Results 141 to 150 of about 12,156 (243)

Deep Learning‐Driven Discovery and Engineering of an Efficient PETase for Depolymerization and Detoxification of PET Microplastics Under Physiological Conditions

open access: yesAdvanced Science, EarlyView.
A deep learning–driven pipeline mining 246 million protein sequences uncovers AhPETase, an evolutionarily distinct PET hydrolase. Engineered variant AhPETaseM1 degrades post‐consumer PET microplastics under physiological conditions and reverses microplasticinduced cytotoxicity in human lung and colon cells, establishing enzymatic microplastic ...
Yuxuan Wang   +9 more
wiley   +1 more source

Stand Up and Educate Ourselves on Academic Freedom. [PDF]

open access: yesJ Grad Med Educ
van der Leeuw RM   +7 more
europepmc   +1 more source

Updatable Closed‐Form Evaluation of Arbitrarily Complex Multiport Network Connections

open access: yesAdvanced Electronic Materials, EarlyView.
The inverse design of electrically large wave devices often uses reduced‐order multiport models with discrete optimization, requiring many evaluations of complex interconnections between subsystems that differ only in a few blocks. This paper introduces a closed‐form framework enabling efficient Woodbury low‐rank updates of related, previous ...
Hugo Prod'homme, Philipp del Hougne
wiley   +1 more source

Enhanced Spin‐Reorientation Transition and Polarization in DyFeO3 Thin Films

open access: yesAdvanced Electronic Materials, EarlyView.
Epitaxial strain in antiferromagnetic orthoferrite thin films enhances known bulk properties into a parameter range that makes them more accessible for potential applications. We show that bulk polar properties move from 4 K towards room temperature and the magnetic field‐induced AFM to FM spin‐flip in the paramagnetic Dy lattice when applying small ...
Banani Biswas   +7 more
wiley   +1 more source

Sulfide‐Based Electrolytes for All‐Solid‐State Sodium Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This review covers the structural features and synthesis strategies of sulfide‐based solid electrolytes, as well as critical challenges related to conductivity, interfacial and moisture stability, and scaling‐up for practical application in Sodium‐based All Solid‐State Batteries.
Han Yang   +6 more
wiley   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

open access: yesAdvanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu   +6 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

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