An experimental study of multimodal glass suspension rheology to test and validate a polydisperse suspension viscosity model

Experimental measurements of non-colloidal multimodal suspension viscosities are performed over a wide range of mixing ratios and used to test the robustness and predictive capability of a recent viscosity model (Mwasame et al. in Phys Fluids 28:061701, 2016b), subsequently referred to as the MWB model. Three unimodally distributed particle suspensions with narrow size distributions are blended to make the bimodal and trimodal suspensions used in the rheological experiments. We demonstrate how predictions for mixture viscosities can be made using the MWB model only requiring the volume-weighted average particle sizes and viscosity correlations of the individual unimodal suspensions comprising the blend. The resultant model predictions are found to be in good agreement with measured bimodal and trimodal viscosity data to within expected experimental uncertainty. The datasets provided here can be used to validate future modeling efforts, and the MWB model can be used to optimize the viscosity of multimodal suspension mixtures for specific performance criteria.     

Desargues Theorem, Dynamics, and Hyperplane Arrangements

The Desargues theorem is a basic theorem in classical projective geometry. In this paper we generalize Desargues theorem in the direction of dynamical systems. Our result comprises an infinite family of configurations, having unbounded complexity. The proof of the result involves constructing special kinds of hyperplane arrangements and then projecting subsets of them into the plane.     

Unsteady circular Couette flow of a Bingham plastic with the Augmented Lagrangian Method

Numerical simulations are undertaken for unsteady flows of an ideal Bingham fluid in a circular Couette viscometer. The main difficulties in such simulations are caused by the non-differentiability of the constitutive equation and the need to determine the position and shape of the yield surface separating the yielded zones from the unyielded ones. In this work, these difficulties are overcome by using a numerical method based on variational inequalities, i.e. the augmented Lagrangian/Uzawa method. The start-up and cessation of circular Couette flows of a Bingham fluid are solved numerically assuming that only one of the cylinders is rotating. An improved theoretical upper bound for the stopping time in the case of cessation is derived. The numerical estimates for the stopping time compare well with the theoretical bounds. Moreover, with the adopted method the evolution of the velocity profiles and the locations of yielded/unyielded surfaces are accurately calculated. In flow cessation, we observe an interesting effect, namely the appearance of a small unyielded region adjoined to the outer cylinder shortly before cessation.     

Hydration of gas-phase gramicidin S (M + 2H)2+ ions formed by electrospray: The transition from solution to gas-phase structure

The hydration of doubly protonated gas-phase ions of gramicidin S formed by electrospray ionization was investigated. Under “gentle” electrospray conditions, a near Gaussian distribution of (M + 2H + nH₂O)²⁺ ions with n up to 50 can be readily formed. These extensively hydrated gas-phase ions should have structures similar to those in solution. For intermediate extents of hydration, the “naked” or unsolvated ion is present in unusually high abundance. This is attributed to a competition between solvation of the charges by water vs intramolecular self-solvation via hydrogen bonding. In addition, “magic” numbers of attached water molecules are observed for n = 8, 11, and 14. These magic numbers are attributed to favorable arrangements of water molecules surrounding the charge and surface of the peptide in the gas phase. These results are indicative of a gentle stepwise transformation from the solution-phase structure of the ion to the preferred gas-phase structure as solvent evaporates from the hydrated ions.     

Ovarian Brenner tumors: MR imaging characteristics

This study describes the appearance of Brenner tumors on MR imaging and compares quantitative signal intensity measurements of Brenner tumors with that of other ovarian tumors. A search of pathologic and MR records disclosed patients who had MRIs showing Brenner tumors prior to surgical excision. Patients (21) with other surgically proven ovarian masses were randomly selected for comparison. MR imaging was performed at 1.5 T with phased array multicoils and fast spin echo T2-weighted images. Region-of-interest measurements of signal intensity (SI) were made to calculate signal intensity ratios (SIR = mass SI/muscle SI). Brenner tumors showed significantly lower SIR than other tumors on T2-weighted images (p = 0 .004) and similar SIR on T1-weighted images. Brenner tumors show lower signal intensity on T2-weighted images than other non-fibrous ovarian tumors. This lower signal intensity may result from the extensive fibrous content of these tumors.     

A Neoglycoprotein-Immobilized Fluorescent Magnetic Bead Suspension Multiplex Array for Galectin-Binding Studies

Carbohydrate-protein conjugates have diverse applications. They have been used clinically as vaccines against bacterial infection and have been developed for high-throughput assays to elucidate the ligand specificities of glycan-binding proteins (GBPs) and antibodies. Here, we report an effective process that combines highly efficient chemoenzymatic synthesis of carbohydrates, production of carbohydrate-bovine serum albumin (glycan-BSA) conjugates using a squarate linker, and convenient immobilization of the resulting neoglycoproteins on carboxylate-coated fluorescent magnetic beads for the development of a suspension multiplex array platform. A glycan-BSA-bead array containing BSA and 50 glycan-BSA conjugates with tuned glycan valency was generated. The binding profiles of six plant lectins with binding preference towards Gal and/or GalNAc, as well as human galectin-3 and galectin-8, were readily obtained. Our results provide useful information to understand the multivalent glycan-binding properties of human galectins. The neoglycoprotein-immobilized fluorescent magnetic bead suspension multiplex array is a robust and flexible platform for rapid analysis of glycan and GBP interactions and will find broad applications.     

Dissociation energies of deoxyribose nucleotide dimer anions measured using blackbody infrared radiative dissociation

The dissociation kinetics of deprotonated deoxyribose nucleotide dimers were measured using blackbody infrared radiative dissociation. Experiments were performed with noncovalently bound dimers of phosphate, adenosine (dAMP), cytosine (dCMP), guanosine (dGMP), thymidine (dTMP), and the mixed dimers dAMP.dTMP and dGMP.dCMP. The nucleotide dimers fragment through two parallel pathways, resulting in formation of the individual nucleotide or nucleotide + HPO3 ion. Master equation modeling of this kinetic data was used to determine threshold dissociation energies. The dissociation energy of (dGMP.dCMP-H)- is much higher than that for the other nucleotide dimers. This indicates that there is a strong interaction between the nucleobases in this dimer, consistent with the existence of Watson-Crick hydrogen bonding between the base pairs. Molecular mechanics simulations indicate that Watson-Crick hydrogen bonding occurs in the lowest energy structures of (dGMP.dCMP-H)-, but not in (dAMP.dTMP-H)-. The trend in gas phase dissociation energies is similar to the trend in binding energies measured in nonaqueous solutions within experimental error. Finally, the acidity ordering of the nucleotides is determined to be dTMP < dGMP < dCMP < dAMP, where dAMP has the highest acidity (largest delta Gacid).     

Low-cost prediction of molecular and transition state partition functions via machine learning

We have generated an open-source dataset of over 30 000 organic chemistry gas phase partition functions. With this data, a machine learning deep neural network estimator was trained to predict partition functions of unknown organic chemistry gas phase transition states. This estimator only relies on reactant and product geometries and partition functions. A second machine learning deep neural network was trained to predict partition functions of chemical species from their geometry. Our models accurately predict the logarithm of test set partition functions with a maximum mean absolute error of 2.7%. Thus, this approach provides a means to reduce the cost of computing reaction rate constants ab initio. The models were also used to compute transition state theory reaction rate constant prefactors and the results were in quantitative agreement with the corresponding ab initio calculations with an accuracy of 98.3% on the log scale.

Deep neural networks accurately predict transition state partition functions at the low cost of reactant and product input features for organic chemistry gas phase reactions.