Advanced Theory and Simulations最新文献

The study investigates the impact of thionation on N,N'-di(dodecyl)-4,5,8,9-naphthalene diimide (NDI) through computational methods such as density functional theory (DFT/TD-DFT), quantum theory of atoms in molecules (QTAIM), and Landauer theory (LT). Thionation, involving the replacement of diamide oxygens with sulfurs in NDI, significantly enhances quantum-electronic/thermoelectric properties. Computational analyzes of energy of frontier orbitals HOMO/LUMO, dipole moment, polarizability, first superpolarizability, UV spectrum, and cohesive energy show the superior performance of the thione structure (M2) compared to the pristine structure (M1). Thionation decreased the energy gap from 01.3 eV (in M1 structure) to 1.87 eV (in M2 structure). The absorption wavelength in the pristine structure (M1) is calculated to be 507 nm, which increased to 1067 nm after thionation (M2). Cohesive energy values for each of M1 and M2 structures are calculated as 12.76 and 12.89 Kcal mol⁻¹, respectively, which indicates the improvement of stability after thionation. After connecting M1 and M2 to gold electrodes (Au-M1-Au and Au-M2-Au) and applying electric fields, the Au-M2-Au structure shows a lower energy gap, lower thermoelectric activity and higher conductivity at field intensities with higher than 140 × 10⁻⁴ (a.u.), indicating its use as a field-effect molecular device (such as molecular wire or molecular switch).

Gamma-ray, fast neutron and charged particle shielding characteristics of Praseodymium (Pr³⁺) activated glasses with composition 10ZnF₂-(10-x)SrO-15Li₂O-65H₃BO₃-xPr₂O₃(where x = 0.1, 0.5, 1.0, 1.5, and 2.0) are investigated. For this, the radiation shielding parameters are estimated by using Photon Shielding and Dosimetry (Phy-X/PSD), Interaction of Proton, Alpha, Gamma rays, Electrons, and X-rays with matter (PAGEX), Stopping Powers and Ranges for Electrons (ESTAR), and The Stopping and Range of Ions in Matter (SRIM) codes. Furthermore, the results are compared comprehensively and comparatively. The glasses with increasing Pr³⁺ content exhibited higher shielding potential. It can be said that the ZFLHBPr2.0 sample could be used as a shielding material in various applied fields. Additionally, the effect of Pr composition on structural transitions and time-dependent volume-collapse of this new family of borate glass doped with Pr is analyzed by molecular dynamics study (MD) based density functional tight binding method. The simulation results show that the addition of Pr led to the cubic-orthorhombic transformation of simulation cell at determined temperature and 1 atm pressure. Also, a sudden decrease in volume are observed within a short time at 8% Pr composition (x = 2.0) atmospheric pressure. This result provides a strong connection between Pr composition and volume change with time and at constant low pressure.

This study presents a comprehensive simulation of a TiSe₂-based photodetector, an optoelectronic device adept at converting a spectrum of electromagnetic radiation spanning ultraviolet (UV), visible, and infrared wavelengths into electrical signals. The TiSe₂ absorber material is characterized by a narrow direct bandgap of 1.2 eV, endowing the photodetector with superior optical and electronic attributes that enhance its photodetection capabilities. In-depth analysis of the energy band diagram, the current-voltage (J-V) characteristics, and spectral responses is conducted. This article involves in methodical variations in the thickness, doping levels, and defect density across different layers to achieve optimal performance. The photodetector's current, J_SC, and voltage, V_OC are recorded at 37.30 mA cm⁻² and 0.795 V, in turn. Additionally, the device achieves a peak responsivity, R of 0.67 A W⁻¹ and a detectivity, D^* of 12.9 × 10¹⁴ Jones at a wavelength of 920 nm. Notably, the spectral response is significantly enhanced between 760 and 1010 nm, indicating the photodetector's proficient detection of near-infrared (NIR) light. The findings underscore the potential of TiSe₂ as an effective material for photodetector applications, marking a significant advancement in the field and paving the way for future research endeavors in photodetector technology.

The inimitable structural, electronic, and optical properties of inorganic cubic rubidium-lead-halide perovskite have obtained significant attention. In this research, novel rubidium-lead-iodide (RbPbI₃)-based perovskite solar cells incorporating Tin Sulfide (SnS₂) is investigated as an efficient buffer layer, utilizing both Density Functional Theory (DFT) calculations and SCAPS-1D simulator. Primarily, DFT is used to compute the bandgap, partial density of states (PDOS), and optical properties of the RbPbI₃ absorber, which are then applied in the SCAPS-1D simulator. An optimized Al/FTO/SnS₂/RbPbI₃/Au device is systematically studied. Additionally, the effect of various influencing factors are investigated such as layer bulk defect density, interface defect density, doping concentration, and thickness. The highest power conversion efficiency (PCE) of 31.11% is achieved for the SnS₂ Electron Transport Layer (ETL), with a J_SC of 32.47 mA cm⁻², V_OC of 1.10 V, and FF of 87.14% for the Al/FTO/SnS₂/RbPbI₃/Au structure. Characteristics of quantum efficiency (QE) are also analyzed. Therefore, SnS₂ ETL demonstrates the robust potential for utilization in high-performance photovoltaic cells based on RbPbI₃ perovskite.

Ion mobility-mass spectrometry (IM-MS) has recently contributed to the structural analysis of molecules, including supramolecules and proteins, by determining the ion arrival time distributions correlated with the collision cross sections (CCSs), as well as the mass-to-charge ratios. However, its application range is still limited owing to the lack of general CCSs simulation methods based on possible molecular conformations. Here, a molecular dynamics-based conformational search method for simulating CCS distributions using projection approximation is reported. As a case study, the gas-phase conformations of the sodium adducts of conformationally flexible polyketones with 3,3-dimethylpentane-2,4-dione as the monomer are analyzed. The sodium adduct of the hexamer (m/z 781.4 for [1 + Na]⁺) showed a monomodal arrival time distribution, but that of the octamer sodium adduct (m/z 1033.5 for [2 + Na]⁺) is multimodal. The conformational analysis indicated an unimodal CCS distribution of simulated [1 + Na]⁺ conformations in which the sodium cation is mainly bound at the chain terminal. Conversely, four clusters of conformations are obtained for [2 + Na]⁺ based on the Na⁺-coordination sites, which qualitatively reproduced the observed CCS distribution. This approach will extend the utility of IM-MS for the conformational analysis of flexible molecules in the gas phase.

Inertial microfluidics is essential for separating particles and cells, enabling numerous biomedical applications. Despite the simplicity of spiral microchannels, the lack of predictive models hampers real-world applications, highlighting the need for cost-effective computational tools. In this study, four novel data fitting models are developed using linear and power regression analyses to investigate how flow conditions influence particle behaviors within spiral microchannels. These models are rigorously tested under two different flow rates, focusing on a smaller particle representing Salmonella Typhimurium and a larger particle representing bacterial aggregates, aiming for effective separation and detection. A critical parameter, the sheath-to-sample flow rate ratio, is either interpolated or extrapolated using the microchannel's aspect ratios to predict particle separation. The models show strong agreement with experimental data, underscoring their predictability and efficiency. These insights suggest that further refinement of these models can significantly reduce research and development costs for advanced inertial microfluidic devices in biomedical applications. This work represents a crucial step towards establishing a robust computational framework, advancing inertial microfluidics towards practical biomedical applications.

KRAS G12D mutation is prevalent in various cancers and is associated with poor prognosis. This study aimed to identify potential drug candidates targeting KRAS G12D using combined machine learning, virtual screening, molecular docking, and molecular dynamics (MD) simulations. The training and test sets are constructed based on a selection of inhibitors targeting the KRAS G12D mutant from the ChEMBL library. A random forest machine learning algorithm is developed to predict potential KRAS G12D binders. Molecular docking and the MM/PBSA binding energy are used to identify the lead compounds. The compound NPC489264 is identified as the top candidate, exhibiting favorable docking energy for the KRAS G12D mutant (−13.16 kcal mol⁻¹). A hydrogen bond between the mutated Asp12 residue in the KRAS G12D mutant and NPC489264 is found to be a key interaction between these 2 molecules. MD simulations and MM/PBSA analysis revealed the strong binding affinity of NPC489264 to the G12D mutant (−5.49 kcal mol⁻¹) compared to the wild type (10.17 kcal mol⁻¹). These findings suggest that NPC489264 is a promising lead compound for further development of KRAS G12D-targeted cancer therapies.

In the present study, a dynamic Monte Carlo (MC) model is applied for predicting the dynamic evolution of monomer Droplet Size Distribution (DSD) and polymer Particle Size Distribution (PSD) within the presence of an inventive time step in the MC algorithm for both non-reactive (liquid–liquid dispersion) and reactive systems. Besides, a combining approach as a second inventive strategy is introduced for implementing the MC simulation with a high number of droplets. An optimization process generated the dimensionless Model Parameters (MPs) and is applied to the MC simulation. The MC algorithm is validated with the experimental data from the literature. The novel time step can predict the dynamic evolution of monomer droplets and polymer particles in the reactive systems and diminish the time of the simulation. The combining approach is an excellent strategy for mixing the same or different number of droplets for decreasing time consumption of MC simulation. Extraordinary findings depicted the model's effectiveness and the validity of the time step and combining strategies.

Synchronous grouting technology is a crucial aspect of shield tunnel construction. However, understanding the mechanism of slurry diffusion during this process is challenging due to its complexity and invisibility. Existing theoretical models often oversimplify the grouting process and do not account for multi-stage diffusion mechanisms. By considering the radial penetration of slurry and viewing the diffusion process as the formation of annular pancakes through circumferential filling, a 3D diffusion numerical model is established using the volume of fluid (VOF)-multiphase flow model in Fluent software. The model's validity is confirmed through calculations based on theoretical formulas and monitoring data from engineering examples. This study uncovers the patterns of slurry diffusion and examines how factors like porosity, grouting pressure, and slurry density impact diffusion radius and segment stress. The findings of this research provide a crucial theoretical foundation for shield synchronous grouting construction.