Results 121 to 130 of about 1,412,151 (261)

The Mathematical Abstraction Theory, The Fundamentals for Knowledge Representation and Self-Evolving Autonomous Problem Solving Systems

, 2014
Seppo Ilari Tirri
openalex   +2 more sources

Bright and Stable Electrochemiluminescence by Heterobimetallic IrIII‐MI (MI = CuI, AuI) Complexes

Advanced Optical Materials, EarlyView.
Bright and stable electrochemiluminescence (ECL) of a new class of heterobimetallic ionic transition metal complexes is triggered in the presence of the coreactant n‐tri propylamine (TPrA) upon highly energetic electron transfer (eT). A quantum efficiency (ΦECL) up to six‐fold higher than that of benchmark tris‐(2,2′‐bipyridyl) ruthenium(II) is ...
Mattia Reato, Beatrice Polido, Anna Bonfiglio, Giulia Moro, Vincent César, Stéphane Bellemin‐Laponnaz, Alessandro Alla, Neso Sojic, Matteo Mauro, Federico Polo   +9 more
wiley   +1 more source

A novel fractal fractional mathematical model for HIV/AIDS transmission stability and sensitivity with numerical analysis. [PDF]

Sci Rep
Khan M, Khan N, Ullah I, Shah K, Abdeljawad T, Abdalla B.   +5 more
europepmc   +1 more source

Chemical AI in the Limelight: The Contribution of Photochromic Materials and Oscillatory Chemical Reactions

Advanced Optical Materials, EarlyView.
Photochromic compounds are versatile ingredients for the development of Chemical AI. When they are embedded in a tight microenvironment, they become Markov blankets. They are also valuable for processing Boolean and Fuzzy logic. They contribute to neuromorphic engineering in wetware based on opto‐chemical signals exchanged with oscillatory chemical ...
Pier Luigi Gentili
wiley   +1 more source

Mathematical study of silicate and oxide networks through Revan topological descriptors for exploring molecular complexity and connectivity. [PDF]

Sci Rep
Zhang Q, Ahmad Z, Ullah A, Hamed YS, Saleem M, Belay MB.   +5 more
europepmc   +1 more source

Exploring the Role of Artificial Intelligence in Precision Photonics: A Case Study on Deep Neural Network‐Based fs Laser Pulsed Parameter Estimation for MoOx Formation

Advanced Photonics Research, EarlyView.
Ultrafast pulsed laser technology enables precise material processing. This study examines molybdenum oxide formation under varying laser parameters. A dataset of 187 samples is generated, and eight deep neural networks (DNNs) with different architectures are trained. Models are validated using three learning rates and evaluated with mean squared error,
Jose R. Paredes‐Miguel, Miroslava Cano‐Lara, Andres A. Garcia‐Granada, Andres Espinal, Marcos J. Villaseñor‐Aguilar, Leonardo Martinez‐Jimenez, Horacio Rostro‐Gonzalez   +6 more
wiley   +1 more source

Expected values of topological descriptors for possible kink chains of type ₂ ⊤ 2 . [PDF]

Front Chem
Chen R, Razzaque A, Khalil M, Kanwal S, Noor S, Nazir R.   +5 more
europepmc   +1 more source

Local Tuning of the Epsilon‐Near‐Zero Condition in Hybrid Silicon Waveguides Using Reactive Laser Annealing

Advanced Photonics Research, EarlyView.
This work demonstrates the use of reactive laser annealing to selectively tune the epsilon‐near‐zero condition of tin‐doped indium oxide patches integrated in silicon waveguides. This postgrowth annealing technique enables flexible control over the optical constants of transparent conducting oxides (TCOs) at critical telecom wavelengths, paving the way
Juan Navarro‐Arenas, Thomas M. Howe, Jorge Parra, Demosthenes C. Koutsogeorgis, James A. Hillier, Nikolaos Kalfagiannis, Pablo Sanchis   +6 more
wiley   +1 more source

Fuzzy and crisp computational analysis of certain graphs structures via machine learning techniques. [PDF]

Sci Rep
Mufti ZS, AlQadi H, Tabraiz A, Hanif MF, Fiidow MA.   +4 more
europepmc   +1 more source

Multiple Incoherent Deconvolutions for Improving the Image Resolution of Diffraction‐Limited Imaging Systems

Advanced Photonics Research, EarlyView.
Multiple incoherent nonlinear deconvolutions (MIND) has extended dimension for optimization that provides a better solution than Wiener deconvolution and nonlinear reconstruction. MIND minimizes deconvolution noise by averaging over multiple deconvolutions each with different system aperture that effectively enhances the resolution.
Jawahar Prabhakar Desai, Vijayakumar Anand, Joseph Rosen   +2 more
wiley   +1 more source