This dataset contains all data relevant to a forthcoming publication in which we used molecular simulation methods to study the phase behavior of supercooled water. The dataset contains simulation input and output files, processed data files, and image files used to create all plots in the manuscript. Python analysis scripts are also included, including instructions for how to re-generate all plots in the manuscript.
Kiefer, Janik; Brunner, Claudia E.; Hansen, Martin O. L.; Hultmark, Marcus
Abstract:
This data set contains data of a NACA 0021 airfoil as it undergoes upward ramp-type pitching motions at high Reynolds numbers and low Mach numbers. The parametric study covers a wide range of chord Reynolds numbers, reduced frequencies and pitching geometries characterized by varying mean angle and angle amplitude. The data were acquired in the High Reynolds number Test Facility at Princeton University, which is a closed-loop wind tunnel that can be pressurized up to 23 MPa and allowed for variation of the chord Reynolds number over a range of 5.0 × 10^5 ≤ Re_c ≤ 5.5 × 10^6. Data were acquired using 32 pressure taps along the surface of the airfoil. The data are the phase-averaged results of 150 individual half-cycles for any given test case.
Geyman, Emily C.; Wu, Ziman; Nadeau, Matthew D.; Edmonsond, Stacey; Turner, Andrew; Purkis, Sam J.; Howes, Bolton; Dyer, Blake; Ahm, Anne-Sofie C.; Yao, Nan; Deutsch, Curtis A.; Higgins, John A.; Stolper, Daniel A.; Maloof, Adam C.
Abstract:
Carbonate mud represents one of the most important geochemical archives for reconstructing ancient climatic, environmental, and evolutionary change from the rock record. Mud also represents a major sink in the global carbon cycle. Yet, there remains no consensus about how and where carbonate mud is formed. In this contribution, we present new geochemical data that bear on this problem, including stable isotope and minor and trace element data from carbonate sources in the modern Bahamas such as ooids, corals, foraminifera, and green algae.
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.
This dataset contains supplementary materials for Chapter 4 and Chapter 5 of Yiheng Tao's PhD dissertation (2022). The dissertation’s abstract is provided here:
Carbon capture, utilization, and storage (CCUS) mitigates climate change by capturing carbon dioxide (CO2) emissions from large point sources, or CO2 from the ambient air, and subsequently reusing the captured CO2 or injecting it into deep geological formations for long-term and secure storage. Almost all current decarbonization pathways include large-scale CCUS, on the order of a billion tonnes (Gt) of CO2 captured and stored each year globally starting in 2030, yet the actual deployment has lagged far behind (around 0.04 Gt CO2 was captured in 2021). In this dissertation, I contribute to several aspects of largescale deployment of CCUS by (1) developing and applying efficient numerical models to simulate geological CO2 storage and (2) identifying key policies to address the bottlenecks of overall CCUS deployment. This dissertation concerns the United States, China, and the Belt and Road Initiative (BRI) region through research projects that are consistent with each location’s current development stage of CCUS.
Chapters 2 and 3 contain computational modeling studies. In Chapter 2, I develop a new series of vertical-equilibrium (VE) models in the dual-continuum modeling framework to simulate CO2 injection and migration in fractured geological formations. Those models are shown to be effective and efficient when properties of the formation allow for the VE assumption. In Chapter 3, I apply a VE model to simulate basin-scale CO2 injection in the Junggar Basin of Northwestern China. The results show that current regional emissions of more than 100 million tonnes of CO2 per year can be stored effectively, thereby confirming the great potential of the Junggar Basin for early CCUS deployment.
Chapters 4 and 5 contain policy analyses. In Chapter 4, I propose a dynamic system consisting of new CO2 pipelines and novel Allam-cycle power plants in the Central United States, and examine how government policies, including an extended Section 45Q tax credit, may improve the economic feasibility of this system. Lastly, in Chapter 5, I investigate and quantify CO2 emissions implications of power plant projects associated with the BRI. I also propose a “greenness ratio” to measure the level of environmental sustainability of BRI in the power sector.
This distribution contains experimentally measured data for the extent of retained enzyme activity post thermal stressing for three distinct enzymes: glucose oxidase, lipase, and horseradish peroxidase. The data is used to form conclusions and develop machine learning models as reported in the publication "Machine Learning on a Robotic Platform for the Design of Polymer-Protein Hybrids" by Matthew Tamasi, Roshan Patel, Carlos Borca, Shashank Kosuri, Heloise Mugnier, Rahul Upadhya, N. Sanjeeva Murthy, Michael Webb*, and Adam Gormley. Details regarding the experimental protocols are reported in the aforementioned paper but are briefly discussed in the README.
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).
This distribution compiles numerous physical properties for 2,585 intrinsically disordered proteins (IDPs) obtained by coarse-grained molecular dynamics simulation. This combination comprises "Dataset A" as reported in "Featurization strategies for polymer sequence or composition design by machine learning" by Roshan A. Patel, Carlos H. Borca, and Michael A. Webb (DOI: 10.1039/D1ME00160D). The specific IDP sequences are sourced from version 9.0 of the DisProt database. The simulations were performed using the LAMMPS molecular dynamics engine. The interactions used for simulation are obtained from R. M. Regy , J. Thompson , Y. C. Kim and J. Mittal , Improved coarse-grained model for studying sequence dependent phase separation of disordered proteins, Protein Sci., 2021, 1371 —1379.
There has been considerable recent interest in the high-pressure behavior of silicon carbide, a potential major constituent of carbon-rich exoplanets. In this work, the atomic-level structure of SiC was determined through in situ X-ray diffraction under laser-driven ramp compression up to 1.5 TPa; stresses more than seven times greater than previous static and shock data. Here we show that the B1-type structure persists over this stress range and we have constrained its equation of state (EOS). Using this data we have determined the first experimentally based mass-radius curves for a hypothetical pure SiC planet. Interior structure models are constructed for planets consisting of a SiC-rich mantle and iron-rich core. Carbide planets are found to be ~10% less dense than corresponding terrestrial planets.
This dataset includes individual CIF files with the refined structure of fluorapatite under compression to 61 GPa. The structures have been discussed in detail in the accompanying manuscript "Single-crystal X-ray diffraction of fluorapatite to 61 GPa"
The dataset contains the model file for the Global Adjoint Tomography Model 25 (GLAD-M25). The model file contains parameters defined on the spectral-element mesh and is recommend to be used in SPECFEM3D GLOBE for seismic wave simulation at the global scale.
This dataset contains input and output files to reproduce the results of the manuscript "Homogeneous ice nucleation in an ab initio machine learning model" by Pablo M. Piaggi, Jack Weis, Athanassios Z. Panagiotopoulos, Pablo G. Debenedetti, and Roberto Car (arXiv preprint https://arxiv.org/abs/2203.01376). In this work, we studied the homogeneous nucleation of ice from supercooled liquid water using a machine learning model trained on ab initio energies and forces. Since nucleation takes place over times much longer than the simulation times that can be afforded using molecular dynamics simulations, we make use of the seeding technique that is based on simulating an ice cluster embedded in liquid water. The key quantity provided by the seeding technique is the size of the critical cluster (i.e., a size such that the cluster has equal probabilities of growing or shrinking at the given supersaturation). Using data from the seeding simulations and the equations of classical nucleation theory we compute nucleation rates that can be compared with experiments.
This dataset comprises of data associated with the publication "Transferability of data-driven, many-body models for CO2 simulations in the vapor and liquid phases", which can be found at https://doi.org/10.1063/5.0080061. The data includes calculations for a Many-Body decomposition, virial coefficient calculations, orientational molecular scan energies, potential energy fields, correlation plots of training and testing data, vapor-liquid equilibrium simulations, liquid density simulations, and solid cell simulations.
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples.
Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
