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Ernst, Frank

Publications and source records attributed to Ernst, Frank.

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗
DOE OSTI2024

Phase Identification in Synchrotron X-ray Diffraction Patterns of Ti–6Al–4V Using Computer Vision and Deep Learning

X-ray diffraction patterns contain information about the atomistic structure and microstructure (defect population) of materials, extracting detailed information from diffraction patterns is complex, demanding and relies on prior knowledge. Here, we hypothesize that deep-learning techniques can help to perform an effective and accurate analysis with high throughput rates. To demonstrate this concept, we applied a novel deep learning framework to determine the evolution of the β-phase volume fraction in a Ti–6Al–4V alloy during heat-treatment from video sequences of 2D diffraction patterns recorded in transmission and with highly monochromatic radiation in a synchrotron beamline. In particular, we studied the impact of network design on prediction reliability and computational performance. Networks of different architectures were trained using 3008 experimental 2D patterns. A well-tuned model was found to reproduce the phase fractions of another experimental data set, consisting of 1100 diffraction patterns, with a mean-square error as small as 2.6 x 10 -4 . The average prediction error of β-phase volume fraction was within 1.6 x 10 -2 (in each diffraction pattern) of the values obtained by conventional methods. Our work demonstrates that convolutional neural networks can evaluate high energy X-ray diffraction patterns with a remarkable level of reliability. Furthermore, it demonstrates the significance of network design on the reliability of predictions and computational performance. The most complex models do not necessarily result in highest accuracy and may even fail to learn from the data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rapid Alloy Surface Engineering through Closed-Vessel Reagent Pyrolysis

For rapid surface engineering of Cr-containing alloys by low-temperature nitrocarburization, we introduce a process based on pyrolysis of solid reagents, e.g., urea, performed in an evacuated closed vessel. Upon heating to temperatures high enough for rapid diffusion of interstitial solute, but low enough to avoid second-phase precipitation, the reagent is pyrolyzed to a gas atmosphere containing molecules that (i) activate the alloy surface by stripping away the passivating Cr 2 O 3 -rich surface film (diffusion barrier) and (ii) rapidly infuse carbon and nitrogen into the alloy. We demonstrate quantitatively that this method can generate a subsurface zone with concentrated carbon and nitrogen comparable to what can be accomplished by established (e.g., gas-phase- or plasma-based) methods, but with significantly reduced processing time. As another important difference to established gas-phase processing, the interaction of gas molecules with the alloy surface can have auto-catalytic effects by altering the gas composition in a way that accelerates solute infusion by providing a high activity of HNCO. The new method lends itself to rapid experimentation with a minimum of laboratory equipment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Understanding the efficacy of concentrated interstitial carbon in enhancing the pitting corrosion resistance of stainless steel

By introducing a high fraction of interstitial carbon through low temperature carburization, the pitting corrosion resistance of austenitic stainless steel can be significantly improved. Previous work attributed this to strengthening of the passive film by carbon. Here, however, we present a paradigm shift by showing that carbon actually weakens the passive film but strengthens the bonding within the alloy by forming localized (covalent) bonds with the metal atoms (Fe, Cr, Ni). Accordingly, the enhancement in pitting resistance is a result of carbon reducing the metal dissolution rate in a local pit environment by many orders of magnitude, which extremely decreases the growth stability of a pit and prevents it from transitioning into stable growth. Electronic structure calculations confirm that carbon bonds to the metal atoms and that the metal–carbon bonds are 1.4 to 2.0 times stronger than the metal–metal bonds. These results suggest a new strategy for the design of corrosion resistant alloys, namely surface engineering by infusion of concentrated interstitials that form strong bonds with the matrix atoms.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2004

Liquid Phase Deposition of Single-Phase Alpha-Copper-Indium-Diselenide

The success of exploratory missions in outer space often depends on a highly efficient renewable energy supply, as provided by solar cells. Since future missions will demand large aggregates of solar cells, and space flight is expensive, the solar cells must furthermore be available at low costs and have a long lifetime and high resistance against structural damage introduced by irradiation with high energy electrons and protons. The photovoltaic materials that are presently available only partly fulfill all these requirements. Therefore, we propose to explore a new method for fabricating thin-films for cost-efficient solar cells with very high specific power,high irradiation resistance and long lifetime based on the alpha-phase of the Cu-In-Se system "alpha-CIS."

Hepp, Aloysius F.↗