Results 131 to 140 of about 907,345 (263)

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin   +7 more
wiley   +1 more source

Quantifying Evolving Defect Parameters in Metal Halide Perovskites via the Measurement and Modeling of Power‐Dependent Transient Photoluminescence

open access: yesAdvanced Energy Materials, EarlyView.
ABSTRACT Dynamic photoinduced defect states in metal halide perovskites (MHPs) critically govern the non‐equilibrium photophysics, metastability, and long‐term performance of optoelectronic devices, such as solar cells. This metastability is evident in steady‐state photoluminescence experiments, where the amplitudes increase or decrease depending on ...
Maxim Simmonds   +6 more
wiley   +1 more source

BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation. [PDF]

open access: yesBMC Bioinformatics, 2022
Yu WY   +6 more
europepmc   +1 more source

Roadmap for High‐Throughput Ceramic Materials Synthesis and Discovery for Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This work examines ceramic synthesis through the lens of high‐throughput synthesis and optimization, identifying opportunities for faster, adaptable routes. It emphasizes flexible liquid precursor–to–solid film methods over slower solid‐state approaches and highlights computer‐aided decision making to optimize both material properties and device ...
Jesse J. Hinricher   +10 more
wiley   +1 more source

Inversion of the Impedance Response Towards Physical Parameter Extraction Using Interpretable Machine Learning

open access: yesAdvanced Energy Materials, EarlyView.
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil   +4 more
wiley   +1 more source

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