Results 201 to 210 of about 67,619 (257)

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Computational design of low-volatility lubricants for space using interpretable machine learning. [PDF]

J Cheminform
Miliate D, Martini A.
europepmc   +1 more source

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

An interpretable machine learning model for diabetic foot risk classification in patients with diabetes. [PDF]

Sci Rep
Hu X, Xi H, Fan Z, Zhu L, Shi J, Qian S, Qiu J, Li Y, Ding H.   +8 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

Development of an interpretable machine learning model for predicting in-hospital mortality in ICU patients with sepsis: a retrospective cohort study. [PDF]

Front Med (Lausanne)
Zhao T, Wen K, Han X, Tan R, Wang Y, Du Q.   +5 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

An interpretable machine-learning model for early prediction of acute kidney injury in polytrauma patients. [PDF]

Front Med (Lausanne)
He Y, Wang X, Huang J, Liu J.
europepmc   +1 more source

An interpretable machine learning framework for classifying human and machine translations across genres. [PDF]

Front Artif Intell
Fan L, Du H, Huang G.
europepmc   +1 more source