Results 191 to 200 of about 61,380 (270)
Gas–solid interface‐assisted growth strategies have unlocked precise control over crystal structure, morphology, dimension, and molecular packing. The obtained organic semiconductor single crystals represent the ideal candidates for high‐performance organic optoelectronic devices.
Tingyi Yan +8 more
wiley +1 more source
Thermodynamic Operations and Entropy Considerations for a Ring-of-Charge Oscillator System. [PDF]
Cole DC.
europepmc +1 more source
A Comprehensive Review of AI‐Powered Energy Systems
The role of Artificial Intelligence (AI) in developing next‐generation energy systems is getting more day by day. Therefore, incorporating AI enables real‐time decision‐making and advanced grid management, which are essential for optimizing the use of intermittent renewable sources like wind and solar power.
Armin Razmjoo +5 more
wiley +1 more source
Entropy Bathtub for Living Systems: A Markovian Perspective. [PDF]
Fornalski KW.
europepmc +1 more source
Wide‐Bandgap Semiconductor‐Based Neuromorphic Computing
Wide‐bandgap semiconductors enable robust, low‐power neuromorphic devices for extreme environments. This review outlines material advantages, device physics, integration, and future directions for next‐generation brain‐inspired computing. ABSTRACT Neuromorphic computing has emerged as a promising paradigm to overcome the energy inefficiency and data ...
Hongyu Tang +6 more
wiley +1 more source
The constrained disorder principle accounts for quantum effects in biological systems. [PDF]
Ilan Y.
europepmc +1 more source
The conventional “local activation–global inhibition” (LAGI) models utilize mean‐field averaging inhibition to suppress distant activations. As the inhibition diminishes with distance, LAGI models struggle to achieve robust single‐axis polarity in large systems.
Chin‐Lin Guo, Chiao‐Yu Tseng
wiley +1 more source
A Variational Formulation for Irreversible Thermodynamics with Path Dependence. [PDF]
Ren H.
europepmc +1 more source
This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig +7 more
wiley +1 more source
Exploring Neurofunctional Phase Transition Patterns in Autism Spectrum Disorder via Thermodynamics Parameters. [PDF]
Qin D, Chen Y, Kuruoglu EE.
europepmc +1 more source

