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39 records · Page 3

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DOE OSTI2022

Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy

The functionality of ferroelastic domain walls in ferroelectric materials is explored in real-time via the in situ implementation of computer vision algorithms in scanning probe microscopy (SPM) experiment. The robust deep convolutional neural network (DCNN) is implemented based on a deep residual learning framework (Res) and holistically nested edge detection (Hed), and ensembled to minimize the out-of-distribution drift effects. The DCNN is implemented for real-time operations on SPM, converting the data stream into the semantically segmented image of domain walls and the corresponding uncertainty. Further the pre-defined experimental workflows perform piezoresponse spectroscopy measurement on thus discovered domain walls, and alternating high- and low-polarization dynamic (out-of-plane) ferroelastic domain walls in a PbTiO 3 (PTO) thin film and high polarization dynamic (out-of-plane) at short ferroelastic walls (compared with long ferroelastic walls) in a lead zirconate titanate (PZT) thin film is reported. This work establishes the framework for real-time DCNN analysis of data streams in scanning probe and other microscopies and highlights the role of out-of-distribution effects and strategies to ameliorate them in real time analytics.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Revealing the role of redox reaction selectivity and mass transfer in current–voltage predictions for ensembles of photocatalysts

Photocatalysts are conceptually simple reaction units where nanoscale semiconductors integrated with catalysts drive a pair of redox reactions on illumination. However, the proximity of reaction sites performing cathodic and anodic reactions poses dire challenges to realize large light-to-fuel conversion efficiencies. In this study, a powerful, yet straightforward, equivalent-circuit detail-balance modeling framework is developed and applied to evaluate the performance of photocatalytic systems featuring multiple light absorbers. Specifically, low bandgap iridium-doped strontium titanate is modeled as a Z-scheme photocatalyst to achieve desirable hydrogen evolution and iron-based redox shuttle oxidation reactions. Our model has unique capabilities to simulate competing redox reactions and address mass-transfer limitations. In a significant departure from state-of-the-art circuit models, our study develops tools to perform load-line analyses by incorporating a net electrochemical load curve that includes both desired and competing redox reactions. Consequently, reaction selectivity is predicted from equivalent circuit models for photocatalytic and photoelectrochemical systems. Our investigation into ensembles comprised of multiple, semi-transparent light absorbers reveals their potential to outperform a single, optically thick light absorber, particularly when operated under mass-transfer-limited conditions. However, this outcome hinges on minimizing mass-transfer rates of select redox species to prevent undesired reactions of hydrogen oxidation and/or redox shuttle reduction. Our findings demonstrate that reaction selectivity can be achieved by tuning asymmetry in redox species mass-transfer even with perfectly symmetric electrocatalytic charge-transfer coefficients. The influences of various kinetic, mass-transfer, and thermodynamic parameters are explored to offer crucial insights for synthesis of the next-generation of photocatalysts and selective coatings, and reactor designs.

25 ENERGY STORAGE↗

DOE OSTI2025

Impact of Electrolyte Solvent on Li 4 Ti 5 O 12 /LiNi 0.90 Mn 0.05 Co 0.05 O 2 Battery Performance for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) systems require dedicated development of battery materials that target long cycle life and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) and LiNi 0.9 Mn 0.05 Co 0.05 O 2 (NMC90-5-5) shows promise to achieve targets for BTMS applications; however, minimal literature is available that discusses electrolyte solvent selection for this pairing. This study explores the role of electrolyte solvent on cycle life in LTO/NMC90-5-5 batteries. Four model electrolytes are evaluated; the baseline, Gen2, is compared with 1M LiPF 6 added to each of three separate solvents: ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). An additional consideration is that NMC90-5-5 undergoes an H2→H3 phase transition that allows for a significant increase to capacity; however, it’s unclear how this phase transition impacts electrolyte stability and cycle life. Therefore, the phase transition is avoided or accessed by cycling to 2.6V or 2.7V, respectively. The cells with Gen2, cycled to 2.6V, show the highest capacity retention due to EC passivating the LTO, EMC improving stability at the NMC90-5-5, and avoiding increased degradation from the 2.7V protocol. Despite having high initial reactivity that causes Li-depletion, FEC was the only solvent to avoid increased degradation when moving to the higher termination voltage.

25 ENERGY STORAGE↗