Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Atomically Dispersed Nickel in Cerium Oxide Aerogel Catalysts Characterized Using Scanning Transmission Electron Microscopy and Spectroscopy. [PDF]
Sendgikoski K +7 more
europepmc +1 more source
Local strain effects on bandgap energy in flexible h-WO3 nanowires. [PDF]
Nekita S +7 more
europepmc +1 more source
Uncertainty-aware machine learning for core-loss background subtraction in EELS. [PDF]
van der Wielen B +4 more
europepmc +1 more source
Beyond structure: spectroscopic imaging in cryogenic electron microscopy. [PDF]
Kim J, Stach EA, Chang YW.
europepmc +1 more source
Partial nocturnal behaviour of giant mottled eels, Anguilla marmorata, in a small river, Amami-Oshima Island, Japan, from acoustic telemetry. [PDF]
Itakura H, Wakiya R.
europepmc +1 more source
Sanguinarine Alleviates the Adverse Effects of Excessive Dietary Histamine on Growth and Intestinal and Hepatic Health in Juvenile American Eels (<i>Anguilla rostrata</i>). [PDF]
Xu Y +5 more
europepmc +1 more source
Diamond Formation at Superlubric Sliding Interface. [PDF]
Wang Y +5 more
europepmc +1 more source
Emigration of silver eels (Anguilla anguilla L.) from the Great Masurian Lakes complex in the southeastern Baltic region. [PDF]
Bernaś R +4 more
europepmc +1 more source
Exciton dispersion fine structure and deep ultraviolet optical conductivity of freestanding two-dimensional h-BN. [PDF]
Hong J +9 more
europepmc +1 more source

