Search
22 articles for “DFT”
-
Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
-
Crystal Defects and Their Characterization in Modern Materials Science
Abstract: The physical and chemical properties of crystalline solids are fundamentally dictated by deviations from structural perfection, known as crystal defects. From the point-scale vacancies that drive diffusion to the planar boundaries that determine mechanical strength, defects serve as the primary "tuning knobs" in material design. This review provides a comprehensive examination of point, line, and planar defects, exploring their formation energetics and their role in plastic deformation via crystallographic slip. …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 15–19 Read article