Search Results (1,473)

Metal–organic frameworks (MOFs) have become a hot topic in various research fields nowadays. And MOF-derived metal oxides prepared by the sacrificial template method have been widely applied as catalysts for pollutant removal. Accordingly, we prepared a series of MOF-derived MnO_x catalysts with diverse morphologies (rod-like, flower-like, slab-like) via the pyrolysis of MOF precursors, and the as-prepared MnO_x catalysts demonstrated superior performance compared to the one prepared using the co-precipitation method. MnO_x-II, with a flower-like structure, exhibited excellent activity for formaldehyde (HCHO) catalytic ozonation at room temperature, reaching complete HCHO conversion at O₃/HCHO of 1.5 and more than 90% CO₂ selectivity at an O₃/HCHO ratio of 2.5. On the basis of various characterization methods, it was clarified that the enhanced catalytic performance of MnO_x-II benefited from its larger BET surface area, abundant oxygen vacancies, better redox ability at lower temperature, and more Lewis acid sites. The H₂O resistance and stability tests were also conducted. Furthermore, DFT calculations substantiated the enhanced adsorption of HCHO and O₃ on oxygen vacancies, while in–situ DRIFTS measurements elucidated the degradation pathway of HCHO during catalytic ozonation through detected intermediates. Full article

This study aims to overcome the limitations of conventional plunge tests for evaluating resistance temperature detector (RTD) response times under actual operating conditions, particularly in confined nuclear power plant piping. An in situ measurement device based on the loop current step response (LCSR) method was developed, with a conversion relationship to plunge test results established through numerical simulation and experimental validation. Investigations in a rotating water channel (over the flow velocity range of 0.2 to 0.6) confirmed excellent agreement in RTD response time, showing only 3.78% deviation between second-order-converted LCSR and plunge test measurements at 0.6 m/s. Both methods consistently revealed reduced RTD response times at higher flow velocities, with deviations consistently within ±10%, complying with nuclear instrumentation standards (NB/T 20069-2012). The LCSR method enables reliable in situ assessment while maintaining strong correlation with laboratory plunge tests. Full article

This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (R_ds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, addressing key limitations in current state-of-the-art (SOTA) methods. Traditional approaches rely on expensive data acquisition systems under controlled laboratory conditions, making them unsuitable for real-world applications due to component variability, time delay, and noise sensitivity. Furthermore, these methods lack cloud interfacing for real-time data analysis and fail to provide comprehensive reliability metrics such as Remaining Useful Life (RUL). Additionally, the proposed CM method benefits from noise mitigation during switching transitions by utilizing delay circuits to ensure stable and accurate data capture. Moreover, collected data are transmitted to the cloud for long-term health assessment and damage evaluation. In this paper, experimental validation follows a structured design involving signal acquisition, filtering, cloud transmission, and temperature and thermal degradation tracking. Experimental testing has been conducted at different temperatures and operating conditions, considering coolant temperature variations (40 °C to 80 °C), and an output power of 7 kW. Results have demonstrated a clear correlation between temperature rise and R_ds,on variations, validating the ability of the proposed method to predict device degradation. Finally, by leveraging cloud computing, this work provides a practical solution for real-world Wide Band Gap (WBG)-based PEC reliability and lifetime assessment. Full article

Relict fern species, confined to microhabitats with stable historical conditions, are especially vulnerable to climate change. The Alboran Arc hosts a unique relict fern flora, including Culcita macrocarpa, Diplazium caudatum, and Pteris incompleta, and functions as a major Pleistocene refuge. This study assesses the population trends and climate sensitivity of these species in Los Alcornocales Natural Park using annual abundance time series for a decade, empirical survival projections, and principal component analysis to identify key climatic drivers. Results reveal distinct climate response clusters among populations, though intra-specific variation highlights the importance of local conditions. Climate change is already impacting population viability, especially for P. incompleta, which shows high sensitivity to rising maximum temperatures and prolonged heatwaves. Climate-driven models forecast more severe declines than empirical ones, particularly for C. macrocarpa and P. incompleta, with the latter showing a projected collapse by the mid-century. In contrast, D. caudatum exhibits moderate vulnerability. Crucially, the divergence between models underscores the impact of conservation efforts: without reinforcement and reintroduction actions, projected declines would likely be more severe. These results project a decline in the populations of the studied ferns, highlighting the urgent need to continue implementing both in situ and ex situ conservation measures. Full article

Climate change has accelerated the retreat of Andean glaciers, with significant recent losses in the tropical Andes. This study evaluates the extinction of the Carihuairazo volcano glacier (Ecuador), quantifying its area from 1312.5 m² in September 2023 to 101.2 m² in January 2024, its thickness (from 2.5 m to 0.71 m), and its volume (from 2638.85 m³ to 457.18 m³), before its complete deglaciation in February 2024; this rapid melting and its small size classify it as a glacierette. Multivariate analyses (PCA and biclustering) were performed to correlate climatic variables (temperature, solar radiation, precipitation, relative humidity, vapor pressure, and wind) with glacier surface and thickness. The PCA explained 70.26% of the total variance, with Axis 1 (28.01%) associated with extreme thermal conditions (temperatures up to 8.18 °C and radiation up to 16.14 kJ m⁻² day⁻¹), which probably drove its disappearance. Likewise, Axis 2 (21.56%) was related to favorable hydric conditions (precipitation between 39 and 94 mm) during the initial phase of glacier monitoring. Biclustering identified three groups of variables: Group 1 (temperature, solar radiation, and vapor pressure) contributed most to deglaciation; Group 2 (precipitation, humidity) apparently benefited initial stability; and Group 3 (wind) played a secondary role. These results, validated through in situ measurements, provide scientific evidence of the disappearance of the Carihuairazo volcano glacier by February 2024. They also corroborate earlier projections that anticipated its extinction by the middle of this decade. The early disappearance of this glacier highlights the vulnerability of small tropical Andean glaciers and underscores the urgent need for water security strategies focused on management, adaptation, and resilience. Full article

Articulated arm coordinate measuring machines are designed for in situ use directly in manufacturing environments, enabling efficient dimensional control outside of climate-controlled laboratories. This study investigates the influence of ambient temperature variation on the accuracy of length measurements performed with the Hexagon Absolute Arm 8312. The experiment was carried out in a laboratory setting simulating typical shop floor conditions through controlled temperature changes in the range of approximately 20–31 °C. A calibrated steel gauge block was used as a reference standard, allowing separation of the influence of the measuring system from that of the measured object. The results showed that the gauge block length changed in line with the expected thermal expansion, while the articulated arm coordinate measuring machine exhibited only a minor residual thermal drift and stable performance. The experiment also revealed a constant measurement offset of approximately 22 µm, likely due to calibration deviation. As part of the study, an uncertainty budget was developed, taking into account all relevant sources of influence and enabling a more realistic estimation of accuracy under operational conditions. The study confirms that modern carbon composite articulated arm coordinate measuring machines with integrated compensation can maintain stable measurement behavior even under fluctuating temperatures in controlled environments. Full article

Dams play a vital role in securing water and electricity supplies for households and industry, and they contribute significantly to flood protection. Regular monitoring of dam deformations holds fundamental socio-economic and ecological importance. Traditionally, this has relied on time-consuming in situ techniques that offer either high spatial or temporal resolution. Persistent Scatterer Interferometry (PSI) addresses these limitations, enabling high-resolution monitoring in both domains. Sensors such as TerraSAR-X (TSX) and Sentinel-1 (S-1) have proven effective for deformation analysis with millimeter accuracy. Combining TSX and S-1 datasets enhances monitoring capabilities by leveraging the high spatial resolution of TSX with the broad coverage of S-1. This improves monitoring by increasing PS point density, reducing revisit intervals, and facilitating the detection of environmental deformation drivers. This study aims to investigate two objectives: first, we evaluate the benefits of a spatially and temporally densified PS time series derived from TSX and S-1 data for detecting radial deformations in individual dam segments. To support this, we developed the TSX2StaMPS toolbox, integrated into the updated snap2stamps workflow for generating single-master interferogram stacks using TSX data. Second, we identify deformation drivers using water level and temperature as exogenous variables. The five-year study period (2017–2022) was conducted on a gravity dam in North Rhine-Westphalia, Germany, which was divided into logically connected segments. The results were compared to in situ data obtained from pendulum measurements. Linear models demonstrated a fair agreement between the combined time series and the pendulum data ($R^2$ = 0.5; MAE = 2.3 mm). Temperature was identified as the primary long-term driver of periodic deformations of the gravity dam. Following the filling of the reservoir, the variance in the PS data increased from 0.9 mm to 3.9 mm in RMSE, suggesting that water level changes are more responsible for short-term variations in the SAR signal. Upon full impoundment, the mean deformation amplitude decreased by approximately 1.7 mm toward the downstream side of the dam, which was attributed to the higher water pressure. The last five meters of water level rise resulted in higher feature importance due to interaction effects with temperature. The study concludes that integrating multiple PS datasets for dam monitoring is beneficial particularly for dams where few PS points can be identified using one sensor or where pendulum systems are not installed. Identifying the drivers of deformation is feasible and can be incorporated into existing monitoring frameworks. Full article

A comparison of two synthesis methods for depositing Au nanoparticles onto TiO₂ was performed: (1) impregnation with HAuCl₄ followed by thermal treatment in argon, and (2) magnetron sputtering from a Au disc. The obtained materials were used for acetaldehyde decomposition in a high temperature reaction chamber and ch aracterised by UV-Vis/DR, XPS, XRD, SEM, and photoluminescence measurements. The process was carried out using an air/acetaldehyde gas flow under UV or UV-Vis LED irradiation. The mechanism of acetaldehyde decomposition and conversion was elaborated by in situ FTIR measurements of the photocatalyst surface during the reaction. Simultaneously, concentration of acetaldehyde in the outlet gas was monitored using gas chromatography. All the Au/TiO₂ samples showed absorption in the visible region, with a maximum around 550 nm. The plasmonic effect of Au nanoparticles was observed under UV-Vis light irradiation, especially at elevated temperatures such as 100 °C, for Au/TiO₂ prepared by the magnetron sputtering method. This resulted in a significant increase in the conversion of acetaldehyde at the beginning, followed by gradual decrease over time. The collected FTIR spectra indicated that, under UV-Vis light, acetaldehyde was strongly adsorbed onto Au/TiO₂ surface and formed crotonaldehyde or aldol. Under UV, acetaldehyde was mainly adsorbed in the form of acetate species. The plasmonic effect of Au nanoparticles increased the adsorption of acetaldehyde molecules onto TiO₂ surface, while reducing their decomposition rate. The increased temperature of the process enhanced the decomposition of the acetaldehyde. Full article

Acoustic tweezers, as advanced micro/nano manipulation tools, play a pivotal role in biomedical engineering, microfluidics, and precision manufacturing. However, piezoelectric-based acoustic tweezers face performance limitations due to multi-physical coupling effects during microfabrication. This study proposes a novel approach using injection molding with embedded electronics (IMEs) technology to fabricate piezoelectric micro-ultrasonic transducers with micron-scale precision, addressing the critical issue of acoustic node displacement caused by thermal–mechanical coupling in injection molding—a problem that impairs wave transmission efficiency and operational stability. To optimize the IME process parameters, a hybrid multi-objective optimization framework integrating NSGA-II and MOPSO is developed, aiming to simultaneously minimize acoustic node displacement, volumetric shrinkage, and residual stress distribution. Key process variables—packing pressure (80–120 MPa), melt temperature (230–280 °C), and packing time (15–30 s)—are analyzed via finite element modeling (FEM) and validated through in situ tie bar elongation measurements. The results show a 27.3% reduction in node displacement amplitude and a 19.6% improvement in wave transmission uniformity compared to conventional methods. This methodology enhances acoustic tweezers’ operational stability and provides a generalizable framework for multi-physics optimization in MEMS manufacturing, laying a foundation for next-generation applications in single-cell manipulation, lab-on-a-chip systems, and nanomaterial assembly. Full article

The field of metal additive manufacturing has witnessed significant growth in recent years, with technology offering the ability to produce complex geometries that are challenging to manufacture using the traditional methods. In situ monitoring and control of the manufacturing process are crucial for increasing the production capacity and improving the quality of manufactured parts. This article provides a comparative analysis of computational, indirect, and direct methods for in situ temperature monitoring during additive manufacturing of metal alloy components. Furthermore, it discusses the current status, recent improvements, and perspectives for in situ temperature measurements. The basic principles of thermal imaging, two-color pyrometry, and millimeter-wave radiometry are explored, highlighting their limitations for addressing challenges related to material emissivity and rapid changes in building material composition. Overcoming the challenges related to the inaccessibility of the chamber where the parts are formed, direct temperature measurements would allow for the integration of collected information into big data systems. Within the framework of Industry 4.0, this approach offers a viable alternative to the conventional metal shaping processes, improving the production capacity and part quality. This research aims to contribute to ongoing advancements in metal additive manufacturing and its potential to completely replace traditional metal casting practices in the Industry 4.0 era. Full article

The continuous casting of Ti-Nb microalloyed steel was simulated with high temperature confocal laser scanning microscopy (HTCLSM). Evolution of the sample surface morphology was observed in-situ, during cooling conditions chosen to represent different locations in a cast slab. Calculations with a thermodynamics model of carbonitride precipitate formation agreed with the transmission electron microscopy (TEM) analysis that fine reliefs observed on the sample surface were actually caused by interior precipitation of (Ti,Nb)(C,N). Precipitation and the resulting reliefs changed with location beneath the slab surface, simulated casting speed, and steel composition. With the same casting speed and steel composition, reliefs in the simulated slab surface sample appeared earlier and were larger than in the slab center. With increased casting speed, reliefs were observed later and decreased in size. With increased titanium or niobium content, reliefs appeared earlier and increased in number. TEM measurement showed that the precipitate diameters were mainly smaller than 4 nm, with a few between 4 and 8 nm. The property of surface reliefs observed via HTCLSM correlated qualitatively with the number and size of internal precipitates measured with TEM, showing this to be an effective tool for indirectly characterizing nanoscale secondary phase precipitation inside the sample. Full article

Chlorophyll-a (Chla) and suspended particulate matter (SPM) are key indicators of water quality, playing critical roles in understanding marine biogeochemical processes and ecosystem health. Although satellite data from the Chinese Ocean Color and Temperature Scanner (COCTS) onboard the Haiyang-1C/D satellites is freely available, there has been limited validation of its standard Chla and SPM products. This study is a first step to address this gap by evaluating COCTS-derived Chla and SPM products against in situ measurements in French coastal waters. The matchup analysis showed robust performance for the Chla product, with a median symmetric accuracy (MSA) of 50.46% over a dynamic range of 0.13–4.31 mg·m⁻³ (n = 24, Bias = 41.11%, Slope = 0.93). In contrast, the SPM product showed significant limitations, particularly in turbid waters, despite a reasonable performance in the matchup exercise, with an MSA of 45.86% within a range of 0.18–10.52 g·m⁻³ (n = 23, Bias = −14.59%, Slope = 2.29). A comparison with another SPM model and Moderate Resolution Imaging Spectroradiometer (MODIS) products showed that the COCTS standard algorithm tends to overestimate SPM and suggests that the issue does not originate from the input radiometric data. This study provides the first regional assessment of COCTS Chla and SPM products in European coastal waters. The findings highlight the need for algorithm refinement to improve the reliability of COCTS SPM products, while the Chla product demonstrates suitability for water quality monitoring in low to moderate Chla concentrations. Future studies should focus on the validation of COCTS ocean color products in more diverse waters. Full article

Current temperature sensors require regular recalibration to maintain reliable temperature measurement. Photonic/quantum-based approaches have the potential to radically change the practice of thermometry through provision of in situ traceability, potentially through practical primary thermometry, without the need for sensor recalibration. This article gives an overview of the European Partnership in Metrology (EPM) project: Photonic and quantum sensors for practical integrated primary thermometry (PhoQuS-T), which aims to develop sensors based on photonic ring resonators and optomechanical resonators for robust, small-scale, integrated, and wide-range temperature measurement. The different phases of the project will be presented. The development of the integrated optical practical primary thermometer operating from 4 K to 500 K will be reached by a combination of different sensing techniques: with the optomechanical sensor, quantum thermometry below 10 K will provide a quantum reference for the optical noise thermometry (operating in the range 4 K to 300 K), whilst using the high-resolution photonic (ring resonator) sensor the temperature range to be extended from 80 K to 500 K. The important issues of robust fibre-to-chip coupling will be addressed, and application case studies of the developed sensors in ion-trap monitoring and quantum-based pressure standards will be discussed. Full article

We studied the adsorption thermodynamics and mechanism behind the binding of nitric oxide (NO) in the interior surfaces and structural fragments of the high metal center density microporous Metal-Organic Framework (MOF) CPO-27-Cu, by gas sorption, at a series of temperatures. For the purpose of comparison, we also measured the corresponding CO₂ adsorption isotherms, and as a result, the isosteric heats of adsorption for the two studied adsorptives were derived, being in the range of 12–15 kJ/mol for NO at loadings up to 0.5 NO molecules per formula unit (f.u.) of the bare compound (C₄O₃HCu), and 23–25 kJ/mol CO₂ in the range 0–1 CO₂ per f.u. Microscopically, the mode of NO binding near the square pyramid Cu(II) centers was directly accessed with the use of in situ NO gas adsorption X-ray Absorption Spectroscopy (XAS). Additionally, during the vacuum/temperature activation of the material and consequent NO adsorption, the electronic state of the Cu-species was monitored by observing the corresponding X-ray Near Edge Spectra (XANES). Contrary to the previously anticipated chemisorption mechanism for NO binding at Cu(II) species, we found that at slightly elevated temperatures, under ambient, but also cryogenic conditions, only relatively weak physisorption takes place, with no evidence for a particular adsorption preference to the coordinatively unsaturated Cu-centers of the material. Full article

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, dense networks of in situ measurements offer more precise data at the street scale. In this work, the Random Forest technique was used to predict street-scale temperatures in the downtown area of Thessaloniki, Greece, during a prolonged heatwave in July 2021. The model was trained using data from a low-cost sensor network, meteorological fields calculated by the mesoscale model MEMO, and micro-environmental spatial features. The results show that, although the MEMO temperature predictions achieve high accuracy during nighttime compared to measurements, they exhibit inconsistent trends across sensor locations during daytime, indicating that the model does not fully account for microclimatic phenomena. Additionally, by using only the observed temperature as the target of the Random Forest model, higher accuracy is achieved, but spatial features are not represented in the predictions. In contrast, the most reliable approach to incorporating spatial characteristics is to use the difference between observed and mesoscale temperatures as the target variable. Full article