​ Zoom link: https://kaust.zoom.us/j/97352129718

ABSTRACT: The demand for renewable energy resources has become increasingly urgent due to global warming and related environmental issues.  Renewable energy systems require an energy storage solution because they are intermittent in nature. Among various alternatives, rechargeable aqueous zinc ion batteries (RAZIBs) with merits of cost-effectiveness, high safety, and environment-friendliness attracted great promise for grid-scale energy storage. Inspired by these merits, great efforts have been devoted to designing and fabricating Zn-based energy storage devices. However, the suitable cathode materials for RAZIBs and the details of the Zn2+ storage mechanism and have not been fully understood. Several methods have been proposed to tackle the issues for both at the cathode and anode side of the ZIB in this dissertation, including cathode structure engineering, interlayer strategy, and zinc anode protection.

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• CONTACTJing Guo
• EMAILjing.guo.1@kaust.edu.sa

​In the early 21^st century, oil and gas production in the U.S. was conjectured to be in terminal-irreversible decline. But, thanks to the advancement of hydraulic fracturing technologies over the last decade, operators are now able to produce two-thirds of U.S. oil and gas output from almost impermeable shale formations. Despite the enormous success of the 'shale revolution', there are still debates about how long shale production will last and if there will be enough to subsidize a meaningful transition to 'greener' power sources. Most official pronouncements of shale oil and gas reserves are based on purely empirical curve-fitting approaches or geological volumetric calculations that tend to largely overestimate the actual reserves. As an alternative to these industry-standard forecasting methods, we propose a more reliable, 'transparent', physics-guided and data-driven approach to estimating future production rates of oil and gas in shales. Our physics-based scaling method captures all essential physics of hydrocarbon production and hydrofracture geometry, yet it is as simple as the industry-favored Decline Curve Analysis (DCA), so that most engineers can adopt it. We also demonstrate that our method is as accurate as other analytical methods and has the same predictive power as commercial reservoir simulators but with less data required and significantly faster computational time. To capture the uncertainties of play-wide production, we combine physical scaling with the Generalized Extreme Value (GEV) statistics. So far, we have implemented this method to nearly half a million wells from all major U.S. shale plays. Since the results of our analyses are not subject to bias, policy-makers ought not to assume that the shale production boom will last for centuries.

Zoom Link:

:https://kaust.zoom.us/j/91729166919

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• CONTACTWardana Saputra
• EMAILWardana .saputra@kaust.edu.sa