SummaryA new two parameter family of life length distributions is presented which is derived from a model for fatigue. This derivation follows from considerations of renewal theory for the number of cycles needed to force a fatigue crack extension to exceed a critical value. Some closure properties of this family are given and some comparisons made with other families such as the lognormal which have been previously used in fatigue studies.

Summary The estimation problem is studied for a new two-parameter family of life length distributions which has been previously derived from a model of fatigue crack growth. Maximum likelihood estimates of both parameters are obtained and iterative computing procedures are given and examined. A simple estimate of the median life is exhibited, shown to be consistent and then compared, favorably, with the maximum likelihood estimate. More important, the asymptotic distribution of this estimate is shown to be within the same class of distributions as the observations themselves. This model, and these estimation procedures, are tried by fitting this distribution to several extensive sets of fatigue data and then some comparisons of practical significance are made.

No abstract

A thermodynamic model was developed for the size-selective fractionation of ligand-stabilized nanoparticles by a CO2 gas-expanded liquid precipitation process. The tunable solvent strength of gas-expanded liquids, via CO2 pressurization, results in an effective method to fractionate nanoparticles, based on the size-dependent dispersibility of the particles. Specifically, the thermodynamic model is used to estimate the size of dodecanethiol-capped Ag nanoparticles that can be dispersed at a given CO2 pressure by equating the total interparticle interaction energy to the Boltzmann threshold stabilization energy (−3/2 k B T). The ligand−solvent interaction is found to have the greatest impact on the total interaction energy. This model illustrates that the entire length of the ligand is not accessible to the solvent, and three phenomenological model variations were developed to vary the ligand−solvent interaction.

SummaryThe estimation problem is studied for a new two-parameter family of life length distributions which has been previously derived from a model of fatigue crack growth. Maximum likelihood estimates of both parameters are obtained and iterative computing procedures are given and examined. A simple estimate of the median life is exhibited, shown to be consistent and then compared, favorably, with the maximum likelihood estimate. More important, the asymptotic distribution of this estimate is shown to be within the same class of distributions as the observations themselves. This model, and these estimation procedures, are tried by fitting this distribution to several extensive sets of fatigue data and then some comparisons of practical significance are made.

Summary A new two parameter family of life length distributions is presented which is derived from a model for fatigue. This derivation follows from considerations of renewal theory for the number of cycles needed to force a fatigue crack extension to exceed a critical value. Some closure properties of this family are given and some comparisons made with other families such as the lognormal which have been previously used in fatigue studies.

Quinoa (Chenopodium quinoa Willd) contains 2 to 5% saponins in the form of oleanane-type triterpenoid glycosides or sapogenins found in the external layers of the seeds. These saponins confer an undesirable bitter flavor. This study maps the content and profile of glycoside-free sapogenins from 22 quinoa varieties and 6 original breeding lines grown in North America under similar agronomical conditions. Saponins were recovered using a novel extraction protocol and quantified by GC-MS. Oleanolic acid (OA), hederagenin (HD), serjanic acid (SA), and phytolaccagenic acid (PA) were identified by their mass spectra. Total saponin content ranged from 3.81 to 27.1 mg/g among the varieties studied. The most predominant sapogenin was phytolaccagenic acid with 16.72 mg/g followed by hederagenin at 4.22 mg/g representing the ∼70% and 30% of the total sapogenin content. Phytolaccagenic acid and the total sapogenin content had a positive correlation of r = 0.88 (p < 0.05). Results showed that none of the varieties we studied can be classified as "sweet". Nine varieties were classified as "low-sapogenin". We recommend six of the varieties be subjected to saponin removal process before consumption. A multivariate analysis was conducted to evaluate and cluster the different genotypes according their sapogenin profile as a way of predicting the possible utility of separate quinoa in food products. The multivariate analysis showed no correlations between origin of seeds and saponin profile and/or content.

INTRODUCTIONThe precipitation and size-selective fractionation of nanoparticles is a crucial and, sometimes, necessary stage of postsynthesis nanomaterial processing to fine-tune the size-dependent properties of nanoparticles for their intended application. Unfortunately, these processes (specifically size-selective fractionation) are somewhat trial-and-error in their application, and predicting the size and size distribution of the recovered nanoparticle fractions is quite difficult. The ability to predict the size and size distributions of the nanoparticles that would disperse and precipitate at different solvent conditions would greatly reduce the need for experimentation and would provide new, physical insights into the underpinning thermophysical phenomena.Traditionally, the size-selective fractionation of nanoparticles has been accomplished through the controlled reduction of solvent strength of a thermodynamically stable nanoparticle dispersion by the addition of an antisolvent 1 (e.g., aliphatic-thiol stabilized nanoparticles dispersed in hexane can be precipitated and fractionated through the addition of ethanol). This liquid-liquid solvent/antisolvent precipitation and fractionation process produces large amounts of organic waste, is very time-intensive, and is capable of producing only monodisperse fractions through repetition. Another method of size-selectively precipitating nanoparticles was developed 2-4 to alievate some of the drawbacks of the liquid-liquid precipitation and fractionation process which makes use of the tunable physicochemical properties of gas-expanded liquids (GXLs): mixtures of an organic solvent and a pressurized gas. An organic solvent (e.g., hexane) dispersion of aliphatic-ligand (e.g., dodecanethiol) stabilized metallic (e.g., gold) nanoparticles can be precipitated when pressured to subvapor pressure levels with CO 2 . The CO 2 partitions (dissolves) into the organic solvent, and as CO 2 is a nonsolvent for the aliphatic ligand tails, the solvent strength of the overall solvent mixture is reduced, thus inducing precipitation of the nanoparticles. The degree to which CO 2 is added to the solvent is simply a function of the applied CO 2 pressure; i.e., CO 2 has a greater solubility at higher applied pressures. Several apparatuses have been developed to make use of this phenomenon to size-selectively fractionate polydisperse nanoparticles. Details on these methods are available elsewhere, 2,4 but in short, if an organic dispersion of nanoparticles is pressurized with CO 2 to a point where only a portion of the nanoparticles precipitate (the largest nanoparticles will precipitate first upon worsening solvent conditions), the nanoparticles which remain dispersed (the smallest nanoparticles) in the solvent mixture can be removed from the precipitated nanoparticles, thereby achieving an effective fractionation.Modeling of these postsynthesis processes involving aqueous nanoparticle dispersions has been successfully accomplished through the use of Derjaguin, Landau, Verwey, and Over...