Surface Concentration Research Articles

(Fe, N)-Doped Carbon Black Catalysts for Oxygen Reduction Reaction Applied to Gas-Diffusion Electrodes

Introduction Addressing the sluggish kinetics of the oxygen reduction reaction (ORR) in metal-air secondary batteries is crucial for practical applications. (Fe, N)-doped carbon-based catalysts (FeNC) have shown promise in enhancing the ORR activity. However, their conventional production process involves high temperatures and prolonged annealing, which leads to significant weight loss of the carbon matrix, defect healing, and active site embedding, thus reducing their efficacy [1,2]. This study employs a rapid thermal annealing (RTA) method to synthesize FeNC catalysts, overcoming these challenges and demonstrating improved ORR activity. Furthermore, this research applied these catalysts to gas diffusion electrodes (GDEs) in the alkaline solutions by integrating binders and employing thermal pressing, achieving highly active ORR activity and durability. Experimental The FeNC were synthesized via the RTA method in an NH3/Ar atmosphere using acid-treated carbon black and FeCl3 powder. The ORR activity was evaluated by the linear sweep voltammetry with a rotating ring-disk electrode (RRDE). GDEs were prepared by cold-pressing hydrophobic carbon paper with a mixed catalyst layer of FeNC and PTFE under 20 kg/cm2 pressure, then hot-pressed at 340°C under 40 kg/cm2 pressure. Electrochemical measurements were performed using a three-electrode cell in an 8 mol dm–3 KOH solution, consisting of a gas chamber, reference electrode chamber, and counter electrode chamber. The X-ray photoelectron spectroscopy (XPS) was utilized to analyze the element concentration of the carbon black-based catalyst surface. The laser Raman spectrometer was used to examine the structure defectiveness. Results and Discussion In this study, we explored the temperature dependence of the (Fe, N)-doped carbon black catalyst. This was achieved by directly heating the catalysts loaded on the surface of electrodes, resulting in highly active ORR activity. Subsequently, to apply this catalyst to a gas diffusion electrode, the method of directly heating an amount of powder was adopted to scale up the production. The obtained FeNC catalyst exhibited significantly high ORR activity in alkaline solutions, with an onset potential of 1.1 V vs. RHE in KOH. RRDE tests indicated that the FeNC catalyst facilitates a four-electron process, directly reducing oxygen to hydroxide ions. The intensity of disordered carbon relative to that of graphitic carbon (I d/I g ratio) obtained from Raman spectroscopy, representing the degree of defects on the surface of carbon materials, was 2.35 for the FeNC powder heated at 900°C, which is higher than that of the original carbon black (2.03). The XPS results showed that the N/C% of the sample annealed at 900°C was 4.9%, and the Fe/C% was 1.5%, which exhibited a higher doping level than the traditional long-time annealing sample [3]. These characteristics make them promising for use in metal-air batteries. In the GDE preparation process, polytetrafluoroethylene (PTFE) integration with hot pressing is generally employed to control the hydrophobicity to effectively prevent carbon loss in KOH solutions. In this study, we examined the effects of PTFE content and hot-pressing duration on the performance of ORR catalysts. We found that higher concentrations of PTFE led to the encapsulation of catalytic sites, while lower concentrations decreased hydrophobicity and failed to adequately bind the ORR catalysts. Similarly, prolonged hot-pressing times resulted in fragmentation of the catalyst films, while insufficient time led to uneven melting of PTFE. As a result, the mixture of 83wt% FeNC powder annealed at 900°C and 17wt% PTFE, subjected to a 10-minute hot press (called FeNC-10hp-17%) achieved a balance. The performances of samples prepared under other conditions will be shown in the meeting. Figure 1 displays the durability of the FeNC catalyst, revealing a marginal decline in activity at the low current density region and a slight increase at the high current density region after 25 cycles (5000 minutes), indicating the overall stability of the catalyst. Ongoing stability assessments suggest that the FeNC catalyst may exhibit further potential for enhanced durability. These findings offer a promising solution to expedite the practical utilization of metal-air secondary batteries.

XAS and XPS Analysis on Surface Reconstruction By Chemical Treatment of Ba0.5Sr0.5Co0.8Fe0.2O3

Alkaline water electrolysis is expected to play a vital role in hydrogen production systems using renewable electricity. However, the intermittent nature of renewable electricity can often cause electrolysis cells to shut down. Such interruptions result in reverse currents that accelerate catalyst degradation. Extensive studies of catalytic activity have elucidated that the oxygen evolution reaction (OER) is contingent on certain descriptors [1]. Recently, the focus has been placed on the surface structure of the catalysts, as the actual OER occurs on the catalyst surface [2]. Previous research has demonstrated that the surfaces of numerous oxide materials with high OER activity undergo surface reconstruction under OER, resulting in the formation of metal oxyhydroxide phases [3]. This surface reconstruction has been reported after OER experiments, although it is challenging to analyze large numbers of samples in this manner. In order to efficiently study and utilize the state of the catalyst surface for material design, a method is needed to induce the surface reconstruction through chemical treatments. Consequently, the present study examines the chemical state of the surface following chemical treatment of perovskite-type oxide Ba0.5Sr0.5Co0.8Fe0.2O3 (BSCF) by stirring in an alkaline solution, employing X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS). BSCF was synthesized using the sol-gel process. The as-prepared samples were subjected to stirring under four different conditions: in 1 M or 7 M KOH solutions with either oxygen or nitrogen bubbling for a duration of 21 hours. The structural and chemical properties were characterized using X-ray diffraction (XRD), XAS, and XPS. XAS measurements were conducted at the BL-2 and BL-11 beamlines of the Ritsumeikan University SR Center. Both total electron yield and partial fluorescence yield modes were employed. XRD analysis did not reveal any significant peak shifts or the formation of a second phase, indicating that the bulk structure of the samples remained unchanged. Comparative studies of the O K-edge XAS for both as-prepared and chemically treated BSCF samples in 7 M KOH with oxygen bubbling were conducted. The peak at approximately 530 eV is attributed to the transition from O 1s to the 3d orbitals of transition metals combined with O 2p. In the as-prepared sample, this peak exhibited low intensity. However, in the chemically treated sample, sharp peaks were observed at approximately 529 eV and 532 eV. These findings indicate that the surface of the perovskite-type oxide underwent a transformation to an oxyhydroxide of Co or Fe, as evidenced by the presence of peaks characteristic of transition metal oxyhydroxides. Despite these surface changes, the results from Co and Fe L-edge XAS showed no peak shifts, indicating that the valence states of Co and Fe remained unchanged. XPS analysis revealed a decrease in the surface concentrations of Ba and Sr. This work is based on results obtained from the project commissioned by the New Energy and Industrial Technology Development Organization (NEDO) of Japan. (JPNP 20003). [1] J. Suntivich, K. May, H. Gasteiger, J. Goodenough, and Y. Shao-Horn, Science, 334, 1383-1385 (2011). [2] I. C. Man, H. Su, F. Call-Vallejo, H. A. Hansen, J. I. Martínez, N. G. Inoglu, J. Kitchin, T. F. Jaramillo, J. K. Nørskov, and J. Rossmeisl, ChemCatChem, 3, 1159-1165 (2011). [3] E. Fabbri, M. Nachtegaal, T. Binninger, X. Cheng, B. Kim, J. Durst, F. Bozza, T. Graule, R. Schaublin, L.Wiles, M. Pertisi, N. Danilovic, K. E. Ayers, and T. J. Schmidt, Nat. Mater., 16, 925-934 (2017).

Quantitative Modelling of Residual Molecular Contamination in Low-Pressure Processing Environments

During the fabrication, micro-chips circuits are very sensitive to all kinds of contamination present in the environments fluid in contact with the wafers.A previous study [1] describes the issue of wafer molecular surface contamination as a result of exposure to clean room air. If needed clean room air can be purified to the desired level using appropriate chemical filters.A lot of state-of-the-art processing steps occur in low pressure environments, or so called vacuum cluster tools comprising a wafer handler equipped with different chambers. All of these chambers have a finite residual base pressure (typically on the order of 1 Pa).A major part of the residual gas may consist of rather harmless inert gas such as N2 or Ar. A fraction of the background ambient may consist of uncontrolled residual gas that could originate from different sources (e.g. desorption from reactor walls or wafer backside, back diffusion from vacuum pumps, )Such uncontrolled molecules could adhere to the wafer surface and leave some surface contaminants that can negatively impact the subsequent process step (e.g.).The current study quantitatively describes this issue.In a gas ambient the ideal gas law provides eq.1Where: C i is the volume concentration of impurity ih i : the fraction of the number of impurity molecules, i, over the total number of all molecules p is the total pressure of all residual gas. In the current study we assume the sticking coefficient to be 1. This is a safe worst-case scenario and also the scenario for the impurity molecules that stick the best and are thus most detrimental and of major concern.The thermal contamination build-up on the surface, si, is determined by the mean thermal velocity. The surface concentration of contaminant i building up on the surface, normalized to its volume concentration in the gas phase, is given by the average thermal bombardment velocity on the surface (= arrival velocity) multiplied with the exposure time. The thermal velocity is roughly independent of pressure and is primarily determined by the temperature and the mass of the molecules: for room temperature air it is as high as 500 m/s. this implies that molecules travel very fast. The normalized concentration is then given by eq.2This normalized concentration has the dimension of length (expressed in units of m).One can compare this length to the characteristic space available in the vacuum chamber perpendicular to the wafer surface. For most systems this is expected to be on the order of 1 to 10 cm.3 numerical examples are provided in Table I.These examples show that significant amounts of contamination (1e11 to 1e13 at/cm2) can readily build-up on the surface.As can be seen, on Figure 1 the normalized deposition reaches already 10 cm in as little 1 msec implying that all available contamination gas inside the reactor would have deposited on the wafer surface in only 1 msec.In real cases there is typically a continuous supply of impurity molecules to the gas phase (from desorption from other surfaces etc..) with the surface with the highest sticking coefficient ultimately collecting the most contaminants.Figure 1 shows the surface concentration of surface contamination normalized to the impurity volume concentration in the ambient as a function of time.References P.W. Mertens, ECSTransactions 92, p.237, (2019); Figure 1

Li+ Ionic Mass Transfer Accompanied with Electrodeposition of Li Metal in High Concentration Electrolyte

Li metal is a promising material for the negative electrode of next-generation secondary batteries because of very large capacity density. However, it is very difficult to keep uniformity of electrode morphology during repeating cycles. The charging reaction is corresponding to the electrodeposition of Li metal. Li metal forms dendrites very easily in the electrodeposition process. Dendrite is very typical non-uniform shape and causes the further current distribution to the electrode surface. The distribution accelerates the non-uniform electrodeposition, and then induces the short circuit phenomenon in the worst case. It is indispensable to understand the morphological variation and control the electrode surface shape during the charging and discharging of Li metal negative electrode for the realization of very high energy density batteries.In general, the electrodeposition of metals is strongly influenced by the ionic mass transfer in the vicinity of the electrode surface. The ionic mass transfer rate is related with the concentration overpotential and decrease of the surface concentration induces the increase the overpotential of the electrode reaction, and the depletion of metal ions become trigger of the dendrite formation. Our previous studies found the Li metal dendrite is induced without the depletion of Li+ ion at the electrode surface. Further, it is noteworthy that the morphology of Li metal dendrite has many kinds of shape. This specialty of Li metal is due to the surface layer called by “Solid Electrolyte Interphase (SEI)”. This layer is formed by the reaction between the Li metal and chemical species in the electrolyte solution. Therefore, it is dependent on the composition of the electrolytes. It is necessary to understand not only the ionic mass transfer but also the nature of SEI layer. In this study, Li+ ionic mass transfer rate was in-situ measured by holographic interferometry microscope and the characterization of SEI was conducted by cryo-STEM-EELS technique. High concentration electrolytes were utilized and current density dependence of surface concentrations, morphological variation, and the characteristics of SEI on the electrodeposited Li metal were discussed. We would like to report these details in the presentation on the day.

Harnessing Deep Eutectic Solvents for Regioselective Polar Additions to α, β Unsaturated Ketones and Aldehydes.

Advancing the use of air-sensitive polar organometallic Grignard and organolithium reagents under more environmentally benign conditions, here we report the addition of these reagents to α,β-unsaturated ketones and aldehydes using the deep eutectic solvent (DES) choline chloride (ChCl): glycerol (Gly) (1 : 2), under air. Reactions occur at room temperature within seconds with excellent regioselective control. Furthering understanding of how these C-C bond forming processes take place in these reaction media, we have explored the surface concentration of the organic substrate (chalcone) in DES using interfacial tension and neutron reflectivity measurements, finding that chalcone is concentrated at the DES-hydrocarbon interface compared to the bulk concentration, although the interfacial chalcone concentration is still relatively low in this system. The influence of aggregation of the organometallic reagent in the organic solvent employed has also been evaluated, revealing the importance of achieving a balance between activation (via de-aggregation) and stability (to avoid its decomposition in the DES). This DES approach has been successfully extended to double additions to α,β-unsaturated esters and for one pot sequential 1,4 and 1,2 additions to ketones, providing a new entry point to a range of tertiary-alcohols, minimising the use of organic solvents and avoiding intermediate time-consuming purification steps.

Classification of surface microdefects based on cluster analysis of diffuse light reflection sensor signal

Early detection of operational microdefects of protective coatings and corrosion damage is important for reliable and long-term operation of materials and structures. Corrosion damage in the early stages is almost impossible to detect by visual testing methods, given the microscopic size of such damage. Laboratory microscopes are unsuitable for field conditions. Flash meters provide an estimate of surface roughness, but do not provide a surface concentration of microdefects, especially when these defects are heterogeneous or polydisperse. A compact prismatic sensor of the angular characteristic of diffuse light reflection is proposed for the detection of microdefects and express diagnostics of surface quality. To increase the informativity of the sensor signal during measurements, the useful signal was calculated as the difference between the base values of the diffuse reflected signal for a surface without defects and the measured values for a surface with defects. The dependence of the signal distribution on the photoline on the geometry of the sensor was taken into account. The article considers the problem of classification by the average size of surface microdefects collected in submillimeter clusters, randomly placed on the surface of materials. The use of numerical methods for solving inverse problems requires large computing power and time, which is not always acceptable for field measurements. The dependence of solution stability on signal measurement errors and random locations of clusters of microdefects on the illuminated area of the investigated surface is important. An effective set of informative signal features is selected. The study explored the possibility of using alternative sets of informative parameters derived from the base set. It was proposed to determine the size of the defects based on the smoothness criteria of the contour signal of the diffuse light reflection sensor. To evaluate the characteristics of the spatial configuration of defects, the positions of the peaks of the signal distribution along the photoline, determined with subpixel accuracy, were used. The classification is made for the selected information features of the signals of the diffuse light reflection sensor. In particular, the number of local signal extrema together with the subpixel position of the global signal maximum produces well-separated clusters, even for randomly located defect aggregations.

Interpreting summertime hourly variation of NO2 columns with implications for geostationary satellite applications

Abstract. Accurate representation of the hourly variation in the NO2-column-to-surface relationship is essential for interpreting geostationary observations of NO2 columns. Previous research indicated inconsistencies in this hourly variation. This study employs the high-performance configuration of the GEOS-Chem model (GCHP) to analyze daytime hourly NO2 total columns and surface concentrations during summer. We use measurements from globally distributed Pandora sun photometers and aircraft observations over the United States. We correct Pandora total NO2 vertical columns for (1) hourly variations in effective temperature driven by vertically resolved contributions to the total column and (2) changes in local solar time along the Pandora line of sight. These corrections increase the total NO2 columns by 5–6 × 1014 molec. cm−2 at 09:00 and 18:00 across all sites. Fine-scale simulations from GHCP (∼12 km) reduce the normalized bias (NB) against Pandora total NO2 columns from 19 % to 10 % and against aircraft measurements from 25 % to 13 % in Maryland, Texas, and Colorado. Similar reductions are observed in NO2 columns over the eastern US (17 % to 9 %), the western US (22 % to 14 %), Europe (24 % to 15 %), and Asia (29 % to 21 %) when compared to 55 km simulations. Our analysis attributes the weaker hourly variability in the total NO2 column to (1) hourly variations in column effective temperature, (2) local solar time changes along the Pandora line of sight, and (3) differences in hourly NO2 variability from different atmospheric layers, with the lowest 500 m exhibiting greater variability, while the dominant residual column above 500 m exhibits weaker variability.

NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations

Abstract. We introduce NitroNet, a deep learning model for the prediction of tropospheric NO2 profiles from satellite column measurements. NitroNet is a neural network trained on synthetic NO2 profiles from the regional chemistry and transport model WRF-Chem, which was operated on a European domain for the month of May 2019. This WRF-Chem simulation was constrained by in situ and satellite measurements, which were used to optimize important simulation parameters (e.g. the boundary layer scheme). The NitroNet model receives NO2 vertical column densities (VCDs) from the TROPOspheric Monitoring Instrument (TROPOMI) and ancillary variables (meteorology, emissions, etc.) as input, from which it reproduces NO2 concentration profiles. Training of the neural network is conducted on a filtered dataset, meaning that NO2 profiles showing strong disagreement (>20 %) with colocated TROPOMI column measurements are discarded. We present a first evaluation of NitroNet over a variety of geographical and temporal domains (Europe, the US West Coast, India, and China) and different seasons. For this purpose, we validate the NO2 profiles predicted by NitroNet against satellite, in situ, and MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) measurements. The training data were previously validated against the same datasets. During summertime, NitroNet shows small biases and strong correlations with all three datasets: a bias of +6.7 % and R=0.95 for TROPOMI NO2 VCDs, a bias of −10.5 % and R=0.75 for AirBase surface concentrations, and a bias of −34.3 % to +99.6 % with R=0.83–0.99 for MAX-DOAS measurements. In comparison to TROPOMI satellite data, NitroNet even shows significantly lower errors and stronger correlation than a direct comparison with WRF-Chem numerical results. During wintertime considerable low biases arise because the summertime/late-spring training data are not fully representative of all atmospheric wintertime characteristics (e.g. longer NO2 lifetimes). Nonetheless, the wintertime performance of NitroNet is surprisingly good and comparable to that of classic regional chemistry and transport models. NitroNet can demonstrably be used outside the geographic and temporal domain of the training data with only slight performance reductions. What makes NitroNet unique when compared to similar existing deep learning models is the inclusion of synthetic model data, which offers important benefits: due to the lack of NO2 profile measurements, models trained on empirical datasets are limited to the prediction of surface concentrations learned from in situ measurements. NitroNet, however, can predict full tropospheric NO2 profiles. Furthermore, in situ measurements of NO2 are known to suffer from biases, often larger than +20 %, due to cross-sensitivities to photooxidants, which other models trained on empirical data inevitably reproduce.

Adsorption-catalytic synergistic Fenton degradation of potassium butyl xanthate in flotation tailing wastewater by renewable iron-loaded sludge: Performance, kinetics and mechanism

The renewable iron-loaded residual sludge heterogeneous catalyst (RLS-Fe) was prepared by impregnation-pyrolysis method and applied to the heterogeneous Fenton for the degradation of potassium butyl xanthate (BX-K) in flotation tailing wastewater. The rich pore structure and uniformly distributed iron oxides endowed the catalyst with excellent adsorption and catalytic capabilities. RLS-Fe exhibited maximum adsorption capacity of 86.47 mg/g, with surface concentration (Cs) of 2.88 mg/cm2 and surface coverage (θ) exceeding 80 %. The interaction of monolayer-adsorbed BX-K with catalytically generated ·OH facilitated the Fenton reaction and enhanced the adsorption process, making the degradation and mineralization of BX-K more efficient, with the removal rate of 99.82 % in 80 min. Through the synergistic effects of adsorption and catalytic processes, H2O2 was efficiently decomposed and effectively utilized. The ·OH generated in the initial stage rapidly degraded the adsorbed BX-K and released the adsorption sites, while the ·O2– produced subsequently targeted the catalytic sites and restored their activity. The Langmuir-Hinshelwood (L-H) kinetic model confirmed that the mutual promotion of adsorption and catalysis elevated the apparent reaction rate constant and accelerated the mineralization of BX-K. Additionally, density functional theory (DFT), Fukui indices and Gibbs free energy calculations were employed to analyze the intermediates and degradation pathways of BX-K. The −C=S– bond was identified as the primary target for ·OH attack. The RLS-Fe catalyst prepared in this study presented excellent stability and renewability, offering new insights for the streamlined preparation of renewable catalysts and efficient treatment of tailings wastewater.

Effect of ocean dynamic processes on the temporal-spatial pattern of persistent organic pollutants (PCB-153 and BDE-47) in the shelf seas

Field observations of persistent organic pollutants (POPs) in shelf seas presented abnormal phenomena such as high-concentration patches in offshore areas and different vertical profiles of POPs at the same location. We assumed that these phenomena were associated with the presence of bottom cold water mass (BCWM) in shelf seas and used a hydrodynamic-ecosystem-POP coupled model to confirm this hypothesis. Based on model results, with the formation of BCWM during summer, POPs accumulated inside BCWM due to their transport across the thermocline by the sorption to sinking particles. With the intensification of vertical mixing during winter, the release of POPs from BCWM induced high-concentration patches of POPs on the surface layer. Meanwhile, the low water temperature in winter was favorable for the gas deposition of POPs, which led to high surface concentrations of POPs. Because the accumulation of POPs in BCWM depended on the sorption of dissolved POPs by particles, not all types of POPs accumulated in BCWM. Some POPs even accumulated at the sea surface above the BCWM due to large gaseous deposition and weak sorption by particles. Using this feature, we proposed a prediction function for the accumulation of POPs in BCWM.

Treating Tropical Soils with Composted Sewage Sludge Reduces the Mineral Fertilizer Requirements in Sugarcane Production

Conventional mineral fertilization (CMF) is a common practice in infertile sugarcane-cultivated tropical soils, increasing production costs and environmental concerns. Combining CMF with composted sewage sludge (CSS) could be a sustainable strategy. We aim to evaluate changes in soil chemical properties, macro- and micronutrient concentrations in the soil surface (Ap1; 0–25 cm) and subsurface (Ap2; 25–50 cm) horizons, after CSS application with or without CMF in sugarcane cultivation (first and second ratoon cane). Eleven treatments, featured by CSS increase rates and mixed with CMF at different concentrations, were tested in the first ratoon; during the second, the CSS residual effect was evaluated. Applying CSS in sugarcane-cultivated soils, improved the following: (i) soil organic matter, pH, the sum of bases, cation-exchange capacity, and base saturation; (ii) overall nutrient concentrations (P, K, Ca, Mg, B, Cu, and Zn). The treatments showing the best performances were those with 5.0 Mg ha−1 of CSS. Composted sewage sludge has the potential for use as an organic natural fertilizer reducing the need for CMF. When applied in infertile tropical soils, additional positive effects can be achieved, such as decreasing production costs and providing socio-economic benefits.

Investigating the Impact of Varied C-Rates on Lithium-Ion Batteries: A 1D Simulation Study

Abstract With the advancement of powertrain technology and progressive vehicle electrification, one of the solutions for the growing need for energy storage is batteries. A secondary battery is a device that stores electrical energy in chemical form and delivers it as electrical energy when needed (discharging), with the possibility to revert the process converting electrical to chemical energy (charging). The lithium-ion battery type used in the study offers increased energy and power density with a cell voltage of approximately 3.6 V, making it suitable for use in portable electronic devices like mobile phones and laptops. In this research, a 1D model (through-electrolyte direction) of lithium-ion battery was analysed, in which the effect of different C-rates was investigated using the battery and design module of COMSOL Multiphysics software for 0.1C, 0.5C, 1C, 2C, and 3C rates, relevant for automotive applications. The simulation results of the lithium-ion battery model constitute an important step towards the development of battery technology, allowing an understanding of the transport processes in the electrodes and electrolyte. The results revealed that under higher C-rates of operation, differences emerge in electrolyte and electrode voltage ranges, salt concentration profiles in the electrolyte, surface and center electrode particle lithium concentrations.

Spatiotemporal estimation of surface NO2 concentrations in the Pearl River Delta region based on TROPOMI data and machine learning

Nitrogen dioxide (NO2) is a major air pollutant, and its concentration data are crucial for the study of air pollution and its impact on the environment. Although satellite data provide an effective method for estimating surface concentrations on a large scale through integrated modeling, the estimation of surface NO2 concentrations is hampered by the substantial amount of missing satellite data. This restricts in-depth studies of surface NO2 pollution. This study aims to reconstruct the missing data on tropospheric NO2 vertical column density from the TROPOspheric Monitoring Instrument (TROPOMI NO2). Subsequently, the reconstructed TROPOMI NO2 data and other predictor variables were utilized to estimate the daily surface NO2 concentrations at a 1 km resolution for the Pearl River Delta (PRD) region. The TROPOMI NO2 reconstruction models and the surface NO2 estimation model were both developed using the Extreme Gradient Boosting (XGBoost) algorithm. Additionally, comparative experiments were conducted between the XGBoost model and other traditional machine learning models, and the performances of the XGBoost model were evaluated through 10-fold cross-validation (CV) sample-based and site-based evaluations. The results indicate that the sample-based and site-based CV R2 values were 0.873 and 0.709, respectively. The feature importance scores indicate that TROPOMI NO2 was the most significant variable contributing to the estimation model. This indicates that the reconstruction of TROPOMI NO2 data and the development of an XGBoost model are suitable for the spatiotemporal estimation of surface NO2 concentrations in the PRD region, effectively reflecting the spatiotemporal distribution and evolution of surface NO2 concentrations in the area.

Cooperative adsorbate binding catalyzes high-temperature hydrogen oxidation on palladium.

Atomic-scale structures that account for the acceleration of reactivity by heterogeneous catalysts often form only under reaction conditions of high temperatures and pressures, making them impossible to observe with low-temperature, ultra-high-vacuum methods. We present velocity-resolved kinetics measurements for catalytic hydrogen oxidation on palladium over a wide range of surface concentrations and at high temperatures. The rates exhibit a complex dependence on oxygen coverage and step density, which can be quantitatively explained by a density functional and transition-state theory-based kinetic model involving a cooperatively stabilized configuration of at least three oxygen atoms at steps. Here, two oxygen atoms recruit a third oxygen atom to a nearby binding site to produce an active configuration that is far more reactive than isolated oxygen atoms. Thus, hydrogen oxidation on palladium provides a clear example of how reactivity can be enhanced on a working catalyst.

Dissolved Nitrous Oxide and Methane in the Taiwan Strait: Distribution, Seasonal Variation, and Emission

AbstractThe global ocean plays an important role in the overall budgets of nitrous oxide (N2O) and methane (CH4), especially in continental estuaries and shelf areas. Four cruises were conducted between 2021 and 2022, covering the spring, summer, and fall seasons, to study the spatial and seasonal characteristics of N2O and CH4 distributions and emissions in the Taiwan Strait (TWS). The surface N2O and CH4 concentrations gradually decreased from the coast to the open sea, with maximum values (14.3 and 15.6 nmol L−1) occurring near the Jiulong and Minjiang estuaries, respectively. The mean surface N2O concentration (8.2 nmol L−1) was highest in the spring and approximately the same in the summer as in the fall. The mean surface concentrations of CH4 (8.8 nmol L−1) were greater in summer than in spring and fall, probably because of the high freshwater input in summer. Except for several stations in fall, surface waters were oversaturated with N2O and CH4 relative to the atmosphere in other seasons, and the TWS was a net source of atmospheric N2O and CH4 in the spring, summer, and fall. In situ production is the main source of N2O and CH4 in the TWS, with nitrification being the dominant mechanism of N2O production in the TWS. In contrast, physical influences (riverine inputs and water mass mixing) reshape the distributions of N2O and CH4. The annual emissions of N2O and CH4 from the TWS were estimated to be 0.9 × 10−3 ± 2.9 × 10−3 Tg yr−1 and 1.6 × 10−3 ± 3.0 × 10−3 Tg yr−1, respectively. Taken together, the TWS accounts for 0.025% of the surface area of the world's oceans and 0.022% ± 0.07% and 0.017% ± 0.033% of global oceanic N2O and CH4 emissions, respectively.

Unveiling the importance of controllable growth of c-axis oriented Sn-doped ZnO nanorod arrays: towards humidity sensing applications

In this study, tin (Sn)-doped zinc oxide (ZnO) nanorod arrays (SZO) were prepared using a sonication assisted sol-gel immersion method, with the growth of the nanorod arrays controlled by varying the immersion time in the precursor material. Morphology images taken using a Field Emission Scanning Electron Microscope (FESEM) demonstrated an enlargement of the average diameter of the nanorod arrays from 55 nm at 5 min immersion to 122 nm at 200 min immersion. The cross-sectional and surface elemental analysis showed that the sample immersed for 60 min has the highest detection of Sn, with a bulk concentration of 1.8 at.% and surface concentration of 1 at.%. Interestingly, we noticed that Sn is not exist on the surface of 200 min immersion, indicating the depletion of the Sn precursor due to the prolongation of the immersion time. From the current voltage (I-V) analysis, 60 min immersion sample generated the lowest thin film resistivity, which engendered the best humidity sensitivity of 4.05. This study demonstrated the significant importance of optimizing the immersion or growth time for doped 1-D nanostructures to obtain the best humidity sensing performance.

An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity

Abstract. The atmospheric composition forecasting system used to produce the Copernicus Atmosphere Monitoring Service (CAMS) forecasts of global aerosol and trace gas distributions, the Integrated Forecasting System (IFS-COMPO), undergoes periodic upgrades. In this study we describe the development of the future operational cycle 49R1 and focus on the implementation of the thermodynamical model EQSAM4Clim version 12, which represents gas–aerosol partitioning processes for the nitric acid–nitrate and ammonia–ammonium couples and computes diagnostic aerosol, cloud, and precipitation pH values at the global scale. This information on aerosol acidity influences the simulated tropospheric chemistry processes associated with aqueous-phase chemistry and wet deposition. The other updates of cycle 49R1 concern wet deposition, sea-salt aerosol emissions, dust optics, and size distribution used for the calculation of sulfate aerosol optics. The implementation of EQSAM4Clim significantly improves the partitioning of reactive nitrogen compounds, decreasing surface concentrations of both nitrate and ammonium in the particulate phase, which reduces PM2.5 biases for Europe, the US, and China, especially during summertime. For aerosol optical depth there is generally a decrease in the simulated wintertime biases and for some regions an increase in the summertime bias. Improvements in the simulated Ångström exponent are noted for almost all regions, resulting in generally good agreement with observations. The diagnostic aerosol and precipitation pH calculated by EQSAM4Clim have been compared to ground observations and published simulation results. For precipitation pH, the annual mean values show relatively good agreement with the regional observational datasets, while for aerosol pH the simulated values over continents are quite close to those simulated by ISORROPIA II. The use of aerosol acidity has a relatively smaller impact on the aqueous-phase production of sulfate compared to the changes in gas-to-particle partitioning induced by the use of EQSAM4Clim.

Boosting the Formation of Brønsted Acids on Flame-made WOx/ZrO2 for Glucose Conversion.

WOx/ZrO2with ahigher concentrationof Brønsted acid sites (BAS) and a bigger ratio of Brønsted to Lewis acid sites (B/L) than achievable by conventional impregnation (IM)were synthesized usingflame spray pyrolysis (FSP). The rapid quenching and short residence time inherent to FSP prevent the accumulation of W atoms on the ZrO2 support and thus provide an excellent surface dispersion of WOx species. As a result, FSP-made WOx/ZrO2 (FSP-WOx/ZrO2) has a much higher surface concentration of three-dimensional Zr-WOx clusters than corresponding materials prepared by conventional impregnation (IM-WOx/ZrO2). The coordination of W-OH to the unsaturated Zr4+ sites in these clusters results in a remarkable decrease of the concentration of Lewis acid sites (LAS) on the surface of ZrO2 and promotes the formation of bridging W-O(H)-Zr hydroxyl groups acting as BAS. FSP-WOx/ZrO2 possesses ~80% of BAS and a B/L ratio of around 4, while IM-WOx/ZrO2 exhibits ~50% BAS and a B/L ratio of around 1. These catalysts were evaluated in the dehydration of glucose to HMF. The catalytic study demonstrated that B/L ratio plays a crucial role in glucose conversion. The best catalyst, FSP-WOx/ZrO2 with a W/Zr ratio of 1/10 affords nearly 100% glucose conversion and an HMF selectivity of 56-69%.

Influence of irradiation wavelength during laser-assisted doping of 4H-silicon carbide in liquid phase

Laser-assisted doping of silicon carbide (SiC) substrates is challenging due to the low diffusion coefficient of dopant atoms and the chemically inert nature of SiC. Single crystal intrinsic 4H-SiC substrate is irradiated with neodymium-doped yttrium aluminium garnet (Nd3+):YAG laser with wavelengths of 1064, 355 and 266 nm, and krypton fluoride (KrF) excimer laser with the wavelength of 248 nm under liquid phase dopant sources. Different liquid solutions were used as dopant sources for aluminium (Al) and phosphorus (P). SiC was transparent to 1064 and 355 nm due to low absorption coefficients, while 266 and 248 nm showed better coupling due to higher absorption coefficients and led to the diffusion of atoms. The electrical resistance of the substrates was measured to be lower than 1000 kΩ after diffusion. Dispersive X-ray spectroscopy (EDS) studies showed that both laser wavelengths of 248 nm and 266 nm resulted in doping of Al and P, with the surface concentrations ranging from 0.5 to 1.5 at.% and from 0.24 to 0.6 at.%, respectively. Two-dimensional thermo-temporal simulation of the laser pulse interaction in the liquid phase revealed that unlike in air, during irradiation with 266 nm laser under liquid, the surface temperature of the substrate was slightly lower. However, the subsurface temperature increased along the depth by a few microns. Similarly, simulation studies with longer pulse irradiation also show that high temperature was maintained for a longer time, indicating improved dopant diffusion into the 4H-SiC substrate.

Simulated Surface‐Column NO2 Connections for Satellite Applications

AbstractObservations of near‐surface NO2 show a diurnal pattern with midday minima and daily maxima in the morning and evening. These surface cycles are dependent on chemical processing, transport, and emissions. We evaluate these cycles with the United States Environmental Protection Agency (EPA) community multiscale air quality (CMAQ) model data from the EPA Air Quality Time Series (EQUATES) project, compared with ground‐based measurements from the EPA air quality system, two Pandora measurement sites, and satellite data from TROPOMI. We find that the morning vertical column density (VCD) lags surface concentrations by 1 hr on average, where this lag varies with location and day. The peak VCD can also lead the surface maximum concentration, especially in the evening, responding to transport and afternoon compression of the boundary layer. Modeled NO2 VCD is sensitive to column calculation technique. With hourly daytime satellite‐based NO2 observations newly available from the TEMPO instrument, the timing and magnitude of cycles in near‐surface NO2 versus column NO2 will help inform the utilization of hourly satellite data. This work will help inform the timing of surface‐column connections to better interpret new hourly satellite observations for health and air quality applications, including emissions characterization.