Diffusion Behavior Research Articles

Enhancing resistance against water vapor in columnar crystal Ni coating through double glow plasma surface alloying technique

Water vapor from hydrogen engines could corrode superalloys. We deposited Ni coatings by using the Double Glow Plasma Surface Alloying technique and studied corrosion resistance in the atmosphere, water vapor, and water vapor containing 30 % CO2, respectively. In the Ar+ bombardment process, dislocations and twins are formed on the substrate, leading to an acceleration of diffusion behavior. The γ-Al2O3, dispersed along the grain boundaries, restricts the migration of grain boundaries which results in grain boundaries strengthening. Columnar crystal boundaries facilitate corrosion between the interdiffusion zone (IDZ) and the external environment. In atmospheric conditions, Cr generates thermally grown oxide (TGO) at a considerable distance from the IDZ. The dissociation of O2– from water vapor is insufficient to establish a consistent TGO layer. Furthermore, the elevated solubility of CO2 in water vapor hastens the corrosion process within the IDZ, indicating the desirability of avoiding its use as a cooling gas whenever feasible.

Hydrogen Embrittlement Behavior of API X70 Linepipe Steel under Ex Situ and In Situ Hydrogen Charging.

This study investigates the hydrogen embrittlement behavior of API X70 linepipe steel. The microstructure was primarily composed of a dislocation-rich bainitic microstructure and polygonal ferrite. Slow strain-rate tests (SSRTs) were performed under both ex situ and in situ electrochemical hydrogen charging conditions to examine the difference between hydrogen diffusion and trapping behaviors. The ex situ SSRTs showed almost the same tensile properties as air and a limited brittle fracture confined to near the surface. In contrast, the in situ SSRTs showed an abrupt failure after the maximum tensile load, leading to a brittle fracture across the entire fracture surface with stress-oriented hydrogen-induced cracking (SOHIC). The crack trace analysis results indicated that SOHIC propagation paths were influenced by localized hydrogen accumulation due to high-stress fields. As a result, the dominant hydrogen embrittlement mechanisms, such as hydrogen-enhanced localized plasticity (HELP) and hydrogen-enhanced decohesion (HEDE), changed. These findings provide critical insights into the microstructural factors affecting hydrogen embrittlement, which are essential for the design of hydrogen-resistant steels in hydrogen infrastructure applications.

Synthesis of high-efficient low-cost fertilizer carriers based on biodegradable lignin hydrogels

Conventional fertilizers face environmental and economic challenges due to their high solubility, leading to significant losses via runoff and leachate. This study presents a biodegradable hydrogel, synthesized from lignin and polyvinyl alcohol (PVA), designed as an eco-friendly carrier for struvite (fertilizer) with controlled phosphate release. The hydrogel was analysed through scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), Thermogravimetric analysis (TGA) and Differential scanning calorimetry (DSC). Furthermore, the prepared hydrogels demonstrated high water absorption capacities (963.4 %, 706.4 %, and 410 % for LH4, LH8, and LH12, respectively) and exhibited Fickian diffusion behaviour. Phosphate release studies showed a gradual release over 6–8 h with concentrations of 20.5 ppm, 19.45 ppm, and 17.85 ppm for St-LH4, St-LH8, and St-LH12. These lignin-based hydrogels offer a promising, cost-effective solution for slow-release fertilizers with high efficiency.

Stochastic stability of random stacking of blocks

The paper explores the stability of a tower obtained by stacking identical rectangular blocks on top of each other with an inherent randomness due to slight positional offsets between successive blocks. With probabilistic modeling techniques, the diffusive behavior of the stacking process is studied and the collapse is seen as a first passage time problem. In the considered model, alignment errors are idealized as independent Gaussian random variables with zero mean and given standard deviation. We derive expressions for the joint probability density functions of block positions, and analyze their correlation. The study extends to the stochastic stability of a stack of given height, by exploring the statistical characteristics of the center of gravity of the part of tower above each block. Eventually, the probabilistic analysis of collapse is developed to quantify the statistics of the number of blocks that can be heaped up before the tower topples. Although this problem may initially appear playful, it offers an illustrated introduction to first passage problems on a non homogenous process. From a practical standpoint, this analysis offers a simple understanding of the influence of alignment errors on the overall stability of a stack, which may find several fields of application.

A study on microstructure evolution of MCrAlY coatings after thermal aging in Te environment

The effects of thermal exposure on tellurium (Te) diffusion behavior in MCrAlY coatings were investigated at 800 °C in Te vapor. The results showed that the diffusion depth of Te in MCrAlY coatings gradually increased with the exposure time, and the dense Cr3Te4 layer formed on the coating surface in the initial stage was no longer continuous, especially under aging conditions with higher Te concentration. The high Cr content of the coating promoted the solid phase transition of the surface reaction product from Cr3Te4 to Cr7Te8, and resulting in the formation of large α-Cr phase either within or beneath the reaction layer during long aging processes. As a result of this phase transition, excess Te atoms were released from Cr3Te4 and continued to diffuse into the coating. Te did not exhibit obvious intergranular diffusion characteristics within the coating. When it encountered Y, it was captured by Y and formed a YTe phase. After aging for 3000 h, Te was distributed throughout the coating, and numerous voids were formed at the interface between the coating and the substrate. These two factors deteriorated the plasticity and adhesion of the coating. Results from molten salt corrosion tests indicated that the high content of Cr and Al in the coating, as well as high densities of grain boundaries providing diffusion pathways, reduced the corrosion resistance of the coating to molten salt.

Diffusion behavior and environmental impact of odorants and TVOCs detected in a wastewater treatment plant for collaborative leachate treatment in Northwest China

Wastewater treatment plants (WWTPs) are major sources of volatile gaseous compounds, especially in mixed-source systems such as domestic wastewater and landfill leachate. This study aimed to investigate the emission behavior and environmental impact of gaseous substances, such as hydrogen sulfide (H2S), ammonia (NH3), carbon sulfide (CS2), and phosphine (PH3), at a WWTP in Northwest China. Odorants were detected in the air surrounding the grid room (XGS), biochemical treatment tank (SHC), secondary sedimentation tank (ECC), and sludge dewatering room (NTS). For comparison, the upwind boundary (O-SF) and downwind boundaries (O-XF) monitoring points were used, with odor concentrations ranging from 3.95 to 725.27 odor units. The concentration ranges of the odorant substances were 5.27–88.69, 5.61–71.96, 5.70–32.63, and 0.12–5.87 mg/m3 for H2S, NH3, CS2, and PH3, respectively. Meteorological factors such as temperature, relative humidity, and wind speed and direction substantially influence odorant emissions. The concentrations of various odorants and volatile organic compounds (VOCs) detected at the O-XF monitoring point were higher than those detected at the O-SF monitoring point, indicating that the wind intensified their diffusion toward the downwind plant boundary. The average odor intensities of odorant substances emitted from wastewater or sludge treatment equipment were 3.37, 5.09, 4.42, 2.00, and 3.82 for total VOCs, H2S, NH3, CS2, and PH3, respectively. Among them four, with downwind diffusion, only H2S presented olfactory and chronic toxicity risks based on Gaussian plume model calculations. The hazard index ranking across monitoring sites was XGS > NTS > SHC > ECC > O-XF > O-SF. These findings emphasize the urgent need for effective measures to control and mitigate gaseous pollutants emitted by collaborative WWTPS, thereby protecting environmental quality and public health.

Selenium Adsorption on the (111), (100), (110) and (211) Surfaces of Face‐Centered‐Cubic Metals: Density Functional Calculations of the Potential Energy Surfaces

AbstractIn this study, we expand the computational investigation of selenium, which has previously been limited to metals such as Cu, Fe, Pd, Au, and Pt. Utilizing density functional theory calculations, we explore the adsorption and diffusion of selenium at a low‐coverage regime of 0.25 ML on a broader range of metal surfaces, including Ni, Cu, Rh, Pd, Ag, Ir, Pt, and Au. Our results reveal that selenium exhibits a distinct preference for three‐fold or four‐fold high‐coordination sites on most studied surfaces. We further analyze the minimum energy diffusion pathways, demonstrating that the energy barrier for selenium's surface diffusion varies significantly based on the orientation and nature of the metal surfaces. Specifically, on (100) surfaces, selenium exhibits the highest diffusion energy, ranging from 0.60 eV in Au(100) to 1.12 eV in Pd(100). The diffusion behavior on (110) and (211) surfaces is also elaborated, emphasizing the unique trends observed compared to previously studied elements like sulfur. Importantly, this study is a new reference for future computational analyses, filling existing gaps by providing comprehensive data on selenium adsorption on various face‐centered cubic metal surfaces not previously reported.

Change-point detection in anomalous-diffusion trajectories utilising machine-learning-based uncertainty estimates

Abstract When recording the movement of individual animals, cells or molecules one will often observe changes in their diffusive behaviour at certain points in time along their trajectory. In order to capture the different diffusive modes assembled in such heterogeneous trajectories it becomes necessary to segment them by determining these change-points. Such a change-point detection can be challenging for conventional statistical methods, especially when the changes are subtle. We here apply Bayesian Deep Learning to obtain point-wise estimates of not only the anomalous diffusion exponent but also the uncertainties in these predictions from a single anomalous diffusion trajectory generated according to four theoretical models of anomalous diffusion. We show that we are able to achieve an accuracy similar to single-mode (without change-points) predictions as well as a well calibrated uncertainty predictions of this accuracy. Additionally, we find that the predicted uncertainties feature interesting behaviour at the change-points leading us to examine the capabilities of these predictions for change-point detection. While the series of predicted uncertainties on their own are not sufficient to improve change-point detection, they do lead to a performance boost when applied in combination with the predicted anomalous diffusion exponents.

Research on the Recognition and Characterization of Fractures in Coal Rock Based on CT Scanning

Abstract Coal rock fractures play a vital role as key channels for gas migration and storage in the exploration and development of coalbed methane. The characteristics of these fractures, such as porosity distribution, specific surface area, and connectivity, directly impact the adsorption, diffusion, and permeability behaviors of coal reservoirs. Therefore, a detailed analysis of coal rock fracture characteristics is vital in assessing the extractability of coalbed methane and during its exploration and development process. Currently, techniques like imaging logging, seismic detection, and micro-CT are employed for characterizing and studying fractures at various scales. Among these, high-resolution non-destructive CT scanning technology, by constructing three-dimensional data models of core samples, enables a quantitative analysis of fracture distribution features and size parameters. Traditional digital image processing methods, such as threshold segmentation and binary segmentation, though advantageous in computational speed, have limitations in the accuracy of fracture identification. With the advancement of artificial intelligence technology, deep learning-based image processing techniques have increasingly become significant tools for fracture detection due to their powerful feature extraction capabilities. This study conducted micrometer-level CT scanning experiments on coal rock samples, using CT image processing technology to construct a digitalized coal rock core model. Deep learning methods were applied for precise fracture identification, establishing an appropriate deep learning architecture and optimized parameters for coal rock fracture recognition. Furthermore, this paper provides a detailed quantitative characterization of the precisely identified fractures, offering robust technical support for the exploration and development of coalbed methane. The high-resolution non-destructive CT scanning technology and three-dimensional fracture network reconstruction method used in this study have been proven to be effective tools for investigating the micro-features of rocks, enabling the three-dimensional visualization and detailed characterization of rock microstructures.

First-principles study on atomic formation and manganese diffusion in MnS/Mg-Ti-oxide complex inclusions in steel

Mg-Ti oxide/MnS complex inclusions effectively serve as nucleation sites for intragranular ferrite. This study employs first-principles calculation methods to investigate the inducing properties of complex inclusions, including the growth of MnS on Ti oxide, the absorption of Mn atoms by Ti oxide, and the diffusion behavior of Mn atoms within Ti oxide, both untreated and Mg-treated. Ti2O3 indicates the untreated group, while MgTiO3 indicates the Mg-treated group. Computational analysis indicated that MnS is more likely to adsorb and grow on MgTiO3 than on Ti2O3. MnS vertically grows on the O-Mg-Mg surface of MgTiO3. By calculating the dissociation energy, it can be determined that the Mn in the oxide of the MnS/oxide complex inclusions originates from the steel matrix rather than from MnS. By analyzing the diffusion behavior of vacancies and Mn atoms through energy barrier calculations, it is evident that the addition of Mg alters the diffusion pathways of Mn atoms in Ti oxide and confirms that the bonding between Mn and O is the limiting step for Mn atom diffusion within the oxides. The diffusion path of Mn atoms in MgTiO3 is Path I → Path II → Path I. Path I: Mn atoms diffuse within the cationic layer. Path II: Mn atoms diffuse by traversing across two layers of O atoms.

Synergistic Gradient Anodes for Long-Term Stability in Aqueous Zinc-Ion Batteries.

The stability of aqueous zinc metal anodes is still constrained by their severe dendrite growth. Optimizing electric field distribution and crystallography to modulate the diffusion and deposition behavior of zinc ions can effectively suppress dendrite growth. However, the fabrication strategy to directly endow specific textured zinc anodes with gradient electric field distribution is still lacking. Herein, a strategy combining crystal reconstruction of commercial zinc foil with graphene oxide (GO) protective layer is proposed to construct an in situ gradient electric field-enhanced strong (002) textured GO@ZnO/Zn(002) anode. Based on the experimental and theoretical results, the GO protective layer can regulate a wide-range homogeneous Zn2+ ions flow, while the dense and uniform ZnO/Zn(002) nanoneedles /nanoparticles can enhance localized polarized electric field to accelerate rapid localized transfer of Zn2+ ions and guide them toward directional deposition along (002) plane. Therefore, the hierarchical GO@ZnO/Zn(002) anode enables the symmetric cell to operate continuously and stably for 5700 and 4200h at 2 and 4mA cm-2, respectively, which is comparable to or better than most high-end Zn anodes. This work presents new insights into the zinc foil reconstruction and gradient electric field fabrication strategy, offering a scalable approach for the development of long-term stable metal anodes.

Direct Measurement of the Diffusion Coefficient of Adhesives from Moisture Distribution in Adhesive Layers Using Near-Infrared Spectroscopy.

In this study, we used near-infrared spectroscopy to measure the moisture penetration in epoxy adhesives and investigated the difference in the diffusion coefficients between the bulk and the adhesive layer. Moisture diffusion was evaluated under 100% RH and water immersion conditions. First, the effects of the curing agents and additives on moisture diffusion in the bulk were gravimetrically evaluated using epoxy-coated quartz glass plates. Different diffusion behaviors were observed depending on the curing agent used. The presence of additives resulted in higher diffusion coefficients, whereas the overall moisture content was low. Next, the moisture distribution in the adhesive layer was visualized using a specimen sandwiched between the quartz glass plates, and the diffusion coefficient of the adhesive layer was calculated. The diffusion coefficient in the adhesive layer was larger than that in the bulk. For adhesives cured with hydrophobic diamine, the diffusion coefficient within the adhesive layer increased by approximately 1.5 times compared with that in the bulk, regardless of the exposure environment. The adhesive, composed of a resin, Dicyandiamide, and additives, showed a 2-fold increase in the diffusion coefficient under high-humidity exposure conditions but no significant change under the water immersion condition. Therefore, these results suggest that, for an accurate analysis of moisture distribution, it is important to measure the diffusion coefficient of the adhesive layer directly rather than using the diffusion coefficient of the material itself.

First-principles study of CoMn2O4-Cr2O3 coherent interface analysis

The CoMn2O4 coating can effectively protect the metallic interconnect of solid oxide fuel cells, which come into direct contact with the naturally occurring Cr2O3 on the matrix surface. However, the properties of CoMn2O4-Cr2O3 interface remain unclear. In this study, the first-principles calculations are utilized to investigate the atom staking, stability, and electronic properties of the CoMn2O4(101)-Cr2O3(001) interface, along with examining the diffusion behavior of Cr atom at the interface. By comparing the adhesion work, the most stable model is determined. Based on the most stable model, the results of electronic structure analysis show that Mn atoms providing vacant orbitals near the conduction band minimum, enhancing the overall conductivity of the interface. The projected density of states metal atoms validates the formation priority of Cr-O bonds. The climbing image nudged elastic band (CI-NEB) method is used to simulate the interstitial diffusion properties of Cr atom at the interface, revealing that the energy barrier is about 3.05 eV. The diffusion coefficients of Cr atom are calculated accordingly. The obtained results can provide theoretical support for relevant experiments and deepen the understanding of the protective effects of spinel coatings on metallic interconnects of solid oxide fuel cells.

Defect related anomalous mobility of small polarons in dielectric oxides at the example of congruent lithium niobate

Polarons play a major role in the description of optical, electrical and dielectrical properties of several ferroelectric oxides. The motion of those particles occurs by elementary hops among the material lattice sites. In order to compute macroscopic transport parameters such as charge mobility, normal (i.e. Fickian) diffusion laws are generally assumed. In this paper we show that when defect states able to trap the polarons for long times are considered, significant deviations from the normal diffusion behaviour arise. As an example of this behavior, we consider here the case of lithium niobate (LN). This can be considered as a prototypical system, having a rich landscape of interacting polaron types and for which a significant wealth of information is available in literature. Our analysis considers the case of a stoichiometric, defect-free lithium niobate containing a certain concentration of small electron polarons hopping on regular Nb sites, and compares it to the material in congruent composition, which is generally found in real-life applications and which is characterized by a large concentration of antisite NbLi defects. While in the first case the charge carriers are free polarons hopping on a regular Nb sublattice, in the second case a fraction of polarons is trapped on antisite defects. Thus, in the congruent material, a range of different hopping possibilities arises, depending on the type of starting and destination sites. We develop a formalism encompassing all these microscopic processes in the framework of a switching diffusion model which can be well approximated by a mobile–immobile transport model providing explicit expressions for the polaron mobility. Finally, starting from the Marcus–Holstein’s model for the polaron hopping frequency we verify by means of a Monte Carlo approach the diffusion/mobility of the different polarons species showing that, while free polarons obey the laws for normal diffusion as expected, bound polarons follow an anomalous diffusion behaviour and that in the case of the congruent crystal where mixed free and bound polaron transport is involved, our expressions indeed provide a satisfactory description.

Robust tissue pattern formation by coupling morphogen signal and cell adhesion

Morphogens, locally produced signaling molecules, form a concentration gradient to guide tissue patterning. Tissue patterns emerge as a collaboration between morphogen diffusion and responsive cell behaviors, but the mechanisms through which diffusing morphogens define precise spatial patterns amidst biological fluctuations remain unclear. To investigate how cells respond to diffusing proteins to generate tissue patterns, we develop SYMPLE3D, a 3D culture platform. By engineering gene expression responsive to artificial morphogens, we observe that coupling morphogen signals with cadherin-based adhesion is sufficient to convert a morphogen gradient into distinct tissue domains. Morphogen-induced cadherins gather activated cells into a single domain, removing ectopically activated cells. In addition, we reveal a switch-like induction of cadherin-mediated compaction and cell mixing, homogenizing activated cells within the morphogen gradient to form a uniformly activated domain with a sharp boundary. These findings highlight the cooperation between morphogen gradients and cell adhesion in robust tissue patterning and introduce a novel method for tissue engineering to develop new tissue domains in organoids.

An atomic insight into effect of grain boundary on diffusion behavior of Cu/Al dissimilar materials undergoing ultrasonic welding

An atomic insight into effect of grain boundary on diffusion behavior of Cu/Al dissimilar materials undergoing ultrasonic welding

Molecular dynamics study of shale oil adsorption and diffusion behavior in reservoir nanopores: Impact of hydrocarbon composition and surface type

Understanding shale oil adsorption in reservoir nanopores is essential for efficient extraction. This study used MD simulations to analyze the adsorption and diffusion of two- and multi-component hydrocarbons (Aromatics, Alkanes, Resin) on various shale surfaces (Calcite, Montmorillonite, Quartzite, Organic) at 353 K and 25 MPa. Hydrocarbons formed a bilayer adsorption structure comprising a high-concentration adsorption layer (L1, 0.35–0.90 g/cm3) and a low concentration weak adsorption layer (L2), with adsorption density ranked as Resin > Aromatics > Alkanes. Reservoir surfaces were classified as ionic (e.g., calcite, montmorillonite) and non-ionic (e.g., quartz, graphite), and polar hydrocarbons exhibited higher adsorption densities and energies on ionic surfaces due to combined electrostatic and van der Waals interactions, while non-ionic surfaces showed smaller adsorption differences. For multicomponent hydrocarbons, adsorption layer densities followed the order: graphite > MMT-SiO > quartz > calcite > MMT-Na, with competitive adsorption observed. The polar component exhibited a greater adsorption advantage on the calcite, MMT-SiO side and graphite surfaces due to electrostatic interactions and π-π interactions, and a lesser advantage on the MMT-Na side and quartz surfaces. Hydrocarbon diffusivity was influenced by molecular mass and polarity and ordered as Alkanes > Aromatics ≫ Resin. Polar molecules had a weaker diffusion than nonpolar molecules at similar molecular masses. Among the multicomponent hydrocarbons, the self-diffusion coefficient (Self-D) of Resin increased, while that of lighter components decreased compared to two-component systems. These findings offer strategies for improving shale oil recovery by tailoring injection fluids to reservoir types, anionic surfactants or chelating agents may be used to reduce electrostatic interactions in carbonate and clay reservoirs, while nonionic surfactants may be more effective in quartz reservoirs.

Ab initio molecular dynamics investigation on hydrogen diffusion behavior in liquid aluminum alloy melts

In this work, ab initio molecular dynamics (AIMD) simulations under both NVT and NPT ensembles were performed to study the influence of alloying elements of Mg, Fe, Si, Ti, Cu, Zn, F, and Cl on the H diffusion behavior in liquid aluminum melt. It is found that the diffusion coefficient of H simulated by AIMD under the NVT model is highly consistent with the reported experimental results. Specifically, the addition of Cu, Cl, Si, and Zn is inclined to increase the diffusion coefficient of H in the melt, whereas the opposite result is observed with the addition of F, Fe, and Ti. Moreover, it is proved that the H diffusion coefficients are positively correlated with the H-Al bond lengths and the coordination number of H in a constant volume system. The obtained results deepen the understanding of the diffusion of H atoms in Al melts and contribute to the optimization of existing melt purification technologies.

Anchoring effect of transition metal dihaloalkanes in lithium-sulfur batteries: A first-principles study

Suppressing the shuttle effect by enhancing the sulfur electrode structure is an effective method to achieve long-term cycle stability of lithium-sulfur batteries. In which, two-dimensional materials are widely used to improve the performance of lithium-sulfur batteries because of their high specific surface area and high electrical conductivity. In this paper, the anchoring effect of NbX2 (X= S,Se,Te) on polysulfides, and the conductivity, stability and diffusion behavior of the adsorption system are studied by using density functional theory calculation. The results show that NbX2 (X= S,Se,Te) has good electrical conductivity and stability, where NbS2 has moderate adsorption strength (0.84–3.28 eV) for lithium polysulfides, and the interaction of S atoms on the surface of Li2S and Nb atoms on the substrate surface is the main source of adsorption energy. In addition, the diffusion potential barrier is low (0.12 eV). The calculated results show that NbS2 may be a potential choice as an anchoring material for Li-sulfur batteries.

Diffusion Coefficients of Coated Plasmonic Nanoparticles in Viscous Environment.

The Stokes-Einstein relationship (SER) is not valid anymore in polymeric solutions for nanoparticles. It is thus important to characterize theirdiffusion properties to get a finer understanding of their behavior and to better tune their attributes for biomedical applications. The diffusion of gold and silver nanoparticles with citrate, hyaluronic acid, methyl-polyethylene glycol, and antibody-polyethylene glycol coatings is studied in hyaluronic-based viscous solutions. The diffusion coefficient D is estimated from the Brownian motion thanks to a cost-effective side-illumination device. It is determined that the nanoparticles (hydrodynamic radius rh: 30-135nm) diffuse up to 4-5 times faster than expected using the SER with a macroscopic viscosity from 1 to 30 mPa·s. It is shown that the adapted Huggins equation is a good model to describe the diffusion behavior of nanoparticles using an effective viscosity ηeff given by where where E is the polymer correlation length, Rh the polymer hydrodynamic radius and ηs the solvent viscosity. The values of k and a are given and allow to obtain D with an error of 10-20%. The impact of chemical interactions on the model parameter values are also highlighted, especially due to electrostatic interactions between the polymer and the nanoparticles.