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1

Gordillo, Jorge A. "Effective Diffusion Coefficient". Defect and Diffusion Forum 384 (maggio 2018): 130–35. http://dx.doi.org/10.4028/www.scientific.net/ddf.384.130.

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Abstract (sommario):
The diffusion of a B element into an A matrix was studied by the random walk theory. Considering that concentration of B element in the A matrix is very low, the jumps of diffusing atoms are independent of each other. The A matrix is a two-region material with different properties, such as a two-phase material, a single crystal with dislocations, or regions influenced by other solute and a polycrystalline material.It is assumed that material B has a penetration that allows it to cross each region of material A several times. This implies that jumps across the surface between those regions have an average frequency and, as a consequence, there is an interdiffusion coefficient between them. The interdiffusion coefficient between those regions is different than the coefficient of the diffusion in each region.Expressions were obtained that allow to delimit the ranges of validation with greater precision than the corrected Hart-Mortlock equation for solute diffusion. In addition, an original relationship was obtained between the segregation coefficient and parameters specific to the diffusion. New powerful tools were also found that can help to understand diffusion in nanocrystalline materials, diffusion in metals influenced by impurities and diffusion produced by different mechanisms.
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2

Rah, Kyunil, Sungjong Kwak, Byung Chan Eu e Michel Lafleur. "Relation of Tracer Diffusion Coefficient and Solvent Self-Diffusion Coefficient". Journal of Physical Chemistry A 106, n. 48 (dicembre 2002): 11841–45. http://dx.doi.org/10.1021/jp021659p.

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3

Mauvy, F., J. M. Bassat, E. Boehm, P. Dordor, J. C. Grenier e J. P. Loup. "Chemical oxygen diffusion coefficient measurement by conductivity relaxation—correlation between tracer diffusion coefficient and chemical diffusion coefficient". Journal of the European Ceramic Society 24, n. 6 (gennaio 2004): 1265–69. http://dx.doi.org/10.1016/s0955-2219(03)00500-4.

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4

Neumann, Gerhard, e C. Tuijn. "Diffusion Mechanisms: The Vacancy Diffusion Coefficient". Solid State Phenomena 88 (novembre 2002): 19–20. http://dx.doi.org/10.4028/www.scientific.net/ssp.88.19.

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5

Graaff, R., e J. J. Ten Bosch. "Diffusion coefficient in photon diffusion theory". Optics Letters 25, n. 1 (1 gennaio 2000): 43. http://dx.doi.org/10.1364/ol.25.000043.

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6

Costa, F. S., E. Capelas de Oliveira e Adrian R. G. Plata. "Fractional Diffusion with Time-Dependent Diffusion Coefficient". Reports on Mathematical Physics 87, n. 1 (febbraio 2021): 59–79. http://dx.doi.org/10.1016/s0034-4877(21)00011-2.

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7

ONISHI, Masami, Kenta KUWAYAMA, Toshitada SHIMOZAKI e Yoshinori WAKAMATSU. "Surface treatment by diffusion and diffusion coefficient." Journal of the Surface Finishing Society of Japan 41, n. 10 (1990): 1020–25. http://dx.doi.org/10.4139/sfj.41.1020.

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8

Kuroiwa, Toshihiko, Tsukasa Nagaoka, Masato Ueki, Ichiro Yamada, Naoyuki Miyasaka e Hideaki Akimoto. "Different Apparent Diffusion Coefficient". Stroke 29, n. 4 (aprile 1998): 859–65. http://dx.doi.org/10.1161/01.str.29.4.859.

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9

Madden, Anthoula, e Martin O. Leach. "Radial diffusion coefficient mapping". British Journal of Radiology 65, n. 778 (ottobre 1992): 885–94. http://dx.doi.org/10.1259/0007-1285-65-778-885.

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10

Vedalakshmi, R., V. Saraswathy, Ha-Won Song e N. Palaniswamy. "Determination of diffusion coefficient of chloride in concrete using Warburg diffusion coefficient". Corrosion Science 51, n. 6 (giugno 2009): 1299–307. http://dx.doi.org/10.1016/j.corsci.2009.03.017.

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11

Le Bihan, Denis, e Peter van Zijl. "From the diffusion coefficient to the diffusion tensor". NMR in Biomedicine 15, n. 7-8 (2002): 431–34. http://dx.doi.org/10.1002/nbm.798.

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12

Dohnal, Gejza. "On estimating the diffusion coefficient". Journal of Applied Probability 24, n. 1 (marzo 1987): 105–14. http://dx.doi.org/10.2307/3214063.

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Abstract (sommario):
Random processes of the diffusion type have the property that microscopic fluctuations of the trajectory make possible the identification of certain statistical parameters from one continuous observation. The paper deals with the construction of parameter estimates when observations are made at discrete but very dense time points.
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13

Breizman, B. N., e J. Weiland. "Calculation of quasilinear diffusion coefficient". European Journal of Physics 7, n. 4 (1 ottobre 1986): 222–24. http://dx.doi.org/10.1088/0143-0807/7/4/002.

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14

Collet, P., e S. Martínez. "Diffusion coefficient in transient chaos". Nonlinearity 12, n. 3 (1 gennaio 1999): 445–50. http://dx.doi.org/10.1088/0951-7715/12/3/001.

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15

Mastryukov, A. F. "Determination of the diffusion coefficient". Mathematical Models and Computer Simulations 7, n. 4 (luglio 2015): 349–59. http://dx.doi.org/10.1134/s2070048215040067.

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16

M. Parti e I.. Dugmanics. "DIFFUSION COEFFICIENT FOR CORN DRYING". Transactions of the ASAE 33, n. 5 (1990): 1652. http://dx.doi.org/10.13031/2013.31523.

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17

al-Baldawi, N. F., e R. F. Abercrombie. "Cytoplasmic hydrogen ion diffusion coefficient". Biophysical Journal 61, n. 6 (giugno 1992): 1470–79. http://dx.doi.org/10.1016/s0006-3495(92)81953-7.

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18

Sharma, Raman, e K. Tankeshwar. "Model for Self-Diffusion Coefficient". Physics and Chemistry of Liquids 32, n. 4 (settembre 1996): 225–32. http://dx.doi.org/10.1080/00319109608030537.

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19

Dohnal, Gejza. "On estimating the diffusion coefficient". Journal of Applied Probability 24, n. 01 (marzo 1987): 105–14. http://dx.doi.org/10.1017/s0021900200030655.

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Abstract (sommario):
Random processes of the diffusion type have the property that microscopic fluctuations of the trajectory make possible the identification of certain statistical parameters from one continuous observation. The paper deals with the construction of parameter estimates when observations are made at discrete but very dense time points.
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20

Dévényi, A., J. Gadó, A. Keresztúri e M. Makai. "Diffusion Coefficient in Nonuniform Lattices". Nuclear Science and Engineering 92, n. 1 (gennaio 1986): 51–55. http://dx.doi.org/10.13182/nse86-a17864.

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21

Taduy, T., F. Millot e G. Dhalenne. "Chemical diffusion coefficient of CoO". Journal of Physics and Chemistry of Solids 53, n. 2 (febbraio 1992): 323–27. http://dx.doi.org/10.1016/0022-3697(92)90063-j.

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22

Marzocca, A. J., F. Povolo e G. H. Rubiolo. "Self-diffusion coefficient ofα-zirconium". Journal of Materials Science Letters 6, n. 4 (aprile 1987): 431–33. http://dx.doi.org/10.1007/bf01756787.

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23

Ferrando, R., R. Spadacini e G. E. Tommei. "Theory of diffusion in periodic systems: the diffusion coefficient". Surface Science 265, n. 1-3 (aprile 1992): 273–82. http://dx.doi.org/10.1016/0039-6028(92)90507-3.

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24

Pankratov, E. L. "Controlling the diffusion process via time-variable diffusion coefficient". Technical Physics 49, n. 1 (gennaio 2004): 114–18. http://dx.doi.org/10.1134/1.1642689.

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25

Escudero, J., J. Lázaro, E. Solórzano, Miguel A. Rodríguez-Pérez e Jose A. de Saja. "Gas Diffusion and Re-Diffusion in Polyethylene Foams". Defect and Diffusion Forum 283-286 (marzo 2009): 583–88. http://dx.doi.org/10.4028/www.scientific.net/ddf.283-286.583.

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In this work, the effective diffusion coefficient of the gas contained in closed cell polyethylene foams under static loading is measured. To do this, compressive creep experiments were performed on low density polyethylene foams produced under a gas diffusion process. Density dependence of this coefficient has been analysed as well as the variation of pressure with time inside the cells. Finally, immediately after compressive creep, the recovery behaviour of the foams was also characterised. Different abilities for recovering were observed depending on the density of the foam and the absolute recovery resulted independent of the initial stress applied.
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26

Doai, Mariko, Hisao Tonami, Munetaka Matoba, Osamu Tachibana, Hideaki Iizuka, Satoko Nakada e Sohuske Yamada. "Pituitary macroadenoma: Accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness". Neuroradiology Journal 32, n. 2 (16 gennaio 2019): 86–91. http://dx.doi.org/10.1177/1971400919825696.

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Purpose The purpose of this study is to evaluate the accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness using histogram apparent diffusion coefficient values. Materials and methods Eighteen patients with surgically proved pituitary macroadenomas were included in this study. Diffusion-weighted imaging with single-shot echo-planar sequence at 3-T with a 32-channel head coil was performed with b values of 0 and 1000 s/mm2. Calculated apparent diffusion coefficient maps were generated, and a 3-D volume of interest was placed on the tumor while superimposing contrast-enhanced magnetic resonance images. All apparent diffusion coefficient values within the volume of interest were used to compute the average apparent diffusion coefficient of the tumor. The apparent diffusion coefficient values were binned to construct the apparent diffusion coefficient histogram. Using the histogram, the mean, percentiles, skewness, and kurtosis of the apparent diffusion coefficient of the entire tumor were computed. Apparent diffusion coefficient histogram parameters were compared with the MIB-1 index, invasiveness, and recurrence for grading tumor aggressiveness of pituitary adenomas. Results The skewness of the apparent diffusion coefficient histogram only showed significant differences among MIB-1 indices ( p = 0.030). All apparent diffusion coefficient histogram parameters showed no significant differences between negative and positive invasion. The skewness and kurtosis of the apparent diffusion coefficient histogram showed significant differences between positive and negative recurrence (skewness p = 0.011, kurtosis p = 0.011). Receiver-operating characteristics analysis between positive and negative recurrence showed that both skewness and kurtosis of the apparent diffusion coefficient achieved area under the curve at 0.967. Conclusion Skewness and kurtosis of the apparent diffusion coefficient histogram were the predictive parameters for assessing tumor proliferative potential and recurrence of pituitary adenomas.
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27

Omura, Yasuhisa. "Theoretical Assessment of Impacts of Energy Band Valley Occupation on Diffusion Coefficient of Nano-Scale Ge Wires". ECS Journal of Solid State Science and Technology 11, n. 3 (1 marzo 2022): 033005. http://dx.doi.org/10.1149/2162-8777/ac557a.

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The purpose of this paper is to theoretically predict the significant impacts of valley occupation on the overall diffusion coefficient of Ge nanowires physically confined by various surfaces. This paper derives an approximate analytical expression of the diffusion coefficient that exists around room temperature. In Ge wires physically confined by {100} surfaces, the overall diffusion coefficient is, around room temperature, almost constant for wire widths larger than 10 nm. However, a step-like decrease is found for wire widths smaller than 7 nm. This behavior of the overall diffusion coefficient stems from the fall in the L-valley component of diffusion coefficient and the rise of X-valley component of diffusion coefficient for wire widths smaller than 10 nm. The behavior of diffusion coefficient of wires physically confined by {111} surfaces is also investigated around room temperature. The overall diffusion coefficient is almost the same as the diffusion coefficient component of X valley because electrons primarily occupy X valleys. It is clearly revealed that the behavior of the diffusion coefficient is primarily ruled by the valley occupation fraction of electrons in Ge wires. These dominant features of the diffusion coefficient of Ge wires are quite different from those of Si wires. Simulation results are assessed in comparisons with past experimental results and past calculation results. Finally, additional consideration is given from the viewpoint of device applications.
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28

Wei, T., e Y. S. Li. "Identifying a diffusion coefficient in a time-fractional diffusion equation". Mathematics and Computers in Simulation 151 (settembre 2018): 77–95. http://dx.doi.org/10.1016/j.matcom.2018.03.006.

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29

Aguilar-Madera, Carlos G., Gilberto Espinosa-Paredes e Lázaro Molina-Espinosa. "Time-dependent neutron diffusion coefficient for the effective diffusion equation". Progress in Nuclear Energy 112 (aprile 2019): 20–33. http://dx.doi.org/10.1016/j.pnucene.2018.12.003.

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30

Bonati, L. H., P. A. Lyrer, S. G. Wetzel, A. J. Steck e S. T. Engelter. "Diffusion weighted imaging, apparent diffusion coefficient maps and stroke etiology". Journal of Neurology 252, n. 11 (17 giugno 2005): 1387–93. http://dx.doi.org/10.1007/s00415-005-0881-1.

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31

Mohamed, S. A., N. A. Mohamed, A. F. Abdel Gawad e M. S. Matbuly. "A modified diffusion coefficient technique for the convection diffusion equation". Applied Mathematics and Computation 219, n. 17 (maggio 2013): 9317–30. http://dx.doi.org/10.1016/j.amc.2013.03.014.

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32

Jardin, S. C., G. Bateman, G. W. Hammett e L. P. Ku. "On 1D diffusion problems with a gradient-dependent diffusion coefficient". Journal of Computational Physics 227, n. 20 (ottobre 2008): 8769–75. http://dx.doi.org/10.1016/j.jcp.2008.06.032.

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33

Shinkai, Soya, e Yuichi Togashi. "Quantitative Theory of Active Diffusion Trajectories by Instantaneous Diffusion Coefficient". Biophysical Journal 108, n. 2 (gennaio 2015): 471a—472a. http://dx.doi.org/10.1016/j.bpj.2014.11.2578.

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34

Pankratov, E. L. "Dopant diffusion dynamics and optimal diffusion time as influenced by diffusion-coefficient nonuniformity". Russian Microelectronics 36, n. 1 (febbraio 2007): 33–39. http://dx.doi.org/10.1134/s1063739707010040.

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35

WANG GANG, YANG GUO-QUAN, GUAN DI-HUA, JIANG LI, PA SI-KUA-LI-MAO-LUO, PI SI TUO YAN-ZHAN FO LAN KE e JIE SI-SHENG. "DIFFUSION COEFFICIENT MEASURED BY IMPEDANCE SPECTROSCOPY". Acta Physica Sinica 44, n. 12 (1995): 1964. http://dx.doi.org/10.7498/aps.44.1964.

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36

Levchenko, A. M., Y. Aldaiye e V. A. Karkhin. "Hydrogen diffusion coefficient in welded steels". Welding and Diagnostics, n. 6 (2021): 20–27. http://dx.doi.org/10.52177/2071-5234_2021_06_20.

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37

Liu, Xian Xi, Jun Ruo Che e Sai Zhang. "Drying Model and Moisture Diffusion Coefficient". Advanced Materials Research 472-475 (febbraio 2012): 519–25. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.519.

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Varied values of moisture diffusivity estimated using Crank’s equation with different initial moisture content, equilibrium moisture content and sample thickness are often reported. However, a theoretical explanation to this phenomenon is not available to date. To explore the possible reason of this phenomenon, a Fick’s second law diffusion equation for drying samples assumed uniform initial moisture distribution and negligible external resistance is solved numerically and the solutions as drying data is used to estimate the moisture diffusion coefficient of the sample through the equation reported by Crank. The result shows the Crank’s equation used to estimate moisture diffusion coefficient could not be theoretical solution of the Fick’s second law diffusion equation and the estimated value of moisture diffusion changing with initial moisture content, equilibrium moisture content and sample thickness perhaps caused by the Crank’s equation itself.
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38

Furman, I. E. "Self-diffusion coefficient of liquid rubidium". Advanced Studies in Theoretical Physics 8 (2014): 653–54. http://dx.doi.org/10.12988/astp.2014.4556.

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39

Zlygostev, S. N. "Self-diffusion coefficient of liquid lithium". Advanced Studies in Theoretical Physics 8 (2014): 679–80. http://dx.doi.org/10.12988/astp.2014.4562.

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40

Mironova, T., e A. Kraiski. "Determination of Diffusion Coefficient in Hydrogel". KnE Energy 3, n. 3 (25 aprile 2018): 429. http://dx.doi.org/10.18502/ken.v3i3.2057.

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41

Will, Fritz G. "Diffusion Coefficient of Dopants in Polyacetylene". Journal of The Electrochemical Society 132, n. 3 (1 marzo 1985): 743–44. http://dx.doi.org/10.1149/1.2113949.

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42

Durian, D. J. "The diffusion coefficient depends on absorption". Optics Letters 23, n. 19 (1 ottobre 1998): 1502. http://dx.doi.org/10.1364/ol.23.001502.

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43

Hara, Hiroaki. "Anomalous temperature dependence of diffusion coefficient". Physical Review B 31, n. 7 (1 aprile 1985): 4612–16. http://dx.doi.org/10.1103/physrevb.31.4612.

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44

OHMORI, Takao, e Mitsutaka KAWAMURA. "Collective diffusion coefficient in polyacrylamide gels." KOBUNSHI RONBUNSHU 46, n. 10 (1989): 639–41. http://dx.doi.org/10.1295/koron.46.639.

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45

Godoy, Salvador. "Landauer diffusion coefficient: A classical result". Physical Review E 56, n. 4 (1 ottobre 1997): 4884–86. http://dx.doi.org/10.1103/physreve.56.4884.

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46

Culbertson, C. "Diffusion coefficient measurements in microfluidic devices". Talanta 56, n. 2 (11 febbraio 2002): 365–73. http://dx.doi.org/10.1016/s0039-9140(01)00602-6.

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47

Rafsanjani, Hossein Khodabakhshi, Mohammad Hossein Sedaaghi e Saeid Saryazdi. "Efficient diffusion coefficient for image denoising". Computers & Mathematics with Applications 72, n. 4 (agosto 2016): 893–903. http://dx.doi.org/10.1016/j.camwa.2016.06.005.

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48

Al-Baldawi, N. "Calcium diffusion coefficient in Myxicola axoplasm". Cell Calcium 17, n. 6 (giugno 1995): 422–30. http://dx.doi.org/10.1016/0143-4160(95)90088-8.

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49

Colbeck, S. C. "The vapor diffusion coefficient for snow". Water Resources Research 29, n. 1 (gennaio 1993): 109–15. http://dx.doi.org/10.1029/92wr02301.

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50

Ghosh, U. K., S. Kumar e S. N. Upadhyay. "Diffusion coefficient in aqueous polymer solutions". Journal of Chemical & Engineering Data 36, n. 4 (ottobre 1991): 413–17. http://dx.doi.org/10.1021/je00004a020.

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