Search Results (63)

Poly(N-isopropylacrylamide) (PNIPAM) hydrogels are temperature-sensitive materials whose swelling is difficult to predict near the gel collapse temperature (GCT). A physics-informed neural network (PINN) was developed in which a stabilized free-energy model is embedded and sparse data for free and uniaxially constrained swelling are assimilated. Across datasets, the PINN reduces test RMSE by 44% at low crosslink density ($N\nu =0.0035$) and by 65% at higher density ($N\nu =0.02$), with coverage inside ±RMSE bands improving from 61.9% to 76.2% for free swelling at Nν = 0.0035. Under constraint, test relative error decreases from 19.95% to 11.86% ($n=1$) and from 9.19% to 5.90% ($n=3$), while preserving thermodynamic stability. The method sharpens the transition slope near the gel-collapse temperature and narrows prediction intervals without overfitting, capturing cold-regime plateaus and hot-side tails more faithfully. The framework integrates governing equations with data to deliver accurate swelling and stress predictions using only eight anchors and thirteen held-out points per case. These results position PINNs as a reliable surrogate for designing thermo-responsive hydrogels in soft actuators and biomedical systems. Full article

We investigate how grain growth, strain relaxation, and vacancy chemistry shape the near-edge optical response of nanocrystalline Ce${\mathrm{O}}_{2-\delta }$ prepared by a chymosin-assisted Pechini route from nitrate–citrate precursors. Rietveld line-profile analysis shows that phase-pure Ce${\mathrm{O}}_{2-\delta }$ forms after calcination between 400 and 1000 °C. Over this range, the average crystallite size increases from ≈3.4 to ≈57 nm, while the microstrain decreases from 0.79% to 0.05%, with size–strain scaling consistent with interface-controlled grain growth that follows a normal growth law with exponent $m=2$ and activation energy $Q\approx 155$ kJ ${\mathrm{mol}}^{-1}$. Raman spectroscopy tracks the sharpening of the $F_{2g}$ mode and the fading of defect-related bands, X-ray photoelectron spectroscopy reveals a nonmonotonic evolution of the surface ${\mathrm{Ce}}^{3+}$ fraction and separates lattice from adsorbed oxygen species, and electron paramagnetic resonance detects vacancy-bound ${\mathrm{Ce}}^{3+}$ polarons that weaken at high temperature. Diffuse-reflectance UV–Vis spectra show a modest blue shift of the apparent band gap from $E_g\approx 2.78$ to 2.95 eV as crystallites coarsen, while the Urbach energy $E_u$ follows the ${\mathrm{Ce}}^{3+}$ content and sub-gap tailing. The structural, spectroscopic, and optical results together map out a quantitative connection between grain growth, vacancy populations, and near-edge optical properties in ${\mathrm{CeO}}_{2-\delta }$ nanoparticles. Full article

Analysis of the EPR of dilute transition-ion complexes and metalloproteins in random phases, such as frozen solutions, powders, glasses, and gels, requires a model for the spectral ‘powder’ shape. Such a model comprises a description of the line shape and the linewidth of individual molecules as well as a notion of their physical origin. Spectral features sharpen up with decreasing temperature until the limit of constant linewidth of inhomogeneous broadening. At and below this temperature limit, each molecule has a linewidth that slightly differs from those of its congeners, and which is not related in a simple way to lifetime broadening. Choice of the model not only affects precise assignment of g-values, but also concentration determination (‘spin counting’), and therefore, calculation of stoichiometries in multi-center complexes. Forty years ago, the theoretically and experimentally well-founded statistical theory of g-strain was developed as a prime model for EPR powder patterns. In the intervening years until today, this model was universally ignored in favor of models that are incompatible with physical reality, resulting in many mistakes in EPR spectral interpretation. The purpose of this review is to outline the differences between the models, to reveal where analyses went astray, and thus to turn a very long standstill in EPR powder shape understanding into a new start towards proper methodology. Full article

Urban surface temperatures are increasing because of climate change and rapid urbanisation, contributing to the urban heat island (UHI) effect and significantly influencing local climates. Satellite-derived land surface temperature (LST) plays a vital role in analysing urban thermal patterns. However, current satellite thermal infrared (TIR) sensors have a low spatial resolution, making it difficult to accurately capture the complex thermal variations within urban areas. This limitation affects the assessments of UHI effects and hinders effective mitigation strategies. We proposed a hybrid model named “geospatial machine learning” (GeoML) to address these challenges, combining random forest and kriging downscaling techniques. This method utilises high spatial resolution data from Sentinel-2 to enhance the LST derived from Landsat 8/9 data. Tested in Perth, Australia, GeoML generated an enhanced LST with good agreement with ground-based measurements, with a Pearson’s correlation coefficient of 0.85, a root mean square error (RMSE) of 2.7 °C, and a mean absolute error (MAE) of less than 2.2 °C. Validation with LST derived from another TIR sensor also provided promising outputs. The results were compared with the high-resolution urban thermal sharpener (HUTS) downscaling methods, which GeoML outperformed, demonstrating its effectiveness as a valuable tool for urban thermal studies involving high-resolution LST data. Full article

Climatic force might sharpen the latitudinal gradients of foliar nutrients directly (the Temperature–Plant Physiological hypothesis) or indirectly (either through soil nutrient, the Soil Substrate Age hypothesis, or plant functional type (e.g., herbs and trees) composition, the Species Composition hypothesis). However, the validities, effectiveness, and key drivers of these hypotheses have not been further examined globally. Here, we tested these hypotheses by synthesizing data from 2344 observations of leaf N, leaf P, and leaf K in terrestrial plants. The results indicated that leaves enriched nutrients towards the polar region. The validity of each hypothesis was confirmed, with the exception of the Soil Substrate Age hypothesis failing to predict leaf N, as the climatic influence on leaf N occurs through a mechanism opposite to what the hypothesis suggests. Additionally, among all hypotheses, the Species Composition hypothesis was the most effective model for leaf N, whereas the Substrate Age hypothesis was the most effective model for leaf P and leaf K. Soil, climate, and plant functional type collectively accounted for over half of the variations in leaf nutrients. Specifically, soil nutrient was the strongest determinant for leaf P and K, whereas plant functional type for leaf N. Taking into account changes in plant functional types and soil nutrients will improve the modeling of biogeochemical cycles under climate change. We expect further verification by global investigations of leaf stoichiometry using uniform methods. Full article

Land surface temperature (LST) plays a pivotal role in many environmental sectors. Unfortunately, thermal bands produced by instruments that are onboard satellites have limited spatial resolutions; this seriously impairs their potential usefulness. In this study, we propose an automatic procedure for the spatial downscaling of the two 100 m thermal infrared (TIR) bands of LandSat 8/9, captured by the TIR spectrometer (TIRS), by exploiting the bands of the optical instrument. The problem of fusion of heterogeneous data is approached as hypersharpening: each of the two sharpening images is synthesized following data assimilation concepts, with the linear combination of 30 m optical bands and the 15 m panchromatic (Pan) image that maximizes the correlation with each thermal channel at its native 100 m scale. The TIR bands resampled at 15 m are sharpened, each by its own synthetic Pan. On two different scenes of an OLI-TIRS image, the proposed approach is compared with 100 m to 15 m pansharpening, carried out uniquely by means of the Pan image of OLI and with the two high-resolution assimilated thermal images that are used for hypersharpening the two TIRS bands. Besides visual evaluations of the temperature maps, statistical indexes measuring radiometric and spatial consistencies are provided and discussed. The superiority of the proposed approach is highlighted: the classical pansharpening approach is radiometrically accurate but weak in the consistency of spatial enhancement. Conversely, the assimilated TIR bands, though adequately sharp, lose more than 20% of radiometric consistency. Our proposal trades off the benefits of its counterparts in a unique method. Full article

The optical properties of MoS₂ and WS₂ monolayers are significantly influenced by fabrication methods, especially with respect to the behavior of excitons at the K−point of the Brillouin zone. Using spectroscopic ellipsometry, we obtain the complex dielectric functions of monolayers of these materials from cryogenic to room temperatures over the energy range 1.5 to 6.0 eV. The excitonic structure of each sample is analyzed meticulously by fitting the data to a standard analytical function to extract the energy positions of the excitons at each temperature. At low temperatures, excitonic structures are blue-shifted and sharpened due to the reduction in phonon noise and lattice distance. The excitons of monolayers fabricated by MOCVD separate into sub-structures at low temperatures, while monolayers grown by LPCVD and APCVD remain a single peak. The origin of these peaks as charged or neutral excitons follows from their temperature dependences. Full article

In advanced engineering applications, there has been an increasing demand for the service performance of materials under high-strain-rate conditions where a key phenomenon of adiabatic shear instability is inevitably involved. The presence of adiabatic shear instability is typically associated with large shear strains, high strain rates, and elevated temperatures. Significant plastic deformation that concentrates within a adiabatic shear band (ASB) often results in catastrophic failure, and it is necessary to avoid the occurrence of such a phenomenon in most areas. However, in certain areas, such as high-speed machining and self-sharpening projectile penetration, this phenomenon can be exploited. The thermal softening effect and microstructural softening effect are widely recognized as the foundational theories for the formation of ASB. Thus, elucidating various complex deformation mechanisms under thermomechanical coupling along with changes in temperatures in the shear instability process has become a focal point of research. This review highlights these two important aspects and examines the development of relevant theories and experimental results, identifying key challenges faced in this field of study. Furthermore, advancements in modern experimental characterization and computational technologies, which lead to a deeper understanding of the adiabatic shear instability phenomenon, have also been summarized. Full article

The <100> oriented single-crystalline Zirconium Carbide (ZrC) nanowires were controllably synthesized on a graphite substrate by chemical vapor deposition (CVD) with optimized growth parameters involving Zirconium tetrachloride (ZrCl₄), flow of methane (CH₄), and growth temperature. The length of nanowires is above 10 µm while the diameter is smaller than 100 nm. A single ZrC nanowire was picked up and fixed on a tungsten tip for field emission measurement. After surface pretreatments, a sharpened and cleaned ZrC nanowire emitter showed a high emission current density of 1.1 × 10¹⁰ A m⁻² at a low turn-on voltage of 440 V. The field emission is stable for 150 min with a fluctuation of 1.77%. This work provides an effective method for synthesizing and stabilizing single-crystalline ZrC nanowire emitters as an electron source for electron-beam applications. Full article

A set of Eu³⁺-doped molybdates, Y₂₋xEuxMo₃O₁₂ (x = 0.04; 0.16; 0.2; 0.4; 0.8; 1; 1.6; 2), was synthesized using a solid-state technique and their properties studied as a function of Eu³⁺ concentration. X-ray diffraction showed that the replacement of Y³⁺ with larger Eu³⁺ resulted in a transformation from orthorhombic (low doping concentrations) through tetragonal (high doping concentrations), reaching monoclinic structure for full replacement in Eu₂Mo₃O₁₂. The intensity of typical Eu³⁺ red emission slightly increases in the orthorhombic structure then rises significantly with dopant concentration and has the highest value for the tetragonal Y₂Mo₃O₁₂:80mol% Eu³⁺. Further, the complete substitution of Y³⁺ with Eu³⁺ in the case of monoclinic Eu₂Mo₃O₁₂ leads to decreased emission intensity. Lifetime follows a similar trend; it is lower in the orthorhombic structure, reaching slightly higher values for the tetragonal structure and showing a strong decrease for monoclinic Eu₂Mo₃O₁₂. Temperature-sensing properties of the sample with the highest red Eu³⁺ emission, Y₂Mo₃O₁₂:80mol% Eu³⁺, were analyzed by the luminescence intensity ratio method. For the first time, the peak-sharpening algorithm was employed to separate overlapping peaks in luminescence thermometry, in contrast to the peak deconvolution method. The Sr (relative sensitivity) value of 2.8 % K⁻¹ was obtained at room temperature. Full article

Creep-feed grinding of high-strength steel is prone to excessive wheel wear and thermal damage defects, which seriously affects the service performance of parts. To solve the above-mentioned issue, a creep-feed grinding test was carried out on high-strength steel using SG and CBN abrasive wheels. The grindability of high-strength steel was scrutinized in terms of grinding force, machining temperature and grinding specific energy. Moreover, the effects of operation parameters and grinder performances on the surface integrity of the workpiece such as surface morphology, roughness, residual stress and hardness were rigorously studied. The results indicate that, when the instantaneous high temperature in the grinding area reaches above the phase transition temperature of the steel, the local organization of the surface layer changes, leading to thermal damage defects in the components. The outstanding hardness and thermal conductivity of CBN abrasives are more productive in suppressing grinding burns than the high self-sharpening properties of SG grits and a more favorable machining response is achieved. The effects of thermal damage on the surface integrity of high-strength steel grinding are mainly in the form of oxidative discoloration, coating texture, hardness reduction and residual tensile stresses. Within the parameter range of this experiment, CBN grinding wheel reduces grinding specific energy by about 33% compared to SG grinding wheel and can control surface roughness below 0.8 µm. The weight of oxygen element in the burn-out workpiece accounts for 21%, and the thickness of the metamorphic layer is about 40 µm. The essential means of achieving burn-free grinding of high-strength steels is to reduce heat generation and enhance heat evacuation. The results obtained can provide technical guidance for high-quality processing of high-strength steel and precision manufacturing of high-end components. Full article

Minimizing the sintering time while ensuring high performances is an important optimization step for the preparation of magnetocaloric or thermomagnetic materials produced by powder metallurgy. Here, we study the influence of sintering time on the properties of a Mn_0.95Fe₁P_0.56Si_0.39B_0.05 compound. In contrast to former reports investigating different annealing temperatures during heat treatments of several hours or days, we pay special attention to the earliest stages of sintering. After ball-milling and powder compaction, 2 min sintering at 1100 °C is found sufficient to form the desired Fe₂P-type phase. Increasing the sintering time leads to a sharper first-order magnetic transition, a stronger latent heat, and usually to a larger isothermal entropy change, though not in all cases. As demonstrated by DSC or magnetization measurements, these parameters present dissimilar time evolutions, highlighting the existence of various underlying mechanisms. Chemical inhomogeneities are likely responsible for broadened transitions for the shortest sinterings. The development of strong latent heat requires longer sinterings than those for sharpening the magnetic transition. The microstructure may play a role as the average grain size progressively increases with the sintering time from 3.5 μm (2 min) to 30.1 μm (100 h). This systematic study has practical consequences for optimizing the preparation of MnFe(P,Si,B) compounds, but also raises intriguing questions on the influence of the microstructure and of the chemical homogeneity on magnetocaloric or thermomagnetic performances. Full article

Reasonable evaluation of evapotranspiration (ET) is crucial for optimizing agricultural water resource management. In the study, we utilized the Data Mining Sharpener (DMS) model; the Landsat thermal infrared images were sharpened from a spatial resolution of 100 m to 30 m. We then used the Surface Energy Balance System (SEBS) to estimate daily ET during the winter wheat growing season in the People’s Victory Irrigation District in Henan, China. It was concluded that the spatiotemporal patterns of land surface temperature and daily evapotranspiration remained consistent before and after sharpening. Results showed that the R² value between the ET of 30 m spatial resolution and the value by eddy covariance method reached 0.814, with an RMSE of 0.516 mm and an MAE of 0.245 mm. All of these were higher than those of 100 m spatial resolution (R² was 0.802, the RMSE was 0.534 mm, and the MAE was 0.253 mm). Furthermore, the daily ET image with a 30 m spatial resolution exhibited clear texture and distinct boundaries, without any noticeable mosaic effects. The changes in surface temperature and ET were more consistent in complex subsurface environments. The daily evapotranspiration of winter wheat was significantly higher in areas with intricate drainage systems compared to other regions. During the early growth stage, daily evapotranspiration decreased steadily until the overwintering stage. After the greening and jointing stages, it began to increase and peaked during the sizing period. The correlation between net solar radiation and temperature with ET was significant, while relative humidity and soil moisture were negatively correlated with ET. Throughout the growth period, net solar radiation had the greatest effect on ET. Full article

Surface urban heat islands (SUHIs) are mostly an urban ecological issue. There is a growing demand for the quantification of the SUHI effect, and for its optimization to mitigate the increasing possible hazards caused by SUHI. Satellite-derived land surface temperature (LST) is an important indicator for quantifying SUHIs with frequent coverage. Current LST data with high spatiotemporal resolution is still lacking due to no single satellite sensor that can resolve the trade-off between spatial and temporal resolutions and this greatly limits its applications. To address this issue, we propose a multiscale geographically weighted regression (MGWR) coupling the comprehensive, flexible, spatiotemporal data fusion (CFSDAF) method to generate a high-spatiotemporal-resolution LST dataset. We then analyzed the SUHI intensity (SUHII) in Chengdu City, a typical cloudy and rainy city in China, from 2002 to 2022. Finally, we selected thirteen potential driving factors of SUHIs and analyzed the relation between these thirteen influential drivers and SUHIIs. Results show that: (1) an MGWR outperforms classic methods for downscaling LST, namely geographically weighted regression (GWR) and thermal image sharpening (TsHARP); (2) compared to classic spatiotemporal fusion methods, our method produces more accurate predicted LST images (R², RMSE, AAD values were in the range of 0.8103 to 0.9476, 1.0601 to 1.4974, 0.8455 to 1.3380); (3) the average summer daytime SUHII increased form 2.08 °C (suburban area as 50% of the urban area) and 2.32 °C (suburban area as 100% of the urban area) in 2002 to 4.93 °C and 5.07 °C, respectively, in 2022 over Chengdu City; and (4) the anthropogenic activity drivers have a higher relative influence on SUHII than other drivers. Therefore, anthropogenic activity driving factors should be considered with CO₂ emissions and land use changes for urban planning to mitigate the SUHI effect. Full article

Climate change is widely acknowledged as the paramount global challenge of the 21st century, bringing economic, social, and environmental impacts due to rising global temperatures, more frequent extreme weather events, and ecosystem disturbances. To combat this, many countries target net-zero carbon emissions by 2050, reshaping both the financial system and consumption patterns. This transition has sharpened the financial sector’s focus on climate-related risks, making the carbon footprint, environmental benefits of investments, and sustainability of financial products critical to investors’ decisions. However, conventional risk prediction methods may not fully capture these climate-associated risks in a carbon-neutral setting. Emerging from this context is the need for innovative predictive tools. Recently, Long Short-Term Memory networks (LSTM) have gained prominence for their efficacy in time-series forecasting. Singular Spectrum Analysis (SSA), effective for extracting time series patterns, combined with LSTM as SSA-LSTM, offers a potentially superior approach to financial risk prediction. Our study, focusing on a case study of the wind energy sector in China, situates itself within the growing body of research focusing on the integration of environmental sustainability and financial risk management. Leveraging the capabilities of SSA-LSTM, we aim to bridge the gap in the current literature by offering a nuanced approach to financial risk prediction in the carbon-neutral landscape. This research not only reveals the superiority of the SSA-LSTM model over traditional methods but also contributes a robust framework to the existing discourse, facilitating a more comprehensive understanding and management of financial risks in the evolving carbon-neutral global trend. Full article