Results 111 to 120 of about 80,670 (263)
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley +1 more source
Bulk FePd2Te2 contains sparse interlayer Pd–Te covalent bonds, giving it unexpectedly low exfoliation energy and enabling van der Waals‐like exfoliation. Cleaving these bonds during exfoliation makes the monolayer magnetically distinct from the bulk: magnetic anisotropy energy increases, and the strain‐response coefficient of the magnetic moment ...
Huaiyuan Zhao +7 more
wiley +1 more source
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou +3 more
wiley +1 more source
Uncertainty‐Aware Deep Ensembles for Robust and Reliable Chemical Sensor Arrays
A reliability‐aware electronic nose is developed using photothermally anchored metal‐catalyst decorated metal oxide nanofiber sensor arrays combined with deep ensemble learning. Diverse catalytic nanofiber channels generate gas‐specific response patterns, enabling selective identification and quantification of sulfur‐containing gases.
Sungwoo Eo +5 more
wiley +1 more source
Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer
This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu +7 more
wiley +1 more source
Study on the Characteristics of MBN and MAE Signals in P92 Steel. [PDF]
Huang Z +6 more
europepmc +1 more source
Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao +4 more
wiley +1 more source
Impact of Salvadora persica aqueous extract on follicular development in female rats. [PDF]
Ghareeb SM +2 more
europepmc +1 more source
Correcting the apparent priming effect resolves systematic biases in Asian rice fertilizer nitrogen accounting. Net soil retention drops below 7%, while 48% of fertilizer escapes, inflicting US$98.53 billion in annual reactive‐nitrogen damages. High‐resolution mapping uncovers N‐risk archetypes across 42% of the rice area, delivering a spatially ...
Xiuyun Liu +5 more
wiley +1 more source
POET: A Software Suite for Mapping the Site-Specific Electronic Origins of Magnetic Anisotropy. [PDF]
Navrátil J, Błoński P.
europepmc +1 more source

