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Accurate and Data-Efficient Micro-XRD Phase Identification Using Multi-Task Learning: Application to Hydrothermal Fluids

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arXiv 2024年

作者： Li, Yanfei Liu, Juejing Zhao, Xiaodong Liu, Wenjun Geng, Tong Li, Ang Zhang, Xin Pacific Northwest National Laboratory RichlandWA99354 United States Materials Science and Engineering Program Washington State University PullmanWA99164 United States Advanced Photon Source Argonne National Laboratory LemontIL60439 United States Department of Electrical and Computer Engineering University of Rochester New York14627 United States

Traditional analysis of highly distorted micro-X-ray diffraction (μ-XRD) patterns from hydrothermal fluid environments is a time-consuming process, often requiring substantial data preprocessing and labeled experimental data. This study demonstrates the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations. We trained MTL models to identify phase information in μ-XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models showed superior accuracy compared to binary classification CNNs. Additionally, introducing a tailored cross-entropy loss function improved MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieved close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor-intensive experimental datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

Towards Space Group Determination from EBSD Patterns: The Role of Deep Learning and High-throughput Dynamical Simulations

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arXiv 2025年

作者： Yan, Alfred Kilic, Muhammad Nur Talha Nolze, Gert Agrawal, Ankit Choudhary, Alok Reis, Roberto dos Dravid, Vinayak Department of Materials Science and Engineering Northwestern University EvanstonIL United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL United States Federal Institute for Materials Research and Testing Berlin Germany International Institute of Nanotechnology Northwestern University EvanstonIL United States The NUANCE Center Northwestern University EvanstonIL United States

The design of novel materials hinges on the understanding of structure-property relationships. However, in recent times, our capability to synthesize a large number of materials has outpaced our speed at characterizing them. While the overall chemical constituents can be readily known during synthesis, the structural evolution and characterization of newly synthesized samples remains a bottleneck for the ultimate goal of high throughput nanomaterials discovery. Thus, scalable methods for crystal symmetry determination that can analyze a large volume of material samples within a short time-frame are especially needed. Kikuchi diffraction in the SEM is a promising technique for this due to its sensitivity to dynamical scattering, which may provide information beyond just the seven crystal systems and fourteen Bravais lattices. After diffraction patterns are collected from material samples, deep learning methods may be able to classify the space group symmetries using the patterns as input, which paired with the elemental composition, would help enable the determination of the crystal structure. To investigate the feasibility of this solution, neural networks were trained to predict the space group type of background corrected EBSD patterns. Our networks were first trained and tested on an artificial dataset of EBSD patterns of 5,148 different cubic phases, created through physics-based dynamical simulations. Next, Maximum Classifier Discrepancy, an unsupervised deep learning-based domain adaptation method, was utilized to train neural networks to make predictions for experimental EBSD patterns. We introduce a relabeling scheme, which enables our models to achieve accuracy scores higher than 90% on simulated and experimental data, suggesting that neural networks are capable of making predictions of crystal symmetry from an EBSD pattern. Copyright © 2025, The Authors. All rights reserved.

关键词： Crystal lattices

Entanglement in Quantum Dots: Insights from Dynamic Susceptibility and Quantum Fisher Information

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arXiv 2024年

作者： Abouie, Jahanfar Vashaee, Daryoosh Department of Physics Institute for Advanced Studies in Basic Sciences Zanjan45137-66731 Iran Department of Materials Science & Engineering North Carolina State University RaleighNC27606 United States Department of Electrical & Computer Engineering North Carolina State University RaleighNC27606 United States

This study investigates the entanglement properties of quantum dots (QDs) under a universal Hamiltonian where the Coulomb interaction between particles (electrons or holes) decouples into charging energy and exchange coupling terms. Although this formalism typically decouples the charge and spin components, confinement-induced energy splitting can induce unexpected entanglement within the system. By analyzing the dynamic susceptibility and quantum Fisher information (QFI), we uncover significant behaviors influenced by exchange constants, temperature variations, and confinement effects. In QDs with Ising exchange interactions, far below the Stoner instability (SI) point, where the QD is in a disordered paramagnetic phase, temperature reductions lead to decreased entanglement, challenging conventional expectations. Our findings demonstrate that for QDs with small exchange interactions, the responses of easy-plane (Jz ⊥) and easy-axis (Jz > J⊥) configurations are similar, with increased anisotropy broadening susceptibility and shifting its maximum to higher frequencies. For large exchange interactions, the susceptibility differences between easy-plane and easy-axis QDs become significant, with easy-plane QDs exhibiting a higher susceptibility magnitude. Additionally, the study reveals that temperature variations affect the dynamic response functions differently in easy-axis and easy-plane QDs. In easy-plane QDs, QFI consistently decreases with increasing temperature, whereas in easy-axis QDs, QFI behavior is highly dependent on the strengths of Jz and J⊥, showing either an increase or decrease with temperature based on specific coupling conditions. Conversely, at low temperatures, anisotropic Heisenberg models exhibit enhanced entanglement near isotropic points. Overall, this work contributes to advancing our understanding of entanglement in QDs and its potential applications in quantum technologies. Copyright © 2024, The Authors. All rights reserved.

关键词： Anisotropy

Enhanced Imaging of Electronic Hot Spots Using Quantum Squeezed Light

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arXiv 2024年

作者： An, Haechan Amiri, Ali Najjar Goronzy, Dominic P. Garcia Wetten, David A. Bedzyk, Michael J. Shakouri, Ali Hersam, Mark C. Hosseini, Mahdi Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Department of Electrical and Computer Engineering and Applied Physics Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Department of Chemistry Northwestern University EvanstonIL60208 United States

Detecting electronic hot spots is important for understanding the heat dissipation and thermal management of electronic and semiconductor devices. Optical thermoreflective imaging is being used to perform precise temporal and spatial imaging of heat on wires and semiconductor materials. We apply quantum squeezed light to perform thermoreflective imaging on micro-wires, surpassing the shot-noise limit of classical approaches. We obtain a far-field temperature sensing accuracy of 42 mK after 50 ms of averaging and show that a 256×256 pixel image can be constructed with such sensitivity in 10 minutes. We can further obtain single-shot temperature sensing of 1.6 K after only 10 µs of averaging enabling dynamical study of heat dissipation. Not only do the quantum images provide accurate spatio-temporal information about heat distribution, but the measure of quantum correlation provides additional information, inaccessible by classical techniques, that can lead to a better understanding of the dynamics. We apply the technique to both Al and Nb microwires and discuss the applications of the technique in studying electron dynamics at low temperatures. © 2024, CC BY.

关键词： Shot noise

Coherent Acoustic Phonons in Bi2Se3 Ultrathin Films Probed by Femtosecond, Optical Pump-Probe Spectroscopy

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Coherent Acoustic Phonons in Bi2Se3 Ultrathin Films Probed b...

CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Cheng, Jing Niherysh, Kiryl A. Francis, Peter Chakraborty, Debamitra Lombardi, Floriana Erts, Donats Prischepa, Serghej L. Laszcz, Adam Komissarov, Ivan V. Sobolewski, Roman Materials Science Graduate Program University of Rochester RochesterNY14627 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623-1299 United States Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg Sweden Institute of Chemical Physics University of Latvia Riga Latvia Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States Dipartimento di Fisica "E.R. Caianiello" Università degli Studi di Salerno Sa FiscianoI-84084 Italy Lukasiewicz Research Network Institute of Microelectronics and Photonics WarszawaPL-02668 Poland

ISBN: (纸本)9781957171395

The dynamics of coherent acoustic phonons in the Bi2Se3 layered crystal system are investigated. The findings reveal that the frequency evolution of breathing modes with the number of the material quintuple layers and the dispersion relation both can be explained by a modified chain model with a nonuniform coupling force. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Ultrathin films

Electronic structure prediction of medium and high entropy alloys across composition space

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arXiv 2024年

作者： Pathrudkar, Shashank Taylor, Stephanie Keripale, Abhishek Gangan, Abhijeet Sadashiv Thiagarajan, Ponkrshnan Agarwal, Shivang Marian, Jaime Ghosh, Susanta Banerjee, Amartya S. Department of Mechanical and Aerospace Engineering Michigan Technological University United States Department of Materials Science and Engineering University of California Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Center for Artificial Intelligence Michigan Technological University United States

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of sampled compositions and descriptors required to accurately predict fields like the electron density increases rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries and maintain approximately the same descriptor-vector size as alloy elements increase. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space. © 2024, CC BY.

关键词： Ground state

Electro-Optic Analog-to-Digital Converter Using Spectral Interferometry

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Electro-Optic Analog-to-Digital Converter Using Spectral Int...

Conference on Lasers and Electro-Optics (CLEO)

作者： Linbo Shao Joseph G Thomas Bernadeta R Srijanto Kevin C Lester Ivan I Kravchenko Yizheng Zhu Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Virginia Tech Center for Quantum Information Science and Engineering Blacksburg VA USA Oak Ridge National Laboratory Center for Nanophase Materials Sciences Oak Ridge TN USA

We demonstrate an optical analog-to-digital converter (ADC) leveraging spectral interferometry of an integrated electro-optic Mach-Zehnder interferometer on thin-film lithium niobate. The ADC features a high dynamic r... 详细信息

ISBN: (纸本)9798350369311

关键词： Mach-Zehnder interferometers Integrated optics Optical interferometry Lithium niobate Lasers and electrooptics High dynamic range Electro-optical waveguides Analog-digital conversion

Dual Mode pMUT for Structural Health Monitoring of Piping Systems in Advanced Reactors

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Dual Mode pMUT for Structural Health Monitoring of Piping Sy...

IEEE Symposium (IUS) Ultrasonics

作者： Talha Masood Khan John Sabino Chenxi Xu Javier Obregon Joshua Wilis Adkins Matthew Daly Alexander Heifetz Derek Wiliam Kultgen Didem Ozevin Department of Civil Materials and Environmental Engineering University of Illinois Chicago Chicago IL USA Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA Nuclear Science and Engineering Division Argonne National Laboratory Lemont IL USA

The objective of this work is to develop a durable MEMS sensor for in situ monitoring of advanced reactor piping. Existing sensors for structural health monitoring (SHM) in nuclear reactor environments have limited temperature ranges and service lifetimes, owing to material constraints. Micromachined transducers using aluminum nitride (AlN) as a sensing element, and silicon carbide (SiC) as a substrate, have the potential to address this challenge. In this work, piezoelectric Micromachined Ultrasonic Transducers (pMUT) capable of delivering passive (acoustic emission) and active (guided wave) ultrasonic sensing for SHM in a high-temperature environment are studied. These sensors will be able to couple directly to the structures for real-time SHM of advanced reactor piping systems. A customized microfabrication process is used to produce dual-mode sensing operation at a small footprint of 5×5 mm 2 . This process involves sputtering a 1 µm thick AlN sandwiched between metal and handle layer. The frequency modes of the pMUT device are tuned to 140 kHz by varying the lateral dimensions of the sensor. Sensor locations on piping are determined by generating plane waves using finite element simulations and studying the wave dispersion. With higher sensitivity, our pMUT sensors are capable of detecting the smallest defect energy at high temperatures, while decreasing the number of sensors on piping.

关键词：

Emerging trends in laser-cooling of Yb-doped silicate fibers

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Journal of Lightwave Technology 2025年

作者： Chen, Chun-Wei Meehan, Bailey Cahoon, Mary Ann Hawkins, Thomas W. Ballato, John Dragic, Peter D. Engholm, Magnus Boilard, Tommy Bernier, Martin Digonnet, Michel J. F. Stanford University Edward L. Ginzton Laboratory StanfordCA94305 United States Clemson University Department of Materials Science and Engineering ClemsonSC29631 United States University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL61801 United States Mid Sweden University Department of Engineering Mathematics and Science Education SundsvallSE-85170 Sweden QuébecQCG1V 0A6 Canada

The recent development of Yb-doped silica fibers that can be optically cooled via anti-Stokes fluorescence is fostering a new generation of fiber lasers and amplifiers that can run without external coolers. Thanks to their greatly reduced thermal loads, these devices are expected to exhibit superior properties in terms of improved power and frequency stability, and reduced thermal lensing and transverse-mode instability. This paper presents a detailed comparative study of the measured cooling properties of eight fibers with record-high Yb quenching concentrations in aluminosilicate and aluminophosphosilicate compositions. Analysis of the experimental cooling data provides valuable quantitative information about the quenching rate and background absorption of each fiber, the two parameters (besides Yb concentration) that influence the cooling performance most strongly. This study shows that aluminophosphosilicates perform better than aluminosilicates, and that very high Yb concentrations (up to 6 wt.%) can be achieved with very low quenching when the glass is co-doped with sufficient phosphorus (∼12 wt.%) and aluminum (1-7 wt.%). With the best aluminophosphosilicate composition, it is now possible to cool a fiber with a small core by as much as -250 mK at atmospheric pressure. Cooling is no longer limited by quenching, but by background absorption. Future work will focus on identifying the impurities in precursor materials responsible for this background absorption and reducing their content to lower this loss from its current 15-dB/km record value. © 2025 IEEE.

关键词： Quenching