Facile and low cost hydrothermal routes are developed to fabricate three-dimensional (3D) hierarchical ZnO structures with high surface-to-volume ratios and an increased fraction of (0001) polar surfaces. Hierarchical ZnO nanowires (ZNWs) and nanodisks (ZNDs) assembled from initial ZnO nanostructures are prepared from sequential nucleation and growth following a hydrothermal process. These hierarchical ZnO structures display an enhancement of gas sensing performance and exhibit significantly improved sensitivity and fast response to acetone in comparison to other mono-morphological ZnO, such as nanoparticles, NWs, or NDs. In addition to the high surface-to-volume ratio due to its small size, the nanowire building blocks show the enhanced gas sensing properties mainly ascribed to the increased proportion of exposed active (0001) planes, and the formation of many nanojunctions at the interface between the initial ZnO nanostructure and secondary NWs. This work provides the route for structure induced enhancement of gas sensing performance by designing a desirable nanostructure, which could also be extended to synthesize other metal oxide nanostructures with superior gas sensing performance.

ZnO nanostructures with different morphologies (nanowires, nanodisks, and nanostars) were synthesized hydrothermally. Gas sensing properties of the as-grown nanostructures were investigated under thermal and UV activation. The performance of the ZnO nanodisk gas sensor was found to be superior to that of other nanostructures (S_g ∼ 3700% to 300 ppm ethanol and response time and recovery time of 8 and 13 s). The enhancement in sensitivity is attributed to the surface polarities of the different structures on the nanoscale. Furthermore, the selectivity of the gas sensors can be achieved by controlling the UV intensity used to activate these sensors. The highest sensitivity value for ethanol, isopropanol, acetone, and toluene are recorded at the optimal UV intensity of 1.6, 2.4, 3.2, and 4 mW/cm², respectively. Finally, the UV activation mechanism for metal oxide gas sensors is compared with the thermal activation process. The UV activation of analytes based on solution processed ZnO structures pave the way for better quality gas sensors.

Developing rationally controlled bottom-up device fabrication processes is essential for the achievement of high performance optimal devices. We report a controlled, seedless and site-selective hydrothermal technique to fabricate high-performance nanostructured ZnO UV-detectors directly on-chip. We demonstrate that by controlling the nanowire growth process, via tuning the experimental parameters such as the concentration of reactants and the growth time and by introducing a refresh of the growth solution, the device structure efficiency can be enhanced to significantly improve its performance. The on-chip fabricated bridging nanosyringe ultraviolet detector demonstrates improved sensitivity (~10⁵), nanowatts detectability and ultrafast response-time (90 ms) and recovery-time (210 ms). The improvement in response-time and recovery-time is attributed to the unique nanowire-nanowire junction barrier dominated resistance and the direct contact between ZnO and Au electrodes. Furthermore, the enhanced sensitivity and nanowatts detectability of the bridging nanosyringe device are due to the reduction in dimensionality and ultrahigh surface-to-volume ratio. This work paves the way toward low cost, large scale, low temperature, seedless and site-selective fabrication of high performance ZnO nanowire sensors on flexible and transparent substrates.

The rapidly increasing population growth and expansion of urban development are undoubtedly two of the main reasons for increasing global energy consumption. Accurate long-term forecasting of peak load is essential for saving time and money for countries’ power generation utilities. This paper introduces the first investigation into the performance of the Prophet model in the long-term peak load forecasting of Kuwait. The Prophet model is compared with the well-established Holt–Winters model to assess its feasibility and accuracy in forecasting long-term peak loads. Real data of electric load peaks from Kuwait powerplants from 2010 to 2020 were used for the electric load peaks, forecasting the peak load between 2020 and 2030. The Prophet model has shown more accurate predictions than the Holt–Winters model in five statistical performance metrics. Besides, the robustness of the two models was investigated by adding Gaussian white noise of different intensities. The Prophet model has proven to be more robust to noise than the Holt–Winters model. Furthermore, the generalizability test of the two models has shown that the Prophet model outperforms the Holt–Winters model. The reported results suggest that the forecasted maximum peak load is expected to reach 18,550 and 19,588 MW for the Prophet and Holt–Winters models by 2030 in Kuwait. The study suggests that the best months for scheduling the preventive maintenance for the year 2020 and 2021 are from November 2020 until March 2021 for both models.

Solution processed core–shell nano-structures of metal oxide-reduced graphene oxide (RGO) are used as improved electron transport layers (ETL), leading to an enhancement in photocurrent charge transport in PCDTBT:PC₇₀BM for both single cell and module photovoltaic devices. As a result, the power conversion efficiency for the devices with RGO-metal oxides for ETL increases 8% in single cells and 20% in module devices.