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This study investigates the potential of two quartz vein ores from the Hunza District, Gilgit-Baltistan, Pakistan, as raw materials to obtain 4N8 high-purity quartz (HPQ) sand. Various quartz purification processes were examined, including ore calcination, water quenching, flotation, sand calcination, acid leaching, and chlorination roasting. Analytical techniques such as optical microscopy, Raman spectroscopy, and inductively coupled plasma spectroscopy were employed to analyze the microstructure, inclusion characteristics, and chemical composition of both the quartz raw ore and the processed quartz sand. Microscopic observation reveals that the PK-AML quartz raw ore has relatively high purity, the secondary fluid inclusions are arranged in a directional–linear manner or developed along crystal micro-cracks, and most intracrystalline regions exhibit low inclusion contents, while the PK-JTLT quartz raw ore contains a certain number of melt inclusions. The two processed quartz sand samples exhibit a smooth surface with extremely low fluid inclusion content. A comparative analysis of different purification processes shows that quartz sand calcination has a higher impurity removal rate than ore calcination. After crushing the raw ore into sand, the particles become finer with a larger specific surface area. Quartz sand calcination maximally exposes the inclusions and lattice impurity elements within the quartz, facilitating subsequent impurity removal through acid leaching. Following the processes of crushing, ultrasonic desliming, flotation, sand calcination, water quenching, acid leaching, and chlorination roasting, the SiO2 content of PK-AML processed quartz sand is 99.998 wt.%, with only a small amount of Ti and Li remaining, and a total impurity element content of 20.83 µg·g−1. This meets the standard requirements for crucible preparation in industrial applications, making this vein quartz suitable for producing high-end HPQ products. In contrast, the overall purity of PK-JTLT quartz is lower, and the high contents of impurity elements such as Li, Al, and Ti are difficult to remove via purification experiments. The SiO2 content of PK-JTLT processed quartz sand is 99.991 wt.%, which is applied to higher-quality glass products such as photovoltaic glass, electronic glass, and optical glass, thus presenting broad prospects for application. [ABSTRACT FROM AUTHOR]

This study introduces the synthesis and detailed characterization of a novel thermochromic material capable of reversible alterations in its thermotropic transmittance. Through an emulsion polymerization process, this newly developed material is composed of 75–85% octadecyl acrylate and 0–7% allyl methacrylate, demonstrating a pronounced discoloration effect across a narrow yet critical temperature range of 24.5–39 °C. The synthesized powder underwent a battery of tests, including differential scanning calorimetry and thermogravimetric analysis, as well as scanning electron microscopy. These comprehensive evaluations confirmed the material's exceptional thermal stability, uniform particle size distribution, and strong anchoring properties. Building upon these findings, we advanced the development of thermochromic polyvinyl butyral films and laminated glass products. By utilizing a coextrusion technique, we integrated these films into laminated glass, setting a new benchmark against existing glass technologies. Remarkably, the incorporation of thermochromic PVB films into laminated glass led to a significant reduction in solar irradiance of 20–30%, outperforming traditional double silver low-emissivity glass. This achievement demonstrates the exceptional shading and thermal insulation properties of the material. The research presented herein not only pioneers a valuable methodology for the engineering of smart materials with tunable thermotropic transmittance but also holds the key to unlocking enhanced energy efficiency across a spectrum of applications. The potential impact of this innovation on the realm of sustainable building materials is profound, promising significant strides toward energy conservation and environmental stewardship. [ABSTRACT FROM AUTHOR]

This paper presents a study of the flammability and thermal decomposition products of glass fiber-reinforced epoxy resin (GFRER) with the addition of cardanol-based phosphorus-containing benzoxazine monomer (CBz) and graphene and their combinations in different proportions (up to 20 wt.%). The addition of CBz alone or in combination with graphene resulted in an increase in the limiting oxygen index (LOI) and self-extinguishing in the UL-94 HB test. The flame-retardant samples had better tensile mechanical properties than the sample without additives. The differential mass-spectrometric thermal analysis (DMSTA) of the thermal decomposition products of GFRER without additives and with the addition of CBz and graphene was carried out. CBz addition promoted the thermal decomposition of high-molecular-weight products of epoxy resin decomposition in the condensed phase and at the same time decreased the time of release of low-molecular-weight thermal decomposition products into the gas phase. Graphene addition resulted in an increase in the relative intensities of high-molecular-mass peaks compared to GFRER without additives. [ABSTRACT FROM AUTHOR]

Recently, there has appeared a tendency to use non-traditional animal raw materials to expand the range of sausages. The purpose of the research is to determine the organoleptic and physico-chemical properties, as well as quality indicators of new sausages with a mass fraction of deer muscle tissue in the recipe (> 60%). An organoleptic evaluation was carried out, then the study of physicochemical parameters, the mass fraction of protein, fat, salt, sodium nitrite, total phosphorus, and residual activity of acid phosphatase was performed. Next there were studied such microbiological indicators as QMAFAnM, BGKP (coliforms), sulfite-reducing clostridia, Staphylococcus aureus, and pathogenic microorganisms: Salmonella, Escherichia coli, Listeria monocytogenes. Safety indicators have been established: the content of toxic elements (mercury, arsenic, cadmium, lead) and quality indicators: the content of nitrosamines, pesticides. The quality control of packaging and labeling was carried out visually in accordance with the requirements of the standard. The temperature is measured inside the product with a glass liquid thermometer. The net weight of consumer packaging was determined gravimetrically by static weighing. It has been proved that all three types of the studied sausages «Zavtrak okhotnika», «Drezdenskiye» and «Oldenburgskiye» corresponded to the normative documentation in terms of organoleptic, physico-chemical properties, quality and safety indicators, nutritional value. [ABSTRACT FROM AUTHOR]

Net radiation (Rn) is a key component of the Earth's energy balance. With the rise of deep learning technology, remote sensing technology has made significant progress in the acquisition of large-scale surface parameters. However, the generally low spatial resolution of net radiation data and the relative scarcity of surface flux site data at home and abroad limit the potential of deep learning methods in constructing high spatial resolution net radiation models. To address this challenge, this study proposes an innovative approach of a multi-scale transfer learning framework, which assumes that composite models at different spatial scales are similar in structure and parameters, thus enabling the training of accurate high-resolution models using fewer samples. In this study, the Heihe River Basin was taken as the study area and the Rn products of the Global Land Surface Satellite (GLASS) were selected as the target for coarse model training. Based on the dense convolutional network (DenseNet) architecture, 25 deep learning models were constructed to learn the spatial and temporal distribution patterns of GLASS Rn products by combining multi-source data, and a 5 km coarse resolution net radiation model was trained. Subsequently, the parameters of the pre-trained coarse-resolution model were fine-tuned with a small amount of measured ground station data to achieve the transfer from the 5 km coarse-resolution model to the 1 km high-resolution model, and a daily high-resolution net radiation model with 1 km resolution for the Heihe River Basin was finally constructed. The results showed that the bias, R2, and RMSE of the high-resolution net radiation model obtained by transfer learning were 0.184 W/m2, 0.924, and 24.29 W/m2, respectively, which was better than those of the GLASS Rn products. The predicted values were highly correlated with the measured values at the stations and the fitted curves were closer to the measured values at the stations than those of the GLASS Rn products, which further demonstrated that the transfer learning method could capture the soil moisture and temporal variation of net radiation. Finally, the model was used to generate 1 km daily net radiation products for the Heihe River Basin in 2020. This study provides new perspectives and methods for future large-scale and long-time-series estimations of surface net radiation. [ABSTRACT FROM AUTHOR]

Fractional Forest cover holds significance in characterizing the ecological condition of forests and serves as a crucial input parameter for climate and hydrological models. This research introduces a novel approach for generating a 250 m fractional forest cover product with an 8-day temporal resolution based on the updated GLASS FVC product and the annualized MODIS VCF product, thereby facilitating the development of a high-quality, long-time-series forest cover product on a global scale. Validation of the proposed product, employing high spatial resolution GFCC data, demonstrates its high accuracy across various continents and forest cover scenarios globally. It yields an average fit coefficient of determination (R2) of 0.9085 and an average root-mean-square error of 7.22%. Furthermore, to assess the availability and credibility of forest cover data with high temporal resolution, this study integrates the CCDC algorithm to map forest disturbances and quantify the yearly and even monthly disturbed trace area within two sub-study areas of the Amazon region. The achieved sample validation accuracy is over 86%, which substantiates the reliability of the data. This investigation offers a fresh perspective on monitoring forest changes and observing forest disturbances by amalgamating data from diverse sources, enabling the mapping of dynamic forest cover over an extensive time series with high temporal resolution, thereby mitigating data gaps and enhancing the precision of existing products. [ABSTRACT FROM AUTHOR]

Ancient glass products have suffered from the baptism of time and experienced changes in the burial environment and weathering, resulting in a change in the proportions of their chemical composition and interfering with their accurate identification by later generations. In this paper, the chemical composition of ancient glass products is predicted and identified. First, the multivariate statistical ANOVA test is applied to explore the relationship between whether the cultural relics samples are weathered or not and the glass type, decoration, and color to derive a law of chemical composition of the cultural relics and to analyze the correlation and difference among the four factors. Second, compared with the relevant data of the existing glass products, the missing values are processed by using the method of filling in the plurality. The weathering condition of the sampling points of the samples whose surfaces are not weathered is judged by the "distance discrimination method." Combined with the characteristics of the lead-barium glass and the high-potassium glass, the law of the chemical composition content on the surface of the samples, weathered or not, is explored. The modeling of the gray prediction method was applied again to predict the chemical composition content before weathering. Finally, the generalized Shapley function of fuzzy measurement was used to analyze the correlation between indicators and the chemical compositions and their differences. The scheme proposed in this paper can solve the difficult problem of category judgment in archeology, which is of great significance in promoting the smooth progress of archaeological work. [ABSTRACT FROM AUTHOR]

Ancient glass artifacts were susceptible to weathering from the environment, causing changes in their chemical composition, which pose significant obstacles to the identification of glass products. Analyzing the chemical composition of ancient glass has been beneficial for evaluating their weathering status and proposing measures to reduce glass weathering. The objective of this study was to explore the optimal machine learning algorithm for glass type classification based on chemical composition. A set of glass artifact data including color, emblazonry, weathering, and chemical composition was employed and various methods including logistic regression and machine learning techniques were used. The results indicated that a significant correlation (p < 0.05) could only observed between surface weathering and the glass types (high-potassium and lead–barium). Based on the random forest and logistic regression models, the primary chemical components that signify glass types and weathering status were determined using PbO, K2O, BaO, SiO2, Al2O3, and P2O5. The random forest model presented a superior ability to identify glass types and weathering status, with a global accuracy of 96.3%. This study demonstrates the great potential of machine learning for glass chemical component estimation and glass type and weathering status identification, providing technical guidance for the appraisal of ancient glass artifacts. [ABSTRACT FROM AUTHOR]

Featured Application: The roller bearing and the through shaft bearing are the rotating and load-bearing components of the annealing kiln roller system, which operate at different locations and under different working conditions. Their health status is significant for maintaining the stable operation of the glass production line. In order to improve the efficiency of bearing condition monitoring, this paper proposes a variable-scale attention mechanism guided time-frequency feature fusion transfer learning method, which is used for bearing fault diagnoses at different installation locations in the annealing kiln roller system. It effectively achieves the intelligent diagnosis of roller bearing and through shaft bearing faults in the annealing kiln roller system. Effective real-time health condition monitoring of the roller table and through shaft bearings in the annealing kiln roller system of glass production lines is crucial for maintaining their operational safety and stability for the quality and production efficiency of glass products. However, the collected vibration signal of the roller bearing system is affected by the low rotating frequency and strong mechanical background noise, which shows the width impact interval and non-stationary multi-component characteristics. Moreover, the distribution characteristics of monitoring data and probability of fault occurrence of the roller bearing and through shaft bearing improve the difficulty of the fault diagnosis and condition monitoring of the annealing kiln roller system, as well as the reliance on professional experience and prior knowledge. Therefore, this paper proposes a variable-scale attention mechanism guided time-frequency feature fusion transfer learning method for a bearing fault diagnosis at different installation positions in an annealing kiln roller system. Firstly, the instinct time decomposition method and the Gini–Kurtosis composed index are used to decompose and reconstruct the signal for noise reduction, wavelet transform with the Morlet basic function is used to extract the time-frequency features, and histogram equalization is introduced to reform the time-frequency map for the blur and implicit time-frequency features. Secondly, a variable-scale attention mechanism guided time-frequency feature fusion framework is established to extract multiscale time-dependency features from the time-frequency representation for the distinguished fault diagnosis of roller table bearings. Then, for through shaft bearings, the vibration signal of the roller table bearing is used as the source domain and the signal of the through shaft bearing is used as the target domain, based on the feature fusion framework and the multi-kernel maximum mean differences metric function, and the transfer diagnosis method is proposed to reduce the distribution differences and extract the across-domain invariant feature to diagnose the through shaft bearing fault speed under different working conditions, using a small sample. Finally, the effectiveness of the proposed method is verified based on the vibration signal from the experimental platform and the roller bearing system of the glass production line. Results show that the proposed method can effectively diagnose roller table and through shaft bearings' fault information in the annealing kiln roller system. [ABSTRACT FROM AUTHOR]

As a new and promising reinforcing filler, electrospun glass nanofibers (EGNFs) have attracted attention in the field of polymer composite materials. However, the reinforcing effectiveness of surface-modified EGNFs using different silane coupling agents in epoxy resin is still not quite clear. In this research, a series of silane coupling agents with increasing chain lengths in the order of methyl trimethoxysilane (MTMS), (3-aminopropyl) triethoxysilane (APTES), (3-glycidyloxypropyl) trimethoxysilane (GPTMS), and dual silane coupling agent APTES–GPTMS were employed to carry out surface treatment on the EGNFs. The pristine and silane functionalized EGNFs were then incorporated into epoxy resin as reinforcing fillers at low loading levels, i.e., 0.25 wt.%, 0.5 wt.%, and 1 wt.%, and the mechanical properties of the resultant epoxy nanocomposites, including strength, stiffness, ductility, and toughness, were evaluated. A commercial product of glass nanoparticles (GNPs) was used as a control to compare the reinforcing effectiveness of the EGNFs and the GNPs. This study revealed that the EGNFs could provide significant reinforcing and toughening effects at ultra-low loading (0.25 wt.%) in epoxy nanocomposite materials. Furthermore, surface modification of the EGNFs with silane coupling agents with long chain lengths, e.g., by using dual silane coupling agents, APTES–GPTMS, could enhance the interfacial bonding between the EGNFs and the epoxy matrix and further increase the mechanical performance of the EGNF-reinforced epoxy nanocomposite materials. Through this research, we realized epoxy nanocomposite materials with much-improved mechanical properties, i.e., 37%, 24%, 18%, 57% improvement in strength, stiffness, ductility, and toughness, respectively, with respect to those of the cured neat epoxy material with an ultra-low loading (0.25 wt.%) of APTES–GPTMS–EGNFs. Our research paves the road for developing lighter and stronger epoxy nanocomposite materials with EGNFs. [ABSTRACT FROM AUTHOR]

Ultrahigh-pressure high-temperature glasses are characterized by unusual structural and phase aspects that require closer investigation in order to elucidate their physical properties and the possibility of using innovative materials as prototypes. Experimental modeling of an impact process in laboratory conditions makes it possible to shed light on the nature of phase transformations on impacto-genesis. Impact glasses were obtained experimentally by melting the aluminosilicate and quartz components of the rocks of the target of the Kara astro-problem at pressure about 90 GPa and temperature about 7000°C. Investigations have shown that as a result of extreme external conditions, glasses of a specific composition are formed containing a high proportion of Ca and carbon. Thus, the results obtained indicate the possibility of obtaining glass of wide compositions, including carbon-containing glass, which can be used for further research in order to develop new materials and technologies for their production. [ABSTRACT FROM AUTHOR]

Massive amounts of deposited coal gangue derived from the mining industry constitute a crucial problem that must be solved. On the other hand, common knowledge about the recycling of glass products and the reuse of waste glass is still insufficient, which in turn causes economic and environmental problems. Therefore, this work investigated lightweight geopolymer foams manufactured based on coal gangue, metakaolin, and a mix of them to evaluate the influence of such waste on the geopolymer matrix. In addition, the effect of 20% (wt.) of waste glass on the foams was determined. Mineralogical and chemical composition, thermal behaviour, thermal conductivity, compressive strength, morphology, and density of foams were investigated. Furthermore, the structure of the geopolymers was examined in detail, including pore and structure thickness, homogeneity, degree of anisotropy, porosity with division for closed and open pores, as well as distribution of additives and pores using micro-computed tomography (microCT). The results show that the incorporation of waste glass increased compressive strength by approximately 54% and 9% in the case of coal-gangue-based and metakaolin-based samples, respectively. The porosity of samples ranged from 67.3% to 58.7%, in which closed pores constituted 0.3–1.8%. Samples had homogeneous distributions of pores and additions. Furthermore, the thermal conductivity ranged from 0.080 W/(m·K) to 0.117 W/(m·K), whereas the degree of anisotropy was 0.126–0.187, indicating that the structure of foams was approximate to isotropic. [ABSTRACT FROM AUTHOR]

The preparation at room temperature of cellular glass from recycled residual glass and fly ash was made adopting a manufacturing method recently applied in the case of geopolymer foam. Sodium perborate in aqueous solution as a blowing agent and detergent as a surfactant have been experimentally tested in several versions. The optimal cellular glass product was obtained by mixing 2.6 % sodium perborate, 0.2 % surfactant, and 7.6 % water addition. The characteristics of this expanded product were: density of 0.65 g·cm-3, heat conductivity of 0.134 W·m-1 ·K-1, and compression resistance of 1.2 MPa, being satisfactory for its application as heat insulating product in construction. The main advantage of this method was the product manufacture in satisfactory quality conditions without supplementary energy consumption and greenhouse gas emissions (CO2) into the atmosphere, like in the case of the usual manufacturing cellular products at high temperature. [ABSTRACT FROM AUTHOR]

The highlights of the 24th International Exposition Glass World held in Moscow are briefly cited. About 100 companies from 12 countries of the world participated. New manufacturing and quality-control technologies of glass products and the main structural components of glass furnaces and methods of their high-quality production are demonstrated at the exposition. Examples of the most successful enterprises in the glass industry are given. [ABSTRACT FROM AUTHOR]

The leaf area index (LAI) is a crucial parameter for analyzing terrestrial ecosystem carbon cycles and global climate change. Obtaining high spatiotemporal resolution forest stand vegetation LAI products over large areas is essential for an accurate understanding of forest ecosystems. This study takes the northwestern part of the Inner Mongolia Autonomous Region (the northern section of the Greater Khingan Mountains) in northern China as the research area. It also generates the LAI time series product of the 8-day and 30 m forest stand vegetation growth period from 2013 to 2017 (from the 121st to the 305th day of each year). The Simulated Annealing-Back Propagation Neural Network (SA-BPNN) model was used to estimate LAI from Landsat8 OLI, and the multi-period GaoFen-1 WideField-View satellite images (GF-1 WFV) and the spatiotemporal adaptive reflectance fusion mode (STARFM) was used to predict high spatiotemporal resolution LAI by combining inversion LAI and Global LAnd Surface Satellite-derived vegetation LAI (GLASS LAI) products. The results showed the following: (1) The SA-BPNN estimation model has relatively high accuracy, with R2 = 0.75 and RMSE = 0.38 for the 2013 LAI estimation model, and R2 = 0.74 and RMSE = 0.17 for the 2016 LAI estimation model. (2) The fused 30 m LAI product has a good correlation with the LAI verification of the measured sample site (R2 = 0.8775) and a high similarity with the GLASS LAI product. (3) The fused 30 m LAI product has a high similarity with the GLASS LAI product, and compared with the GLASS LAI interannual trend line, it accords with the growth trend of plants in the seasons. This study provides a theoretical and technical reference for forest stand vegetation growth period LAI spatiotemporal fusion research based on high-score data, and has an important role in exploring vegetation primary productivity and carbon cycle changes in the future. [ABSTRACT FROM AUTHOR]

The glass relics are precious material evidence of the early trade and cultural exchange between the East and the West. To explore the cultural differences and trade development between early China and foreign countries, it is extremely important to classify glass cultural relics. Despite their similar appearances, Chinese glass contains more lead, while foreign glass contains more potassium. In view of this, this paper proposes a joint Daen-LR, ARIMA-LSTM, and MLR machine learning algorithm (JMLA) for the analysis and identification of the chemical composition of ancient glass. We separate the sampling points of ancient glass into two systems: lead-barium glass and high-potassium glass. Firstly, an improved logistic regression model based on a double adaptive elastic network (Daen-LR) is used to select variables with both Oracle and adaptive classification characteristics. Secondly, the ARIMA-LSTM model was used to establish the correlation curve of chemical composition before and after weathering and to predict the change in chemical composition with weathering. Thirdly, combining the data processed by the above two methods, a multiple linear regression model (MLR) is used to classify unknown glass products. It was shown that the sample obtained by this processing method has a very good fit. In comparison with other similar types of models like Decision Trees (DT), Random Forests (RF), Support Vector Machines (SVM), and Random Forests based on classification and regression trees (CART-RF), the classification accuracy of JMLA is 97.9% on the train set. The accuracy rate on the test set reached 97.6%. The results of the research demonstrate that JMLA can improve the accuracy of the glass type classification problem, greatly enhance the research efficiency of archaeological staff, and gain a more reliable result. [ABSTRACT FROM AUTHOR]

Motivated by the lack of long-term global soil moisture products with both high spatial and temporal resolutions, a global 1 km daily spatiotemporally continuous soil moisture product (GLASS SM) was generated from 2000 to 2020 using an ensemble learning model (eXtreme Gradient Boosting – XGBoost). The model was developed by integrating multiple datasets, including albedo, land surface temperature, and leaf area index products from the Global Land Surface Satellite (GLASS) product suite, as well as the European reanalysis (ERA5-Land) soil moisture product, in situ soil moisture dataset from the International Soil Moisture Network (ISMN), and auxiliary datasets (Multi-Error-Removed Improved-Terrain (MERIT) DEM and Global gridded soil information (SoilGrids)). Given the relatively large-scale differences between point-scale in situ measurements and other datasets, the triple collocation (TC) method was adopted to select the representative soil moisture stations and their measurements for creating the training samples. To fully evaluate the model performance, three validation strategies were explored: random, site independent, and year independent. Results showed that although the XGBoost model achieved the highest accuracy on the random test samples, it was clearly a result of model overfitting. Meanwhile, training the model with representative stations selected by the TC method could considerably improve its performance for site- or year-independent test samples. The overall validation accuracy of the model trained using representative stations on the site-independent test samples, which was least likely to be overfitted, was a correlation coefficient (R) of 0.715 and root mean square error (RMSE) of 0.079 m 3 m -3. Moreover, compared to the model developed without station filtering, the validation accuracies of the model trained with representative stations improved significantly for most stations, with the median R and unbiased RMSE (ubRMSE) of the model for each station increasing from 0.64 to 0.74 and decreasing from 0.055 to 0.052 m 3 m -3 , respectively. Further validation of the GLASS SM product across four independent soil moisture networks revealed its ability to capture the temporal dynamics of measured soil moisture (R=0.69–0.89; ubRMSE = 0.033–0.048 m 3 m -3). Lastly, the intercomparison between the GLASS SM product and two global microwave soil moisture datasets – the 1 km Soil Moisture Active Passive/Sentinel-1 L2 Radiometer/Radar soil moisture product and the European Space Agency Climate Change Initiative combined soil moisture product at 0.25 ∘ – indicated that the derived product maintained a more complete spatial coverage and exhibited high spatiotemporal consistency with those two soil moisture products. The annual average GLASS SM dataset from 2000 to 2020 can be freely downloaded from 10.5281/zenodo.7172664 (Zhang et al., 2022a), and the complete product at daily scale is available at http://glass.umd.edu/soil%5fmoisture/ (last access: 12 May 2023). [ABSTRACT FROM AUTHOR]

At least 25 bioactive glass (BG) medical devices have been approved for clinical use by global regulatory agencies. Diverse applications include monolithic implants, bone void fillers, dentin hypersensitivity agents, wound dressing, and cancer therapeutics. The morphology and delivery systems of bioactive glasses have evolved dramatically since the first devices based on 45S5 Bioglass®. The particle size of these devices has generally decreased with the evolution of bioactive glass technology but primarily lies in the micron size range. Morphologies have progressed from glass monoliths to granules, putties, and cements, allowing medical professionals greater flexibility and control. Compositions of these commercial materials have primarily relied on silicate-based systems with varying concentrations of sodium, calcium, and phosphorus. Furthermore, therapeutic ions have been investigated and show promise for greater control of biological stimulation of genetic processes and increased bioactivity. Some commercial products have exploited the borate and phosphate-based compositions for soft tissue repair/regeneration. Mesoporous BGs also promise anticancer therapies due to their ability to deliver drugs in combination with radiotherapy, photothermal therapy, and magnetic hyperthermia. The objective of this article is to critically discuss all clinically approved bioactive glass products. Understanding essential regulatory standards and rules for production is presented through a review of the commercialization process. The future of bioactive glasses, their promising applications, and the challenges are outlined. Bioactive glasses have evolved into a wide range of products used to treat various medical conditions. They are non-equilibrium, non-crystalline materials that have been designed to induce specific biological activity. They can bond to bone and soft tissues and contribute to their regeneration. They are promising in combating pathogens and malignancies by delivering drugs, inorganic therapeutic ions, and heat for magnetic-induced hyperthermia or laser-induced phototherapy. This review addresses each bioactive glass product approved by regulatory agencies for clinical use. A review of the commercialization process is also provided with insight into critical regulatory standards and guidelines for manufacturing. Finally, a critical evaluation of the future of bioactive glass development, applications, and challenges are discussed. [Display omitted] [ABSTRACT FROM AUTHOR]

Glass products are important evidence of early East–West cultural exchanges. Ancient glass in China mostly consisted of lead glass, and potassium glass is widely believed to be imported abroad. In order to figure out the origin of glass artefacts, it is crucial to define the type of glass products accurately. In contemporary research on the chemical composition of ancient glass products, potassium glass is separated from lead glass primarily by the weight ratio of oxides or the proportion of lead-containing compounds. This approach can be excessively subjective and prone to mistakes while calculating the mass fraction of compounds containing potassium. So, it is better to find out the link between the proportion of glass's chemical composition and its classifications during the weathering process of the glass products, to develop an effective classification model using machine learning techniques. In this research, we suggest employing the slime mould approach to optimise the parameters of a support vector machine and examine a 69-group glass chemical composition dataset. In addition, the results of the proposed algorithm are compared to those of commonly used classification models: decision trees (DT), random forests (RF), support vector machines (SVM), and support vector machines optimised by genetic algorithms (GA-SVM). The results of this research indicated that the support vector machine method with the sticky slime mould algorithm strategy is the most effective. On the training set, 100% accuracy was attained, while on the test set, 97.50% accuracy was attained in this research. The research results demonstrate that the support vector machine algorithm combining the slime mould algorithm strategy is capable of providing a trustworthy classification reference for future glass artefacts. [ABSTRACT FROM AUTHOR]

Contemporaneous trends in the development of technologies for matting glass and products from matted glass are considered. An efficient glass matting technology has been developed using an alternative source of energy—low-temperature plasma. It is demonstrated that a high-quality matt surface of the type 'frosty matting' is formed by using iron powders with dispersivity 160 and 450 µm. The microstructure of the matted surface was investigated. Theoretical aspects of matting glass are considered. The technological parameters of matting are determined and the developed technology is shown to be economically efficient. [ABSTRACT FROM AUTHOR]

Spatial land surface heterogeneities are widespread at various scales and represent a great challenge to leaf area index (LAI) retrievals and product validations. In this paper, considering the mixed water and vegetation pixels prevalent at moderate and low resolutions, we propose a methodological framework for conducting global comparisons of heterogeneous land surfaces based on criterion setting and a global search of high-resolution data. We construct a global network, Heterogeneous Surface Network aiming Water and Vegetation Mixture (HESNet-WV), comprised of three vegetation types: grassland, evergreen broadleaf forests (EBFs), and evergreen needle forests (ENFs). Validation is performed using the MCD15A3H Global 500-m/4-day and GLASS 500-m/8-day LAI products. As the water area fraction (WAF), LAI values and LAI inversion errors increase in the MODIS and GLASS products, the GLASS product errors (relative LAI error (RELAI): 94.43%, bias: 0.858) are lower than the MODIS product errors (RELAI: 124.05%, bias: 1.209). The result indicates that the proposed framework can be applied to evaluate the accuracy of LAI values in mixed water-vegetation pixels in different global LAI products. [ABSTRACT FROM AUTHOR]

The results of studies on the intensification of the dealkalization process of alkaline silicate industrial and synthesized glasses with acid gases are analyzed and summarized. The composition of the reaction products of glasses with gaseous reagents is identified using X-ray phase analysis, X-ray spectral electron probe microanalysis, thermal analysis, flame photometry, and quantitative chemical analysis. The physicochemical properties of industrial glassware modified with gaseous reagents are determined in laboratory and factory experiments. Ways of intensifying the dealkalization process of silicate glasses with acid gases are discussed. [ABSTRACT FROM AUTHOR]

Glass, a near infinitely recyclable material, can be upcycled to create new products such as foamed glass ceramics, which are essentially a synthetic pumice-like material. This material has been demonstrated to sustain preserved biofilms which have application in various fields based on the deployability of the product and the preserved microbes. Foamed glass ceramics have increased surface area compared to typical soda-lime glass cullet. This material has been explored for variety of applications including the growth, storage and transport of biofilms and microbial colonies which can be preserved and deployed later. Here, we demonstrate the ability for microbial cultures including BioTiger™, Escherichia coli K-12, Bacillus thuringiensis, and two environmental eukaryotic cells to colonize the upcycled glass products, undergo preservation, and regrow after 84 days of storage. The growth of preserved samples is correlated to the time spent incubating prior to preservation. These results demonstrate the applicability of this novel glass-biofilm combination in which various preserved microorganisms are able to be rapidly grown after storage on an upcycled glass product. [ABSTRACT FROM AUTHOR]

The weathering of ancient glass relics has long been a concerned. Therefore, a systematic and more comprehensive mathematical model with which to correctly judge the category of ancient glass products whose chemical composition changes due to weathering should be established. This paper systematically analyzes and studies the changes in the composition of ancient glass products as a result of weathering of. We first analyze the surface weathering of glass relics and its correlation with three properties and establish a multivariable time-series model to predict the chemical-composition content before weathering. Next, we use one-way analysis of variance for subclassification and, finally, we use a principal component analysis of the rationality, and change the significance level to determine its sensitivity, for the reasonable prediction of the chemical-composition content and classification to provide a theoretical basis for improving the model. This allows the model to provide reference values, which can be used in the protection of cultural relics, historical research, and other fields. [ABSTRACT FROM AUTHOR]

Motivated by the lack of long-term global soil moisture products with both high spatial and temporal resolutions, a global 1-km daily spatiotemporally continuous soil moisture product (GLASS SM) was generated from 2000 to 2020 using an ensemble learning model (eXtreme Gradient Boosting -- XGBoost). The model was developed by integrating multiple datasets, including albedo, land surface temperature, and leaf area index products from the Global Land Surface Satellite (GLASS) product suite, as well as the European reanalysis (ERA5-Land) soil moisture product, in situ soil moisture dataset from the International Soil Moisture Network (ISMN), and auxiliary datasets (Multi-Error-Removed Improved-Terrain DEM and SoilGrids). Given the relatively large scale differences between point-scale in situ measurements and other datasets, the triple collocation (TC) method was adopted to select the representative soil moisture stations and their measurements for creating the training samples. To fully evaluate the model performance, three validation strategies were explored: random, site-independent, and year-independent. Results showed that for the random test samples, the XGBoost model trained with representative stations selected by the TC method achieved the highest accuracy, with an overall correlation coefficient (R) of 0.941 and root mean square error (RMSE) of 0.038 m3 m-3; whereas for both the site- and year-independent test samples, although the overall model performance was comparatively lower, training the model with representative stations could still considerably improve its overall accuracy. Meanwhile, compared to the model developed without station filtering, the validation accuracies of the model trained with representative stations improved significantly on most station, with the median R and unbiased RMSE (ubRMSE) of the model for each station increasing from 0.64 to 0.74, and decreasing from 0.055 to 30 0.052 m3 m-3, respectively. Further validation of the GLASS SM product across four independent soil moisture networks revealed its ability to capture the temporal dynamics of measured soil moisture (R = 0.69-0.89; ubRMSE = 0.033-0.048 m3 m-3). Lastly, the inter-comparison between the GLASS SM product and two global microwave soil moisture datasets--the 1-km Soil Moisture Active Passive/Sentinel-1 L2 Radiometer/Radar soil moisture 35 product and the European Space Agency Climate Change Initiative combined soil moisture product at 0.25°--indicated that the derived product maintained a more complete spatial coverage, and exhibited high spatiotemporal consistency with those two soil moisture products. The annual average GLASS SM dataset from 2000 to 2020 can be freely downloaded from https://doi.org/10.5281/zenodo.7172664 (Zhang et al., 2022a), and the complete product at daily scale is available at http://glass.umd.edu/soil_moisture/. [ABSTRACT FROM AUTHOR]

A number of modern glass and window products based on novel glazing designs, low-emissivity thin-film coatings, and proprietary fluorescent interlayer types have been developed recently. Advanced windows of today can control properties such as thermal emissivity, heat gain, colour, and transparency. In novel glass products, solar energy harvesting through PV integration is also featured, enabled by either patterned-semiconductor thin-film energy conversion surfaces, or by using luminescent concentrator-type approaches to achieve higher transparency. Typically, semitransparent and also highly-transparent PV windows are purpose-designed, for applications in construction industry and agrivoltaics (greenhousing), to include special types of luminescent materials, diffractive microstructures, and customized glazing systems and electric circuitry. Recently, significant progress has been demonstrated in building integrated high-transparency solar windows (featuring visible light transmission of up to 70%, with electric power output Pmax ∼ 30−33 Wp/m2, e.g. ClearVue PV Solar Windows); these are expected to add momentum towards the development of smart cities and advanced agrivoltaics in greenhouse installations. At present (in 2023), these ClearVue window designs are the only type of visually-clear and deployment-ready construction materials capable of providing significant energy savings in buildings, simultaneously with a significant amount of renewable energy generation. The objective of this study is to place the recent industrialised development of ClearVue® PV window systems into a broader context of prior studies in the field of luminescent concentrators, as well as to provide some details on the measured performance characteristics of several ClearVue window design types deployed within the building envelope of a research greenhouse, and to elucidate the corresponding differences in their energy harvesting behaviour. An evaluation of the practical applications potential of these recently developed transparent agrivoltaic construction materials is provided, focussing on the measured renewable energy generation figures and the seasonal trends observed during a long-term study. This article reports on the measured performance characteristics of research greenhouse-based agrivoltaic installation constructed at Murdoch University (Perth, Australia) in early 2021.The solar greenhouse at Murdoch University has demonstrated great potential for commercial food production with significant energy savings due to on-site energy production from its building envelope. [ABSTRACT FROM AUTHOR]

• Fracture phase field model involving large viscoelastic deformation and stress-diffusion interaction is proposed. • The interactions among the ion-exchange, stress evolution, cracking and deformation are comprehensively studied. • By introducing a damage ratio, the fracture behaviour is qualitatively studied and optimized by the regulation of glass thickness, fracture roughness or edging parameters. A phase field model is proposed to investigate the fracture mechanics of ion-exchanged glass, which involves significant viscoelastic deformation and stress-diffusion interaction. Based on this theoretical model, the fracture behavior of both double-sided and single-sided ion exchange processes was studied. The results indicate that, compared to single-sided ion exchange, the double-sided process is more likely to induce crack initiation and propagation, ultimately resulting in a notable reduction in glass strength. For both cases, increasing the glass thickness and interfacial energy density will significantly improve the fracture resistance of the glass. Notably, when the glass thickness or interfacial energy density is large enough, the crack can be completely closed, ensuring the integrity of the glass during the ion exchange process. Furthermore, the study conducted a preliminary investigation of two industrially relevant conditions: edging and impurities. The impacts of edging parameters, glass interfacial energy density, and covering radius on glass stress evolution, mechanical deformation, crack initiation, and crack propagation during chemical strengthening were summarized. These findings offer valuable theoretical support and a reference for optimizing chemical strengthening process parameters and enhancing the strength of glass products. [ABSTRACT FROM AUTHOR]

The physical explanations and understanding of the order–disorder phenomena in the solid state are commonly inferred from the experimental capabilities of the characterization techniques. Periodicity is recorded according to the averaging procedure of the conventional reciprocal-space techniques (RSTs) in many solids. This approach gives rise to a sharp trimodal view including non-crystalline or amorphous compounds, aperiodic crystals and periodic crystals. However, nuclear magnetic resonance (NMR) spectroscopy offers an alternative approach that is derived from the distinct character of the measurements involved at the local scale. Here, we present a sequence of progressive order–disorder states, from amorphous structures up to fully ordered mineral structures, showing the great diversity existing in the solid state using multinuclear NMR spectroscopy. Some examples in glasses and products of their crystallization are used, as well as several minerals (including beryl-group and feldspar-group minerals) at magnetic fields up to 35.2 T, and some examples from literature. This approach suggests that the solid state is a dynamic medium, whose behavior is due to atomic adjustments from local compensation of electrical charges between similar structural states, which explains Ostwald's step rule of successive reactions. In fully ordered feldspar minerals, we propose that the electronic structure of the elements of the cavity site is involved in bonding, site morphology and feldspar topology. Furthermore, some implications are derived about what is a mineral structure from the point of view of the NMR experiments. They open the possibility for the development of the science of NMR Mineralogy. [ABSTRACT FROM AUTHOR]

Controlled ion release and mineralization of bioactive glasses are essential to their applications in bone regeneration. Tuning the chemical composition and surface structure of glasses are the primary means of achieving this goal. However, most bioactive glasses exhibit a non-linear ion release behavior. Therefore, modifying the immersion environment of glasses through external stimuli becomes an approach. In this study, the ion release and mineralization properties of a borosilicate bioactive glass were investigated in the Tris buffer and K2HPO4 solutions with different pH. The glass had a faster ion release rate at a lower pH, but the overly acidic environment was detrimental to hydroxyapatite production. Using a direct current (DC) electric field as an external stimulus, the pH of the immersion solution could be modulated within a narrow range, thereby modulating ion release from the glass. As a result, significant increases in ion release were observed after three days, and the development of porous mineralization products on the glass surface after six days. This study demonstrates the effectiveness of the DC electric field in modulating the ion release of the bioactive glass in vitro and provides a potential way to regulate the degradation of the glass in vivo. [ABSTRACT FROM AUTHOR]

The land surface albedo (LSA) represents the ability of the land surface to reflect solar radiation. It is one of the driving factors in the energy balance of land surface radiation and in land–air interactions. In this paper, we estimated the land surface albedo based on GF-1 WFV satellite data that have a high spatial and temporal resolution and cross-validated the albedo estimation results. The albedo estimations and validations were performed in the Ganzhou District, Zhangye City, China, and the Sindh Province, Pakistan. We used the direct estimation method which used a radiative transfer simulation to establish the relationship between the narrow band top of the atmosphere bidirectional reflectance and the land broadband albedo to estimate the albedo data. The results were validated with ground data, Landsat data, MODIS products, and GLASS products. The results show that the method can produce highly accurate albedo estimation results on different land cover types (RMSE: 0.026, R2: 0.835) and has a good consistency with the existing albedo products. This study makes a significant contribution to improving the utilization of GF data and contributes to the understanding of land–air interactions. [ABSTRACT FROM AUTHOR]

Many consumer products, e.g., printer’s cartridges, milk’s glass bottles, etc., are sold with reusable parts, which can be formally collected under a used-part-collection (UPC) program. In today’s markets with high volatility, risk is present for UPC operations. In this article, building via standard consumer utility-based models, we uncover the value of the UPC program in a production system. In the basic model, we consider the case when the manufacturer is risk averse. For both the cases with and without UPC, the optimal product pricing and quality decisions are determined and the respective manufacturer’s utility and consumer surplus are derived. The values of UPC to the manufacturer and consumers are found. We find that: 1) both quality improvement and UPC can be beneficial to consumers under some situations and 2) the optimal quality level, the optimal utility, and the consumer surplus are independent of the return fee. In the extended models, we explore two cases, namely, the case when consumers are risk averse, and the case with a collection platform, which can enhance the collection rate. We find that no matter what the level of consumers’ risk averse is, it reduces consumers’ benefits. Moreover, a higher platform’s power is beneficial to the manufacturer and consumers but may reduce the platform’s profit. [ABSTRACT FROM AUTHOR]

The requirements of ecological design for materials for various environmental objects are considered. The types of glasses and glass-ceramic materials for the design of environmental objects are presented. A wide range of surface-treatment methods for glasses and glass materials is shown, which determine their high decorative expressiveness along with operational properties. A classification of glass products is given according to the methods of forming and surface treatment, which determine the artistic, operational-technical, and physicochemical properties of glasses and glass materials. Particular attention is paid to stained-glass windows and the technology of their manufacture. [ABSTRACT FROM AUTHOR]

The conditions under which halogens partition in favor of an exsolved fluid relative to the coexisting melt are key for understanding many magmatic processes, including volcanic degassing, evolution of crustal melt bodies, and ore formation. We report new F, Cl, and Br fluid/melt partition coefficients for intermediate to silicic melts, for which F and Br data are particularly lacking; and for varying CO2- H2O contents to assess the efects of changing fluid composition (XH2O) on Br fluid/melt partitioning for the first time. The experiments were conducted at pressures 50–120 MPa, temperatures 800–1100 °C, and volatile compositions [molar XH2O = H2O/(H2O +CO2)] of 0.55 to 1, with redox conditions around the Nickel-Nickel Oxygen bufer (ƒO2 ≈ NNO). Experiments were not doped with Cl, Br, or F and were conducted on natural crystal-bearing volcanic products at conditions close to their respective pre-eruptive state. The experiments therefore provide realistic constraints on halogen partitioning at naturally occurring, brine-undersaturated conditions. Measurements of Br, Cl, and F were made by Secondary Ion Mass Spectrometry (SIMS) on 13 experimental glass products spanning andesite to rhyolitic compositions, together with their natural starting materials from Kelud volcano, Indonesia, and Quizapu volcano, Chile. Fluid compositions were constrained by mass balance. Average bulk halogen fluid/melt partition coefficients and standard deviations are: DClfluid/melt = 3.4 (±3.7 1 s.d.), DFfluid/melt = 1.7 (±1.7), and DBrfluid/melt = 7.1 (±6.4) for the Kelud starting material (bulk basaltic andesite), and DClfluid/melt = 11.1 (±3.5), DFfluid/melt = 0.8 (±0.8), and DBrfluid/melt = 31.3 (±20.9) for Quizapu starting material (bulk dacite). The large range in average partition coeficients is a product of changing XH2O, pressure and temperature. In agreement with studies on synthetic melts, our data show an exponential increase of halogen Dfluid/melt with increasing ionic radius, with partitioning behavior controlled by melt composition according to the nature of the complexes forming in the melt (e.g., SiF4, NaCl, KBr). The fundamental chemistry of the diferent halogens (differing ionic size and electronegativities) controls the way in which partitioning responds to changes in melt composition and other variables. Experimental results confirm that more Cl partitions into the fluid at higher bulk Cl contents, higher melt Na, higher fluid XH2O ratios, and lower temperatures. Bromine shows similar behavior, though it seems to be more sensitive to temperature and less sensitive to Na content and XH2O. In contrast, F partitioning into the fluid increases as the melt silica content decreases (from 72 to 56 wt% SiO2), which we attribute to the lower abundance of Si available to form F complexes in the melt. These new data provide more insights into the conditions and processes that control halogen degassing from magmas and may help to inform the collection and interpretation of melt inclusions and volcano gas data. [ABSTRACT FROM AUTHOR]

Stromboli (Italy) is a basaltic volcano characterized by persistent, mild strombolian activity, occasionally interrupted by lava effusion and more violent explosive events, named major explosions and paroxysms depending on their intensity and magnitude. The normal activity is fed by a shallow and degassed highly porphyritic (HP) shoshonitic basalt carrying about 50 vol.% crystals settled in a shoshonitic glassy matrix (K2O > 3.8 wt.%). The more energetic explosions erupt a deep, volatile-rich, low-porphyritic (LP) magma with < 10 vol.% crystals in a shoshonitic basaltic glassy matrix (K2O < 2.4 wt.%). Products with intermediate glass composition are also found in the more violent explosive events. In this study, we present a new data set of major and trace element contents in matrix glasses and minerals performed in products from different types of explosive activity that occurred at Stromboli between 1998 and 2020. This large data set is used to put constraints on the evolution and architecture of the intermediate plumbing system, where the transformation from LP to HP occurs. Results indicate that, compared to paroxysms, the glassy matrices of the LP pumices from major explosions are richer in incompatible trace elements (and K2O wt.%) due to < 15 wt.% fractionation of clinopyroxene and olivine. This points to a chemical zoning of the deep reservoir and suggests that major explosions are fed by magmas residing in its upper part. Among the major explosions, the homogeneous intermediate glasses in the products from the 19 July 2020 event originate from the interplay of mixing and crystal fractionation processes. The crystallization of euhedral microphenocrysts of An-rich plagioclase suggests that batches of magma can pond and crystallize for few days (< 11) at the base of the intermediate zone of the plumbing system, at pressure coinciding with the entering of plagioclase into the system (< 100 MPa). As a relevant point for understanding the pre- and syn-eruptive magma dynamics, data indicate a positive correlation between the magnitude of the explosions and the depth of the supply magma. [ABSTRACT FROM AUTHOR]

Highly efficient quantum cutting KY(CO3)2:Tb3+ phosphors excited by ultraviolet B (UVB) and ultraviolet C (UVC) were investigated. The structural and spectroscopic properties were characterized by XRD analysis and fluorescence spectrophotometry, respectively. The results showed that the monoclinic crystal structure of KY(CO3)2:Tb3+ remained in the Tb3+ doping range of 0~100%. In the excitation spectrum, two intense excitation peaks were observed in the ultraviolet range. Under the excitation of 283 nm, the maximum quantum efficiency of KY(CO3)2:0.7Tb3+ could reach 119%. However, the most efficient quantum cutting occurred at the 5K8 excited state in the cross-relaxation of 5K8 + 7F65D4 + 5D4. The Tb3+ content could be selected arbitrarily in the KY(CO3)2 host without any concentration quenching. Optimal quantum cutting concentrations of Tb3+ in KY(CO3)2 were 0.7 and 0.3 for the excitation of UVB and UVC, respectively. UVB-excited phosphors are more popular with high transparency in products such as glass or resin. A quick response code was fabricated by resin to show the hidden information clearly. Therefore, the highly efficient phosphor could be a candidate material for the application in information identification technology. [ABSTRACT FROM AUTHOR]

As an important part of the Earth's environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way. [ABSTRACT FROM AUTHOR]

The caldera-forming Samalas eruption of the Samalas–Rinjani volcanic complex on Lombok, Indonesia, in 1257 CE ranks as one of the most explosive and sulphur-rich eruptions of the past thousand years. Along with other significant events (e.g. Tambora 1815, El Chichón 1982), Samalas 1257 forms a class of powerful eruptions of magmas of intermediate alkaline composition, which remain relatively understudied. This study aims to better understand the pre-eruptive magma reservoir conditions and volatile storage capacities of intermediate alkaline systems, using the 1257 Samalas eruption as a case study. Systematic partial-equilibrium experiments were run to constrain potential magma reservoir conditions (25–200 MPa and 850–1000°C) by examining changes in the chemistry and textures of experimental glass and mineral products. Natural trachydacite pumice from the 1257 Samalas eruption was used as the experimental charge for a series of water-saturated experiments run in cold-seal pressure vessels, buffered at an oxygen fugacity ƒ O2 of NNO/NNO + 1 log units. Assessing the match between natural and experimental glass compositions and mineral phases and textures reveals that pre-eruptive magma reservoir conditions were between 875°C and 930°C and ca. 100–150 MPa (4.5 ± 1km depth). Breakdown of experimental amphibole at pressures below 75 MPa, and plagioclase instability at 950°C/100 MPa, provide the strongest constraints on phase stabilities that are consistent with the magma storage region. In the observed temperature and pressure range, the natural compositions of plagioclase, amphibole and orthopyroxene are replicated in experimentally precipitated rims. Clinopyroxene and high anorthite plagioclase (An>64) in the natural mineral assemblage could not be replicated in the experiments, implying that these compositions most likely did not grow in the shallow pre-eruptive reservoir of Mt Samalas. The pre-eruptive storage depths of trachydacite magma are significantly shallower than the postulated magma storage at the currently active basaltic-andesite magmatic system at Rinjani, and thus monitoring magma storage depth may be a useful indicator of changing magma composition in the future. Our findings show that highly explosive VEI 7 eruptions of intermediate alkaline magma can be fed from a relatively limited range of storage pressures (100–150 MPa), suggesting accumulation of magma in one place, rather than the rapid extraction of magma from a vertically extensive, transcrustal magma system. [ABSTRACT FROM AUTHOR]

The structure and properties of the glass can be modified by introducing appropriate additives. Dolomite is one of the primary raw materials modifying the properties of glass, in which the essential component is calcium-magnesium double carbonate CaCO3∙MgCO3. The paper presents the research results on glasses obtained by smelting pure amphibolite and amphibolite modified with 10 and 20% dolomite additives. The raw material used was mined in the Poland region of Lower Silesia. The glass melting process was carried out in an electric furnace at 1450 °C for 2 h. The structure and properties of the glasses and crystallization products were determined by Differential Scanning Calorimetry (DSC), X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy—Energy Dispersive Spectroscopy (SEM-EDS). Viscosity and Vickers microhardness were also measured. It was found that the modification of amphibolite glass by adding dolomite affects the glasses' properties and structure. The research results determined the effect of dolomite addition on the properties of alumino-silicate glasses in terms of the mineral fibre products used in the construction industry. [ABSTRACT FROM AUTHOR]

High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications including water resource management. However, many of the existing global to continental scale hydrological models are applied at coarse resolution and or neglect lateral surface and groundwater flow, thereby not capturing smaller scale hydrologic processes. Applications of high-resolution and more complex models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically-based coupled land surface groundwater model; Parflow-CLM version 3.6.0, over a pan-European model domain at 0.0275o (~ 3 km) resolution. The model simulates three-dimensional variably saturated groundwater flow solving Richards equation and overland flow with a twodimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of hydrologic states and fluxes, resulting from a 10 year (1997-2006) model simulation, was performed using in10 situ and remote sensing observations including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent and water table depth. Overall, the uncalibrated PF-CLM-EU3km model shows good agreement in simulating river discharge for 176 gauging stations across Europe. Comparison with satellite-based datasets of SM shows that PF-CLM-EU3km performs well in semi-arid and arid regions, but simulates overall higher SM in humid and cold regions. Comparisons with reanalysis and remotely sensed ET datasets (GLEAM and GLASS) show no significant differences, both, across the European domain (on average the difference is -0.09 and 0.30 mm d-1 for GLEAM and GLASS products, respectively), and within regions (R > 0.9). The large-scale high-resolution setup forms a basis for future studies, demonstrating the added value of capturing heterogeneities for improved water and energy flux simulations in physically-based fully distributed hydrologic models over very large model domains. This study also provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting, considering the effects of lateral surface and groundwater flows. [ABSTRACT FROM AUTHOR]

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One of today's most-used glass products is a composite made of at least two glass panels connected with a soft polymeric interlayer—laminated glass. The mechanical properties of such elements are influenced by interlayer properties and the type of glass used. In this work, experimental and numerical analyses of laminated glass panels exposed to four-point bending are performed to observe and compare the stresses and displacements caused by different parameters, such as temperature, load duration, the thickness and type of the interlayers, as well as the symmetrical and nonsymmetrical disposition of the glass plates' thickness. The numerical analysis was verified by four-point bending experimental tests. After validation, a parametric study on these influences was performed. To obtain the relationship between the load duration, temperature, and thickness of the interlayer compared to the maximal displacement (as a measure of flexural stiffness) and tension stress in the bottom glass plate, an analytical polynomial of a sixth total order is proposed. Isosurfaces are created, showing the dependence of stresses and displacements on the specified parameters as well as clearly showing differences in the behavior of laminated glass panels for the same conditions but with different interlayers. Based on the findings of the parametric study, conclusions are derived about the flexural stiffness and stress distribution in two-plate laminated glass with PVB and ionoplast interlayers. [ABSTRACT FROM AUTHOR]

The inversion framework Land continuous Variable Estimator for Landsat data (LoVE)-Landsat has been recently developed, but the estimation accuracy has not been well determined. LoVE-Landsat is a data-assimilation-based inversion framework capable of estimating a series of daily 30-m spatiotemporal continuous land surface variables from Landsat top-of-atmosphere (TOA) data. This paper presents the comprehensive validation results of a land surface variables estimation conducted through LoVE-Landsat, including the leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), surface broadband albedo, incident photosynthetically active radiation (PAR), and incident shortwave radiation (ISR). This validation involved a direct validation using extensive ground measurements and an inter-comparison with existing satellite products. In situ measurements came from a total of 196 sites covering different biome types from seven networks distributed around the world. Among these sites, more than 2000 LAI and FAPAR plot measurements representing the Landsat pixel size were collected from 40 sites of the Bigfoot, VALERI, and ImagineS networks, about 100 LAI and FAPAR reference values at 3-km scale were provided by 52 sites of DIRECT datasets, and nearly 70,000 albedo and ISR and 40,000 PAR tower-based measurements were gathered from 143 sites of Ameriflux, Euroflux, Ozflux, and SURFRAD networks. Results showed that the LoVE-Landsat 30 m LAI estimates were accurate, with R2 = 0.76 and root-mean-square-error (RMSE) = 0.89, and were slightly more accurate than the coarse resolution Global LAnd Surface Satellite (GLASS) LAI product at the kilometer scale (RMSE = 0.75 vs. 0.79). Validation at the 143 flux network sites showed that the daily snow-free LoVE-Landsat 30 m shortwave albedo had an accuracy comparable to the MODIS daily albedo product (RMSE around 0.037) and higher accuracy (RMSE = 0.031) when Landsat had clear-sky observations. Direct validation of ISR and PAR estimation showed high accuracy, with RMSE values of 102.8 and 48.7 W/m2, respectively. Spatial and temporal evaluation at six typical sites also showed that LoVE-Landsat could produce consistent spatially and temporally continuous estimation. Although a more comprehensive validation of all retrievals still needs to be conducted, both the direct validation and product comparison results of the key variables indicate that LoVE-Landsat can estimate a group of spatially and temporally continuous variables from Landsat observations accurately, which demonstrates the strong potential of LoVE-Landsat to generate global 30-m continuous land products.

A new method of cesium immobilization has been successfully developed by combining alkali activation of boro-alumino-silicate glass and viscous flow sintering. Powdered glass from discarded pharmaceutical vials, suspended in a 2.5 M CsOH aqueous solution, underwent surface hydration as well as partial dissolution. Condensation reactions occurring at hydrated surface layers upon drying at 40 °C over 7 days resulted in welding of adjacent particles, forming a network that trapped newly formed gel and crystal phases. The newly formed phases including crystalline boro-pollucite (CsBSi 2 O 6), were derived mostly from Cs+ ions reacting with the products of glass dissolution and exhibited a high chemical stability. Further stabilization was achieved through viscous flow sintering at 700 °C, resulting in the incorporation of Cs+ ions in a glass matrix. The effectiveness of the immobilization was confirmed by leaching test using the Materials Characterization Center-1 Standard (MCC-1). This innovative approach not only enhances the chemical stability of cesium waste forms, but also aligns with principles of cleaner production by repurposing pharmaceutical glass waste, promoting sustainable materials management. [Display omitted] • Discarded pharmaceutical vials were used as a matrix for cesium immobilization. • Cesium (over of 20 wt%) was successfully immobilized by mild alkali activation. • Products of glass dissolution incorporate Cs+ in a boro-pollucite solid solution. • Cold consolidation at 40 °C is sufficient for managing simulated radioactive cesium. • Cesium is immobilized by viscous flow sintering of alkali-activated glass at 700 °C. [ABSTRACT FROM AUTHOR]

We developed a fiber laser based 515 nm single‐mode green laser with pulse width of 5 ns, peak power of greater than 20 kW, and repetition rates from 100 kHz to 500 kHz, which is suitable for glass drilling and grinding. The lithium triborate (LBO) crystal is used for second harmonic generation of 515 nm laser with efficiency of 68%. Glass drilling speed of 50 mm/s @ 0.5 mm thick glass was achieved for industrial environment continuous operation, which is equivalent to 1 s of time to drill a 4 mm diameter hole on a 2 mm thick glass. The typical chip sizes for the rear and front sides are 80 μm and 120 μm, respectively. Seven thousand holes are drilled in 24 hours in glass product line, and the success rate is larger than 99.7%. This laser glass drilling approach is rapidly accepted by glass industrial. Glass surface grinding was demonstrated by using 1 ns pulse width 515 nm lasers. [ABSTRACT FROM AUTHOR]

The article reports that The salvage excavations carried out above Naḥal ‘Anava (Wadi ‘Anabeh) at Modi‘in Kaizer South (see Tendler and Torge, this volume) yielded some 650 fragmentary glass finds, about half of which were diagnostic. All the finds are free-blown, many are decorated. Thirty-nine representative diagnostic fragments were selected for this publication and are presented in chronological and typological order.

The Waste Treatment and Immobilization Plant (WTP) will process and stabilize nuclear waste stored in tanks on the Hanford Site. At the WTP, the tank waste will be combined with glass-forming chemicals to make a melter feed slurry that can be vitrified in joule-heated melters. Technetium-99 (99Tc), a long-lived radionuclide present in tank waste, is semi-volatile from a glass melt at elevated temperatures. A small laboratory-scale melter system has been designed by PNNL to operate under radioactive conditions, giving it the ability to vitrify actual tank waste and gain information about melter feed processability and the partitioning of components of interest. This study describes two runs performed in a duplicate system with non-radioactive simulants of Hanford tanks 241-AP-107 and 241-AN-105 to gain insight into the relationship between the retentions of 99Tc and its non-radioactive surrogate Re while also investigating the effects of increasing the reducing agent such as sucrose during vitrification on processing and the retention of semi-volatile components in the glass product. The results from these runs align with the general trends of greater retention in the glass of Re compared to 99Tc and the improved retention in the glass of Re with increased reducing agent. [ABSTRACT FROM AUTHOR]

The solubility of titanite (CaTiSiO5) in Si-rich melts was measured experimentally through growth experiments at 800–1000 °C, 0.5–1.0 GPa, log fO2 ~ CCO–0.8, t = 72–168 h, and H2O = 0 to 4 wt.%, and in dissolution experiments at 925–1300 °C, 0.8 GPa, t = 18–118 h, and H2O = 1–10 wt.% in a piston-cylinder apparatus. Run product glasses in growth experiments were homogeneous, and iron loss suppressed ilmenite crystallization. Saturation concentrations in dissolution experiments were estimated by fitting measured diffusion profiles. Titanite solubility increases with increasing temperature and melt composition parameter M = molar Na + K + 2Ca / Al × Si . Multiple linear regression of glass composition data from growth and dissolution experiments (n = 29) plus 39 experiments from the LEPR database (Hirschmann et al. 2008) yielded the titanite solubility equation (adj. r2 = 0.95): T i O 2 melt w t. % = 0.978 × M + 0.0048 × T K - 5.90 . This model correctly predicted undersaturation in 95% of 2344 experiments from the LEPR database that did not have titanite or rutile. Application to natural rocks yields saturation temperatures that are similar to independent temperature estimates. This equation should be useful for constraining the temperatures of titanite-saturated melts, for determining whether titanite saturation in magmatic source regions is likely, and for determining when titanite can crystallize and begin to exert an influence on melt geochemistry. [ABSTRACT FROM AUTHOR]