Results 261 to 270 of about 520,977 (330)

Predicting microbial community structure and temporal dynamics by using graph neural network models. [PDF]

open access: yesNat Commun
Andersen KS   +8 more
europepmc   +1 more source

Strategies to Enhance Ionic Conductivity of Na3Zr2Si2O12 Solid Electrolyte for Advanced Solid‐State Sodium Batteries

open access: yesCarbon Energy, EarlyView.
This review presents a comprehensive summary and discussion of some optimization strategies for enhancing room‐temperature ionic conductivity of Na3Zr2Si2PO12 (NZSP) solid electrolyte for solid‐state sodium batteries, including foreign‐ion doping or substitution, sintering behavior modulation, and regulation of chemical composition based on precursors.
Jiawen Hu   +5 more
wiley   +1 more source

Multiple Dimerization Modes in Thiocarboxylate Paddlewheel Complexes: A Comprehensive View of Energy Landscapes from DFT Calculations and Statistics

open access: yesChemistry – A European Journal, EarlyView.
Staggered, square, and heavily bent dimers occur in the five known solvatomorphs of paddlewheel (PW) complex [PtVO(SOCPh)4]. These and other structural motifs are well within energetic reach due to the shallow potential energy surface that guides dimerization and are included in a revised classification of available structural data on heterobimetallic ...
Olga Mironova   +3 more
wiley   +1 more source

Random forest regression for catalyst performance prediction and validation of tri‐reforming of methane (TRM)

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza   +3 more
wiley   +1 more source

Partial identification with categorical data and nonignorable missing outcomes

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Nonignorable missing outcomes are common in real‐world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may wish to forgo them in favour of partially identified models that narrow the set of a priori possible values to an identification region.
Daniel Daly‐Grafstein, Paul Gustafson
wiley   +1 more source

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