Thermal Transport in MoS2_2 from Molecular Dynamics using Different Empirical Potentials

Thermal properties of molybdenum disulfide (MoS$_2$) have recently attracted attention related to fundamentals of heat propagation in strongly anisotropic materials, and in the context of potential applications to optoelectronics and thermoelectrics. Multiple empirical potentials have been developed for classical molecular dynamics (MD) simulations of this material, but it has been unclear which provides the most realistic results. Here, we calculate lattice thermal conductivity of single- and multi-layer pristine MoS$_2$ by employing three different thermal transport MD methods: equilibrium, nonequilibrium, and homogeneous nonequilibrium ones. These methods allow us to verify the consistency of our results and also facilitate comparisons with previous works, where different schemes have been adopted. Our results using variants of the Stillinger-Weber potential are at odds with some previous ones and we analyze the possible origins of the discrepancies in detail. We show that, among the potentials considered here, the reactive empirical bond order (REBO) potential gives the most reasonable predictions of thermal transport properties as compared to experimental data. With the REBO potential, we further find that isotope scattering has only a small effect on thermal conduction in MoS$_2$ and the in-plane thermal conductivity decreases with increasing layer number and saturates beyond about three layers. We identify the REBO potential as a transferable empirical potential for MD simulations of MoS$_2$ which can be used to study thermal transport properties in more complicated situations such as in systems containing defects or engineered nanoscale features. This work establishes a firm foundation for understanding heat transport properties of MoS$_2$ using MD simulations.Comment: 14 pages, 6 figure

Thermal Transport in MoS2_2 from Molecular Dynamics using Different Empirical Potentials

Thermal properties of molybdenum disulfide (MoS$_2$) have recently attracted attention related to fundamentals of heat propagation in strongly anisotropic materials, and in the context of potential applications to optoelectronics and thermoelectrics. Multiple empirical potentials have been developed for classical molecular dynamics (MD) simulations of this material, but it has been unclear which provides the most realistic results. Here, we calculate lattice thermal conductivity of single- and multi-layer pristine MoS$_2$ by employing three different thermal transport MD methods: equilibrium, nonequilibrium, and homogeneous nonequilibrium ones. These methods allow us to verify the consistency of our results and also facilitate comparisons with previous works, where different schemes have been adopted. Our results using variants of the Stillinger-Weber potential are at odds with some previous ones and we analyze the possible origins of the discrepancies in detail. We show that, among the potentials considered here, the reactive empirical bond order (REBO) potential gives the most reasonable predictions of thermal transport properties as compared to experimental data. With the REBO potential, we further find that isotope scattering has only a small effect on thermal conduction in MoS$_2$ and the in-plane thermal conductivity decreases with increasing layer number and saturates beyond about three layers. We identify the REBO potential as a transferable empirical potential for MD simulations of MoS$_2$ which can be used to study thermal transport properties in more complicated situations such as in systems containing defects or engineered nanoscale features. This work establishes a firm foundation for understanding heat transport properties of MoS$_2$ using MD simulations.Comment: 14 pages, 6 figure

Thermal transport in MoS2 from molecular dynamics using different empirical potentials

Thermal properties of molybdenum disulfide (MoS2) have recently attracted attention related to fundamentals of heat propagation in strongly anisotropic materials, and in the context of potential applications to optoelectronics and thermoelectrics. Multiple empirical potentials have been developed for classical molecular dynamics (MD) simulations of this material, but it has been unclear which provides the most realistic results. Here, we calculate lattice thermal conductivity of single- and multilayer pristine MoS2 by employing three different thermal transport MD methods: equilibrium, nonequilibrium, and homogeneous nonequilibrium ones. We mainly use the Graphics Processing Units Molecular Dynamics code for numerical calculations, and the Large-scale Atomic/Molecular Massively Parallel Simulator code for crosschecks. Using different methods and computer codes allows us to verify the consistency of our results and facilitate comparisons with previous studies, where different schemes have been adopted. Our results using variants of the Stillinger-Weber potential are at odds with some previous ones and we analyze the possible origins of the discrepancies in detail. We show that, among the potentials considered here, the reactive empirical bond order (REBO) potential gives the most reasonable predictions of thermal transport properties as compared to experimental data. With the REBO potential, we further find that isotope scattering has only a small effect on thermal conduction in MoS2 and the in-plane thermal conductivity decreases with increasing layer number and saturates beyond about three layers. We identify the REBO potential as a transferable empirical potential for MD simulations of MoS2 which can be used to study thermal transport properties in more complicated situations such as in systems containing defects or engineered nanoscale features. This work establishes a firm foundation for understanding heat transport properties of MoS2 using MD simulations

Non-communicable diseases in the southwest of Iran: profile and baseline data from the Shahrekord PERSIAN Cohort Study

Background Critical inter-provincial differences within Iran in the pattern of non-communicable diseases (NCDs) and difficulties inherent to identifying prevention methods to reduce mortality from NCDs have challenged the implementation of the provincial health system plan. The Shahrekord Cohort Study (SCS) was designed to address these gaps in Chaharmahal and Bakhtiari, a province of high altitude in the southwest of Iran, characterized by its large Bakhtiari population, along with Fars and Turk ethnicity groups. Methods This ongoing cohort, a prospective, large-scale longitudinal study, includes a unique, rich biobank and was conducted for the first time in Chaharmahal and Bakhtiari Province in Iran. SCS is a part of the PERSIAN (Prospective Epidemiological Research Studies in IrAN) cohort. The study began in 2015, recruited 10075 participants (52.8% female, 47.2% male) from both urban (n=7034) and rural (n=3041) areas, and participants will be annually followed up for at least 15 years. A cross-sectional analysis was conducted using baseline data from the SCS, using descriptive statistics and logistic regression. Data analysis was performed using Stata software. Results The prevalence of NCDs was 9.8% for type 2 diabetes, 17.1% for hypertension, 11.6% for thyroid disease, 0.2% for multiple sclerosis and 5.7, 0.9 and 1.3% for ischemic heart disease, stroke and myocardial infarction, respectively. The prevalence of multimorbidity (>= 2 NCDs) was higher in women (39.1%) than men (24.9%). The means (standard deviations) of age, BMI, systolic blood pressure and fasting blood glucose were 49.5 (9) years, 27.6 (4.6) kg/m(2), 115.4 (17.3) mmHg and 96.7 (27.3) mg/dL, respectively. Logistic regression models showed that older age, female gender, living in an urban area, non-native ethnicity, high wealth index, unemployment, obesity, low physical activity, hypertriglyceridemia, high fasting blood sugar, alkaline urine pH and high systolic and diastolic blood pressure were associated with increased prevalence of NCDs. Conclusions The SCS provides a platform for epidemiological studies that will be useful to better control NCDs in the southwest of Iran and to foster research collaboration. The SCS will be an essential resource for identifying NCD risk factors in this region and designing relevant public health interventions

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Modeling Raman and Photoluminescence Spectra of Defective Materials

Defects are inevitable in solid materials as a result of fluctuations in thermal equilibrium and their processing kinetics. Depending on the targeted application, they can be either beneficial or detrimental. For example, doping semiconductors by foreign atoms can be used to increase carrier concentrations, but at the same time, the carrier mobilities decrease due to enhanced scattering. Defects can also introduce a two-state light emitter system to compensate for the indirect nature of the electronic band gap. However, it is necessary to elucidate the presence of defects and their influence on the properties of materials to develop an application-specific strategy for defect engineering. Raman spectroscopy can be utilized as a contactless and inexpensive diagnostic tool to characterize materials and evaluate their qualities. Photoluminescence spectroscopy is another non-destructive technique that helps us to understand the behavior of optically active defects in materials. While experimental measurements can be complicated, modern computational platforms possess good predictive power and can give us a deep insight into the relevant physical processes. In the case of defects, one needs high computational resources and an advanced theoretical framework to calculate Raman spectra. These issues need to be tackled in a reliable way before calculations. This thesis focuses on simulating Raman and photoluminescence spectra to investigate defects signatures in materials. An efficient computational method to simulate Raman spectra of large systems, which applies to alloys and systems with a small number of defects is devised. The method is based on the projection of vibrational eigenvectors of the supercell to the eigenvectors from the pristine primitive unit cell and using the Raman tensors calculated for the latter. Using photoluminescence and accounting for electron-phonon interactions, we investigate vibronic structures of color centers and calculate phonon side bands. Through this thesis, the behavior of phonons in several two-dimensional semiconducting alloys is explored. We demonstrate that (i) the so-called mass approximation significantly facilitates the calculation of Raman spectra, (ii) simulating the Raman spectra for defective materials can be done by a combination of empirical potentials and quantum mechanical density functional theory calculations, (iii) the so-called phonon confinement model can be used to capture the asymmetric broadening of the prominent peaks. In the context of photoluminescence, we compare the vibronic structures of different color centers by evaluating several important characteristics that are experimentally achievable

Understanding Electron Transfer Reactions Using Constrained Density Functional Theory: Complications Due to Surface Interactions

| openaire: EC/H2020/875565/EU//CompBat Funding Information: This study was financed by the Horizon 2020 Framework Programme CompBat with Project No. 875565. We also thank CSC-IT Center for Science Ltd. and Aalto Science-IT project for generous grants of computer time. A.H. thanks Reza Khakpour and Rasmus Kronberg for insightful discussions. Publisher Copyright: © 2023 The Authors. Published by American Chemical Society.The kinetic rates of electrochemical reactions depend on electrodes and molecules in question. In a flow battery, where the electrolyte molecules are charged and discharged on the electrodes, the efficiency of the electron transfer is of crucial importance for the performance of the device. The purpose of this work is to present a systematic atomic-level computational protocol for studying electron transfer between electrolyte and electrode. The computations are done by using constrained density functional theory (CDFT) to ensure that the electron is either on the electrode or in the electrolyte. The ab initio molecular dynamics (AIMD) is used to simulate the movement of the atoms. We use the Marcus theory to predict electron transfer rates and the combined CDFT-AIMD approach to compute the parameters for the Marcus theory where it is needed. We model the electrode with a single layer of graphene and methylviologen, 4,4′-dimethyldiquat, desalted basic red 5, 2-hydroxy-1,4-naphthaquinone, and 1,1-di(2-ethanol)-4,4-bipyridinium were selected for the electrolyte molecules. All of these molecules undergo consecutive electrochemical reactions with one electron being transferred at each stage. Because of significant electrode-molecule interactions, it is not possible to evaluate outer-sphere ET. This theoretical study contributes toward the development of a realistic-level prediction of electron transfer kinetics suitable for energy storage applications.Peer reviewe

Kinetics of N2 Release from Diazo Compounds: A Combined Machine Learning-Density Functional Theory Study

Diazo compounds are commonly employed as carbene precursors in carbene transfer reactions during a variety of functionalization procedures. Release of N2 gas from diazo compounds may lead to carbene formation, and the ease of this dissociation is highly dependent on the characteristics of the substituents located in the vicinity of the diazo moiety. A quantum mechanical density functional theory assisted by machine learning was used to investigate the relationship between the chemical features of diazo compounds and the activation energy required for the N2 dissociation. Our results suggest that diazo molecules possessing a higher positive partial charge on the carbene carbon and more negative charge on the terminal nitrogen, encounter a lower energy barrier. A more positive C charge decreases the π-donor ability of the carbene lone pair to the π∗ orbital of N2 , while the more negative N charge is a result of a weak interaction between N2 lone pair and vacant p orbital of the carbene. The findings of this study can pave the way for molecular engineering for the purpose of carbene generation which serves as a crucial intermediate for many chemical transformations in synthetic chemistry

Kinetics of N2 Release from Diazo Compounds: A Combined Machine Learning-Density Functional Theory Study

Total potential (E) and Thermal correction to Gibbs Free Energies obtained using SMD/M06-2X/def2-TZVP//SMD/M06-2X/6-31G(d) level of theory in dichloroethane and Cartesian coordinates for all of the calculated structures. dataset Python Machine Learning Scrip