Fractures in geological formations may enable migration of environmentally relevant fluids, as in leakage of CO2 through caprocks in geologic carbon sequestration. We investigated geochemically induced alterations of fracture geometry in Indiana Limestone specimens. Experiments were the first of their kind, with periodic high-resolution imaging using X-ray computed tomography (xCT) scanning while maintaining high pore pressure (100 bar). We studied two CO2-acidified brines having the same pH (3.3) and comparable thermodynamic
disequilibrium but different equilibrated pressures of CO2 (PCO2 values of 12 and 77 bar). High-PCO2 brine has a faster calcite dissolution kinetic rate because of the accelerating effect of carbonic acid. Contrary to expectations, dissolution extents were comparable in the two experiments. However, progressive xCT
images revealed extensive channelization for high PCO2, explained by strong positive feedback between ongoing flow and reaction. The pronounced channel increasingly directed flow to a small region of the fracture, which explains why the overall dissolution was lower than expected. Despite this, flow simulations revealed large increases in permeability in the high-PCO2 experiment. This study shows that the permeability evolution of dissolving fractures will be larger for faster-reacting fluids. The overall mechanism is not because more rock dissolves, as would be commonly assumed, but because of accelerated fracture channelization.
Petsev, Nikolai D.; Nikoubashman, Arash; Latinwo, Folarin
Abstract:
Source code for our genetic algorithm optimization investigation of conglomerate and racemic chiral crystals. In this work, we address challenges in determining the stable structures formed by chiral molecules by applying the framework of genetic algorithms to predict the ground state crystal lattices formed by a chiral tetramer model. Using this code, we explore the relative stability and structures of the model’s conglomerate and racemic crystals, and extract a structural phase diagram for the stable Bravais crystal types in the zero-temperature limit.
Sharma, A. Y.; Cole, M. D. J.; Görler, T.; Chen, Y.; Hatch, D. R.; Guttenfelder, W.; Hager, R.; Sturdevant, B. J.; Ku, S.; Mishchenko, A.; Chang, C. S.
The materials include codes and example input / output files for Monte Carlo simulations of lattice chains in the grand canonical ensemble, for determining phase behavior, critical points, and formation of aggregates.
Dielectric tensor for crystalline graphite from X-ray to microwave frequencies, as discussed in the paper "Graphite Revisited" (Draine 2016, Astrophysical Journal, in press). Cross sections for absorption and scattering by graphite spheres and spheroids are also tabulated, as well as Planck-averaged cross sections for absorption and scattering of radiation with a Planck spectrum.
This dataset is affiliated with the publication https://doi.org/10.1007/s00348-022-03455-0. All of the data provided is necessary to reproduce the results with the aforementioned publication. The data in this repository is for the wake of a wind turbine at high Reynolds numbers. The data is mainly used for reproducing the statistics (deficit and variance profiles) and the phase averaged results.
Force-driven parallel shear flow in a spatially periodic domain is shown to be linearly unstable
with respect to both the Reynolds number and the domain aspect ratio. This finding is confirmed
by computer simulations, and a simple expression is derived to determine stable flow conditions.
Periodic extensions of Couette and Poiseuille flows are unstable at Reynolds numbers two orders
of magnitude smaller than their aperiodic equivalents because the periodic boundaries impose
fundamentally different constraints. This instability has important implications for designing computational models of nonlinear dynamic processes with periodicity.
Monitoring the attention of others is fundamental to social cognition. Most of the literature on the topic assumes that our social cognitive machinery is tuned specifically to the gaze direction of others as a proxy for attention. This standard assumption reduces attention to an externally visible parameter. Here we show that this assumption is wrong and a deeper, more meaningful representation is involved. We presented subjects with two cues about the attentional state of a face: direction of gaze and emotional expression. We tested whether people relied predominantly on one cue, the other, or both. If the traditional view is correct, then the gaze cue should dominate. Instead, people employed a variety of strategies, some relying on gaze, some on expression, and some on an integration of cues. We also assessed people’s social cognitive ability using two, independent, standard tests. If the traditional view is correct, then social cognitive ability, as assessed by the independent tests, should correlate with the degree to which people successfully use the gaze cue to judge the attention state of the face. Instead, social cognitive ability correlated best with the degree to which people successfully integrated the cues together, instead of with the use of any one specific cue. The results suggest a rethink of a fundamental component of social cognition: monitoring the attention of others involves constructing a deep model that is informed by a combination of cues. Attention is a rich process and monitoring the attention of others involves a similarly rich representation.
Large-eddy simulations were employed over half-ice and half-water surfaces, with varying surface temperatures, wind speeds, directions, as to test if the atmospheric interaction with the heterogeneous surface can be predicted via a heterogeneity Richardson number. This dataset was used to determine that surface heat fluxes over ice, water, and the aggregate surface seem to be captured reasonably well by the wind direction and the heterogeneity Richardson number, but the mean wind and turbulent kinetic energy (TKE) profiles were not, suggesting that not only the difference in stability between the two surface, but also the individual stabilities over each surface influence the dynamics.
Large-eddy simulations were employed over five different sea ice patterns, with a constant ice fraction, to test if the overlying atmospheric boundary layer (ABL) dynamics and thermodynamics differs. The results of these simulations were used to determine that there were differences in vertical heat flux, momentum flux, and horizontal wind speed, and that more surface information is needed to predict the ABL over the sea ice surface. To see what other surface information is needed, twenty-two landscape metrics were calculated over forty-four different maps at differing resolutions, using the FRAGSTATs program. The results of that analysis are available in a .csv file in this dataset.
The data are 4554 light curves derived from images taken of the globular cluster M4 by the Kepler space telescope during the K2 portion of its mission, specifically during Campaign 2 of that mission, which occurred in 2014. A total of 3856 images were taken over approximately three months at a cadence of approximately half an hour. The purpose of these observations was to find stars and other objects that vary in brightness over time --- variable stars. Also included is a table with associated information for each of the 4554 objects and their light curves.
Canal, G. P.; Ferraro, N. M.; Evans, T. E.; Osborne, T. H.; Menard, J. E.; Ahn, J. -W.; Maingi, R.; Wingen, A.; Ciro, D.; Frerichs, H.; Schmitz, O.; Soukhanovskii, V.; Waters, I.; Sabbagh, S. A.
This item contains two files. A multi-layer perceptron (MLP) neural network is built using the MATLAB Deep Network Designer (.m file). It imports a quantum cascade laser (QCL) dataset and splits it into 70% training, 15% validation, and 15% testing subsets. The network consists of an input layer, three hidden layers (each having a normalization and activation layer), and a regression output layer. All of the layers are fully connected, and the root-mean-square error (RMSE) is used to evaluate the accuracy of the network. An algorithm is trained on the [-2, +3] QCL dataset using 50 neurons, ReLU activation function, solver Adam, 0.001 learning rate, over 150 epochs, and is saved to be used in the prediction of figure of merit values for QCL designs (.mat file).
This item contains two files. A multi-layer perceptron (MLP) neural network is built using the MATLAB Deep Network Designer (.m file). It imports a quantum cascade laser (QCL) dataset and splits it into 70% training, 15% validation, and 15% testing subsets. The network consists of an input layer, three hidden layers (each having a normalization and activation layer), and a regression output layer. All of the layers are fully connected, and the root-mean-square error (RMSE) is used to evaluate the accuracy of the network. An algorithm is trained on the [-5, +20] QCL dataset using 50 neurons, ReLU activation function, solver Adam, 0.001 learning rate, over 50 epochs, and is saved to be used in the prediction of figure of merit values for QCL designs (.mat file).
This is the dataset for the plots presented in the article "CO2-leakage-driven diffusiophoresis causes spontaneous accumulation of charged materials in channel flow."
Natural gas vehicles (NGVs) have been promoted in China to mitigate air pollution, yet our measurements and analyses show that NGV growth in China may have significant negative impacts on climate change. We conducted real-world vehicle emission measurements in China and found high methane emissions from heavy-duty NGVs (90% higher than current emission limits). These emissions have been ignored in previous emission estimates, leading to biased results. Applying our observations to life-cycle analyses, we found that switching to NGVs from conventional vehicles in China has led to a net increase in greenhouse gas (GHG) emissions since 2000. With scenario analyses, we also show that the next decade will be critical for China to reverse the trend with the upcoming China VI standard for heavy-duty vehicles. Implementing and enforcing the China VI standard is challenging, and the method demonstrated here can provide critical information regarding the fleet-level CH4 emissions from NGVs.
Since 1850 the concentration of atmospheric methane (CH4), a potent greenhouse gas, has more than doubled. Recent studies suggest that emission inventories may be missing sources and underestimating emissions. To investigate whether offshore oil and gas platforms leak CH4 during normal operation, we measured CH4 mole fractions around eight oil and gas production platforms in the North Sea which were neither flaring gas nor off-loading oil. We use the measurements from summer 2017, along with meteorological data, in a Gaussian plume model to estimate CH4 emissions from each platform. We find CH4 mole fractions of between 11 and 370 ppb above background concentrations downwind of the platforms measured, corresponding to a median CH4 emission of 6.8 g CH4 s-1 for each platform, with a range of 2.9 to 22.3 g CH4 s-1. When matched to production records, during our measurements individual platforms lost between 0.04% and 1.4% of gas produced with a median loss of 0.23%. When the measured platforms are considered collectively, (i.e. the sum of platforms’ emission fluxes weighted by the sum of the platforms’ production), we estimate the CH4 loss to be 0.19% of gas production. These estimates are substantially higher than the emissions most recently reported to the National Atmospheric Emission Inventory (NAEI) for total CH4 loss from United Kingdom platforms in the North Sea. The NAEI reports CH4 losses from the offshore oil and gas platforms we measured to be 0.13% of gas production, with most of their emissions coming from gas flaring and offshore oil loading, neither of which were taking place at the time of our measurements. All oil and gas platforms we observed were found to leak CH4 during normal operation and much of this leakage has not been included in UK emission inventories. Further research is required to accurately determine total CH4 leakage from all offshore oil and gas operations and to properly include the leakage in national and international emission inventories.
Kramer, G. J.; Bortolon, A.; Ferraro, N. M.; Spong, D. A.; Crocker, N. A.; Darrow, D. S.; Fredrickson, E. D.; Kubota, S.; Park, J.-K.; Podesta, M.; Heidbrink, W. W.
These GROMACS trajectories show the existence of a critical point in deeply supercooled WAIL water. Also included is the code necessary to reproduce the figures in the corresponding paper from these trajectories. From this data the critical temperature, pressure, and density of the model can be found, and critical fluctuations in the deeply supercooled liquid can be directly observed (in a computer-simulation sense).
Movies of relativistic reconnection and particle acceleration in relativistic reconnection accompanying the article "Relativistic Reconnection: an Efficient Source of Nonthermal Particles" by Lorenzo Sironi and Anatoly Spitkovsky.
What mechanisms support our ability to estimate durations on the order of minutes? Behavioral studies in humans have shown that changes in contextual features lead to overestimation of past durations. Based on evidence that the medial temporal lobes and prefrontal cortex represent contextual features, we related the degree of fMRI pattern change in these regions with people's subsequent duration estimates. After listening to a radio story in the scanner, participants were asked how much time had elapsed between pairs of clips from the story. Our ROI analysis found that the neural pattern distance between two clips at encoding was correlated with duration estimates in the right entorhinal cortex and right pars orbitalis. Moreover, a whole-brain searchlight analysis revealed a cluster spanning the right anterior temporal lobe. Our findings provide convergent support for the hypothesis that retrospective time judgments are driven by 'drift' in contextual representations supported by these regions.
Vecchi, Gabriel A.; Landsea, Christopher; Zhang, Wei; Villarini, Gabriele; Knutson, Thomas
Abstract:
These are the data and scripts supporting the manuscript: Vecchi, Landsea, Zhang, Villarini and Knutson (2021): Changes in Atlantic Major Hurricane Frequency Since the Late-19th Century. Nature Communications.
Choi, W.; Poli, F. M.; Li, M. H.; Baek, S. G.; Gorelenkova, M.; Ding, B. J.; Gong, X. Z.; Chan, A.; Duan, Y. M.; Hu, J. H.; Lian, H.; Lin, S. Y.; Liu, H. Q.; Qian, J. P.; Wallace, G.; Wang, Y. M.; Zang, Q.; Zhao, H. L.
