Advanced Theory and Simulations最新文献

We analyze the quantum transport properties of FA-based perovskite solar cells, emphasizing the role of $�{\mathrm{Cs}}^{+}$ and $�{\mathrm{Br}}^{-}$ co-doping in enhancing both charge transport and structural stability. Within the framework of Density Functional Theory (DFT) and the Non-Equilibrium Green's Function (NEGF) formalism, we examine how doping alters the electronic structure, reshaping transport pathways at the quantum level. The results indicate that $�{\mathrm{Cs}}^{+}$ stabilizes the perovskite lattice by suppressing structural instabilities, while $�{\mathrm{Br}}^{-}$ modifies the bandgap, facilitating more efficient charge extraction and suppressing non-radiative recombination. The combined effect of these modifications is a substantial reduction in tunneling barriers and defect-induced scattering, enabling transport that is nearly ballistic under optimal conditions. These findings suggest a direct correspondence between atomic-scale doping mechanisms and large-scale device performance, providing a theoretical basis for the controlled design of high-efficiency perovskite photovoltaics. The broader implications extend beyond a specific material system, offering insight into the interplay of quantum mechanical effects and device-scale efficiency, with potential relevance to the development of next-generation photovoltaic architectures.

In recent years, the integration of electromagnetic metasurfaces with holographic imaging has witnessed significant progress. By engineering the array configuration of coding metasurfaces to manipulate both the amplitude and phase of scattered waves, high-resolution imaging can be achieved. Nevertheless, conventional metasurfaces are usually restricted to reconstructing only a single holographic image on the imaging plane, which greatly limits their versatility. Here, we propose a graphene-based terahertz space–time coding metasurface (STGDM) that employs 2-bit unit cells together with temporal modulation to achieve equivalent 3-bit phase control, enabling independent amplitude and phase modulation at the ±1st harmonics. Leveraging this mechanism, the STGDM achieves multiple advanced functionalities, including dual-hologram reconstruction, simultaneous holography and beam steering, and controllable generation of dual vortex beams. Full-wave simulations confirm that the proposed strategy effectively suppresses undesired harmonics while enhancing the system's degrees of freedom and functional reconfigurability. These results highlight the potential of STGDMs as compact and versatile platforms for high-resolution imaging, security screening, multimodal sensing, and future 6G communication technologies.

Heterostructure solar cells attract significant interest due to the demand for high-efficiency and low-cost photovoltaic technologies. The buffer layer plays a crucial role in determining band alignment, reducing interfacial defects, and improving charge transport, stability, and device performance. This study investigates a ZnO/Buffer Layer/SWCNT/Cu₂O solar cell structure using SCAPS-1D, where Single-Walled Carbon Nanotubes serve as the absorber and Cu₂O as the back surface field. Three buffer materials PCBM, WO₃ and C₆₀ are analyzed, and the SWCNT absorber thickness, acceptor concentration, and defect density are varied to determine optimal conditions. The optimal configuration is achieved with PCBM at an absorber, N_A = 4 × 10¹⁶ cm⁻³ and W = 1000 nm at 300 K, producing a power conversion efficiency of 32.90%, J_SC = 42.98 mA/cm², V_OC = 0.89 V, and FF = 85.87% under AM 1.5G illumination. PCBM shows superior performance compared to WO₃ (32.28%) and C₆₀ (30.93%) due to favorable energy-band alignment and lower recombination rate. The findings indicate that buffer-layer engineering plays a significant role in improving heterostructure solar cell performance and supports the development of efficient, environmentally friendly, and scalable photovoltaic technologies. Furthermore, the materials are non-toxic and abundant in the Earth's crust, making the structure suitable for photovoltaic applications.

In this paper, an ultra-broadband circularly polarized (CP) antenna equipped with quasi-achromatic-focused metasurface (MS) is proposed. To enhance the C-shaped CP antenna's radiation performance, we designed a MS-based on Pancharatnam-Berry (PB) phase theory. Positioning the initial C-shaped CP antenna at the focal point of the designed quasi-achromatic-focused MS enabled an antenna loaded with MS achieving CP radiation. This MS antenna system demonstrated a peak gain of 13.77 dBic with an average gain exceeding 10 dBic over the 4.52–12.82 GHz band (relative bandwidth: 95.7%). Concurrently, its 3-dB axial ratio bandwidth reached 89.1%, covering 4.6–12 GHz. This work provides an efficient method to enhance antenna gain in wideband wireless communication systems.

Nitroimidazoles represent an important class of compounds due to their distinct biological activities and potential therapeutic applications. Among them, 2-nitroimidazole (2-NI) is known for its radiosensitizing effects in radiation therapy, while 4-nitroimidazole (4-NI) exhibits notable antimicrobial activity. Despite their significance, the fragmentation chemistry of nitroimidazole ions remains poorly understood. In this study, the fragmentation behavior of protonated and deprotonated 2-NI and 4-NI ions was investigated using electronic structure calculations combined with direct dynamics simulations under collision-induced dissociation (CID) conditions. All dynamics simulations were performed at the density functional M06-2X/6-31+G* level of theory. Ion activation was modeled through collisions with an Ar atom, and the resulting fragment ions were thoroughly analyzed. The simulations revealed a wide variety of dissociation pathways and product ions. Notably, the CID trajectories were dominated by a direct, non-statistical shattering mechanism, leading to deviations from experimental fragmentation patterns. To account for these differences, statistical unimolecular dissociation simulations were also conducted at fixed total energies. The resulting product branching ratios showed improved agreement with experimental observations, offering deeper insight into the underlying dissociation mechanisms.

This article provides a comprehensive performance analysis of various sensing layers on one-port surface acoustic wave (SAW) resonators exhibiting mass loading effect. Lithium Niobate (LiNbO₃) piezoelectric substrate, polyisobutylene (PIB) polymer and carbon nanotube (CNT) based multilayer SAW sensors were considered for device sensitivity. This study contributes to understanding the CNT-PIB composite layer on 128° YX-cut LiNbO₃ SAW devices for sensing applications. This research proposed four different SAW structures with optimized geometrical boundary conditions. The finite element method is applied to solve the SAW device partial differential equation (PDE) to find the device performance parameters. The proposed one-port SAW sensor has been analyzed with the investigation of change in SAW phase velocity, electromechanical coupling coefficient (K²), device sensitivity, admittance (Y11), S parameter (S11), and quality factor. Electrical response of the proposed SAW device is equivalently modeled with the modified Butterworth-Van Dyke (mBVD) lumped parameters, motional resistance (R_m), motional inductor (L_m), motional capacitor (C_m), and electrostatic capacitance (C₀). The obtained mBVD parameter describes the proposed SAW device's behavior tuned to the desired sensitivity, frequency response and signal-to-noise ratio. High sensitivity of 18.7 MHz/µg is reported for the proposed device. The obtained mass sensitivity is compared and is more effective than the parallel research outcome.

Here, we present a comprehensive computational evaluation of three FDA (Food and Drug Administration) approved drug leads, ZINC150338755, ZINC6716957, and ZINC203686879, as potential inhibitors targeting the Cripto/FRL-1/Cryptic (CFC) domain of the CRIPTO (Teratocarcinoma-derived growth factor1) protein. CRIPTO is a key oncogenic protein implicated in tumor progression, metastasis, and therapy resistance across multiple cancer types. Its overexpression promotes cancer stemness and survival in various tumors, such as liver cancer and glioblastoma, while its restricted expression in normal tissues makes it an attractive therapeutic target. Through an integrated approach merging molecular docking (with results −8.6 to −9.1 kcal/mol affinities), molecular dynamics (MD) simulations, molecular mechanics–generalized Born surface area (MM-GBSA) binding free energy calculations, and free energy landscape (FEL) analysis, we delineate distinct binding modes and thermodynamic fingerprints of the inhibitor complexes. Virtual screening determined the lead compounds, which were subjected to 250 ns MD simulations to check the stability and dynamics of interactions. Binding free energy calculation revealed striking disparities in binding energies (ΔG_bind from −26.83 to −57.37 kcal/mol), where Complex1 exhibited increased stability through hydrophobic superiority, Complex2 showed similar polar/nonpolar interactions, and Complex3 exhibited unique electrostatic-driven recognition. These findings shed atomic-level insight into CRIPTO-inhibitor interactions and offer a solid foundation for structure-based optimization of CRIPTO inhibitors.

Efficient thermal transmission is a necessary requirement of diversified engineering units to attain optimized output. For this purpose, the induction of tri-hybrid nanoparticles to achieve advanced heat transfer is considered as an innovative strategy because of an increase in the specific heat capacity of a system in different ways. The dispersion of silver (Ag), copper (Cu), and alumina (Al₂O₃) in water with different physical factors controlled the flow dynamics. A practical approach to enhance heat transfer effectiveness is to improve the thermal properties of the working fluid. Nanofluids, which are suspensions of nanoparticles in a base fluid, are recommended. In addition, the synergistic effects of homogeneous and heterogeneous reactions among nanoparticle interactions are also accounted for to improve overall thermal efficiency. The findings demonstrated that tri-hybrid nanofluids provide superior thermal conductivity and absorption rates compared with those of conventional fluids. A machine learning framework is employed to predict complex heat transfer behaviors and optimize system performance. Therefore, a machine learning paradigm based on an artificial neural network is used to analyze the particle concentration impacts for the estimation of the friction factor and heat transfer analysis of a water-based tri-hybrid nanofluid. The ANN model training for larger needle sizes exhibits higher accuracy and stability than that for smaller needle sizes, owing to the higher sensitivity and non-linearity, which are also indicated by the larger MSE. Validation failures remain zero in most cases, which represents fitness along with good generalization to the data.