Results 221 to 230 of about 17,314 (301)

Crystal structure of (dibenzo-21-crown-7)di-iodido-samarium(II) 1,2-di-meth-oxy-ethane hemisolvate. [PDF]

open access: yesActa Crystallogr E Crystallogr Commun
Wineinger HB, Sperling JM, Albrecht TE.
europepmc   +1 more source

RBMS1 Contributes to Early Arteriovenous Fistula Neointimal Remodeling Through Modulation of VSMC Phenotypic Responses

open access: yesAdvanced Science, EarlyView.
Postoperative arteriovenous fistulas exhibit increased RBMS1 in vascular smooth muscle cells (VSMCs). In experimental AVFs, RBMS1 overexpression aggravates, whereas deletion attenuates, neointimal hyperplasia. RBMS1 binds MPZL1 mRNA and promotes exon 5 skipping to generate MPZL1‐Δ5, which interacts with G3BP1 to activate AKT, driving VSMC proliferation,
Zongda Li   +14 more
wiley   +1 more source

Magnetoelectric Multiferroics for the Next‐Generation Ultralow‐Power Electronics

open access: yesAdvanced Science, EarlyView.
Magnetoelectric coupling provides a unifying route from electric‐field control of magnetic order to non‐volatile MeRAM, MESO logic, and emerging antiferromagnetic and magnonic devices. By connecting switching physics with device benchmarks, material platforms, and integration strategies, distinctive technological opportunities are identified alongside ...
Yang Liu   +13 more
wiley   +1 more source

Advances in Josephson Junction Materials and Processes Toward Practical Quantum Computing

open access: yesAdvanced Science, EarlyView.
Emerging materials for quantum computing, including crystalline materials, two‐dimensional van der Waals materials, two‐dimensional electron gas systems, ferromagnets, and unconventional (e.g., d‐wave) superconductors, offer opportunities to engineer next‐generation Josephson junctions.
Hyunseong Kim   +11 more
wiley   +1 more source

Pre‐Refinement Prediction of Dopant Site Occupancy in M‐Type Hexaferrites via Hierarchical and Uncertainty‐Aware Machine‐Learning

open access: yesAdvanced Science, EarlyView.
Refined data are extracted from CIF files to construct a hierarchical machine‐learning framework integrating sublattice classification, Fe‐site occupancy prediction, and reliability assessment. External validation yields 96% accuracy for sublattice classification and a macro mean absolute error of 0.0584 for Fe‐site prediction.
Dan Liu   +9 more
wiley   +1 more source

Rare Earth Elements in Testicular Function: Current Knowledge and Future Directions. [PDF]

open access: yesInt J Mol Sci
Santillo A   +5 more
europepmc   +1 more source

Steric‐Pressure‐Driven Topological Reconstruction for High‐Performance Zintl Phase Thermoelectrics with Machine‐Learning Validation

open access: yesAdvanced Science, EarlyView.
Synergistic Sr and Ag co‐doping drives steric‐pressure‐induced reconstruction from a 2D layered structure to a cross‐linked 3D framework in the Ca9‐xSrxZn4+y‐zAgzSb9 system, enhancing carrier mobility while maintaining a large Seebeck coefficient and doubling ZT to 0.73 at 873 K, with hybrid transfer machine learning further capturing the compositional
Siyeon Kim   +7 more
wiley   +1 more source

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