ExxonMobil

About: ExxonMobil is a company organization based out in Irving, Texas, United States. It is known for research contribution in the topics: Catalysis & Polymer. The organization has 16969 authors who have published 23758 publications receiving 535713 citations. The organization is also known as: Exxon Mobil Corporation & Exxon Mobil Corp..

Solution behavior of ionomers. I. Metal sulfonate ionomers in mixed solvents

Abstract: The solution behavior of metal sulfonate-containing ionomers has been investigated in various mixed solvent systems. Ionomers, such as lightly sulfonated polystyrene (sodium salt) and sulfonated ethylene-propylene-diene terpolymer (metal salts) are generally insoluble in typical hydrocarbon solvents, but readily dissolve when small amounts of alcohols or other polar cosolvents are present. At relatively low polymer concentration these ionomers display unusually high thickening behavior in nonpolar solvents when compared with nonionic polymers because of association of the metal sulfonate groups. The addition of modest levels of polar cosolvent markedly decreases the solution viscosity and gives rise to viscosity-temperature relationships different from those of conventional polymer solutions. For example, such solutions can display vicosities which increase, are relatively constant, or display maxima or minima over broad temperature ranges. These observations are interpreted as arising from a temperature-dependent preferential interaction of the cosolvent with the sulfonate groups. While these ionomers can be regarded as polyelectrolytes of low charge density, they do not display the typical “polyelectrolyte” behavior often observed in aqueous solutions. This anomalous behavior is attributed to the fact that the metal sulfonate groups are largely un-ionized in solvents of low dielectric constant. Therefore, the solution behavior is dominated by ion pair interactions rather than free ions.

Maximum statistical increase of optical absorption in textured semiconductor films.

Abstract: Complete statistical randomization of the direction of propagation of light trapped in semiconductor films can result in a large absorption enhancement. We have employed a calorimetric technique, photothermal deflection spectroscopy, to monitor the absorption of alpha-SiH(x) films textured by the natural lithography process. The observed enhancement factors, as high as 11.5, are consistent with full internal phase-space randomization of the incoming light.

Application of abnormal event detection technology to delayed coking unit

Abstract: The present invention is a method for detecting an abnormal event for process units of a Delayed Coking Unit. The method compares the operation of the process units to statistical and engineering models. The statistical models are developed by principal components analysis of the normal operation for these units. The engineering models are based statistical and correlation analysis between variables. If the difference between the operation of a process unit and the normal model result indicates an abnormal condition, then the cause of the abnormal condition is determined and corrected.

Learning to Run Heuristics in Tree Search.

Abstract: “Primal heuristics” are a key contributor to the improved performance of exact branch-and-bound solvers for combinatorial optimization and integer programming. Perhaps the most crucial question concerning primal heuristics is that of at which nodes they should run, to which the typical answer is via hard-coded rules or fixed solver parameters tuned, offline, by trial-and-error. Alternatively, a heuristic should be run when it is most likely to succeed, based on the problem instance’s characteristics, the state of the search, etc. In this work, we study the problem of deciding at which node a heuristic should be run, such that the overall (primal) performance of the solver is optimized. To our knowledge, this is the first attempt at formalizing and systematically addressing this problem. Central to our approach is the use of Machine Learning (ML) for predicting whether a heuristic will succeed at a given node. We give a theoretical framework for analyzing this decision-making process in a simplified setting, propose a ML approach for modeling heuristic success likelihood, and design practical rules that leverage the ML models to dynamically decide whether to run a heuristic at each node of the search tree. Experimentally, our approach improves the primal performance of a stateof-the-art Mixed Integer Programming solver by up to 6% on a set of benchmark instances, and by up to 60% on a family of hard Independent Set instances.

Two catalyst process for making olefin

Abstract: This invention is to a process of making olefin, particularly ethylene and propylene, from an oxygenate feed. The invention uses two or more zeolite catalysts. Examples of zeolite catalysts include a first catalyst containing of ZSM-5, and a second catalyst containing a 10-ring molecular sieve, including but not limited to, ZSM-22, ZSM-23, ZSM35, ZSM-48, and mixtures thereof. The ZSM-5 can be unmodified, phosphorous modified, steam modified having a micropore volume reduced to not less than 50% of that of the unsteamed ZSM-5, or various mixtures thereof.