Search Results (6,258)

The increasing urgency to mitigate plastic pollution has accelerated the shift from linear manufacturing toward circular systems. This review synthesizes current advances in mechanical, chemical, biological, and upcycling pathways, emphasizing how artificial intelligence (AI) is reshaping decision-making, performance prediction, and system-level optimization. Intelligent sensing technologies—such as FTIR, Raman spectroscopy, hyperspectral imaging, and LIBS—combined with Machine Learning (ML) classifiers have improved material identification, reduced reject rates, and enhanced sorting precision. AI-assisted kinetic modeling, catalyst performance prediction, and enzyme design tools have improved process intensification for pyrolysis, solvolysis, depolymerization, and biocatalysis. Life Cycle Assessment (LCA)-integrated datasets reveal that environmental benefits depend strongly on functional-unit selection, energy decarbonization, and substitution factors rather than mass-based comparisons alone. Case studies across Europe, Latin America, and Asia show that digital traceability, Extended Producer Responsibility (EPR), and full-system costing are pivotal to robust circular outcomes. Upcycling strategies increasingly generate high-value materials and composites, supported by digital twins and surrogate models. Collectively, evidence indicates that AI moves from supportive instrumentation to a structural enabler of transparency, performance assurance, and predictive environmental planning. The convergence of AI-based design, standardized LCA frameworks, and inclusive governance emerges as a necessary foundation for scaling circular plastic systems sustainably. Full article

Background/Objectives:Pyrus ussuriensis Maxim. has been cultivated in many regions worldwide. This plant is also regarded as a profitable fruit crop for the development of many food and functional products. There is limited research on the application of the LC-MS associated reaction method for screening active compounds. In this study, we developed an analytical technique employing an ultra-high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UHPLC-ESI-MS/MS) system. Methods: The metabolite annotation procedure was used to interpret and validate data analysis via spectral matching against public databases. Results: As a result, metabolites from P. ussuriensis water and EtOH extracts were identified, and their quantities were further evaluated. The established method was employed to determine antioxidant capacity using a pre-incubation UHPLC-2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, thereby identifying antioxidant ingredients. The antioxidative interference of active constituents was predicted by calculating the decrease in the peak areas of the chemical composition detected in chromatograms between treated and non-treated samples. Furthermore, drug-likeness was also assessed via pharmacokinetics (absorption, distribution, metabolism, and excretion: ADME) evaluation. Conclusions: The online UHPLC-MS-DPPH method would be a powerful tool for the rapid characterization of antioxidant ingredients in plant extracts. The current study highlights the value of P. ussuriensis for improved health benefits. Full article

With the rapid advancement in portable electronics, artificial intelligence, and the Internet of Things, there is an escalating demand for high-density, low-voltage non-volatile memory (NVM) technologies. Germanium (Ge) nanocrystals (NCs) have emerged as a promising candidate for NVM applications; however, traditional synthesis methodologies suffer from limitations in achieving precise control over the size and density of these nanocrystals, which exert a significant influence on device performance. This study presents an innovative Ag-catalyzed chemical vapor deposition (CVD) methodology for the synthesis of Ge NCs with precisely controllable size and density on SiO₂/Si substrates, tailored for NVM applications. Scanning electron microscopy characterization confirms the successful growth of faceted Ge NCs. Electrical characterization of the fabricated devices reveals that Ge NCs grown at temperatures ranging from 700 to 1000 °C exhibit memory windows spanning from 3.0 to 6.8 V under a ±6 V bias. Notably, the device synthesized at 900 °C demonstrates an exceptional memory window of 7.0 V under a ±8 V bias. Furthermore, the Ge NC-based NVM devices exhibit excellent charge retention characteristics. Specifically, for the device with Ge NCs grown at 700 °C, the time required to retain charge from 100% to 95% of its initial value exceeds 10 years, demonstrating long-term stable charge storage capability. These findings underscore the significant potential of this approach for the development of high-performance NVM technologies. Full article

Agricultural production residues are an easily accessible raw material for energy recovery in a circular economy. Therefore, the possibility of biogas production from herb processing waste, namely common thyme (Thymus vulgaris L.), peppermint (Mentha × piperita L.), curled mint (Mentha crispa L.), and currants (woody stems and leaves), was investigated. In this study, the evaluation of the natural biodegradability of plant waste under conditions typical for an agricultural biogas plant was consciously carried out without the application of pre-treatment processes (shredding, steam hydrolysis, chemical treatment) to facilitate the methane fermentation process. The average values of biogas production efficiency ranged from 75 to 320 m³/mg DM for herb species and from 152 to 209 m³/mg DM for currant varieties under normal conditions. As part of laboratory tests, the elemental composition, i.e., C, H, N, S, O, was determined. Moreover, the analysis showed the energy potential of the tested waste in thermochemical processes (combustion). Garden thyme residues have particularly high energy potential, as indicated by the high calorific value, low nitrogen and sulfur content, and low ash content. Full article

Photocatalytic reduction of CO₂ into value-added chemicals offers a sustainable route to mitigate greenhouse gas emissions while producing renewable fuels. However, conventional TiO₂-based systems suffer from limited visible-light activity and inefficient reactor configurations. Here, we developed electrospun polyacrylonitrile (PAN) membranes embedded with TiO₂-Cu₂O heterojunction nanoparticles and integrated them into a custom crossflow photocatalytic membrane reactor. The reactor employed bifacial illumination using a solar simulator (front) and a xenon/mercury lamp (back), each calibrated to 1 Sun (100 mW·cm⁻²). Membrane morphology was characterized by SEM, and chemical composition was confirmed by XPS. Photocatalytic performance was evaluated in CO₂-saturated 0.5 M potassium bicarbonate solution under continuous flow. The PAN/ TiO₂-Cu₂O membrane exhibited a methanol production rate of approximately 300 μmol·g⁻¹·h⁻¹ under dual-light illumination, outperforming single illumination, PAN-TiO₂, and PAN controls. Enhanced activity is attributed to extended visible-light absorption, improved charge separation at the TiO₂-Cu₂O heterojunction, and optimized photon flux through bifacial illumination. The electrospun architecture provided high surface area and porosity, facilitating CO₂ adsorption and catalyst dispersion. Combining heterojunction engineering with bifacial reactor design significantly improves solar-driven CO₂ conversion. This approach offers a scalable pathway for integrating photocatalysis and membrane technology into sustainable fuel synthesis. Full article

Lignin, the most abundant renewable source of aromatic compounds, plays a pivotal role in advancing sustainable biorefineries and reducing dependence on fossil resources. Recent progress in integrated lignin valorization pathways has unlocked opportunities to convert this complex biopolymer into high-value chemicals, materials, and energy carriers, despite its structural heterogeneity and recalcitrance posing major challenges. This review highlights the significant advancements in depolymerization strategies, including catalytic, oxidative, and biological approaches, which are reinforced by innovations in catalyst design and reaction engineering that enhance selectivity and efficiency. It also discusses emerging technologies, such as hybrid chemo-enzymatic systems, solvent fractionation, and continuous-flow reactors, for their potential to improve scalability and sustainability. Furthermore, this review examines the integration of lignin valorization with upstream pretreatment and downstream recovery, emphasizing process intensification, co-product synergy, and techno-economic optimization to achieve commercial viability. Despite these developments, critical gaps remain in understanding the molecular complexity of lignin, developing universally applicable catalytic systems, and optimizing economic and environmental performance. To guide future research, it poses two key questions: how to design catalysts for selective depolymerization across diverse lignin sources, and how to configure biorefineries for maximum lignin utilization while ensuring sustainability? Addressing these challenges will be essential for lignin’s role in next-generation biorefineries and a circular bioeconomy. Full article

In achieving sustainable development goals, soils play a key role in environmental protection, natural resources, and food security. Peatlands are particularly important here, as they function at the interface between terrestrial and aquatic ecosystems and store large amounts of organic matter. However, organic soils are highly susceptible to transformation and degradation; therefore, their degradation caused by, among others, drainage properties is a high risk to both the environment and agriculture—it disrupts the ecosystems, causes greenhouse gas emissions, and eutrophicates the hydrosphere. Soil degradation in drained peatlands is associated with the transformation of soil organic matter (SOM), which in organic soils is the dominant component of the solid phase of the soil. The aim of our study was to assess the properties and degree of organic matter transformation in drained temperate peatland soils, with particular emphasis on sequential fractionation of SOM and humic acid properties. Due to the fact that in Poland, as many as 90% of non-forest peat bogs have been drained, we compare the mursh horizons that formed after peat bog drainage with the peat horizons that constitute the parent rock (where anaerobiosis occurs and morphological changes in the soil material are absent due to peat bog drainage). Studies were conducted on 11 soil profiles located in central-eastern Poland. Basic physicochemical soil properties were determined: pH, bulk density, contents of ash, SOM, total carbon (TC), and total nitrogen (TN). Sequential carbon fractionation was used to qualitatively analyze organic matter, which allowed for the identification of labile fractions, lipid fractions, humic substances (fulvic and humic acids), and residual fractions. Humic acids (HAs) were extracted using the Schnitzer method and analyzed for their elemental composition and spectrometric parameters in the VIS range. It was demonstrated that SOM transformation in drained temperate peatland soils was correlated with comprehensive changes in the soil’s physical and chemical properties. Compared to peat horizons, topsoil horizons were characterized by higher ash content and density, lower SOM content, and a lower TC/TN ratio. Qualitative SOM transformation during aerobic SOM transformation after draining the studied peatlands consisted of an increase in the amount of labile fractions and humic substances and a decrease in the lipid and residual fractions. The research results have shown that the HAs properties depended on the depth. HAs from topsoil horizons, compared to peat horizons, were characterized by a lower “degree of maturity,” as reflected by the values of atomic ratios (H/C, O/C) and absorbance coefficients (A_4/6 and ΔlogK). It was found that the share of the distinguished SOM fractions and HAs properties were closely correlated with the physical and chemical properties of the soils. The study demonstrated the usefulness of the sequential carbon fractionation method for assessing the effects of dewatered peat transformation. The obtained results could contribute to the development of good practices ensuring high quality of organic matter and stability of ecosystems, as well as to the development of methods for limiting the mineralization of organic matter (SOM), greenhouse gas emissions, and the loss of organic soils in agricultural areas. Full article

The six platinum group elements (PGE) are among the rarest elements in the upper continental crust of the earth. Higher values of PGE have been detected in the upper mantle and in chondrite meteorites. The PGE are siderophile and chalcophile elements and are divided into the following: (1) the Ir subgroup (IPGE) = Os, Ir, and Ru and (2) the Pd subgroup (PPGE) = Rh, Pt, and Pd. The IPGE are more refractory and less chalcophile than the PPGE. High concentrations of PGE led, in rare cases, to the formation of mineral deposits. The PGE are carried in discrete phases, the platinum group minerals (PGM), and are included as trace elements into the structure of base metal sulphides (BM), such as pentlandite, chalcopyrite, pyrite, and pyrrhotite. Similarly to PGE, the PGM are also divided into two main groups, i.e., IPGM composed of Os, Ir, and Ru and PPGM containing Rh, Pt, and Pd. The PGM occur both in mafic and ultramafic rocks and are mainly hosted in stratiform reefs, sulphide-rich lenses, and placer deposits. Presently, there are only 169 valid PGM that represent about 2.7% of all 6176 minerals discovered so far. However, 496 PGM are listed among the valid species that have not yet been officially accepted, while a further 641 are considered as invalid or discredited species. The main reason for the incomplete characterization of PGM resides in their mode of occurrence, i.e., as grains in composite aggregates of a few microns in size, which makes it difficult to determine their crystallography. Among the PGM officially accepted by the IMA, only 13 (8%) were discovered before 1958, the year when the IMA was established. The highest number of PGM was discovered between 1970 and 1979, and 99 PGM have been accepted from 1980 until now. Of the 169 PGM accepted by the IMA, 44% are named in honour of a person, typically a scientist or geologist, and 31% are named after their discovery localities. The nomenclature of 25% of the PGM is based on their chemical composition and/or their physical properties. PGM have been discovered in 25 countries throughout the world, with 64 from Russia, 17 from Canada and South Africa (each), 15 from China, 12 from the USA, 8 from Brazil, 6 from Japan, 5 from Congo, 3 from Finland and Germany (each), 2 from the Dominican Republic, Greenland, Malaysia, and Papua New Guinea each, and only 1 from Argentine, Australia, Bulgaria, Colombia, Czech Republic, England, Ethiopia, Guyana, Mexico, Serbia, and Tanzania each. Most PGM phases contain Pd (82 phases, 48% of all accepted PGM), followed, in decreasing order of abundances, by those of Pt 35 phases (21%), Rh 23 phases (14%), Ir 18 phases (11%), Ru 7 phases (4%), and Os 4 phases (2%). The six PGE forming the PGM are bonded to other elements such as Fe, Ni, Cu, S, As, Te, Bi, Sb, Se, Sn, Hg, Ag, Zn, Si, Pb, Ge, In, Mo, and O. Thirty-two percent of the 169 valid PGM crystallize in the cubic system, 17% are orthorhombic, 16% hexagonal, 14% tetragonal, 11% trigonal, 3% monoclinic, and only 1% triclinic. Some PGM are members of a solid-solution series, which may be complete or contain a miscibility gap, providing information concerning the chemical and physical environment in which the mineral was formed. The refractory IPGM precipitate principally in primitive, high-temperature, mantle-hosted rocks such as podiform and layered chromitites. Being more chalcophile, PPGE are preferentially collected and concentrated in an immiscible sulphide liquid, and, under appropriate conditions, the PPGM can precipitate in a thermal range of about 900–300 °C in the presence of fluids and a progressive increase of oxygen fugacity (fO₂). Thus, a great number of Pt and Pd minerals have been described in Ni-Cu sulphide deposits. Two main genetic models have been proposed for the formation of PGM nuggets: (1) Detrital PGM represent magmatic grains that were mechanically liberated from their primary source by weathering and erosion with or without minor alteration processes, and (2) PGM reprecipitated in the supergene environment through a complex process that comprises solubility, the leaching of PGE from the primary PGM, and variation in Eh-pH and microbial activity. These two models do not exclude each other, and alluvial deposits may contain contributions from both processes. Full article

Passive micromixers can be used in a wide range of chemical applications for reagent preparation as well as chemical analysis. To investigate a micromixer with high performance under various Re conditions, based on the research of previous scientists, we hereby parameterize three influential factors on the structural design of the micromixer. In this study, we chose five distinct level values from a set of three influential factors of the micromixer, based on the results of a one-way impact analysis to ascertain their degree of influence. For five different Re cases, the Taguchi orthogonal test was performed using the selected five-level values, the fluid mixing efficiency was examined numerically, and we used the orthogonal table L₂₅5⁶. Finally, a set of optimization parameters was selected. An optimized micromixer structural model with high mixing efficiency under different Re conditions has been achieved. The degree of stirring of the optimized micromixer and the comparison curves before and after the optimization were also analyzed. We have also manufactured and tested the micromixer of this design. The simulation results show that the mixing efficiency of “the After Optimized Y-shaped channel Koch fractal Cesàro construction” micromixer (AOYKC) designs in this paper is increased by 15.99%, 21.19%, 19.34%, 11.41%, and 0.04% at Re = 0.1, 1, 10, 20, and 100. Full article

Excessive application of chemical fertilisers has led to soil phosphorus immobilisation and aquatic eutrophication, making the development of highly efficient acid/neutral phosphatases crucial for sustainable phosphorus utilisation. In this study, we systematically investigated strain J2, which was isolated from phosphate-contaminated soil in Laoshan, Nanjing, China. 16S rRNA gene sequence analysis identified this strain as Acinetobacter nosocomialis J2, with 99.78% sequence similarity. Whole-genome sequencing generated a 3.83 Mb genome with a GC content of 38.59%, revealing multiple phospho-metabolism-related enzyme genes, including phospholipase C and α/β-hydrolases. A large language model–based protein representation learning strategy was employed to mine acid/neutral phosphatase genes from the genome, in which the model learned contextual and functional features from known phosphatase sequences and was used to identify semantically similar genes within the J2 genome. This approach predicted nine phosphatase candidate sequences, including AnACPase, a putative acid/neutral phosphatase. Biochemical characterisation showed that AnACPase exhibits optimal activity at pH 6.0 and 50 °C, with a K_m value of 0.2454 mmol/L for the p-NPP substrate, indicating high substrate affinity. Mn²⁺ and Ni²⁺ significantly enhanced enzyme activity, whereas Cu²⁺ and Zn²⁺ strongly inhibited it. Soil remediation experiments further validated the application potential of AnACPase, which solubilised 171.56 mg/kg of phosphate within seven days. Overall, this study highlights the advantages of deep learning-assisted genome mining for functional enzyme discovery and provides a novel technological pathway for the bioremediation of phosphorus-polluted soils. Full article

Conventional anticorrosive coatings suffer from limitations of low solid content and rigorous surface pretreatment, posing environmental and cost challenges in field applications. In this study, a novel high-solid-content (>95%) epoxy-polysiloxane (Ep-PSA) ceramic metal coating was prepared that enables low-surface-treatment application. The originality lies in the synergistic combination of nano-sized ceramic powders, high-strength metallic powders, polysiloxane resin (PSA), and solvent-free epoxy resin (Ep), which polymerize through an organic–inorganic interpenetrating network to form a dense shielding layer. The as-prepared Ep-PSA coating system chemically bonds with indigenous metal substrate via Zn₃(PO₄)₂ and resin functionalities during curing, forming a conversion layer that reduces surface preparation requirements. Differentiating from existing high-solid coatings, this approach achieves superior long-term barrier properties, evidenced by |Z|_0.01Hz value of 9.64 × 10⁸ Ω·cm², after 6000 h salt spray exposure—four orders of magnitude higher than commercial 60% epoxy zinc-rich coatings (2.26 × 10⁴ Ω·cm², 3000 h salt spray exposure). The coating exhibits excellent adhesion (14.28 MPa) to standard sandblasted steel plates. This environmentally friendly, durable, and easily applicable composite coating demonstrates significant field application value for large-scale energy infrastructure. Full article

Alpine forests are key regulators of soil biogeochemical cycles, yet the extent to which forest type constrains soil microbial diversity and soil quality in high-elevation regions remains insufficiently resolved. Here, we assessed how contrasting alpine forest types influence the taxonomic composition and diversity of soil microbial communities, identified the dominant environmental drivers, and evaluated soil quality along the southern slope of the Qilian Mountains. Six forest types were examined, including four monospecific stands (Picea crassifolia, QQ; Betula spp., HS; Juniperus przewalskii, YB; and Pinus tabuliformis, YS) and two mixed formations (mixed conifer–broadleaf, ZKHJ; and mixed broadleaved, KKHJ). Bacterial and fungal communities were characterized using Illumina high-throughput sequencing, while structural equation modeling (SEM) was used to identify primary drivers of diversity and principal component analysis (PCA) was applied to construct the minimum data set (MDS) for soil quality evaluation. Mixed forests consistently exhibited higher bacterial and fungal alpha diversity than pure stands. Environmental gradients were the strongest positive drivers of microbial diversity, whereas soil chemical properties and vegetation-related biotic factors exerted partially negative effects. Soil quality index (SQI) values ranked as follows: KKHJ (0.55) > ZKHJ (0.49) > YB (0.48) > HS (0.46) > YS (0.44) > QQ (0.43). The mixed broadleaved forest reached Grade IV (upper-intermediate level) soil quality, whereas the other forest types were classified as Grade III (intermediate). Mixed forests showed stronger capacities for organic matter accumulation and nutrient retention. These findings indicate that promoting mixed forest stands is critical for improving soil structure, nutrient retention, and microbial diversity in this alpine region. Accordingly, forest management should prioritize the development of mixed forests to enhance overall soil quality. Full article

Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus, is driven by a tri-component system involving the pinewood nematode, Monochamus spp. beetle vectors, and susceptible pine hosts. Chemical control remains a scenario-dependent option for emergency suppression and high-value protection, but its deployment is constrained by strong regional regulatory and practical differences. In Europe (e.g., Portugal and Spain), field chemical control is generally not practiced; post-harvest phytosanitary treatments for wood and wood packaging rely mainly on heat treatment, and among ISPMs only sulfuryl fluoride is listed for wood treatment with limited use. This review focuses on recent progress in PWD chemical control, summarizing advances in nematicide discovery and modes of action, greener formulations and delivery technologies, and evidence-based, scenario-oriented applications (standing-tree protection, vector suppression, and infested-wood/inoculum management). Recent studies highlight accelerated development of target-oriented nematicides acting on key pathways such as neural transmission and mitochondrial energy metabolism, with structure–activity relationship (SAR) efforts enabling lead optimization. Formulation innovations (water-based and low-solvent products, microemulsions and suspensions) improve stability and operational safety, while controlled-release delivery systems (e.g., micro/nanocapsules) enhance penetration and persistence. Application technologies such as trunk injection, aerial/Unmanned aerial vehicle (UAV) operations, and fumigation/treatment approaches further strengthen scenario compatibility and operational efficiency. Future research should prioritize robust target–mechanism evidence, resistance risk management and rotation strategies, greener formulations with smart delivery, and scenario-based exposure and compliance evaluation to support precise, green, and sustainable integrated control together with biological and other sustainable approaches. Full article

Traditional chemical analysis of plant tissue is time-consuming, costly, and poses risks due to exposure to toxic gases, highlighting the need for faster, low-cost, and safer alternatives. Vis-NIR spectroscopy, combined with machine learning, offers a promising method for estimating leaf nutrient levels without chemical reagents. This study evaluated the potential of Vis-NIR spectroscopy for nutrient estimation in leaf samples of banana (n = 363), mango (n = 239), and grapevine (n = 336) by applying spectral pre-processing techniques—smoothing (SMO) and first derivative Savitzky–Golay (SGD1d) alongside two machine learning methods: Partial Least Squares Regression (PLSR) and Random Forest (RF). Plant tissue samples were analyzed using sulfuric and nitroperchloric wet digestion and hyperspectral sensors. The prediction models were assessed using concordance correlation coefficient (CCC) and mean squared error (MSE). The highest accuracy (CCC > 0.80 and MSE < 2 g kg⁻¹) was achieved for Ca in banana, P in mango, and N and Ca in grapevine across both machine learning methods and pre-processing techniques. The predictive models calibrated for ‘Grapevine’ exhibited the highest accuracy—characterized by higher CCC values and lower MSE values—when compared with the models developed for ‘Mango’ and ‘Banana’. Models using SMO and SGD1d showed better performance than those using raw spectra (RAW). The high amplitudes and variations in nutrient levels, combined with large standard deviations, negatively affected the predictive performance of the models. Full article

Arid and semi-arid ecosystems harbor a wealth of underexplored plant biodiversity with untapped ecological and pharmacological potential. This study integrates morphological and molecular barcoding (ITS and rbcL) to confirm the identity of eight wild plant species native to the Saudi Arabian desert: Calligonum crinitum, Tribulus terrestris, Cornulaca monacantha, Cleome pallida, Leptadenia pyrotechnica, Cyperus conglomeratus, Indigofera argentea, and Artemisia monosperma. High-resolution GC–MS analysis identified over 25 bioactive compounds across these taxa, grouped into functional classes including hydrocarbons, esters, fatty acids, quinones, terpenoids, and phenolics. Notable compounds such as n-hexadecanoic acid, 2,4-di-tert-butylphenol, lupeol, and D-limonene were linked to antioxidant activity, desiccation tolerance, and membrane protection under stress. L. pyrotechnica and A. monosperma emerged as chemical outliers with unique metabolite profiles, suggesting divergent strategies for climate resilience. Our results highlight the ecological and bioeconomic value of desert flora, positioning them as candidates for future research in metabolic engineering, dryland restoration, and plant-based pharmaceuticals. This integrative approach underscores the relevance of desert plants for sustainable development in the face of climate change. Full article