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.
In our study, we compare the three dimensional (3D) morphologic characteristics of Earth's first reef-building animals (archaeocyath sponges) with those of modern, photosynthetic corals. Within this repository are the 3D image data products for both groups of animals. The archaeocyath images were produced through serial grinding and imaging with the Grinding, Imaging, and Reconstruction Instrument at Princeton University. The images in this repository are the downsampled data products used in our study, and the full resolution (>2TB) image stacks are available upon request from the author. For the coral image data, the computed tomography (CT) images of all samples are included at full resolution. Also included in this repository are the manual and automated outline coordinates of the archaeocyath and coral branches, which can be directly used for morphological study.
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).
