Article
Thermodynamics
Mehdi Pishahang, Yngve Larring, Schalk Cloete, Martin Fleissner Sunding, Christelle Denonville, Zuoan Li
Summary: The double-perovskite Ca2AlMnO5+delta has demonstrated excellent oxygen uptake and release capacity at intermediate temperatures (400-700 degrees C), making it a potential candidate for in situ oxygen production in IGCC processes.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2023)
Review
Physics, Applied
Abhijit Biswas, William Joshua Kennedy, Nicholas R. R. Glavin, Pulickel M. M. Ajayan
Summary: In recent decades, there has been a significant increase in research focused on growing high quality atomically smooth epitaxial thin films, demonstrating unprecedented quantum correlated phenomena and a great potential for oxitronics. However, the growth of defect-free and highly conducting perovskite oxide thin films still remains an active area of research due to various factors influencing film quality and electronic properties. This review summarizes the progress in growing atomically smooth epitaxial thin films of highly conducting ABO(3) perovskites with low resistivity and highlights the importance of optimizing growth parameters and film-substrate interaction for achieving high-quality epitaxy. Highly conducting epitaxial oxide thin films are essential for bridging the gap between oxides and their practical integration in electronics.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Chemistry, Physical
Sainan Chen, Jiacheng Jin, Han Chen, Lucun Guo
Summary: Experimental results show that the addition of 30 wt% LSCF into YBC leads to a decrease in polarization resistance, an increase in single cell output by 50% at 800 degrees C. The oxygen exchange capacity and conductivity of the YBC-LSCF composite material are greatly improved from 600 to 800 degrees C.
JOURNAL OF ALLOYS AND COMPOUNDS
(2021)
Correction
Chemistry, Multidisciplinary
Derrick Shao-Heng Liu, Maria Hilse, Jeffrey Shallenberger, Ke Wang, Roman Engel-Herbert, Mengyi Wang, Yun Kyung Shin, Nadire Nayir, Adri C. T. van Duin
Summary: This article focuses on the self-limiting stoichiometry in SnSe thin films.
Article
Chemistry, Physical
Wenqiao Han, Songbai Hu, Qi Liu, Cai Jin, Liang Zhou, Mao Ye, Zedong Xu, Yuanmin Zhu, Lang Chen
Summary: This research demonstrates that microstructure damage of the catalyst during the oxygen evolution reaction significantly impacts its performance, highlighting the importance of eliminating intrinsic strains for enhancing electrode stability.
ACS APPLIED ENERGY MATERIALS
(2021)
Article
Materials Science, Ceramics
A. R. Gilev, E. A. Kiselev, D. S. Chezganov, A. S. Volegov, E. R. Khuzyagulov, V. A. Cherepanov, A. Maignan
Summary: The study reveals that manganese doping in La1.5Sr0.5Ni1-yMnyO4+delta ceramic membranes affects crystallite orientation and oxygen permeation flux, with an increase in Mn4+ concentration contributing to a significant decrease in surface limitations of the oxygen exchange process.
JOURNAL OF THE EUROPEAN CERAMIC SOCIETY
(2021)
Article
Chemistry, Analytical
Jeffrey Wuenschell, Ki-Joong Kim, Michael Buric
Summary: Optical fiber-based sensors are suitable for in-situ sensing applications in high temperature and harsh chemical conditions. This study combines single crystal sapphire fiber with a high-temperature stable perovskite oxide sensing layer to demonstrate all-optical oxygen sensing at extreme temperatures. The stability, humidity resistance, and low cross-sensitivity with CO2 make it viable for use in an operational SOFC or post-combustion environment.
SENSORS AND ACTUATORS B-CHEMICAL
(2023)
Article
Physics, Applied
Jialing Xu, Ying Su, Liyun Jia, Li Ma, Ping Song, Lingjun Zhao, Pu Liu, Tao Wang, Denglu Hou
Summary: Epitaxial Fe1.1Ti0.9O3-delta thin films with a smooth surface were prepared by adjusting the substrate temperature and via pulsed laser deposition. It was found that thin films grown in Ar gas had more oxygen vacancies and significantly widened optical band gap. The substrate temperature had a significant effect on the crystallization and magnetism of the thin films.
JOURNAL OF SUPERCONDUCTIVITY AND NOVEL MAGNETISM
(2022)
Article
Nanoscience & Nanotechnology
Min-Han Lee, Yoav Kalcheim, Javier del Valle, Ivan K. Schuller
Summary: The study demonstrates a high-vacuum gas evolution technique to precisely control oxygen concentrations in VOX thin films. Through detailed structural investigations, optimal stoichiometry is achieved and stabilized. This technique provides new pathways to strategically tune the oxygen stoichiometry in complex oxides and offers insights into the phase stability of VOX thin films.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Nanoscience & Nanotechnology
Tongtong Huang, Yingjie Lyu, Huaixun Huyan, Jinyang Ni, Sahar Saremi, Yujia Wang, Xingxu Yan, Di Yi, Qing He, Lane W. W. Martin, Hongjun Xiang, Xiaoqing Pan, Pu Yu
Summary: The ferromagnetism in LaCoO3 thin films can be modulated by varying the oxygen pressure during thin-film growth. The magnetization of the samples is not influenced by the cobalt valence state and perovskite crystalline structure, but mainly determined by the tetragonal distortion induced by tensile strain, which modifies the orbital occupancy and leads to a low-spin to high-spin transition. This work provides important insights into the understanding of exotic ferromagnetism in LaCoO3 thin films and suggests a promising strategy for designing electronic states in complex oxides through cation-stoichiometry engineering.
ADVANCED ELECTRONIC MATERIALS
(2023)
Article
Crystallography
Yuri A. Mastrikov, Denis Gryaznov, Guntars Zvejnieks, Maksim N. Sokolov, Mara Putnina, Eugene A. Kotomin
Summary: This paper investigates the vacancy formation energy and its relationship with Sr concentration and oxygen nonstoichiometry of Sr-doped lanthanum scandate, a perovskite-type material. Unlike other materials, the electrons in this material are trapped at the oxygen vacancy site instead of being localized on the nearby cations. The saturation level of the vacancy formation energy is reached when the Sr concentration to oxygen nonstoichiometry ratio is greater than or equal to 2, which is potentially beneficial for proton uptake.
Article
Chemistry, Physical
Shailesh Kalal, Mukul Gupta, Rajeev Rawat
Summary: The study focused on the effects of nitrogen concentration on the structural and superconducting properties of niobium mononitride (NbN) thin films deposited using reactive magnetron sputtering of Nb at different partial pressures of N2. It was found that at low nitrogen concentrations, N atoms occupy interstitial sites within Nb leading to lattice distortion, while at intermediate nitrogen concentrations, nearly stoichiometric NbN phase emerges, and further nitridation results in expansion and distortion of NbN. High magnetic field resistivity measurements showed that optimal nitrogen concentration at R-N2 = 16% resulted in maximized superconducting transition temperature (Tc) and upper critical field (HC2(0)). Additionally, applying a radio frequency (rf) bias during the growth of NbN thin films enhanced adatom mobility leading to improved crystalline ordering and higher Tc of 13.2 K.
JOURNAL OF ALLOYS AND COMPOUNDS
(2021)
Article
Materials Science, Multidisciplinary
Lei Cao, Andreas Herklotz, Diana Rata, Chenyang Yin, Oleg Petracic, Ulrich Kentsch, Manfred Helm, Shengqiang Zhou
Summary: The efficient control of vacancy profiles in epitaxial La0.7Sr0.3MnO3-delta thin films through helium implantation leads to significant changes in physical properties, transitioning from ferromagnetic metallic to antiferromagnetic insulating, with a substantial increase in resistivity by four orders of magnitude at room temperature. This result offers an attractive means for tuning the emergent physical properties of oxide thin films through a strong coupling between strain, defects, and valence.
PHYSICA STATUS SOLIDI-RAPID RESEARCH LETTERS
(2021)
Article
Engineering, Chemical
Guoqiu Cai, Cong Luo, Ying Zheng, Dingshan Cao, Tong Luo, Xiaoshan Li, Fan Wu, Liqi Zhang
Summary: In this study, BaCoO3-delta perovskite oxide was proposed as an excellent oxygen carrier for chemical looping air separation (CLAS). The results showed that BaCoO3-delta had a large oxygen capacity and stable oxygen desorption performance, making it suitable for high-temperature gas separation technologies.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Chemistry, Analytical
Niklas Wolff, Md Redwanul Islam, Lutz Kirste, Simon Fichtner, Fabian Lofink, Agne Zukauskaite, Lorenz Kienle
Summary: Research on wurtzite-type aluminum scandium nitride (Al1-xScxN) thin films revealed an anomalous thermal expansion at high temperatures, attributed to the coupling contributions of intrinsic and extrinsic factors. This finding is significant for the manufacturing and operation of Al1-xScxN-based devices.
Article
Chemistry, Multidisciplinary
Reinis Ignatans, Maxim Ziatdinov, Rama Vasudevan, Mani Valleti, Vasiliki Tileli, Sergei Kalinin
Summary: This study introduces a deep learning-based method that learns the latent space representation of the domain dynamics in ferroelectric materials using a combination of semantic segmentation, rotationally invariant variational autoencoder, and non-negative matrix factorization. The method identifies polarization switching and phase transition mechanisms from observational data.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Maxim A. Ziatdinov, Yongtao Liu, Anna N. Morozovska, Eugene A. Eliseev, Xiaohang Zhang, Ichiro Takeuchi, Sergei Kalinin
Summary: This article introduces an active learning approach based on co-navigation of the hypothesis and experimental spaces, combining structured Gaussian processes with reinforcement learning policy. It closely resembles the classical human-driven physical discovery process and has been demonstrated in exploring concentration-induced phase transitions in doped BiFeO3. The method can be extended to higher-dimensional parameter spaces and more complex problems in the future.
ADVANCED MATERIALS
(2022)
Article
Chemistry, Physical
Jonghee Yang, Diana K. LaFollette, Benjamin J. Lawrie, Anton V. Ievlev, Yongtao Liu, Kyle P. Kelley, Sergei V. Kalinin, Juan-Pablo Correa-Baena, Mahshid Ahmadi
Summary: Mixed cesium- and formamidinium-based metal halide perovskites (MHPs) are promising photovoltaic materials, but high cesium ratios result in chemical complexities and local inhomogeneities, compromising the optoelectronic performance.
ADVANCED ENERGY MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Yongtao Liu, Jonghee Yang, Benjamin J. Lawrie, Kyle P. Kelley, Maxim Ziatdinov, Sergei V. Kalinin, Mahshid Ahmadi
Summary: The increasing photovoltaic efficiency and stability of metal halide perovskites (MHPs) are attributed to the improvement in understanding the microstructure of polycrystalline MHP thin films. A workflow combining conductive atomic force microscopy (AFM) measurement with a machine learning (ML) algorithm was designed to systematically investigate the grain boundaries in MHPs. This approach revealed that the properties of grain boundaries play critical roles in MHP stability.
Article
Chemistry, Physical
Yongtao Liu, Jonghee Yang, Rama K. Vasudevan, Kyle P. Kelley, Maxim Ziatdinov, Sergei Kalinin, Mahshid Ahmadi
Summary: We demonstrate an active machine learning framework for driving an automated scanning probe microscope (SPM) to discover the microstructures responsible for specific aspects of transport behavior in metal halide perovskites (MHPs). This approach allows the microscope to discover the microstructural elements that maximize the onset of conduction, hysteresis, or any other characteristic derived from a set of current-voltage spectra. It provides new opportunities for exploring the origins of materials functionality in complex materials by SPM and can be integrated with other characterization techniques.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Review
Materials Science, Multidisciplinary
Jonghee Yang, Sergei V. Kalinin, Ekin D. Cubuk, Maxim Ziatdinov, Mahshid Ahmadi
Summary: Low-dimensional hybrid perovskites combine the physical functionalities of inorganic materials and complexity of organic molecules to form self-organized complex structures. These materials offer high-performance optoelectronics and versatile applications, and can be produced cost-effectively.
Letter
Chemistry, Physical
Andrew R. Akbashev, Sergei V. Kalinin
Article
Chemistry, Multidisciplinary
Muammer Y. Yaman, Sergei V. Kalinin, Kathryn N. Guye, David S. Ginger, Maxim Ziatdinov
Summary: The application of machine learning is demonstrated for rapidly and accurately extracting plasmonic particles cluster geometries from hyperspectral image data using a dual variational autoencoder (dual-VAE). This approach shares information between the latent spaces of two VAEs, one handling particle shape data and the other handling spectral data, while enforcing a common encoding for shape-spectra pairs. The results show that this approach can establish the relationship between the geometric characteristics of nanoparticles and their far-field photonic responses, allowing for accurate prediction of the geometry of multiparticle assemblies below the diffraction limit using hyperspectral darkfield microscopy in an automated manner.
Article
Chemistry, Physical
Yongtao Liu, Rama K. K. Vasudevan, Kyle P. Kelley, Hiroshi Funakubo, Maxim Ziatdinov, Sergei V. V. Kalinin
Summary: We developed automated experiment workflows for identifying the best predictive channel in spectroscopic measurements. The approach combines ensembled deep kernel learning for probabilistic predictions and reinforcement learning for channel selection. The implementation in multimodal imaging of piezoresponse force microscopy (PFM) showed that the amplitude is the best predictive channel for polarization-voltage and frequency-voltage hysteresis loop areas. This workflow and code can be applied to other multimodal imaging and local characterization methods.
NPJ COMPUTATIONAL MATERIALS
(2023)
Article
Computer Science, Artificial Intelligence
Yongtao Liu, Anna N. Morozovska, Eugene A. Eliseev, Kyle P. Kelley, Rama Vasudevan, Maxim Ziatdinov, Sergei V. Kalinin
Summary: Using hypothesis-learning-driven automated scanning probe microscopy (SPM), this study investigates the bias-induced transformations in various devices and materials. It is crucial to understand these mechanisms on the nanometer scale with a wide range of control parameters, which is experimentally challenging. The hypothesis-driven SPM autonomously identifies the mechanisms of bias-induced domain switching and reveals the importance of kinetic control.
Article
Computer Science, Artificial Intelligence
Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov, Sergei Kalinin
Summary: Unsupervised and semi-supervised ML methods like VAE are widely used in physics, chemistry, and materials sciences for disentangling representations and finding latent manifolds in complex experimental data. This study explores a latent Bayesian optimization approach for hyperparameter trajectory optimization in unsupervised and semi-supervised ML, demonstrated by joint-VAE with rotational invariances. The method is applied to finding joint discrete and continuous rotationally invariant representations in the MNIST database and a plasmonic nanoparticles material system.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2023)
Article
Physics, Applied
Jinyuan Yao, Yongtao Liu, Shaoqing Ding, Yanglin Zhu, Zhiqiang Mao, Sergei V. Kalinin, Ying Liu
Summary: Ferroelectricity in van der Waals layered material has attracted significant attention. The ferroelectric properties of CuInP2S6 (CIPS), which is the only van der Waals layered material that has demonstrated ferroelectricity in the bulk, have been observed to persist even at a few nanometers thickness. However, the potential device applications of CIPS' ferroelectric properties are just beginning to be explored.
APPLIED PHYSICS LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Maxim Ziatdinov, Chun Yin (Tommy) Wong, Sergei Kalinin
Summary: Recent advances in scanning tunneling and transmission electron microscopies have generated large volumes of imaging data containing information on the structure and functionality of materials. However, automatic extraction and classification of patterns in the images is non-trivial. To address this problem, the authors propose a shift-invariant variational autoencoder approach and demonstrate its effectiveness on 1D, synthetic, and experimental data. The shift VAE analysis shows promise for pattern discovery, but also has limitations.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2023)
Article
Automation & Control Systems
Sheryl Sanchez, Yongtao Liu, Jonghee Yang, Sergei V. Kalinin, Maxim Ziatdinov, Mahshid Ahmadi
Summary: In recent years, laboratory automation and high-throughput synthesis and characterization have become increasingly important in the research community. To effectively analyze the large datasets and extract system properties, suitable machine learning techniques, such as the variational autoencoder (VAE) approach, are needed. This study explores the binary library of metal halide perovskite microcrystals using low-dimensional latent representations of photoluminescence spectra. The combination of translationally invariant variational autoencoders (tVAEs) and conditional autoencoders (cVAEs) allows for a deeper understanding of the underlying mechanisms within the data.
ADVANCED INTELLIGENT SYSTEMS
(2023)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Anees Al-Najjar, Nageswara S. Rao, Ramanan Sankaran, Maxim Ziatdinov, Debangshu Mukherjee, Olga Ovchinnikova, Kevin Roccapriore, Andrew R. Lupini, Sergei Kalinin
Summary: This article introduces an approach based on separate data and control channels for conducting remotely steered and automated experiments in the ecosystem of Scanning Transmission Electron Microscopes (STEM) and computing systems. The feasibility of this approach is demonstrated through experiments, and the concept of a Virtual Infrastructure Twin (VIT) is proposed for developing and testing control software modules.
2022 IEEE 18TH INTERNATIONAL CONFERENCE ON E-SCIENCE (ESCIENCE 2022)
(2022)
