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Item Influence of annealing on thin film/substrate interface and vacuum ultraviolet photoconductivity of neodymium fluoride thin films(Wiley Online, 2024-02-13) Kato, T.; Raduban, Marilou; Horiuchi, Y.; Ozawa, G.; Ono, S.; Unitec, Te Pūkenga; Nagoya Institute of TechnologyAbstract High photon energy vacuum ultraviolet radiation (VUV, 100?200 nm wavelength) is challenging to detect. It easily degrades conventional silicon and semiconductor photodetectors. Fluoride photodetectors can be the answer, but the correlation between fabrication parameters and photodetector performance is not known. Here, the effect of annealing is investigated on the characteristics of neodymium trifluoride thin film/quartz substrate interface and NdF3 photoconductivity within the VUV. Thin films are deposited on unheated and heated (600 °C) substrates with post-deposition annealing. Dark current of films on unheated substrates decreases by as much as 1/10 as resistance increases from 1 ?12 TΩ after annealing. Dark current of films on heated substrates increases even after annealing, resulting in similar photo and dark currents of ≈303.7 nA and poor detectors. Fluorine diffuses from the film to the substrate during deposition, exacerbated by substrate heating but not by annealing. Fluorine diffusion degrades crystallinity near the interface, increasing the dark current. Fluorine diffusion is absent when MgF2 is used as the heated substrate. Unannealed NdF3/MgF2 detector on 600 °C-heated substrate and 600 °C-annealed NdF3/SiO2 detector on unheated substrate exhibit similar resistances of ≈14 TΩ. Considering the film/substrate interface and annealing is crucial when developing VUV photodetectors.Item Influence of annealing on thin film/substrate interface and vacuum ultraviolet photoconductivity of neodymium fluoride thin films(Wiley, 2024-02-13) Kato, T.; Raduban, Marilou; Horiuchi, Y.; Ozawa, G.; Ono, S.; Unitec, Te Pūkenga; Ngoya Institute of TechnologyHigh photon energy vacuum ultraviolet radiation (VUV, 100−200 nm wavelength) is challenging to detect. It easily degrades conventional silicon and semiconductor photodetectors. Fluoride photodetectors can be the answer, but the correlation between fabrication parameters and photodetector performance is not known. Here, the effect of annealing is investigated on the characteristics of neodymium trifluoride thin film/quartz substrate interface and NdF3 photoconductivity within the VUV. Thin films are deposited on unheated and heated (600 °C) substrates with post-deposition annealing. Dark current of films on unheated substrates decreases by as much as 1/10 as resistance increases from 1 −12 TΩ after annealing. Dark current of films on heated substrates increases even after annealing, resulting in similar photo and dark currents of ≈303.7 nA and poor detectors. Fluorine diffuses from the film to the substrate during deposition, exacerbated by substrate heating but not by annealing. Fluorine diffusion degrades crystallinity near the interface, increasing the dark current. Fluorine diffusion is absent when MgF2 is used as the heated substrate. Unannealed NdF3/MgF2 detector on 600 °C-heated substrate and 600 °C-annealed NdF3/SiO2 detector on unheated substrate exhibit similar resistances of ≈14 TΩ. Considering the film/substrate interface and annealing is crucial when developing VUV photodetectors.Item Estimating emissions from tyre tread wear of motor vehicles in New Zealand(ePress, Unitec | Te Pūkenga, 2024-07-23) Kudin, Roman; Singh, Niranjan; Chand, Prabhat; Bakmeedeniya, Anura; Tawaketini, Jone; Unitec, Te Pūkenga; Te PūkengaOver 5.6 million road vehicles are registered in New Zealand, with a wide range of contaminants released as a result of their operation. The material wearing out from tyre tread has previously been identified as a contaminant of potential concern (COPC) in New Zealand, but its amount has not been quantified. Numerous studies confirm that the wear rate of a tyre depends on multiple factors and can vary significantly, even for the same type of vehicle with the same tyres installed. Such factors have already been classified and weighted; therefore, they were not the subject of the current research. The aim of this study is to estimate the total amount of material released into the environment in New Zealand due to the tread wear of tyres. In this research, the New Zealand motor vehicle fleet was divided into categories according to the available statistical data. The estimation of the amount of the tyre material released into the environment was done separately in each category of vehicle, using the three-point method (Low, Medium and High). The calculation was performed using the statistical average annual distances driven by vehicles, and the tyre abrasion rates, also called emission factors (mg/km). The emission factors were adopted through a thorough review of the available studies of tyre abrasion rates in different countries. The three-point estimate shows that every year roughly 6.5 to 15.5 thousand tonnes of material from tyre tread wear is released into the environment in New Zealand, which gives between 1.26 and 2.97 kg when converted per capita. Such quantification is an important step in understanding the impacts of this contaminant on New Zealand ecosystems. Further research of tyre tread wear material is needed with regard to its emission factors; deposition, migration and concentrations in environmental compartments; accumulation and degradation paths; effects on living organisms and human health.Item Field study to compare and evaluate summer thermal comfort of school buildings with different moderate thermal mass in their building elements(MDPI (Multidisciplinary Digital Publishing Institute), 2023-11-22) Su, Bin; McPherson, Peter; Jadresin-Milic, Renata; Wang, Xinxin; Shamout, Sameh; Liang, Y.; Unitec, Te Pūkenga; Architon (N.Z.)Previous studies show that moderate thermal mass in school building elements can pos itively impact the winter indoor thermal environment in a temperate climate with mild, humid winters. Based on a field study, this research contributes new physical data of the summer indoor thermal environment of Auckland school buildings with different designs of moderate thermal mass in their building elements to add to the previous winter field-study data and demonstrates that a school building with moderate thermal mass is adequate in a temperate climate with mild, humid winters and warm, dry summers. This field study compared and evaluated the summer indoor thermal environment of classrooms with different moderate thermal mass in their building elements during the summer school term and the summer school holidays. This study found that a classroom with thermal mass in its building elements has 19% to 21% more time in summer than a classroom without any thermal mass in its building elements when indoor air temperatures are within the thermal comfort zone, which was solely impacted by the building’s thermal performance. This study established a suitable research method to analyse the field-study data and identify the differences in the indoor thermal environments of the school buildings with different designs of moderate thermal mass in their building element.Item Pavement crack classification using deep convolutional neural network(College of Engineering, Universiti Teknologi MARA (UiTM), 2021-11-15) Osman, M.K.; Mohammed Zamree, M.E.A.; Idris, M.; Ahmad, K.A.; Mohamed Yusof, N.A.; Ibrahim, A.; Hasnur Rabiain, A.; Bahri, Intan; Unitec Institute of Technology; Politeknik Tunku Sultanah Bahiyah (Malaysia); UiTM Cawangan Pulau Pinang (Malaysia); THB Maintenance Sdn. Bhd. (Malaysia)Road safety is one of the more difficult aspects concerning the field of civil engineering. Manual road inspection and distress detection by a road surveyor is a time-consuming, dangerous, and laborious process. This paper proposes an automated method to classify three common types of road distress; namely crocodile, longitudinal and transverse cracks using a deep convolution neural network. Four processes are involved to include data collection, cracked photo enhancement, cracks classification and performance evaluation. The first process of data collection involves capturing pavement crack images using a digital camera. Secondly, the crack images are labelled according to their group and their contrast further improved using the contrast limited adaptive histogram equalization (CLAHE) method. The third process involves training the deep convolutional neural network (DCNN). In this process, two (2) DCNN models are devised which are VGG16 and 9-Layer CNN models. Simulation results show that VGGG-16 with CLAHE enhancement were able to classify pavement cracks with high accuracy, precision, recall and F1-scores of 99.5%, 98.5%, 99.5% and 98.99% respectively. Through deep learning techniques, the VGGG-16 with CLAHE has demonstrated promising potential in classifying pavement cracks.