5632 research outputs found
Sort by
Ab initio study of the structure and relative stability of MgSiO₄H₂ polymorphs at high pressures and temperatures
No full textUsing particle swarm optimization with density functional theory, we identify the positions of hydrogen in a hypothetical Mg-end-member of phase egg (MgSiO₄H₂) and predict the most stable crystal structures with MgSiO₄H₂ stoichiometry at pressures between 0 and 300 GPa. The particle swarm optimization method consistently and systematically identifies phase H as the energetically most stable structure in the pressure range 10–300 GPa at 0 K. Phase Mg-egg has a slightly higher energy compared to phase H at all relevant pressures, such that the energy difference nearly plateaus at high pressures; however, the combined effects of temperature and chemical substitutions may decrease or even reverse the energy difference between the two structures. We find a new MgSiO₄H₂ phase with the P4₃2₁2 space group that has topological similarities to phase Mg-egg and is energetically preferred to phase H at 0–10 GPa and 0 K. We compute the free energies for phase Mg-egg, phase P4₃2₁2, and phase H at 0–30 GPa within the quasi-harmonic approximation and find that the effect of temperature is relatively small. At 1800 K, the stability field of phase P4₃2₁2 relative to the other polymorphs increases to 0–14 GPa, while pure phase Mg-egg remains energetically unfavorable at all pressures. Simulated X-ray diffraction patterns and Raman spectra are provided for the three phases. Additionally, the crystallographic information for two metastable polymorphs with the P1 space group is provided. Our results have implications for the deep hydrogen cycle in that we identify two novel potential carrier phases for hydrogen in the mantles of terrestrial planets and assess their stability relative to phase H. We determine that further experimental and computational investigation of an extended compositional space remains necessary to establish the most stable dense hydrated silicate phases
The Low-redshift Lyman Continuum Survey. I. New, Diverse Local Lyman Continuum Emitters
No full textThe origins of Lyman continuum (LyC) photons responsible for the reionization of the universe are as of yet unknown and highly contested. Detecting LyC photons from the Epoch of Reionization is not possible due to absorption by the intergalactic medium, which has prompted the development of several indirect diagnostics to infer the rate at which galaxies contribute LyC photons to reionize the universe by studying lower-redshift analogs. We present the Low-redshift Lyman Continuum Survey (LzLCS) comprising measurements made with the Hubble Space Telescope Cosmic Origins Spectrograph for a z = 0.2–0.4 sample of 66 galaxies. After careful processing of the far-UV spectra, we obtain a total of 35 Lyman continuum emitters (LCEs) detected with 97.725% confidence, nearly tripling the number of known local LCEs. We estimate escape fractions from the detected LyC flux and upper limits on the undetected LyC flux, finding a range of LyC escape fractions up to 50%. Of the 35 LzLCS LCEs, 12 have LyC escape fractions greater than 5%, more than doubling the number of known local LCEs with cosmologically relevant LyC escape
FC-based shock-dynamics solver with neural-network localized artificial-viscosity assignment
No full textThis paper presents a spectral scheme for the numerical solution of nonlinear conservation laws in non-periodic domains under arbitrary boundary conditions. The approach relies on the use of the Fourier Continuation (FC) method for spectral representation of non-periodic functions in conjunction with smooth localized artificial viscosity assignments produced by means of a Shock-Detecting Neural Network (SDNN). Like previous shock capturing schemes and artificial viscosity techniques, the combined FC-SDNN strategy effectively controls spurious oscillations in the proximity of discontinuities. Thanks to its use of a localized but smooth artificial viscosity term, whose support is restricted to a vicinity of flow-discontinuity points, the algorithm enjoys spectral accuracy and low dissipation away from flow discontinuities, and, in such regions, it produces smooth numerical solutions—as evidenced by an essential absence of spurious oscillations in level set lines. The FC-SDNN viscosity assignment, which does not require use of problem-dependent algorithmic parameters, induces a significantly lower overall dissipation than other methods, including the Fourier-spectral versions of the previous entropy viscosity method. The character of the proposed algorithm is illustrated with a variety of numerical results for the linear advection, Burgers and Euler equations in one and two-dimensional non-periodic spatial domains
Addressing solar photochemistry durability with an amorphous nickel antimonate photoanode
No full textRenewable generation of fuels using solar energy is a promising technology whose deployment hinges on the discovery of materials with a combination of durability and solar-to-chemical conversion efficiency that has yet to be demonstrated. Stable operation of photoanodes has been demonstrated with wide-gap semiconductors, as well as protected visible gap semiconductors. Visible photoresponse from electrochemically stable materials is quite rare. In this paper, we report the high-throughput discovery of an amorphous Ni-Sb (1:1) oxide photoanode that meets the requirements of operational stability, visible photoresponse, and appreciable photovoltage. X-ray absorption characterization of Ni and Sb establishes a structural connection to rutile NiSb₂O₆, guiding electronic structure characterization via X-ray photoelectron experiments and density functional theory. This amorphous photoanode opens avenues for photoelectrode development due to the lack of crystal anisotropy combined with its operational stability, which mitigates the formation of an interphase that disrupts the semiconductor-electrolyte junction
Supersonic Freestream Density Fluctuations from Focused Laser Differential Interferometry and Pitot-Probe Measurements
No full textFocused laser differential interferometry (FLDI) is used to make freestream density fluctuation measurements in the von Kármán Gas Dynamics Facility (VKF) Wind Tunnel D at Arnold Engineering Development Complex. A comparison is made between pitot-probe and FLDI measurements after converting both to freestream pressure fluctuation spectra. A modification of Stainback and Wagner’s theory, incorporating recent numerical results from Chaudhry et al., is used to interpret the pitot data, while a new inversion algorithm is applied to the FLDI data. These methods of interpretation make the assumption that the tunnel freestream disturbance environment is dominated by the acoustic Kovásznay mode, in line with the theoretical and experimental evidence. Close agreement is found between the two sets of spectra, showing that accurate quantitative data can be obtained with FLDI, and the instrument can be used to extend spectra beyond the pitot bandwidth
Structure of Anabaena flos-aquae gas vesicles revealed by cryo-ET
No full textGas vesicles (GVs) are gas-filled protein nanostructures employed by several species of bacteria and archaea as flotation devices to enable access to optimal light and nutrients. The unique physical properties of GVs have led to their use as genetically-encodable contrast agents for ultrasound and MRI. Currently, however, the structure and assembly mechanism of GVs remain unknown. Here we employ cryo-electron tomography to reveal how the GV shell is formed by a helical filament of highly conserved GvpA subunits. This filament changes polarity at the center of the GV cylinder—a site that may act as an elongation center. High-resolution subtomogram averaging reveals a corrugated pattern of the shell arising from polymerization of GvpA into a β-sheet. The accessory protein GvpC forms a helical cage around the GvpA shell, providing structural reinforcement. Together, our results help explain the remarkable mechanical properties of GVs and their ability to adopt different diameters and shapes
Design of a mobile RFI monitoring station for DSA-2000 candidate sites surveys
No full textThe DSA-2000 radio telescope is currently being designed to become the fastest and most sensitive astronomical survey instrument. An important factor in this design is the future Radio Frequency Interference (RFI) environment of the telescope. A careful site selection and RFI risks assessment are important to ensure that the specifications of the telescope are met. To this end, a mobile RFI survey station has been developed to provide an accurate picture of the RFI environment of a candidate telescope site. This paper presents this monitoring station and preliminary results captured at the Owens Valley Radio Observatory
Screening p-Hackers: Dissemination Noise as Bait
No full textWe show that adding noise to data before making data public is effective at screening p-hacked findings: spurious explanations of the outcome variable produced by attempting multiple econometric specifications. Noise creates "baits'' that affect two types of researchers differently. Uninformed p-hackers who engage in data mining with no prior information about the true causal mechanism often fall for baits and report verifiably wrong results when evaluated with the original data. But informed researchers who start with an ex-ante hypothesis about the causal mechanism before seeing any data are minimally affected by noise. We characterize the optimal level of dissemination noise and highlight the relevant trade-offs in a simple theoretical model. Dissemination noise is a tool that statistical agencies (e.g., the US Census Bureau) currently use to protect privacy, and we show this existing practice can be repurposed to improve research credibility
Private Private Information
No full textIn a private private information structure, agents' signals contain no information about the signals of their peers. We study how informative such structures can be, and characterize those that are on the Pareto frontier, in the sense that it is impossible to give more information to any agent without violating privacy. In our main application, we show how to optimally disclose information about an unknown state under the constraint of not revealing anything about a correlated variable that contains sensitive information
Closure Operators: Complexity and Applications to Classification and Decision-making
No full textWe study the complexity of closure operators, with applications to machine learning and decision theory. In machine learning, closure operators emerge naturally in data classification and clustering. In decision theory, they can model equivalence of choice menus, and therefore situations with a preference for flexibility. Our contribution is to formulate a notion of complexity of closure operators, which translate into the complexity of a classifier in ML, or of a utility function in decision theory