Prediction of microemulsion phase behavior from surfactant and co-solvent structures

Structure-property models were developed to predict the optimum salinity, optimum solubilization ratio, and the aqueous stability limit from the molecular structures of surfactants and co-solvents used for enhanced oil recovery. The models are sufficiently accurate to provide a useful guide to experimental testing programs for the development of chemical formulations for enhanced oil recovery and other similar applications requiring low interfacial tension. This is the first time a structure-property model has been developed to predict the optimum solubilization ratio. The solubilization ratio can be used in the Huh equation to predict the interfacial tension, which is the most important property in enhanced oil recovery applications. The UTCEOR Database was constructed and used to develop the models. The database is a collection of highest-quality experimental chemical EOR data conducted at The University of Texas at Austin from 2005 to 2018. It contains several thousand phase behavior experiments using 34 unique crude oils, 294 unique surfactants, and 70 unique co-solvents. The structures of the surfactants and co-solvents were characterized and include variations in the type of hydrophobe (carbon number, degree of branching, polydispersity, and aromaticity), number of alkoxylate groups (propylene oxide and ethylene oxide), and the type of head group. The model focuses on blends of anionic surfactants and nonionic co-solvents. Both the optimum salinity and the optimum solubilization ratio were modeled as a function of monovalent and divalent cations in the brines. The oils were characterized using their equivalent alkane carbon number. The models include the effect of soaps generated from the neutralization of acidic crude oils. Previous models for optimum salinity have not included the effects of divalent cations, soap, and co-solvents among other limitations. Most importantly, the new model can be used to predict interfacial tension as well as optimum salinity whereas previous models were used to predict only optimum salinity. In this research, the structure-concentration and structure-property effect of co-solvents were modeled separately, whereas previous models convoluted both effects and were not predictive. New measurements were made and combined with literature data to develop improved correlations for the oil-water partition coefficient and the interface-water partition coefficient of co-solvents. These correlations were used with pseudophase theory to more accurately model the structure-concentration effect. A structure-property model was developed for the aqueous stability that predicts the coacervation of chemical formulations. The interactions between surfactant hydrophobes and the PO groups were modeled because they influence the stability of micelles. The effects of co-solvent, polymer, and divalent cations were included for the first time. The structure-property models can be used to predict formulations for a given oil, brine and temperature that are likely to achieve ultra-low IFT with aqueous stability at optimum salinity and thus greatly accelerate the process of finding the best formulations to test for chemical EOR.Petroleum and Geosystems Engineerin

Potential and kinetic shaping for control of underactuated mechanical systems

This paper combines techniques of potential shaping with those of kinetic shaping to produce some new methods for stabilization of mechanical control systems. As with each of the techniques themselves, our method employs energy methods and the LaSalle invariance principle. We give explicit criteria for asymptotic stabilization of equilibria of mechanical systems which, in the absence of controls, have a kinetic energy function that is invariant under an Abelian group

Real-time decoding of question-and-answer speech dialogue using human cortical activity.

Natural communication often occurs in dialogue, differentially engaging auditory and sensorimotor brain regions during listening and speaking. However, previous attempts to decode speech directly from the human brain typically consider listening or speaking tasks in isolation. Here, human participants listened to questions and responded aloud with answers while we used high-density electrocorticography (ECoG) recordings to detect when they heard or said an utterance and to then decode the utterance's identity. Because certain answers were only plausible responses to certain questions, we could dynamically update the prior probabilities of each answer using the decoded question likelihoods as context. We decode produced and perceived utterances with accuracy rates as high as 61% and 76%, respectively (chance is 7% and 20%). Contextual integration of decoded question likelihoods significantly improves answer decoding. These results demonstrate real-time decoding of speech in an interactive, conversational setting, which has important implications for patients who are unable to communicate

Density Functional Study of Ternary Topological Insulator Thin Films

Using an ab-initio density functional theory based electronic structure method with a semi-local density approximation, we study thin-film electronic properties of two topological insulators based on ternary compounds of Tl (Thallium) and Bi (Bismuth). We consider TlBiX$_2$ (X=Se, Te) and Bi$_2$$X$_2$Y (X,Y= Se,Te) compounds which provide better Dirac cones, compared to the model binary compounds Bi$_2$X$_3$ (X=Se, Te). With this property in combination with a structurally perfect bulk crystal, the latter ternary compound has been found to have improved surface electronic transport in recent experiments. In this article, we discuss the nature of surface states, their locations in the Brillouin zone and their interactions within the bulk region. Our calculations suggest a critical thin film thickness to maintain the Dirac cone which is significantly smaller than that in binary Bi-based compounds. Atomic relaxations or rearrangements are found to affect the Dirac cone in some of these compounds. And with the help of layer-projected surface charge densities, we discuss the penetration depth of the surface states into the bulk region. The electronic spectrum of these ternary compounds agrees very well with the available experimental results.Comment: 9 pages, 11 figures, 1 table, Accepted for publication in Physical Review

Controlled Lagrangians and the stabilization of mechanical systems. II. Potential shaping

For pt.I, see ibid., vol.45, p.2253-70 (2000). We extend the method of controlled Lagrangians (CL) to include potential shaping, which achieves complete state-space asymptotic stabilization of mechanical systems. The CL method deals with mechanical systems with symmetry and provides symmetry-preserving kinetic shaping and feedback-controlled dissipation for state-space stabilization in all but the symmetry variables. Potential shaping complements the kinetic shaping by breaking symmetry and stabilizing the remaining state variables. The approach also extends the method of controlled Lagrangians to include a class of mechanical systems without symmetry such as the inverted pendulum on a cart that travels along an incline

Investigation of Structural Dynamics of Enzymes and Protonation States of Substrates Using Computational Tools.

This review discusses the use of molecular modeling tools, together with existing experimental findings, to provide a complete atomic-level description of enzyme dynamics and function. We focus on functionally relevant conformational dynamics of enzymes and the protonation states of substrates. The conformational fluctuations of enzymes usually play a crucial role in substrate recognition and catalysis. Protein dynamics can be altered by a tiny change in a molecular system such as different protonation states of various intermediates or by a significant perturbation such as a ligand association. Here we review recent advances in applying atomistic molecular dynamics (MD) simulations to investigate allosteric and network regulation of tryptophan synthase (TRPS) and protonation states of its intermediates and catalysis. In addition, we review studies using quantum mechanics/molecular mechanics (QM/MM) methods to investigate the protonation states of catalytic residues of β-Ketoacyl ACP synthase I (KasA). We also discuss modeling of large-scale protein motions for HIV-1 protease with coarse-grained Brownian dynamics (BD) simulations

SIRT1 Mediates Central Circadian Control in the SCN by a Mechanism that Decays with Aging

SummarySIRT1 is a NAD+-dependent protein deacetylase that governs many physiological pathways, including circadian rhythm in peripheral tissues. Here, we show that SIRT1 in the brain governs central circadian control by activating the transcription of the two major circadian regulators, BMAL1 and CLOCK. This activation comprises an amplifying circadian loop involving SIRT1, PGC-1α, and Nampt. In aged wild-type mice, SIRT1 levels in the suprachiasmatic nucleus are decreased, as are those of BMAL1 and PER2, giving rise to a longer intrinsic period, a more disrupted activity pattern, and an inability to adapt to changes in the light entrainment schedule. Young mice lacking brain SIRT1 phenocopy these aging-dependent circadian changes, whereas mice that overexpress SIRT1 in the brain are protected from the effects of aging. Our findings indicate that SIRT1 activates the central pacemaker to maintain robust circadian control in young animals, and a decay in this activity may play an important role in aging

Asymptotic stabilization of Euler-Poincaré mechanical systems

Stabilization of mechanical control systems by the method of controlled Lagrangians and matching is used to analyze asymptotic stabilization of systems whose underlying dynamics are governed by the Euler-Poincar´e equations. In particular, we analyze asymptotic stabilization of a satellite