Surface Concentration Research Articles

Synthesis of Gold Nanoparticles over CoAl Mixed Oxide for Ethanol Oxidation Reaction

Catalytic total oxidation is an effective technique for the treatment of industrial VOCs principally resulting from industrial processes using solvents and usually containing mono-aromatics (BTEX) and oxygenated compounds (acetone, ethanol, butanone). The aim of this work is to deposit gold nanoparticles on CoAl mixed oxide issued from layered double hydroxide (LDH) precursor by using the deposition precipitation (DP) method, which is applied with two modifications, labeled method (A) and method (B), in order to enhance the interaction of the HAuCl4 precursor with the support. Method (A) involves the hydrolysis of the HAuCl4 precursor after addition of the support, while in method (B), the gold precursor is hydrolyzed before adding the support. The two methods were applied using as support the CoAl mixed oxide and the LDH precursor. Samples were characterized by several physical chemical techniques and evaluated for ethanol total oxidation. Method (B) allowed the ethanol oxidation activity to be enhanced for the resulting Au/CoAlOx catalysts thanks to the high surface concentration of Co2+ and improved reducibility at low temperature. The presence of gold permits to minimize the formation of by-products, notably, methanol, allowed for a total oxidation of ethanol at lower temperature than the corresponding support.

Speleothem-Inspired Copper/Nickel Interfaces for Enhanced Liquid-Vapor Transport by Marangoni and Soret Effects.

Geological formations have superior wickability and support the absorption of water and oils into narrow spaces of Earth's crust without external assistance. In this study, we present speleothem inspired heterogeneous porous and wicked copper (Cu)/nickel (Ni) interfaces for enhanced nucleate boiling of water/ethanol mixtures for energy-efficient separation processes. The incorporation of Ni strands within the copper particle matrix significantly enhanced heat transfer. Compared to plain copper, the Cu/Ni speleothem surfaces exhibited a 61% increase in the heat transfer coefficient for water/ethanol mixtures and a 332% increase for water, with a 58% faster onset of nucleate boiling. This enhancement was attributed to Marangoni and Soret effects at the Cu/Ni interfaces, driven by surface tension and concentration gradients. Furthermore, the synergistic wicking action of the Ni strands facilitated rewetting of the surface, replenishing liquid to the porous nucleation sites and preventing surface dry-out, thereby improving the overall heat transfer performance.

Spatial distribution and environmental/biological co-regulation mechanism of dimethyl sulfur compounds in the eastern Indian Ocean

Dimethyl sulfur compounds including dimethylsulfoniopropionate (DMSP), dimethyl sulfide (DMS), and dimethyl sulfoxide (DMSO), play a crucial part in global sulfur cycling. The eastern Indian Ocean (EIO), characterized by its remarkable diversity of biomes and climate dynamics, is integral to global climate regulation. However, the regulation mechanism of DMS (P, O) in the EIO remains to be elucidated in detail. This paper presented a field survey aimed at investigating the spatial distribution of DMS (P, O) and their relationships with environmental and biological factors in the EIO. The surface concentrations of DMS, DMSPt, and DMSOt varied from 0.07 to 7.37 nmol/L, 0.14 to 9.17 nmol/L, and 0.15 to 3.32 nmol/L, respectively, and their distributions are attributed to high Chl-a concentration near Sri Lanka and the influence of ocean currents (Wyrtki jets, Bay of Bengal runoff). Higher concentrations of DMS (P) and DMSOt were predominantly observed in water columns shallower than 75m and deeper than 75m deep, respectively. The monthly DMS fluxes in the study area peaked in August. Temperature and Dissolved Silica Index (DSI) were the key environmental determinants for DMS distribution, while nitrate (NO3-) was the primary factor for both DMSPt and DMSOt. In terms of biological factors, Prochlorococcus and Synechococcus were significant contributors to DMS (P, O) dynamics. Synechococcus was the dominant influence on the DMS source and DMSPt sink, whereas Prochlorococcus primarily consumed DMSOt. Furthermore, the structural equation modeling (SEM) revealed the relationship between DMS, DMSPt, DMSOt, and the key environmental/biological factors, as well as among them, and together they formed a co-regulatory network in the EIO. This contributes significantly to the advancement of global ecosystem models for DMS (P, O).

Dehydration of Methanol to Dimethyl Ether—Current State and Perspectives

The main groups of catalytic materials used in the conversion of methanol to dimethyl ether (the MTD process) were presented with respect to their advantages, disadvantages, and the methods of their modifications, resulting in catalysts with improved activity, selectivity, and stability. In particular, the effects of strength, surface concentration, and the type of acid sites, the porous structure and morphology of the catalytic materials, the role of catalyst activators, and others, were considered. The prosed mechanisms of the MTD process over various types of catalysts are presented. Moreover, the advantages of membrane reactors for the MTD process are presented and analysed. The perspectives in the development of effective catalysts for the dehydration of methanol to dimethyl ether are presented and discussed.

Slow biological microplastics removal under ocean pollution phase-out trajectories

Abstract Microplastics are ubiquitous in marine environments and can be incorporated into biological aggregates including marine snows and faecal pellets. These aggregates are suspected to be a major removal mechanism for microplastics from the surface ocean, transporting them to deeper levels and the seafloor as they sink and remineralise. However, simple budget calculations, observations, and model parameter testing suggest that aggregation might also lead to retention of microplastics in the upper ocean, sustaining contamination in biologically-productive environments. The ability of the biological microplastic sink to reduce water column contamination has relevance to the setting of ocean plastics pollution reduction targets, as are currently under negotiation by the International Negotiating Committee of the United Nations Environment Assembly (UNEA). Here we apply 8 idealised global pollution reduction trajectories, from 1-100% per year, starting from the year 2026 and ending in the year 2100 to an Earth System Climate Model with a representation of ocean microplastics and their aggregation in biological particles. We find that the global ocean microplastic inventory and surface concentrations stabilize within this century for reduction rates exceeding 5% per year but the inventory does not substantially decrease under any trajectory. Furthermore, microplastics are retained by marine biology in the surface ocean, where concentrations stabilise to a non-zero value over decades. Lastly we find that irrespective of scenario, contamination of deeper ocean layers continues to increase for the duration of our simulations via the export of microplastics by biological aggregates. These results suggest that ambitious targets for pollution reduction exceeding 5\% per year will be required to progress the resolution of the UNEA to ``end plastic pollution'' in this century, and that ongoing microplastic contamination of the marine food web may be unavoidable.

Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model

Abstract. Emissions of anthropogenic aerosol and their precursors are often prescribed in global aerosol models. Most of these emissions are spatially heterogeneous at model grid scales. When remapped from low-resolution data, the spatial heterogeneity in emissions can be lost, leading to large errors in the simulation. It can also cause the conservation problem if non-conservative remapping is used. The default anthropogenic emission treatment in the Energy Exascale Earth System Model (E3SM) is subject to both problems. In this study, we introduce a revised emission treatment for the E3SM Atmosphere Model (EAM) that ensures conservation of mass fluxes and preserves the original emission heterogeneity at the model-resolved grid scale. We assess the error estimates associated with the default emission treatment and the impact of improved heterogeneity and mass conservation in both globally uniform standard-resolution (∼ 165 km) and regionally refined high-resolution (∼ 42 km) simulations. The default treatment incurs significant errors near the surface, particularly over sharp emission gradient zones. Much larger errors are observed in high-resolution simulations. It substantially underestimates the aerosol burden, surface concentration, and aerosol sources over highly polluted regions, while it overestimates these quantities over less-polluted adjacent areas. Large errors can persist at higher elevation for daily mean estimates, which can affect aerosol extinction profiles and aerosol optical depth (AOD). We find that the revised treatment significantly improves the accuracy of the aerosol emissions from surface and elevated sources near sharp spatial gradient regions, with significant improvement in the spatial heterogeneity and variability of simulated surface concentration in high-resolution simulations. In the next-generation E3SM running at convection-permitting scales where the resolved spatial heterogeneity is significantly increased, the revised emission treatment is expected to better represent the aerosol emissions as well as their lifecycle and impacts on climate.

Effects of Gas-Dissolved Water for Ceria Nanoparticles on the SiO2 Film Surface in Post-CMP Cleaning

Abstract As a trend of using colloidal and smaller ceria nanoparticles (CNPs) at the shallow trench isolation (STI) chemical mechanical polishing (CMP) in semiconductor manufacturing, post-CMP cleaning challenges in the removal of residual CNPs on the SiO2 film surface became much more challenging.
We investigated the reduction/oxidation of ceria nanoparticles (CNPs) by hydrogen gas-dissolved water (H2 GDW), carbon dioxide gas-dissolved water (CO2 GDW), and oxygen gas-dissolved water (O2 GDW). The concentration of Ce3+ on the CNPs changed from 18.64% to 19.48%, 20.31% to 21.94%, and 21.27% to 19.22%, respectively, after immersion in H2 GDW, CO2 GDW, and O2 GDW for 3 to 12 h. Following the Ce3+ concentration of the CNP surface, adhesion energies between CNPs immersed in H2 GDW, CO2 GDW, and O2 GDW for 6 hours with SiO2 surface were 6.06E-16 J, 6.18E-16 J, and 4.83E-16 J. Cleaning experiments under megasonic conditions revealed the efficacy of H2 GDW and O2 GDW in removing residual CNPs from SiO2 surfaces. The residual cerium (Ce) ion concentrations remaining on the SiO2 film surface after cleaning, were 0.06, 0.41, and 0.10 ppb for H2 GDW, CO2 GDW, and O2 GDW, respectively.

Analysis of Anodic Linear Sweep Voltammograms Considering Insufficient Lability of Cu|Cu(II), Glycine System

Anodic LS voltammograms of the alkaline Cu|Cu(II), glycine system were converted into mass-transport corrected Tafel plots considering that the glycinate anion L− takes part in the first stage of copper ionization. The anodic current density was normalized relative to the surface concentration of L− species, which was determined using the mass transfer model of chemically interacting species. The lability of the system was assessed based on available kinetic characteristics and specific experimental data. To linearize the Tafel plots, corrections were made to account for the insufficient mobility of the proton attached to glycine amino group. Obtained Tafel constants indicate that the second step of copper ionization, involving the oxidation of the intermediate copper(I)-glycine complex, is the rate-determining step.

Exploring chitosan-plant extract bilayer coatings: Advancements in active food packaging via polypropylene modification

UV-ozone activated polypropylene (PP) food films were subjected to a novel bilayer coating process involving primary or quaternary chitosan (CH/QCH) as the first layer and natural extracts from juniper needles (Juniperus oxycedrus; JUN) or blackberry leaves (Rubus fruticosus; BBL) as the second layer. This innovative approach aims to redefine active packaging (AP) development. Through a detailed analysis by surface characterization and bioactivity assessments (i.e., antioxidant and antimicrobial functionalities), we evaluated different coating combinations. Furthermore, we investigated the stability and barrier characteristics inherent in these coatings. The confirmed deposition, coupled with a comprehensive characterization of their composition and morphology, underscored the efficacy of the coatings. Our investigation included wettability assessment via contact angle (CA) measurements, X-ray photoelectron spectroscopy (XPS), and attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), which revealed substantial enhancements in surface concentrations of elements and functional groups of CH, QCH, JUN, and BBL. Scanning electron microscopy (SEM) unveiled the coatings' heterogeneity, while time-of-flight secondary ion mass spectrometry (ToF-SIMS) and CA profiling showed moderately compact bilayers on PP, providing active species on the hydrophilic surface, respectively. The coatings significantly reduced the oxygen permeability. Additionally, single-layer depositions of CH and QCH remained below the overall migration limit (OML). Remarkably, the coatings exhibited robust antioxidative properties due to plant extracts and exceptional antimicrobial activity against S. aureus, attributed to QCH. These findings underscore the pivotal role of film surface properties in governing bioactive characteristics and offer a promising pathway for enhancing food packaging functionality.

Enhanced Adsorption Response of pH-Sensitive Peptides: The Role of Membrane Acidity.

pH-sensitive peptides bind and traverse lipid membranes in response to changes in pH. They can be used to target tumors and other acidic tissues. We investigate the influence of acidic lipids on the pH-driven adsorption of recently synthesized peptides. Using a statistical-thermodynamic theory that takes into account the acid-base chemistry of peptides and lipids, we find that the presence of acidic lipids amplifies changes in peptide surface concentration when transitioning from high to low pH. We study cyclic and linear peptides, containing tryptophan, glutamic acid, and arginine residues, examining their behavior in both neutral and acidic membranes. Membrane binding consistently results from the shallow insertion of tryptophan residues with hydrophilic residues facing the aqueous solution. Regardless of the pH, the peptide's geometry predominantly determines the orientation and distribution of residues. Notably, we find that not only the extent of adsorption is pH-sensitive but also the underlying adsorption mechanism: it is barrier-free at low pH but hindered by a large free energy barrier at high pH. Hence, under more acidic conditions, pH-sensitive peptides show facilitated adsorption both kinetically and thermodynamically.

The fate of graphene on copper: Intercalation / de-intercalation processes and the role of silicon

Intercalation and de-intercalation processes below graphene (g) grown by chemical vapor deposition (CVD) on Cu foils (g/Cu) were investigated in a combined low-energy electron microscopy and X-ray photoemission electron microscopy study. Exposure of g/Cu to air induces oxygen and water intercalation which can be removed by annealing in vacuum leading to clean and well-ordered graphene on Cu. However, prolonged air exposure leads to intercalation of large amounts of oxygen, most likely inducing the formation of copper oxides. If sufficient intercalated oxygen remains at the interface when exceeding 320 °C, graphene is oxidized and burned off. Cu foils can be loaded with silicon on purpose during foil pre-treatment or accidently during long growth time when applying high temperatures at elevated H2 pressure inducing the reactive removal of Si species from the quartz reactor wall. Due to the dissolution of Si in the Cu bulk, the Si surface concentration remains below detection limit and graphene of equal crystalline quality is grown as if the Cu foil was silicon-free. However, oxygen intercalation underneath graphene on Si-containing Cu foils can induce Si segregation towards the surface and formation of intercalated silica without attacking the covering graphene. Even at high temperatures, segregating Si acts as oxygen scavenger so that graphene resists oxidation. The observed effect explains the usefulness of certain synthesis protocols and paves the way towards large-scale fabrication of electronically decoupled graphene. The effect can be used to immobilize adsorbing oxygen at the interface and image the initial steps of intercalation below graphene in-situ.

Hypoxia forecasting for Chesapeake Bay using artificial intelligence

Abstract Seasonal hypoxia is a recurring threat to ecosystems and fisheries in the Chesapeake Bay. Hypoxia forecasting based on coupled hydrodynamic and biogeochemical models has proven useful for many stakeholders, as these models excel in accounting for the effects of physical forcing on oxygen supply, but may fall short in replicating the more complex biogeochemical processes that govern oxygen consumption. Satellite-derived reflectances could be used to indicate the presence of surface organic matter over the Bay. However, teasing apart the contribution of atmospheric and aquatic constituents from the signal received by the satellite is not straightforward. As a result, it is difficult to derive surface concentrations of organic matter from satellite data in a robust fashion. A potential solution to this complexity is to use deep learning to build end-to-end applications that do not require precise accounting of the satellite signal from atmosphere or water, phytoplankton blooms, or sediment plumes. By training a deep neural network with data from a vast suite of variables that could potentially affect oxygen in the water column, improvement of short-term (daily) hypoxia forecast may be possible. Here we predict oxygen concentrations using inputs that account for both physical and biogeochemical factors. The physical inputs include wind velocity reanalysis information, together with 3D outputs from an estuarine hydrodynamic model, including current velocity, water temperature, and salinity. Satellite-derived spectral reflectance data are used as a surrogate for the biogeochemical factors. These input fields are time series of weekly statistics calculated from daily information, starting 8 weeks before each oxygen observation was collected. To accommodate this input data structure, we adopted a model architecture of long short-term memory networks with 8 time steps. At each time step, a set of convolutional neural networks are used to extract information from the inputs. Ablation and cross validation tests suggest that among all input features, the strongest predictor is the 3D temperature field, with which the new model can outperform the state-of-the-art by ∼20% in terms of median absolute error. Our approach represents a novel application of deep learning to address a complex water management challenge.

Reanalysis of NOAA H2 observations: implications for the H2 budget

Abstract. Hydrogen (H2) is a promising low-carbon alternative to fossil fuels for many applications. However, significant gaps in our understanding of the atmospheric H2 budget limit our ability to predict the impacts of greater H2 usage. Here we use NOAA H2 dry air mole fraction observations from air samples collected from ground-based and ship platforms during 2010–2019 to evaluate the representation of H2 in the NOAA GFDL-AM4.1 atmospheric chemistry-climate model. We find that the base model configuration captures the observed interhemispheric gradient well but underestimates the surface concentration of H2 by about 10 ppb. Additionally, the model fails to reproduce the 1–2 ppb yr−1 mean increase in surface H2 observed at background stations. We show that the cause is most likely an underestimation of current anthropogenic emissions, including potential leakages from H2-producing facilities. We also show that changes in soil moisture, soil temperature, and snow cover have most likely caused an increase in the magnitude of the soil sink, the most important removal mechanism for atmospheric H2, especially in the Northern Hemisphere. However, there remains uncertainty due to fundamental gaps in our understanding of H2 soil removal, such as the minimum moisture required for H2 soil uptake, for which we performed extensive sensitivity analyses. Finally, we show that the observed meridional gradient of the H2 mixing ratio and its seasonality can provide important constraints to test and refine parameterizations of the H2 soil sink.

Pesticide extraction from soil into runoff in North American and Australian croplands

Context Do some pesticides run off more than others? How does pesticide runoff vary with pesticide properties? Aims Improve understanding of pesticide runoff from croplands. Methods Concentrations in surface soil and in runoff from three Australian rainfall simulation studies and three rainfall simulation and five catchment studies in North American croplands were used. The ratio of event averaged runoff concentrations and the surface soil concentrations is the runoff extraction ratio. Key results Pesticide runoff concentrations were closely related to soil surface concentrations at the start of rainfall. Runoff extraction ratios were not significantly different for 13 pesticides with a wide range of properties, on gentle slopes (0–3%), but were significantly lower for three pesticides. On steeper slopes, runoff extraction was significantly greater for atrazine but lower for glyphosate and metolachlor. Low sloping, furrow irrigated fields had low sediment concentrations and low pesticide runoff concentrations for more tightly sorbed pesticides, but not for less sorbed pesticides. Runoff extraction was not significantly different for simulated and most catchment studies. Conclusions Similar runoff extraction ratios were due to similar hydrology and limited sediment concentrations. Different runoff extraction occurs on bare soil if (a) pesticides are leached from the runoff-mixing layer, requiring sorption coefficients less than two and significant infiltration, and no interflow, (b) sediment concentrations are either low (<2 g L−1) or high (>100 g L−1) and (c) pesticides have different concentration profiles in the runoff-mixing layer. Implications Conditions studied apply for croplands in the North American mid-west on silty soils and for Australian clay soils.

Weakening surface hydrogen to enhance permeation in hydrogen selective membranes

Hydrogen selective metallic membranes made of palladium and its alloys are superior to membranes made of other metallic materials due to their unique surface properties. However, the prohibitive cost of Pd has prevented their widespread application. Although the basic mechanisms are known, the link between hydrogen at the surface and that in the bulk has been missing to explain the prominent position of Pd. To provide the missing link between surface and bulk, we measured the hydrogen concentration and depth distribution on the downstream side of a Pd membrane at realistic permeation conditions (temperature and pressure) using a membrane electron spectroscopy setup. We find hydrogen in the vicinity of the surface with intermediate stability. In general, hydrogen on the surface is more stable and thus more concentrated than in the bulk. Subsurface hydrogen with intermediate stability mitigates the difference between surface and bulk concentration and thereby facilitates overall hydrogen permeation. The observations link the results of UHV-compatible hydrogen adsorption experiments with observations made on hydrogen permeation in membranes under technical conditions. Confirming this link enables the application of the wealth of surface science based knowledge to the optimization of hydrogen permeable membrane materials.

Suspended particulate matter dynamics at the interface between an estuary and its adjacent coastal sea: Unravelling the impact of tides, waves and river discharge from 2015 to 2022 in situ high-frequency observations

Suspended particulate matter (SPM) dynamics and exchange fluxes at the interface between a macrotidal estuary and its adjacent coastal sea were investigated from long-term high-frequency in situ observations. Optical and acoustic measurements were coupled to calculate SPM concentration over the whole water column using an existing acoustic inversion algorithm. A method was developed to distribute over the water column the surface and bottom calibrated equivalent particle diameters based on complementary ship-based surveys. Surface and bottom SPM show similar patterns in response to main forcings (tide, river discharge and waves), but present significantly higher concentrations near the bed. Increasing tidal ranges were responsible for higher tidal-median SPM concentrations, with spring/neap SPMC ratio varying from 2 to 3. This increase is driven by local resuspension during flood phase at the bottom, and low salinity turbid water flushed out from the estuary from mid-ebb to low tide at the surface. Increasing river discharge implies a downward shift of the estuarine turbidity maximum from the inner estuary to the mouth, and yields a 2-fold increase in both surface and bottom tidal-median concentration. Waves generated strong resuspension, with the highest SPM concentration recorded both at the surface and near the bed. Analysing SPM residual fluxes highlighted large up-estuary fluxes from low to moderate tidal ranges (below 6 m), and exporting seaward fluxes for higher tidal ranges, due to stronger mixing during spring tides. High river discharge enhanced stratification at the mouth and strengthened density circulation and up-estuary residual bottom circulation, resulting in larger up-estuary fluxes for all tidal ranges. Larger SPM concentrations along the tidal cycle during wave events yield high exporting fluxes.

Highly Efficient Iridium-Iron-Molybdenum Catalysts Condensed on Boron Nitride for Biomass-Derived Diols' Hydrogenolysis to Secondary Monoalcohols.

A trade-off of activity-selectivity exists in primary C-O hydrogenolysis of biomass-derived diols to secondary alcohols over bimetallic catalysts, especially the combination of noble metal and early transition metal in the metallic state and metal oxide state, respectively. Herein, the combination of high surface concentration of boron nitride (BN)-supported metals and the addition of Mo as third metal broke the trade-off. High yields (>50%) of secondary alcohols were obtained with robust productivity up to 25-fold based on Ir over Ir-Fe0.13-Mo0.08/BN (Ir = 20 wt %, Fe/Ir = 0.13, Mo/Ir = 0.08) than previously reported Ir-Fe catalysts. In contrast, simply increasing the loading amount of Ir-Fe catalysts or the addition of Mo species only enhanced the productivity by <2-4-fold. Various characterizations showed that large Ir loading enables the formation of condensed nanostructures (∼2 nm) on the BN support, which further alloy with Mo and Fe to form an face centred cubic (fcc)-type trimetallic alloy with surface enrichment of Fe. On the other hand, in Ir-Fe0.25-Mo0.08/BN with lower Ir (5 wt %) and lower Ir-based activity, the Mo species were rather bound on the support surface possibly as the MoBx state. These structures were formed by simple impregnation and reduction with H2 at the reaction temperature (453 K). The high activity of Ir-Fe0.13-Mo0.08/BN (20 wt % Ir) is derived from two aspects: (1) the formation of condensed nanostructures (∼2 nm) exposing more active sites and (2) alloying with Mo to modify the electronic state of Ir to enhance the H2 activation ability, as shown by the decreased Ea (82-84 → 67 kJ mol-1).

A finite difference study of radiative mixed convection MHD heat propagating Casson fluid past an accelerating porous plate including viscous dissipation and Joule heating effects

A finite difference numerical simulation scrutiny is executed to evaluate the combined impacts of heat generation, buoyancy forces, viscous dissipation and Joule heating in unsteady hydro-magnetic mixed convective chemically reactive and radiative Casson fluid flowing along an exponentially accelerating permeable vertical plate engrossed in a porous media by considering ramp surface concentration and temperature. The dimensionless non-linear coupled PDEs describing the flow model are dealt numerically by adopting the competent implicit Crank-Nicolson finite difference procedure. The variance of velocity, temperature, and concentration distributions are exposed via graphical representations due to the dissimilarity of the flow restrained parameters. Computational outcomes of the skin-friction, Nusselt and the Sherwood numbers are portrayed in the tabular pattern. The final outcomes of the research exposed that the impacts of thermal radiation, viscous dissipation, and heat production parameters enlarges the temperature and velocity distributions. The fluid motion deflates for growing Casson parameter and magnetic field intensity. The rising chemical reaction parameter suppresses the concentration and velocity distributions. Very importantly it is distinguished that fluid momentum, temperature, and concentration are quicker in the instance of isothermal plate temperature than ramp wall temperature. This kind of research may find specific industrial and medical utilizations such as glass manufacturing, crude oil purification, lubrication, paper production, blood transport study in cardiovascular design, etc.

A Multi-Method Approach to Geophysical Imaging of a Composite Pluton in North Portugal

Potassium (K), thorium (Th), and uranium (U) are good markers of magmatic or alteration processes and the surface concentrations of these radioelements can be mapped at the regional or local scale through radiometric (gamma) surveys. In this study, a radiometric survey was performed in a post-orogenic pluton located in North Portugal, namely the Lamas de Olo Pluton, composed by three granitic facies. This pluton has already been intensively studied, including magnetic susceptibility, gravimetric, geochemical, and petrographic studies. The main objective of this work is to evaluate the radiometric data and combine them with other characteristics, such as magnetic susceptibility, and gravimetry, as well as to elucidate structures such as faults and fractures, outline geological boundaries, and identify alteration zones within various granites of the pluton. The radiometric approach reveals the spatial distribution of radioelements, offering a more distinct portrayal of the geology in the studied area. The radioactive heat production rate was calculated for the studied pluton, showing that the mean value is 4.09 µW m−3, surpassing the known mean values for granites. Our study highlights that radiometric measurements unveil compositional variations within granitic pluton and aid in identifying feeder zones. Furthermore, these measurements can be correlated with each type of granites, demonstrating associations with surface concentrations of K-Th-U. Our findings indicate a spatial alignment between the NE feeder root and a U-rich granite (Barragem granite), as evidenced by its elevated concentration of this radioelement. Conversely, the other root displays a notable relative concentration of Th, consistent with the Th-rich characteristics observed of the two other granites (Lamas de Olo and Alto dos Cabeços granites).

A novel nonlinearity-aware adaptive observer for estimating surface concentration and state of charge of lithium-ion batteries

Physically based electrochemical models can provide internal state information of batteries, exhibiting significant potential for application in battery management systems across various lithium-ion battery products. However, the complex structure and limited observability of electrochemical models make their integration into battery management systems challenging. In this paper, a novel nonlinearity-aware adaptive (i.e., NAA) observer based on a simplified electrochemical model is proposed for estimating the electrode surface concentration and state of charge. The proposed NAA observer can identify the nonlinearity of the electrochemical model and switches to the most suitable observer structure automatically. Experimental tests on a cylindrical battery were conducted to observe the performance of the observer. The results demonstrate rapid convergence and high accuracy of all estimated states under an initial state error of 20%. Furthermore, to thoroughly validate the performance of the proposed observer, a comparison was made with an interconnected sliding mode observer based on electrochemical models, considering initial state uncertainty, sensor noise, and computation time.