Engineering topics
Stach, Eric A.
Publications and source records attributed to Stach, Eric A..
In Situ Investigation of Chemomechanical Effects in Thiophosphate Solid Electrolytes
Solid-state batteries can suffer from catastrophic failure at high current densities due to solid electrolyte fracture, interface decomposition, or lithium filament growth. Failure is linked to chemomechanical material transformations that can manifest during electrochemical cycling. We systematically investigate how solid electrolyte microstructure and interfacial decomposition (e.g., interphase) affect failure mechanisms in lithium thiophosphates (Li3PS4, LPS) electrolytes. Kinetically metastable interphases are engineered with iodine doping, and microstructural control is achieved using milling and annealing processing techniques. In situ transmission electron microscopy reveals iodine diffusion to the interphase, and upon electrochemical cycling, pores are formed in the interphase region. In situ synchrotron tomography reveals that interphase pore formation drives edge fracture events, which are the origin of through-plane fracture failure. Fractures in thiophosphate electrolytes actively grow toward regions of higher porosity and are affected by heterogeneity in microstructure (e.g., porosity factor). This report provides fundamental design guidelines for high-performance solid-state batteries.
Zeolite Nanosheets Stabilize Catalyst Particles to Promote the Growth of Thermodynamically Unfavorable, Small–Diameter Carbon Nanotubes
A challenge in the synthesis of single–wall carbon nanotubes (SWCNTs) is the lack of control over the formation and evolution of catalyst nanoparticles and the lack of control over their size or chirality. Here, zeolite MFI nanosheets (MFI–Ns) are used to keep cobalt (Co) nanoparticles stable during prolonged annealing conditions. Environmental transmission electron microscopy (ETEM) shows that the MFI–Ns can influence the size and shape of nanoparticles via particle/support registry, which leads to the preferential docking of nanoparticles to four or fewer pores and to the regulation of the SWCNT synthesis products. The resulting SWCNT population exhibits a narrow diameter distribution and SWCNTs of nearly all chiral angles, including sub–nm zigzag (ZZ) and near–ZZ tubes. Theoretical simulations reveal that the growth of these unfavorable tubes from unsupported catalysts leads to the rapid encapsulation of catalyst nanoparticles bearing them; their presence in the growth products suggests that the MFI–Ns prevent nanoparticle encapsulation and prologue ZZ and near–ZZ SWCNT growth. Furthermore, these results thus present a path forward for controlling nanoparticle formation and evolution, for achieving size– and shape–selectivity at high temperature, and for controlling SWCNT synthesis.
Replication Data for: New Role of Pd Hydride as a Sensor of Surface Pd Distributions in Pd-Au Catalysts
The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.
Investigation of Rh–titanate (ATiO 3 ) interactions on high-surface-area perovskite thin films prepared by atomic layer deposition
Thin, ~1 nm films of CaTiO 3 , SrTiO 3 , and BaTiO 3 were deposited onto MgAl 2 O 4 by Atomic Layer Deposition (ALD) and studied as catalyst supports for Rh. Scanning Transmission Electron Microcopy (STEM) and X-Ray Diffraction (XRD) demonstrated that the films had the perovskite structure and formed uniform coatings stable up to 1073 K. Rh, added by ALD, interacted strongly with CaTiO 3 and somewhat less strongly with SrTiO 3 , while Rh on BaTiO 3 was similar to Rh on unmodified MgAl 2 O 4 . STEM measurements of Rh on CaTiO 3 films showed Rh remained well dispersed after repeated oxidations and reductions at 1073 K; however, the Rh was inactive for CO-oxidation. Rh formed small particles on SrTiO 3 films and was active for CO oxidation after reduction at 1073 K. The reducibility and catalytic activity of Rh/BaTiO 3 /MgAl 2 O 4 were similar to that of Rh/MgAl 2 O 4 . Evidence from CO-TPR, FTIR, and XPS all indicated that the degree of interaction between Rh and the three perovskite films can be ranked in the following order: Rh/CaTiO 3 /MgAl 2 O 4 > Rh/SrTiO 3 /MgAl 2 O 4 > Rh/BaTiO 3 /MgAl 2 O 4 . Here, bulk ex-solution catalysts, synthesized by reduction of ATi 0.98 Rh 0.02 O 3 (A = Ca, Sr, and Ba), were also examined for comparison.
Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images
Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.