Tag

Materials Design

All articles tagged with #materials design

technology5 hours ago•4 min saved

Theory-guided design accelerates solar-fuel catalysts from polyheptazine imides

Researchers developed and validated a reproducible theory based on many-body perturbation theory to predict how different metal ions affect the structure, band gaps, and light absorption of polyheptazine imides, testing 53 ions and eight synthesized materials; the results, confirmed by measurements of hydrogen peroxide production, enable faster, targeted design of solar-to-chemical catalysts for water splitting and CO2 reduction.

via ScienceDaily|

#carbon-nitride #many-body-perturbation-theory #materials-design

physics2 years ago•6 min saved

"Revolutionizing Two-Dimensional Solids: Active Particles Break Barriers"

Active particles can form two-dimensional solids with long-range crystalline order and giant spontaneous deformations, which differ from those formed by nonmotile particles. These active systems exhibit quasi-long-range positional order and true long-range orientational order, similar to equilibrium solids. The power-law exponents describing the positional order in active systems cover a wide range, reaching values as high as 20. Understanding the interplay between order and fluctuations in active solids is crucial for integrating active elements into materials and fabrication processes.

via Physics|

#active-particles #crystal-structures #equilibrium

science-and-technology2 years ago•3 min saved

"Revolutionizing Materials Design: Generative Neural Networks for Structure Prediction"

Recent advancements in structural feature representations and generative neural networks have the potential to efficiently predict stable crystal structures, enabling the design of solid-state crystalline materials with desired properties. Crystal structure prediction (CSP) plays a crucial role in discovering stable and metastable structures for materials of unknown structure. Efficient optimization techniques, such as evolutionary algorithms and particle swarm optimization, have led to the discovery of various new materials. The use of generative adversarial networks and Euclidean neural networks shows promise in learning and discovering crystallographic structures.

via Nature.com|

#computational-science #crystal-structures #generative-neural-networks