Results 81 to 90 of about 483,459 (273)
Molecular doping of conjugated polymers is fundamentally constrained by thermodynamic phase behavior. This Perspective reframes doping efficiency and stability in terms of miscibility limits, binodals, and solvus boundaries, highlighting the role of effective interaction parameters and charge transfer.
Somayeh Kashani +10 more
wiley +1 more source
Numerical Study of Stainless Steel Pitting Process Based on the Lattice Boltzmann Method
The application of computers to numerical calculations has become an important means of studying corrosion problems, and in this work, the lattice Boltzmann method (LBM) was used to numerically simulate the pitting corrosion of stainless steel. The multi-
Jing Cui +3 more
doaj +1 more source
Direct numerical simulation of complex viscoelastic flows via fast lattice-Boltzmann solution of the Fokker–Planck equation [PDF]
Micro–macro simulations of polymeric solutions rely on the coupling between macroscopic conservation equations for the fluid flow and stochastic differential equations for kinetic viscoelastic models at the microscopic scale.
Izquierdo, S. +6 more
core +1 more source
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh +2 more
wiley +1 more source
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
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
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 +3 more
wiley +1 more source
Nonuniqueness of lattice Boltzmann schemes derived from finite difference methods
Recently, the construction of finite difference schemes from lattice Boltzmann schemes has been rigorously analyzed [Bellotti et al. (2022), Numer. Math. 152, pp. 1–40].
Eliane Kummer, Stephan Simonis
doaj +1 more source
Lattice Boltzmann simulation of droplet behaviour in microfluidic devices [PDF]
We developed a lattice Boltzmann model to investigate the droplet dynamics in microfluidic devices. In our model, a stress-free boundary condition was proposed to conserve the total mass of flow system and improve the numerical stability for flows with ...
Zhang, Yonghao, Liu, Haihu
core +3 more sources
Laser‐Assisted Phase Engineering of 2D MoS2 for Efficient Solution‐Processed Electronics
Here, local laser‐assisted phase transition from solution‐processed phase‐pure 1T′ to 2H MoS2 is shown to critically depend on the irradiation atmosphere. While processing in air leads to damaged insulating regions, inert conditions yield semiconducting 2H domains, enabling direct field‐effect transistor patterning with optimized lateral 1T′‐2H MoS2 ...
Anna Zhuravlova +10 more
wiley +1 more source
Emergent Spin Supersolids in Frustrated Quantum Materials
This review highlights developments in the study of spin super‐solids in frustrated quantum materials. Advanced experimental characterizations and computational studies enable a comprehensive understanding of the driving mechanisms of spin super‐solidity in various layered transition‐metal compounds, bridging materials, experiments, and theory aspects.
Yixuan Huang +2 more
wiley +1 more source

