Non-volatile tunable optics by design: from chalcogenide phase-change materials to device structures

D Wang, L Zhao, S Yu, X Shen, JJ Wang, C Hu… - Materials Today, 2023 - Elsevier
Integration of chalcogenide phase-change materials (PCMs) with planar multilayer
structures, metasurfaces, waveguides and photonic integrated circuits has sparked …

Glass formulation and composition optimization with property models: A review

X Lu, JD Vienna, J Du - Journal of the American Ceramic …, 2024 - Wiley Online Library
Glass is a versatile material with a remarkable history and many practical applications. It
plays a critical role in our everyday lives, the advancement of science, and the development …

Glass hardness: Predicting composition and load effects via symbolic reasoning-informed machine learning

S Mannan, M Zaki, S Bishnoi, DR Cassar, J Jiusti… - Acta Materialia, 2023 - Elsevier
Glass hardness varies in a non-linear fashion with the chemical composition and applied
load, a phenomenon known as the indentation size effect (ISE), which is challenging to …

Machine learning-assisted MD simulation of melting in superheated AlCu validates the Classical Nucleation Theory

AO Tipeev, RE Ryltsev, NM Chtchelkatchev… - Journal of Molecular …, 2023 - Elsevier
The validity of the Classical Nucleation Theory (CNT), the standard tool for describing and
predicting nucleation kinetics in metastable systems, has been under scrutiny for almost a …

[HTML][HTML] Predicting the stacking fault energy in FCC high-entropy alloys based on data-driven machine learning

X Zhang, R Dong, Q Guo, H Hou, Y Zhao - Journal of Materials Research …, 2023 - Elsevier
The properties of high-entropy alloys (HEAs) depend primarily on the composition and
content of elements. However, getting the optimal composition of alloying elements through …

Predicting the anion conductivities and alkaline stabilities of anion conducting membrane polymeric materials: development of explainable machine learning models

YK Phua, T Fujigaya, K Kato - Science and Technology of …, 2023 - Taylor & Francis
Anion exchange membranes (AEMs) are core components in fuel cells and water
electrolyzers, which are crucial to realize a sustainable hydrogen society. The low anion …

Accelerated design of chalcogenide glasses through interpretable machine learning for composition–property relationships

S Singla, S Mannan, M Zaki… - Journal of Physics …, 2023 - iopscience.iop.org
Chalcogenide glasses (ChGs) possess various outstanding properties enabling essential
applications, such as optical discs, infrared cameras, and thermal imaging systems. Despite …

Predicting spectroscopic properties of quaternary phosphate laser glasses

S Dong, W Wang, Y Jia, Q Zhang - Journal of the American …, 2024 - Wiley Online Library
Quantitative composition‐structure‐property (C–S–P) relationship analysis is a promising
approach to correlate structural features with properties of glasses that have complex …

[HTML][HTML] Design of a homologous series of molecular glassformers

SE Wolf, T Liu, S Govind, H Zhao, G Huang… - The Journal of …, 2021 - pubs.aip.org
We design and synthesize a set of homologous organic molecules by taking advantage of
facile and tailorable Suzuki cross coupling reactions to produce triarylbenzene derivatives …

Concurring effect of doping and composition on the thermodynamic properties of amorphous GexSe1-x alloys

F Tavanti, A Calzolari - Acta Materialia, 2024 - Elsevier
Chalcogenide materials are attracting growing attention for their ability to switch between
different electrical states in response to temperature or current changes. In particular …