Nucleation and early stage crystallization in barium disilicate glass
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The design space of sequence defined molecules for inorganic nanoparticle synthesis is exceedingly large. We present an experimental and data analysis workflow for studying the effects of peptide modification on Au nanoparticle synthesis outcomes.
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The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods. Dilitometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post-processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions. Levitation processing of refractory materials in ultra high vacuum provides an avenue to conduct these kinetic studies on single samples. Two experimental methods have been identified where ultra high vacuum experiments are possible; electrostatic levitation in ground-based experiments and electromagnetic processing in low earth orbit on TEMPUS. Such experiments, reported here, were conducted on zirconium. Liquid zirconium is an excellent solvent and has a high solubility for contaminants contained in the bulk material as well as those contaminants found in the vacuum environment. Oxides, nitrides, and carbides do not exist in the melt, and do not form on the surface of molten zirconium, for the materials and vacuum levels used in this study. Ground-based experiments with electrostatic levitation have shown that the statistical nucleation kinetic experiments are viable and yield results which are consistent with classical nucleation theory. The advantage of low earth orbit experiments is the ability to vary the flow conditions in the liquid prior to nucleation. The put-pose of nucleation experiments in TEMPUS was to examine.
We report nucleation and growth processes of minerals and other crystals can significantly affect one another due to the transport limitations and local depletion of reactive ions in the solution. Most numerical models and experimental measurements have typically focused on either growth or nucleation, but not both. In this work, we incorporate a heterogeneous nucleation process based on classical nucleation theory into a microcontinuum model that implements the Darcy–Brinkman–Stokes approach to study the interplay between nucleation and crystal growth on a substrate in diffusive systems. We demonstrate how the Damköhler number (reaction rate) and nucleation rate prefactor change the effective nucleation rate on a substrate. Higher surface growth rates deplete the solute concentration around the nuclei that appear initially on the substrate, creating islands that screen against further nucleation. The model predicts that measured nucleation rates may be affected by the history of crystal nucleation on the substrate. In the extreme case of high growth rates relative to diffusion, it predicts that the rate of subsequent nucleation is limited by reactant depletion. We introduce a nondimensional number α to represent the relation between surface propagation rate during growth and the heterogeneous nucleation rate. We show that it is important to control Damköhler number and α to achieve similar precipitation regimes at different reaction and nucleation rates. We suggest that the observed universality can guide the interpretation of experimental results on nucleation rates, since matching experiment can be achieved by tuning transport, reaction, and nucleation parameters simultaneously. In addition, we show how the bulk solution concentration affects the structure and topology of precipitation on a substrate.
Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.
Formation and evolution of cirrostratus in response to weak, uniform and constant synoptic forcing is simulated using a one-dimensional numerical model with explicit microphysics, in which the particle size distribution in each grid box is fully resolved. A series of tests of the model response to nucleation modes (homogeneous-freezing-only/heterogeneous nucleation) and heterogeneous nucleation parameters are performed. In the case studied here, nucleation is first activated in the prescribed moist layer. A continuous cloud-top nucleation zone with a depth depending on the vertical humidity gradient and one of the nucleation parameters is developed afterward. For the heterogeneous nucleation cases, intermittent nucleation zones in the mid-upper portion of the cloud form where the relative humidity is on the rise, because existent ice crystals do not uptake excess water vapor efficiently, and ice nuclei (IN) are available. Vertical resolution as fine as 1 m is required for realistic simulation of the homogeneous-freezing-only scenario, while the model resolution requirement is more relaxed in the cases where heterogeneous nucleation dominates. Bulk microphysical and optical properties are evaluated and compared. Ice particle number flux divergence, which is due to the vertical gradient of the gravity-induced particle sedimentation, is constantly and rapidly changing the local ice number concentration, even in the nucleation zone. When the depth of the nucleation zone is shallow, particle number concentration decreases rapidly as ice particles grow and sediment away from the nucleation zone. When the depth of the nucleation zone is large, a region of high ice number concentration can be sustained. The depth of nucleation zone is an important parameter to be considered in parametric treatments of ice cloud generation.
This work presents a novel formulation of the ice nucleation spectrum, i.e. the function relating the ice crystal concentration to cloud formation conditions and aerosol properties. The new formulation is physically-based and explicitly accounts for the dependency of the ice crystal concentration on temperature, supersaturation, cooling rate, and particle size, surface area and composition. This is achieved by introducing the concepts of ice nucleation coefficient (the number of ice germs present in a particle) and nucleation probability dispersion function (the distribution of ice nucleation coefficients within the aerosol population). The new formulation is used to generate ice nucleation parameterizations for the homogeneous freezing of cloud droplets and the heterogeneous deposition ice nucleation on dust and soot ice nuclei. For homogeneous freezing, it was found that by increasing the dispersion in the droplet volume distribution the fraction of supercooled droplets in the population increases. For heterogeneous ice nucleation the new formulation consistently describes singular and stochastic behavior within a single framework. Using a fundamentally stochastic approach, both cooling rate independence and constancy of the ice nucleation fraction over time, features typically associated with singular behavior, were reproduced. Analysis of the temporal dependency of the ice nucleation spectrum suggested that experimental methods that measure the ice nucleation fraction over few seconds would tend to underestimate the ice nuclei concentration. It is shown that inferring the aerosol heterogeneous ice nucleation properties from measurements of the onset supersaturation and temperature may carry significant error as the variability in ice nucleation properties within the aerosol population is not accounted for. This work provides a simple and rigorous ice nucleation framework where theoretical predictions, laboratory measurements and field campaign data can be reconciled, and that is suitable for application in atmospheric modeling studies.
We report on atomic-scale analyses of nucleation and growth of Zr oxide precipitates and the microstructural evolution of internally oxidized Nb3Sn wires for high-field superconducting magnet applications, utilizing atom probe tomography (APT), transmission electron microscopy (TEM), and first-principles calculations. APT analyses reveal that oxygen and zirconium are already segregated at grain boundaries (GBs) in the unreacted Nb-1Zr-4Ta (at%) alloy prior to forming Nb3Sn through reacting the Nb alloy with Sn and SnO2. After forming Nb3Sn, Zr oxide precipitates nucleate both at the Nb3Sn/Nb heterophase interfaces and in the Nb3Sn grains, driven by the small solubilities of Zr and O in Nb3Sn compared to their value in Nb. A high number density (Nv) of Zr oxide nanoprecipitates is observed in the Nb3Sn layers, ∼10 23 m −3 , with a mean diameter <10 nm for a heat treatment at 625 °C. Quantitative APT and TEM analyses of the Zr oxide precipitates in the reacted Nb3Sn layers elucidate details of the nucleation, growth, and coarsening processes of the Zr oxide precipitates in Nb3Sn. First-principles calculations and classical nucleation theory are employed to study the nucleation of Zr oxide precipitates in Nb3Sn and to estimate the maximum energy barrier and critical radius for nucleation. Our research unveils the kinetic pathways for nucleation and growth of Zr oxide precipitates and the microstructural evolution of Nb3Sn layers, which helps to understand and improve the superconducting properties of internally oxidized Nb3Sn wires for use in high-field superconducting magnets. •We investigated the nucleation and growth of Zr oxide nanoprecipitates in Nb3Sn superconductors for magnet applications.•APT and TEM analyses reveals the nucleation and growth process of Zr oxide precipitates in Nb3Sn layers.•Classical nucleation theory with DFT is employed to describe the nucleation process of Zr oxide precipitates in Nb3Sn.•We find that the interfacial reactions at Nb/Nb3Sn interface play a critical role in the nucleation of Zr oxide precipitates.•Current study provides a pathway to improve the properties of internally oxidized Nb3Sn superconducting wires.
A method is introduced to measure the free-energy barrier W(sup *), the activation energy, and activation entropy to nucleation of crystallites in amorphous solids, independent of the energy barrier to growth. The method allows one to determine the temperature dependence of W(sup *), and the effect of the preparation conditions of the initial amorphous phase, the dopants, and the crystallization methds on W(sup *). The method is applied to determine the free-energy barrier to nucleation of crystallites in amorphous silicon (a-Si) thin films. For thermally induced nucleation in a-Si thin films with annealing temperatures in the range of from 824 to 983 K, the free-energy barrier W(sup *) to nucleation of silicon crystals is about 2.0 - 2.1 eV regardless of the preparation conditions of the films. The observation supports the idea that a-Si transforms into an intermediate amorphous state through the structural relaxation prior to the onset of nucleation of crystallites in a-Si. The observation also indicates that the activation entropy may be an insignificant part of the free-energy barrier for the nucleation of crystallites in a-Si. Compared with the free-energy barrier to nucleation of crystallites in undoped a-Si films, a significant reduction is observed in the free-energy barrier to nucleation in Cu-doped a-Si films. For a-Si under irradiation of Xe(2+) at 10(exp 5) eV, the free-energy barrier to ion-induced nucleation of crystallites is shown to be about half of the value associated with thermal-induced nucleation of crystallites in a-Si under the otherwise same conditions, which is much more significant than previously expected. The present method has a general kinetic basis; it thus should be equally applicable to nucleation of crystallites in any amorphous elemental semiconductors and semiconductor alloys, metallic and polymeric glasses, and to nucleation of crystallites in melts and solutions.
The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods. Dilatometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions.
The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods [1-6]. Dilitometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics [7]. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov [8]. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions.
The objective of this paper is to develop further a framework for computationally modeling microstructurally small fatigue crack growth in AA 7075-T651 [1]. The focus is on the nucleation event, when a crack extends from within a second-phase particle into a surrounding grain, since this has been observed to be an initiating mechanism for fatigue crack growth in this alloy. It is hypothesized that nucleation can be predicted by computing a non-local nucleation metric near the crack front. The hypothesis is tested by employing a combination of experimentation and nite element modeling in which various slip-based and energy-based nucleation metrics are tested for validity, where each metric is derived from a continuum crystal plasticity formulation. To investigate each metric, a non-local procedure is developed for the calculation of nucleation metrics in the neighborhood of a crack front. Initially, an idealized baseline model consisting of a single grain containing a semi-ellipsoidal surface particle is studied to investigate the dependence of each nucleation metric on lattice orientation, number of load cycles, and non-local regularization method. This is followed by a comparison of experimental observations and computational results for microstructural models constructed by replicating the observed microstructural geometry near second-phase particles in fatigue specimens. It is found that orientation strongly influences the direction of slip localization and, as a result, in uences the nucleation mechanism. Also, the baseline models, replication models, and past experimental observation consistently suggest that a set of particular grain orientations is most likely to nucleate fatigue cracks. It is found that a continuum crystal plasticity model and a non-local nucleation metric can be used to predict the nucleation event in AA 7075-T651. However, nucleation metric threshold values that correspond to various nucleation governing mechanisms must be calibrated.
Mineral dust can indirectly impact climate by nucleation of atmospheric solids, for example, by heterogeneously nucleating ice in mixed-phase clouds or by impacting the phase of aerosols and clouds through contact nucleation. The effectiveness toward nucleation of individual components of mineral dust requires further study. Here, the nucleation behavior of metal oxide nanoparticle components of atmospheric mineral dust is investigated. A long-working-distance optical trap is used to study contact and immersion nucleation of ammonium sulfate by transition-metal oxides, and an environmental chamber is used to probe depositional ice nucleation on metal oxide particles. Previous theory dictates that ice nucleation and heterogeneous nucleation of atmospheric salts can be impacted by several factors including morphology, lattice match, and surface area. Here, we observe a correlation between the cationic oxidation states of the metal oxide heterogeneous nuclei and their effectiveness in causing nucleation in both contact efflorescence mode and depositional freezing mode. In contrast to the activity of contact efflorescence, the same metal oxide particles did not cause a significant increase in efflorescence relative humidity when immersed in the droplet. In conclusion, these experiments suggest that metal speciation, possibly as a result of cationic charge sites, may play a role in the effectiveness of nucleation that is initiated at particle surfaces.