Diffusion Properties Research Articles

Microstructure and Mechanical Properties of Ti/Al-SiC/Ti Clad Plates Prepared via the Powder-in-Tube Method.

SiC particle-reinforced Ti/Al/Ti clad plates were successfully fabricated by the powder-in-tube method. The surface micrography, element diffusion, peeling strength and tensile property of clad plates were studied after annealing and cold rolling. The experimental results show that 6 wt.% is optimal. The presence of SiC particles has been seen to significantly enhance the diffusion of Ti and Al elements. Additionally, it has been observed that the diffusion width of the intermetallic compound (IMC) increases as the size of SiC particles grows. However, it is worth noting that the average of Ti/Al-SiC/Ti clad plates initially increases and subsequently falls. The optimized diffusion thickness of the Ti/Al-SiC/Ti clad plate's IMC layer determined via the powder-in-tube method is approximately 4.5 μm. The 1 μm SiC-reinforced Ti/Al/Ti clad plate can obtain the best mechanical properties after annealing at 500 °C and further hot rolling, and the peeling strength, ultimate tensile strength and elongation are 31.5 N/mm, 305 MPa and 26%, respectively. The efficacy of Ti/Al-SiC/Ti clad plates in delivering exceptional performance is substantiated by the analysis of peeling surfaces, peeling tests and tensile testing, which collectively demonstrate the presence of compact and homogenous intermetallic compounds.

A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal.

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.

Strongly damped wave equations with mass-like terms of the logarithmic-Laplacian

We consider strongly damped wave equations with logarithmic mass-like terms with a parameter θ∈(0,1]. This research is a part of a series of wave equations that was initiated by Charão-Ikehata [6], Charão-D'Abbicco-Ikehata considered in [5] depending on a parameter θ∈(1/2,1) and Piske-Charão-Ikehata [26] for small parameter θ∈(0,1/2). We derive a leading term as t→∞ of the solution, and by using it, a growth and a decay property of the solution itself can be precisely studied in terms of L2-norm. An interesting aspect appears in the case of n=1, roughly speaking, a small θ produces a diffusive property, and a large θ gives a kind of singularity, expressed by growth rates.

Modification of Misfit-Layered Cathode Materials for Improving Electrocatalyic Activity in Reversible Protonic Ceramic Cells

The demand for sustainable regeneration energies such as solar and wind has been continuously increasing by the rise of environmental issues. However, several major technical issues such as intermittent electricity production and high system construction cost are major obstacles to large-scale commercialization for regeneration energies [1]. Reversible protonic ceramic cells (RPCCs) can be an alternative choice because of their high efficiency, long-term durability at intermediate temperatures, and bifunctionality for producing both hydrogen and electricity in an electrochemical device [2]. Until now, perovskite-structured cathode (air/steam electrode) materials have been in spotlight due to their fast oxygen reaction kinetics in RPCCs [3]. However, in spite of their high electrocatalytic activity for oxygen electrode reactions (oxygen evolution and reduction), low phase stability in humid atmospheres, thermal expansion mismatch to common proton electrolytes, and relatively low proton conductivity of RPCCs are still major obstacles to enter the era of hydrogen economy [4, 5]. Hence, we demonstrate novel misfit-layered structure Ca3Co4O9+δ (CCO)-based materials to overcome these technical issues with superior catalytic activity for high performance RPCCs. The thermal expansion coefficient value of CCO is 10-12×10−6 K−1, which is relatively similar to that of the BaCeO3-based proton electrolytes, implying that the CCO-based materials are thermo-mechanically stable during cell operations [6]. In addition, the needle-like morphology of the CCO-based materials is quite valuable in the supply of steam (or air) to the catalytic active sites and elimination the water produced by the electrochemical reaction. Furthermore, with the doping of alkali metal ion (Li, Na, and K) into Ca-site, CCO generates extra charge carrier species with the modified Co oxidation state. This triggers the proton uptake and diffusion properties of CCO-based materials with the improved electrical conductivity. As a result, 5 mol% Na-doped CCO-cell shows exceptionally high performance in both protonic ceramic fuel cell and electrolysis cell modes for RPCCs.

(Invited) Additives Approach to Improve the Performance of LiNi0.5Mn1.5O2 5V Cathodes

The high voltage spinel cathode of LiNi0.5Mn1.5O2 has an average working voltage of 4.7 V, high-rate performance with faster diffusion properties, and is viewed as one of the promising cathode materials for high energy lithium-ion batteries. The lack of Co in such cathode materials is also advantageous due to the issues of artisan mining and geopolitical tensions associated with Co mining. However, the high working voltages in LiNi0.5Mn1.5O2 exceeds the stability of electrolyte window and the redox center in the cathode materials is mainly Ni2+ while Mn stays at the 4+ charge state. Due to the dominance of the Mn elements in the cathode, acid leaching from the impurity of the electrolytes can cause Mn dissolution, and the degradation of LNMO//Gr is associated with transition metal dissolution and crosstalk to the anode side, causing loss of inventory Li loss. For example, the decomposition of ethylene carbonate leads to formation of glycolic acid and difluorophosphoric acid (HPO2F2).Using additives in the electrolyte formulation is an economic way of improving the performance without significant change in either the processing industry or manufacturing technology, and here we present the approach of using a combinatorial approach to optimize the additives for LNMO//Gr full cells. The degradation mechanism will also be discussed. Machine learning (ML) method has been used effectively to predict molecular structures, preferred quantity, as well as formation of interfaces.1-3 In this study, we used ML to formulate the high-performance additives with both improved capacity retention and reduced initial and final impedance. Okamoto, Y.; Kubo, Y., Ab Initio Calculations of the Redox Potentials of Additives for Lithium-Ion Batteries and Their Prediction through Machine Learning. ACS Omega 2018, 3 (7), 7868-7874.Bhowmik, A.; Castelli, I. E.; Garcia-Lastra, J. M.; Jørgensen, P. B.; Winther, O.; Vegge, T., A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning. Energy Storage Materials 2019, 21, 446-456.Hildenbrand, F.; Aupperle, F.; Stahl, G.; Figgmeier, E.; Sauer, D. U., Selection of Electrolyte Additive Quantities for Lithium-Ion Batteries Using Bayesian Optimization. Batteries & Supercaps 2022, 5 (7), e202200038.

GaN/graphene heterostructures as promising anode materials for Li-ion batteries

In this research, the properties of GaN monolayer, defective GaN monolayer with N vacancies (GaN-VN), and van der Waals (vdW) heterostructures composed of them and graphene (GaN/graphene, GaN-VN/graphene) are systematically investigated using density functional theory (DFT), which includes assessment of the structure's stability, mechanical property, electronic structure analysis, lithium adsorption and diffusion properties, maximum theoretical capacity, and average open-circuit voltage. The calculations show that two-dimensional GaN transforms from semiconductor to metal by forming nitrogen-vacancy defects. This increases lithium adsorption performance while ensuring rapid electron motion in the electrode during lithium adsorption and removal processes. The synergistic effect between the heterostructure layers and the presence of the built-in electric field improves the electron and ion conductivity and lowers the migration energy barriers. In addition, the maximum theoretical capacities of defective GaN-VN, GaN/graphene, and GaN-VN/graphene can reach 970 mAh/g, 884 mAh/g, and 890 mAh/g, respectively, far exceeding those of the conventional graphite anode material (372 mAh/g). The above advantages indicate that defective GaN-VN, GaN/graphene, and GaN-VN/graphene are potential replacements for lithium-ion battery anodes.

Simultaneously Probing Gaseous Diffusion and Adsorption Properties in Porous Materials Using Molecular Dynamics Simulations

Simultaneously Probing Gaseous Diffusion and Adsorption Properties in Porous Materials Using Molecular Dynamics Simulations

Theoretical prediction of chloride diffusion into concrete compared to natural chloride contamination of existing bridges

A large number of bridges in Slovakia currently show signs of significant deterioration. These are predominantly prestressed and reinforced concrete bridges affected by chemicals used for winter infrastructure maintenance, mainly de-icing salts. Growing concerns about the progressive salinisation of concrete are creating pressure to refine the diffusion models currently used for predictions. Their reliability for structures in natural conditions proves problematic due to simplifying assumptions or the unknown inputs for the existing construction material. This article aimed to create a theoretical particle simulation model for a more accurate prediction of concrete contamination with chlorides promoted by carbonation based on data obtained from existing bridges. The proposed simulation model works based on Einstein’s – Brownian random walk particle model with consideration of non-interacting particle movement. The unknown diffusion properties of concrete are replaced by the probability of particle diffusion, which is obtained by iteration based on the satisfaction of convergence criteria determined from laboratory-measured concentrations of chlorides. The natural chloride profile is simulated considering a sharp-moving carbonation front, where different diffusion probabilities of particles are assumed in the carbonated and intact zone of the concrete at each time step. After obtaining the diffusion probabilities in the concrete cover, it is possible to predict the evolution of the chloride concentration. The paper further presents data obtained from two bridges whose piers are in close proximity to the traffic lanes.

Anomalous Diffusion of Helium and Neon in Low-Density Silica Glass.

The diffusion properties of low-density non-porous silica glasses (expanded silica glasses) were researched with the aim of searching for the molecular structure of membrane materials intended for the effective separation of helium-neon gas mixtures. It has been shown on a large number (84) of computer models of such glasses that there are molecular structures of silica in which various helium and neon diffusion mechanisms are simultaneously implemented: superdiffusion for helium and subdiffusion for neon. This makes it possible to significantly (by 3-5 orders of magnitude) increase the helium permeability of such glasses at room temperature and maintain a high selectivity for the separation of helium and neon (at the level of 104-105) at the same time.

Altered corpus callosum structure in adolescents with cerebral palsy: connection to gait and balance.

Cerebral palsy (CP) is the most common motor disorder in childhood. Recent studies in children with CP have associated weakened sensorimotor performance with impairments in the major brain white-matter (WM) structure, corpus callosum (CC). However, the relationship between CC structure and lower extremity performance, specifically gait and balance, remains unknown. This study investigated the transcallosal WM structure and lower limb motor stability performance in adolescents aged 10-18 years with spastic hemiplegic (n = 18) or diplegic (n = 13) CP and in their age-matched controls (n = 34). The modern diffusion-weighted MRI analysis included the diffusivity properties of seven CC subparts and the transcallosal lower limb sensorimotor tract of the dominant hemisphere. Children with CP had comprehensive impairments in the cross-sectional area, fractional anisotropy, and mean diffusivity of the CC and sensorimotor tract. Additionally, the extent of WM alterations varied between hemiplegic and diplegic subgroups, which was seen especially in the fractional anisotropy values along the sensorimotor tract. The diffusion properties of transcallosal WM were further associated with static stability in all groups, and with dynamic stability in healthy controls. Our novel results clarify the mechanistic role of the corpus callosum in adolescents with and without CP offering valuable insight into the complex interplay between the brain's WM organization and motor performance. A better understanding of the brain basis of weakened stability performance could, in addition, improve the specificity of clinical diagnosis and targeted rehabilitation in CP.

A Novel Na4MnCr(PO4)2F3 Cathode with High Energy Density for Sodium-Ion Batteries.

Na3V2(PO4)2F3 (NVPF) is a representative cathode material of sodium-ion batteries (SIBs) due to its high working voltage and high structural stability. However, its specific capacity is limited to the reversible inserting and extracting of two sodium ions per formula unit, which hampers the improvement of its energy density. In this study, we propose a new NASICON-type Na4MnCr(PO4)2F3 (NMCPF) cathode and systematically investigate its key properties using first-principles calculations. NMCPF exhibits the ability to extract/insert three sodium ions per formula unit, resulting in a high specific capacity of 180.34 mAh/g, and demonstrates three-electron redox reactions involving three redox couples of Mn2+/3+ (3.05 V), Mn3+/4+ (4.11 V), and Cr3+/4+ (4.64 V). Consequently, its energy density can reach 709.33 Wh/kg. In addition, NMCPF exhibits a small volume change of 8.2% during the charging/discharging process and sodium ion diffusion properties comparable to those of NVPF. This study demonstrates the potential of NMCPF as a promising cathode material with high energy density for SIBs.

The diffusion characteristics of POSS under electric field and non-uniform temperature field in natural ester insulating oil

The natural ester insulating oil is a green and environmentally friendly liquid dielectric, and nano additives can effectively improve its dielectric and heat transfer performance. However, nano additives are prone to agglomeration, especially under the influence of electric and temperature fields, which can impact the prolonged stable operation of power transformers. In this paper, the diffusion properties of caged Polysilsesquioxane (POSS) molecules in natural ester insulating oil under external electric field and non-uniform temperature field were investigated via simulation, and the effects of temperature and electric field on POSS molecules were expounded from the perspective of interaction. The results show that the high temperature difference and strong electric field can effectively improve the mobility of POSS molecules, and the temperature difference has a greater impact on the diffusion. The decrease of interaction energy is mainly due to the negative positive interaction between Si-O molecules in POSS molecules and insulating oil at high temperature, which counteracts the attraction of branch chains. At the same time, POSS molecules in the electric field will also show obvious polarization due to temperature changes, which further reduces the interaction between POSS molecules and insulating oil molecules. In addition, the electrostatic interaction energy decreases most obviously, which is the main reason that affects the migration characteristics of POSS molecules in natural ester insulating oil. This study provides a theoretical explanation for the migration mechanism of insulating oil in the microenvironment.

The entropy production of stationary diffusions

The entropy production rate is a central quantity in non-equilibrium statistical physics, scoring how far a stochastic process is from being time-reversible. In this paper, we compute the entropy production of diffusion processes at non-equilibrium steady-state under the condition that the time-reversal of the diffusion remains a diffusion. We start by characterising the entropy production of both discrete and continuous-time Markov processes. We investigate the time-reversal of time-homogeneous stationary diffusions and recall the most general conditions for the reversibility of the diffusion property, which includes hypoelliptic and degenerate diffusions, and locally Lipschitz vector fields. We decompose the drift into its time-reversible and irreversible parts, or equivalently, the generator into symmetric and antisymmetric operators. We show the equivalence with a decomposition of the backward Kolmogorov equation considered in hypocoercivity theory, and a decomposition of the Fokker-Planck equation in GENERIC form. The main result shows that when the time-irreversible part of the drift is in the range of the volatility matrix (almost everywhere) the forward and time-reversed path space measures of the process are mutually equivalent, and evaluates the entropy production. When this does not hold, the measures are mutually singular and the entropy production is infinite. We verify these results using exact numerical simulations of linear diffusions. We illustrate the discrepancy between the entropy production of non-linear diffusions and their numerical simulations in several examples and illustrate how the entropy production can be used for accurate numerical simulation. Finally, we discuss the relationship between time-irreversibility and sampling efficiency, and how we can modify the definition of entropy production to score how far a process is from being generalised reversible.

Anion‐based regulating mechanism of structural and diffusive property of ionic liquids

AbstractUnderstanding the regulating mechanism of diffusive properties of ionic liquids (ILs) is vital for their practical chemical engineering applications. Herein, we investigate the regulating mechanism of three properties, the structural, thermodynamical, and diffusive properties, of imidazole ILs with 18 kinds of anion via molecular dynamics simulations combined with theoretical analysis. It shows that the radial distribution function and coordinate number for these 18 ILs are similar to each other. However, the vibrational spectrum and diffusive property change greatly with the anion structure, in which the self‐diffusive coefficient (SDC) even changes by an order of magnitude. Furthermore, free energy and entropy have an exponential relationship with SDC, while other structural properties or cation–anion correlations cannot be directly related to SDC. These quantitative relationships suggest that entropy or free energy can serve as the key indicators in designing functional ILs for high‐performance applications in the chemical engineering field.

Effect of wire diameter on structure and electrical properties of (Al + Al2O3)-sheathed MgB2 with Nb barrier

Effect of wire diameter and annealing on the properties of internal magnesium diffusion (IMD)-processed MgB2 composite wires is studied by establishing a correlation with the characteristics of the interfacial reaction zones developed at Mg − B and barrier (Nb) – sheath (Al + Al2O3) interfaces. The MgB2 superconductor phase grows at the Mg − B interface along with the B-rich MgB4 phase. Formation of MgB2 prior to MgB4 is anticipated owing to a relatively lower Gibbs free energy at annealing temperatures studied. An intermetallic NbAl3 phase has developed at the barrier – sheath interface whose thickness decreases with an increase in the wire diameter. Development of NbAl3 further provides mechanical reinforcement and aids at yielding a dense superconductor phase. Resistivity – voltage characteristics of wire indicates the formation of MgB2 through a huge drop in resistivity values across the core of the wire. An annealing temperature of 645 °C near the melting point of pure Mg (650 °C) and annealing time of 120 min results in highest critical current of the MgB2 wire. Annealing time beyond 120 min has shown an impediment to the flow current due to crack propagation possibly because of accumulation of stresses within the developed superconductor phase due to grain growth. A significantly greater resistance for the wire with the smallest diameter is attributed to the formation of a thicker NbAl3 phase. However, highest engineering current density has also been attained by the wire with the smallest diameter annealed at 645 °C for 60 min.

Minimal Coarse-Grained Model for Immunoglobulin G: Diffusion and Binding under Crowding.

Immunoglobulin G (IgG) is the most common type of antibody found in blood and extracellular fluids and plays an essential role in our immune response. However, studies of the dynamics and reaction kinetics of IgG-antigen binding under physiological crowding conditions are scarce. Herein, we develop a coarse-grained model of IgG consisting of only six beads that we find minimal for a coarse representation of IgG's shape and a decent reproduction of its flexibility and diffusion properties measured experimentally. Using this model in Brownian dynamics simulations, we find that macromolecular crowding affects only slightly the IgG's flexibility, as described by the distribution of angles between the IgG's arms and stem. Our simulations indicate that, contrary to expectations, crowders slow down the translational diffusion of an IgG less strongly than they do for a smaller Ficoll 70, which we relate to the IgG's conformational size changes induced by crowding. We also find that crowders affect the binding kinetics by decreasing the rate of the first binding step and enhancing the second binding step.

The Role of Self-Catalysis Induced by Co Doping in Nonaqueous Li-O2 Batteries.

This work systematically studies the product self-catalysis of in situ electrochemical cobalt doping of Li2O2 and reveals its potential mechanism for improving the performance of lithium-oxygen (Li-O2) batteries. Theoretical calculations demonstrate that the discharge products contain substituted and interstitial Co impurities, which serve as active sites to promote the formation of Li3O4 crystallization, thus switching the nucleation mechanism from the main discharge product Li2O2 to Li3O4. This Co-doping behavior leads to the thermodynamically favorable and dynamically stable formation of Li3O4 crystals during the discharge process. Through systematic investigation of the structural, energetic, electronic, diffusive, and catalytic properties of the Co-doped Li2O2 and Li3O4 compounds, we found that Li3O4 has better charge/mass transport and a lower overpotential for the Li3O4 formation/decomposition reaction. Consequently, this work elucidates that Co doping provides a simple and effective approach for increasing the proportion of Li3O4, which can significantly improve the Li-O2 battery performance.

Data-driven predictions of complex organic mixture permeation in polymer membranes

Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures.

A novel approach of 19F NMR based sensor

Reliable and precise methods are to be applied ranging from biological field to diagnosis and quality control to identify target analytes in samples. Nuclear magnetic resonance (NMR) is a strongly recommended process that is suitable for collecting data multidimensionally at molecular and atomic levels. Information obtained from the NMR technique provides molecular structures, molecular interactions, dynamic and diffusional properties of molecules. Overlapping of NMR signals of each component makes it difficult to interpret data and low sensitivity makes it unfitting for many samples with a low concentration of analytes. These limitations can be rectified by adding heteronuclear specially designed sensors, inventive transduction mechanism and strong pulse sequences. 19F NMR tool is extensively accepted method to detect the interactions among a variety of biological substrates with 19F-isotopic species. This review includes the detection of biomolecules, mainly enzymes and enzymatic reactions based on sensor applicability.

Optimization of ammonium fluoride route to hierarchical ZSM-5 zeolites

Preparation of hierarchical zeolites via a chemical etching is a hot topic as it strongly improves microporous material's diffusive properties and thus their catalytic activity. However, an issue that is often neglected is the softening the post-treatment condition. Herein we report the optimization of NH4F etching, using less concentrated solutions and milder treatment conditions. Following characterization by ICP-AES, XRD, 27Al MAS NMR, TEM, and N2 physisorption, it has been shown that it is possible to soften the post-treatment conditions by playing with three synthesis parameters: (1) Decreasing the NH4F/ZSM-5 wt/wt ratio allows the generation of mesopores of different diameter (from 27 to 55 nm); (2) Decreasing the etching time provides precise control over the textural properties of the hierarchical ZSM-5; (3) Decreasing the initial NH4F weight concentration also allows to tune the pore diameter from large (55 nm) to a small mesopore (5 nm).