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Gartner III, Thomas E.; Torquato, Salvatore; Car, Roberto; Debenedetti, Pablo G.
Abstract:
This dataset contains all data related to the publication "Manifestations of metastable criticality in glassy water-like models detected by large-scale structural properties" by Gartner et al., in preparation 2020. In this work, we used molecular dynamics simulations to explore the relationship between water's polyamorphism (multiple amorphous solid states) and its hypothesized liquid-liquid transition. Using the TIP4P/2005 molecular model of water, we found a surprising signature of water's liquid-liquid critical point in the long-range structure of water's amorphous solid states formed by isobaric cooling at different pressures. This structural signature was absent in two other systems that lack a critical point. This dataset contains molecular dynamics simulation trajectories, as well as processed data, analysis codes, and image files used in the publication.
Kim, Donghoon; Tracy, Sally J.; Smith, Raymond F.; Gleason, Arianna E.; Bolme, Cindy A.; Prakapenka, Vitali B.; Appel, Karen; Speziable, Sergio; Wicks, June K.; Berryman, Eleanor J.; Han, Sirus K.; Schoelmerich, Markus O.; Lee, Hae Ja; Nagler, Bob; Cunningham, Eric F.; Akin, Minta C.; Asimow, Paul D.; Eggert, Jon H.; Duffy, Thomas S.
Abstract:
The behavior of forsterite, Mg2SiO4, under dynamic compression is of fundamental importance for understanding its phase transformations and high-pressure behavior. Here, we have carried out an in situ X-ray diffraction study of laser-shocked poly- and single-crystal forsterite (a-, b-, and c- orientations) from 19 to 122 GPa using the Matter in Extreme Conditions end-station of the Linac Coherent Light Source. Under laser-based shock loading, forsterite does not transform to the high-pressure equilibrium assemblage of MgSiO3 bridgmanite and MgO periclase, as was suggested previously. Instead, we observe forsterite and forsterite III, a metastable polymorph of Mg2SiO4, coexisting in a mixed-phase region from 33 to 75 GPa for both polycrystalline and single-crystal samples. Densities inferred from X-ray diffraction data are consistent with earlier gas-gun shock data. At higher stress, the behavior observed is sample-dependent. Polycrystalline samples undergo amorphization above 79 GPa. For [010]- and [001]-oriented crystals, a mixture of crystalline and amorphous material is observed to 108 GPa, whereas the [100]-oriented crystal adopts an unknown crystal structure at 122 GPa. The Q values of the first two sharp diffraction peaks of amorphous Mg2SiO4 show a similar trend with compression as those observed for MgSiO3 glass in both recent static and laser-compression experiments. Upon release to ambient pressure, all samples retain or revert to forsterite with evidence for amorphous material also present in some cases. This study demonstrates the utility of femtosecond free-electron laser X-ray sources for probing the time evolution of high-pressure silicates through the nanosecond-scale events of shock compression and release.
The Molino suite contains 75,000 galaxy mock catalogs designed to quantify the information content of any cosmological observable for a redshift-space galaxy sample. They are constructed from the Quijote N-body simulations (Villaescusa-Navarro et al. 2020) using the standard Zheng et al. (2007) Halo Occupation Distribution (HOD) model. The fiducial HOD parameters are based on the SDSS high luminosity samples. The suite contains 15,000 mocks at the fiducial cosmology and HOD parameters for covariance matrix estimation. It also includes (500 N-body realizations) x (5 HOD realizations)=2,500 mocks at 24 other parameter values to estimate the derivative of the observable with respect to six cosmological parameters (Omega_m, Omega_b, h, n_s, sigma_8, and M_nu) and five HOD parameters (logMmin, sigma_logM, log M_0, alpha, and log M_1). Using the covariance matrix and derivatives calculated from Molino, one can derive Fisher matrix forecasts on the cosmological parameters marginalized over HOD parameters.
Data set used to train a Deep Potential (DP) model for crystalline and disordered TiO2 phases. Training data contain atomic forces, potential energy, atomic coordinates and cell tensor. Energy and forces were evaluated with the density functional SCAN, as implemented in Quantum-ESPRESSO. Atomic configurations of crystalline systems were generated by random perturbation of atomic positions (0-0.3 A) and cell tensor (1-10%). Amorphous TiO2 was explored by DP molecular dynamics (DPMD) at temperatures in the range 300−2500 K and pressure in the range 0−81 GPa.
Pacheco, Diego A; Thiberge, Stephan; Pnevmatikakis, Eftychios; Murthy, Mala
Abstract:
Sensory pathways are typically studied starting at receptor neurons and following postsynaptic neurons into the brain. However, this leads to a bias in analysis of activity towards the earliest layers of processing. Here, we present new methods for volumetric neural imaging with precise across-brain registration, to characterize auditory activity throughout the entire central brain of Drosophila and make comparisons across trials, individuals, and sexes. We discover that auditory activity is present in most central brain regions and in neurons responsive to other modalities. Auditory responses are temporally diverse, but the majority of activity is tuned to courtship song features. Auditory responses are stereotyped across trials and animals in early mechanosensory regions, becoming more variable at higher layers of the putative pathway, and this variability is largely independent of spontaneous movements. This study highlights the power of using an unbiased, brain-wide approach for mapping the functional organization of sensory activity.
Data set used to train a Deep Potential (DP) model for
subcritical and supercritical water. Training data contain atomic forces,
potential energy, atomic coordinates and cell tensor. Energy and forces
were evaluated with the density functional SCAN. Atomic configurations
were extracted from DP molecular dynamics at P = 250 bar and
T = 553, 623, 663, 733 and 823 K. Input files used to train the DP model
are also provided.
Gartner, Thomas III; Zhang, Linfeng; Piaggi, Pablo; Car, Roberto; Panagiotopoulos, Athanassios; Debenedetti, Pablo
Abstract:
This dataset contains all data related to the publication "Signatures of a liquid-liquid transition in an ab initio deep neural network model for water", by Gartner et al., 2020. In this work, we used neural networks to generate a computational model for water using high-accuracy quantum chemistry calculations. Then, we used advanced molecular simulations to demonstrate evidence that suggests this model exhibits a liquid-liquid transition, a phenomenon that can explain many of water's anomalous properties. This dataset contains links to all software used, all data generated as part of this work, as well as scripts to generate and analyze all data and generate the plots reported in the publication.
This dataset includes information about approximately 6,000 books and other items with bibliographic data as well as summary information about when the item circulated in the Shakespeare and Company lending library and the number of times an item was borrowed or purchased.
The events dataset includes information about approximately 33,700 lending library events including membership activities such as subscriptions, renewals and reimbursements and book-related activities such as borrowing and purchasing. For events related to lending library cards that are available as digital surrogates, IIIF links are provided.
The Shakespeare and Company Project: Lending Library Members dataset includes information about approximately 5,700 members of Sylvia Beach's Shakespeare and Company lending library.
