Evolution Of Surface Area Research Articles

Benzothiadiazole Based Bifunctional Monomers: Design, Electronic and Geometric Effects on Their Tri(4‐Ethynylphenyl)amine Based Conjugated Microporous Polymers for Photocatalytic Hydrogen Evolution

ABSTRACTGuided by density functional theory (DFT), four benzothiadiazole based bifunctional monomers with varying electronic properties and geometric sizes have been designed. Utilizing tri(4‐ethynylphenyl)amine (TEA) as a multifunctional monomer, with temperature control, four TEA‐based conjugated microporous polymers (CMPs) TEA‐BT1‐TEA‐BT4 have been synthesized by Sonogashira Hagihara coupling polymerization. The electronic and geometric effects of the bifunctional monomers on the photocatalytic water splitting hydrogen evolution of TEA based CMPs have been investigated in detail. It shows that as the electron donating ability of the bifunctional monomers increases, the thermal stability enhances and the bandgap increases while the specific surface area and hydrogen evolution performance remain relatively unchanged. As the geometric area increases, the thermal stability decreases, the bandgap increases, the specific surface area and hydrogen evolution performance decreases seriously. All four polymers exhibit excellent thermal stability and stable photocatalytic water splitting hydrogen evolution properties. Without the presence of a cocatalyst, TEA‐BT1 gives the highest hydrogen evolution efficiency(115.74 μmol g−1 h−1). This research suggests that TEA is a novel and excellent multifunctional block for CMPs based photocatalysts, above all, it provides a new method to optimize CMPs properties to design high efficiency photocatalysts.

Towards a physically and microstructure-based equation for the evolution of the specific surface area in snow

Towards a physically and microstructure-based equation for the evolution of the specific surface area in snow

Quantifying the relationship between bubble surface area and gas evolution rate

Quantifying the relationship between bubble surface area and gas evolution rate

Microfluidics and Spectral Induced Polarization for Direct Observation and Petrophysical Modeling of Calcite Dissolution

AbstractWe investigate how micro‐geoelectrical monitoring is promising for studying microscale coupled processes since it facilitates the upscaling of pore‐scale observations and enhances the petrophysical interpretation of the geoelectrical measurements. Microscale geophysics using microfluidics emerges and combines direct visualization of pore scale dynamics and chemical reactivity with geoelectrical monitoring. Calcite dissolution is a usual geochemical reaction considered as an analog of water–mineral interactions involved in the critical zone. We develop a numerical workflow combining image processing and geochemical simulation as inputs for the petrophysical modeling applied to a published data set of microscale induced polarization monitoring of calcite dissolution under partially saturated conditions. The successful interpretation provides the cation exchange capacity and specific surface area evolution; essential parameters in field‐scale surveys.

Preparation of high density activated carbon by mechanical compression of precursors for compact capacitive energy storage

Activated carbons are widely used as the electrode material for supercapacitors owing to their large surface area, moderate conductivity, and outstanding electrochemical stability. However, large-surface-area activated carbons usually show low density and poor volumetric energy storage performance, which is difficult to meet the development of devices miniaturization. Mechanical compression is a simple and effective method to improve the density of the activated carbons. However, most of the studies focus on mechanical compression of the as-prepared porous carbon materials. Preparation of high-density activated carbons by mechanical compression of the carbon precursors has been proposed. But the surface area and porous structure evolution, and the possible mechanism have rarely investigated. Herein, we propose a universal method to improve the density of the activated carbons by mechanical compression of the precursors before activation. The influence of mechanical compression on the surface area, porous structure, and capacitive energy storage performance of the activated carbons prepared by two typical methods, outside-in activation (carbon powder/KOH mixture) and homogeneous ion activation (pyrolysis of potassium-containing salts), are studied. Mechanical compression of the precursors can generally improve the activation reaction efficiency, as well as the density and volumetric capacitive performance of the activated carbons. However, the surface area and porous structure evolution mainly depend on the carbon precursor and pore-forming process. For outside-in activation, the surface area and porosity of the activated carbons show a first increasing and then decreasing trend with the increase of mechanical pressure. This is because mechanical compression enhances the contact between the carbon precursors and activator through eliminating the voids between particles, significantly improves the activation efficiency. For homogeneous ion activation, the surface area and porosity of activated carbons show a trend of decreasing first and then increasing. The reason is deduced as compressed precursors inhibit the rapid release of active gas molecules (H2O, CO2etc.) produced during pyrolysis. These gas molecules further participate in the activation etching reaction and promote the activation efficiency. The optimized sample shows high gravimetric and volumetric capacitances of 316 ​F ​g−1/291 ​F ​cm−3 and 131 ​F ​g−1/92 ​F ​cm−3 ​at 1 ​A ​g−1 in aqueous and organic electrolytes, respectively. This work provides a simple way for design and preparation of activated carbons with large surface area and high density.

Nucleation Behavior of Pitting and Evolution of Stripping on Lithium Metal Batteries

The stripping reaction of lithium will greatly impact the cyclability and safety of Li metal batteries. However, lithium pits' nucleation and growth, the origin of uneven stripping, are still poorly understood. In this study, we analyze the nucleation mechanism of Li pits and their morphology evolution with a large population and electrode area (>0.45 cm2). We elucidate the dependence of pit size and density on current density and overpotential, which is aligned with classical nucleation theory. With laser scanning confocal microscope, we reveal the preferential stripping on certain crystal grains and a new stripping mode between pure pitting and stripping without pitting. Descriptors like circularity and the aspect ratio (R) of pit radius to depth are used to quantify the evolution of lithium pits in three dimensions. As pits grow, growth predominates along the through-plane direction, surpassing the expanding rate at the in-plane direction. After analyzing more than 1000 pits at each condition, we validate that the overpotential is inversely related to the pit radius and exponentially related to the rate of nucleation. With this established nucleation-overpotential relationship, we can better understand and predict the evolution of surface area and roughness of lithium electrodes under different stripping conditions. The knowledge and methodology developed in this work will significantly benefit lithium metal batteries' charging/discharging profile design and the assessment of large-scale lithium metal foils. DOI of publication: 10.1021/acsami.4c01530Acknowledgments: H.Z., M.U., and F.S. thank the support from the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the US Department of Energy through the Advanced Battery Materials Research Program. F.S. thanks the support from the National Science Foundation under Grant No. 2239690.

Wind tunnel experiments to quantify the effect of aeolian snow transport on the surface snow microstructure

Abstract. The evolution of the surface snow microstructure under the influence of wind during precipitation events is hardly understood but crucial for polar and alpine snowpacks. Available statistical models are solely parameterized from field data where conditions are difficult to control. Controlled experiments which exemplify the physical processes underlying the evolution of density or specific surface area (SSA) of surface snow under windy conditions are virtually non-existent. As a remedy, we conducted experiments in a cold laboratory using a ring-shaped wind tunnel with an infinite fetch to systematically investigate wind-induced microstructure modifications under controlled atmospheric, flow and snow conditions and to identify the relevant processes. Airborne snow particles are characterized by high-speed imaging, while deposited snow is characterized by density and SSA measurements. We used a single snow type (dendritic fresh snow) for simulating different precipitation intensities, varied wind speeds at a height of 0.4 m from 3 to 7 m s−1 (for fixed temperature) and varied temperatures from −24 to −2 °C (for fixed wind speed). The measured airborne impact trajectories confirm the consistency of our coefficient of restitution with large-scale saltation, rendering the setup suitable for realistically studying interactions between airborne and deposited snow. Increasing wind speeds resulted in intensified densification and stronger SSA decreases. The most drastic snow density and SSA changes in deposited snow are observed close to the melting point. Our measured densification rates as a function of wind speed show clear deviations from existing statistical models but can be re-parameterized through our data. This study, as a first of its kind, exemplifies a rich nonlinear interplay between airborne and deposited snow particles, which is discussed in view of a multitude of involved processes, i.e., airborne metamorphism, cohesion, particle separation and fragmentation.

Characterization of evolution of reactive transport parameters during leaching process of sandstone uranium ore by combining porosity and lacunarity

During the in-situ leaching process of sandstone uranium ore deposits, the dynamic evolution of reactive transport parameters, including permeability, tortuosity, and specific surface area (SSA), plays a crucial role in solution flow and solute transport. Characterizing the evolution of these parameters is essential for understanding the leaching process. However, the heterogeneous pore structure of sandstone renders porosity alone insufficient to capture changes in these parameters. This study combines porosity and lacunarity to comprehensively characterize these parameters. For this purpose, leaching experiments were conducted on sandstone uranium ore samples, and CT imaging was performed at different leaching time points. The evolution of reactive transport parameters was analyzed by studying cubic subsamples from the images. The results indicate that both porosity and lacunarity are significant factors influencing the reactive transport parameters. However, neither parameter alone adequately characterizes their evolution. In contrast, combining them accurately characterizes the evolution of reactive transport parameters. Porosity reflects pore quantity, while lacunarity represents pore heterogeneity. Combining these measures facilitates a comprehensive understanding of the evolution of reactive transport parameters and the influence of pore microstructure on macroscopic reactive transport parameters. This research provides valuable insights for optimizing the leaching process in sandstone uranium ore deposits.

Characterizing the combined impact of nucleation-driven precipitation and secondary passivation on carbon mineralization

The evolution of mineral reactive surface area is one of the primary phenomena controlling the progression and extent of mineral carbonation. The CO2 mineralization begins with nucleation of crystals that provide initial surface area for subsequent growth of the mineral. However, many reactive transport models (RTMs) for CO2 mineralization do not include the nucleation process. The few RTMs that do include it are yet to be validated against experimental data. Similarly, many RTMs ignore passivating effects of the secondary mineral, which coats the surface of the dissolving mineral, slow down the reaction process, and reduce the total extent of carbonation. Furthermore, the combined impact of nucleation and passivation on carbon mineralization is yet to be properly characterized. In this study, we consider the coupled effects of passivation and nucleation on the mineralization extent. The nucleation-driven precipitation model relies on the formation of nuclei to provide a surface area for crystal growth, while a new model is proposed to account for passivation effects. Our analysis shows that (i) omission of nucleation leads to overestimation of extent of mineralization, and (ii) omission of passivation leads to overestimation of host rock reactivity. The model was evaluated via comparison with CO2 mineralization data from the literature and models that ignore these processes. We observed that including nucleation and passivation lead to closer predictions of the CO2 mineralization extent. Therefore, this study highlights the importance of including the coupled nucleation-driven precipitation and secondary passivation in RTMs. The findings from the study can be applied in various scientific and engineering applications such as petroleum production, cement carbonation, CO2 sequestration, chemical weathering, and concrete degradation.

A rigorous approach to the specific surface area evolution in snow during temperature gradient metamorphism

Abstract. Despite being one of the most fundamental microstructural parameters of snow, the specific surface area (SSA) dynamics during temperature gradient metamorphism (TGM) have so far been addressed only within empirical modeling. To surpass this limitation, we propose a rigorous modeling of SSA dynamics using an exact equation for the temporal evolution of the surface area, fed by pore-scale finite-element simulations of the water vapor field coupled with the temperature field on X-ray computed tomography images. The proposed methodology is derived from the first principles of physics and thus does not rely on any empirical parameter. Since the calculated evolution of the SSA is highly sensitive to fluctuations in the experimental data, we quantify the impact of these fluctuations within a stochastic error model. In our simulations, the only poorly constrained physical parameter is the condensation coefficient α. We address this problem by simulating the SSA evolution for a wide range of α values and estimate optimal values by minimizing the differences between simulations and experiments. This methodology suggests that α lies in the intermediate range 10-3<α<10-1 and slightly varies between experiments. Also, our results suggest a transition of the value of α in one TGM experiment, which can be explained by a transition in the underlying surface morphology. Overall, we are able to reproduce very subtle variations in the SSA evolution with correlations of R2=0.95 and 0.99, respectively, for the two TGM time series considered. Finally, our work highlights the necessity of including kinetic effects and of using realistic microstructures to comprehend the evolution of SSA during TGM.

Modeling of the evolution of the porous structure during a physical activation process for the production of activated biocarbon: A novel low conversion approach

Many experimental studies have shown the feasibility of using biomass precursors to produce activated carbon, often improving the properties obtained from traditional materials. However, hardly any models focus on the development of porosity during the process. Among the so-called pore models, the random pore model (RPM) is the most popular and accurately predicts the evolution of the porous structure due to pore growth and coalescence. However, in activation processes with a low degree of conversion, in which pore formation is the dominant mechanism, the RPM does not correctly predict the evolution of the specific surface area since it does not consider the appearance and creation of new porosity. In this work, a new model is proposed that predicts the specific surface area created due to the formation of new pores. Subsequently, it is combined with the determination of the variation of the specific surface area predicted by the RPM due to the growth and coalescence of existing pores. The validation of the new pore evolution model with activated carbon samples obtained at different conversions shows that the model proposed adequately predicts the specific surface area and pore distribution evolution throughout the activation process.

First principle based rate equation (1pRE) for random pore model in Fe2O3 reduction reaction with CO

AbstractThe redox kinetics of the oxygen carriers are crucial in Chemical‐Looping Combustion (CLC) systems. The random pore model (RPM) was widely used to investigate the macroscale redox kinetics of oxygen carriers in previous studies, in which the reaction rate constants were obtained just by fitting the experimental data. This study presents a first principle based rate equation (1pRE) applied to the RPM to calculate the reaction rate constants directly using density functional theory (DFT). The 1pRE is integrated with the RPM that accounts for the effect of pore size distribution derived from the surface area evolution of reaction interface and product layer diffusion, thus bridging the gap between the microscale elementary surface reactions and macroscale overall conversion. The developed 1pRE predicts the reduction kinetics of Fe2O3 oxygen carriers accurately, thereby facilitating the optimization of design processes for oxygen carrier materials and the scale up of CLC reactors.

A 3D PtCo degradation model for long-term performance prediction of a scaled-up PEMFC under constant voltage operation

The non-uniform distribution of reactants, pressure, temperature and reaction rate in a scaled-up proton exchange membrane fuel cell (PEMFC) can lead to different catalyst degradation rate, impacting the long-term performance of PEMFCs. However, the local catalyst degradation behaviors in a PEMFC stack have not yet been fully understood due to the lack of experimental approaches and catalyst degradation model. In the present study, a numerical model is established for a 200 cm2 commercial-sized PEMFC stack with realistic anode and cathode flow fields. PtCo is employed as the cathode catalyst, and a 3D PtCo catalyst degradation model is developed to analyze the non-uniform evolution of the electrochemical active surface area (ECSA), current density, and Co2+ in the catalyst layers under the constant voltage conditions. The modeling results demonstrated that catalyst degradation is more severe downstream as well as under land of the cathode flow field, and the cathode catalyst layer (CCL) is the area most contaminated by the Co2+. The non-uniform catalyst degradation as well as Co2+ contamination increased the activation losses and local oxygen transport resistance. The catalyst degradation leads to a total power loss of 43.3 % after 80,000 h operation. The aging model provides a better understanding for large scale PEMFC stacks regarding its non-uniform PtCo degradation and can assist the future design of commercial PEMFCs with better lifetime.

New Insights into the Dissolution Kinetics of Alite Powder and the Effects of Organic Toughening Materials.

Alite dissolution plays a crucial role in cement hydration. However, quantitative investigations into alite powder dissolution are limited, especially regarding the influence of chemical admixtures. This study investigates the impact of particle size, temperature, saturation level, and mixing speed on alite powder dissolution rate, considering the real-time evolution of specific surface area during the alite powder dissolution process. Furthermore, the study delves into the influence of two organic toughening agents, chitosan oligosaccharide (COS) and anionic/non-ionic polyester-based polyurethane (PU), on the kinetics of alite powder dissolution. The results demonstrate a specific-surface-area change formula during alite powder dissolution: SS0=0.348e1-m/m0/0.085+0.651. Notably, the temperature and saturation level significantly affect dissolution rates, whereas the effect of particle size is more complicated. COS shows dosage-dependent effects on alite dissolution, acting through both its acidic nature and surface coverage. On the other hand, PU inhibits alite dissolution by blocking the active sites of alite through electrostatic adsorption, which is particularly evident at high temperatures.

Comprehensive analysis of early-stage hydration and microstructure evolution in Sufflaminate cement: Insights from low-field NMR and isothermal calorimetry

This study presented a comprehensive investigation of the early hydration reaction and microstructure evolution of sulfoaluminate cement (SAC) using low-field nuclear magnetic resonance (LF-NMR) and isothermal calorimetry (IC). LF-NMR, combined with total relaxation signal and transverse relaxation time (T2), was employed to characterize the evolution of evaporation water (EW) and the degree of hydration (αlf) during the initial stage of SAC hydration. The hydration process was divided into four phases. The relative content of different EW types within the paste was investigated, and the pore structure and specific surface area evolution of SAC paste were studied based on the T2. The heat release of hydration of SAC was measured using IC, and the hydration kinetics was fitted with the JMAK model. The results demonstrated that the early hydration reaction of SAC was a multidimensional controlled process influenced by various factors. Also, the crystallization nucleation rate of hydration products was inversely related to w/c. Furthermore, a successful nonlinear fitting between the weighted average of T2 and the hydration degree (αt) obtained from IC was established, providing a standard reference curve for studying hydration degree and microstructure. Finally, the hydration products and microstructure were investigated using, SEM, and TG, and the evolution of the compressive strength of SAC was also analyzed. This work gave valuable insights into SAC's early hydration behavior and microstructural development, which can contribute to a better understanding of its performance and potential applications.

Experimental study on influence of blade angle and particle size on particle mechanics on a batch-operated single floor of a multiple hearth furnace

In industry, multiple hearth furnaces are used for the thermal treatment of particulate material. The current contribution concentrates on the experimental analysis of particle mechanics for a batch-operated single floor of a multiple hearth furnace. The particles are agitated on the circular floor by a single, rotating rabble arm equipped with three flat rabble blades of 10 mm thickness. The blade angle, defined as the angle, which the blade is inclined against the tangential direction, is varied from 0° to 90°. A single layer of spherical polyoxymethylene (POM) particles with three different diameters (5, 10 and 20 mm) is placed on the floor. To analyze the results, two parameters have been extracted from image analysis when the bed of particles is agitated, first, the area not covered by particles and second, the frequency distribution of the mean distance among the particles. The particle free surface area increases with the inclination of the blades. The evolution of the particle free surface area differs for the different particle diameters. In general, the maximum particle free area for all blade angles is the largest for the 5 mm particles followed by the 20 mm particles. For the 10 mm particles, the particle free surface area starts for a blade angle of 0° at larger values than for the 20 mm particles but the values fall below the values for the 20 mm particles for larger blade angles. The reason for this behavior is discussed in detail. The mean distance among the particles is a parameter characterizing the length scales dominating the effects on the floor. The frequency distribution of the mean distance among particles provides information about the morphology of the particle bulk, for example, whether the free surface area is interspersed with particles.

Evolution of surface area and membrane shear modulus of matured human red blood cells during mechanical fatigue

Mechanical properties of red blood cells (RBCs) change during their senescence which supports numerous physiological or pathological processes in circulatory systems by providing crucial cellular mechanical environments of hemodynamics. However, quantitative studies on the aging and variations of RBC properties are largely lacking. Herein, we investigate morphological changes, softening or stiffening of single RBCs during aging using an in vitro mechanical fatigue model. Using a microfluidic system with microtubes, RBCs are repeatedly subjected to stretch and relaxation as they squeeze into and out of a sudden contraction region. Geometric parameters and mechanical properties of healthy human RBCs are characterized systematically upon each mechanical loading cycle. Our experimental results identify three typical shape transformations of RBCs during mechanical fatigue, which are all strongly associated with the loss of surface area. We constructed mathematical models for the evolution of surface area and membrane shear modulus of single RBCs during mechanical fatigue, and quantitatively developed an ensemble parameter to evaluate the aging status of RBCs. This study provides not only a novel in vitro fatigue model for investigating the mechanical behavior of RBCs, but also an index closely related to the age and inherent physical properties for a quantitative differentiation of individual RBCs.

Coarse-grain molecular dynamics simulation framework to unravel the interactions of surfactants on silica surfaces for oil recovery

A coarse-grained molecular dynamics (CG-MD) framework, based on the MARTINI 3.0 model, was developed to characterise the interactions between surfactants and oil-silica substrates to resemble chemical enhanced oil recovery (EOR) processes. Previous computational studies, at the atomistic scale, addressed interactions between surfactants and oil over diverse surfaces. Even though simulations provided significant information involved throughout different stages of oil extraction from surfaces, atomistic scale simulations fail when approaching the time and size scale required to address the surfactant phase behaviour that can also impact the oil detachment. Our coarse-grained model aims to overcome the lack of computer approaches that can tackle the surfactant self-assembly and the formation of ordered structures in the removal of oil from silica substrates. A new MARTINI 3.0 coarse-grain framework to model silica surfaces and aqueous solutions of CiEj and C16TAB surfactants is presented. Coarse-grained simulations entailing a silica surface, covered by dodecane or eicosane were brought in contact with aqueous solutions of C16TAB and four nonionic CiEj (C8E6, C8E12, C12E6, C16E12) surfactants to resemble EOR processes with a size/time scale several orders of magnitude larger than previous simulations. The impact of concentration and hydrophilic-lipophilic balance (HLB) of surfactants on the detachment of dodecane and eicosane from the silica surface was evaluated by visual inspection of the simulation snapshots and the evolution of the solvent accessible surface areas (SASA). In contrast with previous atomistic simulations, nonionic surfactants seem the best candidates for an optimal oil removal from silica-based surfaces whereas the presence of charged moieties hinders the process. Diluted nonionic CE aqueous solutions were shown to be the most effective solutions, unlike more concentrated ones. When compared with dodecane, eicosane was less prone to be removed from the silica surface due to the increased alkyl chain length. Our study demonstrates that not only the surfactant nature but also the phase behaviour, clearly impact the detachment of oil from silica surfaces. This is an important aspect to consider for a proper choice of surfactants in EOR processes, that is only attainable through a coarse-grained framework.

A CFD-based porous medium model for simulating municipal solid waste incineration grates: A sensitivity analysis

This study starts from a generalized CFD-based porous medium model developed in previous work simulating the combustion of municipal solid waste (MSW) on incineration grates. In this paper, three specific bed models are compared: a newly developed whole moving bed model, a newly developed multi-zone model, and a fixed bed model. Although the whole moving bed model covers the entire gas flow field, this advantage is offset by a high computational cost. In the multi-zone model, different zones of the waste bed are computed consecutively. This helps to reduce the computational time by about 75% but causes a loss of accuracy in predicting the gas flow field at the transition between the zones. For the fixed bed model, the walking column approach is needed. Additional accuracy loss is introduced but the computational time is significantly reduced even further compared to the multi-zone model. Because of the trade-off between computational cost and accuracy and the great uncertainty of the model parameters in industrial practice, the fixed bed model is suggested for simulating industrial grate-firing systems. In addition to these moving bed modeling strategies, this study also investigates how sensitive model results are to the assumed minimum and maximum solid fractions, which determine the evolution of porosity along the grate. The results show that the conversion rates are relatively insensitive to these criteria within the investigated range. Conversely, the effective surface area greatly influences the combustion characteristics as it affects the drying and char conversion rate and governs the temperature difference between the solid and gas phases. This finding calls for a better understanding of the evolution of the effective surface area and equivalent particle diameter during the combustion of MSW.

Evolution of Mineral-Accessible Surface Area Induced by Geochemical Reactions

Mineral dissolution and precipitation reactions occur in a wide range of porous media systems, driven by deviations from an equilibrium between solid and fluid phases. Reactions occur at mineral surfaces in contact with reactive fluids or accessible mineral surface areas. These mineral surface areas can be determined using a multiscale imaging approach and have been shown to improve the simulation of mineral reaction rates in porous media compared to other estimates of reactive surface area. As reactions progress, mineral surface area evolves, and reactive transport simulations often use a simplified model assuming spherical grains to estimate mineral surface area evolution. This, however, does not depict the evolution of reactive surfaces in porous media systems with varying mineral accessibility. This work aims to quantitatively assess the evolution of accessible mineral surface area in porous media for a multimineralic system undergoing mineral dissolution reactions induced by acid exposure. Before and after the reaction, accessible mineral surface areas are determined from 2D scanning electron microscopy, and 3D X-ray computed tomography imaging of a sandstone sample. The quantified evolution of accessible surface area is compared to the calculated mineral surface area evolution using current approaches. Results show an overall increase in total surface area due to the reaction; however, individual mineral surface areas may increase or decrease. Variation is observed in mineral surface area values measured from imaging and equations used in models. The evolution of mineral surface area is largely impacted by the total surface area as well as the pore connectivity rather than porosity and volume fraction evolution.