Diffusion Process Research Articles

Research on new magnetic epoxy resin composite slurry materials and localization grouting diffusion mechanism

A significant number of steep cracks are frequently encountered in underground engineering, posing a threat to operation. The high-pressure grouting method is a commonly utilized repair technique. Nevertheless, conventional grout is prone to displacement due to its weight, making it challenging to ensure adequate filling of the cracks. Therefore, this study aims to develop a grouting material with targeted displacement and anchoring properties. Firstly, an optimal magnetic slurry composition was determined through an orthogonal test. Subsequently, XRD and SEM were used to analyze the impact of the magnetic field on the composition distribution, internal pore structure, and transient viscosity of the slurry. Afterwards, a model for localized grout diffusion under magnetic was established. The results show that the application of a magnetic field caused the slurry to compact due to magnetic forces, reducing its porosity. Moreover, the dynamic viscosity of the slurry increased exponentially with rising magnetic induction intensity. Notably, a 40.5% increase in the diffusion area was observed when the magnetic field intensity rose from 2500 to 4500 GS. The error between the measured and theoretical values of the magnetic slurry diffusion model was only 8.91%, indicating the model's accuracy in describing the slurry diffusion process under magnetic field influence.

A finite volume approach to dosimetric calculations in diffusing alpha-emitters radiation therapy

Objective.In diffusing alpha-emitters radiation therapy ('Alpha DaRT'), the diffusion-leakage (DL) model is used to determine the spatial distributions of the emitters and the corresponding alpha dose, critical for a successful treatment. This work first introduces a finite volume (FV) approach to develop numerical schemes to simulate the DL model in one, two and three dimensions then presents how variations over realistic ranges of the DL model parameters related to desorption, diffusion and leakage processes affect the alpha dose distribution and the position of the clinically significant alpha particle10Gy isodose. This work also presents the effects of three modeling approximations: two source geometry approximations (solid cylinder instead of hollow, pixelized cross section instead of circular), and one dosimetric approximation (single-source dose superposition instead of multiple-sources direct dose calculation).Approach.The introduced FV approach was used to obtain spatial distributions of the emitters, from which the corresponding alpha dose distributions were calculated under the assumption of a local deposition of the alpha particles' energies. Variation ranges of the DL model parameters were based on previously published data. For each modeling approximation studied, the error and relative error on the alpha dose distribution were calculated and the displacement of the10Gy isodose was evaluated.Main results.Over realistic ranges, the desorption probabilities, diffusion lengths, and leakage probabilities affect the position of the alpha particle10Gy isodose by∼0.1mm,∼1.5mm and∼0.5mm, respectively. The three modeling approximations studied have a negligible effect on the alpha particle10Gy isodose position, with displacements⩽0.01mm.Significance.This work quantitatively evaluates the relative importance of different parameters and approximations in Alpha-DaRT alpha dose calculations based on their impact not only on the dose variation at a given distance from the source but also on the displacement of clinically significant isodoses.

Neurogenic Arthropathies of the Lower Limbs: About A Case Followed in Rehabilitation at the Chu-Bogodogo

Abstract we report a case of pelvic limb neurogenic arthropathies (NA) in a young 25-year-old patient following severe cranioencephalic trauma in a road traffic accident. The aim of this clinical case was to report the contribution of physical medicine and rehabilitation in the management of neurogenic arthropathies. The patient was admitted to the Physical Medicine and Rehabilitation Department only six months after his trauma. Nervous system disorders were represented by a frontal syndrome and significant spasticity in the pelvic limbs. Deficiencies founds was pain, multiple joint stiffness of the pelvic limbs, induration of the thighs related to arthropathies objectified to the standard x-ray of the thighs. The rehabilitation approach consisted of postures associated with targeted cryotherapy of the muscles. The gait rehabilitation was done gradually between the parallel bars and then with a deanbulator Rehabilitation led to functional improvement, with the patient returning to independent walking using simple techniques. The presentation of this case study provided an overview of this pathology, its functional consequences and the role of Physical and Rehabilitation Medicine in the management of NA. The techniques we used have made it possible to limit the diffusion processes of neurogenic arthropathies by limiting inflammation through associated cryotherapy sessions. The presence of nervous system disorder such as frontal syndrome could have limited rehabilitation, but thanks to collaboration with psychiatrists the evolution was favorable and allowed the patient to actively participate in his rehabilitationThe case also underlined the importance of multidisciplinary patient management, which should be a goal for all practitioners. Keywords: arthropathies ; cryotherapy ; neurogenic ; rehabilitation ; traumatic brain injury

Non-metal doping enhsances oxygen reduction kinetics and CO2 tolerance of SrFeO3-δ perovskite as high-performance cathodes for solid oxide fuel cells

The sluggish of the oxygen reduction reaction (ORR) kinetics and the susceptibility to CO2 interactions are major barriers to the widespread application of solid oxide fuel cells (SOFCs). In this study, a non-metal cation doping strategy was employed to enhance the ORR catalytic activity and CO2 tolerance of SrFeO3-δ cathode. SrFe1-xPxO3-δ (SFPx, x = 0, 0.05, 0.1, 0.15, 0.2) materials were synthesized by substituting phosphorus (P) for Fe in SrFeO3-δ. The doping of P facilitated the formation of oxygen vacancies in SrFeO3-δ, enhancing oxygen adsorption, dissociation, diffusion, and charge transfer processes, leading to a notable increase in ORR catalytic activity. At 800 ℃, the polarization resistance of SFP0.15 was 0.08 Ω cm2, a reduction of 42.86 % compared to undoped SrFeO3-δ. Additionally, SFP0.15 achieved a peak power density of 749.36 mW cm2, representing a 91.99 % enhancement over SrFeO3-δ. These findings suggest that non-metal cation doping is an effective approach to boost the performance of SrFeO3-δ perovskite cathode.

Analysis of the Use of Qris as Social Change Among Students

Background: This research aims to analyze the use of QRIS as an alternative to digital payments at Hasanuddin University, explore the factors influencing its adoption among students, and provide recommendations for increasing its implementation, while assessing social changes related to the shift from cash to digital money. Objective: This research aims to describe Hasanuddin University students' awareness of the use of QRIS as a digital payment solution and analyze the social changes that occur as a result of the use of QRIS among students. Method: This research uses a quantitative approach with descriptive research type. The population in this study were students registered in the Hasanuddin University FISIP Sociology Masters Program, and the sampling technique in this study was a probability sampling method with types. The type of method used was total sampling where the sample size was the same as the population with the number of research samples being 86 person. Results: The results of this research show that: first, the level of awareness of Hasanuddin University FISIP Masters students regarding the use of the QRIS application as a transaction method is in the "Enough" category with a TCR of 60.093; second, QRIS functions as a social fact that maintains social order by reducing criminal acts and building trust between individuals; third, there are five stages of the innovation diffusion process in the practice of using the QRIS application among students, namely the stages of introduction, persuasion, decision, implementation, and confirmation. Conclusion: Digital awareness in the use of the QRIS application among students of the Master of Sociology FISIP University of Hasanuddin involves seven main aspects: Posthumanism, Human-Machine Interaction, Digital Aesthetics, Fluidity of Identity and Consciousness, Technology and the Evolution of Consciousness, Transcendence of Physical Boundaries, and Interdisciplinarity.

Thermodynamic analysis of MHD Prandtl-Eyring fluid flow through a microchannel: A spectral quasi-linearization approach

In designing efficient micro devices, particularly microchannels used in cooling electronic components and biomedical microfluidic systems, The foremost application explored is the design and optimization of microchannels employed in the electronic device cooling systems. To possess these microchannels from overheating and damaging their gentle electronic components, exact fluid flow and heat transmission regulation are required. To better design cooling systems, engineers can use mathematical models of Prandtl-Eyring fluid flows to antedate temperature and velocity profiles. The entropy generation also helps in optimizing the design for better fluid transport efficiency. Therefore, the present aim is to characterize the impact of dissipative heat along with magnetization in Prandtl-Eyring non-Newtonian fluid via microchannel. The novelty of the study is the assumption of convective thermal boundary conditions that show efficient heat transport phenomena. A set of similarity rules is adopted for the transformation of the governing equations, and a spectral quasi-linearization technique is then utilized for the solution of the designed miniature. One of the special attractions of the proposed study is the analysis of entropy, which is obtained due to the irreversibility processes within the system. However, irreversibility occurs because of heat transfer, diffusion processes, viscous dissipation, etc. The physical behavior of the pertinent factors is deployed graphically, whereas the validation of the result in a particular case is displayed in tabular form. We use a second law analysis to determine the origins of irreversibility in the thermal system. It is evident that an increase in fluid parameters results in a reduction in entropy generation. An augmentation in the Biot number substantially intensifies the Bejan number. The findings suggest that the magnetic parameter and fluid parameter α have a diminishing effect on velocity.

A highly polarizable concentrated dipole glass for ultrahigh energy storage

Relaxor ferroelectrics are highly desired for pulse-power dielectric capacitors, however it has become a bottleneck that substantial enhancements of energy density generally sacrifice energy efficiency under superhigh fields. Here, we demonstrate a novel concept of highly polarizable concentrated dipole glass in delicately-designed high-entropy (Bi1/3Ba1/3Na1/3)(Fe2/9Ti5/9Nb2/9)O3 ceramic achieved via substitution of multiple heterovalent ferroelectric-active principal cation species on equivalent lattice sites. The atomic-scaled polar heterogeneity of dipoles with different polar vectors between adjacent unit cells enables diffuse reorientation process but disables appreciable growth with electric fields. These unique features cause superior recoverable energy density of ~15.9 J cm−3 and efficiency of ~93.3% in bulk ceramics. We also extend the highly polarizable concentrated dipole glass to the prototype multilayer ceramic capacitor, which exhibits record-breaking recoverable energy density of ~26.3 J cm−3 and efficiency of ~92.4% with excellent temperature and cycle stability. This research presents a distinctive approach for designing high-performance energy-storage dielectric capacitors.

Biopharmaceutical studies of a novel sedative sublingual lozenge based on glycine and tryptophan: A rationale for mucoadhesive agent selection

Effective sedative drugs are in great demand due to increasing incidence of nervous disorders. The present work was aimed to develop a novel sublingual sedative drug based on glycine and L-tryptophan amino acids. Carbopol and different hydroxypropyl methylcellulose species were alternatively tested as mucoadhesive agents intended to prolong tryptophan sublingual release time. A model lipid medium of fully hydrated L-α-dimyristoylphosphatidylcholine was used for optimal mucoadhesive agents selection. Simultaneous processes of drug release and diffusion in lipid medium were first investigated involving both experimental and theoretical approaches. Individual substances, their selected combinations as well as different drug formulations were consecutively examined. Application of kinetic differential scanning calorimetry method allowed us to reveal a number of specific drug-excipient effects. Lactose was found to essentially facilitate tryptophan release and provide its ability to get into the bloodstream simultaneously with glycine, which is necessary to achieve glycine-tryptophan synergism. Introduction of a mucoadhesive agent into the formulation was shown to change kinetics of drug-membrane interactions variously depending on viscosity grade. Among the mucoadhesive agents, hydroxypropyl methylcellulose species K4M and E4M were shown to further accelerate drug release, therefore they were selected as optimal. Thus, effectiveness of the novel sedative drug was provided by including some excipients, such as lactose and the selected mucoadhesive agent species. A dynamic mathematical model was developed properly describing release and diffusion in lipid medium of various drug substances. Our study clearly showed applicability of a lipid medium to meet challenges such as drug-excipient interactions and optimization of drug formulations.

Honeycomb-like macroporous crosslinked chitosan assisted EDTA-intercalated Ca-Mg-Al layered hydrotalcite composite foams for efficient U(VI) biosorption

The biosorption is considered to be highly efficient for the separation of radionuclide from radioactive wastewater. Herein, the crosslinked chitosan assisted EDTA intercalated Ca-Mg-Al layered double hydroxides composite foam (CS-EDTA-LDH) was synthesized by combining EDTA intercalation and freeze-drying methods. The macroporous and ultralight properties of CS-EDTA-LDH facilitates its rapid adsorption and facile recovery, and the inorganic/organic incorporation can avoid pore collapse and provide numerous adsorption sites, while the EDTA intercalation can enhance the complex capture of U(VI). The CS-EDTA-LDH presents various functional groups (carboxyl, hydroxyl and amino groups) for U(VI) adsorption, and the adsorption capacity for U(VI) reached 272.3 mg/g at pH 5.0 and 298 K. The adsorption kinetics of U(VI) conformed to PSO equation, whereas the isotherms conformed to the Freundlich model, indicating heterogeneous adsorption with diffusion process as a rate-controlling step. The thermodynamic parameters indicate that U(VI) adsorption by CS-EDTA-LDH is endothermic and spontaneous in nature. The adsorption mechanism is related to the synergic complexation by multi-functional groups, ion exchange, and possible isomeric substitution. Overall, CS-EDTA-LDH could be a promising biosorbent for the cleanup of radioactive pollution due to its high performance for U(VI) adsorption and facile recovery.

Classification of adsorbates in scanning tunneling microscopy images of Fe3O4(111) surfaces exposed to water and carbon monoxide

Understanding the structure of catalyst surfaces with adsorbed molecules is key to improving catalyst design. Scanning tunneling microscopy (STM) allows the observation of adsorption states and sites and provides insights into diffusion and desorption processes; however, the presence of multiple types of molecules on the surface presents challenges such as the identification of species and verification of reaction progress, particularly at room temperature or higher. In this study, we develop a protocol for the height classification analysis of STM images using the Watershed algorithm. This method is applied to a system involving the co-adsorption of H2O and CO on the Fe3O4(111) surface, which represents the beginning of the water-gas shift reaction. Water molecules and dissociated OH species were identified in STM images of the Fe3O4(111) surface following the adsorption of water. Furthermore, gradual changes in the types of surface species were observed upon exposure of the surface to CO, indicating reaction progression. Our observations suggest that CO may react with molecular water rather than with dissociated OH on Fe sites. Despite its simplicity, the height classification analysis effectively identifies changes in the adsorbates on the catalyst surface. This method can be extended to other catalyst surfaces with adsorbed gasses.

Epoxy composite microspheres as a versatile platform for enhancement of chlorophyll dispersion and photostability in coatings

Chlorophyll (Chl), as a rich natural pigment, is limited in applications due to poor photostability. The hydrophobic properties of Chl attributed to the tetrapyrrole ring and terminal long-chain hydrocarbons further constrains its dispersion in aqueous coatings. In this work, chlorophyll/epoxy composite microspheres (Chl/EMs) were prepared as candidate pigments via emulsion polymerization to provide a versatile platform for enhanced dispersion and photostability. The optimal reaction temperature of 75 °C for achieving the appropriate particle size distribution of epoxy microspheres (EMs) was first determined. Chl/EMs were then prepared by (1) the combination of Chl and DGEBA in the emulsification process, or by (2) mixing Chl with m-xylylenediamine (MXDA) during curing. The effects of Chl introduction at different steps on the emulsification, curing agent diffusion, and curing process were studied using off-site microscopy observation and aggregation-induced emission technique, to clarify the structure and morphology evolution during emulsion polymerization. The particle size of the microspheres was mainly determined by the emulsification process of the epoxy precursor. Chl participates in emulsification of Chl/EMs in case (1), resulting in a large average particle size and poor particle size distribution. In case (2), the diffusion of MXDA into epoxy emulsion particles is completed within 30 min and does not impede the quicker diffusion process of Chl which was mixed with MXDA. The prepared Chl/EMs with size ranging from 1 to 10 μm create a conducive oxygen blocking environment. Compared to the complete degradation period of untreated Chl coatings, the photostability of Chl/EMs coatings increased nearly 7-fold. Remarkably, Chl/EMs exhibit superior dispersion capability in waterborne polyurethane coatings compared to pure Chl coatings. The EMs with controllable morphology and size can be used as a versatile platform for enhancing dispersion and photostability of other organic or natural dyes and pigments in waterborne coatings.

Uncovering the stochastic dynamics of solitons of the Chaffee–Infante equation

In this paper, we apply stochastic differential equations with the Wiener process to investigate the soliton solutions of the Chaffee–Infante (CI) equation. The CI equation, a fundamental model in mathematical physics, explains concepts such as wave propagation and diffusion processes. Exact soliton solutions are obtained through the application of the modified extended tanh (MET) method. The obtained wave figures in 3D, 2D, and contour are highly localized and determine an individual frequency shift under the behavior of sharp peak, periodic wave, and singular soliton. The MET method shows to be a valuable analytical tool for obtaining soliton solutions, essential for understanding the dynamics of nonlinear wave phenomena. Numerical simulations enable us to explore soliton solutions in two and three dimensions, shedding light on their properties over time. Our results have wide applications in various domains, including stochastic processes and nonlinear dynamics, impacting advancements in physics, engineering, finance, biology, and beyond.

Diffusion Models-Based Purification for Common Corruptions on Robust 3D Object Detection.

LiDAR sensors have been shown to generate data with various common corruptions, which seriously affect their applications in 3D vision tasks, particularly object detection. At the same time, it has been demonstrated that traditional defense strategies, including adversarial training, are prone to suffering from gradient confusion during training. Moreover, they can only improve their robustness against specific types of data corruption. In this work, we propose LiDARPure, which leverages the powerful generation ability of diffusion models to purify corruption in the LiDAR scene data. By dividing the entire scene into voxels to facilitate the processes of diffusion and reverse diffusion, LiDARPure overcomes challenges induced from adversarial training, such as sparse point clouds in large-scale LiDAR data and gradient confusion. In addition, we utilize the latent geometric features of a scene as a condition to assist the generation of diffusion models. Detailed experiments show that LiDARPure can effectively purify 19 common types of LiDAR data corruption. Further evaluation results demonstrate that it can improve the average precision of 3D object detectors to an extent of 20% in the face of data corruption, much higher than existing defence strategies.

Fast and efficient chromium(VI) extraction by colloidal Mg/Al layered double hydroxide nanoparticles

Due to the constraints associated with diffusion and mixing time, traditional kinetic and thermodynamic approaches were inadequate for probing the true mechanism of interaction between chromate and Layered Double Hydroxide (LDH). To circumvent these limitations, colloidal suspensions of Mg/Al-NO3 LDH, characterized by a positively charged surface (approximately +50 mV) in ultrapure water and a mean average diameter of 140 nm, allowing the formation of stable suspensions for days, were swiftly mixed with Cr(VI) suspensions at both pH = 4 and 9 using a stopped flow technique. This rapid mixing, accomplished in <5 milliseconds, enabled the examination of the initial stages of interaction between the toxic anion and the host compound. Two distinct steps in the adsorption process were identified: a very fast step (completed in <5 ms), representing up to 80% of the measured variation, and a slower step lasting up to 100 s. The fast step assumed to be driven by electrostatic interaction (ζ ∼ +50 mV) with the surface, and sites close to the surface are easily accessible to the chromate anions. The slower step corresponded to a diffusion process close or inside the particles. Chromate extraction efficiency was investigated through ultrafiltration tests, varying the LDH and chromate amounts, indicating that 2 nitrate ions are exchanged for 1 chromate, regardless of the pH considered, and a total exchange can be fulfilled with 0.1 g L−1 of LDH within the explored concentration range.

ScDiffusion: conditional generation of high-quality single-cell data using diffusion model.

Single-cell RNA sequencing (scRNA-seq) data are important for studying the laws of life at single-cell level. However, it is still challenging to obtain enough high-quality scRNA-seq data. To mitigate the limited availability of data, generative models have been proposed to computationally generate synthetic scRNA-seq data. Nevertheless, the data generated with current models are not very realistic yet, especially when we need to generate data with controlled conditions. In the meantime, diffusion models have shown their power in generating data with high fidelity, providing a new opportunity for scRNA-seq generation. In this study, we developed scDiffusion, a generative model combining the diffusion model and foundation model to generate high-quality scRNA-seq data with controlled conditions. We designed multiple classifiers to guide the diffusion process simultaneously, enabling scDiffusion to generate data under multiple condition combinations. We also proposed a new control strategy called Gradient Interpolation. This strategy allows the model to generate continuous trajectories of cell development from a given cell state. Experiments showed that scDiffusion could generate single-cell gene expression data closely resembling real scRNA-seq data. Also, scDiffusion can conditionally produce data on specific cell types including rare cell types. Furthermore, we could use the multiple-condition generation of scDiffusion to generate cell type that was out of the training data. Leveraging the Gradient Interpolation strategy, we generated a continuous developmental trajectory of mouse embryonic cells. These experiments demonstrate that scDiffusion is a powerful tool for augmenting the real scRNA-seq data and can provide insights into cell fate research. scDiffusion is openly available at the GitHub repository https://github.com/EperLuo/scDiffusion or Zenodo https://zenodo.org/doi/10.5281/zenodo.13268742.

Microstructure evolution and degradation mechanisms of amorphous FeCrAlMoSiY coated Zr in 1200 °C steam

Herein, structural evolution and degradation mechanisms of the amorphous FeCrAlMoSiY coating during oxidation up to 16 h in 1200 °C steam was studied, using scanning electron microscopy, transmission electron microscopy, x-ray diffractometer, and Raman spectroscopy. The results revealed that no significant oxidation of the Zr substrate occurred within 12 h, which was attributed to the retarded atomic diffusion processes. These processes were achieved through the Al outward diffusion and formation of α-Al2O3 scale, along with the formation of an in-situ Zr2Si-rich diffusion barrier at the coating-substrate interface and the Y2O3 particles segregated at grain boundaries within the coating. Degradation of the coating was primarily due to the destruction of the α-Al2O3 scale by cracks caused by internal oxidation and voids accumulation. These results have implications for understanding the degradation mechanisms and achieving long-term stable protection of the coatings for Zr-based nuclear fuel claddings.

MADMFuse: A multi-attribute diffusion model to fuse infrared and visible images

In the field of deep learning vision, infrared and visible image fusion (IVIF) has received significant attention due to its ability to enhance scene comprehension by combining the complementary features of both types of images. Existing methods based on generative models are either unstable in training, such as generative adversarial network, or only have a single denoising object, such as diffusion models, resulting in poor fused results that cannot fully contain multi-modal features. To solve these problems, we propose a multi-attribute diffusion model to fuse infrared and visible images, termed MADMFuse. Specifically, to preserve the salient information in infrared images and the texture details in visible images, we have designed a forward diffusion process with shared noise for multiple independent attributes, ensuring that the denoising network learns complementary features of different attributes simultaneously during training. Subsequently, our reverse process with multi-attribute as conditions employs the denoising network that iteratively reparameterizes noise, gradually adjusting and achieving fine image fusion. Furthermore, to address the issue of feature degradation resulting from solely focusing on a single denoising object, we derive a multiple diffusion object loss function based on pixel-level fusion target, the fidelity and luminance term in this loss function aim to guide the fused results towards visual similarity with the source image while preserving its brightness. Extensive experiments indicate that MADMFuse is more effective than other state-of-the-art image fusion methods.

High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark

Vast amounts of pathogen genomic, demographic and spatial data are transforming our understanding of SARS-CoV-2 emergence and spread. We examined the drivers of molecular evolution and spread of 291,791 SARS-CoV-2 genomes from Denmark in 2021. With a sequencing rate consistently exceeding 60%, and up to 80% of PCR-positive samples between March and November, the viral genome set is broadly whole-epidemic representative. We identify a consistent rise in viral diversity over time, with notable spikes upon the importation of novel variants (e.g., Delta and Omicron). By linking genomic data with rich individual-level demographic data from national registers, we find that individuals aged < 15 and > 75 years had a lower contribution to molecular change (i.e., branch lengths) compared to other age groups, but similar molecular evolutionary rates, suggesting a lower likelihood of introducing novel variants. Similarly, we find greater molecular change among vaccinated individuals, suggestive of immune evasion. We also observe evidence of transmission in rural areas to follow predictable diffusion processes. Conversely, urban areas are expectedly more complex due to their high mobility, emphasising the role of population structure in driving virus spread. Our analyses highlight the added value of integrating genomic data with detailed demographic and spatial information, particularly in the absence of structured infection surveys.

Gate-Switchable Molecular Diffusion on a Graphene Field-Effect Transistor.

Controlling the surface diffusion of particles on 2D devices creates opportunities for advancing microscopic processes such as nanoassembly, thin-film growth, and catalysis. Here, we demonstrate the ability to control the diffusion of F4TCNQ molecules at the surface of clean graphene field-effect transistors (FETs) via electrostatic gating. Tuning the back-gate voltage (VG) of a graphene FET switches molecular adsorbates between negative and neutral charge states, leading to dramatic changes in their diffusion properties. Scanning tunneling microscopy measurements reveal that the diffusivity of neutral molecules decreases rapidly with a decreasing VG and involves rotational diffusion processes. The molecular diffusivity of negatively charged molecules, on the other hand, remains nearly constant over a wide range of applied VG values and is dominated by purely translational processes. First-principles density functional theory calculations confirm that the energy landscapes experienced by neutral vs charged molecules lead to diffusion behavior consistent with experiment. Gate-tunability of the diffusion barrier for F4TCNQ molecules on graphene enables graphene FETs to act as diffusion switches.

A hybrid yang transform adomian decomposition method for solving time-fractional nonlinear partial differential equation

Nonlinear time-fractional partial differential equations (NTFPDEs) play a great role in the mathematical modeling of real-world phenomena like traffic models, the design of earthquakes, fractional stochastic systems, diffusion processes, and control processing. Solving such problems is reasonably challenging, and the nonlinear part and fractional operator make them more problematic. Thus, developing suitable numerical methods is an active area of research. In this paper, we develop a new numerical method called Yang transform Adomian decomposition method (YTADM) by mixing the Yang transform and the Adomian decomposition method for solving NTFPDEs. The derivative of the problem is considered in sense of Caputo fractional order. The stability and convergence of the developed method are discussed in the Banach space sense. The effectiveness, validity, and practicability of the method are demonstrated by solving four examples of NTFPEs. The findings suggest that the proposed method gives a better solution than other compared numerical methods. Additionally, the proposed scheme achieves an accurate solution with a few numbers of iteration, and thus the method is suitable for handling a wide class of NTFPDEs arising in the application of nonlinear phenomena.