Results 131 to 140 of about 74,247 (264)

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

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

Comparing the Performances of Support Vector Machines and Artificial Neural Networks for Predicting Coronary Artery Diseases: A Cross-Sectional Study. [PDF]

Cardiol Res Pract
Shariatnia S, Rajabi A, Ziaratban M, Salehi A, Vakili M.   +4 more
europepmc   +1 more source

Deep learning and support vector machines for transcription start site identification. [PDF]

PeerJ Comput Sci, 2023
Barbero-Aparicio JA, Olivares-Gil A, Díez-Pastor JF, García-Osorio C.   +3 more
europepmc   +1 more source

Lead Halide Perovskite Photoelectrocatalysis

Advanced Materials, EarlyView.
Lead halide perovskite semiconductors have emerged as highly promising materials for solar fuel and chemical synthesis. This perspective discusses advances made in the rational photoelectrode design to improve solar‐to‐chemical conversion, product scope, and scalability.
Virgil Andrei
wiley   +1 more source

Prediction model for frailty risk in ischemic stroke patients: Application and validation of support vector machines and nomograms. [PDF]

Medicine (Baltimore)
Kang YL, Kong JT, Tian H.
europepmc   +1 more source

Retracted: Design of a Regional Economic Forecasting Model Using Optimal Nonlinear Support Vector Machines. [PDF]

Comput Intell Neurosci, 2023
Neuroscience CIA.
europepmc   +1 more source

Space‐Time Coding Conformal Metasurfaces for Multifrequency Beam Steering and Shaping

Advanced Materials, EarlyView.
Space‐time coding conformal metasurfaces enable dynamic wave control on curved surfaces by combining programmable spatial patterns with temporal modulation. This study shows that a single conformal aperture can independently manipulate multiple frequency components, achieving multifunctional beam shaping and steering, with implications for ...
Filippo Pepe, Lei Zhang, Yi Ning Zheng, Xiao Qing Chen, Ivan Iudice, Giuseppe Castaldi, Marco Di Renzo, Tie Jun Cui, Vincenzo Galdi   +8 more
wiley   +1 more source

PET-TURTLE: Deep Unsupervised Support Vector Machines for Imbalanced Data Clusters. [PDF]

IEEE Signal Process Lett
Salazar Cavazos J.
europepmc   +1 more source

Field‐Programmed Anisotropy in Magneto‐Piezoelectric Composites for Material‐Encoded Mechanoperception

Advanced Materials, EarlyView.
Field‐programmed anisotropy imparts material‐level intelligence to soft composites. Magnetic torque dynamics drive magneto‐piezoelectric nanowires from random dispersion into deterministic axial alignment. The resulting hierarchical percolation networks confine electromechanical coupling to specific axes and intrinsically decouple superposed force ...
Yubin Kim, Yumin Kwon, Dabin Kim, Minsun Oh, Jin Young Jung, Dongyeong Gim, Kootak Hong, Jun Yeon Hwang, Sang‐Woo Kim, Minjeong Ha   +9 more
wiley   +1 more source