Extraction Rate Research Articles

A knowledge graph based remanufacturing equipment resource modeling method.

Background The uncertainty and non-standardization of the remanufacturing process result in multi-source heterogeneity of remanufacturing equipment capabilities and knowledge information, which limits the development of informationization and intelligence in remanufacturing. Methods Therefore, we propose a knowledge graph-based modeling method for Remanufacturing Equipment Resource (RMER) information. By analyzing the categories of remanufacturing equipment resources and integrating resource information such as man, machine, material, method, and environment, a unified remanufacturing equipment information model and service capability information model were constructed. Based on the top-down knowledge graph construction process, the RMER semantic association information of the ontology pattern and data layers was extracted and integrated to construct the RMER knowledge graph. Results In this paper, 18 enterprise texts, 50 experience texts and thesis patent texts were selected as the training set, and 2 enterprise texts, 50 experience texts and thesis patent texts were selected as the test set. After multiple rounds of model training, the accuracy rate of entity information extraction reached 91.4%, which proved the accuracy and effectiveness of the model for entity information document extraction. Conclusions This study provides a unified information foundation for mapping and optimizing the resource capabilities of remanufacturing equipment. It can help remanufacturing enterprises to quickly configure equipment resources, and improve the intelligent and automated management level of RMER.

Aerobic capacity of healthy young men associated with muscle oxygen extraction rate of the vastus lateralis muscle.

The determinants of aerobic capacity are oxygen delivery by the cardiopulmonary system and oxygen extraction by the skeletal muscles. However, the impact of the oxygen extraction capacity of the skeletal muscle is unclear. This study aimed to examine the associations between aerobic capacity; muscle strength, endurance, mass, and quality; and oxygen extraction capacity. Twenty-seven healthy young men (mean age, 20.7 ± 0.8 years; body mass index, 21.6 ± 3.2 kg m-2) were recruited. The following parameters were determined: peak work rate (WR) and oxygen uptake (V˙O2) corrected for body mass using the cardiopulmonary exercise testing; muscle strength and endurance using isokinetic muscle testing; muscle mass using bioelectrical impedance; muscle quality (muscle echo intensity) using an ultrasound imaging device, and muscle oxygen extraction rate (MOER) using near-infrared spectroscopy. Multiple regression analysis was performed using WR/kg peak and V˙O2/kg peak as dependent variables and each assessment index as an independent variable. Multiple regression analysis with WR/kg peak as the dependent variable resulted in the adoption of SMI (β = -0.41, P = 0.036), muscle echo intensity (β=-0.45, P = 0.012) and ΔMOER (β = 0.73, P < 0.001) as significantly associated factors. Multiple regression analysis with V˙O2/kg peak as the dependent variable resulted in ΔMOER (β = 0.65, P = 0.001) being adopted as a significantly associated factor. These findings suggest that muscle oxygen extraction rate is associated with aerobic capacity. MOER is a useful indicator because it is not affected by body mass.

Evironmentally friendly comprehensive utilization of retired waste electrolytes of aluminum electrolysis by calcification leaching

Low energy consumption and environmentally friendly recycling methods can extract high-added value and high-demand elements from retired waste fluorinated aluminum electrolytes (RWE-Al), which is crucial for alleviating resource shortages and environmental hazards. This study aims to develop a method for recovering fluorine and aluminum from RWE-Al through calcium leaching transformation combined with acid leaching. Compared to the traditional high-temperature roasting transformation and high-concentration alkali-metal-salt leaching process, this new process only involves one step of low-temperature leaching, purification of fluorine, carbonization of excess calcium, and evaporation extraction of aluminum, avoiding the generation of high energy consumption and secondary hazardous waste (F-containing liquid/ residue). Fluorine and aluminum are effectively separated and purified with extraction rates exceeding 96%. The effects of leaching temperature, CaO addition coefficient, liquid–solid ratio, and leaching time on the leaching process were systematically studied. The effects of acid concentration, liquid–solid ratio, time, and temperature on the acid-leaching process were also investigated. In summary, the comprehensive utilization of RWE-Al by this new process has proved to be feasible.

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by the solution of Darcy’s partial differential equation for a given permeability field. The subsurface permeability is modeled as a random field since it is known only up to statistical properties. This induces uncertainty in the computed pressure. Solving the partial differential equation for an ensemble of random permeability simulations enables estimating a probability distribution for the pressure at the critical location. These simulations are computationally expensive, and practitioners often need rapid online guidance for real-time pressure management. An ensemble of numerical partial differential equation solutions is used to construct a Gaussian process regression model that can quickly predict the pressure at the critical location as a function of the extraction rate and permeability realization. The Gaussian process surrogate analyzes the ensemble of numerical pressure solutions at the critical location as noisy observations of the true pressure solution, enabling robust inference using the conditional Gaussian process distribution.Our first novel contribution is to identify a sampling methodology for the random environment and matching kernel technology for which fitting the Gaussian process regression model scales as O(nlogn) instead of the typical O(n3) rate in the number of samples n used to fit the surrogate. The surrogate model allows almost instantaneous predictions for the pressure at the critical location as a function of the extraction rate and permeability realization. Our second contribution is a novel algorithm to calibrate the uncertainty in the surrogate model to the discrepancy between the true pressure solution of Darcy’s equation and the numerical solution. Although our method is derived for building a surrogate for the solution of Darcy’s equation with a random permeability field, the framework broadly applies to solutions of other partial differential equations with random coefficients.

Charge Carrier Dynamics at the Perovskite Interface with Self-Assembled Monolayers.

Self-assembled monolayers (SAMs) deposited on the hole-collecting electrodes of p-i-n perovskite solar cells effectively replace bulky hole transporting layers. However, the mechanism by which monolayers control the electronic processes and how they depend on the properties of the monolayer molecules remain poorly understood. In this study, we developed a simplified perovskite solar cell imitator with blocked electron extraction to investigate the photocurrent dynamics between the perovskite and the hole-collecting ITO electrode. We investigated the photoluminescence and photovoltage dynamics under short laser pulse excitation and addressed the influence of bulky and monomolecular hole transport layers. Our findings reveal that the photovoltage dynamics is significantly affected by the properties of the transport and perovskite layers, which in turn depend on the methods of sample preparation and exploration. Photocurrent dynamics is determined by several processes, including charge carrier displacement in the local electric field, hole transport to ITO, trapping of holes in interface trap states, and electron-hole recombination at the interface. We propose a model that takes into account molecular dipole moments and their ionization potentials to partially explain the different influences of different monolayers on the hole extraction and interfacial recombination rates. Additionally, the photovoltage dynamics also strongly depends on the illumination of the sample and shows memory effects that persist over minutes and hours and are attributed to the redistribution of ions.

Optimization of Ultrasonic Extraction, Functional Properties, and Antioxidant Activity of Naematelia aurantialba Polysaccharides

AbstractNaematelia aurantialba (N. aurantialba) is a fungus rich in polysaccharides with medicinal and edible properties. Polysaccharides are the main active components of N. aurantialba; however, their biological activities and functional properties have not been widely explored. In this study, the ultrasonic extraction process for N. aurantialba polysaccharides (NAP) is optimized, and the physicochemical, functional, and antioxidant activities of the homogeneous fraction (NAP) are investigated. The optimal extraction conditions are a liquid–solid ratio of 50 mL g−1, ultrasonic power of 430 W, ultrasonic time of 32 min, resulting in an extraction rate of N. aurantialba polysaccharides of 48.68% ± 0.83%. NAP has a molecular weight of 915 kDa. The monosaccharide composition of NAP is as follows: mannose (59.04% ± 0.12%), xylose (23.89% ± 0.03%), glucuronic acid (14.07% ± 0.24%), galacturonic acid (2.12% ± 0.02%), and glucose (0.76% ± 0.02%). NAP exhibites water and oil retention capacities of 14.62 ± 0.25 g g−1 and 23.73 ± 0.85 g g−1, respectively. Furthermore, NAP demonstrates favorable moisture absorption and retention properties. The results show that NAP has a significantly stronger antioxidant effect, as demonstrated by its concentration‐dependent scavenging of ABTS, DPPH, and hydroxyl radicals.

Recovery of Selenium-Enriched Polysaccharides from Cardamine violifolia Residues: Comparison on Structure and Antioxidant Activity by Different Extraction Methods.

The residues from selenium-enriched Cardamine violifolia after the extraction of protein were still rich in polysaccharides. Thus, the recovery of selenium polysaccharides (SePSs) was compared using hot water extraction and ultrasonic-assisted extraction techniques. The yield, extraction rate, purity, specific energy consumption, and content of total and organic selenium from different SePS extracts were determined. The results indicated that at conditions of 250 W (ultrasonic power), 30 °C, and a liquid-to-material ratio of 30:1 extracted for 60 min, the yield of SePSs was 3.97 ± 0.07%, the extraction rate was 22.76 ± 0.40%, and the purity was 65.56 ± 0.35%, while the total and organic selenium content was 749.16 ± 6.91 mg/kg and 628.37 ± 5.93 mg/kg, respectively. Compared to traditional hot water extraction, ultrasonic-assisted extraction significantly improves efficiency, reduces energy use, and boosts both total and organic selenium content in the extract. Measurements of particle size, molecular weight, and monosaccharide composition, along with infrared and ultraviolet spectroscopy, revealed that ultrasonic-assisted extraction breaks down long-chain structures, decreases particle size, and changes monosaccharide composition in SePSs, leading to lower molecular weight and reduced dispersity. The unique structure of SePSs, which integrates selenium with polysaccharide groups, results in markedly improved antioxidant activity and reducing power, even at low concentrations, due to the synergistic effects of selenium and polysaccharides. This study establishes a basis for using SePSs in functional foods.

Magnesiothermic reduction of beryllium fluoride: Reaction mechanism and kinetic study

Beryllium (Be) is mainly produced by magnesiothermic reduction of beryllium fluoride (BeF2). This research aims to improve the extraction rate of Be by investigating the reaction mechanism and kinetics during the magnesiothermic reduction of BeF2. It was found that the solid product layer composed of MgF2 and Be metal produced during the magnesiothermic reduction process is the main reason hindering the further improvement of the reduction rate. Kinetic study on the magnesiothermic reduction of BeF2 shows that it was controlled by volume diffusion. An apparent activation energy of 66.01 kJ/mol was obtained for the magnesiothermic reduction in the temperature range of 850–950 °C. Aiming to extract Be from BeF2 with a high efficiency, granular-shaped Mg (particle size 0.2–5 mm) and BeF2 powder (particle size < 0.83 mm) were used as raw materials for magnesiothermic reduction at 900 °C for 30 min, protected using Ar atmosphere. This was followed by further heating to 1300 °C and holding for 10 min, and the highest extraction rate of Be was achieved at 90.1 wt% with the Be purity of 94.2 wt%.

Influence of Structure from Motion Algorithm Parameters on Metrics for Individual Tree Detection Accuracy and Precision

Uncrewed aerial system (UAS) structure from motion (SfM) monitoring strategies for individual trees has rapidly expanded in the early 21st century. It has become common for studies to report accuracies for individual tree heights and DBH, along with stand density metrics. This study evaluates individual tree detection and stand basal area accuracy and precision in five ponderosa pine sites against the range of SfM parameters in the Agisoft Metashape, Pix4DMapper, and OpenDroneMap algorithms. The study is designed to frame UAS-SfM individual tree monitoring accuracy in the context of data processing and storage demands as a function of SfM algorithm parameter levels. Results show that when SfM algorithms are properly tuned, differences between software types are negligible, with Metashape providing a median F-score improvement over OpenDroneMap of 0.02 and PIX4DMapper of 0.06. However, tree extraction performance varied greatly across algorithm parameters, with the greatest extraction rates typically coming from parameters causing increased density in dense point clouds and minimal point cloud filtering. Transferring UAS-SfM forest monitoring into management will require tradeoffs between accuracy and efficiency. Our analysis shows that a one-step reduction in dense point cloud quality saves 77–86% in point cloud processing time without decreasing tree extraction (F-score) or basal area precision using Metashape and PIX4DMapper but the same parameter change for OpenDroneMap caused a ~5% loss in precision. Providing reproducible processing strategies is a vital step in successfully transferring these technologies into usage as management tools.

Optimization of Polysaccharide Extraction from Polygonatum cyrtonema Hua by Freeze–Thaw Method Using Response Surface Methodology

Polygonatum cyrtonema polysaccharides have a variety of pharmacological effects. The commonly used extraction methods include traditional hot water extraction, alkaline extraction, enzymatic hydrolysis method, ultrasonic-assisted extraction, etc., but there are problems such as low yield, high temperature, high cost, strict extraction conditions, and insufficient environmental protection. In this study, crude polysaccharide extraction from the Polygonatum cyrtonema Hua was performed using the freeze–thaw method. Response surface methodology (RSM), based on a three-level, three-variable Box–Behnken design (BBD), was employed to obtain the best possible combination of water-to-raw material ratio (A: 30–50), freezing time (B: 2–10 h), and thawing temperature (C: 40–60 °C) for maximum polysaccharide extraction. Using the multiple regression analysis and analysis of variance (ANOVA), the experimental data were fitted to a second-order polynomial equation and were used to generate the mathematical model of optimization experiments. The optimum extraction conditions were as follows: a water-to-raw material ratio of 36.95:1, a freezing time of 4.8 h, and a thawing temperature of 55.99 °C. Under the optimal extraction conditions, the extraction rate of Polygonatum cyrtonema Hua polysaccharide (PCP) was 65.76 ± 0.32%, which is well in close agreement with the value predicted by the model, 65.92%. In addition, PCP has significant antioxidant activity. This result shows that the freeze–thaw method can improve the extraction efficiency, maintain the structural integrity of polysaccharides, simplify the extraction process, promote the dispersion of polysaccharides, and is suitable for large-scale industrial production.

Supercritical Extraction of Ylang Ylang (Cananga odorata) Essential Oil at the Near-Critical Region

The flowers of the ylang ylang tree contain an essential oil which is utilized in high-quality perfumes. The traditional mode of extraction is by steam distillation but it has been shown that the more modern supercritical fluid extraction (SFE) using carbon dioxide has potential for replacing steam distillation. This technology, however, generally operates under high pressures, up to 500 bar. The work described in this paper examines the possibility of using carbon dioxide at much lower pressures, close to the critical point, i.e., 75 bar and 30 °C. Two series of experiments were therefore carried out under such conditions, the first using carbon dioxide alone and the second utilizing ethanol as a co-solvent, the conditions being chosen by applying the Design of Experiments (DOE) technique over ranges of pressure from 80 to 120 bar and temperatures from 35 to 50 °C. Extraction curves are presented which show the rates of extraction to be significantly increased by the use of the co-solvent, with the measured values being 0.74% to 0.97% with no co-solvent addition, increasing to 0.92% to 1.16% with co-solvent addition. These rates are, however, lower than the rates previously reported at higher pressures, i.e., 0.9 to 1.8%. Better quality oils are, however, produced compared to those at higher pressures, with the major components being benzene benzoate, benzene salicylate, cubebene, and benzyl acetate. It is recommended that an economic study be carried out to evaluate whether it is feasible to utilize this process commercially.

Ultrasound-assisted extraction of sumac fruit oil and analysis of its fatty acid composition.

The use of ultrasound for enhancing the extraction of sumac fruit oil was investigated to maximize the utilization of available sumac fruit resources. The optimal extraction parameters were determined using single-factor trials and Box-Behnken design optimization and were found to be a liquid-to-material ratio of 13:1mL/g, an ultrasound temperature of 47°C, and an ultrasound duration of 32min. These yielded a 20.59% extraction rate of the oil. The ultrasonic-assisted approach markedly increased the extraction rate and significantly reduced the extraction time when compared to classical Soxhlet extraction. The resulting sumac fruit oil had a brown-yellow color with peroxide, acid, and iodine concentrations of 2.43mg/g, 0.44g/100g, and 135g/100g, respectively, and relative density (d20 20), and refractive index (20°C) values of 0.911, and 1.469, respectively. The primary fatty acids in the oil were stearic, linoleic, palmitic, linolenic, and oleic acids. With a 74.14% unsaturated fatty acid content, it has a high nutritional value as well as significant development and usage potential. PRACTICAL APPLICATION: This study demonstrates a highly efficient method for extracting vegetable oils and fats. It has the advantages of simple operation, low extraction temperature, short extraction time, high extraction rate, no damage to the material structure, excellent phusicai and chemical properties of the extracted vegetable oil, low cost, and the potential application in the food industry is crucial.

Physicochemical and Functional Properties of DND358 (A Hypocholesterolemic Soybean) Protein Isolate.

The properties and applications of soybean protein isolates (SPIs) have been extensively investigated. In this study, we determined the optimal conditions for the preparation of the DND358 soybean protein isolate (DND358-SPI), assessed its physicochemical and functional properties, and investigated its potential applications in the food industry. According to the results, the highest extraction rate of DND358-SPI was observed when the pH was 9.5, the temperature was 55 °C, the duration was 80 min, and the material-to-liquid ratio was 1:20 (w/v). With regard to the functional properties, the water-holding capacity (WHC) and oil-binding capacity (OBC) of DND358-SPI were higher than those of other varieties, reaching 4.73% and 11.04%, respectively. In addition, the hardness, adhesiveness, chewiness, and resilience of DND358-SPI were higher than those of other varieties, reaching 159.27 g, 186.07 g, 6.78 mj, and 1.88, respectively. These findings indicate that DND358-SPI can reduce cholesterol levels and may be used to produce cholesterol-lowering food products.

The application of Xinjiang safflower extract on Aidelaisi silk fabric

Purpose This study aims to explore the traditional plant dyeing of Xinjiang Atlas silk fabrics, providing references for the comprehensive utilization of plant dyes in intangible cultural heritage.Design/methodology/approach The focus of this study is on dyeing experiments of Atlas silk fabrics using safflower extracts, constrained by regional resources. Safflower dry flowers grown in Xinjiang were selected, rinsed with pure water and rubbed. Yellow pigments were removed by adding edible white vinegar. Red pigments from safflower were extracted using an alkaline solution prepared with Populus euphratica ash, a special product of Xinjiang. The extraction rate was analyzed under varying material-to-liquor ratios, pH values, times and temperatures. Direct dyeing process experiments were conducted to obtain different colorimetric L, a, b and K/S values for comparison. Samples with good color development were selected to test the impact of dyeing immersions on color development, and their color fastness, UV protection and antibacterial effects were verified.FindingsThe dyeing experiments on silk fabrics confirmed their UV protection capabilities and antibacterial properties, demonstrating effectiveness against E. coli and Staphylococcus aureus. As a major producer of safflower, Xinjiang underscores the significance of safflower as an essential plant dyes on the Silk Road. This study reveals its market potential and suitability for use in the plant dyeing process of Atlas silk, producing vibrant red and pink colors.Originality/valueThe experiments indicated that after removing yellow pigments, the highest extraction rate of red pigment from safflower was achieved at a pH value of 10–11, a temperature of 30°C and an extraction time of 40 min. The best bright red color effect with strong color fastness was obtained with a material-to-liquor ratio of 1:20, a temperature of 40°C and three immersions. The best light pink color effect with strong color fastness was a material-to-liquor ratio of 1:80, a temperature of 30°C and two immersions.

Separation and production of metallic magnesium from salt lake brine by extraction-electrodeposition technology

The conventional methods of producing metallic magnesium involve high temperatures, high pollution, and high energy consumption. Herein, the separation and production of metallic magnesium from salt lake brine was carried out using an environmentally friendly extraction-electrodeposition method. 16 functional ionic liquids, consisting of four saponified anions and four quaternary ammonium salt cations, were synthesized and employed as both extractants and supporting electrolytes. The study showed that the compound [A336][V10], which was produced using methyltrioctylammonium ([A336]+) and saponified neodecanoic acid ([V10]−), exhibited a significant extraction rate of Mg2+ and electrical conductivity in methyl isobutyl ketone (MIBK). The extraction efficiency for Mg2+ with a concentration of 54.04 g·L−1 was found to be 60.98%. After extraction, the electrical conductivity of the organic phase was measured to be 649 μS·cm−1. The extraction mechanism and phase equilibria showed that the organic system exhibited limited solubility with the aqueous phase, and the Mg2+ in the brine was extracted by [A336][V10] in the form of MgCl2·2[A336][V10] through monodentate coordination with the carboxyl group in [V10]−. Following extraction, metallic magnesium was successfully electrodeposited from the organic phase. This is the first time that metallic magnesium was directly produced from a common extraction system at room temperature. This method avoids both the dehydration of MgCl2·6H2O and the melting of anhydrous MgCl2 at high temperatures, which are typically encountered in the traditional procedure of producing metallic magnesium from brines, and it offers a new strategy for metallic magnesium production with low energy consumption.

Grayscale Iterative Star Spot Extraction Algorithm Based on Image Entropy

Star trackers are susceptible to interference from stray light, such as sunlight, moonlight, and Earth atmosphere light, in the space environment, resulting in an overall improvement in the star image grayscale, poor background uniformity, low star extraction rate, and high number of false star spots. In response to these challenges, this paper proposes a grayscale iterative star spot extraction algorithm based on image entropy. The implementation of the algorithm is mainly divided into two steps: (1) The algorithm conducts multiple grayscale iterations, effectively utilizing the prior information on the local contrast of star spots to filter out stray light backgrounds to a certain extent. (2) By establishing an inner–outer template, the image entropy algorithm is employed to obtain the real star targets to be extracted, which further suppresses the background clutter and noise. Numerical simulations and experimental results demonstrate that, compared to traditional detection algorithms, this algorithm can effectively suppress background stray light, enhance star extraction rates, and reduce the number of false star spots, and it exhibits superior detection performance in complex backgrounds across various scenarios.

Protein digestibility in wheat noodles: The inhibitory effect and its mechanism of wheat bran dietary fiber

This study investigated the effects of different wheat flour extraction rate (35–95%) on the protein digestibility of those noodles. And to further elucidate the internal mechanism of above phenomenon, wheat flour with different amounts of wheat bran dietary fiber (WBDF) was produced by adding endogenous WBDF. Results indicated that protein digestibility rose significantly with increasing flour extraction rate, peaking at 91.85% at 80% extraction, before trending downward to 85.71% at 95% extraction. Further, among noodles containing different WBDF content, increasing WBDF content to 6% enhanced the formation of β-sheets, boosting I755 levels and reducing I854/I830 levels, thus decreasing protein digestibility. As WBDF content rose further, it promoted transition from β-sheets to β-turn, decreasing I755 and increasing I854/I830, enhancing protein digestibility slightly. The changes indicated that low level of WBDF induced a more compact protein secondary structure to inhibit protein digestion. Conversely, in noodles with high level of WBDF (>6%), the looser protein secondary structure partially alleviated the inhibitory effect of WBDF on protein digestion, which was caused by part of WBDF penetrating the protein's hydrophobic core. Moreover, the static quenching effect of WBDF on pepsin hydrolysis sites through hydrophobic interaction, especially the tyrosine, was another significant factor inhibiting protein digestion.

Hobli wise hydro geomorphological evaluation of the groundwater prospects mapping

ABSTRACT Numerous studies highlight the urgent issue of groundwater depletion due to overexploitation. The United Nations’ World Water Development Report (2023) warns that if current extraction rates persist, many regions could face severe groundwater shortages in the coming decades. A 2021 study in Nature reports that about one-third of the world’s largest groundwater basins are depleting faster than they are replenished, escalating the risk of critical shortages. In Chickballapur District, excessive agricultural activity has led to an imbalance between groundwater loss and recharge. To address this challenge, a weighted overlay analysis of spatial layers in QGIS was employed to identify potential groundwater zones. This methodical approach involved mapping topographic features and integrating six spatial layers: slope, geomorphology, lithology, drainage, lineament and land use/cover. Each subcategory was ranked and scored based on expert opinion and existing literature. The Central Ground Water Board data was used to validate the resulting groundwater prospect map. The study further included an assessment of groundwater prospects across administrative units by superimposing the administrative boundaries on the final map. Calculating the percentage of land within each groundwater prospect category is crucial for effective groundwater management at the administrative level.

Power text information extraction based on multi-task learning

In order to improve the analysis and processing speed of power system fault text in actual business scenarios, a power fault text information automatic extraction model based on pre-training and multi-task learning is proposed. The pre-training model is used to learn the context information of power text words, and the first-order and second-order fusion features of words are mined to enhance the representation ability of features. The multi-task learning framework is used to combine the learning of named entity recognition and relationship extraction tasks to achieve mutual complementation and mutual promotion between entity recognition and relationship extraction, thereby improving the performance of power fault text information extraction. Finally, the model is verified by the daily business data of a power grid data center. Compared with other models, the accuracy and recall rate of power fault text entity recognition and relationship extraction are improved.

Precise Electrocatalysis on Fe-Porphyrin Conjugated Networks Achieves Energy-Efficient Extraction of Uranium.

Electrochemical extraction has the potential to enhance uranium (U) extraction capacity and rates, but thus far, high selectivity and energy efficiency have not been achieved through the design of electrode materials. Herein, a precise electrocatalysis strategy is developed using a Ferrum (Fe)porphyrin-phenanthroline conjugated network (Fe@PDACN) for energy-efficient uranium extraction. The phenanthroline provides specific binding sites for selective enrichment of U(VI) at active sites (Kd = 2.79×105mL g-1 in multi-ion solution). The Fe(II) sites have strong trap-redox activity for U(VI) and act as dynamic electron donors to rapidly mediate electrocatalytic U(VI) extraction through the redox reaction of Fe(0/II)/Fe(III). Moreover, the Fe-porphyrin blocks support sustained electron donation for U(VI) electrocatalysis by pre-storing electrons. These features enable selective uranium capture and a high electroextraction capacity of 24646.3mg g-1 from simulated nuclear wastewater in 280h at a low voltage of -1.5V. An ultra-high Faraday efficiency of 90.1% is achieved, and the energy cost is 3.22×10-2 $ kg-1 U, significantly lower than the previously reported materials. This work provides a highly efficient strategy for uranium extraction from water.