowledge of the Universe in this challenging and impressive region of the sky.

Mathematical modelling of couple stress fluid flow around a semi‐permeable sphere enclosing a solid core

AbstractThe focus of this article is to study theoretically the steady‐axisymmetric creeping flow dynamics of a couple stress fluid external to a semi‐permeable sphere containing a solid core. This problem is motivated by emulsion hydrodynamics in chemical engineering where rheological behaviour often arises in addition to porous media effects. The non‐Newtonian Stokes’ couple stress fluid model features couple stresses and body couples that are absent in the classical Navier–Stokes viscous model. It provides a robust framework for simulating emulsions, complex suspensions and other liquids which possess microstructure. The physical regime is delineated into two zones – the interior of the semi‐permeable zone (region II) which engulfs the solid core and the external couple stress fluid zone (region I). The model is formulated using a spherical polar coordinate system in terms of the stream function ψ. The Brinkman‐extended Darcy model is deployed for the porous medium hydrodynamics and isotropic permeability is considered. Analytical expressions are derived for dimensionless pressure, tangential stress and the couple stress components using the method of separation of variables and Gegenbauer functions of the first kind. The integration constants are evaluated with appropriate boundary conditions on the inner and outer boundary of the semi‐permeable zone with the aid of Mathematica symbolic software. Solutions for the drag force exerted by the couple stress fluid on the semi‐permeable sphere and volumetric flow rate are also derived with corresponding expressions for the drag coefficient and non‐dimensional volumetric flow rate. The influence of permeability (k), separation parameter (l), couple stress viscosity coefficient (η), couple stress inverse length dependent parameter (λ = √(μ/η)) and couple stress viscosity ratio (τ = η/η/) on all key variables is studied graphically. Additionally, streamline contours are computed for a range of parameters including inverse permeability parameter (α = 1/k). The computations show that increasing couple stress inverse length dependent parameter (λ) greatly reduces the dimensionless volumetric flow rate in particular at high values of separation parameter (l). Flow rate is, however, markedly enhanced with permeability (k) and also couple stress viscosity parameter (η). In the presence of the solid core, a much greater drag coefficient is observed at all values of couple stress inverse length dependent parameter (λ) relative to the case without a solid core. A significant distortion in streamlines is computed with increasing separation parameter (l) with a dual vortex structure emanating. With greater couple stress viscosity parameter (τ), no tangible modification is observed in the streamline contours. The present work generalizes the earlier study of Krishnan and Shukla to consider a semi‐permeable (porous medium) outer sphere and furthermore presents detailed streamline visualizations of the creeping flow for a range of emerging parameters of relevance to non‐Newtonian chemical engineering processes including emulsion droplet dynamics in porous materials.

Small-Occupation Density Functional Correlation Energy Correction to Wave Function Approximations.

In this work, we introduce a novel hybrid approach, termed WFT-soDFT, designed to seamlessly incorporate DFT correlation into wave function ansatzes. This is achieved through a partitioning of the orbital space, distinguishing between large and small natural occupation numbers associated with wave function theory (WFT) and DFT correlation, respectively. The method uses a novel criterion for partitioning the orbital space and mapping the electron density in natural orbitals with a small occupation with the correlation energy of fast electrons within the homogeneous electron gas. Central to our approach is the introduction of a separation parameter ν, the choice of the WFT approach, and the correlation functional. Here, we combine the RASCI wave function with hole and particle truncation with a local density correlation functional to only account for small-occupation correlation energy. We investigate the performance of the method in the study of small but challenging chemical systems, for which WFT-soDFT demonstrates notable improvements over pristine wave function calculations. These findings collectively highlight the potential of the WFT-soDFT approach as a computationally affordable strategy to improve the accuracy of WFT electronic structure calculations.

Study on the behavior of clusters in the physical recovery of GaAs scrap

Gallium arsenide (GaAs) is the most widely used second-generation semiconductor material. However, a large amount of GaAs scrap is generated at various stages of the GaAs wafer production process. Volatile GaAs clusters are inevitably generated during the process of GaAs vacuum thermal decomposition, resulting in lower purity of the recovered arsenic and the loss of gallium. In this study, thermodynamic analysis and dynamics simulation were combined to discuss the possibility of separating GaAs clusters and arsenic from a microscopic perspective. A vacuum thermal decomposition-directional condensation recovery process for GaAs scrap was proposed. By properly adjusting the separation parameters such as heating temperature, holding time and raw material size, high purity of gallium (99.99%) and arsenic (99.5%) were directly recovered under a system pressure of 1 Pa, heating temperature of 1323 K, holding time of 3 h, and GaAs scrap size of 2.5 cm. GaAs clusters were also recovered in powder form. The problem of difficult separation of GaAs clusters from arsenic was effectively solved by this method, and the purity of recovered arsenic was greatly improved. No additives are required and no waste liquid or gas emission in the whole process. The complexity of subsequent arsenic purification operations and the threat of arsenic containing waste to the environment were reduced as well.

A comparison of QTP functionals against coupled-cluster methods for EAs of small organic molecules.

EA-EOM-CCSD electron affinities and LUMO energies of various Kohn-Sham density functional theory (DFT) methods are calculated for an a priori IP benchmark set of 64 small, closed-shell molecules. The purpose of these calculations was to investigate whether the QTP KS-DFT functionals can emulate EA-EOM-CC with only a mean-field approximation. We show that the accuracy of DFT-relative to CCSD-improves significantly when elements of correlated orbital theory are introduced into the parameterization to define the QTP family of functionals. In particular, QTP(02), which has only a single range separation parameter, provides results accurate to a MAD of <0.15eV for the whole set of 64 molecules compared to EA-EOM-CCSD, far exceeding the results from the non-QTP family of density functionals.

Study on mechanical and micro structural properties of spin arc welding in Hastelloy C-2000

Nickel-based Hastelloy C-2000 is widely used in the aerospace, chemical, and medicinal sectors. Investigating the potential efficacy of the spin arc welding process on Hastelloy C-2000 was the main focus of this study. In spin arc welding the centrifugal force has been obtained in the fusion zone, thus the weldbead quality increases. Weld current, rotating speed, and spin diameter are all separate parameters used in the welding procedure. The microstructural investigation was carried out using optical microscopy, X-Ray Diffraction (XRD), and field emission scanning electron microscopy (FESEM). The mechanical characteristics of the welded specimens were examined closely. Spin Arc Welding ultimate tensile strength (UTS), hardness value (HV), and impact experiments were compared to those of the Multi-pass Pulsed Current Gas Tungsten Arc welding method (MPCGTAW). In 27 tests, increasing the current and rotating speed resulted in greater penetration depth and weld height. The width of the weld was found to be a little high, with a spinning diameter of 2 mm. In comparison, samples 5 and 15 were found to have better hardness, tensile strength, and toughness, especially with suitable welding parameters such as current (120 I and 140 I), speed (1800 rpm), and spin diameter (2 mm and 3 mm). A microstructural study showed no grain segregation, contributing to the material’s increased hardness and tensile strength. The novel findings of the present study suggest that spin arc welding might be superior for various Hastelloy C-2000 connections that might have great applications in industries.

Spectroscopic analysis of residual radicals of gamma sterilized UHMWPE with fractional order differential operators

The purpose of this research was to evaluate the Grunwald-Letnikov definition of fractional order derivatives for determining the fractional derivative of ESR signals from UHMWPE free radicals using the fitted Gaussian distribution method. Specifically, the study focused on analyzing two long-lasting oxygen-induced residual radicals di- or tri-enyls with a carbon center radical (R1) and the oxygen-containing radical (R2). The impact of the derivative order on ESR spectral parameters, such as the Landé g-factor and peak-to-peak separation, was analyzed, and new spectral parameters were established for both radicals. The samples were measured in an ESR tube using ESR power saturation techniques at room temperature. Following the measurements, the fitted Gaussian distribution of the ESR signals was used to determine the fractional derivative using the Grunwald-Letnikov definition. Two estimators (I and II) were developed for both radicals, and their values were found to be 9.19 and 4.27 for Radical R1 and 11.51 and 2060.62 for Radical R2. Our results showed that the fractional derivative approach provided accurate and reliable estimations for the radicals. This method can be easily implemented for various ESR signals and can be useful in many applications, including materials science and biomedical research. The accuracy and reliability of our estimators were confirmed by comparing them with the results obtained from the conventional method. Our findings have important implications for materials science and biomedical research, where ESR signals are widely used. This method can help researchers to obtain more accurate and reliable estimations of radicals, which can ultimately lead to more accurate and reliable conclusions in their studies. Additional research is required to assess the effectiveness of this approach on various ESR signals and to investigate its potential use in other fields of study.

Carbon Capture and Storage Optimization with Machine Learning

This study examines the potential for enhancing carbon capture and storage (CCS) processes by machine learning to markedly improve performance across diverse capture methods, including as absorption, adsorption, membrane separation, and cryogenic distillation. Through the systematic adjustment of critical operating parameters, including temperature, pressure, flow rates, and sorbent characteristics using machine learning algorithms, we saw significant improvements in CO₂ collection efficiency. The use of optimum operating parameters, namely a temperature range of 40-60°C for absorption and a pressure range of 3-5 bar for adsorption, resulted in a 30% enhancement in capture efficiency. Moreover, machine learning models, namely Random Forest and Support Vector Machines (SVM), achieved a maximum enhancement of 20% in forecasting ideal operating parameters for membrane separation and cryogenic systems. Reduced cycle durations in adsorption processes, facilitated by predictive modeling, resulted in a 15% improvement in CO₂ removal rates. The models’ capacity to forecast sorbent regeneration conditions led to a 10% decrease in energy use. Machine learning algorithms adeptly optimized process-specific parameters, including material composition and flow dynamics, enhancing membrane performance by 18% and cryogenic systems by 12%. These results highlight the significance of using machine learning to customize CCS methods for particular materials and situations, facilitating more sustainable, efficient, and scalable carbon capture systems.

Predicting polymer solubility from phase diagrams to compatibility: a perspective on challenges and opportunities.

Polymer processing, purification, and self-assembly have significant roles in the design of polymeric materials. Understanding how polymers behave in solution (e.g., their solubility, chemical properties, etc.) can improve our control over material properties via their processing-structure-property relationships. For many decades the polymer science community has relied on thermodynamic and physics-based models to aid in this endeavor, but all rely on disparate data sets and use-case scenarios. Hence, there are still significant challenges to predict a priori the solubility of a polymer, whether it is for selecting sustainable solvents, obtaining thermodynamic parameters for phase separation, or navigating the coexistence curve. This perspective aims to discuss the different approaches of applying computational tools to predict polymer solubility, with a significant focus on machine learning techniques to capture the rapid progress in that space. We examine challenges and opportunities that remain for creating a comprehensive solubility toolset that can accelerate the design of a broad range of applications including films, membranes, and pharmaceuticals.

Fast and High-Performance Learned Image Compression With Improved Checkerboard Context Model, Deformable Residual Module, and Knowledge Distillation.

Deep learning-based image compression has made great progresses recently. However, some leading schemes use serial context-adaptive entropy model to improve the rate-distortion (R-D) performance, which is very slow. In addition, the complexities of the encoding and decoding networks are quite high and not suitable for many practical applications. In this paper, we propose four techniques to balance the trade-off between the complexity and performance. We first introduce the deformable residual module to remove more redundancies in the input image, thereby enhancing compression performance. Second, we design an improved checkerboard context model with two separate distribution parameter estimation networks and different probability models, which enables parallel decoding without sacrificing the performance compared to the sequential context-adaptive model. Third, we develop a three-pass knowledge distillation scheme to retrain the decoder and entropy coding, and reduce the complexity of the core decoder network, which transfers both the final and intermediate results of the teacher network to the student network to improve its performance. Fourth, we introduce L1 regularization to make the numerical values of the latent representation more sparse, and we only encode non-zero channels in the encoding and decoding process to reduce the bit rate. This also reduces the encoding and decoding time. Experiments show that compared to the state-of-the-art learned image coding scheme, our method can be about 20 times faster in encoding and 70-90 times faster in decoding, and our R-D performance is also 2.3% higher. Our method achieves better rate-distortion performance than classical image codecs including H.266/VVC-intra (4:4:4) and some recent learned methods, as measured by both PSNR and MS-SSIM metrics on the Kodak and Tecnick-40 datasets.

Reinforcement Learning-Based Predefined-Time Tracking Control for Nonlinear Systems Under Identifier-Critic-Actor Structure.

A novel reinforcement learning-based predefined-time tracking control scheme with prescribed performance is presented in this article for nonlinear systems in the presence of external disturbances. First, by employing the backstepping strategy, an adaptive optimized controller is developed under the identifier-critic-actor framework. Therein, the unknown nonlinear dynamics and the system control behavior can be learned effectively through neural networks. Moreover, aiming at obtaining the preset tracking performance, the prescribed performance control is integrated with the predefined-time control. In contrast to previous studies, the proposed scheme can not only constrain the tracking error rapidly to a prearranged vicinity of origin, but also ensure that the upper bound of convergence time can be adjusted in advance via a separate control parameter. In terms of the predefined-time stability theory, the boundedness of all system states can be proven within a predefined time. Finally, the availability and improved performances of the proposed control scheme are demonstrated by a numerical example and a single-link manipulator example.

Numerical analysis of single SC-50-800 and SC-50-500x2-x4 group centrifugal cyclones: efficiency comparison

Centrifugal cyclones are important devices used to separate solids or liquids from gas streams using centrifugal forces. They are widely used in various industrial processes and air and gas purification systems. In this work, numerical modeling and study of the efficiency of cyclones of various configurations are carried out: single cyclone SC-50-800, group cyclones SC-50-500x2 and SC-50-400x4. To conduct the study, the engineering software package Comsol Multiphysics 6.1 was used with the addition of the Flow Simulation module, specialized for modeling hydrodynamic processes. To simulate turbulent flows, the v2-f model was chosen, which is often used in the case of swirling flows. The computational experiment was carried out at a constant air flow rate of 4500 m3/h. Based on the obtained numerical data, an analysis of the effectiveness of various cyclone configurations was carried out. The results of the study show that the operating efficiency of group cyclones significantly exceeds the efficiency of single cyclones. This is confirmed by analysis of separation parameters and comparison of performance indicators of various cyclone configurations. The data obtained can be useful for the design and optimization of gas stream purification systems in various industrial and environmental applications.

Experimental evaluation of fatigue performance of recycled asphalt mixture using refined separation recycled aggregates

In order to improve the utilization of reclaimed asphalt pavement (RAP) in recycled asphalt mixtures (RAMs), RAP was firstly separated into recycled mortar and coarse refined separation recycled aggregates (CRSRAs) with different particle sizes based on a laboratory refined separation method. Meanwhile, the process parameters for RAP separation were optimized by using the orthogonal test method. The related properties of the aggregates before and after refined separation, including residual bitumen binder content, particle agglomeration, angularity, and sphericity, were characterized. The cumulative distribution of sphericity of CRSRAs was fitted with the Weibull function. Asphalt mixtures with 0, 30%, and 50% RAP content were prepared by the Marshall design method. Moreover, the indirect tensile dynamic modulus and fatigue life of these asphalt mixtures after different water immersion periods were evaluated. The results showed that the CRSRAs had a residual binder content less than 1.0% and fewer pseudo particles after refined separation. Furthermore, a bitumen-rich mortar with a particle size less than 2.36 mm and a bitumen content of 10–14% was obtained. Angularity and Weibull fitting results verified that refined separation could homogenize RAP and obtain CRSRAs with a low variability, which helps to prepare better RAMs with high RAP content. RAMs prepared with CRSRAs exhibit superior fatigue performance compared to the traditional RAMs. Their fatigue life was less sensitive to stress changes and fluctuated little with the increasing water immersion time.

THEORY OF UNIFORM RISE/FALL OF A PHYSICAL BODY IN A MOVING MEDIUM

Well production collection and preparation systems play an important role in the separation of oil, gas and water. Proper control of the parameters of gas separators and settling tanks is a key task for their efficient operation. In this paper, the determination of the performance of separators and settling tanks is considered, and special attention is paid to the boundary conditions for maximum efficiency of the separation process. At the moment, the calculation of the performance of gas separators and various settling tanks is carried out according to formulas derived in the twentieth century, and the scientific world does not question their reliability or the reliability of their conclusion. And in order to either prove the reliability of these calculations, or to refute them, an analysis of work was carried out to determine the performance of separators and settling tanks. At the beginning of the work there is a description of how productivity is calculated in the modern world. After that, a discussion is held about the reliability of these calculations, where in the course of reasoning, logical arguments are given about the erroneous conclusions of past calculations. So it was found out that the main assumption in the previous calculations was the use of the absolute velocity of the body in determining the resistance force of the medium, while it was necessary to use the relative velocity of the body, namely the velocity of the body relative to the medium. The following are the new boundary conditions, the solution of this problem, and the conclusions obtained.But the most interesting are the further discussions in the work, during which answers to the questions are given: how and at what speed will the oil particle move in the gas environment of the gas separator at different ratios of forces acting on the particle. Thus, it was concluded that the relative velocity of a body floating freely in a liquid or gaseous medium always tends to a certain constant value, which is numerically equal to the critical velocity of the medium, that is, such a speed at which a particle of oil would be stationary relative to the earth with a moving medium. In this case, the absolute velocity of the body (particles of oil, water, gas) will be equal to the vector difference between the velocity of the medium and the critical velocity of the medium. Combining the obtained conclusions, a new theory about the motion of bodies in a moving medium is created.

Diffusion approximation of a special bandwidth sharing model via infinitesimal generators with a lifting-projection method

We consider a proposed unsolved conjecture of a special bandwidth-sharing model integrating streamings and file transfers as initiated in Kumar and Massoulié (2007). Using the infinitesimal generator approach, we demonstrate its diffusion approximation with a special time-scale separation parameter. To this end, we introduce a lifting-projection method, and exhibit a novel function to show the generator of a joint process converges to that of a univariate limiting file-transfer process, where the streaming flows are averaged out in heavy traffic.

Method Development for Aminopyralid Residues Determination by Ultra-High-Performance Liquid Chromatography Coupled to Tandem Mass Spectrometry in Straw

Straw is an important by-product of crop production. It has been widely used as a feed as well as in fruit–vegetable production due to exerting a positive impact on soil and crop health and quality in the operated areas. On the other hand, applied crop-specific herbicides throughout the production stage, like aminopyralid (AP), may lead to significant plant injuries in sensitive vegetable plantations, even in very low concentrations. This study aims to optimize a short time, minimal consumables needed, and sensitive extraction and analytical method for AP residues in straw material using LC-MS/MS. For this purpose, standard AP signal response in acetonitrile (MeCN) and 1% of formic acid (FA) in methanol (MeOH) were tested; several chromatographic separation and mass spectroscopy (MS) parameters were improved and optimized. Subsequently, two different extraction methods were performed in AP spiked straw samples, and extraction efficacies were compared. Salting-out assisted liquid–liquid extraction (SALLE) by acidified MeCN combined with final dissolution in MeOH with 1% of FA prior to the analysis was chosen as the most appropriate method for the straw matrix. This method was then used for validation and real sample test analysis. The limit of quantification (LOQ) of AP in this optimized extraction method achieved 10 ng/g straw with a recovery rate of 71% and 13% RSD. The method was also tested on field straw mulch samples and 22.54 ± 0.8 ng/g of AP was detected.