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Machine learning PODA model projects the impact of COVID-19 on US motor gasoline demand

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The PODA model is a machine-learning-based model to project the US gasoline demand using COVID-19 pandemic data, government policies and demographic information. The Motor Gasoline Demand Estimation Module quantifies motor gasoline demands due to the changes in travel mobility. —Ou et al.

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UW Madison team finds methylbutenol a potentially promising biofuel for blending with gasoline

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A team at the University of Madison-Wisconsin studied critical sooting equivalence ratios and subsequent particulate formation during spark-ignition combustion for blends of ethanol, isobutanol (2-methyl-1-propanol), and methylbutenol (2-methyl-3-buten-2-ol) with gasoline using premixed prevaporized (PMPV) fueling.

Gasoline 333
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Sugar-derived levulinic esters and cyclic ether show superior anti-knock quality to Euro95 reference gasoline

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A team from The Netherlands and the US reports that the sugar-derived levulinic esters methyl levulinate (ML) and ethyl levulinate (EL) and the sugar-derived cyclic ether (furfuryl ethyl ether (FEE) demonstrate superior anti-knock quality (in 10% blends) to a reference Euro95 gasoline. —Tian et al.

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EIA: fuel economy standards drive down projected gasoline use; diesel use, product exports rise

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In the US Energy Information Administration’s Annual Energy Outlook 2014 (AEO2014) Reference case, more-stringent vehicle fuel economy standards contribute to a decline in motor gasoline consumption through 2040. The Reference case projects an increase in VMT that, all else equal, would increase motor gasoline fuel consumption.

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€7M German project to develop processes and demand scenarios for the mass production of synthetic fuels; “Refineries for Future”

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When talking about phasing out of combustion engines, it is referred to car engines only. According to these scenarios, gasoline will disappear from the market first, Dahmen points out. According to these scenarios, gasoline will disappear from the market first, Dahmen points out. This will affect future production capacities.

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Fraunhofer team developing continuous rapid production line for fuel cell components

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A team from Fraunhofer IPT is developing a continuous production line that will be able to process fuel cell components in cycles lasting just seconds. Moreover, they plan to transfer the action plan and the individual technologies for the production of fuel cells from research to industrial application. © Fraunhofer IPT.

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KAUST team develops computational model for simulating soot production in gasoline direct injection engines

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Researchers at KAUST have developed a computational model capable of simulating soot production inside gasoline direct injection (GDI) engines. Particulate matter emissions are presently a concern in gasoline fueled direct-injection spark-ignition (DISI) engines. —Park et al.

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