Sustainable Materials Design With Multi‐Modal Artificial Intelligence
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
Molecular blueprints for cleaner air: theoretical insights into Cu(i)-decorated heterocycles for greenhouse gas (CO/CO<sub>2</sub>/CH<sub>4</sub>) capture. [PDF]
Bag A, Roymahapatra G.
europepmc +1 more source
Phenomenology of the stream of thought: dissociable dynamic dimensions revealed through experience sampling. [PDF]
Sheth SKS +5 more
europepmc +1 more source
Hierarchical Embedded Sphere Model: An Interpretable ML-Guided Multiscale Descriptor Engineering Decodes OER Activity on TM@MO<sub>2</sub> Catalysts. [PDF]
Li Z +5 more
europepmc +1 more source
Experimental realization of dice-lattice flat band at the Fermi level in layered electride YCl. [PDF]
Geng S +17 more
europepmc +1 more source
Density functional theory-accelerated design of perovskite quantum dots: unlocking atomic-level control for next-generation optoelectronics and sensors. [PDF]
Al Omari RH +8 more
europepmc +1 more source
Transition-Metal Hydride Catalysis Meets Nitrenoid Transfer: Design Principles for Precision C-N Bond Formation. [PDF]
Lyu X, Choi H, Chang S.
europepmc +1 more source

