Non-associating Components Research Articles

Prediction of ionic liquids solubility parameter using PC-SAFT equation of state

In this work, the solubility parameters of three families of ionic liquids (ILs) have been predicted using the PC-SAFT equation of state (EoS). The effect of association interaction between ILs molecules on the solubility parameter has been studied. Four scenarios have been considered to optimize the model parameters. In scenario 1, the ILs have been considered as non-associating components and in scenarios 2 to 4, 2B, 3B, and 4C schemes for association interaction between ILs molecules have been considered. The model parameters have been obtained using liquid density experimental data. The molecular approach has been utilized to optimize the model parameters. Using obtained model parameters, the solubility parameter of ILs has been predicted without using any additional adjustable parameter. The results show that, the association schemes have a minor effect on solubility parameter prediction. For all scenarios, the PC-SAFT EoS predicts the solubility parameter at various temperatures satisfactory. This model can be of great interest to engineers to select and design the optimum solvent for specific processes.

Slow or sudden: Re-interpreting the learning curve for modern systems neuroscience.

Learning is fundamental to animal survival. Animals must learn to link sensory cues in the environment to actions that lead to reward or avoid punishment. Rapid learning can then be highly adaptive and the difference between life or death. To explore the neural dynamics and circuits that underlie learning, however, has typically required the use of laboratory paradigms with tight control of stimuli, action sets, and outcomes. Learning curves in such reward-based tasks are reported as slow and gradual, with animals often taking hundreds to thousands of trials to reach expert performance. The slow, highly variable, and incremental learning curve remains the largely unchallenged belief in modern systems neuroscience. Here, we provide historical and contemporary evidence that instrumental forms of reward-learning can be dissociated into two parallel processes: knowledge acquisition which is rapid with step-like improvements, and behavioral expression which is slower and more variable. We further propose that this conceptual distinction may allow us to isolate the associative (knowledge-related) and non-associative (performance-related) components that influence learning. We then discuss the implications that this revised understanding of the learning curve has for systems neuroscience.

The trade-off between experimental effort and accuracy for determination of PCP-SAFT parameters

Parameterizing equations of state is often a compromise between minimizing experimental effort and maximizing accuracy of the calculated thermodynamic properties. Parameter prediction methods can avoid experimental effort altogether. Alternatively, we need at least as many experimental property data points as the number of model parameters to parameterize the equation of state. Thus, for PCP-SAFT, we need at least three experimental data points corresponding to the three parameters required to model non-associating components. In this work, we present a systematic approach to combine predicted parameters with data points chosen by Optimal Experimental Design. This approach allows to find a trade-off between experimental effort and accuracy of the estimated thermodynamic properties. Predicted parameters yield an average RMSD (root mean square relative deviation) of 40% from vapor pressure data. Combining predicted parameters with one optimally chosen data point for vapor pressure yields already an accuracy of 4% average RMSD in vapor pressure. The presented approach allows to obtain PCP-SAFT parameters which are more accurate than the predicted parameters at a lower experimental effort than required for parameter fitting without predictive information. Our results can serve as a guide for the practitioner to evaluate the minimal experimental effort necessary in order to reach a desired accuracy.

Development of a multiphase flash in presence of hydrates: Experimental measurements and validation with the CPA equation of state

A new robust flash algorithm was developed for equilibrium calculation in systems with clathrate hydrates. The algorithm is based on the minimization of the Gibbs free energy by solving the reformulated Richford–Rice equation. Special considerations have been taken for the algorithm to work with clathrate hydrates of different structures. In the current work, the cubic plus association equation of state (combined with the Peng–Robinson equation of state and a group contribution method to calculate binary interaction parameters between non-associating components) is used to calculate fugacity in fluid phases while the van der Waals and Platteeuw approach is used to calculate the fugacity of water in the hydrate phase.The developed algorithm has been applied to complex multicomponent example systems for which experimental data are available as well as new experimental data on both hydrate dissociation points and composition of vapour phase in equilibrium with hydrates inside the hydrate phase boundary for a natural gas. The new algorithm is fast and offers a simple routine for initial guess calculation and is capable of showing complex behaviours in hydrate forming systems including stability of more than one hydrate structure at equilibrium conditions and pseudo-retrograde behaviour in hydrate formation. For the examples used in this work, a good agreement between the experimental measurements and predictions is observed, demonstrating the reliability of the approach.

Estimation of the binary interaction parameter kij of the PC-SAFT Equation of State based on pure component parameters using a QSPR method

Statistical Associating Fluid Theory (SAFT) equations of state (EoS) for mixtures require cross-interaction parameters. For real systems, combining rules, such as the Lorenz-Berthelot combining rules, have to be corrected using at least one binary interaction parameter, kij. Values of kij are usually adjusted to experimental data of phase equilibria. Here, we correlate kij to the pure component parameters of the Perturbed Chain – Statistical Associating Fluid Theory (PC-SAFT) EoS, using a Quantitative Structure Property Relationship (QSPR) model. The coefficients of the proposed QSPR model are regressed separately for mixtures with non-associating components and for mixtures with associating components. The QSPR model is validated using the statistical measures of the QSPR method. We compare the values of kij that are estimated from the QSPR model to values of kij estimated from London's dispersive theory. Phase equilibrium calculations carried out with these two approaches of estimating kij values are compared to experimental data. The estimation of kij values as function of the pure component PC-SAFT parameters can be applied to problems of process design and in Computer Aided Molecular Design (CAMD), to allow for calculations that are reasonably accurate and independent from the availability of experimental mixture data.

Modeling adsorption in binary associating solvents using the extended MPTA model

Application of the MPTA model has been extended to associative liquid adsorption. The MPTA model describes fluid–fluid interactions using an equation of state (EoS) term, and fluid–solid interactions using a potential equation. In order to extend the application to associative liquid adsorption, an association term has been considered for fluid–fluid interactions. Sixteen binary mixtures containing associating and non-associating components in equilibrium with various adsorbents have been studied; fluid–fluid interactions have been modeled using the Peng–Robinson, Soave–Redlich–Kwong, volume-translated SRK and CPA equations of state, while the effects of fluid–solid interactions have been taken into account using Dubinin–Radushkevich–Astakhov (DRA) and Steele potential functions. The model parameters have been obtained by fitting the model to experimental data on surface excess. For the studied systems, the accuracy of fitted isotherms has been found to be more dependent on the fluid–solid potential equation rather than the applied EoS. Calculations show that the SRK equation is a suitable choice for non-associating systems, while the CPA equation is found to be more appropriate for associating systems, as would be expected. The results also show that the Steele potential function is in better agreement with experimental data than the DRA potential function.

Role of bed nucleus of the stria terminalis and amygdala AMPA receptors in the development and expression of context conditioning and sensitization of startle by prior shock

A core symptom of post-traumatic stress disorder is hyper-arousal-manifest in part by increases in the amplitude of the acoustic startle reflex. Gewirtz et al. (Prog Neuropsychopharmacol Biol Psychiatry 22:625-648, 1998) found that, in rats, persistent shock-induced startle increases were prevented by pre-test electrolytic lesions of the bed nucleus of the stria terminalis (BNST). We used reversible inactivation to determine if similar effects reflect actions on (a) BNST neurons themselves versus fibers-of-passage, (b) the development versus expression of such increases, and (c) associative fear versus non-associative sensitization. Twenty-four hours after the last of three shock sessions, startle was markedly enhanced when rats were tested in a non-shock context. These increases decayed over the course of several days. Decay was unaffected by context exposure, and elevated startle was restored when rats were tested for the first time in the original shock context. Thus, both associative and non-associative components could be measured under different conditions. Pre-test intra-BNST infusions of the AMPA receptor antagonist NBQX (3μg/side) blocked the non-associative (as did infusions into the basolateral amygdala) but not the associative component, whereas pre-shock infusions disrupted both. NBQX did not affect baseline startle or shock reactivity. These results indicate that AMPA receptors in or very near to the BNST are critical for the expression and development of non-associative shock-induced startle sensitization, and also for context fear conditioning, but not context fear expression. More generally, they suggest that treatments targeting the BNST may be clinically useful for treating trauma-related hyper-arousal and perhaps for retarding its development.

Effect of Asphaltene Structure on Association and Aggregation Using Molecular Dynamics

The aggregation of asphaltenes has been established for decades by numerous experimental techniques; however, very few studies have been performed on the association free energy and asphaltene aggregation in solvents. The lack of reliable and coherent data on the free energy of association and aggregation size of asphaltene has imposed severe limitations on the thermodynamic modeling of asphaltene phase behavior. Current thermodynamic models either consider asphaltenes as non-associating components or use fitting parameters to characterize the association. In this work, the relations between Gibbs free energy of asphaltene association and asphaltene molecular structure are studied using molecular dynamics (MD). The free energy of association is computed from the potential of mean force profile along the separation distance between the centers of mass of two asphaltene molecules using the umbrella sampling technique in the GROMACS simulation package. The average aggregation number for asphaltene nanoaggregates and clusters is also calculated through MD simulations of 36 asphaltene molecules in toluene and heptane in order to estimate the effects of association free energy and steric repulsion on the aggregation behavior of asphaltenes. Our simulation results confirm that the interactions between aromatic cores of asphaltene molecules are the major driving force for association as the energy of association increases substantially with the number of aromatic rings. Moreover, heteroatoms attached to the aromatic cores have much more influence on the association free energy than to ones attached to the aliphatic chains. The length and number of aliphatic chains do not seem to have a noticeable effect on asphaltene dimerization; however, they have a profound effect on asphaltene aggregation size since steric repulsion can prevent asphaltenes from forming T-shape configurations and therefore decrease the aggregation size of asphaltenes significantly. Our MD simulation results show for the first time asphaltene precipitation in heptane as an explicit solvent, and predict three distinct stages of aggregation (nanoaggregation, clustering, and flocculation) as proposed by the modified Yen model. Finally, the association free energy for asphaltenes in heptane is higher than that in toluene, which is consistent with asphaltene aggregate sizes obtained from MD simulations.

Molecular Weight and Density Distributions of Asphaltenes from Crude Oils

Asphaltenes self-associate, and the molecular weight and density distributions are a factor in asphaltene precipitiation. To determine these distributions, heptane-extracted asphaltenes from four crude oils were fractionated into solubility cuts. The asphaltenes were dissolved in toluene and then partially precipitated at specified ratios of heptane/toluene to generate sets of light (soluble) and heavy (insoluble) cuts. The molecular weight and density were measured for each cut. The asphaltenes were found to include both associating and non-associating asphaltenes. The content of non-associating components was up to 15 wt % of the asphaltenes. The density distributions were determined directly from the data. The molecular weight data were fitted with a self-association model to predict the distributions at any given concentration. Then, a guideline was developed to represent the molecular weight distribution of non-associated and associated asphaltenes with a Γ distribution function. Finally, the density of asphaltene cuts was correlated to their molecular weight. This correlation fit the data with an average absolute deviation of 11 kg/m3.

Minimal Experimental Data Set Required for Estimating PCP-SAFT Parameters

The pure-component parameters of the Perturbed Chain Polar-Statistical Associating Fluid Theory (PCP-SAFT) equation of state are usually fitted to experimental data over broad temperature ranges. Against a background of limited experimental data, this article examines the amount and type of experimental data that are minimally required for safe parameter estimation. For nonassociating components, a minimal data set containing three data points is sufficient. For associating components, five data points are sufficient. The influence of vapor-pressure data on parameter estimation and the modeling results is larger than that of liquid-volume data. The temperature ranges of the experimental data can be chosen to be as small as 5 K for all of the data, except for the vapor pressures of associating components. These data require a range of at least 20 K. Application of the parameters fitted to the minimal experimental data set led to convincing results for the modeling of pure-component properties and binary mixtures.

Extinction after retrieval: Effects on the associative and nonassociative components of remote contextual fear memory

Long-lasting memories of adverse experiences are essential for individuals' survival but are also involved, in the form of recurrent recollections of the traumatic experience, in the aetiology of anxiety diseases (e.g., post-traumatic stress disorder [PTSD]). Extinction-based erasure of fear memories has long been pursued as a behavioral way to treat anxiety disorders; yet, such a procedure turns out to be transient, context-dependent, and ineffective unless it is applied immediately after trauma. Recent evidence indicates that, in both rats and humans, extinction training can prevent the return of fear if administered within the reconsolidation window, when memories become temporarily labile and susceptible of being updated. Here, we show that the reconsolidation-extinction procedure fails to prevent the spontaneous recovery of a remote contextual fear memory in a mouse model of PTSD, as well as the long-lasting behavioral abnormalities induced by traumatic experience on anxiety and in both social and cognitive domains (i.e., social withdrawal and spatial learning deficits). Such a failure appears to be related to the ineffectiveness of the reconsolidation-extinction procedure in targeting the pathogenic process of fear sensitization, a nonassociative component of traumatic memory that causes animals to react aberrantly to harmless stimuli. This indicates fear sensitization as a major target for treatments aimed at mitigating anxiety and the behavioral outcomes of traumatic experiences.

Two streams make a river: The rabbit in Richard F. Thompson’s laboratory

The rabbit nictitating membrane (NM) preparation was developed in 1962 by Gormezano as a model system for classical conditioning. It had many features that made it ideal for use in exploring the laws of this conditioning paradigm, including easily obtainable subjects, good control of stimulus delivery and precise response specifications. Most importantly, the preparation evidenced very low spontaneous response rates and showed no evidence of nonassociative effects of sensitization and pseudoconditioning and had highly predictable learning functions. In contrast, previous human and animal models that had been utilized to explore the features of classical conditioning, such as the dog salivary model were far less easy to use, showed high spontaneous response rates, and had high nonassociative components. Over the ensuing years, Gormezano and his students characterized most of the parametric characteristics of classical conditioning with the use of the preparation. In 1970, Richard Thompson began exploring the use of the rabbit NM preparation in his laboratory as a model system with which to explore the brain substrates of classical conditioning. At the time, his work was centered around exploring the neural substrates of sensitization and habituation in spinal reflexes. Soon, however, he turned his attention to the brain substrates of classical conditioning almost exclusively, and produced an impressive amount of data detailing the neural underpinnings of classical conditioning. His work has generated perhaps the most detailed and complete picture of the neural mechanisms of learning currently available, and has led to countless other research efforts in the area of brain and behavior. Current understandings of neural mechanisms of associative learning owe much to Thompson and his various colleagues.

Blocking GABAA neurotransmission in the interposed nuclei: Effects on conditioned and unconditioned eyeblinks

The interposed nuclei (IN) of the intermediate cerebellum are critical components of the circuits that control associative learning of eyeblinks and other defensive reflexes in mammals. The IN, which represent the sole output of the intermediate cerebellum, receive massive GABAergic input from Purkinje cells of the cerebellar cortex and are thought to contribute to the acquisition and performance of classically conditioned eyeblinks. The specific role of deep cerebellar nuclei and the cerebellar cortex in eyeblink conditioning are not well understood. One group of studies reported that blocking GABAA neurotransmission in the IN altered the time profile of conditioned responses (CRs), suggesting that the main function of the cerebellar cortex is to shape the timing of CRs. Other studies reported that blocking GABAA neurotransmission in the IN abolished CRs, indicating a more fundamental involvement of the cerebellar cortex in CR generation. When examining this controversy, we hypothesized that the behavioral effect of GABAA blockers could be dose-dependent. The IN of classically conditioned rabbits were injected with high and low doses of picrotoxin and gabazine. Both GABAA blockers produced tonic eyelid closure. A high dose of both drugs abolished CRs, whereas a less complete block of GABAA-mediated inputs with substantially smaller drug doses shortened CR latencies. In addition, low doses of picrotoxin facilitated the expression of unconditioned eyeblinks evoked by trigeminal stimulation. These results suggest that the intermediate cerebellum regulates both associative and non-associative components of the eyeblink reflex, and that behavioral effects of blocking Purkinje cell action on IN neurons are related to collective changes in cerebellar signals and in the excitability of extra-cerebellar eyeblink circuits.

Application of a New Statistical Mechanical Model for Calculating Kirkwood Factors in Alkanol−Heptane Mixtures

A recently developed statistical mechanical model for predicting Kirkwood factors in self-associating molecular liquids and their mixtures with nonassociating components has been applied for the simultaneous description of the Kirkwood correlation factor, gK, and the molar enthalpy of mixing, Hm(E), as a function of the composition in alkanol-heptane mixtures. Most of the molecular parameters involved in the theory have been fixed by independent quantum mechanical ab initio calculations of associated molecular clusters. The model is also able to predict other thermodynamic mixture properties such as the enthalpy of mixing. Experimental results of nine alcohol-heptane mixtures taken from the literature have been used to test the new model. The Kirkwood correlation factor gK and the molar enthalpy of mixing Hm(E) can be described simultaneously with an excellent agreement with experimental data covering the whole range of mole fraction, including temperature dependence. Two parameters have been adjusted freely for each system. A third parameter for the nonspecific intermolecular dispersion interactions has been adjusted within a limited range of possible values given by physical arguments. The successful application of the model opens a new way to a more reliable understanding of structures and equilibrium properties of such liquid systems.

New statistical mechanical model for calculating Kirkwood factors in self-associating liquid systems and its application to alkanol+cyclohexane mixtures

A new statistical mechanical model for calculating Kirkwood factors in self-associating molecular liquids and their mixtures with nonassociating components has been developed in a consistent way which is based on an extended version of the Flory-Huggins model taking into account chemical association equilibria. The majority of molecular parameters involved into the theory has been fixed by independent quantum mechanical ab initio calculations of associated molecular clusters. The model is also able to predict other thermodynamic mixture properties such as the enthalpy of mixing and also the infrared absorbance of monomer alcohol species as function of concentration. Experimental results of nine alcohol+cyclohexane mixtures taken from the literature have been used to test the new model. The Kirkwood correlation factor gK, the molar enthalpy of mixing HmE, and the monomer IR absorbance can be described simultaneously in excellent agreement with experimental data covering the whole range of mole fraction including temperature dependence of gK, HmE, and the IR absorbance. Two parameters have been adjusted freely for each system. A third parameter for the nonspecific intermolecular dispersion interactions has been adjusted within a limited range of possible values given by physical arguments. The model opens a new way of a more reliable understanding of structures and equilibrium properties of hydrogen bonded systems in the condensed liquid state.

The parasitic mite Varroa destructor affects non-associative learning in honey bee foragers, Apis mellifera L.

The parasitic mite Varroa destructor influences flight behavior, orientation and returning success of forager honeybees (Apis mellifera) infested as adults. As impaired orientation toward the nest entrance might be due to deficiency in recognition and responsiveness to stimuli in the environment, we examined effects of V. destructor on sensory responsiveness, non-associative and associative learning of honey bee foragers by using proboscis extension reaction paradigm (PER). Although infested and uninfested workers were initially equally responsive to different concentrations of sugar water, we found differences in non-associative learning. In habituation, PER to repeated sugar stimulation of the antennae occurred faster in infested foragers compared to uninfested foragers. In sensitization, infested foragers showed a lower response to an odor stimulus following sugar stimulation than non-infested foragers. Differences in non-associative paradigms were more pronounced in bees with lower responsiveness to sucrose. In conditioning learning experiments, a significant reduction in proboscis extension response was found 1 min but not 12 min after a single conditioning trial indicating that V. destructor predominantly affects the non-associative components of learning and its underlying neural and molecular processes.

A mouse model of posttraumatic stress disorder that distinguishes between conditioned and sensitised fear

The pathomechanisms of posttraumatic stress disorder (PTSD) are still unknown, but both fear conditioning and stress sensitisation are supposed to play a crucial role. Hence, valid animal models that model both associative and non-associative components of fear will facilitate elucidation of the biological substrates of the illness, and to develop novel and specific approaches for its prevention and therapy. Here we applied a single electric footshock to C57BL/6N (B6N) and C57BL/6JOla (B6JOla) mice and recorded the conditioned response to contextual trauma reminders (associative fear), the sensitised reaction to a neutral tone in a novel environment (non-associative fear, hyperarousal), social interaction and various emotional behaviours using Modified Holeboard, Test for Novelty-Induced Suppression of Feeding and Forced Swimming Test, after different incubation times (1, 14, 28 days). Freezing generally increased as a function of shock intensity. In B6N mice, sensitised fear was maximal 28 days after trauma and was accompanied by signs of emotional blunting and social withdrawal. B6JOla mice, in contrast, were less susceptible to develop PTSD-like symptoms. The phenotype of B6N exhibited high behavioural variance, allowing distinction between vulnerable and resilient individuals. Only in vulnerable B6N mice, chronic fluoxetine treatment – initiated after an incubation period of 28 days – ameliorated sensitised fear. This new mouse model fulfils common criteria for face and predictive validity and can be used to investigate the biological correlates of individual fear susceptibility, as well as the impact and interrelationship of associative and non-associative fear components in the development and maintenance of PTSD.

Effects of 4-aminopyridine on classical conditioning of the rabbit (Oryctolagus cuniculus) nictitating membrane response

A large body of data suggests that potassium channels may play an important role in learning and memory. Previous in-vitro research in a number of species including Hermissenda and the rabbit suggests that a 4-aminopyridine-sensitive transient potassium channel may be involved in classical conditioning. We investigated the effects of in-vivo 4-aminopyridine administration (0.5 mg/kg) on classical conditioning of the rabbit nictitating membrane response using a battery of tests designed to assess the associative, sensory, and motor contributors of 4-aminopyridine to responding. 4-Aminopyridine enhanced both classical conditioning and conditioning-specific reflex modification compared with a saline vehicle control, and these effects had several nonassociative components including an increase in the frequency of responding to both the conditioned and the unconditioned stimuli, suggesting a sensitizing effect of the drug. Although 4-aminopyridine can have peripheral effects, it may also modify cerebellar excitability or hippocampal neurotransmitter balance resulting in heightened responsiveness to stimulation.

Differential transcriptional response to nonassociative and associative components of classical fear conditioning in the amygdala and hippocampus

Classical fear conditioning requires the recognition of conditioned stimuli (CS) and the association of the CS with an aversive stimulus. We used Affymetrix oligonucleotide microarrays to characterize changes in gene expression compared to naive mice in both the amygdala and the hippocampus 30 min after classical fear conditioning and 30 min after exposure to the CS in the absence of an aversive stimulus. We found that in the hippocampus, levels of gene regulation induced by classical fear conditioning were not significantly greater than those induced by CS alone, whereas in the amygdala, classical fear conditioning did induce significantly greater levels of gene regulation compared to the CS. Computational studies suggest that transcriptional changes in the hippocampus and amygdala are mediated by large and overlapping but distinct combinations of molecular events. Our results demonstrate that an increase in gene regulation in the amygdala was partially correlated to associative learning and partially correlated to nonassociative components of the task, while gene regulation in the hippocampus was correlated to nonassociative components of classical fear conditioning, including configural learning.

05/00904 Procedure for determination of combustion relevant data of combustible materials planned for energy generation

An association model recently introduced by the author [D. Browarzik, Fluid Phase Equilibr. 217 (2004) 125–135] is modified and applied to more systems including aqueous systems. The model is based on chemical theory, on a GE-expression and on continuous thermodynamics and, is focused to the simultaneous description of liquid–liquid equilibrium (LLE) and vapor–liquid equilibrium (VLE). There is an improved calculation of the vapor pressure of the hypothetical pure associates. Furthermore, the calculation of the segment numbers in this version is based on van der Waals volumes. The model permits phase-equilibrium calculations of binary systems consisting of an associating and a non-associating component. The associating component is considered to be a mixture of associates with the composition described by a continuous distribution function that depends on temperature and on one of the mole fractions of the binary system. The equilibrium constant of association is fitted to vapor-pressure data of the associating components. The model needs only one interaction parameter depending on temperature. The accuracy of the simultaneous description of LLE and VLE is reasonably well. The systems considered are: n-pentane + methanol, n-hexane + methanol, n-heptane + methanol, n-octane + methanol, carbon disulfide + methanol, n-hexane + ethanol (VLE only), hexadecane + ethanol, 2-butanone + water, tetrahydrofuran + water.