Search Results (313)

This study investigates the phase formation and smelting process of a complex Al-Si-Mn alloy based on thermodynamic diagram analysis (TDA). The Fe-Si-Mn-Al system was analyzed considering binary and ternary subsystems, and the standard Gibbs free energy of formation of selected ternary compounds was calculated using the additive method. Based on these results, phase equilibrium diagrams were constructed, and the system was tetrahedralized, leading to the identification of 15 thermodynamically stable tetrahedra. It was established that compositions of industrial interest are predominantly localized within tetrahedra enriched in silicide and aluminosilicide phases, particularly FeSi-Fe₂Al₂Si-Fe₃Al₁₁Si₆-Mn₅Si₃. Experimental verification was carried out in a 250 kVA ore-thermal furnace using manganese ore, high-ash coal, and quartzite. The smelting process was conducted under slag-free conditions with stable electrical operation. The obtained alloy had the following composition (wt.%): Fe ~ 12.1, Si ~ 44.7, Mn ~ 34.5, and Al ~ 5.1, with low impurity levels (C < 0.5%, S < 0.02%, p < 0.09%). Microstructural analysis using SEM-EDS confirmed the formation of silicide (FeSi, Mn₅Si₃) and aluminosilicide phases, which ensure the structural stability of the alloy. It is shown that the localization of alloy compositions within specific tetrahedra of the Fe-Si-Mn-Al system prevents self-disintegration. The results demonstrate that TDA is an effective tool for predicting phase composition and optimizing the production technology of complex ferroalloys. Full article

Illyrian helmets represent a key element of Iron Age martial culture in the western Balkans, reflecting technological knowledge, workshop traditions, and long-distance cultural exchange. Based on the currently available archaeological record, Illyrian helmets are first attested in contexts dating to the 8th–7th centuries BC, with finds concentrated in Greece and the central and western Balkans, including Macedonia, Albania, Dalmatia, and the wider interior. Over time, the form developed into several variants (Types I–IIIB). This study presents the elemental characterization of the total set of 27 Illyrian helmets excavated in Albania and currently preserved in local museum collections, a region where the later types are particularly well attested. As the helmets are intact and exhibited in museums, portable in situ XRF analysis was employed. The main research questions addressed how the alloy composition, including minor and trace elements, reflects local metallurgical practices and distinguishes Illyrian helmets from similar helmets in neighboring regions. The results indicate the consistent use of bronze alloys dominated by copper (89–95%) with low- to medium-tin contents (3.5–9.9%), consistent with established alloying practices for durable protective equipment. Minor and trace elements, including iron (up to 1.5%), lead (up to 0.76%), arsenic (up to 0.09%), zinc (up to 1.17%), and antimony (up to 2.36%), likely reflect metallurgical choices, recycling practices, or impurities linked to regional copper deposits. Principal Component Analysis of four retained components, collectively accounting for 88.5% of the total variance, confirms a broadly standardized bronze tradition, with compositional outliers suggesting locally variable ore sources or recycling rather than systematic typological change. These elemental signatures, particularly the association of arsenic, antimony, zinc, and iron, suggest regional metallurgical characteristics consistent with Albanian sulphide ore deposits, while the overall compositional homogeneity supports the hypothesis of centralized production at workshops such as Epidamnus and Apollonia. Full article

The large-scale generation of industrial waste salts (IWSs) across sectors such as coal chemical, pesticide, pharmaceutical, and dye manufacturing has raised increasing environmental and regulatory concerns. These IWSs often exhibit complex physicochemical profiles—featuring high concentrations of inorganic salts, persistent organic pollutants, and trace heavy metals—that pose significant challenges for both safe disposal and resource recovery. This review provides a comprehensive and pollutant-oriented overview of industrial waste salts, focusing on their sector-specific characteristics, dominant contaminant types, and tailored treatment strategies. Removal pathways for organic matter (e.g., thermal decomposition, advanced oxidation) and inorganic impurities (e.g., precipitation, ion exchange) are systematically analyzed, followed by technical pathways for salt separation based on crystallization and membrane processes. Resource utilization routes for major salt components, particularly NaCl and Na₂SO₄, are critically assessed in terms of technical feasibility, impurity tolerance, and end-use compatibility. The emergence of reclaimed salt quality standards and sector-specific impurity thresholds reflects a paradigm shift from purity-based to performance-based reuse evaluation. Finally, the review highlights future priorities including adaptive impurity control, downstream-specific salt grading, and enforceable regulatory frameworks to ensure the safe, scalable, and circular deployment of reclaimed salts in industrial systems. This study supports the coordinated advancement of control technologies and reuse standards, enabling the transformation of waste salts from environmental liabilities to secondary resources. Full article

Flocs, visible particles formed in sugar-sweetened beverages, reduce clarity and consumer acceptance of products. Their presence can be caused not only by different types of trace impurities in the sugar but also by interactions among beverage components. In this review, scientific reports on acid beverage flocs (ABFs) and alcohol flocs are summarized, the main pathways for their formation are described, and practical options for detecting them and preventing their formation in beverages are compiled. Using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 and related guidance, literature searches of Scopus, Web of Science (WoS), PubMed, Food Science and Technology Abstracts (FSTA), CAB Abstracts, and International Commission for Uniform Methods of Sugar Analysis (ICUMSA) resulted in the inclusion of 56 studies. In various types of beverages, complexes formed between proteins (Ps) and polyphenols (PPs) often initiate haze and floc formation, while polysaccharides (dextran, pectin, and starch), silica or silicates, and inorganic ions influence charge balance, particle bridging, and floc growth rate. Ethanol in alcohol beverages can further destabilize colloids and promote aggregation. For beet sugars, saponin–protein interactions are a likely pathway for the formation of ABF, but the available evidence is not consistent. In cane sugars, the reported roles of proteins, polysaccharides, silica, and starch in floc formation vary considerably between studies. For quality assurance, ICUMSA floc tests (GS2-40 and GS2-44) should be complemented by turbidity or haze measurement and colloid characterization such as light scattering, ζ–potential, and infrared IR-based analytical methods supported by chemometrics. Risk mitigation works best as a two-level strategy that combines impurity removal during sugar production and stabilization steps in beverage formulation and storage, including the use of clarification agents and control of pH, temperature, ionic strength, and oxygen exposure. Standardized reporting and validation of rapid predictors against ICUMSA benchmarks remain essential. Full article

Background: Maintaining therapeutic meropenem plasma concentrations requires prolonged infusion, but stability concerns exist between preparation and administration. This study compared the stability and operability of ready-to-use powder–liquid double-chamber bag (DCB) infusions versus traditional powder-for-injection (PFI) meropenem under clinical conditions. Methods: Infusions at clinically relevant concentrations were stored at 2–8 °C, 25 ± 5 °C, and 40 ± 2 °C for 12 h. Stability assessments included appearance, pH, osmolality, insoluble particle count, meropenem content (HPLC), and impurity A level. Results: DCBs demonstrated superior content uniformity, significantly fewer insoluble particles (p < 0.05), and greater operational simplicity compared to PFI. Refrigeration maintained meropenem content > 95% and effectively suppressed impurity formation for up to 12 h. However, at both room temperature and elevated temperature, impurity A exceeded pharmacopoeial limits within 2 h, particularly at higher concentrations. An innovative bedside solvent volume adjustment method enabled DCBs to deliver high-concentration infusions, facilitating individualized critical care dosing. Conclusions: Compared with traditional powder injection formulations, the Meropenem powder–liquid dual-chamber bag offers more convenient operation under routine preparation conditions and poses a lower risk of contamination during the preparation process. Its stability is more sensitive to storage temperature, requiring strict adherence to refrigeration conditions. When stored under standardized conditions, the dual-chamber bag can better ensure drug efficacy stability and medication safety, making it particularly suitable for clinical emergency use and standardized workflow management. Full article

The mechanical performance of secondary aluminum alloys depends on Secondary Dendrite Arm Spacing (SDAS). Commercial casting simulations accurately predict local thermal history but typically neglect the influence of compositional variability on SDAS by using fixed material constants. This study introduces a physics-informed machine learning framework to bridge macroscopic process simulation and microscopic solidification physics. A computational Design of Experiments covering 500 AlSi7 alloy variants was generated, and a theoretical SDAS ground truth was calculated using an analytical model incorporating the growth restriction factor. A Gradient Boosting Regressor surrogate was trained to predict the physics-informed SDAS from thermal and chemical inputs. The analysis reveals a solute sensitivity gap, where standard simulations misestimate SDAS by up to 20% for high-impurity batches. The surrogate model captures this variance ($R^2=0.95$, $\mathrm{MAE}=0.24\mathsf{\mu }\mathrm{m}$), enabling rapid, composition-specific microstructural prediction without additional simulation cost. This approach supports the reliable simulation of casting with secondary alloys, where the composition can be hardly considered constant. Full article

Metallurgical chromium slag is a hazardous by-product generated during the production of chromium salts and metallic chromium, containing significant amounts of leachable Cr(VI), which poses severe environmental and human health risks. To address this challenge, this study presents an integrated “alkaline roasting, water leaching with impurity removal, glucose reduction and vacuum calcination” process for its direct preparation to nano-pigment-grade Cr₂O₃. The reduction process was systematically optimized by investigating the effects of critical parameters: glucose dosage, HCl concentration, reduction temperature and time. Optimal conditions were established as 2.5 g of C₆H₁₂O₆, 20 mL of 12 M HCl, 55 °C and 4 h, achieving the Cr(VI) reduction efficiency of 99.66%. Comprehensive characterization of the final product via XRD, SEM-EDS and XRF confirmed its high quality. The Cr₂O₃ exhibited a purity of 99.31%, well-developed crystallinity and a uniform sub-micron particle size distribution, fully meeting industrial standards for pigment applications. By substituting conventional hazardous reductants with glucose, this route demonstrates enhanced safety, environmental compatibility and cost-effectiveness. The proposed methodology not only provides a practical and scalable solution for the valorization of hazardous chromium slag but also contributes to the advancement of green processing technologies in the metallurgical sector, supporting the transition towards a circular economy. Full article

Hydrogen energy is acknowledged as being the cleanest energy source. As hydrogen fuel cell technology advances, the development of low-cost, high-quality hydrogen purification technologies has grown increasingly critical. Targeting the separation of steam methane reforming gas mixture with a typical composition of H₂/CO₂/CH₄/CO = 76%/20%/3.5%/0.5%, a 6-bed-13-step pressure-swing adsorption process featuring four pressure-equalization steps was designed, in which a multi-layer adsorbent packing strategy was adopted to investigate the purification performance. The effects of feed flow rate, adsorbent packing combination, and purge-to-feed ratio on hydrogen purity and recovery, and on the impurity content level were analyzed. Furthermore, the gas-phase and solid-phase concentration distributions of each adsorbent layer under cyclic steady state were studied in detail, and the variation characteristics of their adsorption–desorption behaviors were systematically elaborated. Eventually, the optimal adsorbent combination and process condition configurations were determined. The results show that the proposed process can achieve a hydrogen purity of 99.99971%, with a concentration of CO of less than 0.2 ppm, which meets the fuel cell-grade hydrogen standard. Full article

An advanced artificial intelligence (AI)-powered mobile automated impurity removal system was developed and integrated into potato harvesting machinery for decentralized agricultural environments in Japan. As opposed existing stationary AI systems in centralized processing facilities, this mobile prototype enables on-field impurity removal in real time through a systematic dual-evaluation methodology. The system integrates the YOLOX-small architecture with precision pneumatic actuators and achieves 40–50 FPS processing under dynamic field conditions. Algorithm validation across 10 morphologically diverse potato varieties (Danshaku, Harrow Moon, Hokkaikogane, Kitaakari, Kitahime, May Queen, Sayaka, Snowden, Snow March, and Toyoshiro) using count-based analysis showed exceptional recognition, with potato misclassification rates of 0.08 ± 0.03% (range: 0.01–0.32%) and impurity detection rates of 89.99 ± 1.25% (range: 80.00–93.30%). Cross-farm validation across seven commercial farms in Hokkaido confirmed robust algorithm consistency (PMR: 0.08 ± 0.03%, IDR: 90.56 ± 0.82%) without farm-specific calibration, establishing variety-independent and environment-independent operation. Field validation using weight-based analysis during actual harvesting at 1–4 km/h confirmed successful AI-to-field translation, with 0.22–0.42% potato misclassification and adaptive impurity removal of 71.43–85.29%. The system adapted intelligently, employing conservative sorting under high-impurity loads (71.43% removal, 0.33% misclassification) to prioritize potato preservation while maximizing efficiency under standard conditions (85.29% removal, 0.30% misclassification). The dual-evaluation framework successfully bridged the gap between AI accuracy in laboratory settings and effectiveness in agricultural operations. The proposed AI algorithm surpassed project targets for all tested conditions (>60% impurity removal, <1% potato misclassification). This successful integration demonstrates technical feasibility and commercial viability for widespread agricultural automation, with a validated 50% reduction in labor (four workers to two workers). This implementation provides a comprehensive validation methodology for next-generation autonomous harvesting systems. Full article

Background/Objectives: Cell-free DNA (cfDNA) is a valuable biomarker for cancer diagnosis and therapy monitoring; however, its low abundance and fragmented nature present major challenges for reliable isolation, particularly from limited plasma volumes. Here, we report the development and evaluation of a novel magnetically assisted microfluidic chip with a three-inlet design for efficient cfDNA extraction from small-volume plasma samples. Methods: The platform enables controlled infusion of plasma, lysis buffer, and magnetic nanoparticle suspensions at defined flow rates. An external magnetic field selectively captures cfDNA-bound nanoparticles while efficiently removing background impurities. Results: Direct comparison with two in vitro diagnostic (IVD)-certified commercial cfDNA extraction kits showed that the microfluidic system achieved comparable cfDNA yields at standard plasma volumes and superior performance at reduced input volumes. High DNA purity and integrity were confirmed by quantitative PCR amplification of a housekeeping gene and clinically relevant targets. The complete workflow required approximately 9 min, used minimal equipment, reduced contamination risk, and enabled rapid processing with future potential for parallel multi-chip configurations. Conclusions: These findings establish the proposed microfluidic platform as a rapid, reproducible, and scalable alternative to conventional cfDNA extraction methods. By significantly improving recovery efficiency from small plasma volumes, the system enhances the clinical feasibility of liquid biopsy applications in cancer diagnostics and precision medicine. Full article

Exploitation of waste streams has gained prominence not only in sustainable use of resources but also as a potential source of raw materials. Silicon kerf is one such waste stream and its recycling has been quite topical in recent years. In the present study, the characterization of different industrial kerf samples was carried out using several techniques. The average metallic impurity concentration was approximately 400 ppmw with average particle size (D50) of 3.5 µm and surface area of approximately 33 m²/g. The inhomogeneity of kerf was shown to pose challenges like potential isotope interferences during analysis as well as being susceptible to high uncertainties and relative standard deviation (RSD). Remedies and best practices were recommended for successful characterization of such inhomogeneous materials. Full article

We present the first European intercomparison of primary flow measurement standards with hydrogen-enriched natural gas (up to 20% hydrogen in molar fraction) and natural gas with pressure up to 60 bar and volume flow rates in the range (5 to 160) m³/h. We describe the principles of operation of the primary standards and present the transfer standards, a rotary meter and an ultrasonic meter, used for the intercomparison. In many instances, the overlap between the different laboratories is satisfactory, but the collected results are limited and do not allow us to make advanced conclusions. In addition, we investigate the effect of nitrogen impurities (2% in molar fraction) on the performance of low-pressure gas meters for pure hydrogen using newly developed measurement standards. We present the methods and results of this investigation. We show that nitrogen impurities affect the volume flow measurements of an ultrasonic meter but seem to have little effect on a thermal mass flow meter. This paper explores future opportunities and challenges in international intercomparisons involving hydrogen blends and highlights key issues and solutions with hydrogen gas metering in the presence of impurities. Full article

Binder jet 3D printing combined with a low-temperature phase transformation process has emerged as a promising route for producing 3D-printed hydroxyapatite (3DPHA) scaffolds with controlled architecture for bone grafting applications. However, the toxicological profile of this unique binder jet-derived material has not yet been established. In this study, we conducted a comprehensive compositional and toxicological assessment of 3DPHA fabricated via the calcium sulfate transformation route. The material exhibited phase-pure hydroxyapatite (HA) with a Ca/P ratio consistent with non-stoichiometric HA and low levels of trace elemental impurities. In vitro assays revealed no cytotoxic, irritant, sensitizing, or mutagenic effects. This work provides a standardized toxicological and compositional safety validation of 3DPHA. By linking compositional purity to biological safety and demonstrating compliance with international benchmarks, this study establishes a regulatory foundation confirming that 3DPHA is chemically pure, biologically safe, and ready for clinical translation as a bone-graft material. Full article

The growing demand for sustainable and renewable materials has intensified interest in agro-industrial waste as an alternative source of cellulose. This review critically examines current approaches to cellulose production from major agro-industrial residues, including cereal straw, corn residues, rice waste, sugarcane bagasse, and oilseed by-products. Emphasis is placed on the relationship between feedstock composition and extraction efficiency, highlighting how lignin distribution, hemicellulose content, and mineral impurities influence pretreatment severity, cellulose yield, and process sustainability. The review systematically analyzes chemical, enzymatic, and mechanical processing routes, with particular attention being paid to pretreatment strategies, fibrillation intensity, and yield variability. Beyond cellulose recovery, key sustainability indicators—such as energy demand, water and chemical consumption, waste generation, and chemical recovery—are evaluated to provide a system-level perspective on process efficiency. The analysis demonstrates that cellulose yield alone is an insufficient criterion for sustainable process design and must be considered alongside environmental and techno-economic metrics. Advanced applications of agro-waste-derived cellulose are discussed using a feedstock-driven approach, showing that high functional performance can often be achieved with moderately processed cellulose tailored to specific end uses. Finally, the review addresses challenges related to feedstock heterogeneity, mineral management, standardization, and industrial scale-up, underscoring the importance of biorefinery integration, closed-loop resource management, and harmonized quality descriptors. These insights provide a foundation for the development of scalable and sustainable cellulose production pathways based on agro-industrial waste. Full article

CO₂ corrosion remains a critical challenge for the safe and reliable operation of Carbon Capture, Utilization, and Storage (CCUS) infrastructure. This review summarizes CO₂ corrosion implications from material selection, exposure time, CO₂ phase behavior, flow conditions, and impurities such as H₂O, O₂, SO_x, NO_x, and H₂S. CO₂ corrosion modeling has, since early works by de Waard in 1975, expanded to a wide range of models and software tools, many of which have already been reviewed and compared. This work provides a historical timeline and a comparative summary of models and software tools to assist in selecting models for CCUS applications. Modeling approaches are classified into empirical, semi-empirical, and mechanistic categories, with their assumptions, strengths, and limitations. CO₂ corrosion modeling has persistent challenges relating to data quality, data quantity, and parameter interactions, which reduce model accuracy, especially for machine learning approaches. The provided perspective emphasizes that machine learning and hybrid modeling approaches for CO₂ corrosion prediction are gaining popularity, and their effectiveness is currently limited by the quality and quantity of available corrosion data. The provided opportunities include recommendations for standardized experimental procedures and hybrid modeling strategies that combine physics-based insights from mechanistic modeling approaches with data-driven machine learning approaches. Full article