Search Results (446)

Ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) are physically complementary non-destructive evaluation methods for reinforced concrete, yet their integrated diagnostic use has been limited by the absence of controlled, ground-truth-validated calibration of the joint-signature space. This paper presents a laboratory calibration programme in which a single C30/37 reinforced concrete beam (3000 mm × 300 mm × 200 mm, three T12 bars at 35 mm cover, CEM I 42.5N, w/c = 0.50) was sequentially conditioned through four controlled deterioration states—intact reference (Model A), water-filled saw-cut crack (Model B), full saturation by seven-day top-surface ponding (Model C), and chloride-induced active corrosion (Model D). Seven RES2DINV inverted ERT sections at three electrode spacings (a = 7, 15, and 30 mm) and three 800 MHz GPR profiles were acquired across the four known ground-truth conditions. The intact-reference resistivity ρ₀ = 558 Ω·m (full-section median of the mlab dataset at a = 7 mm) and GPR-calibrated velocity v = 0.095 ± 0.008 m/ns (from hyperbola fitting at 35 mm rebar cover) establish the absolute baselines. The four conditions produce systematically distinct joint signatures: Model A exhibits uniform high resistivity with clean rebar hyperbolae and no anomalous reflections; Model B produces a localised ERT low-ρ anomaly (ρ_min = 1.46 Ω·m) co-located with a negative-polarity (R = −0.68) GPR crack-mouth reflection confirming water-fill; Model C produces pervasive low-ρ with a smooth depth gradient and 50–65% GPR amplitude attenuation (−6.0 to −9.1 dB); Model D produces the same bulk GPR signatures as Model C but with a critically different ERT spatial texture—a heterogeneous near-surface layer above a sharp boundary at z ≈ 40 mm with depth-preferential low-ρ concentrated at rebar level. This depth-preferential signature, quantified here by a reproducible Depth-Preferential Index (DPI), is the primary ERT-only diagnostic criterion distinguishing active corrosion from pervasive saturation. For the Model C versus Model D distinction, the GPR response is non-discriminating; this high-risk distinction is resolved exclusively by the ERT depth-preferential criterion. The calibration demonstrates that GPR and ERT are physically non-redundant in the strict sense: neither method alone can unambiguously discriminate all four states, but their combination yields correct classification within the controlled laboratory conditions and subject to the stated qualification conditions. The corrosion state was confirmed at the regime level (chloride above the depassivation threshold, under accelerated polarisation) but was not quantified electrochemically, so the depth-preferential signature is interpreted as an indirect spatial proxy for active corrosion rather than a measurement of corrosion rate. Seven failure modes are quantitatively characterised and embedded in the framework as a priori qualification conditions. The calibrated reference values (ρ₀, A₀, Stage 2 thresholds, depth-preferential criterion) are specific to the laboratory mix and curing history and require local Stage 1 recalibration for field application. Full article

To easily recover and reuse nano-magnetite (Fe₃O₄) during the catalytic process, Fe₃O₄ is successfully dispersed by coprecipitation of Fe(II, III) salts on anchoring sites of bagasse-sugarcane fibers generated by gliding-arc plasma. Previously, we explored the effect of ascorbic acid (ASC), hydrochloric acid (HCl) and plasma-activated water (PAW) acting as oxidation inhibitors of Fe(II) solution. Prepared materials were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDX). The obtained results show that the oxidation inhibitor agent influences the morphology, texture and activity of the synthesized bulk-magnetite, where Fe₃O₄-nanorods, Fe₃O₄-nanospheres and Fe₃O₄-nanosheets were, respectively, obtained with PAW, HCl and ASC. The Fenton-plasmacatalytic treatment of amaranth red dye used as a model pollutant for 30 min revealed degradation rates of 53, 79 and 80%, respectively, for Fe₃O₄-ASC, Fe₃O₄-HCl, and Fe₃O₄-PAW each coupled to plasma. The deposition of nano-magnetite on the plasma-activated bagasse-sugarcane fibers (BM) using PAW as the best oxidation inhibitor agent exhibited characteristic FTIR-absorption bands of -OH, -CH₂ and Fe-O, attesting the bagasse-sugarcane-Fe₃O₄ linkage. The supported magnetite revealed a pollutant degradation rate of 99%, which deeply highlights an activity improvement after Fe₃O₄ deposition on plasma-activated bagasse sugarcane. The reusability of supported-Fe₃O₄ catalyst revealed a pollutant degradation rate of 95% after the fourth cycle, thus highlighting its easy recovery and catalytic stability (reuse). Full article

Soil texture is a key determinant shaping bacterial communities in vineyard ecosystems, yet how different soil textures modulate bacterial characteristics in rhizosphere versus bulk soils during grapevine growth remains poorly understood. This study collected rhizosphere and bulk soil samples from five commercial Vitis vinifera cv. Cabernet Sauvignon vineyards in the eastern piedmont of Helan Mountain, Ningxia, China, spanning three distinct textures (gravelly, calcareous, and aeolian sandy soils). Shotgun metagenomic sequencing, soil physicochemical analysis, and four soil enzyme activity (alkaline phosphatase, urease, catalase, and invertase) measurements were conducted, using PERMANOVA and RDA to identify dominant driving factors. The results showed that bacteria accounted for 97.6% of all annotated sequences, representing the dominant group in soil microbial communities. Significant differences in bacterial abundance and alpha diversity (Chao1, ACE, Shannon, and Simpson) were observed in bulk soils across textures, whereas rhizosphere soils showed significant abundance differences but similar diversity levels. However, the 50 cm bulk soil sampling distance may have attenuated the true rhizosphere effect, and these findings should be interpreted with this methodological constraint in mind. Notably, bacterial community structure differed significantly between soils of the same pedogenic type but different textures, confirming that soil texture, rather than pedogenic classification, is the primary driver. Thirteen dominant bacterial phyla (>1% relative abundance) were identified, with Proteobacteria (47.7%), Actinobacteriota (22.9%), and Acidobacteriota (6.5%) as the main taxa. Mantel tests revealed significant correlations between nitrogen, phosphorus, organic matter contents and enzyme activities in rhizosphere soils (r ≥ 0.4, p < 0.01). RDA indicated that total phosphorus (TP), organic matter (OM), alkali-hydrolyzable nitrogen (AN), Mg, pH, available K (AK), and enzyme activities were key drivers of bacterial community structure (p < 0.05). Annotated metabolic functions based on KEGG orthology indicated lower overall metabolic pathway abundances in gravelly soils compared to calcareous and aeolian sandy soils. In conclusion, soil texture, rather than broad pedogenic classification, primarily shapes vineyard bacterial communities, providing a theoretical basis for precision viticulture and sustainable soil management. Full article

Accurate field-scale surface soil moisture (SSM) measures are important for agricultural water management. Conventional satellite SSM products remain too coarse for within-field applications. Here, we developed sequence-aware deep learning models for growing-season SSM estimation by fusing data from Sentinel-1 C-band SAR, harmonized Landsat-8/Sentinel-2 (HLS), and local ancillary datasets. We assembled a multi-source dataset on Sentinel-1 overpass time for 2016–2024 (May–September), yielding 1469 samples and 65 features per sample, including SAR and optical features, meteorological data, soil texture and bulk density, topography, crop labels, irrigation-likelihood flag, and irregular-time-step encoding. We compared long short-term memory (LSTM) and temporal convolutional neural network (TCN) architectures together with attention-augmented variants, including feature attention (FA), temporal attention (TA), and the combined feature–temporal attention (FTA). Models were trained and tested on seven years of data and were validated based on a temporal generalization using combined data of a wet year (2016) and a dry year (2023). The best model, FTA-TCN, achieved R² = 0.851, RMSE = 0.024 m³.m⁻³, and MAE = 0.020 m³.m⁻³ on the withheld validation years, outperforming the base LSTM (R² = 0.422; RMSE = 0.053 m³.m⁻³; MAE = 0.043 m³.m⁻³) and the base TCN (R² = 0.746; RMSE = 0.034 m³.m⁻³; MAE = 0.022 m³.m⁻³). Shapley additive explanations (SHAP) analysis indicated that antecedent precipitation and short-term rainfall accumulations were dominant forcings, while soil texture, elevation, incidence angle, and vegetation indices modulated SSM variability. Satellite-derived features accounted for ~28.5% of aggregated SHAP importance. Overall, the results show that dual-attention temporal convolution can capture field-scale SSM dynamics across wet and dry seasons when satellite signals are coupled with local soil-meteorological-management context. Full article

Citrus peel is examined here as a naturally evolved protective surface, with the goal of developing a transferable quantitative framework for extracting engineering-relevant descriptors from biological protective surfaces and using them as design templates for biomimetic counterparts. A single-specimen-per-species design is adopted to map intra-fruit geometric variation across regions and magnifications; absolute descriptor values are therefore reported as ordinal indicators of inter-species ranking rather than as population means. Five citrus species (lemon, orange, mandarin, grapefruit, and bitter orange) were characterised by mechanical testing (cutting, puncture, and compression; five replicates per fruit), gravimetric peel density and thickness, and scanning electron microscopy (SEM) at 100×–10,000×. The 135-image SEM dataset was processed with an automatic-calibration pipeline performing per-image scale-bar detection, multilevel-Otsu segmentation of albedo air space, cell-bounded surface segment (CBSS) and oil-gland segmentation on flavedo, and grey-level co-occurrence matrix (GLCM) texture analysis with a directional anisotropy index $A_F$. Calibration was consistent across all images (FoV × magnification $=\mathrm{403,273}\pm 410$ $\mathsf{\mu }$m$·\times$, $\pm 0.10\%$). Principal component analysis separated flavedo and albedo at every magnification (PC1 + PC2 = 84–92%). Within this dataset, grapefruit showed the densest CBSS cover (1072 ${\mathrm{mm}}^{-2}$) together with the highest oil-gland density (2.77 ${\mathrm{mm}}^{-2}$); bitter orange showed the largest CBSS area (23.7 $\mathsf{\mu }{\mathrm{m}}^2$) and the thickest peel (13.1 mm); mandarin showed the most directionally oriented flavedo film ($A_F=0.0885$); and lemon showed the most open albedo (${\phi }_{2D}=36.2\%$). Oil-gland equivalent diameter was essentially invariant (∼45 $\mathsf{\mu }$m) across the five fruits, while gland density varied 4.4-fold. The structural metrics define a layered descriptor space—a dense isotropic surface relief versus a thick cellular bulk—that supplies two distinct bioinspired-design priors: dense surface films as a structural prior for selective-permeability membranes and layered cellular cores as a prior for impact-absorbing panels. A modified-atmosphere packaging (MAP)-compatible biomimetic film is identified as one downstream design hypothesis requiring direct gas-permeability verification on synthetic membranes. Full article

Germanium (Ge) is a high-tech critical metal typically hosted at trace levels in sphalerite, making its detection and characterization challenging in both primary ores and mine residues. This study presents a multi-scale analytical workflow combining laser-induced breakdown spectroscopy (LIBS), electron probe micro-analysis (EPMA), and multivariate statistics to detect, map and quantify Ge distribution in a representative Pb-Zn sample from the Les Malines deposit (France). µ-LIBS mapping enables rapid centimeter-scale screening at 15 µm resolution and identifies Ge-bearing domains over large areas, which are subsequently investigated at micrometer scale using EPMA chemical mapping and quantitative analyses. Results reveal a strong µm-scale heterogeneity of Ge distribution within sphalerite, with Ge systematically concentrated in an Fe-rich intermediate zonation associated with prismatic growth textures, while Cu/Cd/Ag are enriched in distinct collomorph domains. Multivariate statistical analyses (correlation matrices and PCA) confirm a strong geochemical structuring opposing an Fe/Ge association against a Cu/Cd/Ag pole. These findings demonstrate that Ge incorporation is controlled by localized growth conditions rather than bulk composition. The proposed workflow provides an efficient and scalable framework for exploration, enabling rapid targeting of critical metal enrichments and supporting their extension to multiple mineralization stages, Pb-Zn deposits, and other high-tech critical metals (HTCMs) such as Ga and In. Full article

This study investigates the effect of dilute organic acid treatment on the structural, textural, electronic, and catalytic properties of layered La–Sr–Fe–O Ruddlesden–Popper (R–P) oxides using XRD, TEM, BET, Mössbauer spectroscopy, XPS, H₂-TPR, C₂H₆-TPR and catalytic testing. XRD and TEM confirm that the overall layered Ruddlesden–Popper structure is preserved after acid treatment and during catalysis, with minor changes in phase composition, including a decrease in the n = 1 phase and a relative increase in the n = 2 phase. BET analysis shows increased specific surface area and pore volume, forming a more accessible mesoporous structure that is retained under reaction conditions. Mössbauer spectroscopy and XPS reveal an increased Fe⁴⁺ fraction and formation of hydroxylated and carbonated surface species stabilizing active Fe sites. During catalysis, a dynamic Fe³⁺/Fe⁴⁺ redox cycle occurs, along with surface restructuring and involvement of non-lattice oxygen, while the bulk electronic structure remains largely unchanged. Catalytic tests show improved activity, with a 40–60 °C reduction in operating temperature for all acid-treated samples, independent of acid type. This enhancement is mainly attributed to surface-related modifications, including removal of surface Sr-containing species, improved surface accessibility, and enhanced mass transport, while the overall R–P structural remains preserved. Full article

For hydrological parameterization in high-Andean catchments, it is necessary to understand whether near-surface hydro-structural soil properties can provide a surrogate signal of particle-size composition when direct texture information is sparse. This study evaluated the extent to which sand, silt, and clay fractions can be approximated from organic matter ($\mathrm{OM}$), bulk density (${\rho }_b$), and saturated hydraulic conductivity ($K_{\mathrm{sat}}$) in the Zamora Huayco (ZH) and Irquis catchments, southern Ecuador. A harmonized dataset ($n=44$) was analyzed through exploratory statistics, compositional assessment, correlation analysis, PCA, fraction-wise regression, $\mathrm{ILR}$-based modeling, AIC/BIC term reduction, sensitivity analysis excluding $\mathrm{OM}$, nested $\mathrm{LOOCV}$, and bootstrap-based uncertainty intervals. Among LULC classes, samples classified as paramo occupied a distinct high-Andean hydro-edaphic domain, characterized by a differentiated relationship between soil physical properties and hydrological behavior. PCA showed that the dominant covariance structure involved $\mathrm{OM}$, ${\rho }_b$, $K_{\mathrm{sat}}$, and the redistribution between sand and silt. The BIC-reduced $\mathrm{ILR}$ model provided the most balanced formulation, with positive nested $\mathrm{LOOCV}$ performance for sand, silt, and clay ($R_{\mathrm{LOOCV}}^2=0.147$, $0.704$, and $0.124$, respectively) and exact $100\%$ compositional closure after inverse transformation. Silt was the most stable predicted fraction, whereas sand and clay retained larger residual uncertainty, stronger tail departures, and partial compression of the observed variability. The proposed equations provide local hydro-pedotransfer support, although their predictive signal remains dependent on further refinement, uncertainty assessment, and external validation before regional application. Full article

Nickel ferrite (NiFe₂O₄) is one of the most studied inverse-spinel ferrites because it combines moderate saturation magnetization, comparatively high electrical resistivity, chemical stability, and broad synthesis flexibility. Yet the literature shows that the measured structure and magnetism of NiFe₂O₄ are not intrinsic constants; they evolve strongly with dimensionality, size, thickness, strain state, cation distribution, surface spin disorder, and synthesis pathway. This review develops a unified theoretical and literature-based interpretation of how dimensionality reshapes the structural and magnetic behavior of NiFe₂O₄ across bulk ceramics, nanoparticles, one-dimensional nanostructures, polycrystalline thin films, and ultrathin epitaxial films. The review is anchored in the two uploaded nickel ferrite attachments and expanded using internet-sourced journal literature on spinel inversion, surface effects, mechanochemical synthesis, sputtered and pulsed laser deposited thin films, and epitaxial ultrathin-film anomalies. The central novelty of this article is the formulation of a dimensionality-dependent framework in which the observed magnetic response is governed by a competition among three coupled factors: (i) the cation-distribution function, which controls the A–B superexchange balance and therefore the net ferrimagnetic moment; (ii) the microstructural coherence function, which measures how crystallinity, strain, defects, and anti-phase boundaries preserve or degrade exchange continuity; and (iii) the surface/interface spin-order parameter, which quantifies the loss or reconfiguration of magnetic order at free surfaces and buried interfaces. Within this framework, bulk NiFe₂O₄ behaves as a near-equilibrium inverse spinel with relatively stable magnetization, whereas nanoscale NiFe₂O₄ experiences strong spin canting and finite-size suppression due to the growing fraction of disordered surface spins. Thin films introduce a distinct regime in which strain, texture, anti-phase boundaries, substrate mismatch, and growth kinetics determine both anisotropy and magnetization. In ultrathin epitaxial films, off-equilibrium cation redistribution and interface-controlled electronic reconstruction may even generate magnetization values far above bulk expectations. The review also compares major synthesis routes—solid-state reaction, sol–gel, co-precipitation, hydrothermal growth, reactive milling, combustion, pulsed laser deposition, and radio-frequency sputtering—and explains why each route biases the final dimensionality-dependent properties differently. A set of word-style equations is provided to formalize spinel inversion, finite-size suppression, anisotropy scaling, coercivity trends, and superparamagnetic crossover. Beyond summarizing the field, the review proposes a regime map linking dimensionality to characteristic structural defects and magnetic signatures, and it identifies unresolved questions concerning the true origin of enhanced magnetization in ultrathin NiFe₂O₄, the interplay between anti-phase boundaries and strain, and the distinction between intrinsic inversion changes and extrinsic substrate artifacts. The resulting article offers a submission-ready, originality-focused review that positions dimensionality as the master variable governing structure–magnetism correlations in nickel ferrite. Full article

Northeast China’s black soil region serves as a critical cornerstone of national food security, yet accelerating soil degradation, characterized by declining soil organic matter (SOM) and rising bulk density (BD), threatens the productive capacity of its farmland. Understanding how soil physicochemical properties regulate crop yields in this ecologically heterogeneous landscape is essential for sustainable agricultural development. Here, 2916 soil samples from 201 counties across six ecological zones were analyzed in conjunction with county-level rice and maize yield records. Our findings revealed that crop yield determinants are fundamentally governed by regional resource endowment characteristics rather than uniform factors. In areas characterized by sandy soil texture, low precipitation (<400 mm yr⁻¹), and inherently low fertility, elevated bulk density (BD, >1.34 g cm⁻³) and alkaline soil conditions (pH > 7.0) constitute the primary constraints to productivity through restricting root development. Conversely, in regions with fertile mollisols and high baseline soil organic matter (SOM > 40 g kg⁻¹), nutrient dynamics emerge as the dominant yield-regulating factors. For volcanic soil landscapes with strong phosphorus fixation capacity, available phosphorus deficiency represents the critical bottleneck for maize production. Path analysis further demonstrates that BD and pH operate predominantly through indirect mechanisms, modulating SOM accumulation and nutrient cycling rather than directly constraining yield. Threshold analysis identified that BD exceeding 1.34 g cm⁻³ and SOM below 26 g kg⁻¹ markedly reduce productivity, while SOM levels above 40 g kg⁻¹ yield diminishing marginal returns. These findings advance our mechanistic understanding and provide scientific foundations for spatially differentiated soil conservation and precision nutrient management strategies essential for sustaining grain production capacity in northeast China’s black soil region. Full article

Background: Existing therapies for xerostomia are primarily symptomatic, providing temporary mucosal hydration without addressing underlying pathological changes in the oral cavity. In this context, medicated chewing gums containing ascorbic acid and lysozyme hydrochloride offer a promising approach, combining antimicrobial, antioxidant, and trophic effects with physiological salivary stimulation and prolonged local delivery. Methods: For the development of compressed chewing gum formulation, the physicochemical (particle size distribution, moisture absorption capacity, and microscopic characteristics) and technological (flowability, angle of repose, bulk and tapped density, Carr’s index (CI), and Hausner ratio (HR)) properties of the active substances and their formulations with excipients were evaluated. Pharmacological activity was assessed in an atropine-induced xerostomia rat model. Results: The physical mixture of all components showed inferior flow properties compared with the formulation containing pre-granulated lysozyme hydrochloride, as evidenced by higher Carr’s index and Hausner ratio values (CI = 17, HR = 1.20 vs. CI = 13, HR = 1.14), indicating improved processability after pre-granulation. The effect of relative humidity during formulation was also assessed, with an optimal level of 40% required to ensure process stability due to the hygroscopic nature of the components. Based on these data, technological approaches ensuring processability were established, including wet pre-granulation of lysozyme hydrochloride and premixing of ascorbic acid to reduce oxidation risk. These approaches resulted in an optimized compression mass with excellent flowability (CI = 8, HR = 1.09), suitable for the preparation of medicated chewing gum. An optimal compression force (7 kN) ensured suitable rheological and textural properties, resulting in rapid and nearly complete release of the active ingredients from the medicated chewing gum, consistent with kinetic analysis. In vivo studies using an atropine-induced xerostomia rat model demonstrated that the combination of ascorbic acid and lysozyme hydrochloride significantly increased salivary secretion (2.17-fold vs. control pathology group) and reduced salivary gland mass coefficients (by 13–18% compared with the control pathology group and groups receiving individual active ingredients), alongside improvement of oxidative stress markers, including a reduction in TBA-reactants (by 51.6%) and an increase in catalase activity (by 51.0%). Conclusions: The developed medicated chewing gum showed favorable technological properties, efficient release of active ingredients, and anti-xerostomic activity in vivo, indicating its potential for xerostomia relief and oral health support. Full article

Glauconite-rich sands can generate authigenic clays during burial, as glauconite breaks down and supplies material for smectite that may subsequently transform into illite. The smectite-to-illite transformation is a key burial diagenetic reaction that strongly influences sandstone reservoir quality; however, the reaction pathways and resulting textures in glauconite-rich sands remain insufficiently documented. To better constrain illitization in glauconitic systems, we conducted four hydrothermal batch experiments using glauconitic greensand from the Arnager Greensand Formation (Bornholm Island, Denmark), reacted with Red Sea water at 80 °C, 150 °C, 200 °C, and 250 °C for 21 days. Reaction products were characterized using bulk and clay-fraction XRD, XRF, and SEM–EDS, together with pre- and post-reaction fluid chemistry. At 80 °C, early dissolution of glauconite and other detrital components (K-feldspar, muscovite and calcite) was observed, resulting in increased concentrations of dissolved ions in the fluid but no authigenic clay formation. Authigenic smectite first developed at 150 °C, occurring primarily as grain-coating clay. With further heating to 200 °C, smectite began to transform into mixed-layer illite–smectite, accompanied by the first clear development of illite textures. At 250 °C, illitization advanced significantly, and the reacted products were dominated by wavy to fibrous illite. The resulting clay minerals and their grain-coating morphologies are comparable to coatings reported from buried sandstone reservoirs. These findings suggest that glauconite alteration can generate grain-coating clays that may help limit quartz cement growth and preserve porosity. However, the development of wavy/fibrous illite may also obstruct pore spaces and reduce permeability. Overall, glauconite-derived clay evolution may preserve porosity while still degrading permeability, and the net reservoir effect depends on the morphology and distribution (thickness and coverage) of the newly developed clay minerals. Full article

Soil water retention curves (SWRCs) are fundamental inputs for simulating vadose-zone processes, yet their direct measurement is labor-intensive and often impractical across large spatial domains. Pedotransfer functions (PTFs), therefore, provide an essential alternative for estimating SWRCs from readily measured soil properties. This study developed machine learning-based PTFs to estimate SWRCs using the UNSODA 2.0 database. An extreme gradient boosting (XGB) model was implemented and optimized using two Bayesian hyperparameter tuning frameworks, Hyperopt and Optuna, across eleven input scenarios incorporating combinations of textural, structural, and compositional soil attributes. Model performance was assessed using RMSE, R², and Kling–Gupta efficiency (KGE). To prevent data leakage from the hierarchical structure of the UNSODA 2.0 database, a nested grouped cross-validation framework was employed, ensuring an unbiased assessment of model generalization performance across independent soil samples. The Optuna-tuned XGB model trained on the full feature set achieved the highest accuracy, with a test RMSE of 0.0183, R² of 0.9815, and KGE of 0.9825, outperforming both the baseline and Hyperopt-optimized models. Feature importance and SHAP analyses indicated that soil texture dominated the estimations, while porosity, bulk density, and organic matter provided complementary improvements and particle density contributed marginally. These findings demonstrate that advanced hyperparameter optimization enhances the accuracy and interpretability of XGB-based PTFs, offering a robust framework for improved estimation of SWRCs in hydrological and soil-management applications. Full article

Handheld X-ray fluorescence (HHXRF) scanners generate rapid, low-cost geochemical datasets from core and cuttings, yet their potential for quantitative reservoir characterisation remains largely unrealised, partly because standard multivariate methods are inappropriate for the compositional nature of geochemical data. Here we test, for the first time within a compositional data analysis framework, whether centred log-ratio-transformed HHXRF element compositions can simultaneously predict plug-scale porosity, directional permeability and facies in a siliciclastic reservoir in a continuously cored Brent Group well from the Northern North Sea. The cored interval was logged for facies, sampled for routine core analysis, and analysed by HHXRF at plug sample positions. Sixteen consistently detectable elements were transformed using centred log-ratios to respect the compositional nature of the data, and four Random Forest models were trained: regression models for porosity, horizontal permeability and vertical permeability and a seven-category facies classifier. Models were evaluated using out-of-bag predictions, residual analyses, class-wise reliability metrics and permutation-based variable importance. The models reproduce porosity and permeability with high coefficients of determination (R² > 0.95) and low errors relative to observed ranges and achieve facies classification with substantial agreement (κ = 0.705), with best performance in clean sandstone facies. Predictive skill is dominated by a consistent subset of elements (notably Ca, Ti, Si, V, Zn and Rb), linking bulk composition to mineralogy, depositional texture and diagenetic modification. These results demonstrate that compositional data from HHXRF alone can quantitatively recover key reservoir attributes and facies architecture at plug scale, establishing bulk geochemistry as a robust proxy for reservoir quality in quartz-rich, moderately buried siliciclastic reservoirs. The workflow provides a methodological template for integrating compositional geochemistry with machine learning in subsurface characterisation and, pending multi-well validation, offers a route to cost-effective prediction of porosity, permeability anisotropy and facies from cuttings or high-resolution core scanning. The workflow has direct application to geocellular model population in carbon and hydrogen storage sites, geothermal reservoirs and conventional hydrocarbon fields. Full article

Potato nitrogen (N) demand varies with developmental stage rather than remaining uniformly high throughout the season. This review re-examines the “nitrate-first, ammonium-later” strategy by separating total N amount, N-supply timing, N form, and soil N transformation. Current evidence suggests that nitrate is better aligned with pre-tuber initiation because it supports stolon development and tuber set under non-excessive N supply, whereas ammonium-containing nutrition may benefit tuber bulking only when NH₄⁺ persists in the root zone and soil chemical constraints are controlled. Field responses attributed to N form are often shaped by crop N status, genotype × environment × management interactions, nitrification–denitrification dynamics, water regime, soil texture, fertilizer placement, and cultivar. We therefore interpret the strategy as a conditional, stage-oriented framework rather than a universal fertilizer prescription. Integrating NNI-/CNDC-based diagnosis, root-zone monitoring, enhanced-efficiency fertilizers, and soil-process evidence can improve synchronization between N supply and potato demand, supporting yield formation, N-use efficiency, and reduced environmental risk. Full article