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Patrick Avery

Publications and source records attributed to Patrick Avery.

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Real-time 3D analysis during electron tomography using tomviz

The demand for high-throughput electron tomography is rapidly increasing in biological and material sciences. However, this 3D imaging technique is computationally bottlenecked by alignment and reconstruction which runs from hours to days. We demonstrate real-time tomography with dynamic 3D tomographic visualization to enable rapid interpretation of specimen structure immediately as data is collected on an electron microscope. Using geometrically complex chiral nanoparticles, we show volumetric interpretation can begin in less than 10 minutes and a high quality tomogram is available within 30 minutes. Real time tomography is integrated into tomviz, an open source and cross platform 3D analysis tool that contains intuitive graphical user interfaces (GUI) to enable any scientist to characterize biological and material structure in 3D.

cond-mat.mtrl-sci

Predicting Superhard Materials via a Machine Learning Informed Evolutionary Structure Search

Good agreement was found between experimental Vickers hardnesses, $H_\text{v}$, of a wide range of materials and those calculated by three macroscopic hardness models that employ the shear and/or bulk moduli obtained from: (i) first principles via AFLOW-AEL (AFLOW Automatic Elastic Library), and (ii) a machine learning (ML) model trained on materials within the AFLOW repository. Because $H_\text{v}^\text{ML} $ values can be quickly estimated, they can be used in conjunction with an evolutionary search to predict stable, superhard materials. This methodology is implemented in the XtalOpt evolutionary algorithm. Each crystal is minimized to the nearest local minimum, and its Vickers hardness is computed via a linear relationship with the shear modulus discovered by Teter. Both the energy/enthalpy and $H_\text{v, Teter}^{\text{ML}}$ are employed to determine a structure's fitness. This implementation is applied towards the carbon system, and 43 new superhard phases are found. A topological analysis reveals that phases estimated to be slightly harder than diamond contain a substantial fraction of diamond and/or lonsdaleite.

cond-mat.mtrl-sci

Decomposition Products of Phosphine Under Pressure: PH2 Stable and Superconducting?

Evolutionary algorithms (EA) coupled with Density Functional Theory (DFT) calculations have been used to predict the most stable hydrides of phosphorous (PHn, n = 1-6) at 100, 150 and 200 GPa. At these pressures phosphine is unstable with respect to decomposition into the elemental phases, as well as PH2 and H2. Three metallic PH2 phases were found to be dynamically stable and superconducting between 100-200 GPa. One of these contains five formula units in the primitive cell and has C2/m symmetry (5FU-C2/m). It is comprised of 1D periodic PH3-PH-PH2-PH-PH3 oligomers. Two structurally related phases consisting of phosphorous atoms that are octahedrally coordinated by four phosphorous atoms in the equatorial positions and two hydrogen atoms in the axial positions (I4/mmm and 2FU-C2/m) were the most stable phases between ~160-200 GPa. Their superconducting critical temperatures (Tc) were computed as being 70 and 76 K, respectively, via the Allen-Dynes modified McMillan formula and using a value of 0.1 for the Coulomb pseudopotential, u*. Our results suggest that the superconductivity recently observed by Drozdov, Eremets and Troyan when phosphine was subject to pressures of 207 GPa in a diamond anvil cell may result from these, and other, decomposition products of phosphine.

cond-mat.supr-con