Results 281 to 290 of about 2,619,028 (337)

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

open access: yesAdvanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

Quantum Models of Consciousness from a Quantum Information Science Perspective. [PDF]

open access: yesEntropy (Basel)
Gassab L   +3 more
europepmc   +1 more source

Powder Metallurgy and Additive Manufacturing of High‐Nitrogen Alloyed FeCr(Si)N Stainless Steel

open access: yesAdvanced Engineering Materials, EarlyView.
The alloying element Nitrogen enhances stainless steel strength, corrosion resistance, and stabilizes austenite. This study develops austenitic FeCr(Si)N steel production via powder metallurgy. Fe20Cr and Si3N4 are hot isostatically pressed, creating an austenitic microstructure.
Louis Becker   +5 more
wiley   +1 more source

Motor Control Exercises and Their Design for Short-Term Pain Modulation in Patients with Pelvic Girdle Pain: A Narrative Review. [PDF]

open access: yesHealthcare (Basel)
Zitti M   +8 more
europepmc   +1 more source

Effective Field Theory for Low-Energy Two-Nucleon Systems

open access: green, 1997
Tae-Sun Park   +3 more
openalex   +2 more sources

Enhanced Fog Water Harvesting on Superhydrophobic Steel Meshes

open access: yesAdvanced Engineering Materials, EarlyView.
Fog harvesting using mesh designs offers a sustainable solution to water scarcity. This study highlights key considerations for fog harvesting research and develops a methodology for a standardized protocol reflecting fog characteristics and environmental conditions.
Pegah Sartipizadeh   +3 more
wiley   +1 more source

Machine Learning‐Guided Discovery of Factors Governing Deformation Twinning in Mg–Y Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
This study uses interpretable machine learning to identify key microstructural and processing parameters related to twinning in magnesium‐yttrium (Mg–Y) alloys. It is identified that using only grain size, grain orientation, and total applied strain, grains can be classified with 84% accuracy based on whether the grain contains a twin.
Peter Mastracco   +8 more
wiley   +1 more source

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