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Nanomedicine: Could It Be a Boon for Pulmonary Fungal Infections?
Published in Sarwar Beg, Mahfoozur Rahman, Md. Abul Barkat, Farhan J. Ahmad, Nanomedicine for the Treatment of Disease, 2019
Biswajit Mukherjee, Ashique Al Hoque, Shreyasi Chakraborty, Leena Kumari, Somdatta Roy, Paramita Paul
Apart from impaction and sedimentation, Brownian motion plays a major role in the deeper alveolar areas of the lungs. Brownian motion is the random microscopic motion of small particles due to the numerous random collisions by gas molecules. In the small airways where the distance is short and residence time is long, diffusion is an important mechanism for the deposition of small particles (<0.5 μm). Macroscopically, we see the overall movement of particles from a higher concentration region (i.e., the center of air stream) to a lower concentration region (i.e., the airway wall). Since it is caused by gas molecule collisions, the effectiveness of this mechanism increases as particle size decreases. The Brownian motion of the surrounding molecules of the aqueous lung surfactant causes a random movement of the particles. Upon contact with the lung surfactant, the dissolution of the drug in alveolar fluid is essential for diffusion. Additionally, the concentration gradient also influences the diffusion process. Particles smaller than 1 to 0.5 μm are deposited in the alveolar region, while most of the particles, owing to smaller sizes, are exhaled.
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Published in Richard C. Dorf, Circuits, Signals, and Speech and Image Processing, 2018
J. Gregory Rollins, Sina Balkir, Peter Bendix
Here, A and B are experimentally determined constants, different for each type of impurity (x, +, −, =). B is the activation energy for the process. This expression derives from the Maxwellian distribution of particle energies and will be seen many times in process simulation. It is easily seen that the diffusion process is strongly influenced by temperature. The term FIV is an enhancement factor which is dependent on the concentration of interstitials and vacancies within the crystal lattice (an interstitial is an extra silicon atom which is not located on a regular lattice site; a vacancy is a missing silicon atom which results in an empty lattice site) FIV ∝ CI + Cv. The concentration of vacancies, Cv, and interstitials, CI, are in turn determined by their own diffusion equation: ∂Cv∂t=+∇⋅Dv⋅∇Cv−R+G
Stochastic modelling of the diffusion coefficient for concrete
Published in H. Furuta, M. Dogaki, M. Sakano, Reliability and Optimization of Structural Systems, 2018
It follows from (2) that the time to corrosion imitation is inversely proportional in D. It is therefore of great interest to get a good estimate of D. According to extensive experimental investigations (Jensen 1998, Jensen et al. 1999) it can be concluded that the most important factors are the water/cement (w/c) ratio, the temperature Φ, and the amount of e.g. silica fume (s.f.) The experiments show that the diffusion coefficient D increases significantly with w/c as well as with the temperature Φ. The influence of w/c and the temperature Φ may be explained by the chloride binding. Only the free chloride is important for the diffusion coefficient D. With increased w/c ratio less chloride is bound and therefore D is increased. The strong influence of the temperature is mainly caused by thermal activation of the diffusion process, but may also be due to a reduced chloride binding when the temperature is increased. The purpose of the paper is to use the experimental results in (Jensen 1998, Jensen et al. 1999) to make an improved stochastic modelling of the diffusion coefficient D, see also (Thoft-Christensen, 2001, 2002).
Experimental measurements of the moisture diffusion and strength damage mechanism of dense asphalt mixtures
Published in International Journal of Pavement Engineering, 2023
Qinglin Guo, Lili Li, Yubo Jiao, Meng Guo, Wensheng Wang, Weiwei Yu, Wenli He
As shown in Figure 6, there are rapid increases in the diffusion depth in the first two days, which indicates that moisture quickly diffuses into the mixture during the initial stage. Then, the depth of diffusion increases gradually. Although the diffusion rate drops, moisture keeps moving into the deep position of the mixture. Based on the results at different temperatures, it is obvious that the depth and rate of moisture diffusion at 40°C are higher than those at 5 and 20°C. The difference between 5°C and 20°C is not obvious. The rate of moisture diffusion at low temperatures is roughly the same as that at medium temperatures. High temperature accelerates the diffusion process. In addition, there are still some differences between the experimental results and numerical results. This is because the numerical analysis is based on a 2D perspective. In fact, water can also diffuse through the third-dimensional path during soaking. The complexity and random structure of the mixture bring about these differences.
Impact of fractional strain on medium containing spherical cavity in the framework of generalized thermoviscoelastic diffusion
Published in Journal of Thermal Stresses, 2023
Geetanjali Geetanjali, Pawan Kumar Sharma
With temperature or stress gradient in thermoelastic solid, substances (atoms, molecules, and ions etc.) may exhibit small amplitude vibrations about their equilibrium position and hence causing movement from one position to the other. This random movement of substance in a material is known as diffusion. Basically, the diffusion process is modeled by Fick’s law which interprets that mass flux in the medium is proportional to concentration gradient. This law does not consider the interrelation of the infused substance and the medium to which it is infused or the coupling of thermal effects in this process. To incorporate such effects, Nowacki [31] introduced the theory of thermoelastic diffusion by considering classical coupled thermoelastic model. Hence, according to this model, thermal and elastic waves propagate with an infinite speed. To overcome this drawback, a generalization of coupled thermoelastic diffusion theory was developed in frame of LS model by Sherief et al. [32] for isotropic medium where uniqueness and reciprocity theorem are also proved with variational principle. Gilhotra and Sharma [33] discussed spherical cavity problem under unified model of generalized thermoelastic diffusion with nonlocal elastic effects whereas thermal and diffusion phenomenon are memory dependent. Atwa et al. [34] presented the effect of two temperature and three phase lags on half space considering generalized thermoelastic diffusion model. Li et al. [35] studied a problem of thermoelastic sandwich plate considering fractional order strain and diffusion effects.
A novel mathematical model on generalized thermoelastic diffusion theory
Published in Journal of Thermal Stresses, 2023
Kamalesh Paul, Basudeb Mukhopadhyay
We can define “Diffusion” as a random transportation of assemblies of molecules from a high-concentration region to a low-concentration region until the system goes to equilibrium. The important of advanced technologies in the years before, during and after the second world-war has clearly influenced investigations that could not ignore the field of diffusion and temperature in solid materials. At any kind of temperature, mass and heat transport processes play a vital role in many satellites problems and aircraft landing on land or water. Nowadays, diffusion in solids is fundamental in art and science of materials in the topic of solid state physics, physical metallurgy and material engineering. Further, oil companies are concerned with thermo-diffusion processes to exact oil more efficiently than oil deposit. Diffusion process has industrial applications like optimal extraction of oil from hydrocarbon reservoirs, fabrication of semi-conductor devices in mixture metal and molten semi-conductor, separation of types like polymers and manipulations of macro-molecules like DNA, etc.