Search Results (1,578)

Perovskite solar cells (PSCs) still suffer from varying degrees of optical and electrical losses. To enhance the light decoupling and capture ability of Planar PSCs, an ultra-thin PSC structure with an Al₂O₃ pyramid anti-reflection layer (Al₂O₃ PARL) is proposed. The effect of the structure of the Al₂O₃ PARL on the photoelectric performance of PSCs was investigated by changing various parameters. Under the AM1.5 solar spectrum (300–800 nm), the average light absorption rates and quantum efficiency (QE) of PSCs containing pyramid-array textured rear layers (PARLs) were significantly higher than those of planar PSCs. The Al₂O₃ PARL-based PSCs achieved a light absorption rate of 96.05%. Additionally, electrical simulations were performed using the finite element method (FEM) to calculate the short-circuit current density (J_SC), open-circuit voltage (V_OC), and maximum power (Pmax). Based on the maximum value of the average light absorbance, the geometric structure of the Al₂O₃ pyramid PSCs was optimized, and the optimization results coincided with the J_SC and QE results. The results of the electrical simulation indicated that the maximum J_SC was 23.54 mA/cm². Additionally, the J_SC of the Al₂O₃ pyramid PSCs was 22.73% higher than that of planar PSCs, resulting in a photoelectric conversion efficiency (PCE) of 24.34%. As a result, the photoelectric conversion rate of the solar cells increased from 14.01% to 17.19%. These findings suggest that the presence of the Al₂O₃ PARL enhanced photon absorption, leading to an increase in electron–hole pairs and ultimately improving the photocurrent of the solar cells. Full article

Photoresponsive drug delivery stands as a pivotal frontier in smart drug administration, leveraging the non-invasive, stable, and finely tunable nature of light-triggered methodologies. The generative pre-trained transformer (GPT) has been employed to generate molecular structures. In our study, we harnessed GPT-2 on the QM7b dataset to refine a UV-GPT model with adapters, enabling the generation of molecules responsive to UV light excitation. Utilizing the Coulomb matrix as a molecular descriptor, we predicted the excitation wavelengths of these molecules. Furthermore, we validated the excited state properties through quantum chemical simulations. Based on the results of these calculations, we summarized some tips for chemical structures and integrated them into the alignment of large-scale language models within the reinforcement learning from human feedback (RLHF) framework. The synergy of these findings underscores the successful application of GPT technology in this critical domain. Full article

Since the protocol for counterfactual quantum communication was proposed, complete counterfactuality can be achieved as there are no physical particles in the transmission channel. However, it relies on some restrictive factors, such as requiring an infinite number of beam splitters and no degradation. We conducted numerical simulations to assess the reliability of quantum communication combined with the actual test environment and found that the inevitable degradation, including component losses or path losses, limits the number of beam splitters. Furthermore, we carried out the experimental simulation of a high-reliability direct communication protocol using the method of controllable-signal attenuation. The peak reliability of ${\mu }_1=27.6\pm 0.22$ that was obtained was much higher than the current communication protocol of the chained interferometer system. The optimized experimental equipment could compensate the system’s balance under various restrictive conditions and make it possible to achieve 100% reliability with imperfect interferometers. Full article

Blue honeysuckle (Lonicera caerulea L.) is a deciduous shrub with perennial rootstock found in China. The objectives of this study were to explore the drought tolerance of blue honeysuckle, determine the effect of drought stress on two photosystems, and examine the mechanism of acquired drought tolerance. In this study, blue honeysuckle under four levels of simulated field capacity (100%, 85%, 75%, and 65% RH) was grown in split-root pots for drought stress treatment, for measuring the changes in chlorophyll content, photosynthetic characteristics, and leaf chlorophyll fluorescence parameters. The chlorophyll content of each increased under mild stress and decreased under moderate and severe stress. The net photosynthetic rate, transpiration rate, intercellular carbon dioxide concentration, and stomatal conductance of blue honeysuckle decreased with the increase in water stress. However, the water utilization rate and stomatal limit system increased under mild and moderate stress and decreased under severe stress. The maximum fluorescence (Fm), maximum photochemical efficiency, and quantum efficiency of photosystem II decreased with the decrease in soil water content, and the initial fluorescence increased significantly (p < 0.01). With the decrease in soil water content, the energy allocation ratio parameters decreased under severe drought stress. The main activity of the unit reaction center parameters first increased and then decreased. ABS/CSm, TRo/CSm, ETo/CSm, and REo/CSm gradually declined. After a comprehensive analysis, the highest scores were obtained under adequate irrigation (CK). Overall, we concluded that the water irrigation system of blue honeysuckle should be considered adequate. Full article

In this study, the PennyLane quantum device simulator was used to investigate quantum and hybrid, quantum/classical physics-informed neural networks (PINNs) for solutions to both transient and steady-state, $1D$ and $2D$ partial differential equations. The comparative expressibility of the purely quantum, hybrid and classical neural networks is discussed, and hybrid configurations are explored. The results show that (1) for some applications, quantum PINNs can obtain comparable accuracy with less neural network parameters than classical PINNs, and (2) adding quantum nodes in classical PINNs can increase model accuracy with less total network parameters for noiseless models. Full article

Extensive ab initio density functional theory molecular dynamics calculations were used to evaluate stability conditions for relevant phases of InN. In particular, the p-T conditions of the thermal decomposition of InN and pressure-induced wurtzite–rocksalt solid–solid phase transition were established. The comparison of the simulation results with the available experimental data allowed for a critical evaluation of the capabilities and limitations of the proposed simulation method. It is shown that ab initio molecular dynamics can be used as an efficient tool for simulations of phase transformations of InN, including solid–solid structural transition and thermal decomposition with formation of N₂ molecules. It is of high interest, because InN is an important component of epitaxial quantum structures, but it has not been obtained as a bulk single crystal. This makes it difficult to determine its basic physical properties to develop new applications. Full article

Context: Quantum software development is a complex and intricate process that diverges significantly from traditional software development. Quantum computing and quantum software are deeply entangled with quantum mechanics, which introduces a different level of abstraction and a deep dependence on quantum physical properties. The classical requirements engineering methods must be adapted to encompass the essential quantum features in this new paradigm. Aim: This study aims to systematically identify and analyze challenges, opportunities, developments, and new lines of research in requirements engineering for quantum computing. Method: We conducted a systematic literature review, including three research questions. This study included 105 papers published from 2017 to 2024. Results: The main results include the identification of problems associated with defining specific requirements for quantum software and hybrid system requirements. In addition, we identified challenges related to the absence of standards for quantum requirements engineering. Finally, we can see the advances in developing programming languages and simulation tools for developing software in hybrid systems. Conclusions: This study presents the challenges and opportunities in quantum computing requirements engineering, emphasizing the need for new methodologies and tools. It proposes a roadmap for future research to develop a standardized framework, contributing to theoretical foundations and practical applications. Full article

To address the potential threat to the power grid industry posed by quantum computers and ensure the security of bidirectional communication in smart grids, it is imperative to develop quantum-safe authentication protocols. This paper proposes a semi-quantum bidirectional authentication protocol between a control center (CC) and a neighboring gateway (NG). This method uses single photons to facilitate communication between the CC and the NG. Security analysis demonstrates that the protocol can effectively resist common attack methods, including double CNOT attacks, impersonation attacks, interception-measurement-retransmission attacks, and entanglement-measurement attacks. Comparisons with other protocols reveal that this protocol has significant advantages, making it more appealing and practical for real-world applications. Finally, by simulating the protocol on the IBM quantum simulator, this protocol not only validates the theoretical framework but also confirms the practical feasibility of the protocol. Full article

Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available number of physical qubits with high fidelity limit its application to small chemical systems. This work employed a quantum-classical framework which features a quantum active space-embedding approach to perform simulations of chemical reactions that require up to 14 qubits. This framework was applied to prototypical example metal hydrogenation reactions: the coupling between hydrogen and Li₂, Li₃, and Li₄ clusters. Particular attention was paid to the computation of barriers and reaction energies. The predicted reaction profiles compare well with advanced classical quantum chemistry methods, demonstrating the potential of the quantum embedding algorithm to map out reaction profiles of realistic gas-phase chemical reactions to ascertain qualitative energetic trends. Additionally, the predicted potential energy curves provide a benchmark to compare against both current and future quantum embedding approaches. Full article

This paper presents a quantum algorithm for solving the one-dimensional heat equation with Dirichlet boundary conditions. The algorithm utilizes discretization techniques and employs quantum gates to emulate the heat propagation operator. Central to the algorithm is the Trotter–Suzuki decomposition, enabling the simulation of the time evolution of the temperature distribution. The initial temperature distribution is encoded into quantum states, and the evolution of these states is driven by quantum gates tailored to mimic the heat propagation process. As per the literature, quantum algorithms exhibit an exponential computational speedup with increasing qubit counts, albeit facing challenges such as exponential growth in relative error and cost functions. This study addresses these challenges by assessing the potential impact of quantum simulations on heat conduction modeling. Simulation outcomes across various quantum devices, including simulators and real quantum computers, demonstrate a decrease in the relative error with an increasing number of qubits. Notably, simulators like the simulator_statevector exhibit lower relative errors compared to the ibmq_qasm_simulator and ibm_osaka. The proposed approach underscores the broader applicability of quantum computing in physical systems modeling, particularly in advancing heat conductivity analysis methods. Through its innovative approach, this study contributes to enhancing modeling accuracy and efficiency in heat conduction simulations across diverse domains. Full article

For silicon-based epitaxial quantum dot lasers (QDLs), the mismatches of the lattice constants and the thermal expansion coefficients lead to the generation of threaded dislocations (TDs), which act as the non-radiative recombination centers through the Shockley–Read–Hall (SRH) recombination. Based on a three-level model including the SRH recombination, the nonlinear properties of the silicon-based epitaxial QDLs under optical injection have been investigated theoretically. The simulated results show that, through adjusting the injection parameters including injection strength and frequency detuning, the silicon-based epitaxial QDLs can display rich nonlinear dynamical states such as period one (P1), period two (P2), multi-period (MP), chaos (C), and injection locking (IL). Relatively speaking, for a negative frequency detuning, the evolution of the dynamical state with the injection strength is more abundant, and an evolution path P1-P2-MP-C-MP-IL has been observed. Via mapping the dynamical state in the parameter space of injection strength and frequency detuning under different SRH recombination lifetime, the effects of SRH recombination lifetime on the nonlinear dynamical state of silicon-based epitaxial QDLs have been analyzed. Full article

The widely used Laurdan probe has two conformers, resulting in different optical properties when embedded in a lipid bilayer membrane, as demonstrated by our previous simulations. Up to now, the two conformers’ optical responses have, however, not been investigated when the temperature and the phase of the membrane change. Since Laurdan is known to be both a molecular rotor and a solvatochromic probe, it is subject to a profound interaction with both neighboring lipids and water molecules. In the current study, molecular dynamics simulations and hybrid Quantum Mechanics/Molecular Mechanics calculations are performed for a DPPC membrane at eight temperatures between 270K and 320K, while the position, orientation, fluorescence lifetime and fluorescence anisotropy of the embedded probes are monitored. The importance of both conformers is proven through a stringent comparison with experiments, which corroborates the theoretical findings. It is seen that for Conf-I, the excited state lifetime is longer than the relaxation of the environment, while for Conf-II, the surroundings are not yet adapted when the probe returns to the ground state. Throughout the temperature range, the lifetime and anisotropy decay curves can be used to identify the different membrane phases. The current work might, therefore, be of importance for biomedical studies on diseases, which are associated with cell membrane transformations. Full article

This paper presents the application of a compact and fully integrated LED quantum sensor based on the NV centers in diamond for current measurement in a busbar. The magnetic field measurements from the sensor are directly compared with measurements from a numerical simulation, eliminating the need for calibration. The sensor setup achieves an accuracy of 0.28% in the measurement range of 0–30 $\mathrm{A}$ DC. The integration of advanced quantum sensing technology with practical current measurement demonstrates the potential of this sensor for applications in electrical and distribution networks. Full article

Reversible computation is very important to minimize energy dissipation and prevent information loss not only in quantum computing but also in digital computing. Therefore, interest in designing efficient universal logic gates has recently increased. In this study, we efficiently design the Fredkin gate (FRG), a well-known conservative reversible operation gate, using quantum-dot cellular automata (QCA), and propose a D-latch using it. The proposed FRG structure can be designed efficiently using the structure of a QCA multiplexer using cell interaction, and a symmetric structure was designed. The proposed structure was simulated using QCADesigner 2.0.3 and QCADesigner-E for accurate comparison of various performance metrics, and the proposed structure clearly shows superiority in most performances and two representative design costs. Therefore, the lightweight design of an efficient reversible gate prevents data loss and increases information reliability. Full article

Ultrathin cells are gaining popularity due to their lower weight, reduced cost, and enhanced flexibility. However, compared to bulk cells, light absorption in ultrathin cells is generally much lower. This study presents a numerical simulation of a metamaterial light management structure made of ultrathin lead sulfide colloidal quantum dots (PbS CQDs) sandwiched between a top ITO grating and a tungsten backing to develop an efficient hybrid solar/thermophotovoltaic cell (HSTPVC). The optical properties were computed using both the finite integration technique (FIT) and the finite element method (FEM). The absorptance enhancement was attributed to the excitations of magnetic polaritons (MP), surface plasmon polaritons (SPP), and lossy mode resonance (LMR). The HSTPVC with the metamaterial optical light management structure was assessed for short-circuit current density, open-circuit voltage, and conversion efficiency. The results show a conversion efficiency of 18.02% under AM 1.5 solar illumination and a maximum thermophotovoltaic conversion efficiency of 12.96% at TB = 1600 K. The HSTPVC can operate in a hybrid solar/thermal conversion state when the ITO grating is included by combining the advantages of QDs and metamaterials. This work highlights the potential for developing a new generation of hybrid STPV cells through theoretical modeling and numerical simulations. Full article