Results 91 to 100 of about 12,571,794 (304)

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

Conversion of Monte Carlo Steps to Real Time for Grain Growth Simulation

Advances in Mathematical Physics, 2017
Monte Carlo (MC) technique is becoming a very effective simulation method for prediction and analysis of the grain growth kinetics at mesoscopic level.
N. Maazi
doaj   +1 more source

Multilevel Monte Carlo Methods [PDF]

, 2001
We study Monte Carlo approximations to high dimensional parameter dependent integrals. We survey the multilevel variance reduction technique introduced by the author in [4] and present extensions and new developments of it. The tools needed for the convergence analysis of vector-valued Monte Carlo methods are discussed, as well.
openaire   +1 more source

1T‐to‐2H Phase Evolution During Epitaxial Growth of Transition Metal Dichalcogenides

Advanced Materials, EarlyView.
During MOCVD growth of MoS2 and WSe2, a transient metallic 1T phase emerges in early, edge‐rich, chalcogen‐deficient domains and declines as the films ultimately coalesce as 2H material. Together, experiments and ReaxFF simulations link domain size, edge stoichiometry, and vacancies to this evolution.
Andrew R. Graves, Yiru Zhu, Matin Salimi Irdmusa, Nadire Nayir, Thomas V. Mc Knight, Chen Chen, Ke Wang, Adri C. T. van Duin, Joan M. Redwing   +8 more
wiley   +1 more source

Monte Carlo simulation of coherent effects in multiple scattering [PDF]

, 2005
Using a combination of the stochastic Monte Carlo technique and the iteration procedure of the solution to the Bethe-Salpeter equation, it has been shown that the simulation of the optical path of a photon packet undergoing an nth scattering event ...
Churmakov, D. Y., Greenhalgh, Douglas A., Meglinski, Igor V., Kuzmin, Vladimir L.   +3 more
core   +1 more source

Stochastic Assessment of Voltage Sags in Distribution Networks

Iranian Journal of Electrical and Electronic Engineering, 2008
This paper compares fault position and Monte Carlo methods as the most common methods in stochastic assessment of voltage sags. To compare their abilities, symmetrical and unsymmetrical faults with different probability distribution of fault positions ...
M. Aliakbar-Golkar, Y. Raisee-Gahrooyi
doaj  

Monte Carlo Option Princing

Lecturas de Economía, 2009
El método Monte Carlo se aplica a varios casos de valoración de opciones financieras. El método genera una buena aproximación al comparar su precisión con la de otros métodos numéricos.
Cecilia Maya
doaj   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

Hybrid Monte Carlo on Hilbert spaces [PDF]

, 2011
The Hybrid Monte Carlo (HMC) algorithm provides a framework for sampling from complex, high-dimensional target distributions. In contrast with standard Markov chain Monte Carlo (MCMC) algorithms, it generates nonlocal, nonsymmetric moves in the state ...
Beskos, A, Sanz-Serna, JM, Pinski, F. J., F.J. Pinski, J.M. Sanz-Serna, A. Beskos, Pinski, FJ, A.M. Stuart, Stuart, AM, Sanz-Serna, J. M., Beskos, Alexandros, Stuart, A. M.   +11 more
core   +1 more source

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source