Search Results (84)

Phosphogypsum (PG) is a byproduct of the wet phosphoric acid (WPA) production process. Since PG originates from phosphate rock (PR), it holds various concentrations of heavy metal and radionuclide, posing an environmental threat because of its large production and long-term accumulation. In addition to toxic heavy metals, PG may also be an alternative source of rare earth elements (REEs), since over 60% of REEs in PR transfer to PG during acid digestion. With the increasing demand of phosphoric acid (PA), global PG generation is approaching 300 million tons annually. Since 1994, an estimated 6.73 billion tons of PG has been produced worldwide, with approximately 58% (approx. 3.7 billion tons) ending up in stacks. Assuming a conservative REE content of 0.1%, these stacks may hold over 3.7 million tons of REEs. This review discusses phosphoric acid production processes and the transfer of REEs from PR to PG. In addition, it also discusses the current REEs world reserves, their presence in primary and secondary sources, and their uses. The review critically evaluates the research that has been conducted so far and the recent innovations in REE recovery from PG, and discusses the challenges associated with scalability and raw material variability. Full article

Rice direct seeding for bunch planting is a sustainable agricultural production method that reduces production costs, improves rice lodging resistance, and conserves irrigation water in the field. However, there are notable differences in seed treatment between direct seeding on dry land and in paddy fields, which can impact the seeding process’s accuracy. This study employs the numerical simulation methods of computational fluid dynamics (CFDs) and discrete element method (DEM) to examine the motion characteristics of dry and wet rice seeds in a fluid–solid coupled domain and their impact on seeding accuracy. The aim is to guide the optimization of the rice air-suction seed metering device. Rice seeds were divided into dry and wet groups, and their physical properties were measured. Discrete element models of rice seeds were constructed and calibrated using a polyhedral method. The results show that the static friction coefficient between the seed meter and the seed ranged from 0.902 to 0.950, and the thousand-grain weights ranged from 25.89 to 32.42 g, which were higher than those of the dry rice seed, which ranged from 0.774 to 0.839, and from 25.89 to 32.42 g. After calibration, the errors between the simulated dynamic stacking angles of HHZD, HYD, YLYD, HHZW, HYW, and YLYW and the physical–dynamic stacking angles were 0.12%, 0.13%, 0.75%, 0.62%, 0.08%, 0.75%, 0.59%, and 1.24%, respectively, which indicated that the discrete element model for rice was reliable. Additionally, a seeding accuracy test revealed that wet seeds of the same variety had higher missing and single indices, while dry seeds had higher triple and multiple indices. Furthermore, CFD-DEM simulations demonstrated that wet seeds’ normal and tangential forces were more significant than those on dry seeds during the seed-filling process. At 40 rpm, the normal and tangential forces during the seed-filling process of HYW are 37.69 × 10⁻³ N and 12.47 × 10⁻³ N, respectively, which are higher than those of HYD (25.18 × 10⁻³ N and 9.19 × 10⁻³ N). The action force of suctioned rice seeds was directly proportional to the missing and single indices. The primary factors contributing to the discrepancy in seeding accuracy between dry and wet rice are the thousand-grain weight, the static friction coefficient between the seed meter and the seed, and the action force exerted between the rice seeds. In addition, using a shaped hole structure and optimizing the seed chamber structure can reduce normal and tangential forces and improve seeding accuracy. This study provides a reference for the simulation of rice seed flow-solid coupling and optimization of air-suction seed metering devices. Full article

Sandy red clay, abundant in clay minerals, exhibits a marked sensitivity to variations in water content. Several of its properties are highly prone to deterioration due to wet–dry cycling, potentially leading to slope instability. To investigate the multi-scale deterioration patterns and the underlying chain mechanism of sandy red clay subjected to wet–dry cycles, this study conducted systematic tests on remolded sandy red clay specimens through 0 to 5 wet–dry cycles, with the number of cycles (N) as the variable. The study’s results indicated the following, under wet–dry cycling: (1) Regarding the expansion and shrinking properties, the absolute expansion rate (δ_a) progressively increased, whereas the absolute shrinkage rate (η_a) gradually decreased. Concurrently, the relative expansion rate (δ_r) and relative shrinkage rate (η_r) gradually declined. (2) At the microscale, wet–dry cycles induced significant changes in the microstructure, characterized by increased particle rounding, disrupted stacked aggregates, altered inter-particle contacts, enlarged and interconnected pores, increased number of pores, and a reduction in clay mineral content. (3) At the mesoscale, cracks initiated and propagated. The evolution of cracks undergoes stages of initiation stage, propagation stage, and stable stage, and with the crack rate increasing to 2.0% after five cycles. (4) At the macroscale, the shear strength exhibited a continuous decline. After five cycles, cohesion decreased by as much as 49.6%, whereas the internal friction angle only decreased by 4.3%. This indicates that the loss of cohesion was the primary factor contributing to the strength deterioration. (5) A 19.4% decrease in the slope factor of safety (F_v) occurred after five cycles. This reduction was primarily attributed to the decrease in material cohesion and the upward shift in the potential sliding surface. Under the influence of wet–dry cycles, slope failures typically transitioned from overall or deep sliding to localized or shallow sliding. Full article

This study evaluates the impact of phosphogypsum stacks on the chemical composition of rainwater in the Huelva metropolitan area, a metal-polluted area with high cancer and heart disease mortality rates. A total of 612 rainwater samples were collected using 17 rain gauges located around the study area between January 2021 and December 2022. The pH, conductivity, major ions, and trace metals were detected in the soluble fraction of rainwater. The results revealed spatial variability in the rainwater quality. The highest values of As, Ca²⁺, Cr, F⁻, NH₄⁺, Ni, PO₄³⁻, SO₄²⁻, Sr, and V were detected in rain-gauges near phosphogypsum stacks, exceeding the levels of pH, F⁻, and Ni according to the guideline values for drinking water quality from the WHO. Additionally, other pollution sources also contributed: a regional source (marine factors: Ca²⁺, Cl⁻, K⁺, Mg²⁺, and Na⁺) and a local source (chemical complexes emissions: Co, Cu, Pb, and Zn). A downward trend of most toxic metal(loid) concentrations in wet depositions was detected as the distance to the affected area increased. The findings revealed that phosphogypsum stacks are a relevant source of metal(loid)s with potentially adverse environmental and public health effects that, if replicated, could be relevant for environmental monitoring and policy making. Full article

Extensive research has been conducted on the application of pyrolysis and hydrothermal carbonization (HTC) biochar for soil amendment. However, hydrochar from hydrothermal liquefaction (HTL) has received little attention regarding its potential for such application. This research paper aims to fill this knowledge gap. In this study, corn stover-derived hydrochar from HTL at 280 °C was characterized using suitable analytical techniques to determine the functional groups, specific surface area, and morphology. The effects of HTL hydrochar on water holding capacity (WHC) and water retention of sandy loam soil and the resistance to biodegradation were also studied. The BET surface area of hydrochar was found to be 27.6 m²/g. The hydrochar particles are micro-sized stacking of nanometer-thick foliates. The hydrochar-amended soil consistently showed better WHC ranging from 50 to 55% compared to the unamended soil of 48%. A similar trend was observed for water retention over a period of four days. No notable biodegradation was observed for the hydrochar over a period of 106 days in wet soil at the ambient temperature. Overall, these results demonstrate the potential of HTL hydrochar as a valuable soil amendment to enhance agriculture sustainability. Full article

The electrodes of thin film transistors (TFTs) have evolved from conventional single Cu layers to multi-layered structures formed by Cu and other metals or alloys. Different etching rates of various metals and galvanic corrosion between distinct metals may cause etching defects such as rough or uneven cross-sectional surfaces of stacked electrodes. Therefore, the etching of stacked electrodes faces new challenges. CD Bias and profile angle (PA) are two main performance indicators for the wet etching of TFT electrodes. Adjusting CD Bias and PAs quantitatively and evaluating their stability accurately is crucial to ensure the performance and yield of TFTs. In this work, the bilayer MoNb/Cu-stacked electrodes with different MoNb thicknesses and the MoNb/Cu/MTD triple-layered electrodes were prepared, and the influence of MoNb thickness and stacked structure on the CD Bias and PAs was investigated. It is found that in the H₂O₂-based etchant, the order of corrosion potential is E_MTD < E_MoNb < E_Cu; both MoNb/Cu and Cu/MTD will form a primary cell with MoNb or MTD as the anodes. The CD Bias and PAs of the MoNb/Cu bilayer structure also increase with MoNb thickness, but those of the MoNb/Cu/MTD triple-layered structure decrease with the introduction of the top MTD film. Finally, regression equations between CD Bias or PA and etching parameters were established based on the results of uniform experiments, and the 95% confidence intervals for CD Bias and PA were proposed after the Monte Carlo simulation. These obtained results provide a basis for quantitative adjustment of CD Bias and PA and precise control of etching stability. Full article

This paper introduces a Coriolis mass flow and density sensor. The sensor is made using Surface Channel Technology (SCT) but with selective wet etching to create the channels. This method forms suspended microfluidic channels with a larger cross-sectional area. Because of this larger cross-sectional area, the sensor has a much higher flow range, up to 50 $\mathrm{g} {\mathrm{h}}^{-1}$ (for water) with a pressure drop of 1 bar, compared to the standard SCT-based Coriolis sensor, which is only 1.2 $\mathrm{g} {\mathrm{h}}^{-1}$. The channel has a semi-elliptical cross-sectional area, measuring 200 micrometers wide and 70 micrometers deep. The channel wall is made of a stack of thin films with a total thickness of 2.5 $\mu \mathrm{m}$. Water, isopropyl alcohol (IPA), and nitrogen (N₂) are used to test and evaluate the sensor’s mass flow and density sensing performance. Full article

While geobotanists have long used plant occurrence to locate subsurface resources, none have utilised floristic surveys as evidence in models of mineral potential. Here, we combine plant species distributions with terrain metrics to produce predictive models showing the probability of bauxite presence. We identified nineteen taxa with statistically significant associations with known bauxite deposits and identified eleven terrain metrics from previous studies. We grouped variables into three variable sets (floristic, topographic, and topo-flora) and produced mineral potential models for each using four algorithms or approaches: (a) a generalised linear model (GLM); (b) random forest (RF); (c) maxent (ME); and (d) a heterogenous stacking ensemble (GLM-RF-ME). Overall, the random forest model outperformed all algorithms including the ensemble based on the area under the curve (AUC) metric. The floristic set of variables outperformed the topographic set (AUC: 0.86 v 0.82). However, together they had the greatest predictive capacity (AUC: 0.89). Six taxa, including Banksia grandis, Leucopogon verticillatus, and Persoonia longifolia, were indicators of bauxite presence, while five other taxa, including Xanthorrhoea preissii and Hypocalymma angustifolium, were associated with bauxite absence. Important topographic variables were topographic wetness, landscape position, and valley depth, which characterised bauxite locations as being well drained, in the upper slope positions of subdued hills, and at some distance from valleys. The addition of floristic surveys provides a new line of evidence about the overlying botanical life that tolerates, accumulates, or avoids bauxite or associated minerals. As opposed to drilling, both datasets can be collected and interrogated at low cost and without impact to the surrounding environment. These data are valuable additions to future applications of mineral potential modelling. Full article

Fungal keratitis (FK), a severe eye infection that leads to vision impairment and blindness, poses a high risk to contact lens users, and Candida albicans remains the most common underpinning fungal pathogen in temperate climates. Patients are initially treated empirically (econazole 1% drops hourly for 24–48 h), and if there is no response, amphotericin B (AmB) 0.15% eye drops (extemporaneously manufactured to be stable for a week) are the gold-standard treatment. Here, we aim to develop a sustained-release AmB ocular film to treat FK with an enhanced corneal retention time. As there is a paucity of reliable in vitro models to evaluate ocular drug release and antifungal efficacy under flow, we developed a 3D-printed microfluidic device based on four chambers stacked in parallel, in which lenses previously inoculated with a C. albicans suspension were placed. Under the flow of a physiological fluid over 24 h, the release from the AmB-loaded film that was placed dry onto the surface of the wetted contact lenses was quantified, and their antifungal activity was assessed. AmB sodium deoxycholate micelle (dimeric form) was mixed with sodium alginate and hyaluronic acid (3:1 w/w) and cast into films (0.48 or 2.4%), which showed sustained release over 24 h and resulted in a 1.23-fold reduction and a 5.7-fold reduction in CFU/mL of C. albicans, respectively. This study demonstrates that the sustained delivery of dimeric AmB can be used for the treatment of FK and provides a facile in vitro microfluidic model for the development and testing of ophthalmic antimicrobial therapies. Full article

Entrapped air in porous media can significantly affect water flow but simulations of air entrapment are still challenging. We developed a pore-network model using quasi-static algorithms to simulate air entrapment during spontaneous wetting and subsequent drainage processes. The model, implemented in OpenPNM, was tailored to replicate an experiment conducted on a medium-sized unconsolidated sand sample. We started building the model with three types of relatively small networks formed by 54,000 pore bodies which we used to calibrate basic network topological parameters by fitting the model to the water retention curve and the saturated hydraulic conductivity of the sand sample. Using these parameters, along with X-ray image data (µCT), a larger network formed by over 250,000 pore bodies was introduced in the form of stacked sub-networks where topological parameters were scaled along the z-axis. We investigated the impact of two different contact angles on air entrapment. For a contact angle of 0, the model showed good agreement with the experimental data, accurately predicting the amount of entrapped air and the saturated hydraulic conductivity. On the contrary, for a contact angle of π/4, the model provided reasonable accuracy for saturated hydraulic conductivity but overestimated the amount of entrapped air. Overall, this approach demonstrated that a reasonable match between simulated and experimental data can be achieved with minimal computational costs. Full article

The Cu undercut is a recently discovered new defect generated in the wet stripping process of MoNb/Cu gate stacked electrodes for thin-film transistors (TFTs). The formation mechanism and preventive strategy of this defect were identified and investigated in this paper. The impact of stripper concentration and stripping times on the morphology and the corrosion potential (E_corr) of Cu and MoNb were studied. It is observed that the undercut is Cu tip-deficient, not the theoretical MoNb indentation, and the undercut becomes severer with the increase in stripping times. The in-depth mechanism analysis revealed that the abnormal Cu undercut was not ascribed to the galvanic corrosion between MoNb and Cu but to the local crevice corrosion caused by the corrosive medium intruding along the MoNb/Cu interface. Based on this newly found knowledge, three possible prevention schemes (MoNiTi (abbreviated as Mo technology development (MTD) layer/Cu), MoNb/Cu/MTD, and MoNb/Cu/MoNb) were proposed. The experimental validation shows that the Cu undercut can only be completely eliminated in the MoNb/Cu/MTD triple-stacked structure with the top MTD layer as a sacrificial anode. This work provides an effective and economical method to avoid the Cu undercut defect. The obtained results can help ensure TFT yield and improve the performance of TFT devices. Full article

In the framework of fully vertical GaN-on-Silicon device technology development, we report on the optimization of non-alloyed ohmic contacts on the N-polar n+-doped GaN face backside layer. This evaluation is made possible by using patterned TLMs (Transmission Line Model) through direct laser writing lithography after locally removing the substrate and buffer layers in order to access the n+-doped backside layer. As deposited non-alloyed metal stack on top of N-polar orientation GaN layer after buffer layers removal results in poor ohmic contact quality. To significantly reduce the related specific contact resistance, an HCl treatment is applied prior to metallization under various time and temperature conditions. A 3 min HCl treatment at 70 °C is found to be the optimum condition to achieve thermally stable high ohmic contact quality. To further understand the impact of the wet treatment, SEM (Scanning Electron Microscopy) and XPS (X-ray Photoelectron Spectroscopy) analyses were performed. XPS revealed a decrease in Ga-O concentration after applying the treatment, reflecting the higher oxidation susceptibility of the N-polar face compared to the Ga-polar face, which was used as a reference. SEM images of the treated samples show the formation of pyramids on the N-face after HCl treatment, suggesting specific wet etching planes of the GaN crystal from the N-face. The size of the pyramids is time-dependent; thus, increasing the treatment duration results in larger pyramids, which explains the degradation of ohmic contact quality after prolonged high-temperature HCl treatment. Full article

A common and natural physiological response of the human body is cough, which tries to push air and other wastage thoroughly from the airways. Due to environmental factors, allergic responses, pollution or some diseases, cough occurs. A cough can be either dry or wet depending on the amount of mucus produced. A characteristic feature of the cough is the sound, which is a quacking sound mostly. Human cough sounds can be monitored continuously, and so, cough sound classification has attracted a lot of interest in the research community in the last decade. In this research, three systematic conglomerated models (SCMs) are proposed for audio cough signal classification. The first conglomerated technique utilizes the concept of robust models like the Cross-Correlation Function (CCF) and Partial Cross-Correlation Function (PCCF) model, Least Absolute Shrinkage and Selection Operator (LASSO) model, elastic net regularization model with Gabor dictionary analysis and efficient ensemble machine learning techniques, the second technique utilizes the concept of stacked conditional autoencoders (SAEs) and the third technique utilizes the concept of using some efficient feature extraction schemes like Tunable Q Wavelet Transform (TQWT), sparse TQWT, Maximal Information Coefficient (MIC), Distance Correlation Coefficient (DCC) and some feature selection techniques like the Binary Tunicate Swarm Algorithm (BTSA), aggregation functions (AFs), factor analysis (FA), explanatory factor analysis (EFA) classified with machine learning classifiers, kernel extreme learning machine (KELM), arc-cosine ELM, Rat Swarm Optimization (RSO)-based KELM, etc. The techniques are utilized on publicly available datasets, and the results show that the highest classification accuracy of 98.99% was obtained when sparse TQWT with AF was implemented with an arc-cosine ELM classifier. Full article

Climate change is causing permafrost in the Qinghai–Tibet Plateau to degrade, triggering thermokarst hazards and impacting the environment. Despite their ecological importance, the distribution and risks of thermokarst lakes are not well understood due to complex influencing factors. In this study, we introduced a new interpretable ensemble learning method designed to improve the global and local interpretation of susceptibility assessments for thermokarst lakes. Our primary aim was to offer scientific support for precisely evaluating areas prone to thermokarst lake formation. In the thermokarst lake susceptibility assessment, we identified ten conditioning factors related to the formation and distribution of thermokarst lakes. In this highly accurate stacking model, the primary learning units were the random forest (RF), extremely randomized trees (EXTs), extreme gradient boosting (XGBoost), and categorical boosting (CatBoost) algorithms. Meanwhile, gradient boosted decision trees (GBDTs) were employed as the secondary learning unit. Based on the stacking model, we assessed thermokarst lake susceptibility and validated accuracy through six evaluation indices. We examined the interpretability of the stacking model using three interpretation methods: accumulated local effects (ALE), local interpretable model-agnostic explanations (LIME), and Shapley additive explanations (SHAP). The results showed that the ensemble learning stacking model demonstrated superior performance and the highest prediction accuracy. Approximately 91.20% of the total thermokarst hazard points fell within the high and very high susceptible areas, encompassing 20.08% of the permafrost expanse in the QTP. The conclusive findings revealed that slope, elevation, the topographic wetness index (TWI), and precipitation were the primary factors influencing the assessment of thermokarst lake susceptibility. This comprehensive analysis extends to the broader impacts of thermokarst hazards, with the identified high and very high susceptibility zones affecting significant stretches of railway and highway infrastructure, substantial soil organic carbon reserves, and vast alpine grasslands. This interpretable ensemble learning model, which exhibits high accuracy, offers substantial practical significance for project route selection, construction, and operation in the QTP. Full article

The production of wood chips can be achieved using different types of wood chippers whose productivity can be influenced by many factors including proper knife management. Research was conducted to determine the productivity of the new Diamant chipper in chipping air-dried tops stacked at a roadside landing and to compare the efficiency of dry sharpening and wet sharpening in restoring chipper productivity, the time required by dry sharpening with that of knife replacement, and the cost of dry sharpening to knife change in real-life conditions. To clearly define the influence of knife management, a model of the effect of knife wear on chipper productivity was produced. Analysis of variance was used to check the significance of any differences in chipping and total time consumption per cycle. Multiple regression was used to express the relationship between chipping time consumption per cycle and the cumulated mass processed by a set of knives—the latter taken as an indicator of knife wear. The study lasted 10 full workdays, included a total of 136 truckloads or 3560 t of fresh wood chips (or green tons = gt), and resulted in the average productivity of 59.0 gt per productive chipping hour (excluding all delays) or 39.4 gt per machine scheduled hour (including all delays). Delays represented 37% of total worksite time. Knife management (dry sharpening or change) accounted for 30% of the total delay time due to raw material contamination. Dry sharpening took 30% less time than a full knife change. As wear accumulated and knives lost their edge, the chipping time per cycle increased from 25 in the first cycle (full truck load) to 38 min in the third cycle. The presented study offers robust productivity figures, together with a reliable estimate of the productivity losses caused by knife wear, and could help improve knife management in order to increase chipper productivity as well as reduce unnecessary delays. Full article