Results 201 to 210 of about 1,110,706 (305)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

REvolutionH-tl 2.0: A fast and robust tool for decoding evolutionary gene histories. [PDF]

open access: yesPLoS Comput Biol
Ramírez-Rafael JA   +8 more
europepmc   +1 more source

Polychip‐A High‐Throughput Droplet Microfluidics Platform for Interrogating Microbial Interactions

open access: yesAdvanced Science, EarlyView.
Polychip, a fully integrated droplet microfluidics platform, enables high‐throughput, single‐cell resolution screening of polymicrobial interactions. By seamlessly combining six automated microfluidics operations on a single chip, the system accelerates antimicrobial discovery by 11 to 14 times compared to traditional robotic methods.
Jeong Jae Han   +11 more
wiley   +1 more source

RNAi in the Rhizarian Phytopathogen Plasmodiophora brassicae: The Causal Agent of Clubroot Disease in Cruciferous Crops

open access: yesAdvanced Science, EarlyView.
This study uncovers an unusual RNAi pathway in the rhizarian pathogen Plasmodiophora brassicae. In the absence of Dicer, a Drosha‐like RNase III protein supports the biogenesis of predominant 21‐nt small RNAs, and two Argonaute proteins mediate small RNA‐guided silencing.
Xiong Zhang   +13 more
wiley   +1 more source

Phylo-Movies: animating phylogenetic trees from sliding-window analyses. [PDF]

open access: yesMol Biol Evol
Sakalli E   +3 more
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

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