Search Results (304)

Arabinoxylan is a polysaccharide with film-forming properties, present in corn fiber, and a low-value by-product. The extract has a deep brown color, producing films of the same shade, which may not be appealing. This study addresses, for the first time, the adsorption of colored compounds present in an arabinoxylan extract using resin MN102. The resin successfully adsorbed the colored compounds from the arabinoxylan extract. After four consecutive adsorption/desorption cycles, the efficiency of the resin was similar, only decreasing from 63.3% to 52.9%. Langmuir and Freundlich models were fitted to the results of adsorption isotherm experiments, with the Freundlich model demonstrating the best fit to the experimental results. A fixed-bed column loaded with the resin was used for the removal of the colored compounds from the arabinoxylan extract, and the effect of the volumetric flow rate was investigated. The Yan and log-Gompertz models showed the best fit to the experimental breakthrough curves. This study systematically evaluated the adsorption conditions, providing a comprehensive analysis of the performance of the resin in the removal of the colored compounds. Additionally, the ability of the extract to maintain its film-forming properties after decolorization was evaluated, and some of the film’s key characteristics were evaluated, namely its color, solubility in water and mechanical properties. Full article

Background/Objectives: On 6 June 2023, two varicella cases were reported at a highly vaccinated elementary school in Gyeonggi Province, Republic of Korea. We investigated the outbreak to describe its transmission dynamics; quantify attack rates in school, household, and private-academy settings; and assess the impact of coordinated control measures. Methods: A case-series study included 89 teachers and students who had contact with suspected patients. Using case definitions, laboratory tests, questionnaires, and environmental assessments, we evaluated exposures and factors facilitating spread. Results: Varicella developed in 23 of 89 contacts (25.8%); laboratory confirmation was obtained in 2 (8.7% of cases). The mean incubation period was 13 days. Epidemic-curve and network analyses indicated that the outbreak began with a single index case and extended through household contacts and private educational facilities, ultimately involving multiple schools. Conclusions: Breakthrough transmission can occur even when single-dose coverage exceeds 95%, particularly as vaccine-induced immunity may wane over time. Poorly regulated extracurricular facilities, such as private academies, act as bridging hubs that amplify spread across grades and even between schools. For timely detection and control, these venues should be incorporated into routine varicella surveillance, and rapid, coordinated infection-control measures are required across all educational settings. Full article

Path planning for picking safflowers is a key component in ensuring the efficient operation of robotic safflower-picking systems. However, existing single-arm picking devices have become a bottleneck due to their limited operating range, and a breakthrough in multi-arm cooperative picking is urgently needed. To address the issue of inadequate adaptability in current path planning strategies for dual-arm systems, this paper proposes a novel path planning method for dual-arm picking (LTSACO). The technique centers on a dynamic-weight heuristic strategy and achieves optimization through the following steps: first, the K-means clustering algorithm divides the target area; second, the heuristic mechanism of the Ant Colony Optimization (ACO) algorithm is improved by dynamically adjusting the weight factor of the state transition probability, thereby enhancing the diversity of path selection; third, a 2-OPT local search strategy eliminates path crossings through neighborhood search; finally, a cubic Bézier curve heuristically smooths and optimizes the picking trajectory, ensuring the continuity of the trajectory’s curvature. Experimental results show that the length of the parallelogram trajectory, after smoothing with the Bézier curve, is reduced by 20.52% compared to the gantry trajectory. In terms of average picking time, the LTSACO algorithm reduces the time by 2.00%, 2.60%, and 5.60% compared to DCACO, IACO, and the traditional ACO algorithm, respectively. In conclusion, the LTSACO algorithm demonstrates high efficiency and strong robustness, providing an effective optimization solution for multi-arm cooperative picking and significantly contributing to the advancement of multi-arm robotic picking systems. Full article

In this study, MIL-101 (Cr) was synthesized and characterized in terms of its physical properties. The adsorption breakthrough curves for toluene were measured and compared to those of conventional adsorbents (i.e., silica gel and activated carbon) at typical indoor concentrations of toluene. The results show that MIL-101 (Cr) exhibits a 5–8 times higher adsorption capacity for toluene compared to silica gel at low concentrations. The adsorption isotherm of MIL-101 (Cr) for toluene conforms to the Langmuir model. Increasing temperature reduces the adsorption breakthrough time and saturation time, but it leads to a significant decrease in the adsorption capacity. During the breakthrough experiment, flow rate had little effect on adsorption capacity, but higher flow rates notably decreased the breakthrough and saturation times. The negative values of ΔG, ΔH, and ΔS indicate that the adsorption of toluene on MIL-101 (Cr) is a spontaneous and exothermic process. Compared to traditional adsorbents, MIL-101 (Cr) exhibits desirable performance in toluene adsorption in indoor environments. It shows significant potential for indoor air purification applications. Full article

Arsenic contamination in groundwater is a significant public health concern, with As(III) posing a greater and more challenging risk than As(V) due to its higher toxicity, mobility, and weaker adsorption affinity. Fe-Mn-based adsorbents offer a promising solution, simultaneously oxidizing As(III) to As(V), enhancing its adsorption. This study evaluates an Fe-Mn nanocomposite across typical batch (20 mg of adsorbent), fixed-bed column (28 g), and pilot-scale (2.5 kg) studies, bridging the gap between laboratory and real-world applications. Batch experiments yielded maximum adsorption capacities of 6.25 mg/g and 4.71 mg/g in a synthetic matrix and real groundwater, respectively, demonstrating the impact of the water matrix on adsorption. Operational constraints and competing anions led to a lower capacity in the pilot (0.551 mg/g). Good agreement was observed between the breakthrough curves in the pilot (breakthrough at 475 bed volumes) and the fixed-bed column studies (365–587 bed volumes) under similar empty bed contact times (EBCTs). The Thomas, Adams–Bohart, and Yoon–Nelson models demonstrated that lower flow rates and extended EBCTs significantly enhance arsenic removal efficiency, prolonging the operational lifespan. Our findings demonstrate the necessity of continuous-flow experiments using real contaminated water sources and the importance of optimizing flow conditions, EBCTs, and pre-treatment in order to successfully scale up Fe-Mn-based adsorbents for sustainable arsenic removal. Full article

With the current acceleration of climate change, there is a global demand for sustainable development and carbon emission reduction. As a major link in the global supply chain, the logistics industry’s green and low-carbon transformation has become a critical breakthrough in achieving the objective of reducing carbon emissions. This study develops a multidimensional assessment index method for the green logistics level. The study selects 51 major economies worldwide from 2000 to 2022 as research subjects. The cloud model–entropy value–TOPSIS method is applied to measure the green logistics level. The results of the green logistics level are analyzed from the perspectives of developed and developing countries, and their spatiotemporal evolution characteristics are explored. The study shows that (1) the green logistics level in developed countries is relatively high, mainly due to policy-driven, core technology advantages. However, they continue to encounter issues, such as regional imbalance and excessive green costs. (2) The green logistics level in developing countries is in the middle to lower level, limited by technological dependence, outdated infrastructure, and so on. They are generally caught in a “high-carbon lock-in” situation. (3) From the perspective of time, the global level of green logistics shows a rising trend year by year. The peak of the kernel density curve of the green logistics level is characterized by an “I” shape. There is a significant disparity in each country’s green logistics level, although it is narrowing every year. (4) From the spatial perspective, the green logistics level in each country shows a rising trend year by year vertically, while the horizontal disparity between countries is enormous. The development of the green logistics level between continents is unbalanced. The study presents several recommendations, including boosting technology transfer, giving financial support, strengthening international cooperation, and developing green infrastructure, to promote the global logistics industry’s green and low-carbon transformation to accomplish sustainable development goals. Full article

Numerous studies have been conducted employing various techniques to remove pollutants from water bodies. Among these techniques, adsorption a surface phenomenon that utilises adsorbents derived from agricultural residues has shown considerable potential for the removal of contaminants such as heavy metals. However, most of these investigations have been carried out at the laboratory scale, with limited efforts directed towards predicting the performance of these systems at an industrial level. Accordingly, the present study aims to model a packed bed column at industrial scale for the removal of Pb(II) and Ni(II) ions from aqueous solutions, employing biomass derived from oil palm residues as the adsorbent material. To achieve this, Aspen Adsorption was used as a modelling and simulation tool to evaluate the impact of bed height, inlet flow rate, and initial concentration through a parametric assessment. This evaluation incorporated the Freundlich, Langmuir, and Langmuir–Freundlich isotherm models in conjunction with the Linear Driving Force (LDF) kinetic model. The results indicated that the optimal operating parameters included a column height of 5 m, a flow rate of 250 m³/day, and an initial metal concentration of 5000 mg/L. Moreover, all models demonstrated removal efficiencies of up to 94.6% for both Pb(II) and Ni(II). An increase in bed height resulted in longer breakthrough and saturation times but led to a reduction in adsorption efficiency. Conversely, higher flow rates shortened these times yet enhanced efficiency. These findings underscore the potential of computational modelling tools as predictive instruments for evaluating the performance of adsorption systems at an industrial scale. Full article

Sedimentary facies identification constitutes a cornerstone of reservoir engineering. Traditional facies interpretation methods, reliant on manual log-response parameter analysis, are constrained by interpreter subjectivity, reservoir heterogeneity, and inefficiencies in resolving thin interbedded sequences and concealed fluvial sand bodies—issues marked by high interpretive ambiguity, prolonged cycles, and elevated costs. This study focuses on the Lower Cretaceous Yaojia Formation Member 1 (K2y1) in the satellite oilfield of the Songliao Basin, integrating sequence stratigraphy into a machine learning framework to propose an innovative convolutional neural network (CNN)-based facies recognition method using log-curve image groups by graphically transforming five log curves and establishing a CNN model that correlates log responses with microfacies. Results demonstrate the model’s capability to identify six microfacies types (e.g., subaqueous distributary channels, estuary bars, sheet sands) with 83% accuracy, significantly surpassing conventional log facies analysis. This breakthrough in interpreting complex heterogeneous reservoir lithofacies establishes a novel technical avenue for intelligent exploration of subtle hydrocarbon reservoirs. Full article

This study addresses the growing concern of water contamination by pharmaceutical residues, focusing on the simultaneous removal of paracetamol (PAR) and metronidazole (MTZ). Batch and fixed-bed column adsorption processes were evaluated using activated carbon. In the batch experiments, the effects of pH (3, 7, and 11), adsorbent mass (0.5, 1.25, and 2 g), and contact time (10, 30, and 60 min) were evaluated, while the fixed-bed column was optimized considering initial pollutants concentration (30, 40, and 50 mg/L), adsorbent mass (0.5, 0.75, and 1 g), and flow rate (5, 10, and 15 mL/min) to improve the maximum adsorption capacity of the bed for both pollutants (q_maxPAR and q_maxMTZ). Parameter estimation and model selection were performed using a Bayesian Monte Carlo approach. Optimal conditions in the batch system (pH = 7, W = 2 g, and time = 60 min) led to high removal efficiencies for both compounds (≥98%), while in the column system, the initial pollutant concentration was the most significant parameter to improve the maximum adsorption capacity of the bed, resulting in values equal to 49.5 and 43.6 mg/g for PAR and MTZ, respectively. The multicomponent Gompertz model showed the best performance for representing the breakthrough curves and is suitable for scale-up (R² ≥ 0.75). These findings highlight the complexity of multicomponent adsorption and provide insights, contributing to the development of more efficient and sustainable water treatment technologies for pharmaceutical residues. Full article

The simultaneous adsorption and removal of low concentrations of SO₂ and H₂S using experimental and simulation methods were investigated in this paper. The adsorption breakthrough performance of the single-component SO₂ or H₂S was determined in the activated carbon fixed-bed test. Langmuir and extended Langmuir equations in the Aspen adsorption module were used to describe the adsorption equilibrium of the single and bi-component SO₂ and H₂S system, respectively. The effects of gas hourly space velocity (GHSV) and temperature on the dynamic adsorption process of the bi-component SO₂/H₂S system were investigated. The concentration distribution and adsorption capacity of SO₂/H₂S in the bed were simulated. The results showed that the simulation for the single-component breakthrough curves of SO₂ or H₂S agreed well with the experimental data. It indicated that the model and simulation yielded engineering acceptable accuracy. For the bi-component adsorption, the competitive adsorption effect was observed, with H₂S as the weakly adsorbed component and SO₂ as the strongly adsorbed component. The dynamic adsorption process showed the sequence of initial adsorption, breakthrough, replacement, and equilibrium. The breakthrough curves were characterized by the distinct hump (roll-up) for H₂S, resulting from the replacement effect. The influence of GHSV and the temperature on the dynamic adsorption process were investigated, revealing that the lower velocity and temperature enhanced the adsorption. This work might be used for the design and optimization of adsorption bed for the simultaneous removal of SO₂ and H₂S in Claus tail gas. Full article

Activated carbons (ACs) are employed in the nuclear industry to mitigate the emission of potential radioactive iodine species. Their retention performances towards iodine are mainly dependent on the relative humidity due to the competitive effect induced by adsorbed water molecules. Thus, this work will focus on the prediction of AC behavior toward the capture of water vapor to better assess the poisoning effect on radiotoxic iodine removal. For the first time, H₂O breakthrough curves (BTCs) on nuclear grade ACs are predicted through a specific methodology based on the combination of transport phenomena with adsorption kinetics and equilibrium. Three ACs, similar to those deployed in the nuclear context, are considered within the present study. Our model is based on the Linear Driving Force Model (LDF), governed by an intraparticle diffusion mechanism, notably surface and Knudsen diffusions. In addition, the type V isotherms obtained for H₂O and the investigated carbon supports were described through the Klotz equation, taking into account the formation and progressive growth of H₂O clusters within the internal porosity. This methodology allowed us to successfully simulate the H₂O adsorption by a non-impregnated AC, where only physisorption phenomena are involved. In addition, promising results were highlighted when extrapolating to the two other impregnated ACs (AC 5KI and AC Nuclear). Full article

The large-scale production of high-purity hydrogen via pressure swing adsorption (PSA) remains a prominent research focus. This study develops a multi-component heat and mass transfer model for a lean hydrogen mixture (N₂/CO₂/H₂/CO = 44.6/35.4/19.9/0.1 mol%) on a coal-derived activated carbon (AC)/zeolite 13X layered bed to investigate its breakthrough curve and PSA purification performance. The model is implemented on the Aspen Adsorption platform and validated with published data. Parametric analysis of the breakthrough curve reveals that a high pressure and a low feed flow rate can delay the breakthrough of impurity gases. The simulated variations in pressure, purity, and recovery during the PSA cycle align with the published results. Studies on PSA cycle parameters show that, in general, a high pressure, a low feed flow rate, a short adsorption time, and a high P/F ratio improve purity but reduce recovery. The purity and recovery of the layered bed outperform those of the single-layer bed. Specifically, gradually modifying the AC/zeolite 13X length ratio from 10:0 to 5:5 enhances hydrogen purity, while adjusting it from 10:0 to 3:7 enhances hydrogen recovery. At AC/zeolite 13X = 5:5, the highest purity was 97.38%, while at AC/zeolite 13X = 3:7, the highest recovery was 49.13%. Full article

This paper presents the world’s first radar detection experiment conducted in a 7500-m ultra-deep well. By applying ground-penetrating radar technology to petroleum logging, the developed borehole radar system successfully achieved stratigraphic information detection in the 7200–7500 m section of Shunbei Well No. 2. Utilizing electromagnetic wave reflection principles, the system acquires echo signals carrying medium characteristics through transmit–receive antenna arrays coupled with field-programmable gate array (FPGA)-based high-speed acquisition for real-time downhole data transmission. Experimental results demonstrate high consistency in Gamma Ray (GR) curves (correlation coefficient: 0.92) between radar data and Sinopec’s geological drilling data, particularly in key stratigraphic features such as casing reflections at a 7250-m depth (error of 0.013%). This breakthrough validates the operational stability and detection accuracy of borehole radar in complex subsurface environments, providing an innovative technological approach for ultra-deep hydrocarbon exploration. Full article

Stormwater reuse plays a critical role under changing climates and increasing water demands. This study investigates the removal efficacy of lead (Pb²⁺) and ammonia (NH₃) using sand and rice husk (RH) biochar for potential stormwater quality improvements and treatments. Column experiments combined with HYDRUS inverse modeling were conducted to optimize adsorption isotherms from breakthrough curves. Among linear and non-linear models, the Langmuir and Freundlich models performed better for sand and biochar, respectively. RH biochar showed much higher adsorption capacity of both Pb²⁺ (4.813 mg/g) and NH₃ (6.188 mg/g). In contrast, sand showed a relatively limited adsorption capacity for Pb²⁺ (0.118 mg/g) and NH₃ (0.104 mg/g). This can be contributed to higher pore size distribution, surface area, and the presence of different functional groups of biochar. The optimized adsorption coefficients and adsorption capacity parameters of sand and RH biochar by inverse modeling provided useful input for improving field designs. These findings will enhance the development of the best management practices (BMPs) for managing heavy metal and solute pollution in groundwater or stormwater low-impact development (LID) infrastructure systems. Full article

This study investigates the adsorption and reduction of NO₂ on biochar (BCC) and silver-modified biochar (Ag-BCC) in a continuous flow. Ag-BCC showed a higher NO₂ adsorption capacity (11.78 mg/g) than BCC (11.04 mg/g) at 200 °C, despite its lower surface area (345 vs. 402 m²/g). While neither material decomposed NO₂ at 22 °C, Ag-BCC achieved a NO/NO₂ ratio of 20% (vs. 9% for BCC) at 200 °C, highlighting the catalytic role of silver in NO₂ conversion. Breakthrough curve modeling identified the Dose–Response model as optimal, accurately describing adsorption kinetics at all temperatures (22–200 °C). Adsorption rate constants decreased with increasing temperature, confirming exothermicity. Overall, the results highlight the enhanced performance of Ag-BCC for NO₂ capture and conversion, underlining the potential of surface-modified biochars in the sustainable mitigation of air pollution. Full article