Extraction Process Research Articles

Comparative analysis of Environmental Impact of Each Building Material using Life Cycle assessment(LCA)_Focusing on Types of Construction Wood and Concrete

Objectives:The construction sector is a very important sector in achieving carbon neutrality. In modern society, construction has grown rapidly, and basic materials such as cement and concrete have contributed greatly to the development of construction. These materials emit a large amount of global warming substances during the raw material extraction and production process, causing serious environmental pollution. In order to establish a carbon reduction strategy to slow down global warming, we compared the environmental impacts of each building material and showed the current situation.Methods:The LCI DB for the construction materials used in the two-story wooden house (Building area 128.67m2, total floor area 235.73m2) located in the National Institute of Forest Science was extracted. Then, the data for LCA was processed and performed through the life cycle assessment methodology for the resources consumed from raw material collection, material production, and transportation stages. Then, based on the environmental performance labeling impact assessment method, a study was conducted on the environmental impact categories of the actual construction materials used and comparisons with other construction materials.Results and Discussion:When analyzing the environmental impact of concrete [25-21-120] and construction wood used in wooden house, the environmental impact was found to be 98.79% higher on average in the pre-manufacturing stage than in the manufacturing stage, and construction wood was confirmed to have a reduction effect of 62.21 kg CO2-eq per 1 m3 compared to concrete. Through the scenario, there was a carbon reduction effect of up to 36% when the entire area was replaced with wood. In addition, the environmental impact by major construction material was quantitatively quantified.Conclusion:When building a wooden house, reducing the amount of concrete equivalent to the amount of wood is expected to have a greenhouse gas reduction effect, so it is time to activate construction wood from the production process to the post-production stage to replace concrete. In addition, follow-up research on the development of construction technology with low environmental impact during construction should be continued. This study is expected to be used as a useful indicator for R&D and policies in the construction field in the future, as it quantitatively quantified the amount of CO2 reduction per m3 when replacing concrete with construction wood and numerically compared and analyzed six major environmental impact categories by major construction materials.

Innovations in residue upgrading for the Niger delta by transforming heavy oil fractions into high-value products: A state of the art review

This review discusses new innovations in residue upgrading technologies for the conversion of heavy oil fractions into high-value products, especially for Delta and Rivers States of the Niger Delta region. Recent works within the 2020-2024 period show that upgrading methods have been significantly developed; however, no prior work has been done regarding applying those upgrading techniques to the peculiar nature of crude oil from this region. The paper probes the environmental impacts of these technologies, emphasizing the need for localized assessment that would take into consideration the fragile ecosystems of Delta and Rivers States. It further assesses the economic viability of scaling up the implementation of advanced upgrading processes within the current refining infrastructure. The discussion covers variable quality heavy oil in these regions and what that does to upgrading efficiency, how to integrate these technologies into the current refining practices, underlines the potential socio-economic advantages for the local communities through the creation of jobs and enhancing the skills of those communities to underscore the importance of these innovations for sustainable development. The review establishes that in such siamese twin areas, further research is needed to ensure that heavy oil resources in Delta and Rivers States are utilized effectively while ensuring that there is a minimal environmental impact from the extraction process.

Machine learning-aided enhancement of white tea extraction efficiency using hybridized GMDH models in microwave-assisted extraction

White tea is valuable for having a high antioxidant content, which is considered to possess numerous beneficial effects on health. This study investigated the application of microwave-assisted extraction (MAE) for the extraction of total phenolic compounds from white tea. The experimental setup included four independent variables: microwave power (ranging from 100 to 300 W), extraction time (ranging from 10 to 40 min), temperature (ranging from 35 to 50 °C), and the ratio of food to solvent (ranging from 0.25 to 0.5 g/10 mL). The responses that were evaluated were IC50 (ppm) and total phenolic content (mg/g). The experimental design consisted of thirty runs conducted within the MAE system. The group method of data handling (GMDH) models were used to predict important efficiency measures (IC50 and total phenol content) in the extraction process. The models were assessed based on their ability to capture the relationships between input conditions and efficiency outputs. Three GMDH variants were compared: baseline GMDH, GMDH optimized with a genetic algorithm (GMDH-GA), and GMDH optimized with a harmony search algorithm (GMDH-HS). While all models achieved high predictive ability on a test set, GMDH-HS emerged as the superior performer. It achieved near-perfect agreement with observations (d-index > 0.998), minimal errors (NRMSE < 0.02), and effectively captured data variance (NSE > 0.99) for both outputs. Correlation diagrams and Taylor diagrams confirmed the superior performance of GMDH-HS in terms of linearity, correlation, and error minimization. This study demonstrates the effectiveness of hybridizing GMDH with a harmony search algorithm for complex modeling tasks, paving the way for improved efficiency and yield optimization in extraction processes.

Pressurized liquid extraction of sulfite for quantitation by capillary zone electrophoresis.

Sulfite is an additive used in shrimp processing to prevent discoloration. However, sulfite can cause health issues for sensitive consumers, making its monitoring necessary. Determining sulfite concentrations is complex because the Monier-Williams reference method is laborious and has low analytical throughput. Additionally, new techniques are needed to stabilize sulfite during the extraction process because this analyte undergoes rapid oxidation. A new method involving extraction and derivatization of sulfite with formaldehyde through automated pressurized liquid extraction (PLE), followed by quantitation by capillary zone electrophoresis with diode-array detector in indirect mode, was developed and optimized using multivariate planning. The PLE procedure was compared to another solid-liquid extraction method. The new method successfully stabilized and extracted sulfite from shrimp in few steps with adequate precision (CV<3.8%), producing extracts that were stable for 10 days. Recovery was satisfactory (97%-99%), and the limits of detection (4.6mgkg-1) and quantitation (15.4mgkg-1) were suitable for the intended purpose.

Efficacy of Fresh Versus Preserved Amniotic Membrane Grafts for Ocular Surface Reconstruction: META = meta-analysis.

Amniotic membrane transplantation is commonly employed in ophthalmology to mend corneal epithelial and stromal defects. Its effectiveness in restoring the ocular surface has been widely acknowledged in clinical practice. Nevertheless, there is ongoing debate regarding the comparative effectiveness of using fresh amniotic membranes versus preserved ones. The objective of this meta-analysis was to ascertain whether there is a disparity in the effectiveness of fresh versus preserved amniotic membrane in the restoration of the ocular surface in clinical practice. The study utilized the following keywords: "fresh amniotic membrane," "preserved amniotic membrane," "amniotic membrane transplantation," and "ocular surface reconstruction." The study conducted a comprehensive search for relevant studies published until April 18, 2024. Seven different databases, namely PubMed, Web of Science, Embase, Cochrane, China Knowledge, China Science and Technology Journal VIP database, and Wanfang database, were utilized. The search was performed using the keywords "fresh amniotic membrane," "preserved amniotic membrane," "amniotic membrane transplantation," and "ocular surface reconstruction." The process of literature review and data extraction was carried out separately by two researchers, and all statistical analyses were conducted using Review Manager 5.4.1. The final analysis comprised nine cohort studies, encompassing a total of 408 participants. The statistics included six outcome indicators: visual acuity (relative risk [RR] = 1.07, 95% confidence interval [CI] = 0.93-1.24, I2 = 0); amniotic membrane viability (RR = 1.00, 95% CI = 0.93-1.08, I2 = 0); ocular congestion resolution (RR = 1.11, 95% CI = 0.97-1.26, I2 = 0); fluorescent staining of amniotic membranes on the second day after the operation (RR = 1.31, 95% CI = 0.80-2.14, I2 = 11); postoperative recurrence rate (RR = 1.01, 95% CI = 0.50-2.03, I2 = 0); and premature lysis of amniotic membrane implants (RR = 0.96, 95% CI = 0.49-1.88, I2 = 0). The findings indicated that there was no statistically significant disparity between fresh and preserved amniotic membranes across any of the measured variables. There is no substantial disparity in the effectiveness of fresh and preserved amniotic membrane transplants in restoring the ocular surface, and both yield favorable and consistent outcomes.

Optimization of extraction for efficient recovery of kenaf seed protein isolates: evaluation of physicochemical and techno-functional characteristics.

Kenaf seeds are a rich source of protein; however, finding the best extraction method is crucial to obtaining high-quality protein from these underutilized seeds. This research devised an optimized extraction process for best recovery of kenaf seeds protein using response surface methodology. The key parameters affecting the yield and protein content were optimized, including extraction pH (2-11), seed:water ratio (5:1-50:1), temperature (30-90 °C), and duration (20-360 min). The physicochemical and techno-functional properties of kenaf seed protein isolates (KSPIs) were examined. A maximum protein yield of 12.05 g/100 g with purity level 91.94 g/100 g was obtained using an optimized extraction with pH 11.0, seed:water ratio 50:1, 360 min duration, and temperature 50 °C. The oil and water retention capacities of KSPI were 1.14 mL g-1 and 1.37 mL g-1 respectively. After 30 min at pH 7, KSPIs demonstrated remarkable emulsion capacity (83.12%) and stability (75.63%), along with high foaming capacity (106%) and stability (18.3%). As per high-performance liquid chromatography analysis, arginine, glutamic acid, leucine, phenylalanine, and lysine were the most abundant amino acids detected in KPSIs. The KSPIs' globular protein structure was successfully verified using analytical approaches, including Fourier transform infrared spectroscopy, protein fraction ratios, and differential scanning calorimetry. Sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis revealed that KPSI has a molecular weight distribution ranging from 10 kDa to 50 kDa. The results of this study support the application of the proposed response-surface-methodology-optimized extraction method for efficient recovery of high-quality kenaf seed proteins that meet the necessary physicochemical and techno-functional requirements. © 2024 Society of Chemical Industry.

Biological activities of Hypericum spectabile extract optimized using artificial neural network combined with genetic algorithm application

Optimizing extraction conditions can help maximize the efficiency and yield of the extraction process while minimizing negative impacts on the environment and human health. For the purpose of the current study, an artificial neural network (ANN) combined with a genetic algorithm (GA) was utilized for that the extraction conditions of Hypericum spectabile were optimized. In this particular investigation, the main objective was to get the highest possible levels of total antioxidant status (TAS) for the extracts that were obtained. In addition to this, conditions of the extract that exhibited the maximum activity have been determined and the biological activity of the extract that was obtained under these conditions was analyzed. TAS values were obtained from extracts obtained using extraction temperatures of 30–60 °C, extraction times of 4–10 h, and extract concentrations of 0.25-2 mg/mL. The best model selected from the established ANN models had a mean absolute percentage error (MAPE) value of 0.643%, a mean squared error (MSE) value of 0.004, and a correlation coefficient (R) value of 0.996, respectively. The genetic algorithm proposed optimal extraction conditions of an extraction temperature of 59.391 °C, an extraction time of 8.841 h, and an extraction concentration of 1.951 mg/mL. It was concluded that the integration of ANN-GA can successfully be used to optimize extraction parameters of Hypericum spectabile. The total antioxidant value of the extract obtained under optimum conditions was determined as 9.306 ± 0.080 mmol/L, total oxidant value as 13.065 ± 0.112 µmol/L, oxidative stress index as 0.140 ± 0.001. Total phenolic content (TPC) was 109.34 ± 1.29 mg/g, total flavonoid content (TFC) was measured as 148.34 ± 1.48 mg/g. Anti-AChE value was determined as 30.68 ± 0.77 µg/mL, anti-BChE value was determined as 41.30 ± 0.48 µg/mL. It was also observed that the extract exhibited strong antiproliferative activities depending on the increase in concentration. As a result of LC-MS/MS analysis of the extract produced under optimum conditions in terms of phenolic content. The presence of fumaric, gallic, protocatechuic, 4-hydroxybenzoic, caffeic, 2-hydoxycinamic acids, quercetin and kaempferol was detected. As a result, it was determined that the H. spectabile extract produced under optimum conditions had significant effects in terms of biological activity.

How characteristics of place affect multimorbidity: a systematic scoping review

Abstract Background Multimorbidity has become a global public health challenge. Increasing work has identified different individual- and household-level determinants of multimorbidity; however, our understanding of how characteristics of place affect multimorbidity remains limited. This scoping review aims to identify the place-based risk factors of multimorbidity and to synthesis evidence (longitudinal in particular) on how place-based risk factors affect multimorbidity. Methods Following PRISMA-ScR guidelines, a predefined search strategy (https://osf.io/bf84m) was run across 7 major databases in 2023, with a double screening and data extraction process. English-language peer-reviewed studies exploring the relationship between place-based characteristics (from neighbourhood to region) and multimorbidity among the general population aged over 18 years old were included from 2010 to 2023. Results Out of 7761 records, 129 underwent full-text review, resulting in 76 included studies (15 longitudinal). We identified 12 types of place-based risk factors of multimorbidity, with area-level deprivation/SES, pollution, and urban/rurality most frequently examined. Fairly consistent findings suggested that people in more deprived, polluted, or urbanised areas were more likely to be multimorbid, which may further vary by multimorbidity definitions/measurements. Other place-based risk factors, such as social cohesion and greenspace availability, were linked to different single health conditions, but their associations with multimorbidity were underexplored. Finally, we proposed a potential theoretical framework that links place and multimorbidity through multiple pathways based on the synthesised evidence. Conclusions There remains only a partial understanding of how ‘place’ affects multimorbidity. Future studies should employ more precise measures for both place-based risk factors and multimorbidity and use longitudinal designs and analytical approaches for more causal insights. Key messages • This is the first scoping review that proposed a theoretical framework that demonstrates the links between place and multimorbidity. • This study will greatly benefit local policymaking and public health intervention initiation.

Enhancing the performance of a resonance-based sensor network for soft robots using binary excitation.

Embedded, flexible, multi-sensor sensing networks have shown the potential to provide soft robots with reliable feedback while navigating unstructured environments. Time delay associated with extracting information from these sensing networks and the complexity of constructing them are significant obstacles to their development. This paper presents a novel enhancement to an existing class of embedded sensor network with the potential to overcome these challenges. In its original version, this sensor network extracts information from multiple reactive sensors on a two-wire electrical circuit simultaneously. This paper proposes to change the excitation signal applied to this sensor network to a binary signal. This change offers two key advantages: it provides the ability to employ small, inexpensive microcontrollers and results in a faster data extraction process. The potential of this enhanced system is demonstrated here with a proof of concept implementation. The self-inductance of all inductance-based sensors within this proof of concept sensor network can be measured at a rate of over 5000 times per second with an average measurement error of less than 2%.

Solid–Liquid Phase Equilibria of the Aqueous Quaternary System Rb+, Cs+, Mg2+//SO42− - H2O at T = 323.2 K

Sulfate-type salt lakes constitute over half of the total salt lakes in China and are rich in rare elements, such as rubidium and cesium. However, the complex interactions between ions make the separation and extraction process quite challenging. To address this, phase equilibrium studies were conducted on the sulfate system containing rubidium, cesium, and magnesium. Specifically, the phase equilibria of the aqueous quaternary system Rb+, Cs+, Mg2+//SO42− - H2O at 323.2 K were investigated using the isothermal dissolution method. The solubility, density, and refractive index of the system were experimentally measured. The results indicate that the system at 323.2 K belongs to a complex type with the formation of one solid solution (Rb, Cs)2SO4 and two double salts (Rb2SO4·MgSO4·6H2O, Cs2SO4·MgSO4·6H2O). The corresponding phase diagram consists of four quaternary invariant points, nine univariate curves, and six crystallization regions. Among these, the crystalline region for Cs2SO4·MgSO4·6H2O is the largest, while that for the single salt Cs2SO4 is the smallest. Moreover, the crystalline regions for the double salt and solid solutions are significantly larger than those for the single salt, highlighting the difficulty in separation of valuable single salts. A comparison of multi-temperature phase diagrams from 298.2 K to 323.2 K reveals that the crystalline form of MgSO4 changes from MgSO4·7H2O (298.2 K) to MgSO4·6H2O (323.2 K). As the temperature increases, the phase regions for Rb2SO4, Cs2SO4, (Rb, Cs)2SO4, and Cs2SO4·MgSO4·6H2O expand, while the phase region of Rb2SO4·MgSO4·6H2O contracts, indicating that the single salts (Rb2SO4, Cs2SO4) are more readily precipitated at higher temperature, which provides theoretical guidance for the future production and separation of Rb, Cs, and Mg from sulfate-type salt lakes.

Optimization of Crystal Structures in Polylithionite Concentrate: A Molecular Dynamics Approach to Lithium Extraction Efficiency

Molecular dynamics (MD) techniques offer significant potential for optimizing mineral extraction processes by simulating economically or physically restrictive conditions at the laboratory level. Lithium, a crucial metal in the electromobility era, exemplifies the need for ongoing re-evaluation of extraction techniques. This research aims to simulate the crystal structures of mineral species present in a polylithionite mineral concentrate [KLi2Al(Si4O10)(F,OH)2] using crystallographic data obtained from X-ray diffraction analysis. This study focuses on optimizing these structures, validating them through density comparisons, and determining the interaction parameter between the identified phases and lithium oxide (Li2O). The X-ray diffraction analysis revealed five predominant mineral phases: quartz (SiO2), calcite [Ca(CO3)], pyrite (FeS2), cassiterite (SiO2), and a compound Pb6O2(BO3)2SO4. Structural data, including lattice parameters, space groups, and atomic coordinates, were used to construct the crystal structures with Materials Studio 8.0, employing the Crystal Builder module. Optimization was performed using the Forcite module with the Smart optimization algorithm and the Universal force field. The interaction parameter (χ) indicated an affinity between lithium oxide and pyrite, as well as between calcite and quartz.

Enhancing Antioxidant Activity from Aquatic Plant Cymodocea nodosa for Cosmetic Formulation Through Optimized Ultrasound-Assisted Extraction Using Response Surface Methodology

This study aimed to enhance antioxidant extraction from the aquatic plant Cymodocea nodosa for cosmetic formulation through optimized ultrasound-assisted extraction using response surface methodology. The optimized conditions—30 min of extraction time, 30% ultrasonic power, and 25% hydro-ethanolic solvent—resulted in a high total phenolic content of 113.07 mg EAG/g DM and antioxidant activity of 67.02%. Chromatographic analysis revealed a rich profile of phenolic compounds, including sinapic acid (0.741 mg/g), myricetin (0.62 mg/g), and quercetin-3-O-rutinoside (0.3 mg/g), demonstrating the extract’s potent therapeutic properties. While the extract exhibited limited anti-inflammatory activity, it showed no cytotoxic effects on RAW 267.4 cells, ensuring its safety for cosmetic applications. The formulated cream maintained stable pH (6.58 to 6.6), consistent viscosity (5966.38 to 5980.6 cp), and minimal color changes over a 30-day period, indicating robust stability across various temperatures (4 °C, 25 °C, and 40 °C). These results confirm the potential of C. nodosa extracts to develop effective, stable, and eco-friendly cosmetic products, offering substantial benefits for skin health and emphasizing the importance of sustainable extraction processes in the cosmetics industry.

Bio-Guided Extraction of a Phenolic-Rich Extract from Industrial Peanut Skin with Antioxidant and Hypotensive Potential

Peanut composition includes phenolic compounds, especially in the skins, which are often not consumed. High blood pressure affects more than one billion people worldwide and is considered a high-risk factor for cardiovascular diseases. Several studies have correlated antihypertensive activity with the total phenolic content present in the plants. This study evaluated the hydroethanolic extraction of phenolic compounds from the industrial residue of peanut skin and evaluated the antioxidant and antihypertensive capacity of these extracts using in vitro models. A rotational central composite design (DCCR) was proposed to study the influence of the variables: (1) the ethanol concentration on the hydroalcoholic extractor solution, and (2) the proportion of solid sample (waste) per liquid in the extraction (mass/volume) in a simple solid—a liquid extraction process. The optimal extraction conditions within this model were 50% ethanol in water, and the proportion of sample to extraction solution (m/v) equaled to 0.2. The extract obtained had significant antioxidant capacity, both in chemical (ORAC) and in cellular models, with potential for free radical scavenging. Significant levels of ACE inhibition were also found, indicating antihypertensive activity.

Detecting command injection attacks in web applications based on novel deep learning methods

Web command injection attacks pose significant security threats to web applications, leading to potential server information leakage or severe server disruption. Traditional detection methods struggle with the increasing complexity and obfuscation of these attacks, resulting in poor identification of malicious code, complicated feature extraction processes, and low detection efficiency. To address these challenges, a novel detection model, the Convolutional Channel-BiLSTM Attention (CCBA) model, is proposed, leveraging deep learning techniques to enhance the identification of web command injection attacks. The model utilizes dual CNN convolutional channels for comprehensive feature extraction and employs a BiLSTM network for bidirectional recognition of temporal features. An attention mechanism is also incorporated to assign weights to critical features, improving the model’s detection performance. Experimental results demonstrate that the CCBA model achieves 99.3% accuracy and 98.2% recall on a real-world dataset. To validate the robustness and generalization of the model, tests were conducted on two widely recognized public cybersecurity datasets, consistently achieving over 98% accuracy. Compared to existing methods, the proposed model offers a more effective solution for identifying web command injection attacks.

Valorization of Residual Fractions from Defatted Rice Bran Protein Extraction: A Carbohydrate-Rich Source for Bioprocess Applications

Defatted rice bran (DRB) is the by-product of rice bran oil extraction and presents approximately 66% carbohydrates and 15% proteins, a composition with the potential to integrate biorefinery systems. This study aimed to investigate the feasibility of residual fractions from ultrasound-assisted protein extraction from DRB as sources of carbohydrates in bioprocesses. First, DRB was exposed to protein extraction in an alkaline medium assisted by ultrasound. The residual fractions, including the precipitate from the extraction process (P1) and the supernatant from protein precipitation (S2), were combined and autoclaved to gelatinize the starch. Enzyme activity tests showed that a temperature of 70 °C was optimal for the simultaneous application of α-amylase and amyloglucosidase (AMG). To study enzymatic hydrolysis, a Full Factorial Design (FFD) 22 was employed, with α-amylase and AMG concentrations ranging from 0.12 to 0.18 mL∙L−1 and a substrate concentration (P1/S2 ratio) between 30 and 70 g∙L−1, resulting in a maximum of 18 g∙L−1 of reducing sugars (RS). Fermentation assays with Saccharomyces cerevisiae demonstrated that the hydrolysate of the residual fractions was effective for ethanol production (8.84 g∙L−1 of ethanol; YP/S: 0.614 gethanol∙gRS−1; η: 120.24%), achieving results comparable to control media (with sucrose as the substrate), indicating its potential for application in bioprocesses. These outcomes highlight a promising technological approach for utilizing DRB in integrated biorefineries.

Deep Eutectic Solvents Coated with Glycoside Surfactants-Based Novel Micelles for Simultaneous Extraction and In Situ Enrichment of Natural Phenolic Compounds in One Extraction Process

Deep Eutectic Solvents Coated with Glycoside Surfactants-Based Novel Micelles for Simultaneous Extraction and In Situ Enrichment of Natural Phenolic Compounds in One Extraction Process

Recovery and partial isolation of ⍺-mangostin from mangosteen pericarpsvia sequential extraction and precipitation.

This study introduced an innovative sequential extraction methodology designed for the efficient recovery of alpha-mangostin (⍺-M) from mangosteen pericarps. Alpha-mangostin, renowned for its pharmacological properties including anti-inflammatory, anti-cancer, and anti-bacterial effects, has garnered significant attention across diverse industries. The proposed method of sequential extraction achieved 73% recovery and a yield of 46.75 mg/g based on the weight/weight percentage of the mass of ⍺-M extracted from the sequence and the mass of raw material. Furthermore, the purity of the dried product was 67.9%. The sequence solvent extraction system, comprising water, hexane, and acetonitrile, plays a pivotal role in enhancing the efficacy of the extraction process. Notably, this methodology offers a cost-effective alternative to conventional extraction methods. It reduces the need for complex equipment and processes, positioning it as a resource-efficient extraction technique in comparison to existing methodologies. This novel sequential extraction method presents a promising avenue for the economical and sustainable recovery of alpha-mangostin (⍺-M) from pericarps.

Influence of polypropylene fiber length and geometric shape on the compressive strength of cemented lepidolite tailings backfill

Lepidolite ore contains abundant lithium resources; however, the extraction process generates a large number of tailings, which are environmentally hazardous solid waste. Currently, cemented fiber reinforcement and tailings filling technologies are commonly used methods for tailings treatment. The fiber length and geometric shape significantly affect the performance of fiber-reinforced cemented lepidolite tailing backfill (CLTB). However, there is limited research on the impact of these two factors on the performance of CLTB. Consequently, Polypropylene fiber-reinforced CLTB of four sizes and four fiber lengths were prepared and used for uniaxial compressive strength (UCS) tests. The max UCS of fiber-reinforced CLTB was 2.84 MPa, and the maximum increase percent was 83.7% compared with the non-fiber-reinforced CLTB. The experimental results show that when the fiber length was 12 mm the CLTB had the maximum UCS, longer fibers did not necessarily result in a higher UCS. The end effect was significant when the difference in cross-sectional area was small. The UCS of the L-40 sample was higher than that of the Y-50 sample under the same fiber length. The differences in the size effect and geometric shape were the main factors influencing their mechanical performance. When the fiber length was from 0 mm to 6 mm, the size effect was obvious, the UCS values gradually decreased with an increase in the volume ratio and cross-sectional area. However, the fiber length was the primary factor influencing the fitting curve of the UCS when the fiber length was from 12 mm to 19 mm. Additionally, the addition of fibers enhanced the integrity of CLTB. In other words, fiber-reinforced CLTB exhibited improving structural integrity. This study can provide theoretical references for the research and practical applications of fiber-reinforced fillers and size effects, as well as the treatment of lepidolite tailings, while also reflecting the CLTB performance under the action of different sizes and different fiber lengths, improving the filling efficiency, mining, and backfill safety.

Recovery of Rhodium by Solvent Extraction using N, N, N′, N′, N″, N″-Hexahexyl-nitrilotriacetamide and Electrodeposition

The development of solvent extraction and direct electrodeposition processes is crucial for reducing the volume of secondary waste. In this study, the extraction behavior of Rh(III) using N, N, N, N′, N′, N′-hexahexyl nitrilotriacetamide (NTAamide(C6)) was investigated with three different diluents that have relatively high dielectric constants. Slope analysis revealed that the extraction mechanism of Rh(III) is based on ion-pair extraction. The electrochemical behavior of the extracted Rh(III) complexes in each diluent was investigated using cyclic voltammetry. Rh(III) was reduced to Rh(0) through a three-electron transfer in the NTAamide(C6)/acetophenone, 1,2-dichloroethane, and 1-octanol systems. Moreover, the diffusion coefficient of the extracted Rh(III) complex was evaluated using semi-differential analysis. The electrodeposits were recovered through continuous solvent extraction and direct electrodeposition. The electrodeposits were identified as Rh metals by X-ray photoelectron spectroscopy and X-ray diffraction analyses.

Optimization of the Helium Extraction Process from Natural Gas with Integrated Cryogenic–Membrane Separation

Optimization of the Helium Extraction Process from Natural Gas with Integrated Cryogenic–Membrane Separation