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RESEARCH PAPER · Journal of Materiomics · 2021

Machine learning approaches for permittivity prediction and rational design of microwave dielectric ceramics

Jincheng Qin, Zhifu Liu, Mingsheng Ma, Yongxiang Li

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Machine learning approaches for permittivity prediction and rational design of microwave dielectric ceramicsOriginalSintering, Microstructure, and Dielectric Properties of Copper Borates for High Frequency LTCC Applications10The latest process and challenges of microwave dielectric ceramics based on pseudo phase diagrams211Exploring Dielectric Constant and Dissipation Factor of LTCC Using Machine Learning9Crystal structure, far-infrared spectra, and microwave dielectric properties of bazirite-type BaZr(Si1-xGex)3O9 ceramics20Artificial Intelligence based Approach for Rapid Material Discovery: From Chemical Synthesis to Quantum Materials0Machine Learning-Assisted Materials Design and Discovery of Low-Melting-Point Inorganic Oxides for Low-Temperature Cofired Ceramic Applications18Preparation and characterization of doped LiZn0.92Cu0.08PO4 ceramic for microwave and millimeter-wave substrates2Machine learning approach for ball milling of alumina ceramics0XGBoost model for electrocaloric temperature change prediction in ceramics70A machine learning approach for ball milling of alumina ceramics6Novel copper borate ceramics with lithium-based sintering aids for LTCC terahertz applications10Optimization of multilayered electromagnetic shielding using mesh adaptive direct search5Enhancing the bandwidth of antennas using polymer composites with high dielectric relaxation17Ultra-low temperature cofired ceramics based on Li2WO4as perspective substrate materials for terahertz frequencies28Dielectric constant prediction of perovskite microwave dielectric ceramics via machine learning24Correlation between structural characteristics and microwave dielectric properties of walstromite BaCa 2 M 3 O 9 ( M = Si, Ge) ceramics13Evolution of Phase Transformation on Microwave Dielectric Properties of BaSixO1+2x Ceramics and Their Temperature-Stable LTCC Materials6Can CNNs be Used to Predict Multi-Physics Simulations of Microwave Induced Damage to Basalt?0Optimizing and extending ion dielectric polarizability database for microwave frequencies using machine learning methods55Novel ultralow-permittivity BaMg2Al6Si9O30-based microwave dielectric ceramics with self near-zero temperature coefficient of resonant frequency and thermal expansion25Machine learning aided accelerated prediction and experimental validation of functional properties of K1-xNaxNbO3-based piezoelectric ceramics18Materials Development and Potential Applications of Ceramics: New Opportunities and Challenges5Thermal conductivity prediction of sintered reaction bonded silicon nitride ceramics using a machine learning approach based on process conditions19From Graph Machine Learning to Furnaces: Permittivity Exploring of Dielectric Ceramics0Improved Arithmetic Optimization Algorithm with Multi-Strategy Fusion Mechanism and Its Application in Engineering Design6Machine learning enhanced prediction of permittivity of spinel microwave dielectric ceramics compared to traditional C-M calculation4An Automated Machine Learning Approach to Inkjet Printed Component Analysis: A Step Toward Smart Additive Manufacturing2Multilayer artificial intelligence for thermal-conductivity prediction of silicon nitride ceramics from powder processing conditions and predicted densities7Machine Learning in Biomaterials, Biomechanics/Mechanobiology, and Biofabrication: State of the Art and Perspective60Optimizing a machine learning design of dielectric properties in lead-free piezoelectric ceramics17GemNet: Analysis and Prediction of Building Materials for Optimizing Indoor Wireless Networks1AI for dielectric capacitors16Discovering ABO3-type perovskite with different dielectric constants via intelligent optimization algorithm6Structure and microwave dielectric characteristics of (Ba,Sr,Ca)HfO3 ceramics8Machine learning assisted Q×f value prediction of ABO4-type microwave dielectric ceramics18A strategy for accurate prediction of dielectric permittivity and dielectric strength in polyimide6Microstructural basis of AI predictions for material properties: A case study of silicon nitride ceramics using t ‐SNE8Advancements in microwave dielectric ceramics with K20 for 5G/6G communication systems: a review32Nondestructive Electrical Permittivity Detection Using ANN-Enhanced Microstrip Sensors1Exceptionally optimized millimeter-wave properties of cordierite-based materials via innovative processing and predictive analytics7Interpretable model of dielectric constant for rational design of microwave dielectric materials: a machine learning study11Multiobjective optimization of dielectric, thermal, and mechanical properties of inorganic glasses utilizing explainable machine learning and genetic algorithm8Data-driven analysis and visualization of dielectric properties curated from scientific literature4A novel hybrid 2D-FDTD-PML and Nelder–Mead methods for estimating liquid complex permittivity using a rectangular waveguide3Deep learning enhanced prediction of microwave dielectric constant of spinel ceramics eliminating manual feature engineering4Compositionally Complex Oxide Dielectrics for Microwave Applications: Current Status and Future Trends: A Review0Impact of Cu2+ doping on the structure and electromagnetic properties of Zn3B2O6 ceramics2Accelerating Low-k Dielectric Material Discovery: From Graph Machine Learning to Synthesis9Prediction of piezoelectric properties of NBT-based ceramics based on deep neural networks4A review on the applications of machine learning in biomaterials, biomechanics, and biomanufacturing for tissue engineering20Predicting mechanical properties and behavioral performance of ceramic-modified concrete using optimized multidimensional refinement graph convolutional networks4Machine learning assisted τf value prediction of ABO3-type microwave dielectric ceramics8Optimizing dielectric properties of corannulene nanomaterial for enhanced performance of next-generation electric vehicle batteries: A Machine learning and Nelder-Mead optimization approach1Impact of AlF3-CaB4O7 Doping on Terahertz Dielectric Properties and Feasibility of Low/Ultra-Low Temperature Co-Fired Ceramics3Enhanced permittivity prediction in microwave dielectric ceramics and structure-property insights via CGCNN combined with GNNExplainer2Machine learning‐enabled prediction of oxide glasses’ dielectric constants via augmented data and physicochemical descriptors1Support Vector Machine‐Based Modeling and Prediction of the Dielectric Properties of Saffron Stigma and Style0Broadband Validation of a 2D-FDTD-PML and Nelder-Mead Framework for Liquid Permittivity Extraction0Revealing loss mechanisms through interpretable machine learning and accelerated discovery of ultra-low-loss dielectric ceramics in the Li2TiO3-Li3NbO4-MgO system12A new approach for estimating the complex permittivity of powdered dielectrics using a rectangular waveguide in the X-band0An Adaptive Neuro-Fuzzy Inference System for Retrieving the Complex Permittivity and Permeability of Composite Materials0Interpretable machine learning-assisted discovery of BaTiO 3 -based ceramics with enhanced dielectric constant1Li2WO4 and LiBO2 as the basic components and additives in ULTCC/LTCC substrates for 5G/6G applications0Advances in Low‐Temperature Co‐Fired Ceramics for Next‐Generation Electronics Applications15Neural Network‐Based Permittivity Engineering of Magnetic Absorbers for Customizable Microwave Absorption10Establishing a Trustworthy Discovery Workflow for High-Entropy BNT Ceramics via SHAP-Interpretable Machine Learning0Closing the loop from materials design to mmWave devices: Ultrahigh-Q, thermally stable Mg2SiO4 ceramics enabled by synergistic ionic engineering for 24GHz dielectric resonator antennas1Garnet-structured microwave dielectric ceramics: Structural characteristics, lattice vibrations, dielectric mechanisms, and machine learning2Machine learning assisted τf value prediction of ABO4-type microwave dielectric ceramics0Dielectric, thermal, compositional and microstructural characterization of copper doped LiZnPO4 ceramics for ULTCC terahertz applications0Machine-learning-guided inverse design of lead-free relaxors enabled by multimodal literature mining0Process-structure-property relationships in low-temperature microwave dielectric ceramics: from glass-assisted sintering to cold sintering for 5G/6G devices0Forecasting the Dielectric Properties of Obsidian Containing Cement Mortars Using Distinct Approaches in Machine Learning0Optimization of microwave dielectric properties based on charge compensation and preparation of novel electronic glass fibers for electronic substrates0Lithium metaborate as a lightweight ultra low temperature cofired ceramic substrate for high speed communication systems1Machine learning-assisted prediction of microwave dielectric properties in high-entropy titanate ceramics0Machine Learning–Assisted Exploration of the Structural, Dielectric, and Ferroelectric Properties of CaTiO3 Nanoceramics0Surrogate Modelling Approach in Materials Dielectric Constant Prediction: Sim-to-Real and Generalization Capability Analysis0Composition-only machine-learning benchmark for three dielectric properties of single-phase ULTCC ceramics0Machine learning-based prediction and explainability of frequency and temperature dependent dielectric properties of GdFeTiO5 oxide0

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  1. Sintering, Microstructure, and Dielectric Properties of Copper Borates for High Frequency LTCC Applications

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    Dorota Szwagierczak, Beata Synkiewicz-Musialska, Jan Kulawik, Norbert Pałka

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  2. The latest process and challenges of microwave dielectric ceramics based on pseudo phase diagrams

    Journal of Advanced Ceramics · 2021-10-01

    Hongcheng Yang, Shuren Zhang, Hongyu Yang, Qingyu Wen, Yang Qiu, Ling Gui, Qian Zhao, Enzhu Li

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  3. Exploring Dielectric Constant and Dissipation Factor of LTCC Using Machine Learning

    Materials · 2021-10-03

    Yuchen Liu, Tzu‐Yu Liu, Tien-Heng Huang, Kuo‐Chuang Chiu, Shih‐kang Lin

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  4. Crystal structure, far-infrared spectra, and microwave dielectric properties of bazirite-type BaZr(Si1-xGex)3O9 ceramics

    Ceramics International · 2021-10-25

    Kang Du, Changzhi Yin, Jiaqing Yang, Wei Luo, Xiao‐Chuan Wang, Wenzhong Lü, Wen Lei

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  5. Artificial Intelligence based Approach for Rapid Material Discovery: From Chemical Synthesis to Quantum Materials

    Unknown journal · 2022-01-01

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  6. Machine Learning-Assisted Materials Design and Discovery of Low-Melting-Point Inorganic Oxides for Low-Temperature Cofired Ceramic Applications

    ACS Sustainable Chemistry & Engineering · 2022-01-20

    Jincheng Qin, Zhifu Liu, Mingsheng Ma, Yongxiang Li

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  7. Preparation and characterization of doped LiZn0.92Cu0.08PO4 ceramic for microwave and millimeter-wave substrates

    Microelectronics International · 2022-02-04

    Beata Synkiewicz-Musialska, Dorota Szwagierczak, Jan Kulawik, Elżbieta Czerwińska

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  8. Machine learning approach for ball milling of alumina ceramics

    Research Square · 2022-06-06

    Jungwon Yu, Raju Kati, So-Hyun Jin, Young-Jae Lee, Hyun Kwuon Lee

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  9. XGBoost model for electrocaloric temperature change prediction in ceramics

    npj Computational Materials · 2022-07-01

    Jie Gong, Sharon Chu, Rohan K. Mehta, Alan J. H. McGaughey

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  10. A machine learning approach for ball milling of alumina ceramics

    The International Journal of Advanced Manufacturing Technology · 2022-11-18

    Jungwon Yu, Kati Raju, So-Hyun Jin, Young-Jae Lee, Hyun-Kwuon Lee

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  11. Novel copper borate ceramics with lithium-based sintering aids for LTCC terahertz applications

    Journal of Materials Chemistry C · 2023-01-01

    Dorota Szwagierczak, Beata Synkiewicz-Musialska, Jan Kulawik, Elżbieta Czerwińska, Norbert Pałka

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  12. Optimization of multilayered electromagnetic shielding using mesh adaptive direct search

    Applied Nanoscience · 2023-02-06

    Л. Л. Вовченко, Oleg V. Lozitsky, Lyudmila Yu. Matzui, Volodymyr V. Zagorodnii

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  13. Enhancing the bandwidth of antennas using polymer composites with high dielectric relaxation

    Materials Today Electronics · 2023-02-15

    Ilkan Calisir, Xiantao Yang, Elliot L. Bennett, Jianliang Xiao, Yi Huang

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  14. Ultra-low temperature cofired ceramics based on Li2WO4as perspective substrate materials for terahertz frequencies

    Journal of Advanced Ceramics · 2023-02-15

    Dorota Szwagierczak, Beata Synkiewicz-Musialska, Jan Kulawik, Elżbieta Czerwińska, Norbert Pałka

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  15. Dielectric constant prediction of perovskite microwave dielectric ceramics via machine learning

    Materials Today Communications · 2023-03-01

    Yicong Ye, Ziqi Ni, Kaijia Hu, Yahao Li, Yongqian Peng, Xingyu Chen

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  16. Correlation between structural characteristics and microwave dielectric properties of walstromite BaCa 2 M 3 O 9 ( M = Si, Ge) ceramics

    Journal of the American Ceramic Society · 2023-05-20

    Kang Du, Changzhi Yin, Zheng‐Yu Zou, Mingfei Cheng, Yiyang Cai, Jiaqing Yang, Meng Zhang, Wenzhong Lü, Shengxiang Wang, Wen Lei

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  17. Evolution of Phase Transformation on Microwave Dielectric Properties of BaSixO1+2x Ceramics and Their Temperature-Stable LTCC Materials

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  18. Can CNNs be Used to Predict Multi-Physics Simulations of Microwave Induced Damage to Basalt?

    Unknown journal · 2023-07-24

    Reena Patel, Jeff Allen, Tomas Mondragon, Oliver Taylor

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  19. Optimizing and extending ion dielectric polarizability database for microwave frequencies using machine learning methods

    npj Computational Materials · 2023-07-28

    Jincheng Qin, Zhifu Liu, Mingsheng Ma, Yongxiang Li

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  20. Novel ultralow-permittivity BaMg2Al6Si9O30-based microwave dielectric ceramics with self near-zero temperature coefficient of resonant frequency and thermal expansion

    Journal of the European Ceramic Society · 2023-07-31

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  21. Machine learning aided accelerated prediction and experimental validation of functional properties of K1-xNaxNbO3-based piezoelectric ceramics

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  22. Materials Development and Potential Applications of Ceramics: New Opportunities and Challenges

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  23. Thermal conductivity prediction of sintered reaction bonded silicon nitride ceramics using a machine learning approach based on process conditions

    Ceramics International · 2023-12-19

    Ryoichi Furushima, Yuki Nakashima, You Ya Zhou, Kiyoshi Hirao, Tatsuki Ohji, Manabu Fukushima

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  24. From Graph Machine Learning to Furnaces: Permittivity Exploring of Dielectric Ceramics

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  25. Improved Arithmetic Optimization Algorithm with Multi-Strategy Fusion Mechanism and Its Application in Engineering Design

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  26. Machine learning enhanced prediction of permittivity of spinel microwave dielectric ceramics compared to traditional C-M calculation

    Modelling and Simulation in Materials Science and Engineering · 2024-01-16

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  27. An Automated Machine Learning Approach to Inkjet Printed Component Analysis: A Step Toward Smart Additive Manufacturing

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  28. Multilayer artificial intelligence for thermal-conductivity prediction of silicon nitride ceramics from powder processing conditions and predicted densities

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  30. Optimizing a machine learning design of dielectric properties in lead-free piezoelectric ceramics

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  32. AI for dielectric capacitors

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  33. Discovering ABO3-type perovskite with different dielectric constants via intelligent optimization algorithm

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  34. Structure and microwave dielectric characteristics of (Ba,Sr,Ca)HfO3 ceramics

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  35. Machine learning assisted Q×f value prediction of ABO4-type microwave dielectric ceramics

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  36. A strategy for accurate prediction of dielectric permittivity and dielectric strength in polyimide

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  37. Microstructural basis of AI predictions for material properties: A case study of silicon nitride ceramics using t ‐SNE

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  38. Advancements in microwave dielectric ceramics with K20 for 5G/6G communication systems: a review

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  39. Nondestructive Electrical Permittivity Detection Using ANN-Enhanced Microstrip Sensors

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  40. Exceptionally optimized millimeter-wave properties of cordierite-based materials via innovative processing and predictive analytics

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  41. Interpretable model of dielectric constant for rational design of microwave dielectric materials: a machine learning study

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  42. Multiobjective optimization of dielectric, thermal, and mechanical properties of inorganic glasses utilizing explainable machine learning and genetic algorithm

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  43. Data-driven analysis and visualization of dielectric properties curated from scientific literature

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  44. A novel hybrid 2D-FDTD-PML and Nelder–Mead methods for estimating liquid complex permittivity using a rectangular waveguide

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  45. Deep learning enhanced prediction of microwave dielectric constant of spinel ceramics eliminating manual feature engineering

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  46. Compositionally Complex Oxide Dielectrics for Microwave Applications: Current Status and Future Trends: A Review

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  47. Impact of Cu2+ doping on the structure and electromagnetic properties of Zn3B2O6 ceramics

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  48. Accelerating Low-k Dielectric Material Discovery: From Graph Machine Learning to Synthesis

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  49. Prediction of piezoelectric properties of NBT-based ceramics based on deep neural networks

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  50. A review on the applications of machine learning in biomaterials, biomechanics, and biomanufacturing for tissue engineering

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