Monte Carlo and Kinetic Monte Carlo Models for Deposition Processes: A Review of Recent Works

Cheimarios, Nikolaos; To, Deifilia; Kokkoris, George; Memos, George; Boudouvis, Andreas G.

doi:10.3389/fphy.2021.631918

Cited by 31 publications

(15 citation statements)

References 78 publications

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“…The Monte Carlo method is based on probability theory and mathematical statistics to solve mathematical physics and engineering technology problems. The specific issue first establishes a probability model, carries the random test to the model, and statistically solves it. − Specifically, the Monte Carlo principle is a way to calculate the statistical characteristics of the required parameters by observing the model and the process or conducting sampling experiments. Thus the relationship between A and B is solved.…”

Section: Samples and Methodsmentioning

confidence: 99%

Characteristics of Natural Fractures in an Ultradeep Marine Carbonate Gas Reservoir and Their Impact on the Reservoir: A Case Study of the Maokou Formation of the JLS Structure in the Sichuan Basin, China

Wang

Qin

et al. 2021

Energy Fuels

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The primary gas layer of the Maokou Formation of the JLS structure in the Sichuan Basin is a typical pore-fracture carbonate gas reservoir. Natural fractures (mainly tectonic fractures) serve as the critical factor in improving the reservoir's physical properties. The characteristics, formation mechanisms of natural fractures, and their impact on the reservoir are analyzed using the core, thin slice, full microresistivity imager imaging logging, production testing, and the Monte Carlo method multiple approximations. The results show that the fractures in the Maokou Formation reservoir generally refer to shear fractures of a tectonic origin, with the characteristics of a medium scale (10−20 cm), a large inclination angle (45− 90), a high density (greater than 5 m −1 ), a medium opening (1−3 mm), and a low filling degree. There are three primary formation stages of natural fractures in the area, the Indosinian stage (232−210 Ma), the early-middle Yanshanian stage (145−90 Ma), and the late Yanshanian−Himalayan stage (90−0 Ma). The corresponding principal stress directions are NW, near-SN, and NNW, respectively. Natural fractures have a positive effect on the improvement of reservoir physical properties. The fracture's physical parameters show a good positive correlation with the physical properties of the reservoirs. The fracture parameters influence the reservoir's physical properties ranked from biggest to smallest: opening, length, and density. The greater the development degree of fractures, the greater the corresponding natural gas production capacity. The research results provide a new technical method for quantifying the influence of fracture parameters on reservoir's physical properties.

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Section: Samples and Methodsmentioning

confidence: 99%

Characteristics of Natural Fractures in an Ultradeep Marine Carbonate Gas Reservoir and Their Impact on the Reservoir: A Case Study of the Maokou Formation of the JLS Structure in the Sichuan Basin, China

Wang

Qin

et al. 2021

Energy Fuels

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“…670 However, multiscale simulation design is more often piecemeal, applying the techniques discussed previously at their respective length scales to develop a holistic understanding of the relationships among optoelectronic processes, self-assembly, bulk morphology, and (thermo)mechanical properties. For example, after FF parametrization, a sample morphology can be generated through classical simulations, optionally using coarse-grained MD or enhanced sampling techniques to accelerate the exploration of 672,673 Of particular interest to this work, several works have reviewed KMC simulations of OSC materials for modeling CCT, exciton diffusion lengths, charge recombination, and Seebeck coefficients. 333,674−679 We also highlight a handful of additional works that used KMC methods to characterize a variety of phenomena in OSC materials.…”

Section: Connecting Optoelectronics To Morphologymentioning

confidence: 99%

Computational Approaches for Organic Semiconductors: From Chemical and Physical Understanding to Predicting New Materials

2023

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While a complete understanding of organic semiconductor (OSC) design principles remains elusive, computational methods�ranging from techniques based in classical and quantum mechanics to more recent data-enabled models�can complement experimental observations and provide deep physicochemical insights into OSC structure− processing−property relationships, offering new capabilities for in silico OSC discovery and design. In this Review, we trace the evolution of these computational methods and their application to OSCs, beginning with early quantum-chemical methods to investigate resonance in benzene and building to recent machine-learning (ML) techniques and their application to ever more sophisticated OSC scientific and engineering challenges. Along the way, we highlight the limitations of the methods and how sophisticated physical and mathematical frameworks have been created to overcome those limitations. We illustrate applications of these methods to a range of specific challenges in OSCs derived from π-conjugated polymers and molecules, including predicting charge-carrier transport, modeling chain conformations and bulk morphology, estimating thermomechanical properties, and describing phonons and thermal transport, to name a few. Through these examples, we demonstrate how advances in computational methods accelerate the deployment of OSCsin wide-ranging technologies, such as organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), organic thermoelectrics, organic batteries, and organic (bio)sensors. We conclude by providing an outlook for the future development of computational techniques to discover and assess the properties of highperforming OSCs with greater accuracy.

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“…The Monte-Carlo method [139 -141] has also been successfully applied to sputtering [142][143][144][145][146][147][148][149][150][151][152][153][154][155][156][157][158] and sputtered material transport [159][160][161][162][163][164][165][166][167][168][169][170][171][172][173][174][175]. Kinetic Monte-Carlo simulations are able to address deposition and the resulting thin-film growth [176][177][178][179][180][181][182][183][184][185][186][187][188]…”

Section: Monte-carlo Modelsmentioning

confidence: 99%

Theory and molecular simulations of plasma sputtering, transport and deposition processes

2023

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The present review provides an overview of the basic theory of sputtering with recent models, focussing in particular on sputtered atom energy distribution functions. Molecular models such as Monte-Carlo, kinetic Monte-Carlo, and classical Molecular Dynamics simulations are presented due to their ability to describe the various processes involved in sputter deposition at the atomic and molecular scale as required. The sputter plasma, the sputtering mechanisms, the transport of sputtered material and its deposition leading to thin film growth can be addressed using these molecular simulations. In all cases, the underlying methodologies and some selected mechanisms are highlighted.

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Monte Carlo and Kinetic Monte Carlo Models for Deposition Processes: A Review of Recent Works

Cited by 31 publications

References 78 publications

Characteristics of Natural Fractures in an Ultradeep Marine Carbonate Gas Reservoir and Their Impact on the Reservoir: A Case Study of the Maokou Formation of the JLS Structure in the Sichuan Basin, China

Characteristics of Natural Fractures in an Ultradeep Marine Carbonate Gas Reservoir and Their Impact on the Reservoir: A Case Study of the Maokou Formation of the JLS Structure in the Sichuan Basin, China

Computational Approaches for Organic Semiconductors: From Chemical and Physical Understanding to Predicting New Materials

Theory and molecular simulations of plasma sputtering, transport and deposition processes

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