Tetrabutylammonium Bromide Functionalized Ti3C2Tx MXene as Versatile Cathode Buffer Layer for Efficient and Stable Inverted Perovskite Solar Cells

2D Ti₃C₂T_x MXene, possessing facile preparation, high electrical conductivity, flexibility, and solution processability, shows good application potential for enhancing device performance of perovskite solar cells (PVSCs). In this study, tetrabutylammonium bromide functionalized Ti₃C₂T_x (TBAB-Ti₃C₂T_x) is developed as cathode buffer layer (CBL) to regulate the PCBM/Ag cathode interfacial property for the first time. By virtue of the charge transfer from TBAB to Ti₃C₂T_x demonstrated by electron paramagnetic resonance and density functional theory, the TBAB-Ti₃C₂T_x CBL with high electrical conductivity exhibits significantly reduced work function of 3.9 eV, which enables optimization of energy level alignment and enhancement of charge extraction. Moreover, the TBAB-Ti₃C₂T_x CBL can effectively inhibit the migration of iodine ions from perovskite layer to Ag cathode, which synergistically suppresses defect states and reduce charge recombination. Consequently, utilizing MAPbI₃ perovskite without post-treatment, the TBAB-Ti₃C₂T_x based device exhibits a dramatically improved power conversion efficiency of 21.65% with significantly improved operational stability, which is one of the best efficiencies reported for the devices based on MAPbI₃/PCBM with different CBLs. These results indicate that TBAB-Ti₃C₂T_x shall be a promising CBL for high-performance inverted PVSCs and inspire the further applications of quaternary ammonium functionalized MXenes in PVSCs.     

Noble Metal Ion-Directed Assembly of 2D Materials for Heterostructured Catalysts and Metallic Micro-Texturing

Assembling 2D-material (2DM) nanosheets into micro- and macro-architectures with augmented functionalities requires effective strategies to overcome nanosheet restacking. Conventional assembly approaches involve external binders and/or functionalization, which inevitably sacrifice 2DM's nanoscale properties. Noble metal ions (NMI) are promising ionic crosslinkers, which can simultaneously assemble 2DM nanosheets and induce synergistic properties. Herein, a collection of NMI–2DM complexes are screened and categorized into two sub-groups. Based on the zeta potentials, two assembly approaches are developed to obtain 1) NMI-crosslinked 2DM hydrogels/aerogels for heterostructured catalysts and 2) NMI–2DM inks for templated synthesis. First, tetraammineplatinum(II) nitrate (TPtN) serves as an efficient ionic crosslinker to agglomerate various 2DM dispersions. By utilizing micro-textured assembly platforms, various TPtN–2DM hydrogels are fabricated in a scalable fashion. Afterward, these hydrogels are lyophilized and thermally reduced to synthesize Pt-decorated 2DM aerogels (Pt@2DM). The Pt@2DM heterostructures demonstrate high, substrate-dependent catalytic activities and promote different reaction pathways in the hydrogenation of 3-nitrostyrene. Second, PtCl₄ can be incorporated into 2DM dispersions at high NMI molarities to prepare a series of PtCl₄–2DM inks with high colloidal stability. By adopting the PtCl₄–graphene oxide ink, various Pt micro-structures with replicated topographies are synthesized with accurate control of grain sizes and porosities.     

Simultaneous CO2 and H2O Activation via Integrated Cu Single Atom and N Vacancy Dual-Site for Enhanced CO Photo-Production

Photocatalytic conversion of CO₂ into fuels using pure water as the proton source is of immense potential in simultaneously addressing the climate-change crisis and realizing a carbon-neutral economy. Single-atom photocatalysts with tunable local atomic configurations and unique electronic properties have exhibited outstanding catalytic performance in the past decade. However, given their single-site features they are usually only amenable to activations involving single molecules. For CO₂ photoreduction entailing complex activation and dissociation process, designing multiple active sites on a photocatalyst for both CO₂ reduction and H₂O dissociation simultaneously is still a daunting challenge. Herein, it is precisely construct Cu single-atom centers and two-coordinated N vacancies as dual active sites on CN (Cu₁/N_2CV-CN). Experimental and theoretical results show that Cu single-atom centers promote CO₂ chemisorption and activation via accumulating photogenerated electrons, and the N_2CV sites enhance the dissociation of H₂O, thereby facilitating the conversion from COO* to COOH*. Benefiting from the dual-functional sites, the Cu₁/N_2CV-CN exhibits a high selectivity (98.50%) and decent CO production rate of 11.12 µmol g⁻¹ h⁻¹. An ingenious atomic-level design provides a platform for precisely integrating the modified catalyst with the deterministic identification of the electronic property during CO₂ photoreduction process.     

Optimization of Quantum Cost for Low Energy Reversible Signed/Unsigned Multiplier Using Urdhva-Tiryakbhyam Sutra

One of the elementary operations in computing systems is multiplication. Therefore, high-speed and low-power multipliers design is mandatory for efficient computing systems. In designing low-energy dissipation circuits, reversible logic is more efficient than irreversible logic circuits but at the cost of higher complexity. This paper introduces an efficient signed/unsigned 4 × 4 reversible Vedic multiplier with minimum quantum cost. The Vedic multiplier is considered fast as it generates all partial product and their sum in one step. This paper proposes two reversible Vedic multipliers with optimized quantum cost and garbage output. First, the unsigned Vedic multiplier is designed based on the Urdhava Tiryakbhyam (UT) Sutra. This multiplier consists of bitwise multiplication and adder compressors. Compared with Vedic multipliers in the literature, the proposed design has a quantum cost of 111 with a reduction of 94% compared to the previous design. It has a garbage output of 30 with optimization of the best-compared design. Second, the proposed unsigned multiplier is expanded to allow the multiplication of signed numbers as well as unsigned numbers. Two signed Vedic multipliers are presented with the aim of obtaining more optimization in performance parameters. DesignI has separate binary two’s complement (B2C) and MUX circuits, while DesignII combines binary two’s complement and MUX circuits in one circuit. DesignI shows the lowest quantum cost, 231, regarding state-of-the-art. DesignII has a quantum cost of 199, reducing to 86.14% of DesignI. The functionality of the proposed multiplier is simulated and verified using XILINX ISE 14.2.     

Thermodynamic assessment of RuO4 oxide

RuO₄ oxide appears much less stable than RuO₂(s) in the Ru–O binary system with a melting point close to room temperature and a certain propensity to vaporize or decompose at low temperatures. Ab initio simulations in the framework of density functional theory (DFT) on RuO₄(s) are performed to analyze the cubic and monoclinic structures and to evaluate the heat capacities at low temperatures. Then, a critical evaluation of thermodynamic data from calorimetry and vapor pressure determinations - was carried out coupled with ab-initio calculations to propose new thermodynamic data: the entropy.S° (RuO_4, s, cubic, 298K) = 132.7 J·K⁻¹mol⁻¹ and formation enthalpy.Δ_fH° (RuO₄, s, cubic, 298K) = −252.4 ± 5.5 kJ mol⁻¹.     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.     

Almost sure stability of stochastic neutral Cohen–Grossberg neural networks with Lévy noise and time-varying delays

The almost sure stability for the stochastic neutral Cohen–Grossberg neural networks (SNCGNNs) with Lévy noise, time-varying delays, and Markovian switching would be deliberated in this article. By means of the nonnegative semimartingale convergence theorem (NSCT), the neutral Itô formula, M-matrix method, and selecting appropriate Lyapunov function, several almost sure stability criterions for the SNCGNNs could be derived. Moreover, according to the M-matrix theory, the upper bounds of the coefficients at any mode are given. Finally, two examples and numerical simulations verify the correctness of theoretical analysis for the stability criterions proposed in the article.     

Spatial-temporal analysis of safety risks in trajectories of construction workers based on complex network theory

Understanding the traffic patterns of construction workers on high-risk construction sites is important for implementing behaviour-based safety management. However, safety risks in worker trajectories are a complex system with high uncertainty. This resulted in few studies focusing on analysing the spatial–temporal risk in workers' trajectories from a systematic perspective. This study designs a new framework to explore the spatial–temporal patterns of safety risks in the trajectories of construction workers based on complex network theory. First, an integrated site safety risk classification method by combining hazard sources and group trajectory distribution is developed to accurately describe the spatial distribution of site risks. Second, a new complex network chronnet is used to construct complex networks containing risk information for spatial–temporal analysis. Finally, key risk areas and risk transition patterns are identified through the analysis of network measures. The study also developed a computational program that allows the network to be constructed and analysed in real-time. The feasibility and effectiveness of the method are verified through a case study. The results show that the method can reveal the risk distribution at the micro level, and explore the risk clustering and transition features in worker trajectories at the macro level. The study allows for an accurate analysis of dynamic risk patterns in construction workers' trajectories from a systematic perspective. It can also provide theoretical and practical support for personalized and adaptive behaviour-based safety management for construction workers.     

Indirect Exciton–Phonon Dynamics in MoS2 Revealed by Ultrafast Electron Diffraction

Transition metal dichalcogenides layered nano-crystals are emerging as promising candidates for next-generation optoelectronic and quantum devices. In such systems, the interaction between excitonic states and atomic vibrations is crucial for many fundamental properties, such as carrier mobilities, quantum coherence loss, and heat dissipation. In particular, to fully exploit their valley-selective excitations, one has to understand the many-body exciton physics of zone-edge states. So far, theoretical and experimental studies have mainly focused on the exciton–phonon dynamics in high-energy direct excitons involving zone-center phonons. Here, ultrafast electron diffraction and ab initio calculations are used to investigate the many-body structural dynamics following nearly- resonant excitation of low-energy indirect excitons in MoS₂. By exploiting the large momentum carried by scattered electrons, the excitation of in-plane K- and Q- phonon modes are identified with 𝑬^′ symmetry as key for the stabilization of indirect excitons generated via near-infrared light at 1.55 eV, and light is shed on the role of phonon anharmonicity and the ensuing structural evolution of the MoS₂ crystal lattice. The results highlight the strong selectivity of phononic excitations directly associated with the specific indirect- exciton nature of the wavelength-dependent electronic transitions triggered in the system.