Advanced Theory and Simulations最新文献

We propose here a zinc selenide (ZnSe)-graphene-reliant sensitive surface plasmon resonance (SPR) sensor for detecting chemicals such as D₂O, alcohol, and acetone. The sensor's performance is evaluated using the transfer matrix method (TMM) with respect to reflectivity, sensitivity, detection accuracy, and figure of merit. The results are then further analyzed by adjusting the sensor's structural parameters to design an optimal structure with optimal performance. Nine ZnSe layers and a monolayer of graphene were used to optimize sensor performance. With a Figure of Merit (FoM) of 46.704 RIU⁻¹ and a maximum sensitivity of 279.666 deg/RIU, this hybrid structure is positioned atop a 45 nm thick layer of silver. The performance of the sensor structure was also evaluated over a wide detection range of 1.33–1.39, as many biological solutions fall within this range.

The growing need for reliable, maintenance-free monitoring of power line infrastructure has intensified interest in sustainable power sources for wireless sensors. Piezoelectric energy harvesting offers a promising alternative to batteries. However, most existing power line harvesters deliberately ignore the combined effects of air damping, strain rate damping, and optimal positioning relative to AC power lines, which limits their power output and real-world applicability. This study addresses the gap and explicitly integrates them within a unified analytical, numerical, and experimental framework validating an optimally positioned piezoelectric energy harvester that extracts mechanical energy from the alternating magnetic field generated by current-carrying conductors. A coupled electromechanical model was formulated, incorporating magnetic excitation, air damping, strain damping to support and verify the results from the experimental setup. Results show that a 6.35 mm³ magnet placed beneath the power line, generates a peak force of 5.386 mN and an output voltage of 563.68 mV, with the harvested power increasing linearly with airflow velocity under a 9 A current flow at 4 mm from the AC power Line. The LTC3588-1 interface subsequently rectified and boosted the harvested voltage to a stable 3.3 V DC supply, demonstrating suitability for powering low-power Internet of Things (IoT) sensors in smart grid applications.

Amorphous silica-based materials are often used as support for catalysis experiments. The insertion of heteroelements (i.e., neither a silicon nor an oxygen atom) leads to the formation of Brønsted or Lewis acid sites. Despite their widespread use, the characterization of their acidic properties and the correlation with structural features remain challenging. In this context, computing chemical properties with quantum chemical methods can bring insights into such materials, while the large size of these systems implies the use of models to control the computational effort. This work aims to present a general procedure for calculating chemical properties of amorphous silica-based catalysts. The amorphous network is generated using classical molecular dynamics via a thermal treatment called melt-and-quench. Particular attention is devoted to the catalyst shape and the silanol coverage. The quality of the final amorphous network is assessed through the characterization of the geometrical structures involving primitive ring analysis. DFT calculations are then performed on hemispheres extracted from the amorphous silica frameworks to model aluminosilicate Brønsted acid sites. The impact of cluster size on the prediction of chemical properties is illustrated by calculations of deprotonation energies, chemical shifts, and vibrational frequencies. The influence of the exchange-correlation (XC) functional on those quantities is also discussed.

A theoretical investigation on the Zn₃MoN₄ compound was carried out using WIEN2k, DFT-based code, to calculate the electronic, optoelectronic, and thermal properties of the wurtzite-based diamond-like Zn₃MoN₄ structure. This compound exhibits an orthorhombic structure with the space group Pmn2₁. The structural, electronic, optoelectronic and thermoelectric properties were calculated within the GGA approximation. As GGA tends to underestimate the band gap, both GGA and the hybrid functional (YS-PBE0) methods were implemented, yielding indirect band gaps of 2.062 and 3.106 eV, respectively. Band gaps predicted using Extra Trees (2.081 eV) and K-Nearest Neighbors (2.087 eV) closely matched the DFT value of 2.06 eV for Zn₃MoN₄, outperforming Random Forest (1.700 eV), Gradient Boost (1.404 eV) and XGBoost (1.455 eV). From the density of states, it was observed that Mo-d and N-p orbitals have the major electronic contribution. The calculated optoelectronic properties, including dielectric constants, absorption coefficient, refractive index, reflectivity, and energy loss, suggest promising potential for optoelectronic applications. Additionally, effective mass, exciton binding energy, and exciton Bohr radius were calculated, with the effective mass of holes being greater than that of electrons, signifying holes as the major carriers. The thermoelectric properties were also investigated, including Seebeck coefficient, electrical conductivity, thermal conductivity, power factor, and figure of merit, across the temperature range 0–1000 K. The ZT values were modelled with consistent R² and RMSE performance for the aforementioned models.

Recently asymmetric squaraine dyes have drawn considerable interest for dye-sensitized solar cells (DSSCs) owing to their strong absorption spanning the visible to near-infrared region, remarkable molar extinction coefficients, and versatile structural. However, some squaraine dyes still suffer from limitations, such as narrow spectral coverage and insufficient intramolecular charge transfer (ICT), which adversely affect the power conversion efficiency (PCE) of the dyes. Here, two new molecules, AK4-S and AK4-DTS, are constructed by introducing conjugated bridges between the D2 moiety and the anchoring group of the reference dye AK4. Employing density functional theory (DFT) and time-dependent density functional theory (TD-DFT), the computational study revealed that incorporating a π-conjugated spacer can reduce the energy gap (Eg), broaden the absorption spectrum, enhance the oscillator strength (f), suppress charge recombination, improve thermal stability, and significantly promote the ICT process, thereby facilitating electron injection into the TiO₂ substrate. Among them, AK4-DTS demonstrated the best performance, achieving a theoretical PCE of 9.946%, which is markedly higher than that of the original AK4 (9.050%). These findings demonstrate that incorporating a π-conjugated bridge serves as a viable approach to improve the PCE of squaraine-based dyes, thereby providing key guidance for the development of high-performance sensitizers in DSSCs.

A narrowband all-dielectric absorber capable of covering the long-infrared band is designed. The structure of this absorber consists of an upper dielectric layer, a lower dielectric substrate, and a reflective layer. The absorption bandwidth of the absorber is 5 µm for an absorption greater than 90%. The absorber demonstrates polarization-insensitive and large-angle absorption characteristics in the wavelength range of 6–18 µm. To further broaden the absorption bandwidth, a broadband metamaterial absorber (BMA) was designed, which consists of a top Ti layer, middle and lower Si₃N₄ dielectric layers, and a substrate layer. The absorption bandwidth of the BMA is 10.5 µm, with an average absorption of up to 92.5% in the 6–18 µm wavelength range. The BMA exhibits polarization-insensitive and large-angle absorption characteristics. At a 60° incident angle under TM and TE modes, the average absorption is 89% and 77%, respectively. The high absorption and broadband characteristics of the absorber are mainly attributed to the synergistic effect of localized surface plasmon resonance, propagating surface plasmon resonance, and cavity resonance, which jointly dominate the absorption process. This high-performance absorber has promising development prospects in cutting-edge fields such as infrared detection, stealth technology, and sensing.

A comprehensive first-principles investigation of the structural, optoelectronic, mechanical, and thermoelectric properties of wurtzite In_xAl_1-xN (0 ≤ x ≤ 1) alloys was performed using the linearized augmented plane wave (FP—LAPW) method within the Wien2K code. The equilibrium structural parameters including lattice constants a and c and their ratio c/a were calculated employing the Wu—Cohen generalized gradient approximation (WC—GGA), and showing excellent agreement with available experimental data, which confirms the reliability of the computational approach. The electronic behavior of wurtzite In_xAl_1-xN, modeled through the advanced nKTB—mBJ potential, with their calculated band gaps ranging from 5.54 to 0.87 eV confirm their semiconducting nature and tunability across a wide spectral range. Optical analysis reveals that the static dielectric constant (ε₁(0)) ranges from 3.27 to 5.69, the refractive index varies between 1.89 and 2.38, and strong absorption occurs above energies (8.87–18 eV), indicating potential for UV—visible optoelectronic applications. The studied wurtzite In_xAl_1-xN alloys demonstrate mechanical stability with a brittle character, evidenced by B/G ratios ranging from 1.279 to 1.561 (<1.75), ν values between 0.19 and 0.236 (<0.25), and negative Cauchy pressures. Thermoelectric behavior was studied by applying Boltzmann transport theory as implemented in BoltzTrap, revealing ZT values close to 0.82 at higher temperatures, indicating strong potential for thermoelectric applications. The Slack model was applied to estimate lattice thermal conductivity, providing insights into phonon transport behavior and heat management in device applications.

Climate change and global targets to achieve net-zero carbon goals need efficient energy storage systems that are capable of powering green mobility and have the capacity to mitigate the irregular supply of renewable sources. Among the various available technologies, energy storage devices such as batteries, supercapacitors, etc., provide a sustainable solution. However, these devices currently lack the required performance to meet the growing demands, particularly in terms of power and energy densities, fast charging capabilities, longer cycle life, etc. Their electrochemical performance is mainly determined by how many electrolyte ions are stored within the electrodes without the crowding effect. The shape and size of electrolyte ions, along with electrode pore connectivity, are two major factors that significantly affect charge storage capabilities. Determining these relations using traditional experimental methods is time-consuming, expensive, complex, and ineffective. Hence, this study uses molecular dynamics simulation integrated with density functional theory calculations to gain insights into how ion shape and size affect the charge storage mechanism. Further, the significance of electrode pore interconnectivity in governing charge storage is also explored in this work. The study employed a microporous carbon electrode with a pore size distribution ranging from ∼0.3 to 1.0 nm. Results indicate that [EMIM]⁺ (∼0.76 × 0.43 nm) with [Cl]⁻ (∼0.18 nm) is significantly smaller than [C₄C₁Pyrr]⁺ (∼1.10 × 0.60 nm) and [TFSI]⁻ (∼0.79 × 0.29 nm). Further, the ionic size of [EMIM]⁺/[Cl]⁻ fall within the pore size distribution and was thus diffuse more readily and yield higher in‑pore ion counts and charge storage. Bulkier ions like [C₄C₁Pyrr]⁺ and [TFSI]⁻ systems were found to be locally concentrated near the initial sections of the electrode, partly due to their large size and/or due to their shape. Density functional theory studies also support the results obtained from molecular dynamics simulations and confirm that smaller ions whose size falls within the electrode pore size distribution contribute to double-layer formation and thereby aid in improving the charge storage of energy storage devices.

The use of solid additives is crucial for optimizing blend morphology and enhancing power conversion efficiency (PCE) in organic photovoltaics (OPVs). This study investigates four naphthalene-derived additives (2-chloronaphthalene (2-CN), 2-methylnaphthalene (2-MN), 2-methylthionaphthalene (2-sMN), and 2-methoxynaphthalene (2-oMN)) in PM6:PYIT blends via coarse-grained molecular dynamics simulations. Results show that these additives effectively regulate morphology and microstructure. Specifically, 2-CN strengthens π–π stacking among PM6 molecules and enriches the PM6 phase, while 2-MN significantly enhances phase separation between PM6 and PYIT. In contrast, 2-sMN and 2-oMN exhibit weaker effects due to steric hindrance from their substituents. This work demonstrates that substituent engineering in naphthalene derivatives can selectively tune π–π stacking and phase separation. The chlorine group in 2-CN enhances intermolecular interactions, and the methyl group in 2-MN promotes phase separation with minimal steric hindrance. Meanwhile, bulkier ─SCH₃ and ─OCH₃ groups impede similar improvements. Such synergistic mechanisms contribute to optimized morphology and improved PCE in OPVs.