Asphaltene aggregation in organic solvents

Asphaltenic solids formed in the Rangely field in the course of a carbon dioxide flood and heptane insolubles in the oil from the same field were used in this study. Four different solvents were used to dissolve the asphaltenes. Near-infrared (NIR) spectroscopy was used to determine the onset of asphaltene precipitation by heptane titration. When the onset values were plotted versus asphaltene concentrations, distinct break points (called critical aggregation concentrations (CAC) in this paper) were observed. CACs for the field asphaltenes dissolved in toluene, trichloroethylene, tetrahydrofuran, and pyridine occurred at concentrations of 3.0, 3.7, 5.0, and 8.2 g/l, respectively. CACs are observed at similar concentrations as critical micelle concentrations (CMC) for the asphaltenes in the solvents employed and can be interpreted to be the points at which rates of asphaltene aggregations change. CMC values of asphaltenes determined from surface tension measurements (in pyridine and TCE) were slightly higher than the CAC values measured by NIR onset measurements. The CAC for heptane-insoluble asphaltenes in toluene was 3.1 g/l. Thermal gravimetric analysis (TGA) and elemental compositions of the two asphaltenes showed that the H/C ratio of the heptane-insoluble asphaltenes was higher and molecular weight (measured by vapor pressure osmometry) was lower.     

Health risk assessment for nanoparticles: A case for using expert judgment

Uncertainties in conventional quantitative risk assessment typically relate to values of parameters in risk models. For many environmental contaminants, there is a lack of sufficient information about multiple components of the risk assessment framework. In such cases, the use of default assumptions and extrapolations to fill in the data gaps is a common practice. Nanoparticle risks, however, pose a new form of risk assessment challenge. Besides a lack of data, there is deep scientific uncertainty regarding every aspect of the risk assessment framework: (a) particle characteristics that may affect toxicity; (b) their fate and transport through the environment; (c) the routes of exposure and the metrics by which exposure ought to be measured; (d) the mechanisms of translocation to different parts of the body; and (e) the mechanisms of toxicity and disease. In each of these areas, there are multiple and competing models and hypotheses. These are not merely parametric uncertainties but uncertainties about the choice of the causal mechanisms themselves and the proper model variables to be used, i.e., structural uncertainties. While these uncertainties exist for PM2.5 as well, risk assessment for PM2.5 has avoided dealing with these issues because of a plethora of epidemiological studies. However, such studies don’t exist for the case of nanoparticles. Even if such studies are done in the future, they will be very specific to a particular type of engineered nanoparticle and not generalizable to other nanoparticles. Therefore, risk assessment for nanoparticles will have to deal with the various uncertainties that were avoided in the case of PM2.5. Consequently, uncertainties in estimating risks due to nanoparticle exposures may be characterized as ‘extreme’. This paper proposes a methodology by which risk analysts can cope with such extreme uncertainty. One way to make these problems analytically tractable is to use expert judgment approaches to study the degree of consensus and/or disagreement between experts on different parts of the exposure–response paradigm. This can be done by eliciting judgments from a wide range of experts on different parts of the risk causal chain. We also use examples to illustrate how studying expert consensus/disagreement helps in research prioritization and budget allocation exercises. The expert elicitation can be repeated over the course of several years, over which time, the state of scientific knowledge will also improve and uncertainties may possibly reduce. Results from expert the elicitation exercise can be used by risk managers or managers of funding agencies as a tool for research prioritization.     

Unstable flux flow due to heated electrons in superconducting films

A flux instability occurs in superconductors at low temperatures, where e-e scattering is more rapid than e-ph, whereby the dissipation significantly elevates the electronic temperature while maintaining a thermal-like distribution function. The reduction in condensate and rise in resistivity produce a nonmonotonic current-voltage response. In contrast to the Larkin-Ovchinnikov instability where the vortex shrinks, in this scenario the vortex expands and the quasiparticle population rises. Measurements in Y(1)Ba(2)Cu(3)O(7-delta) agree quantitatively with the distinct predictions of this mechanism.     

Horses for courses: risk information and decision making in the regulation of nanomaterials

Despite the widespread commercial use of nanomaterials, regulators currently have a limited ability to characterize and manage risks. There is a paucity of data available on the current production and use of nanomaterials and extreme scientific uncertainty on most aspects of the risk assessment “causal chain.” Regulatory decisions will need to be made in the near-term in the absence formal quantitative risk assessments. The article draws on examples from three different regulatory contexts—baseline data monitoring efforts of the U.S. Environmental Protection Agency and California Department of Toxic Substances Control, prioritization of risk information in the context of environmental releases, and mitigation of occupational risks—to argue for the use of decision-analytic tools in lieu of formal risk assessment to help regulatory bodies. We advocate a “horses for courses” approach whereby existing analytical tools (such as risk ranking, multi-criteria decision analysis, and “control banding” approaches) might be adapted to regulators’ goals in particular decision contexts. While efforts to build new and modify existing tools are underway, they need greater support from funding and regulatory agencies because innovative approaches are needed for the “extreme” uncertainty problems that nanomaterials pose.     

Direct Allylation of In Situ Generated Aldehyde Acyl Anions by Synergistic NHC and Palladium Catalysis

The direct regioselective allylation of in situ generated aldehyde acyl anions has been achieved by synergistic NHC and Pd catalysis. It provides an efficient access to valuable β,γ‐unsaturated ketones under mild reaction conditions starting from easily accessible allylic carbonates and aldehydes without any preactivation. The synergistic catalysis method demonstrated herein adds a new dimension to the area of metal‐mediated C allylation.     

Intramolecular hydrogen bonding and cooperative interactions in carbohydrates via the molecular tailoring approach

In spite of many theoretical and experimental attempts for understanding intramolecular hydrogen bonding (H-bonding) in carbohydrates, a direct quantification of individual intramolecular H-bond energies and the cooperativity among the H-bonded networks has not been reported in the literature. The present work attempts, for the first time, a direct estimation of individual intramolecular O-H...O interaction energies in sugar molecules using the recently developed molecular tailoring approach (MTA). The estimated H-bond energies are in the range of 1.2-4.1 kcal mol(-1). It is seen that the OH...O equatorial-equatorial interaction energies lie between 1.8 and 2.5 kcal mol(-1), with axial-equatorial ones being stronger (2.0-3.5 kcal mol(-1)). The strongest bonds are nonvicinal axial-axial H-bonds (3.0-4.1 kcal mol(-1)). This trend in H-bond energies is in agreement with the earlier reports based on the water-water H-bond angle, solvent-accessible surface area (SASA), and (1)H NMR analysis. The contribution to the H-bond energy from the cooperativity is also estimated using MTA. This contribution is seen to be typically between 0.1 and 0.6 kcal mol(-1) when H-bonds are a part of a relatively weak equatorial-equatorial H-bond network and is much higher (0.5-1.1 kcal mol(-1)) when H-bonds participate in an axial-axial H-bond network.     

Two-step evaluation of binding energy and potential energy surface of van der Waals complexes

Evaluation of intermolecular distance and binding energy (BE) of van der Waals complex/cluster at ab initio level of theory is computationally demanding when many monomers are involved. Starting from MP2 energy, we reached a two-step evaluation method of BE of van der Waals complex/cluster through reasonable approximations; BE = BE(HF) + sum Mi> Mj{BE (Mi- Mj)(MP2 or MP2.5) - BE(Mi-Mj)(HF)} where HF represents the Hartree-Fock calculation, Mi, Mj, etc. are interacting monomers, and MP2.5 represents the arithmetic mean of MP2 and MP3. The first term is the usual BE of the complex/cluster evaluated at the HF level. The second term is the sum of the difference in two-body BE between the correlated and HF levels of theory. This equation was applied to various van der Waals complexes consisting of up-to-four monomers at MP2 and MP2.5 levels of theory. We found that this method is capable of providing precise estimate of the BE and reproducing well the potential energy surface of van der Waals complexes/clusters; the maximum error of the BE is less than 1 kcal/mol and 1% in most cases except for several limited cases. The origins of error in these cases are discussed in detail.     

Cation interdiffusion model for enhanced oxygen kinetics at oxide heterostructure interfaces

An interface between the perovskite La(0.8)Sr(0.2)CoO(3-δ) (LSC-113) and the K(2)NiF(4)-type (La(0.5)Sr(0.5))(2)CoO(4-δ) (LSC-214) heterostructure was recently shown to enhance oxygen surface exchange and the rate of the oxygen reduction reaction (ORR) by orders of magnitude compared to either the LSC-113 or LSC-214 phase alone. This result is of interest to develop better optimized materials for solid-state electrochemical devices, e.g. solid oxide fuel cells. The effect has been attributed to the interface itself, rather than changes in the bulk LSC-113 or LSC-214 phases. Using density functional theory (DFT)-based simulations, we demonstrate that there is a ～0.9 eV (～1.3 eV) energy gain for exchanging a Sr from LSC-113(25%Sr) (LSC-113(40%Sr)) with a La from LSC-214(50%Sr). These changes in energy create a large driving force for interdiffusion across the heterostructure interface from Sr into LSC-214 and La into LSC-113. We estimate that the Sr concentrations (in the LSC-214 phase) in a typical experimental temperature range of 500-600 °C and in equilibrium with LSC-113(25%Sr) and LSC-113(40%Sr), may be about 75% Sr and 90% Sr, respectively. Based on the bulk behavior of the LSC-214 phase (Vashook et al., Solid State Ionics, 2000, 138, 99-104), an Sr enrichment from x = 0.5 to x = 0.75 in (La(1-x)Sr(x))(2)CoO(4-δ) is expected to enhance the oxygen vacancy concentration by 2-2.5 orders of magnitude under typical experimental conditions. An increased vacancy concentration in LSC-214 near the interface can explain most of the enhanced oxygen kinetics observed up until now in these heterostructures.