High Extraction Ability Research Articles

Production of high-grade antimony oxide from smelter slag via leaching and hydrolysis process

This study aimed to investigate the recovery of antimony (Sb) from slag generated in an antimony smelting plant using leaching followed by hydrolysis processes. The leaching behaviors of rare earth elements (REEs) were also examined. The physicochemical properties of the slag were determined using various analytical techniques. The slag (4.12 % Sb) was mainly composed of quartz and minor minerals, including microline, magnetite, hedenbergite, and stibiconite. The Sb types in the slag determined by XPS were found to be in the oxide form. The concentrations of REEs (La, Y, Ce, and Nd) in the slag were 169.21 g/t. Preliminary leaching experiment results indicate that (i) HCl was selected rather than other acids due to its high extraction ability on the Sb from the slag, (ii) a sample with a d50 of < 25 µm should be used, (iii) the slurry should be mixed at 300 rpm. In the following leaching tests, the effects of leaching parameters (HCl acid concentration, amount of tartaric acid, solid-to-liquid ratio, reaction temperature, and time) on the extraction rates of Sb, impurities, and REEs were investigated. At the best leaching conditions (HCl: 8 M, amount of tartaric acid: 1 g/L, stirring speed: 300 rpm, reaction temperature: 75 °C, and time: 180 min), the extraction rates of Sb from the slag were determined to be 91.19 %, but the extraction rates of REEs were measured to be ≤ 50 %. The activation energy (Ea) for Sb leaching was found to be 46.75 kJ/mol, indicating that the reaction was governed by the chemically controlled mechanism. In particular, it was understood from the additional experimental results that the leaching procedure should be carried out for 20 h to extract La with an extraction rate of > 90 %. However, the extraction rate of Sb was negligible in extended times. It was determined that using tartaric acid positively affected La’s leaching mechanism, and the required leaching time for La decreased to 180 min from 20 h with the increase of tartaric acid from 1 g/L to 6 g/L. Hydrolysis tests were conducted using the Taguchi approach (L32, 2^1 4^3). The effects of the alkaline type (NH4OH and NaOH), stirring speed (100, 200, 300, and 400 rpm), temperature (50, 60, 70, and 80 °C), and pH (1.5, 2, 2.5, and 3) on the precipitation of Sb from the PLS were investigated. NH4OH was suggested for use in the hydrolysis test to obtain precipitates with higher purities. The product obtained under the optimal conditions comprised 81.43 % Sb, 16.23 % O, and 2.34 % Fe. The product was identified as antimony oxide by XRD.

Ionic Liquid-Based Extraction Strategy for the Efficient and Selective Recovery of Scandium.

The recovery of scandium (Sc) from highly acidic industrial effluents is currently hindered by the use of large quantities of flammable and toxic organic solvents. This study developed an extraction system using ionic liquids (ILs) and phenylphosphinic acid (PPAH) as diluents and an extractant, respectively, to selectively recover Sc from the aqueous phase. The effect of IL chemical structure, aqueous pH and temperature on the extraction of Sc was systematically investigated and the findings revealed that ILs with longer alkyl side chains had reduced Sc extraction ability due to the presence of continuous nonpolar domains formed by the self-aggregation of the IL alkyl side chain. The IL/PPAH system maintained high extraction ability toward Sc across a wide temperature range (288 K to 318 K) and the extraction efficiency of Sc could be improved significantly by increasing the aqueous pH. The extraction process involved proton exchange, resulting in the formation of a metal-ligand complex (Sc(PPA)3).

Acmella oleracea Metabolite Extraction Using Natural Deep Eutectic Solvents

For plant metabolite extraction, natural deep eutectic solvents (NADESs) have many benefits over conventional solvents and ionic liquids. These advantages include high solubility and extraction ability, a low melting point (&lt;100 °C), low toxicity, environmental friendliness, recyclability, and better biodegradability. This study analyses a natural deep eutectic solvent for Acmella oleracea (A. oleracea) metabolite extraction, considering the following process parameters: temperature, component ratio in the eutectic solvent, water addition, solid/liquid ratio, and extraction duration. NADESs were synthesised using a simple heating method, and the synthesis of the NADESs was verified by Fourier transform infrared spectroscopy (FTIR). In terms of total polyphenol content (TPC) and flavonoid content (TFC), the betaine/propanediol ratio in a NADES of 1:3 and S/L = 1:5 yielded the highest efficiency. A value of 8.37 mg GAE/mL was obtained for TPC by ultrasound-assisted extraction with 40% water addition, 25 °C extraction temperature, and 60 min contact time. The best result in terms of TFC was 14.50 mg QE/mL obtained through ultrasound-assisted extraction with 0% water added, 25 °C extraction temperature, and 60 min contact time.

Highly Efficient and Selective Extraction of Gold from Thiosulfate Leaching Solution Using Functionalized Dicationic Ionic Liquids.

Thiosulfate leaching has been regarded as a promising alternative to cyanidation, but it still faces the challenge of the recovery of low content of gold from high concentrations of thiosulfate solutions. Liquid-liquid extraction is a method to address this issue but is still limited by the use of volatile and toxic organic solvents. To overcome this limitation, this work synthesized some functionalized dicationic ionic liquids (DILs) to serve as extraction solvents for the recovery of the gold-thiosulfate complex, [Au(S2O3)2]3-, from thiosulfate solutions. Experimental results indicated that the DILs showed higher extraction rates toward [Au(S2O3)2]3- compared with their monocationic-based counterparts, likely due to the stronger electrostatic interaction between the dications of the ILs and [Au(S2O3)2]3-. The transfer of [Au(S2O3)2]3- from the water phase to the IL phase was identified as an anion exchange and endothermic process. The rate of extraction was limited by the anion exchange process occurring at the IL-water interface. The extraction ability of ILs highly depended on the type of anion; specifically, the ILs with anions that had strong hydrogen-bonding ability exhibited high extraction ability toward [Au(S2O3)2]3-. Finally, DILs proved effective in the recovery of [Au(S2O3)2]3- from an actual gold leaching solution and exhibited high selectivity toward coexisting ions, indicating their potential as environmentally friendly solvents for gold recovery.

Polysaccharide‐Modified SnO2 for Highly Efficient Perovskite Solar Cells

Tin oxide (SnO2) has been demonstrated as a promising electron transport material for perovskite solar cells (PSCs) due to its low‐temperature process and high charge extraction ability. However, the key to improving the internal performance of PSCs toward unity lies in the ability of enhancing bulk SnO2 quality and reducing the energy level mismatch between SnO2 and perovskite layer. Herein, a facile and effective strategy to simultaneously functionalize SnO2 structure by sodium alginate (SA) polysaccharide compound is reported. The investigations reveal that SA leads to the formation of nanosynapse structure of SnO2 films, which allows the aligned energy levels and suppressed charge recombination, significantly enhancing carrier extraction and transport. Consequently, CsMAFAPb(IxBr1−x)3 and CsPbI2Br solar cells achieve a remarkable power conversion efficiency of 24.11% and 16.90%, respectively, based on SnO2‐SA electron transport layers (ETLs). This work offers a facile and effective way to fabricate high‐performance SnO2 ETL in PSCs.

Application of a novel deep eutectic solvent modified carbon nanotube for pipette-tip micro solid phase extraction of 6-mercaptopurine

Background6-mercaptopurine (6-MP) is a chemotherapy drug mainly used to treat leukemia. It is a persistent organic pollutant and can remain in the environment for a long period of time. The presence of 6-MP in the environment poses a number of hazards and needs to be assessed to monitor its potential risk to human health and the environment. However, due to its trace amount in complicated matrices, a clean-up and preconcentration step before its determination is compulsory.ResultsAs a highly efficient adsorbent for the extrication of 6-mercaptopurine (6-MP), a novel carbon nanotube doped with camphor: decanoic acid deep eutectic solvent was synthesized and applied as a packing material for the pipette-tip micro solid phase extraction sorbent of 6-MP from tap, wastewater and seawater samples before its spectrophotometric determination. Characteristics and structure of this adsorbent was fully investigated. Factors affecting extraction, including type and volume of the eluent, ionic strength and pH of the sample solution, amount of adsorbent, and number of extraction and elution cycles were optimized using one-factor-at-a-time and response surface methodologies. The method was found to be linear in the range of 1 to 1000 µg/L with a limit of detection and quantification of 0.2 and 0.7 µg/L, respectively. Reproducibility as relative standard deviation was better than 4.6%.ConclusionApplication of deep eutectic solvent modified carbon nanotube indicated suitable microextraction results and good potential for rapid extraction of trace amounts of 6-MP from different aqueous samples. The amount of sample required for the analysis was less than 10 mL and only 1.5 mg of the adsorbent was used. The total analysis time, including extraction was less than 15 min and the adsorbent could be used for at least 10 times, without significantly losing its adsorption ability. Compared to using unmodified usual carbon nanotubes, deep eutectic solvent doped carbon nanotubes showed 19.8% higher extraction ability.

Highly selective removal of U(VI) from aqueous solutions by porous nanomaterials

AbstractWith the fast development of nuclear energy peaceful utilization, large amounts of U(VI) are not only required to be extracted from solutions for sustainable nuclear fuel supply but also inevitably released into the environment to result in pollution, which is hazardous to human health. Thereby, the selective extraction of U(VI) from aqueous solutions is crucial to U(VI) pollution treatment and also to nuclear industry sustainable development. In this minireview, we summarized the selective extraction of U(VI) from solutions by porous nanomaterials (i.e., porous carbon nanomaterials, covalent organic frameworks, metal organic frameworks, and other nanomaterials) using different techniques, that is, sorption, electrocatalysis, photocatalysis, and other strategies. The efficient high extraction ability is dependent on the properties of porous nanomaterials and the used techniques. The high surface areas, abundant active sites, and functional groups are efficient for the high sorption of U(VI), but the special functional groups such as amidoxime groups are more critical for high selective extraction. The electrocatalytic extraction is related to the active sites, especially the single atom sites, of the porous nanomaterials as electrode. The special functional groups, bandgap, electron transfer pathway and electron donor–acceptor structures of photocatalysts contribute the high photocatalytic extraction of U(VI). The interaction mechanisms are discussed from spectroscopic analysis and computational simulation at molecular level. In the end, the challenges and prospectives for the efficient extraction of U(VI) are described.

BHOEOCC6/n-dodecane: A new solvent extraction media for Cs removal from nuclear waste without using any phase modifier

Modifier-free diluent is most advantageous in hydrometallurgical route for separation of any radioactive element from high level liquid waste (HLLW). However there is not even a single calix crown reported in the literature that is soluble in pure n-dodecane and shows very high Cs extraction from such high nitric acid condition of 4.0 M prevalent in HLLW. Herein we designed a new calix crown-6-ether with an aim to reduce polarity so as to increase solubility in n-dodecane for extraction of Cs by density functional theory (DFT). The theoretically designed calix crown has been synthesised by introducing two 2-(hexyloxy)ethoxy alkyl arms at 1, 3 position calix[4]-arene framework and abbreviated as BHOEOCC6. Characterisation of BHOEOCC6 was carried out using 1H NMR, 13C NMR, and ESI-MS etc. techniques. 0.1 M BHOEOCC6/n-dodecane mixture shows exceptionally high stability as well as high Cs extraction ability (DCs = 10.75 @ 4.0 M HNO3) from highly acidic nuclear waste solution. The mechanism and interaction of Cs with BHOEOCC6 were also probed by experimental distribution ratio studies and instrumental techniques of UV–VIS titration and NMR studies of Cs-BHOEOCC6 complex.

Construction of cationic covalent organic framework for efficient gold extraction.

In this work, we report a rare ionic covalent organic framework (named as ECUT-iCOF-5) synthesized by the Knoevenagel reaction using an ionic liquid monomer. ECUT-iCOF-5 is found to show a promising potential for gold extraction with a high extraction ability towards gold, including a high extraction capacity (3260 mg g-1), good selectivity over both cations and anions, and good recycle use (at least six times).

Thickness Tolerance in Large-Area Organic Photovoltaics with Fluorine-Substituted Regioregular Conjugated Polymer.

Large areas and simple processing methods are necessary for the commercialization of organic photovoltaics (OPVs). However, the efficiency drop due to the variation in thickness of OPVs limits their large-scale applications. Regioregular polymers with good crystallinity and packing properties that exhibit high charge mobility and extraction ability can help overcome these limitations. In this study, a regioregular polymer named PDBD-2FBT was synthesized. The crystallinity and packing properties of PDBD-2FBT were enhanced by a simple thermal treatment. Using PDBD-2FBT material as a donor and Y6-HU as an acceptor, we fabricated binary blend OPV devices. The devices with optimized active layer thickness achieved a power conversion efficiency (PCE) of 14.14%. A PCE of 13.18% was maintained even in thick-film conditions (400 nm), and thickness tolerance was observed. Based on the thickness tolerance, a 5-line module measuring 36 cm2 was fabricated via the bar-coating method, and a PCE of approximately 10% was achieved.

Extraction of actinides and lanthanides from nitric acid solutions with phosphorylated pyrazines

The extraction of U(VI), Th(IV), Am(III), and lanthanides(III) from nitric acid solutions with solutions of phosphorylated pyrazines in organic solvents has been studied. The stoichiometry of the extracted complexes was determined, and the in uence of the structure of the extractant and the concentration of HNO3 in the aqueous phase on the e ciency of the extraction of metal ions into the organic phase was considered. It has been established thatm among the studied compounds, bis(diphenylphosphine)quinoxaline dioxide has the highest extraction ability with respect to actinides and lanthanides in nitric acid media.

Highly Selective Extraction of U(VI) from Solutions by Metal Organic Framework-Based Nanomaterials through Sorption, Photochemistry, and Electrochemistry Strategies.

With the rapid development of nuclear technology and peaceful utilization of nuclear energy, plentiful U(VI) not only is required to be extracted from solutions for a sustainable nuclear fuel supply but also is inevitably released into the surrounding environment to result in pollution and threaten human health. Thereby, realizing selective extraction of U(VI) from aqueous solutions is crucial for U(VI) pollution control and a sustainable nuclear industry. Metal organic frameworks (MOFs) have gained multidisciplinary attention due to their excellent properties including large specific surface areas, tunable pore structures, easy functionalization, etc. This Review comprehensively summarizes the research progress of MOFs and MOF-based materials on U(VI) removal from aqueous solutions by sorption, photocatalysis, electrocatalysis, membrane separation, etc. The efficient high extraction ability is dependent on the intrinsic properties of MOFs and the techniques used. The removal properties of MOF-based materials as adsorbents, photocatalysts, and electrocatalysts for U(VI) are discussed. Information about the interaction mechanisms between U(VI) and MOF-based materials are analyzed in-depth, including experiments, theoretical calculations, and advanced spectroscopy analysis. The removal properties for U(VI) of various MOF-based materials are assessed through different techniques. Finally, a summary and perspective on the direction and challenges of MOF-based materials and various pollutant removal technologies are proposed to provide some significant information on designing and fabricating MOF-based materials for environmental pollution management.

Eco-Friendly Boost for Perovskite Photovoltaics: Harnessing Cellulose-Modified SnO2 as a High-Performance Electron Transporting Material.

In this study, a passivated tin oxide (SnO2) film is successfully obtained through the implementation of sodium carboxymethyl cellulose (Na-CMC) modifier agent and used as the electron transporting layer (ETL) within the assembly of perovskite solar cells (PSCs). The strategic incorporation of the Na-CMC modifier agent yields discernible enhancements in the optoelectronic properties of the ETL. Among the fabricated cells, the champion cell based on Na-CMC-complexed SnO2 ETL achieves a conversion efficiency of 22.2% with an open-circuit voltage (VOC) of 1.12 V, short-circuit current density (JSC) of 24.57 mA/cm2, and fill factor (FF) of 80.6%. On the other hand, these values are measured for the pristine SnO2 ETL-based control cell as VOC = 1.11 V, JSC = 23.59 mA/cm2, and FF = 76.7% with an efficiency of 20.1%. This improvement can be ascribed to the high charge extraction ability, higher optical transmittance, better conductivity, and decrease in the trap state density associated with the passivated ETL structure. In addition, the cells employing Na-CMC-complexed SnO2 ETL exhibit prolonged stability under ambient conditions during 2000 h. Based on the preliminary results, this study also presents a set of findings that could have substantial implications for the potential use of the Na-CMC molecule in both large-scale perovskite cells and perovskite/Si tandem configuration.

An Improved Deep Learning Model for DDoS Detection Based on Hybrid Stacked Autoencoder and Checkpoint Network

The software defined network (SDN) collects network traffic data and proactively manages networks. SDN’s programmability makes it excellent for developing distributed applications, cybersecurity, and decentralized network control in multitenant data centers. This exceptional architecture is vulnerable to security concerns, such as distributed denial of service (DDoS) attacks. DDoS attacks can be very serious due to the fact that they prevent authentic users from accessing, temporarily or indefinitely, resources they would normally expect to have. Moreover, there are continuous efforts from attackers to produce new techniques to avoid detection. Furthermore, many existing DDoS detection methods now in use have a high potential for producing false positives. This motivates us to provide an overview of the research studies that have already been conducted in this area and point out the strengths and weaknesses of each of those approaches. Hence, adopting an optimal detection method is necessary to overcome these issues. Thus, it is crucial to accurately detect abnormal flows to maintain the availability and security of the network. In this work, we propose hybrid deep learning algorithms, which are the long short-term memory network (LSTM) and convolutional neural network (CNN) with a stack autoencoder for DDoS attack detection and checkpoint network, which is a fault tolerance strategy for long-running processes. The proposed approach is trained and tested with the aid of two DDoS attack datasets in the SDN environment: the DDoS attack SDN dataset and Botnet dataset. The results show that the proposed model achieves a very high accuracy, reaching 99.99% in training, 99.92% in validation, and 100% in precision, recall, and F1 score with the DDoS attack SDN dataset. Also, it achieves 100% in all metrics with the Botnet dataset. Experimental results reveal that our proposed model has a high feature extraction ability and high performance in detecting attacks. All performance metrics indicate that the proposed approach is appropriate for a real-world flow detection environment.

Ultra‐Selective and Efficient Static/Dynamic Palladium Capture from Highly Acidic Solution with Robust Macrocycle‐Based Polymers

AbstractThe capture of palladium from spent nuclear fuel is crucial for the sustainable development of nuclear energy and resource recovery. One of the most challenging issues in this direction is the survival of adsorbents under extreme reprocessing conditions such as strongly acidic media and high radiation fields while still maintaining high extraction ability and selectivity. Herein, an approach to addressing this issue is reported by incorporating macrocycle into nitrogen‐rich covalent organic polymers (COPs). Dramatically outperforming current adsorbing materials, pillar[5]arene‐based COPs with pyridyl and triazolyl functionalities display record adsorption capacity for Pd(II) at 3 M HNO3 (403 mg g−1), extraordinary stability under 500 kGy gamma irradiation, and ultra‐high selectivity toward Pd(II) over both 17 coexisting cations and six anions. In particular, the material P5COP‐m‐BPT with the best performance also shows remarkable dynamic adsorption efficiency for Pd(II). This study not only provides a strategy to enhance all‐sided adsorption performance in palladium separation with nitrogen‐rich COPs materials but also demonstrates the superiority of customizing advanced materials with macrocycles.

PFP-HOG: Pyramid and Fixed-Size Patch-Based HOG Technique for Automated Brain Abnormality Classification with MRI.

Detecting neurological abnormalities such as brain tumors and Alzheimer's disease (AD) using magnetic resonance imaging (MRI) images is an important research topic in the literature. Numerous machine learning models have been used to detect brain abnormalities accurately. This study addresses the problem of detecting neurological abnormalities in MRI. The motivation behind this problem lies in the need for accurate and efficient methods to assist neurologists in the diagnosis of these disorders. In addition, many deep learning techniques have been applied to MRI to develop accurate brain abnormality detection models, but these networks have high time complexity. Hence, a novel hand-modeled feature-based learning network is presented to reduce the time complexity and obtain high classification performance. The model proposed in this work uses a new feature generation architecture named pyramid and fixed-size patch (PFP). The main aim of the proposed PFP structure is to attain high classification performance using essential feature extractors with both multilevel and local features. Furthermore, the PFP feature extractor generates low- and high-level features using a handcrafted extractor. To obtain the high discriminative feature extraction ability of the PFP, we have used histogram-oriented gradients (HOG); hence, it is named PFP-HOG. Furthermore, the iterative Chi2 (IChi2) is utilized to choose the clinically significant features. Finally, the k-nearest neighbors (kNN) with tenfold cross-validation is used for automated classification. Four MRI neurological databases (AD dataset, brain tumor dataset 1, brain tumor dataset 2, and merged dataset) have been utilized to develop our model. PFP-HOG and IChi2-based models attained 100%, 94.98%, 98.19%, and 97.80% using the AD dataset, brain tumor dataset1, brain tumor dataset 2, and merged brain MRI dataset, respectively. These findings not only provide an accurate and robust classification of various neurological disorders using MRI but also hold the potential to assist neurologists in validating manual MRI brain abnormality screening.

Potential of cobalt ferrite-graphitic carbon nitride nanocomposite in trace determination of pyrene as one of the priority pollutants in water and food samples

In this research, cobalt ferrite-graphitic carbon nitride (CoFe2O4/GC3N4) nanocomposite with high extraction ability, high sensitivity, and strong magnetic properties was successfully synthesized and evaluated as a sorbent for ultrasound-assisted dispersive magnetic micro-solid phase extraction (UA-DM-μ-SPE) of pyrene (Py) in food and water samples. A successful synthesis of CoFe2O4/GC3N4 was inspected by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), field emission scanning electron microscope (FE-SEM), energy-dispersive X-ray spectrometry (EDXS), and vibrating sample magnetometer (VSM) techniques. The experimental parameters affecting the UA-DM-μ-SPE efficiency, such as the amount of sorbent, pH, adsorption time, desorption time, and temperature, were effectively investigated according to a multivariate optimization approach. Under the optimal conditions, the detection limit, quantification limit, and relative standard deviation (RSD) for the target analyte were achieved at 2.33 ng mL−1, 7.70 ng mL−1, and 3.12%, respectively. The CoFe2O4/GC3N4 based UA-DM-μ-SPE followed by spectrofluorometry confirmed favorable results for the convenient and efficient determination of Py in the samples of vegetable, fruit, tea, and water.

Lead free CsSn0.5Ge0.5I3 perovskite solar cell with different layer properties via SCAPS‐1D simulation

AbstractOrganic–inorganic halide perovskite solar cells (PSCs) have been extensively studied due to their simple fabrication methods and obvious device efficiency advantages. In this work, the perovskite CsSn0.5Ge0.5I3 is used as the light absorption layer, which is doped with Ge2+ in CsSnI3 to improve its stability. The polymers of 3‐hexylthiophene (P3HT) with excellent optoelectronic properties and low price, and SnO2 with high electron extraction ability is selected as charge transport layers. Based on these, a novel PSC structure (FTO/SnO2/IDL1/CsSn0.5Ge0.5I3/IDL2/P3HT/Au) has been simulated via solar cell capacitor simulator (SCAPS‐1D). The PSC performance is optimized by adjusting a series of parameters, including the layer thickness, defect density, electron affinity potential energy, and operating temperature, and so forth. The results show that the PSC defects are passivated by adjusting the appropriate parameters, and the final optimized open circuit voltage (VOC) is 1.08 V, short‐circuit current density (JSC) is 27.37 mA/cm2, fill factor (FF) is 83.32%, while the power conversion efficiency (PCE) is increased from the initial 10.89% to 24.63%, which provides theoretical reference for experiments and new ideas for the preparation and development of efficient and environmentally friendly PSCs. Finally, the effect of different metal cathodes with and without hole transport layer (HTL) on PSC performance is compared. The PSCs without HTL are more dependent on battery cathodes, which provided a way to replace precious metals with other electrode materials.

Synthesis and extraction properties of 4,5-diphosphorylated triazoles

A method for the synthesis of 4,5-diphosphorylated 1,2,3-triazoles has been developed, and the extraction of U(VI), Th(IV), and lanthanides(III) from nitric acid solutions by them was studied. A synergistic effect was found in the extraction of metal ions with mixtures of 4,5-diphosphorylated 1,2,3-triazoles and dinonylnaphthalenesulfonic acid. The stoichiometry of the extracted complexes was determined, and the influence of the structure of the extractant and the concentration of HNO3 in the aqueous phase on the efficiency of the extraction of metal ions into the organic phase was considered. It was established that 4,5-diphosphorylated 1,2,3-triazole with the octyl substituent at nitrogen atom has the highest extraction ability with respect to actinides and lanthanides in nitric acid media.

A new deep eutectic solvent based on diphenylguanidine for the effective extraction of pertechnetate anion

In this work, for the first time, a new class of deep eutectic solvents has been synthesized and applied for the efficient extraction of pertechnetate anion from imitators of real media from which pertechnetate removal is needed: high-level waste imitator and sea water imitator. Diphenyl guanidine was studied as a hydrogen bond acceptor, which exhibits a high extraction ability for pertechnetate anion separation. Natural fatty acid and natural terpene were studied as hydrogen bond donors. The structure, properties, viscosity and stability of the obtained eutectic solvents were studied. Also, the radiation resistance of the obtained solvents was studied from the point of view of distribution ratio saving. It was shown that the new class of solvents has a high radiation resistance and efficiently extracts pertechnetate anion even from acidic media in high-temperature extraction process and can be the first step platform for solving technological and radiation safety problems.