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Borophene and silicene, two novel members of the Xene family, feature high surface reactivity and stability suitable for sensing applications. However, the gas sensing capabilities of these materials in their pristine form have not been systematically investigated. Here we show that borophene- and silicene-based quartz crystal microbalance (QCM) sensors achieve stable and sensitive relative humidity detection and we model their adsorption-desorption mechanisms. Borophene and silicene nanosheets were synthesized via liquid-phase exfoliation and characterized by transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, and Brunauer-Emmett-Teller surface area analysis. The QCM sensors exhibited sensitivities of 3.2 Hz/%RH and 3.9 Hz/%RH, response/recovery times of 122/65 s and 47/130 s and hysteresis of 1.8% and 3.8% hysteresis for borophene and silicene, respectively. The dominant sensing mechanism was determined to be chemisorption, supported by thermodynamic modeling. These results suggest that 2D borophene and silicene can significantly contribute to sensing applications, especially in environments requiring air stability.

To be used as efficient alpha particle scintillator in the fields of nuclear security, nuclear nonproliferation and high-energy physics, scintillator screens must have high light output and fast decay properties. While there has been a great deal of progress in scintillation efficiency, achieving fast decay time properties are still a challenge. In this work, the near band edge (NBE) UV luminescence and alpha particle induced scintillation properties of vertically aligned densely packed ZnO nanorods (NRs) doped with Al, Ga, and In have been thoroughly investigated. The high crystalline hexagonal wurtzite structure with a strong orientation through the c-axis plane (002) and aspect ratios in the range 13-22 have been observed for all ZnO NRs. Electron paramagnetic resonance (EPR) analysis exhibited paramagnetic signals at g ≈ 1.96 for all ZnO NRs. A cost effective green hydrothermal synthesis technique was employed to grow well-aligned NRs. Using citrate as an additive acting as a strong reducing agent in the solution during the crystal growth, defects on the surface are significantly suppressed, thereby enhancing the NBE UV emission. Significantly higher NBE UV emission was observed from the top surface of ZnO NRs in cathodoluminescence (CL) microscopy. Results show that citrate assisted donor doping of ZnO NRs not only reduces the defect emission and NBE self-absorption, but also induces fast decay time (~ 600-700 ps), which makes ZnO NRs a good candidate for fast alpha particle scintillator screens used in associated particle imaging for time and direction tagging of individual neutrons generated in D-T and D-D neutron generators.

With the gradual improvement of electromagnetic protection of equipment and electromagnetic pollution prevention requirements, carbon heterostructured wave-absorbing nanomaterials have become a research hotspot due to their tunable electromagnetic properties, high stability, and lightweight advantages. In this paper, we comprehensively and deeply discuss the multi-scale construction of carbon nano-absorbent materials, and elaborate on the design strategy and research progress from the micro-, meso- and macro-levels. At the microscopic level, the structure of carbon materials is controlled at the nanoscale by means of intrinsic structural design, elemental doping and interfacial modulation to introduce more microstructural defects to enhance the polarisation and scattering of electromagnetic waves, thereby improving the wave-absorbing performance. The mesoscopic level focuses on the modulation of the micro-nano multilevel structure of carbon absorbers, such as the in situ multilevel assembly of MXene, MOFs and heterogeneous continuous fibers at the mesoscopic scale, which is conducive to the enhancement of the absorber's conductivity and interfacial loss to enhance its wave-absorbing ability. The macroscopic level focuses on structure-function integrated design, such as 3D porous structures, sandwich honeycomb structures, and surface superstructures, which enable the materials to possess excellent mechanical properties along with good wave-absorbing properties. The comprehensive use of these design strategies to optimize the whole design chain of wave-absorbing materials is conducive to maximizing the performance and application value of the materials. The aim of this paper is to elucidate the effect of multiscale heterostructures on carbon-based wave-absorbing materials, which provides a reference for the precise design of their wave-absorbing properties.

We examine the performance of nanomechanical resonators for mass and stiffness sensing of nanoparticulate analytes with focus on their application for untargeted infectious virus detection. The characteristic narrow mass distributions of viruses, together with the existing correlations between their stiffness and infectivity, point out to nanomechanical sensors as a particularly suited alternative to molecular detection techniques, constrained by limited processing speed, target-specificity, and the inability to directly assess infectivity. We present a theoretical analysis of the response of flexural beam resonators to the adsorption of nanoparticulate analytes, and derive analytical expressions for the mass and stiffness sensing responsivity, resolution and signal to noise ratio as a function of the beam characteristics and analyte adsorption parameters. We demonstrate that both the mass and stiffness of viruses can contribute to resonance frequency shifts that significantly exceed the fundamental detection limits of beams with plausible dimensions and for realistic adsorption parameters. Particularly, stiffness resolution can reach levels well below the stiffness variations observed in some viruses as a consequence of maturation, enabling an integrated approach for infectivity assessment. We conclude that the practical application of nanomechanical spectrometry for infectious virus detection is not limited by the performance of state-of-the-art sensor technology, but by the efficiency of analyte delivery methods, encouraging future research on optimizing their implementation.

The selective photocatalytic epoxidation of propylene using molecular oxygen under UV-A irradiation presents a promising sustainable alternative for propylene oxide (PO) production. In this study, NiO/TiO₂ and CuO/NiO/TiO₂ heterojunction photocatalysts were synthesized via the thermal annealing of sol-gel-derived TiO₂ and tested in a fluidized bed photoreactor. Structural and optical characterizations confirmed the successful deposition of NiO onto TiO₂ and highlighted the crucial role of NiO content in optimizing charge separation and catalytic efficiency. Among the NiO/TiO₂ series, the NiO(1.1%)/TiO₂ composite exhibited the lowest photoluminescence intensity, indicating reduced electron-hole recombination, while UV-Vis DRS analysis revealed a red shift in the absorption onset and a reduction in the band gap energy. These features resulted in enhanced light absorption and facilitated charge transfer, leading to superior photocatalytic performance compared to lower and higher NiO loadings. Under irradiation, NiO(1.1%)/TiO₂ achieved a propylene conversion of 52.5%, a selectivity to PO of 83.4%, and a PO yield of 43.8%, confirming its effectiveness in promoting selective epoxidation. The introduction of CuO to form the CuO(1.1%)/NiO(1.1%)/TiO₂ heterojunction further enhanced the catalytic performance, reaching 61% propylene conversion, 92% selectivity to PO, and a PO yield of 56%. The improved activity was attributed to the efficient conversion of molecular oxygen into hydrogen peroxide, which acts as a selective oxidant for epoxide formation. Process optimization revealed that water vapor (1000 ppm) significantly enhanced PO selectivity, while incident light intensity played a crucial role in determining conversion rates. The system exhibited excellent stability over 24 h of continuous operation, with no observable deactivation. Furthermore, an energy efficiency analysis demonstrated an exceptionally low energy consumption of 0.019 kWh per mole of propylene converted, significantly outperforming existing photocatalytic systems. These findings highlight the potential of CuO/NiO/TiO₂-based photocatalysts, combined with fluidized bed reactors, as an energy-efficient and scalable approach for sustainable PO production.

Psoriasis is a chronic inflammatory autoimmune skin disease with enhanced skin cell turnover. Despite the therapies currently available, better and target-oriented therapies are needed. Fisetin is a flavonoid with antioxidant, anti-inflammatory, and immunomodulatory properties. It shows therapeutic potential, but its poor bioavailability and penetration into the skin cannot be used effectively to treat psoriasis. While fisetin-loaded nanoformulations in cancer and other diseases have been explored, their potential as a therapy for psoriasis is unexplored. Most reviews detail the biological activities of fisetin or nanoformulations for psoriasis therapy but not their combination. The review here compiles fisetin's chemical and pharmacological properties along with the problems with conventional drug delivery and fisetin-loaded nanoformulations such as polymeric nanoparticles, liposomes, solid lipid nanoparticles, nanogels, and micelles. It also discusses their mechanisms, preclinical results, and potential for the clinic. Preclinical studies demonstrate fisetin nanoformulations to enhance penetration into the skin, reduce inflammation, promote skin regeneration in psoriasis models, and alleviate symptoms of redness and scaling. Clinical trials are lacking, and studies are needed to assess safety and efficacy. Fisetin nanoformulations are a potential target-oriented psoriasis therapy with better drug delivery and fewer side effects than conventional therapies. Despite formulation stability, scalability, and regulatory issues, the potential for fisetin-loaded nanoformulations is excellent and needs further exploration for their safety and efficacy in patients.

Photothermal therapy (PTT) represents a promising advance in oncological treatments, utilizing light-induced heat mediated by photothermal agents to target and destroy cancer cells with high precision. Despite its potential, the clinical application of PTT is often limited by the efficiency of photothermal agents and their biocompatibility, highlighting a crucial need for novel materials that can safely and effectively convert light into therapeutic heat. This study demonstrates the two-dimensional Bi₂Se₃ nanosheets with tailored nanostructure via a solvothermal process. This study controls over their structural and photothermal properties by accurately optimizing synthesis conditions. In situ experiments provide insights into the crystallographic and phonon characteristics at varying temperatures, underscoring the thermal stability of Bi₂Se₃ nanosheets. Notably, these nanosheets demonstrate a high photothermal conversion efficiency, rapidly raising the tumor site temperature to 53.1 °C within 180 s, resulting in rapid tumor cell ablation. Significant tumor growth suppression is also observed, with the median survival of mice treated with the particle and light combination extending to 34 days. These findings confirm the stable in vivo thermal properties of Bi₂Se₃ nanosheets, establishing them as a potent candidate for future photothermal therapy applications.

Green nanoparticles are economically beneficial and do not harm the environment as they are eco-friendly when compared with chemically synthesized silver nanoparticles. Contamination of food and food products with micro-organisms can cause food spoilage and food-borne diseases. This research mainly focuses on United Nations Sustainable Development Goals (SDGs 2, 3, 6, 9, 12), particularly in the areas of health, food safety, and sustainable innovation. The aim of the study was to synthesize Moringa oleifera flower mediated silver nanoparticles to control the growth and biofilm formation in isolated food - borne pathogens. The fresh extract obtained from the flowers of Moringa oleifera has been utilized for the synthesis of silver nanoparticles (Mo-AgNPs). The Mo-AgNPs were characterized by using various analytical techniques. In silico analysis has been carried out to know the binding potential of phytocompounds of Moringa oleifera with the virulent proteins of bacterial strains. The toxicity effect of Mo-AgNPs was evaluated by using seed germination studies with the seeds of Vigna radiata and evaluated the toxicity effect in Artemia nauplii based on its mortality rate. The novelty of the work is to evaluate the antibacterial efficacy of the synthesized Mo-AgNPs, antimicrobial assays including agar well diffusion, Minimum Inhibition Concentration (MIC), Minimum Bactericidal Concentration (MBC) and Biofilm formation assay were performed in the bacterial strains isolated from spoiled food. Mo-AgNPs confirmed its nanosize by depicting the particle size as 12.73 nm with 0.115 mV. Mo-AgNPs showed potential benefit for plant growth and exhibited toxicity to Artemia nauplii at higher concentration. The maximum concentrations of Mo-AgNPs that inhibit and kill the isolated food - borne pathogens were 3.125 and 50 µg/ml respectively. Mo-AgNPs effectively reduced the biofilm formation in all the tested strains. Molecular docking studies confirmed that the Ellagic acid has the least value of - 8.6 and - 8.9 kcal/mol with beta lactamase of Enterobacter cloacae and beta lactamase OXY1 of Klebsiella oxytoca respectively. Quercetin, Apigenin, Riboflavin and kaempferol have lower values of - 7.7, - 7.6, - 7.8 and - 7 kcal/mol (Enterobacter cloacae) and - 8.3, - 7.8, - 7.9 and - 7.7 kcal/mol (Klebsiella oxytoca), respectively. Through this study it was proven that the synthesized Mo-AgNPs could have the potential to fight against the bacterial pathogens that are responsible for food - borne diseases and food spoilage. In the future, Mo-AgNPs can be utilized to develop food packaging biomaterials that can increase the shelf life and prevent food from spoilage.

In nanostructure extraction, advanced techniques like synchrotron radiation and electron microscopy are often hindered by radiation damage and charging artifacts from long exposure times. This study presents a multiframe superresolution method using sparse coding to enhance synchrotron radiation microspectroscopy images. By reconstructing high-resolution images from multiple low-resolution ones, exposure time is minimized, reducing radiation effects, thermal drift, and sample degradation while preserving spatial resolution. Unlike deep learning-based superresolution methods, which overlook positional misalignment, our approach treats positional shifts as known control parameters, enhancing superresolution accuracy with a small, noisy dataset. Additionally, our sparse coding method learns an optimal dictionary tailored for nanostructure extraction, fine-tuning the SR process to the unique characteristics of the data, even with noise and limited samples. Applied to 3D nanoscale electron spectroscopy for chemical analysis (nano-ESCA) data, our method, utilizing a high-resolution dictionary learned from 3D nano-ESCA datasets, significantly improves image quality, preserving structural details. Unlike state-of-the-art deep learning techniques that require large datasets, our method excels with limited data, making it ideal for real-world scenarios with constrained sample sizes. High-resolution quality can be maintained while reducing the measurement time by over [Formula: see text], highlighting the efficiency of our approach. The results underscore the potential of this superresolution technique to not only advance synchrotron radiation microspectroscopy but also to be adapted for other high-resolution imaging modalities, such as electron microscopy. This approach offers enhanced image quality, reduced exposure times, and improved interpretability of scientific data, making it a versatile tool for overcoming the challenges associated with radiation damage and sample degradation in nanoscale imaging.

Neuromorphic computing is an emerging architype representing a cutting-edge approach to computing that emulates the structure and function of human brain, leveraging neuroscience concepts to develop efficient, adaptive, and power conscious computing system surpassing the von Neumann architecture. Herein, we report artificial synaptic device defined on a paper using ${\text{MoO}}_3$ embedded Aloe vera matrix as an active material. The multilayer graphene electrode (MLG) is drawn using pencil-on-paper (PoP) method. Devices could be programmed for multi bit-states to avail several conducting states ( $2^n$ with n = 1,2,3,4). Further, the devices can be operated at low energy consumption ( $\sim$ pJ) stable at ambient conditions. Activity dependent measurements show that the synaptic weight update depends on the history of activity. The potentiation and depression can be tuned by properly choosing the prior activity. The threshold frequency at which transition into potentiation occurs is shifted towards lower frequency and depends on the number of prior activities. The potentiation and depression curves indicate that the nonlinearity can be controlled by utilizing non-identical pulse sequences. The pencil-on-paper (PoP) method could represent a new frontier in electronic devices leading to the development of portable, environment friendly, and flexible synaptic devices for versatile synaptic and memory applications.