activity
20242026
most citedLarge Language Model-Guided Prediction Toward Quantum Materials Synthesis

3 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2026

Quasicrystals are Functionally Graded Materials

Michael J. Landry, Dominic Bollettieri, Akhil Sadam +2

Quasicrystals exhibit long-range order without translational periodicity, posing challenges to compute their electronic properties. Here we show that a quasicrystal can be represen…

cond-mat.mtrl-sci2026

Agentic inverse design of spatially programmed materials

Denisse Córdova Carrizales, Abhijatmedhi Chotrattanapituk, L. Dagny Davis +4

Spatially programmed functional materials, from functionally graded alloys and metamaterials to quantum superlattices, use their spatial structure to tailor physical properties. Ho…

cond-mat.mtrl-sci2025

AI-Driven Defect Engineering for Advanced Thermoelectric Materials

Chu-Liang Fu, Mouyang Cheng, Nguyen Tuan Hung +7

Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-off…

cond-mat.mtrl-sci2024

Quantum Theory of X-ray Photon Correlation Spectroscopy

Phum Siriviboon, Chu-Liang Fu, Michael Landry +4

Characterizing quantum materials is essential for understanding their microscopic interactions and advancing quantum technology. X-ray photon correlation spectroscopy (XPCS) with c…

cond-mat.mtrl-sci2024★ 3 cited

Large Language Model-Guided Prediction Toward Quantum Materials Synthesis

Ryotaro Okabe, Zack West, Abhijatmedhi Chotrattanapituk +5

The synthesis of inorganic crystalline materials is essential for modern technology, especially in quantum materials development. However, designing efficient synthesis workflows r…