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Spectral descriptors for bulk metallic glasses based on the thermodynamics of competing crystalline phases
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Processing of Bulk Metallic Glass
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Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set
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Nucleation in Condensed Matter - Applications in Materials and Biology
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Bulk metallic glass formation in binary Cu-rich alloy series – Cu100−xZrx (x=34, 36, 38.2, 40 at.%) and mechanical properties of bulk Cu64Zr36 glass
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AFLOW: An automatic framework for high-throughput materials discovery
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Voronoi analysis of the structure of Cu–Zr and Ni–Zr metallic glasses
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Generalized Gradient Approximation Made Simple
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Bulk Glass-Forming Metallic Alloys: Science and Technology
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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On the Formation of Metallic Glass
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High-entropy non-covalent cyclic peptide glass
inferred← citeshttps://doi.org/10.1038/s41578-021-00340-wopenalex-snapshot
Machine learning for alloys
inferred← citeshttps://doi.org/10.1038/s41586-023-06786-yopenalex-snapshot
Disordered enthalpy–entropy descriptor for high-entropy ceramics discovery
inferred← citeshttps://doi.org/10.1038/s41598-018-36224-3openalex-snapshot
Probabilistic Assessment of Glass Forming Ability Rules for Metallic Glasses Aided by Automated Analysis of Phase Diagrams
inferred← citeshttps://doi.org/10.1038/s41598-024-53509-yopenalex-snapshot
Comprehensive characterization of the structure of Zr-based metallic glasses
inferred← citeshttps://doi.org/10.1038/s43246-025-00838-8openalex-snapshot
Surface-engineered nanostructured high-entropy alloys for advanced electrocatalysis
inferred← citeshttps://doi.org/10.1038/srep39917openalex-snapshot
Parametric Study of Amorphous High-Entropy Alloys formation from two New Perspectives: Atomic Radius Modification and Crystalline Structure of Alloying Elements
inferred← citeshttps://doi.org/10.1039/c6sc02199aopenalex-snapshot
Organised chaos: entropy in hybrid inorganic–organic systems and other materials
inferred← citeshttps://doi.org/10.1039/d3dd00082fopenalex-snapshot
Interpretable models for extrapolation in scientific machine learning
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Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
inferred← citeshttps://doi.org/10.1039/d5sm00697jopenalex-snapshot
Transitional patterns on a spherical surface: from scars to domain defects of mixed lattices
inferred← citeshttps://doi.org/10.1063/1.5098297openalex-snapshot
Nanocalorimetry: Exploring materials faster and smaller
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Metastable materials discovery in the age of large-scale computation
inferred← citeshttps://doi.org/10.1063/5.0093785openalex-snapshot
Understanding of glass-forming ability of Zr–Cu alloys from the perspective of vibrational entropy of crystalline phases
inferred← citeshttps://doi.org/10.1063/5.0144250openalex-snapshot
A perspective on metallic liquids and glasses
inferred← citeshttps://doi.org/10.1063/5.0162158openalex-snapshot
Experimental data management platform for data-driven investigation of combinatorial alloy thin films
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Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment
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Recent Advancements in Bulk Metallic Glasses and Their Applications: A Review
inferred← citeshttps://doi.org/10.1088/1361-648x/abba8dopenalex-snapshot
Screening potential topological insulators in half-Heusler compounds via compressed-sensing
inferred← citeshttps://doi.org/10.1088/1361-651x/ab2ebeopenalex-snapshot
Ab initio inversion of structure and the lattice dynamics of a metallic glass: the case of Pd 40 Ni 40 P 20
inferred← citeshttps://doi.org/10.1088/1402-4896/ac698aopenalex-snapshot
Force constant disorder in the Ni44Nb56 bulk metallic glass as observed by deep inelastic neutron scattering augmented by isotopic substitution
inferred← citeshttps://doi.org/10.1088/1674-1056/abc14fopenalex-snapshot
Internal friction behavior of Zr59Fe18Al10Ni10Nb3 metallic glass under different aging temperatures
inferred← citeshttps://doi.org/10.1088/2053-1591/aaf014openalex-snapshot
Effect of nanocrystalline process on microstructure of Zr-based metallic glass
inferred← citeshttps://doi.org/10.1088/2399-1984/ae19b0openalex-snapshot
The search for high-entropy fuel-cell catalysts using disorder descriptors
inferred← citeshttps://doi.org/10.1088/2516-1075/ac572fopenalex-snapshot
Roadmap on Machine learning in electronic structure
inferred← citeshttps://doi.org/10.1103/physrevb.96.064201openalex-snapshot
Analysis of the fragility of the Zr77Ni23 metallic glass based on low-temperature heat capacity measurements
inferred← citeshttps://doi.org/10.1103/physrevlett.123.015701openalex-snapshot
Percolated Strain Networks and Universal Scaling Properties of Strain Glasses
inferred← citeshttps://doi.org/10.1103/physrevmaterials.2.083802openalex-snapshot
SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates
inferred← citeshttps://doi.org/10.1103/physrevmaterials.3.063603openalex-snapshot
van der Waals forces stabilize low-energy polymorphism in B2O3 : Implications for the crystallization anomaly
inferred← citeshttps://doi.org/10.1103/physrevmaterials.4.105602openalex-snapshot
Glass formation in binary alloys with different atomic symmetries
inferred← citeshttps://doi.org/10.1103/physrevmaterials.5.105003openalex-snapshot
High-throughput crystal structure solution using prototypes
inferred← citeshttps://doi.org/10.1103/physrevmaterials.7.063801openalex-snapshot
Simulating high-entropy alloys at finite temperatures: An uncertainty-based approach
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AFLOW-SYM: platform for the complete, automatic and self-consistent symmetry analysis of crystals
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Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability
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Atomistic Simulation of Glasses and Amorphous Materials: Challenges and Opportunities for the Next Decade
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Novel phase diagram behavior and materials design in heterostructural semiconductor alloys
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Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments
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Unconventional grain growth suppression in oxygen-rich metal oxide nanoribbons
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The “glass transition” as a topological defect driven transition in a distribution of crystals and a prediction of a universal viscosity collapse
inferred← citeshttps://doi.org/10.1146/annurev-matsci-110519-094700openalex-snapshot
Machine Learning for Structural Materials
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On-the-fly segmentation approaches for x-ray diffraction datasets for metallic glasses
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Data-driven design of inorganic materials with the Automatic Flow Framework for Materials Discovery
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Interpretable Machine-Learning-Guided Composition Design and Experimental Validation of Atomized Fe–Si–B–C Amorphous Soft-Magnetic Powders
inferred← citeshttps://doi.org/10.2339/politeknik.1652973openalex-snapshot
Geçmişten Günümüze Kütlesel Metalik Camlar ve Yenilikçi Uygulamaları
inferred← citeshttps://doi.org/10.3390/coatings13101689openalex-snapshot
Distinctive Features and Fabrication Routes of Metallic-Glass Systems Designed for Different Engineering Applications: A Review
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Revealing Nanoindentation Size-Dependent Creep Behavior in a La-Based Metallic Glassy Film
inferred← citeshttps://doi.org/10.3390/pr10061203openalex-snapshot
A Review of the Preparation, Machining Performance, and Application of Fe-Based Amorphous Alloys
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Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
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Retracted: Development of Bulk Metallic Glass Matrix Composites (BMGMC) by Additive Manufacturing: Modelling and Simulation – A Review: Part B
inferred← citeshttps://doi.org/10.4236/eng.2018.104010openalex-snapshot
Probabilistic Modelling of Microstructural Evolution in Zr Based Bulk Metallic Glass Matrix Composites during Solidification in Additive Manufacturing
inferred← citeshttps://doi.org/10.4236/jeas.2018.82005openalex-snapshot
Modelling and Simulation of Solidification Phenomena during Additive Manufacturing of Bulk Metallic Glass Matrix Composites (BMGMC)—A Brief Review and Introduction of Technique
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Machine learning, phase stability, and disorder with the Automatic Flow Framework for Materials Discovery
inferred← citeshttps://doi.org/10.48550/arxiv.1902.00485openalex-snapshot
Metallic glasses for biodegradable implants
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Prediction of Reduced Glass Transition Temperature using Machine Learning
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The AFLOW Library of Crystallographic Prototypes: Part 4
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
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