THE MONTE CARLO METHOD APPLIED TO A PROBLEM IN $gamma$-RAY DIFFUSION
, 1953 B. V. Carlson
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Test of the Monte Carlo Method: Fast Simulation of a Small Ising Lattice [PDF]
, 1970 R. Friedberg, J. E. Cameron
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Supramolecular Chemistry in Metal–Organic Framework Materials
Advanced Materials, EarlyView.This review highlights synergies between reticular chemistry and supramolecular chemistry. The role of supramolecular interactions in determining framework…guest interactions and attempts to understand dynamic behavior in metal–organic frameworks (MOFs), particularly emphasizing the development of crystal sponges, studying reactions in frameworks and ...
Eugenia Miguel‐Casañ +3 more
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Determination of the detection efficiency of in thiroid using Monte Carlo method
Nucleus, 2016 Monte Carlo Method was the base to estimate the detection efficiency of of the identiFINDER ultra detector in “thyroid” geometry. The suitability of the calibration methodology is discussed using a comparison of the results of the Direct Monte Carlo ...
Dayana Ramos Machado +3 more
doaj
Attitude Control System for Quadrotor Using Robust Monte Carlo Model Predictive Control
ActuatorsMonte Carlo Model Predictive Control (MCMPC) is a kind of non-linear Model Predictive Control (MPC) that determines control inputs using the Monte Carlo method.
Kai Masuda, Kenji Uchiyama
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Two Recent Developments Concerning the Monte Carlo Method [PDF]
, 1975 M. Hénon
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Structural Quantification of the Surface-Confined Metal-Organic Precursors Simulated with the Lattice Monte Carlo Method. [PDF]
Molecules, 2023 Lisiecki J, Szabelski P.
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Adsorption and Separation by Flexible MOFs
Advanced Materials, EarlyView.Flexible metal–organic frameworks (MOFs) present significant potential for gas storage and separation due to their structural dynamic. This review explores the rationale behind the flexible MOFs' enhanced working capacity and separation factors. It also addresses key challenges, including phase transition kinetics, crystal robustness, cycling, shaping,
Irena Senkovska +4 more
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Simple rejection Monte Carlo algorithm and its application to multivariate statistical inference [PDF]
arXivThe Monte Carlo algorithm is increasingly utilized, with its central step involving computer-based random sampling from stochastic models. While both Markov Chain Monte Carlo (MCMC) and Reject Monte Carlo serve as sampling methods, the latter finds fewer applications compared to the former. Hence, this paper initially provides a concise introduction to
arxiv
Some results on transport theory and their application to Monte Carlo methods
, 1967 Jerome Spanier
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