Guest Editor(s)
Prof. Dr. Chia-Jyi Liu
Email: liucj@cc.ncue.edu.tw
Affiliation: Department of Physics, National Changhua University of Education, Changhua, Taiwan
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Research Interests: thermoelectric physics; chalcogenide-based energy materials; organic–inorganic hybrid thermoelectrics; interfacial engineering; solid-state chemistry; nanomaterials
Summary
Chalcogenide-based energy materials continue to attract strong attention because their tunable electronic structures, diverse bonding motifs, and intrinsically low lattice thermal conductivity make them highly promising for thermoelectrics, optoelectronics, and related energy-conversion technologies. This Special Issue will spotlight how artificial intelligence, data-driven screening, and interfacial engineering can accelerate the discovery and optimization of chalcogenide-based materials and devices. We particularly welcome contributions on AI-guided compositional design, interface-controlled transport, defect and microstructure engineering, organic–inorganic hybrid architectures, and advanced characterization/modeling of structure–property relationships.
The following are the suggested themes and are not limited to:
· AI-driven discovery of chalcogenide energy materials;
· interfacial engineering for phonon–charge decoupling;
· thermoelectric transport optimization in chalcogenides;
· hybrid and composite energy materials;
· machine learning for structure–property prediction;
· defect, phase, and microstructure control;
· advanced characterization and multiscale simulation of interfaces.
Keywords
AI-driven materials design, chalcogenides, thermoelectric materials, interfacial engineering, machine learning, hybrid energy materials, phonon transport, defect engineering; energy conversion
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