:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Nandal, Vickey, Beneš, Vít, Baláž, Pavel, Ryjáček, Jiří, Tesař, Karel
Format:	Preprint
Published:	2026
Subjects:	Materials Science
Online Access:	https://arxiv.org/abs/2604.19939
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dilute Zn alloying in biodegradable Mg wires: microstructure, mechanical performance, and degradation behavior
by: Ryjáček, Jiří, et al.
Published: (2026)

Predicting Grain Boundary Segregation in Magnesium Alloys: An Atomistically Informed Machine Learning Approach
by: Xie, Zhuocheng, et al.
Published: (2024)

MATAI: A Generalist Machine Learning Framework for Property Prediction and Inverse Design of Advanced Alloys
by: Deng, Yanchen, et al.
Published: (2025)

Accelerating Amorphous Alloy Discovery: Data-Driven Property Prediction via General-Purpose Machine Learning Interatomic Potential
by: Gong, Xuhe, et al.
Published: (2025)

Machine Learning Approach to Predict the Curie Temperature of Fe- and Pt-Based Alloys
by: Ponomarova, Svitlana, et al.
Published: (2025)

Analysis of Phase Formations and Mechanical Properties in Complex Concentrated Alloys by Machine Learning Approach
by: Xiong, Jie, et al.
Published: (2020)

Machine Learning Approach to Predict Curie Temperature in Binary Alloys
by: Ponomarova, Svitlana, et al.
Published: (2025)

Deep Learning Accelerated Phase Prediction of Refractory Multi-Principal Element Alloys
by: Shargh, A. K., et al.
Published: (2024)

From Quantum Annealing to Alloy Discovery: Towards Accelerated Design of High-Entropy Alloys
by: Ibarra-Hoyos, Diego, et al.
Published: (2025)

Interpretable Machine Learning for High-Strength High-Entropy Alloy Design
by: Bajpai, Anurag, et al.
Published: (2024)

AlloyBERT: Alloy Property Prediction with Large Language Models
by: Chaudhari, Akshat, et al.
Published: (2024)

First Principles Studies of Stacking Fault Energies in Ternary Magnesium Alloys
by: Qiu, Qiwen, et al.
Published: (2024)

Accelerating CALPHAD-based Phase Diagram Predictions in Complex Alloys Using Universal Machine Learning Potentials: Opportunities and Challenges
by: Zhu, Siya, et al.
Published: (2024)

Applications of Machine Learning in Polymer Materials: Property Prediction, Material Design, and Systematic Processes
by: Li, Hongtao Guo Shuai Li Shu
Published: (2025)

A Machine Learning Framework for Predicting Glass-Forming Ability in Ternary Alloy Systems
by: Mahmoudi, Fatemeh
Published: (2025)

Magnesium‐Based Biodegradable Alloy Materials for Bone Healing Application
by: Kena Dachasa, et al.
Published: (2024)

Machine Learning Potentials for Alloys: A Detailed Workflow to Predict Phase Diagrams and Benchmark Accuracy
by: Zhu, Siya, et al.
Published: (2025)

From Data to Alloys Predicting and Screening High Entropy Alloys for High Hardness Using Machine Learning
by: Bouri, Rahul, et al.
Published: (2025)

Machine Learning for Electrode Materials: Property Prediction via Composition
by: Wu, Hao, et al.
Published: (2026)

Delta Machine Learning for Predicting Dielectric Properties and Raman Spectra
by: Grumet, Manuel, et al.
Published: (2023)

Understanding Magnesium Dissolution through Machine Learn-ing Molecular Dynamics
by: Liu, Zhoulin, et al.
Published: (2025)

Physically Consistent Machine Learning for Melting Temperature Prediction of Refractory High-Entropy Alloys
by: Hasnain, Mohd
Published: (2026)

Predicting and Accelerating Nanomaterials Synthesis Using Machine Learning Featurization
by: Price, Christopher C., et al.
Published: (2024)

Plastic Work Partitioning During Slip- and Twinning-Dominated Deformation in AZ31B Magnesium Alloy
by: Maj, Michał, et al.
Published: (2025)

Harmonizing Microstructures and Enhancing Mechanical Resilience: Novel Powder Metallurgy Approach for Zn-Mg Alloys
by: Boukalova, Anna, et al.
Published: (2024)

AI-Driven Accelerated Discovery of Intercalation-type Cathode Materials for Magnesium Batteries
by: Chen, Wenjie, et al.
Published: (2024)

Benchmarking Universal Machine Learning Interatomic Potentials for Elastic Property Prediction
by: Gao, Pengfei, et al.
Published: (2025)

Discovery of High-Voltage Magnesium-Ion Cathodes using Machine Learning and First-Principles Calculations
by: Florida, Jhon Rogelnor A., et al.
Published: (2026)

Thermal conductivity of CdCr$_{2}$Se$_{4}$ ferromagnet at low temperatures: role of grain boundaries and porosity
by: Hejtmánek, Jiří, et al.
Published: (2026)

Decoding Complex Compositions in Topologically Close-Packed Nano-plates of Magnesium Alloys: A High-Throughput Route to Stable Precipitates
by: Bai, Junyuan, et al.
Published: (2023)

Machine Learning Prediction Models for Solid Electrolytes based on Lattice Dynamics Properties
by: Kim, Jiyeon, et al.
Published: (2024)

Machine Learning Interatomic Potentials for Million-Atom Simulations of Multicomponent Alloys
by: Shuang, Fei, et al.
Published: (2026)

Accelerated Prediction of Temperature-Dependent Lattice Thermal Conductivity via Ensembled Machine Learning Models
by: Paliwal, Piyush, et al.
Published: (2025)

Favorable band alignment for photocatalysis at the strontium germanate interface with silicon
by: Rauch, Tomáš, et al.
Published: (2022)

Uncertainty-Aware Machine-Learning Framework for Predicting Dislocation Plasticity and Stress-Strain Response in FCC Alloys
by: Luo, Jing, et al.
Published: (2025)

Generative Inversion for Property-Targeted Materials Design: Application to Shape Memory Alloys
by: Li, Cheng, et al.
Published: (2025)

Accelerated Design of Mechanically Hard Magnetically Soft High-entropy Alloys via Multi-objective Bayesian Optimization
by: Dai, Mian, et al.
Published: (2025)

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
by: Vuong, An, et al.
Published: (2026)

Descriptor and Graph-based Molecular Representations in Prediction of Copolymer Properties Using Machine Learning
by: Kazemi-Khasragh, Elaheh, et al.
Published: (2025)

Reexamining Machine Learning Models on Predicting Thermoelectric Properties
by: Ma, Chung T., et al.
Published: (2025)