Results 211 to 220 of about 82,480 (289)

Copper Single‐Atom Decorated Microfibrous Catalysts for Continuous‐Flow Reduction of Nitroarenes

open access: yesAdvanced Functional Materials, Volume 36, Issue 12, 9 February 2026.
Herein, a Cu‐single‐atom decorated, microfibrous catalyst (Cu1/CMF) is fabricated for chemoselective reduction of nitroarenes, demonstrating a superior processing capacity of 1.92 mmol mgcat−1 h−1 and superior durability (≥ 25 cycles) in a continuous‐flow manner.
Jiahan Zhao   +12 more
wiley   +1 more source

Advanced Ceramics in Aerospace and Defense: The Interrelationship between Traditional and Additive Manufacturing Approaches

open access: yesAdvanced Materials Technologies, Volume 11, Issue 3, 5 February 2026.
Additive manufacturing revolutionizes production by enabling on‐demand, customized, and sustainable manufacturing with streamlined supply chains. While metal and polymer AM are well‐established, advanced ceramic AM is rapidly emerging, overcoming traditional material challenges.
Kateryna Oleksandrivna Shvydyuk   +2 more
wiley   +1 more source

Molecular Layer Deposited Aluminum‐Based Hybrid Resist for High‐Resolution Nanolithography and Direct Ultra‐High Aspect Ratio Pattern Transfer

open access: yesAdvanced Materials Technologies, Volume 11, Issue 3, 5 February 2026.
This study demonstrates an aluminum‐based hybrid photoresist synthesized via molecular layer deposition (MLD) using trimethylaluminum and hydroquinone. The resist achieves sub‐20 nm resolution and virtually infinite silicon etch selectivity, enabling 40 nm‐wide, micrometer‐tall nanostructures.
Won‐Il Lee   +8 more
wiley   +1 more source

Dynamic activation catalysts for CO<sub>2</sub> hydrogenation. [PDF]

open access: yesNat Commun
Zhang Z   +11 more
europepmc   +1 more source

A Machine Learning‐Driven Pore‐Scale Network Model Coupling Reaction Kinetics and Interparticle Transport for Catalytic Process Design

open access: yesAdvanced Science, Volume 13, Issue 8, 9 February 2026.
Designing catalytic processes in porous reactors requires resolving coupled multiscale reaction–transport phenomena. We develop a machine‐learning‐accelerated pore‐scale dual‐network model with kinetics (DNMK), which captures reaction kinetics, pore‐scale transport, and reactor‐level behavior.
Ming‐Liang Qu   +10 more
wiley   +1 more source

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