Results 241 to 250 of about 11,467,392 (329)

When Poor Exciton Dissociation Limits Photocurrents in Organic Solar Cells: Why Low Offset Non‐Fullerene Acceptor Blends Can't Be Efficient

Advanced Materials, EarlyView.
The energetic offset between the donor and the acceptor components in organic photoactive layers is central to the tradeoff between photovoltage and photocurrent losses. This Perspective covers the most important issues surrounding this topic in non‐fullerene acceptor blends, from the difficulty of accurately determining state energies and driving ...
Dieter Neher, Manasi Pranav
wiley   +1 more source

Predicting PFAS Exposure Risks from Rural Private Wells Using Integrated Mechanistic and Machine-Learned Bayesian Network Models. [PDF]

Environ Sci Technol
Long HC, Warrier R, Ganta K, Mulhern R, Lillys T, Hoponick Redmon J, Gibson JM.   +6 more
europepmc   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Special Issue "Machine Learning Applications in Bioinformatics and Biomedicine: 3rd Edition". [PDF]

Int J Mol Sci
Lyu H.
europepmc   +1 more source

“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

A Visualization Analysis of Machine Learning Applications in Gas Adsorption Using Nanoporous Materials. [PDF]

Nanomaterials (Basel)
Zhong X, Liang X, Zhang H.
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 Approach to Ecologically Characterize Soil Carbon and Structure From Multi-Kingdom Microbiome, Texture and Climate. [PDF]

Mol Ecol
Jeanne T, Prunier J, Hogue R, Droit A.
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

Machine learning-based solar radiation prediction across heterogeneous climatic zones using NASA POWER data: a case study in Nigeria. [PDF]

Front Artif Intell
Faloye OT, Awotoye GT, Akinremi J, Olaleye OS, Oluwadare AO, Adeyeri OE, Laokhongthavorn L, Kamchoom V.   +7 more
europepmc   +1 more source