Results 201 to 210 of about 57,852 (256)

Recent Progress in the Phase‐Controlled Synthesis of Ruthenium Nanocrystals for Catalytic Applications

Advanced Materials, EarlyView.
Template effect and kinetic control enable crystal‐phase engineering of Ru nanocrystals, granting access to either metastable fcc‐Ru or stable hcp‐Ru with distinct surface structures, thermal stabilities, and catalytic behaviors. Moreover, the hcp‐Ru can further serve as an epitaxial template to direct Pd and Rh nanocrystals into the metastable hcp ...
Jianlong He, Zhiqi Wang, Jiaqi Guan, Younan Xia   +3 more
wiley   +1 more source

MetaXVP: an interpretable machine learning framework for deep insight into variant pathogenicity and VUS classification. [PDF]

Sci Rep
Dehghan Tezerjani M, Sehhati M, Tabatabaiefar MA.   +2 more
europepmc   +1 more source

Large‐Scale Determination of Frontier Orbital Energies of Disordered Small‐Molecule Organic Semiconductors Using Exciplex Emission Spectra

Advanced Materials, EarlyView.
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald, Hiroki Tomita, Giacomo Cotelli, Louka L. Brüll, Nanno G. de Rooij, Lucas R.L. Norg, Milo Clément, Reinder Coehoorn   +7 more
wiley   +1 more source

Interpretable Machine Learning for Predicting Splitting Strength of Asphalt Concrete: Insights from SHAP Analysis. [PDF]

Materials (Basel)
Xing J, Tan X, Li Y, Jin D, Guo P, Wang Y, Niu H.   +6 more
europepmc   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Interpretable machine learning for identifying adolescent obesity risk and identifying key determinants. [PDF]

Front Public Health
Huang L, Chen J.
europepmc   +1 more source

Electrical Resistivity Change Upon Crystallization as a Robust Descriptor for Metallic Glass Forming Ability

Advanced Materials, EarlyView.
Electrical resistivity change upon annealing is introduced as a rapid descriptor for identifying high glass‐forming ability in metallic glasses. High‐throughput combinatorial thin‐film libraries reveal that compositions exhibiting small resistivity changes correspond to sluggish crystallization behavior and known bulk metallic glass regions, enabling ...
Haechan Jo, Hongxi Duan, Mingxing Li, Liwei Hu, Yanhui Liu, Dongwoo Lee   +5 more
wiley   +1 more source

Interpretable machine learning for identifying ICU readmission risk in subgroups with probabilistic rules. [PDF]

J Am Med Inform Assoc
Yang L, van der Meijden SL, Arbous SM, van Leeuwen M.   +3 more
europepmc   +1 more source

Recent Advances in Ferrite‐Based Materials for Biomedical Applications: A Comprehensive Review

Advanced Materials, EarlyView.
Ferrite nanoplatforms are presented as tunable biomedical materials in which synthesis control, cation engineering, defect/morphology regulation, and surface functionalization govern structure–property–bioactivity relationships. These design strategies enable multifunctional applications including MRI contrast, magnetic hyperthermia, targeted drug ...
Pramod D. Mhase, Varsha C. Pujari, Akash V. Fulari, Sunil M. Patange, Sean Li, Danyang Wang, Sagar E. Shirsath   +6 more
wiley   +1 more source

Interpretable Machine Learning to Anticipate the Diagnostic Yield of EEG in the Emergency department. The EMINENCE study. [PDF]

J Med Syst
Scarpino M, Marra E, Liuzzi P, Piccardi B, Nazerian P, Sgrilli I, Mannini A, Nencioni A, Grippo A.   +8 more
europepmc   +1 more source