Results 101 to 110 of about 3,744,625 (291)
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
Adaptive Memory Saving Strategy in Shielding Calculation of RMC [PDF]
EPJ Web of ConferencesRMC(Reactor Monte Carlo) is a Monte Carlo simulation software used in reactor design and has been verified by different benchmarks. The former data structure and algorithm have been optimized for criticality and burn-up calculation making it inconvenient
Hu Yingzhe +5 more
doaj +1 more source
Advanced Materials, EarlyView.Anion‐exchange doping of conjugated polymers is an effective way to achieve high conductivities. Here, we report over 2000 S cm−1 electrical conductivity for doped P(g3BTTT). In addition, we show that P(g3BTTT) sustains exceptionally high doping levels without any drop in the charge mobility.
Basil Hunger +14 more
wiley +1 more source
Advances in Mechanical Engineering, 2017 Uncertainty-based design and optimization is becoming one of the research focuses for high safety of complex engineering systems. Evaluating failure probability is essential and necessary in uncertainty-based design and optimization. Reliability analysis
Rong Yuan +4 more
doaj +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 +3 more
wiley +1 more source
The valuation of exotic barrier options and American options using Monte Carlo simulation [PDF]
Monte Carlo simulation is a widely used numerical method for valuing financial derivatives. It can be used to value high-dimensional options or complex path-dependent options.
Chirayukool, Pokpong
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Geodesic Monte Carlo on Embedded Manifolds [PDF]
, 2013 Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows
Simon Byrne +5 more
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Emergent Spin Supersolids in Frustrated Quantum Materials
Advanced Materials, EarlyView.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
A Method for Estimating Annual Energy Production Using Monte Carlo Wind Speed Simulation
Energies, 2016 A novel Monte Carlo (MC) approach is proposed for the simulation of wind speed samples to assess the wind energy production potential of a site. The Monte Carlo approach is based on historical wind speed data and reserves the effect of autocorrelation ...
Birgir Hrafnkelsson +2 more
doaj +1 more source
Multilevel Monte Carlo simulation in options pricing [PDF]
, 2014 >Magister Scientiae - MScIn Monte Carlo path simulations, which are used extensively in computational -finance, one is interested in the expected value of a quantity which is a functional of the solution to a stochastic differential equation [M.B. Giles,
Kazeem, Funmilayo Eniola
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