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Savitzky, Benjamin H.

Publications and source records attributed to Savitzky, Benjamin H..

The hierarchical structure of organic mixed ionic–electronic conductors and its evolution in water

Polymeric organic mixed ionic–electronic conductors underpin several technologies in which their electrochemical properties are desirable. These properties, however, depend on the microstructure that develops in their aqueous operational environment. We investigated the structure of a model organic mixed ionic–electronic conductor across multiple length scales using cryogenic four-dimensional scanning transmission electron microscopy in both its dry and hydrated states. Four-dimensional scanning transmission electron microscopy allows us to identify the prevalent defects in the polymer crystalline regions and to analyse the liquid crystalline nature of the polymer. The orientation maps of the dry and hydrated polymers show that swelling-induced disorder is mostly localized in discrete regions, thereby largely preserving the liquid crystalline order. Therefore, the liquid crystalline mesostructure makes electronic transport robust to electrolyte ingress. Furthermore, this study demonstrates that cryogenic four-dimensional scanning transmission electron microscopy provides multiscale structural insights into complex, hierarchical structures such as polymeric organic mixed ionic–electronic conductors, even in their hydrated operating state.

36 MATERIALS SCIENCE↗

Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.

36 MATERIALS SCIENCE↗

The 4D Camera: An 87 kHz Direct Electron Detector for Scanning/Transmission Electron Microscopy

We describe the development, operation, and application of the 4D Camera—a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ~480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10–700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

47 OTHER INSTRUMENTATION↗