Search Results (35)

To explore the influence of guide vanes on the energy loss of hydraulic turbines, a pump characterized by a simple structure and convenient operation was selected as the research subject. Entropy generation theory was utilized to analyze entropy generation losses at different flow rates, with a particular emphasis on the mechanisms in the impeller and draft tube. The findings indicate that turbulent entropy production dominates energy dissipation. Under the best efficiency point (BEP), the total entropy generation loss of Z₀ = 11 turbine was 7.18% and 5.76% lower than that of Z₀ = 7 and Z₀ = 9, respectively. The proportion of entropy generation loss in the impeller was highest under low-flow and optimal operating conditions, while the proportion of entropy generation loss in the draft tube was highest under high-flow conditions. In guide-vane-free turbines, the impeller’s high turbulent entropy generation rate was attributed to vortices and backflow caused by significant velocity gradients. For guide-vane-equipped turbines, high turbulent entropy generation rates arose from rotor–stator interactions and flow separation at blade inlets. Under high-flow-rate conditions, the entropy generation loss in the draft tube was significantly larger than that in other flow components, primarily due to vortices generated by excessive velocity circulation at the impeller outlet near the upstream draft tube flow passages, leading to high turbulent entropy generation rates. Full article

The gas-liquid sulfonation of α-olefin sulfonate (AOS) in falling film reactors faces significant limitations, primarily due to poor mass transfer efficiency and excessive byproduct formation. To overcome these challenges, a novel cross-shaped microchannel reactor was developed for the continuous gas-liquid sulfonation of α-olefin (AO) with gaseous sulfur trioxide (SO₃). The influence of key process parameters, including gas-phase flow rate, reaction temperature, SO₃/AO molar ratio, and SO₃ volume fraction, on product characteristics and their interactions was systematically investigated using the single-factor experiment and response surface methodology (RSM). A high-precision empirical model (coefficient of determination, R² = 0.9882) to predict product content was successfully constructed. To achieve multi-objective optimization considering product active substance content and energy efficiency, a strategy combining a two-population genetic algorithm with the entropy-weighted TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method was implemented. Optimal conditions were determined as follows: gas-phase flow rate of 228 mL/min, reaction temperature of 52 °C, SO₃/AO molar ratio of 1.27, and SO₃ volume fraction of 4%. Compared to conditions optimized solely by RSM, this multi-objective approach achieved a significant 10% reduction in energy efficiency, with only a marginal 3.8% decrease in active substance content. This study demonstrates the feasibility and advantages of microreactors for the efficient and green synthesis of AOS. Full article

Biodegradable mulch films not only provide similar field benefits to conventional mulch films but also degrade naturally, rendering them an effective alternative to traditional polyethylene mulch films for mitigating “white pollution”. However, recent studies have focused on the material selection and soil ecological impacts of biodegradable mulch films, while their effects on soil water temperature regulation and root architecture in drip-irrigated rice cultivation remain unclear. To address this research gap, in this study, various treatments including no mulch (NM), conventional plastic mulch (PM), and four types of biodegradable mulch films (BM-W₁, BM-B₁, BM-B₂, and BM-B₃) were established, and their effects on the soil hydrothermal flux, root architecture, biomass accumulation, and resource use efficiency of drip-irrigated rice were analyzed at different growth stages. The results indicated the following: (1) Compared with the NM treatment, film mulching increased the soil hydrothermal fluxes and water retention capacity, thereby promoting root growth and biomass accumulation, ultimately increasing the effective panicle number and grain yield. (2) Among the biodegradable film treatments, BM-B₃ (with a degradation period of 105 days) maintained relatively higher soil temperature for a longer duration, which increased surface root distribution in the mid-to-late growth stages, further improving fine root growth and biomass accumulation, consequently enhancing both yield and water use efficiency. In contrast, BM-B₁ and BM-B₂ exhibited excessively rapid degradation rates, leading to significant fluctuations in soil moisture and temperature, thereby negatively affecting water supply and nutrient uptake and ultimately restricting root growth and development. (3) The entropy weight (EW) technique for order of preference by similarity to ideal solution (TOPSIS) model results revealed that although the PM treatment was more advantageous in terms of soil temperature, root dry weight, and soil moisture content, BM-B₃ provided a slightly higher yield than the PM treatment did and offered the advantage of biodegradability, making it a preferred alternative to conventional mulch film. In summary, this study revealed the mechanism by which biodegradable mulch films enhanced biomass accumulation and yield formation in drip-irrigated rice production by optimizing soil hydrothermal dynamics and root architecture, thereby exploring their potential as replacements for conventional mulch films. These findings provide a theoretical basis for the efficient and sustainable production of drip-irrigated rice in arid regions. Full article

The exchange of food commodities significantly contributes to alleviating the strain on land used for agricultural production by linking areas rich in land with those facing resource limitations. This study employs the entropy weight–TOPSIS method to measure the water–land–food system, utilizes a two-way fixed-effects model to examine the impact of food import competition on the coordination of the water–land–food system, and applies a spatial Durbin model to explore the spatial spillover effects of this impact. The findings indicate the following: (1) The average coordination level of the WLF system in China stands at 0.317, showing considerable variability. The WLF system coordination in all regions of China initially decreased and then increased in the period studied, with the northeast region exhibiting the highest level of coordination. (2) The competitive effect of domestic and foreign food costs driven by food imports has a positive impact on the coordination of the WLF system. For every 100,000 hectares of land saved through the competition effect, the coordination of China’s WLF system increases by 0.002. However, once the saved land exceeds 1.5 million hectares, the impact of import competition on the importing country’s food market becomes excessive and starts to have a negative effect. (3) Split-sample regression revealed that the positive effect of food import competition on the coordination of the WLF system is stronger in the southern region compared to the northern region. Additionally, the increase in the competition effect has a more pronounced impact on the coordination of the WLF system in major food production areas than in non-major production areas. (4) Based on the results of the spatial econometric model, the increase in the competitive effect of food imports in a region not only increases the coordination of the WLF system within that region but also positively impacts the coordination of the system in neighboring regions. (5) The land use efficiency of food imports acts as a conduit for the impact of food import competition on the coordination of the WLF system. Full article

The seawater circulation pump represents the pump product with the largest flow rate within nuclear power plants. Its energy consumption accounts for a substantial portion of the energy consumed by nuclear power plants. To investigate the internal flow characteristics of the seawater circulation pump and optimize the performance while reducing energy consumption, taking the seawater circulation pump as the research object, the entropy production of each flow passage component of the pump under different flow conditions are analyzed by employing numerical simulation based on the entropy production theory. Additionally, the entropy production mechanisms of the impeller and volute are specifically analyzed. The results demonstrate that under different flow conditions, the impeller and volute are the main flow components contributing to entropy production losses for the entire pump. The leading and trailing edges of the blade and the shroud are the main locations where entropy production occurs in the impeller. Excessive attack angle and circulation are the main factors leading to entropy production. The throat area of the volute is the main entropy production area of the volute, and the secondary flow and vortex caused by flow separation are the main causes of entropy production. Full article

Chatter is a common phenomenon in micromachining processes that adversely affects machining quality, reduces tool life, and generates excessive noise that contributes to environmental pollution. Therefore, the timely detection of chatter is crucial for sustainable production. This paper presents an investigation on the extraction of two types of features, i.e., probability-related and entropy-related, using Shannon entropy and Rényi entropy algorithms, respectively, for chatter detection in micro milling. First, four chatter features were examined using actual machining tests under stable, weak-chatter, and severe-chatter conditions. Second, the proposed chatter features were systematically assessed by combining the characteristic change rates, threshold intervals, and computation times. The results demonstrated that the proposed features can effectively detect the occurrence of chatters at various severity levels. It was found that the probability-related features exhibit better sensitivity compared to entropy-related features, and the features extracted from Shannon entropy algorithm are more sensitive than the Rényi entropy algorithm. Full article

Excessive non-grain production of farmland (NGPF) seriously affects food security and hinders progress toward Sustainable Development Goal 2 (Zero Hunger). Understanding the spatial distribution and influencing factors of NGPF is essential for food and agricultural management. However, previous studies on NGPF identification have mainly relied on high-cost methods (e.g., visual interpretation). Furthermore, common machine learning techniques have difficulty in accurately identifying NGPF based solely on spectral information, as NGPF is not merely a natural phenomenon. Accurately identifying the distribution of NGPF at a grid scale and elucidating its influencing factors have emerged as critical scientific challenges in current literature. Therefore, the aims of this study are to develop a grid-scale method that integrates multisource remote sensing data and spatial factors to enhance the precision of NGPF identification and provide a more comprehensive understanding of its influencing factors. To overcome these challenges, we combined multisource remote sensing images, natural/anthropogenic spatial factors, and the maximum entropy model to reveal the spatial distribution of NGPF and its influencing factors at the grid scale. This combination can reveal more detailed spatial information on NGPF and quantify the integrated influences of multiple spatial factors from a microscale perspective. In this case study of Foshan, China, the area under the receiver operating characteristic curve is 0.786, with results differing by only 1.74% from the statistical yearbook results, demonstrating the reliability of the method. Additionally, the total error of our NGPF identification result is lower than that of using only natural/anthropogenic information. Our method enhances the spatial resolution of NGPF identification and effectively detects small and fragmented farmlands. We identified elevation, farming radius, and population density as dominant factors affecting the spatial distribution of NGPF. These results offer targeted strategies to mitigate excessive NGPF. The advantage of our method lies in its independence from negative samples. This feature enhances its applicability to other cases, particularly in regions lacking high-resolution grain crop-related data. Full article

The health monitoring of vegetable and fruit plants, especially during the critical seedling growth stage, is essential to protect them from various environmental stresses and prevent yield loss. Different environmental stresses may cause similar symptoms, making visual inspection alone unreliable and potentially leading to an incorrect diagnosis and delayed corrective actions. This study aimed to address these challenges by proposing a segmented regression model and a Mask R-CNN model for detecting the initiation time and symptoms of nutrient stress in cucumber seedlings within a controlled environment. Nutrient stress was induced by applying two different treatments: an indicative nutrient deficiency with an electrical conductivity (EC) of 0 dSm⁻¹, and excess nutrients with a high-concentration nutrient solution and an EC of 6 dSm⁻¹. Images of the seedlings were collected using an automatic image acquisition system two weeks after germination. The early initiation of nutrient stress was detected using a segmented regression analysis, which analyzed morphological and textural features extracted from the images. For the Mask R-CNN model, 800 seedling images were annotated based on the segmented regression analysis results. Nutrient-stressed seedlings were identified from the initiation day to 4.2 days after treatment application. The Mask R-CNN model, implemented using ResNet-101 for feature extraction, leveraged transfer learning to train the network with a smaller dataset, thereby reducing the processing time. This study identifies the top projected canopy area (TPCA), energy, entropy, and homogeneity as prospective indicators of nutritional deficits in cucumber seedlings. The results from the Mask R-CNN model are promising, with the best-fit image achieving an F1 score of 93.4%, a precision of 93%, and a recall of 94%. These findings demonstrate the effectiveness of the integrated statistical and machine learning (ML) methods for the early and accurate diagnosis of nutrient stress. The use of segmented regression for initial detection, followed by the Mask R-CNN for precise identification, emphasizes the potential of this approach to enhance agricultural practices. By facilitating the early detection and accurate diagnosis of nutrient stress, this approach allows for quicker and more precise treatments, which improve crop health and productivity. Future research could expand this methodology to other crop types and field conditions to enhance image processing techniques, and researchers may also integrate real-time monitoring systems. Full article

As one of the main industrial segments of the current geoeconomics scenario, agro-industrial activities generate excessive amounts of waste. The gasification of such waste using supercritical water (SCWG) has the potential to convert the waste and generate products with high added value, hydrogen being the product of greatest interest. Within this context, this article presents studies on the SCWG processes of lignocellulosic residues from cotton, rice, and mustard husks. The Gibbs energy minimization (minG) and entropy maximization (maxS) approaches were applied to evaluate the processes conditioned in isothermal and adiabatic reactors, respectively. The thermodynamic and phase equilibria were written as a nonlinear programming problem using the Peng–Robinson state solution for the prediction of fugacity coefficients. As an optimization tool, TeS (Thermodynamic Equilibrium Simulation) software v.10 was used with the help of the trust-constr algorithm to search for the optimal point. The simulated results were validated with experimental data presenting surface coefficients greater than 0.99, validating the use of the proposed modeling to evaluate reaction systems of interest. It was found that increases in temperature and amounts of biomass in the process feed tend to maximize hydrogen formation. In addition to these variables, the H₂/CO ratio is of interest considering that these processes can be directed toward the production of synthesis gas (syngas). The results indicated that the selected processes can be directed to the production of synthesis gas, including the production of chemicals such as methanol, dimethyl ether, and ammonia. Using an entropy maximization approach, it was possible to verify the thermal behavior of reaction systems. The maxS results indicated that the selected processes have a predominantly exothermic character. The initial temperature and biomass composition had predominant effects on the equilibrium temperature of the system. In summary, this work applied advanced optimization and modeling methodologies to validate the feasibility of SCWG processes in producing hydrogen and other valuable chemicals from agro-industrial waste. Full article

A hypothesis is presented to explain how the ageing process might be influenced by optimizing mitochondrial efficiency to reduce intracellular entropy. Research-based quantifications of entropy are scarce. Non-equilibrium metabolic reactions and compartmentalization were found to contribute most to lowering entropy in the cells. Like the cells, mitochondria are thermodynamically open systems exchanging matter and energy with their surroundings—the rest of the cell. Based on the calculations from cancer cells, glycolysis was reported to produce less entropy than mitochondrial oxidative phosphorylation. However, these estimations depended on the CO₂ concentration so that at slightly increased CO₂, it was oxidative phosphorylation that produced less entropy. Also, the thermodynamic efficiency of mitochondrial respiratory complexes varies depending on the respiratory state and oxidant/antioxidant balance. Therefore, in spite of long-standing theoretical and practical efforts, more measurements, also in isolated mitochondria, with intact and suboptimal respiration, are needed to resolve the issue. Entropy increases in ageing while mitochondrial efficiency of energy conversion, quality control, and turnover mechanisms deteriorate. Optimally functioning mitochondria are necessary to meet energy demands for cellular defence and repair processes to attenuate ageing. The intuitive approach of simply supplying more metabolic fuels (more nutrients) often has the opposite effect, namely a decrease in energy production in the case of nutrient overload. Excessive nutrient intake and obesity accelerate ageing, while calorie restriction without malnutrition can prolong life. Balanced nutrient intake adapted to needs/activity-based high ATP requirement increases mitochondrial respiratory efficiency and leads to multiple alterations in gene expression and metabolic adaptations. Therefore, rather than overfeeding, it is necessary to fine-tune energy production by optimizing mitochondrial function and reducing oxidative stress; the evidence is discussed in this paper. Full article

Properties such as lower melting temperature, good tensile strength, good reliability, and well creep resistance, together with low production cost, make the system Bi-Sn an ideal candidate for fine soldering in applications such as reballing or reflow. The first objective of the work was to determine the thermodynamic quantities of Bi and Sn using the electromotive force measurement method in an electrolytic cell (Gibbs’ enthalpies of the mixture, integral molar entropies, and the integral molar excess entropies were determined) at temperatures of 600 K and 903 K. The second objective addressed is the comprehensive characterization of three alloy compositions that were selected and elaborated, namely Bi25Sn75, Bi50Sn50, and Bi75Sn25, and morphological and structural investigations were carried out on them. Optical microscopy and SEM-EDS characterization revealed significant changes in the structure of the elaborated alloys, with all phases being uniformly distributed in the Bi50Sn50 and Bi75Sn25 alloys. These observations were confirmed by XRD and EDP-XRFS analyses. Diffractometric analysis reveals the prevalence of metallic Bi and traces of Sn, the formation of the Sn_0.3Bi_0.7, Sn_0.95Bi_0.05 compounds, and SnO and SnO₂ phases. Full article

The development of high-entropy anodes, known for their excellent catalytic activity for water oxidation, can depress the energy consumption of hydrogen production by water electrolysis. However, the complex preparation methods and poor stability hindered their practical application. In this work, a one-step co-precipitation method has been modified to rapidly synthesize ultrathin high-entropy layered double hydroxide containing Ni, Co, Fe, Cr, Zn. Through the rational selection of metal elements, the stability of the optimized anode under Ampere-level current density has been significantly improved. Compared to NiFe-LDH, the active site leaching of high-entropy LDH is reduced by 42.7%, and as a result, it achieves a performance decay that is approximately eight times lower than that of NiFe-LDH. Experiment results show that the active sites in the high-entropy LDH can maintain a relatively low oxidation state both before and after activation, thus preventing material deactivation caused by excessive oxidation. Full article

Why do fractals appear in so many domains of science? What is the physical principle that generates them? While it is true that fractals naturally appear in many physical systems, it has so far been impossible to derive them from first physical principles. However, a proposed interpretation could shed light on the inherent principle behind the creation of fractals. This is the multiscale thermodynamic perspective, which states that an increase in external energy could initiate energy transport mechanisms that facilitate the dissipation or release of excess energy at different scales. Within this framework, it is revealed that power law patterns, and to a lesser extent, fractals, can emerge as a geometric manifestation to dissipate energy in response to external forces. In this context, the exponent of these power law patterns (thermodynamic fractal dimension $D$) serves as an indicator of the balance between entropy production at small and large scales. Thus, when a system is more efficient at releasing excess energy at the microscopic (macroscopic) level, $D$ tends to increase (decrease). While this principle, known as Principium luxuriæ, may sound promising for describing both multiscale and complex systems, there is still uncertainty about its true applicability. Thus, this work explores different physical, astrophysical, sociological, and biological systems to attempt to describe and interpret them through the lens of the Principium luxuriæ. The analyzed physical systems correspond to emergent behaviors, chaos theory, and turbulence. To a lesser extent, the cosmic evolution of the universe and geomorphology are examined. Biological systems such as the geometry of human organs, aging, human brain development and cognition, moral evolution, Natural Selection, and biological death are also analyzed. It is found that these systems can be reinterpreted and described through the thermodynamic fractal dimension. Therefore, it is proposed that the physical principle that could be behind the creation of fractals is the Principium luxuriæ, which can be defined as “Systems that interact with each other can trigger responses at multiple scales as a manner to dissipate the excess energy that comes from this interaction”. That is why this framework has the potential to uncover new discoveries in various fields. For example, it is suggested that the reduction in $D$ in the universe could generate emergent behavior and the proliferation of complexity in numerous fields or the reinterpretation of Natural Selection. Full article

Accurate soil management has long been the focus of research in agroecology. Crop productivity can be enhanced while reducing environmental threats from excessive fertilization by fully comprehending the spatial variability of soil properties and delineating management zones (MZs). A field investigation was carried out at experimental sites outside Hefei City’s administrative districts in China to study the spatial variability of soil properties and the delineation of MZs. A total of 9601 soil samples were collected in the study area. A variety of soil properties were analyzed, including the pH, organic matter, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, available potassium, slowly released potassium, available sulfur, available boron, available copper, available zinc, available iron, and available manganese. The coefficient of variation for various soil properties exhibited a wide range, spanning from 12.2% to 100.5%. The geostatistical results show that most soil properties have moderate to strong spatial autocorrelation, and the ordinary kriging method is used to map the distribution of soil properties. The principal component analysis method was used to reduce the dimension of 13 soil properties to 4 principal components, and the fuzzy c-means clustering method was used to delineate MZs. The calculation results of the fuzzy performance index and normalized classification entropy show that the optimum number of MZs is five. In the study area, the western part exhibits the highest soil fertility, primarily attributed to its elevated organic matter content. Additionally, organic matter emerges as a key factor influencing sustainable agricultural production in this region. These results form the basis for soil managing areas outside the administrative districts of Hefei City. Full article

Water scarcity and the excessive application of nitrogen fertilizer are key factors limiting the sustainable development of the hybrid seed maize industry in the oasis agricultural areas of the Hexi Corridor in China. To determine the optimal water–nitrogen management regime of hybrid seed maize, we established a field experiment in 2020–2021 with three irrigation quotas (W1, W2, and W3 were 60, 80, and 100% of the local conventional irrigation quota, respectively) and four nitrogen application levels (N0, N1, N2, and N3 were 0, 190, 285, 380 kg·hm⁻²). We analysed the influence of different water–nitrogen combinations on indices of seed vigour, yield, water use efficiency (WUE), irrigation water use efficiency (IUE), the partial productivity of nitrogen fertilizer (NFP), and the nitrogen fertilizer agronomic use efficiency (NFA) of hybrid seed maize. A comprehensive growth evaluation system for hybrid seed maize was established based on the AHP, entropy weight, and TOPSIS methods, and a coupled water–nitrogen response model for hybrid seed maize was established with the objectives of obtaining high-yield, efficient, and high-seed vigour. The results showed that the yield of hybrid seed maize, NFP, and NFA gradually increased with the increase in the irrigation amount, while IUE continuously decreased; the yield of hybrid seed maize, WUE, and NFA increased and then decreased, while NFP continuously decreased with an increase in the amount of nitrogen application. Further, treatment N2W3 had higher water and nitrogen use efficiency and the highest yield and seed viability with a yield of 9209.11 kg·hm⁻² and germination percentage, germination index, and vigour index of 97.22, 58.91, and 1.55%, respectively. The model of the integrated growth response of hybrid seed maize to water–nitrogen showed that the combined benefits of the hybrid seed maize yield, WUE, and seed viability could be maximised in conjunction with the irrigation rate ranging from 3558.90 to 3971.64 m³·hm⁻² and the fertiliser application rate of 262.20 to 320.53 kg·hm⁻². This study can provide scientific guidance and act as a decision-making reference for the productive, efficient, and sustainable development of hybrid seed maize in the oasis agricultural area of the Hexi Corridor. Full article