Compositional Changes at the Early Stages of Nanoparticles Growth in Glasses

Blanc, Wilfried; Martin, Isabelle; Francois‐Saint‐Cyr, Hugues; Bidault, Xavier; Chaussedent, Stéphane; Hombourger, Chrystel; Lacomme, Sabrina; Coustumer, Philippe Le; Neuville, Daniel R.; Larson, David J.; Prosa, Ty J.; Guillermier, Christelle

doi:10.1021/acs.jpcc.9b08577

Cited by 41 publications

(22 citation statements)

References 45 publications

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“…Indeed, as far as the bulk properties of the clusters are defined, one parameter specifying the size of the clusters is sufficient to complete their description. Note that the bulk properties of sub-, critical, and super-critical clusters may deviate from the properties of the evolving macroscopic phases [ 4 , 5 , 9 , 56 ]. Their dependence on cluster size can be determined based on the generalized Gibbs’ approach [ 21 , 22 , 23 , 24 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

Crystallization of Supercooled Liquids: Self-Consistency Correction of the Steady-State Nucleation Rate

Abyzov

Schmelzer

Fokin

et al. 2020

Entropy

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Crystal nucleation can be described by a set of kinetic equations that appropriately account for both the thermodynamic and kinetic factors governing this process. The mathematical analysis of this set of equations allows one to formulate analytical expressions for the basic characteristics of nucleation, i.e., the steady-state nucleation rate and the steady-state cluster-size distribution. These two quantities depend on the work of formation, Δ G ( n ) = − n Δ μ + γ n 2 / 3 , of crystal clusters of size n and, in particular, on the work of critical cluster formation, Δ G ( n c ) . The first term in the expression for Δ G ( n ) describes changes in the bulk contributions (expressed by the chemical potential difference, Δ μ ) to the Gibbs free energy caused by cluster formation, whereas the second one reflects surface contributions (expressed by the surface tension, σ : γ = Ω d 0 2 σ , Ω = 4 π ( 3 / 4 π ) 2 / 3 , where d 0 is a parameter describing the size of the particles in the liquid undergoing crystallization), n is the number of particles (atoms or molecules) in a crystallite, and n = n c defines the size of the critical crystallite, corresponding to the maximum (in general, a saddle point) of the Gibbs free energy, G. The work of cluster formation is commonly identified with the difference between the Gibbs free energy of a system containing a cluster with n particles and the homogeneous initial state. For the formation of a “cluster” of size n = 1 , no work is required. However, the commonly used relation for Δ G ( n ) given above leads to a finite value for n = 1 . By this reason, for a correct determination of the work of cluster formation, a self-consistency correction should be introduced employing instead of Δ G ( n ) an expression of the form Δ G ˜ ( n ) = Δ G ( n ) − Δ G ( 1 ) . Such self-consistency correction is usually omitted assuming that the inequality Δ G ( n ) ≫ Δ G ( 1 ) holds. In the present paper, we show that: (i) This inequality is frequently not fulfilled in crystal nucleation processes. (ii) The form and the results of the numerical solution of the set of kinetic equations are not affected by self-consistency corrections. However, (iii) the predictions of the analytical relations for the steady-state nucleation rate and the steady-state cluster-size distribution differ considerably in dependence of whether such correction is introduced or not. In particular, neglecting the self-consistency correction overestimates the work of critical cluster formation and leads, consequently, to far too low theoretical values for the steady-state nucleation rates. For the system studied here as a typical example (lithium disilicate, Li 2 O · 2 SiO 2 ), the resulting deviations from the correct values may reach 20 orders of magnitude. Consequently, neglecting self-consistency corrections may result in severe errors in the interpretation of experimental data if, as it is usually done, the analytical relations for the steady-state nucleation rate or the steady-state cluster-size distribution are employed for their determination.

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Section: Introductionmentioning

confidence: 99%

Crystallization of Supercooled Liquids: Self-Consistency Correction of the Steady-State Nucleation Rate

Abyzov

Schmelzer

Fokin

et al. 2020

Entropy

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“…The NPDF fiber has been fabricated in two steps: at first, using modified chemical vapor deposition (MCVD) a silica preform was fabricated, with the addition of MgCl 2 and ErCl 3 dopants; then, the fiber was drawn in a standard drawing tower. The high temperature up to 2000 °C causes a separation of silica and alkaline ions, forming MgO-based nanoparticles with 20-100 nm diameter that elongate along with the fiber through the drawing process 30,31 . Four NPDFs with the core diameter of 10 µm and 125 cladding diameter are spliced with SMF pigtails of different lengths so that two neighboring NPDFs are spatially separated by the SMF fiber from the neighboring NPDF.…”

Section: Methodsmentioning

confidence: 99%

Distributed 2D temperature sensing during nanoparticles assisted laser ablation by means of high-scattering fiber sensors

Ashikbayeva

Aitkulov

Jelbuldina

et al. 2020

Sci Rep

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The high demand in effective and minimally invasive cancer treatments, namely thermal ablation, leads to the demand for real-time multi-dimensional thermometry to evaluate the treatment effectiveness, which can be also assisted by the use of nanoparticles. We report the results of 20-nm gold and magnetic iron oxide nanoparticles-assisted laser ablation on a porcine liver phantom. The experimental setup consisting of high-scattering nanoparticle-doped fibers was operated by means of a scattering-level multiplexing arrangement and interrogated via optical backscattered reflectometry, together with a solid-state laser diode operating at 980 nm. The multiplexed 2-dimensional fiber arrangement based on nanoparticle-doped fibers allowed an accurate superficial thermal map detected in real-time. Laser ablation (LA) is a minimally invasive and alternative thermal therapy technique to the surgical resection for the treatment of cancer that aimed to destroy the tumor at high temperatures. Laser ablation works on the principle of conversion of absorbed laser light into heat in tissue leading to coagulative necrosis. The laser light inside the tumor is distributed according to the phenomena of scattering, absorption, and bending. The rate of absorption mainly depends on the water and hemoglobin load 1. The widely employed laser types for LA are Neodymium: Yttrium aluminum garnet operating at a wavelength of 1,064 nm and solid-state diode working at a wavelength of 800-980 nm due to the best light penetration ability at near-infrared region 2. However, currently, laser diodes gaining more interest and replacing the Nd: YAG laser because they are cheaper, easier to transport due to the lightweight and shows the similar tissue penetration performance at the wavelengths between 800 and 980 nm 3. In the last 4 decades, many studies have investigated the efficacy of LA for the treatment of cancer, demonstrated its advances, and evaluated the settings responsible for the therapy outcome. Indeed, the size of the heated area significantly depends on the laser power, laser wavelength, absorption features, optical properties of the biological tissue, and time of laser irradiation 4,5. In the clinical practice, laser light is delivered in different modalities depending on the location of the tumor and the desired thermal effect: deep-seated tumors in the liver 6,7 , pancreas 8,9 , brain 10 and other organs can be reached by thin optical applicators; superficial tumors like nonmelanoma skin cancer 11,12 , superficial bladder carcinoma 13 can be treated with external and non-invasive approaches. The pioneering work of laser application in tumor treatment was done by Bown in 1983 4. LA is mostly known as interstitial laser thermotherapy, where the light delivered by means of delivery fiber into the tumor, usually a large core fiber or a side-firing fiber ranging in diameter from 0.5 to 2.5 mm 14-16. The laser light is further converted into the thermal energy leading to the tumor damage. Nowadays, the reliable method of real-time

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“…Fibers have been drawn from silica preforms made with modified chemical vapor deposition (MCVD) [25]. The addition of magnesium during the fabrication activates the formation of Mg-silicate nanoparticles [26], as reported by Blanc et al [20], which act as a scattering source for input signals.…”

Section: High Scattering Fibersmentioning

confidence: 99%

Performance Analysis of Scattering-Level Multiplexing (SLMux) in Distributed Fiber-Optic Backscatter Reflectometry Physical Sensors

Tosi

Molardi

Blanc

et al. 2020

Sensors

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Optical backscatter reflectometry (OBR) is a method for the interrogation of Rayleigh scattering occurring in each section of an optical fiber, resulting in a single-fiber-distributed sensor with sub-millimeter spatial resolution. The use of high-scattering fibers, doped with MgO-based nanoparticles in the core section, provides a scattering increase which can overcome 40 dB. Using a configuration-labeled Scattering-Level Multiplexing (SLMux), we can arrange a network of high-scattering fibers to perform a simultaneous scan of multiple fiber sections, therefore extending the OBR method from a single fiber to multiple fibers. In this work, we analyze the performance and boundary limits of SLMux, drawing the limits of detection of N-channel SLMux, and evaluating the performance of scattering-enhancement methods in optical fibers.

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Compositional Changes at the Early Stages of Nanoparticles Growth in Glasses

Cited by 41 publications

References 45 publications

Crystallization of Supercooled Liquids: Self-Consistency Correction of the Steady-State Nucleation Rate

Crystallization of Supercooled Liquids: Self-Consistency Correction of the Steady-State Nucleation Rate

Distributed 2D temperature sensing during nanoparticles assisted laser ablation by means of high-scattering fiber sensors

Performance Analysis of Scattering-Level Multiplexing (SLMux) in Distributed Fiber-Optic Backscatter Reflectometry Physical Sensors

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