EverGlass Database

[EN] EVERGLASS DATABASE is a Python-based graphical application (Tkinter-based) designed to manage and visualize datasets related to glass properties. -Users can load CSV files containing chemical compositions, viscosity data, physical properties, and general thermal properties of glasses. -The software automatically recalculates missing chemical values (e.g., molar % from weight %) using an internal molar mass dictionary. -It provides interactive visualization of viscosity curves based on Vogel–Fulcher–Tammann (VFT) parameters (A, B, T₀), with real-time cursor tracking. -Data is displayed in organized tabs and tables, and users can export results to CSV. -The interface includes contextual help, an info viewer, and a logo-branded welcome screen.

Publication Details

Journal
DIGITAL.CSIC (Spanish National Research Council (CSIC))
Published
2025-09-01
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

EverGlass Database

DIGITAL.CSIC (Spanish National Research Council (CSIC))
Machine Learning in Materials Science
article

EverGlass Database

article en

Abstract

[EN] EVERGLASS DATABASE is a Python-based graphical application (Tkinter-based) designed to manage and visualize datasets related to glass properties. -Users can load CSV files containing chemical compositions, viscosity data, physical properties, and general thermal properties of glasses. -The software automatically recalculates missing chemical values (e.g., molar % from weight %) using an internal molar mass dictionary. -It provides interactive visualization of viscosity curves based on Vogel–Fulcher–Tammann (VFT) parameters (A, B, T₀), with real-time cursor tracking. -Data is displayed in organized tabs and tables, and users can export results to CSV. -The interface includes contextual help, an info viewer, and a logo-branded welcome screen.

DIGITAL.CSIC (Spanish National Research Council (CSIC))
Openalex Percentile: Top 50%
Machine Learning in Materials Science
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EverGlass Database · DIGITAL.CSIC (Spanish National Research Council (CSIC)) (2025) | TGRS Research Map | TGRS