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19912026
Showing 2022 · cond-mat.mtrl-sciShow all

30 papers · 2 filters

cond-mat.mtrl-sci2022★ 14 cited

Delamination-assisted ultrafast wrinkle formation in a freestanding film

Yifan Su, Alfred Zong, Anshul Kogar +6

The ability to synthesize and control two-dimensional (2D) crystals creates numerous opportunities for studying emergent states of matter and their novel functionalities. Freestand…

cond-mat.mtrl-sci2022★ 12 cited

Influence of local symmetry on lattice dynamics coupled to topological surface states

Jonathan A. Sobota, Samuel W. Teitelbaum, Yijing Huang +18

We investigate coupled electron-lattice dynamics in the topological insulator Bi2Te3 with time-resolved photoemission and time-resolved x-ray diffraction. It is well established th…

cond-mat.mtrl-sci2022★ 52 cited

Exciton lifetime and optical linewidth profile via exciton-phonon interactions: Theory and first-principles calculations for monolayer MoS

Y. -H. Chan, Jonah B. Haber, Mit H. Naik +4

Exciton dynamics dictate the evolution of photoexcited carriers in photovoltaic and optoelectronic devices. However, interpreting their experimental signatures is a challenging the…

cond-mat.mtrl-sci2022★ 6 cited

Automating Dislocation Characterization in 3D Dark Field X-ray Microscopy

Pin-Hua Huang, Ryan Coffee, Leora Dresselhaus-Marais

Mechanical properties in crystals are strongly correlated to the arrangement of 1D line defects, termed dislocations. Recently, Dark field X-ray Microscopy (DFXM) has emerged as a…

cond-mat.mtrl-sci2022★ 63 cited

Floquet engineering of strongly-driven excitons in monolayer tungsten disulfide

Yuki Kobayashi, Christian Heide, Amalya C. Johnson +4

Interactions of quantum materials with strong-laser fields can induce exotic nonequilibrium electronic states. Monolayer transition-metal dichalcogenides, a new class of direct-gap…

cond-mat.mtrl-sci2022★ 48 cited

Quantifying the performance of machine learning models in materials discovery

Christopher K. H. Borg, Eric S. Muckley, Clara Nyby +4

The predictive capabilities of machine learning (ML) models used in materials discovery are typically measured using simple statistics such as the root-mean-square error (RMSE) or…