Results 151 to 160 of about 1,008 (212)
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Cigarette smoke accelerates the aging of immune cells in the lung. By combining human single‐cell sequencing, cell culture, and mouse models, the authors show that the protein GEM drives mitochondrial damage and senescence in alveolar macrophages by suppressing SIRT3.
Jin Wang +8 more
wiley +1 more source
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren +8 more
wiley +1 more source
Polymorphic Superparaelectric Engineering Boosting Energy Storage Capacity in BaTiO3‐Based Ceramics
Herein, Ca2+ incorporation promotes the coexistence of CaTiO3‐/BaTiO3‐derived paraferroelectric states, stabilizing cubic‐orthorhombic‐tetragonal polymorphic superparaelectric phases. This minimizes polarization energy barriers, facilitating full polarization saturation without compromising efficiency.
Pan Liu +9 more
wiley +1 more source
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu +3 more
wiley +1 more source
Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu +5 more
wiley +1 more source
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan +8 more
wiley +1 more source
Superatom Distortion Induces Triferroicity and Spin Splitting in Two‐Dimensional Antiferromagnets
The incorporation of superatoms into a 2D square lattice induces symmetry breaking, thereby enabling concurrent coupling among magnetism, ferroelectricity, and ferroelasticity. This strategy achieves triferroic behavior—characterized by spin‐split antiferromagnetic ground states—and offers a viable pathway toward energy‐efficient spintronic devices ...
Zhen Gao +6 more
wiley +1 more source
We elucidate the key roles of metal p‐d orbital hybridization, excited‐state metal–ligand π‐interactions, and structural rotation in TADF of d10 CMA complexes. Introducing electron‐withdrawing or π‐extended ligand substituents weakens excited‐state metal‐ligand π‐interactions and improves kTADF, but may compromise emitter stability in device operation.
Shuo Xu +5 more
wiley +1 more source
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source

