Advances in rapid and effective break-in/conditioning/recovery of automotive PEMFC stacks

Automotive proton exchange membrane fuel cell stacks need to meet manufacturer specified rated beginning-of-life (BOL) performance before being assembled into vehicles and shipped off to customers. The process of “breaking-in” of a freshly assembled stack is often referred to as “conditioning.” It has become an intensely researched area especially in automotive companies, where imminent commercialization of fuel cell electric vehicles (FCEVs) demands a short, energy- and cost-efficient, and practical conditioning protocol. Significant advances in reducing the conditioning time from 1 to 2 days to as low as 4h or less, in some cases without the use of additional inert gases such as nitrogen, and with minimal use of hydrogen, and specialized test stations will be discussed.     

13C and 1H NMR analysis of the nitration products of 2-amino-4-oxo-(3H)-5-trifluoromethylquinazoline and 2-amino-4-oxo-(3H)-5-fluoroquinazoline

Nitration of 2-amino-4-oxo-(3H)-5-trifluoromethylquinazoline is shown to occur exclusively at C⁶ as determined from an analysis of long range ¹H and ¹⁹F scalar couplings to ring carbons. Nitration of 2-amino-4-oxo-(3H)-5-fluoroquinazoline is found to occur both at C⁶ and C⁸ as evident from an analysis of the ¹⁹F and ¹H couplings of the ring protons.     

The effect of rapid rotation on a vertical bridgman furnace at large Rayleigh number

In quasi-steady operation, convection currents in a Bridgmandevice, used for producing a semi-conductor crystal, createinhomogeneities that may make the crystal unusable. It has oftenbeen suggested that additional forces due to rotation or magnetismmight be efficacious in reducing the segregation of the elementsof the alloy. It has been found that, over a wide range of rotationrates, there is no improvement in performance due to rotationabout the vertical axis. However, numerical results that havebeen obtained previously (Lee & Pearlstein, J. Crys. Growth240, 2002) indicate that, when effects of centrifugal buoyancyare introduced, a substantial reduction in segregation is achieved.In the work reported here, by contrast, in which we extend previouslarge-Rayleigh-number asymptotic analysis to include centrifugalbuoyancy, we find no improvement in radial segregation, butrather increasing segregation with increasing rotation rate.     

Sulfonylcarbamimidic azides from sulfonyl chlorides and 5-aminotetrazole

Treatment of o-nitrobenzenesulfonyl chloride ( 3 ) with 5-aminotetrazole (5-AT) gave [(2-nitrophenyl)-sulfonyl]carbamimidic azide ( 6 ), a ring-opened isomer of the expected N-(1H-tetrazol-5-yl)-2-nitrobenzenesulfonamide ( 4 ). Sulfonylcarbamimidic azide 6 was converted to 2-amino-N-(aminoiminomethyl)benzene-sulfonamide ( 7 ) with ethanolic stannous chloride, and to 3-amino-1,2,4-thiadiazine 1,1-dioxide ( 8 ) with sodium dithionite. Methanesulfonyl chloride ( 9 ) and 5-AT gave 2-(methylsulfonyl)carbamimidic azide ( 10 ), which isomerized to 5-[(methylsulfonyl)amino]-1H-tetrazole ( 11 ) in warm ethanol. Attempted cycloaddition of 2-(phenylsulfonyl)carbamimidic azide ( 13 ) and ethyl vinyl ether led only to alkylated tetrazole products. In addition, other tetrazole-alkylating reactions are described. Isomers produced from these alkylations were differentiated with ¹³C nmr spectroscopy.     

Solution properties of amitriptyline and its partitioning into lipid bilayers

Solution properties of a drug and its partitioning into lipid bilayers were studied for drug extraction using several different techniques, such as surface tension, zeta potential, ultra filtration and UV-Vis spectroscopy. From the surface tension study it was found that the presence of salt makes the drug molecules more surface-active. Zeta potential revealed the adsorption of the drug into the liposome bilayers to be governed mostly by electrostatic forces. The drug retention volume was expressed as a capacity factor, K, and that was normalized with respect to the amount of the immobilized phospholipids. The K-values for the positively charged drug on the liposomes decreased in the presence of phosphate buffer due to the presence of the oppositely charged ions. The above methods can thus be used to understand the mechanism of drug-membrane interaction and quantification of drug absorption into liposomes.     

BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules

A broad collection of technologies, including e.g. drug metabolism, biofuel combustion, photochemical decontamination of water, and interfacial passivation in energy production/storage systems rely on chemical processes that involve bond-breaking molecular reactions. In this context, a fundamental thermodynamic property of interest is the bond dissociation energy (BDE) which measures the strength of a chemical bond. Fast and accurate prediction of BDEs for arbitrary molecules would lay the groundwork for data-driven projections of complex reaction cascades and hence a deeper understanding of these critical chemical processes and, ultimately, how to reverse design them. In this paper, we propose a chemically inspired graph neural network machine learning model, BonDNet, for the rapid and accurate prediction of BDEs. BonDNet maps the difference between the molecular representations of the reactants and products to the reaction BDE. Because of the use of this difference representation and the introduction of global features, including molecular charge, it is the first machine learning model capable of predicting both homolytic and heterolytic BDEs for molecules of any charge. To test the model, we have constructed a dataset of both homolytic and heterolytic BDEs for neutral and charged (−1 and +1) molecules. BonDNet achieves a mean absolute error (MAE) of 0.022 eV for unseen test data, significantly below chemical accuracy (0.043 eV). Besides the ability to handle complex bond dissociation reactions that no previous model could consider, BonDNet distinguishes itself even in only predicting homolytic BDEs for neutral molecules; it achieves an MAE of 0.020 eV on the PubChem BDE dataset, a 20% improvement over the previous best performing model. We gain additional insight into the model''s predictions by analyzing the patterns in the features representing the molecules and the bond dissociation reactions, which are qualitatively consistent with chemical rules and intuition. BonDNet is just one application of our general approach to representing and learning chemical reactivity, and it could be easily extended to the prediction of other reaction properties in the future.

Prediction of bond dissociation energies for charged molecules with a graph neural network enabled by global molecular features and reaction difference features between products and reactants.     

Negative adsorption due to electrostatic exclusion of micelles

Interactions of surfactants with solid substrates are important in the controlling of processes such as flotation, coating, flocculation and sedimentation. These interactions usually lead to adsorption on solids, but can also result in an exclusion of the reagents with dire consequences. In this work electrostatic exclusion of negatively charged dodecylbenzene sulfonate micelles from quartz/water, Bio-Sil/water and alumina/water interfaces has been investigated as a function of pH and ionic strength. Measurable negative adsorption of these surfactants from similarly charged solid/liquid interface was observed in the micellar region. In the case of porous samples with large surface area, comparison of pore size with the micelle size is necessary to avoid any erroneous conclusions regarding the role of electrostatic exclusion in a given system. A theoretical model for the electrostatic exclusion of micelles is developed and used to calculate the adsorption of negatively charged dodecylbenzene sulfonate on negatively charged quartz (pH 7), silica (Bio-Sil A, pH 3) and alumina (pH 11) in the micellar concentration region. The micellar exclusion values calculated using the model are in excellent agreement with the experimental results.     

Conformational changes of pyrene-labeled polyelectrolytes with pH: effect of hydrophobic modifications

Structural changes of pyrene-labeled and unlabeled poly(maleic acid/octyl vinyl ether) (PMAOVE) and poly(maleic acid/methyl vinyl ether) (PMAMVE) with changes in pH have been investigated in this study. The changes in the photophysical properties of pyrene are interpreted to investigate uncoiling or swelling of the polymeric chains with pH. The vibrational fine structure of the pyrene fluorescence (I(3)/I(1)) and the ratio between excimer and monomer fluorescence (I(e)/I(m)) of both pyrene-labeled and unlabeled PMAMVE and PMAOVE suggest that, at pH 4, the polymers are in the coiled form and PMAOVE forms hydrophobic nanodomains. An increase in pH ionizes a number of COOH groups on both PMAMVE and PMAOVE, which leads to the stretching or swelling of the polymers.