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Abstract The fate and aggregation of nanoparticles (NPs) in the subsurface are important due to potentially harmful impacts on the environment and human health. This study aims to investigate the effects of flow velocity, particle size, and particle concentration on the aggregation rate of NPs in a diffusion-limited regime and build an equation to predict the aggregation rate when NPs move in the pore space between randomly packed spheres (including mono-disperse, bi-disperse, and tri-disperse spheres). The flow of 0.2 M potassium chloride (KCl) through the random sphere packings was simulated by the lattice Boltzmann method (LBM). The movement and aggregation of cerium oxide (CeO₂) particles were then examined by using a Lagrangian particle tracking method based on a force balance approach. This method relied on Newton's second law of motion and took the interaction forces among particles into account. The aggregation rate of NPs was found to depend linearly on time, and the slope of the line was a power function of the particle concentration, the Reynolds (Re) and Schmidt (Sc) numbers. The exponent for theScnumber was triple that of theRenumber, which was evidence that the random movement of NPs has a much stronger effect on the rate of diffusion-controlled aggregation than the convection. 

Understanding the dynamics of a methane bubble in a liquid metal bubble column reactor is important for optimizing the reactor design and improving efficiency. To better understand methane bubble dynamics and the reaction to produce hydrogen, we employ ANSYS Fluent to investigate the gas-liquid interface, to relate the surface area where reaction occurs to bubble size, and to determine coalescing behavior as a function of dimensionless numbers. Once the simulation is verified by comparing bubble velocity [1], shape [2], and coalescing distance [3] for a water-air system, a methane bubble in liquid bismuth at 1000 k is examined [4] [5]. Experimentally obtained kinetic parameters for the reaction are used in the computations. The bubble interfacial area to volume ratio is maximized at a diameter of 4mm and does not induce breakage of the bubble. The coalescing distance for two bubbles of methane in bismuth is a third of the distance for air in water bubbles. REFERENCES 1. S. Baz-Rodríguez, A. Aguilar-Corona, and A. Soria, Rev. Mex. Ing. Quím. 8, 213 (2009). 2. R. Clift, J. R. Grace, and M. E. Weber, Bubbles, Drops, and Particles (Academic Press, New York, 1978). 3. T. Otake, S. Tone, K. Nakao, and Y. Mitsuhashi, Chem. Eng. Sci. 32, 377 (1977). 4. M. J. Assael, K. Gialou, K. Kakosimos, and I. Metaxa, High Temp. High Press. 41, 101 (2012). 5. Engineering ToolBox (2004), https://www.engineeringtoolbox.com/methane-d_1420.html. Funding acknowledgement The support of the US National Science Foundation under grant number 2317726 is gratefully acknowledged. 

Disposal of industrial wastewater and activities such as CO2 depend on pressure conditions within deep geologic reservoirs. Injection and storage are also associated with induced seismicity, suggested to result from reservoir compartmentalization and leakage into faults. To understand subsurface pressure conditions within a major regional disposal reservoir, the carbonate Arbuckle Group of Oklahoma, we monitored the water levels in 15 inactive injection wells. The wells were monitored at 30-second intervals, with eight wells monitored since September 2016, and an additional seven from July 2017. All of the wells were monitored until early March 2020. Since 2016, well levels decreased in 3 of the 15 wells (a.k.a. hydraulic head), proportional to near-borehole fluid pressure even considering decreasing regional injection volumes during this period. The well pressures respond to three types of perturbations: (i) gravitational fkuctuations (a.k.a. solid-earth tides) (ii) distal and proximal earthquakes, and (iii) injections into nearby wells. Parameterization of tidal responses illustrates that the near wellbore environments have negative fluid flux (i.e. are leaking). Earthquakes cause differing pressure responses from well to well, with some highly sensitive to proximal events, some to distal events, and some apparently insensitive. Injections have variable impacts in some cases masking tidal and earthquake pressure signals. Collectively, there appears to be a threshold injection rate above which well pressure becomes less sensitive to the volume of injections within 15 km. Multi-scale geological structure and temporal permeability changes are likely controlling the pressure field, indicating leakage of fluids across the system.