Current state-of-the-art coherent fiber bundles, with core densities as high as 65,000 (65 k) cores/mm(2), are limited to a maximum number of 100 k cores. To address this limitation, this work presents a new fabrication approach for increasing the core count. This approach involves mechanically reshaping multiple existing circular bundles into hexagonal-like shapes and assembling them to form a large imaging array, with minimal dead-space (non-imaging region). The reshaping and assembly process is only applied to one end of the fiber bundles for reducing image dead-space, while the remaining length is untouched for retaining mechanical flexibility. Through applying this process to three existing 1 m length, 100 k core count fiber bundles, a combined imaging array consisting of 254 k (+/- 5%) cores over a total cross-sectional area of 3.94 mm(2) was fabricated. This core count is extremely close to the video graphics array (VGA) imaging standard consisting of 0.3 Megapixels. With this new approach, achieving flexible, high density imaging arrays with core counts approaching 1 million pixels, the high definition (HD) standard, is a real possibility in the upcoming decade.

Melt electrowriting (MEW) is a high-resolution additive manufacturing technology capable of depositing micrometric fibers onto a moving collector to form 3D scaffolds of controlled mechanical properties. While the critical role of layer bonding to achieve mechanical integrity in fused deposition modeling has been widely reported, it remains largely unknown in MEW, in part due to a lack of methods to assess it. Here, a systematic framework is developed to unravel the significance of layer bonding in MEW scaffolds and its ultimate effect on their mechanical properties. Results show that printing parameters, scaffold design, and print path have a strong impact on layer bonding strength of poly(ɛ-caprolactone) MEW scaffolds. This study demonstrates that a small increase of 5 µm in fiber diameter can enhance the layer bonding strength by as much as 70%, greatly impacting the overall scaffold properties. A method is also established to control MEW scaffold layer bonding using a heated collector. Importantly, this study reveals that scaffold architecture alone is not responsible for the overall mechanical properties. Finally, a method to obtain tailored layer bond strengths within a given scaffold is established. This has significant implications as provides new possibilities to control mechanical properties of MEW scaffolds through layer bonding.

Over the past three decades, silicon photonic devices have been core to the realization of large‐scale photonic‐integrated circuits. However, silicon nitride is another key complementary metal oxide semiconductor‐compatible material for high‐density photonic‐integrated circuits, having low manufacturing costs, low optical losses, and excellent mechanical properties, that can provide enhanced performance over silicon in an integrated photonic platform. This article presents the design, fabrication, and testing of a proof‐of‐concept switchable silicon nitride photonic coupler that leverages these properties combined with microelectromechanical systems actuation. The photonic platform uses a moveable suspended waveguide to enable efficient out‐of‐plane switching and is built using conventional lithographic techniques to demonstrate the high compatibility with existing microelectronic fabrication techniques. The photonic switch is measured to have an insertion loss of 2.6 dB and an ON/OFF extinction ratio of 34 dB at the output of the suspended waveguide, at a wavelength of 1470 nm. Detailed simulations demonstrate broadband operation over a 600 nm wavelength range from 1.25 to 1.85 μm which is experimentally validated over the range from 1.25 to 1.61 μm. To the best of knowledge, this is the broadest operation range ever demonstrated by a photonic switch in simulation.

While agile multispectral imaging solutions presently exist, their size, weight and power (SWaP) specifications prevents deployment on small portable platforms such as drones. As much of the size and weight of existing solutions is attributed to the wavelength-selective optical subsystem, realizing low-SWaP hinges on miniaturization of this subsystem. The ultimate multispectral imaging implementation would integrate the wavelength-selective component at the imaging focal plane array. This paper presents a solution which aims to achieve such integration. Recent developments in microelectromechanical systems (MEMS) have realized a surface-micromachined optical tunable filter, operating in the shortwave infrared wavelength band (SWIR: 1 mu m - 2.6 mu m) for applications in miniature optical spectrometers. The tunable filter is a Fabry-Perot (FP) structure, composed of a fixed dielectric mirror on a silicon substrate, and a movable dielectric mirror suspended above. The separation (air gap) between these two mirrors defines the optical transmission centre-wavelength of this Fabry Perot structure. Consequently, electrostatic actuation of the top mirror towards the bottom mirror allows the gap, and thus the transmission centre-wavelength, to be controlled. This paper presents work towards integration of such a MEMS tunable filter technology directly on an infrared focal plan array. Realizing this integration relies on: (1) expanding the optical area of the MEMS Fabry Perot structure to cover a significant portion of the two-dimensional focal plan array, which is generally multi-millimetre in each of its two dimensions; and (2) devising a structure that will allow actuation of the MEMS filter with under 20 V.

The Microelectronics Research Group (MRG) at The University of Western Australia is a key partner of the Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems. In this presentation, an overview of ongoing research will be given with an emphasis on the flagship research activities of MCT- based imaging arrays and Microelectromechanical Systems (MEMS). The MCT research and development utilise a vertically integrated capability from semiconductor material growth, through device modelling and design, to focal-plane-array fabrication and packaging. In support of the detector array capability, fully integrated MEMS technology can be used to further enhance the sensor device performance through the focal plane integration of tunable filters for spectral classification and infrared spectroscopy. The combination of high-performance detector designs and tunable spectral filters provides a major differentiator for military imaging systems, particularly for those operating in complex and degraded environments. This talk will highlight several research activities that are highly relevant to defence applications including metamaterial enhanced infra-red detectors, and the fabrication of infra-red focal plane arrays on flexible substrates. For the MEMS technology, both wideband and narrowband tunable spectral filters will be discussed for multispectral imaging in the SWIR, MWIR and LWIR bands, and for hyperspectral imaging and spectroscopy. Considerations on future research activities and technology trends will be presented including opportunities for the rapid development of high- performance and spectrally adaptive low SWaP sensing systems for enhanced detection and discrimination of partially concealed or camouflaged targets in cluttered backgrounds.

Porous silicon (PS) is often overlooked as a platform for creating large‐mode area waveguides suitable for optical sensing applications due to challenges around creating laterally confined (in‐plane) open‐pore waveguide structures in the PS film. Direct laser writing (DLW) in hydrocarbon atmospheres can selectively increase the refractive index of the PS film; however, this results in large amounts of absorbing pyrolytic carbon in the pores. The efficacy of postprocessing techniques to remove unwanted absorbing carbon species created by this method is investigated through energy‐dispersive X‐ray and Raman analysis. The results show that oxygen plasma ashing effectively removes carbon from the pores and considerably reduces propagation losses, resulting in the lowest reported laterally confined refractive index contrast in PS waveguides. The low‐index‐contrast PS waveguides are shown to require adequate insulation from the high‐index silicon substrate to further reduce propagation losses. The carbonized PS waveguide mode is modeled and resulting simulations show low alignment tolerance with a SMF‐28 fiber mode. Herein, a method is demonstrated for creating carbonized (passivated), open‐pore, and low‐loss buried waveguide structures in PS films with a low alignment tolerance to SMF‐28 fiber using a DLW approach in ethylene and propane atmospheres.

Direct laser writing (DLW) of mesoporous porous silicon (PS) films is shown to selectively create spatially separated nitridized and carbonized features on a single film. Nitridized or carbonized features are formed during DLW at 405 nm in an ambient of nitrogen and propane gas, respectively. The range of laser fluence required to create varying feature sizes while avoiding damage to the PS film is identified. At high enough fluence, nitridation using DLW has been shown as an effective method for laterally isolating regions on the PS films. The efficacy in preventing oxidation once passivated is investigated via energy dispersive X-ray spectroscopy. Changes in composition and optical properties of the DL written films are investigated using spectroscopic analysis. Results show carbonized DLW regions have a much higher absorption than as-fabricated PS, attributed to pyrolytic carbon or transpolyacetylene deposits in the pores. Nitridized regions exhibit optical loss similar to previously published thermally nitridized PS films. This work presents methods to engineer PS films for a variety of potential device applications, including the application of carbonized PS to selectively engineer thermal conductivity and electrical resistivity and of nitridized PS to micromachining and selective modification of refractive index for optical applications.

Porous silicon holds great promise as an optically and electrically tuneable material platform for high performance thermo-resistive sensing. Fulfilling this promise requires the ability to independently control the two critical parameters which determine the sensitivity (specifically the minimum temperature difference resolution) of thermal detectors: the temperature coefficient of resistance (TCR) and 1/f noise of the sensing material. In single porosity films these two properties are monolithically dependent, with both TCR and 1/f noise constant increasing with porosity. Here we show that use of multilayer films allows manipulation of properties of the overall structure to simultaneously achieve high TCR and low 1/f noise. Characterization of electrical properties of various porosity combinations revealed that using a two-layer heterostructure on Si substrate with low porosity (48 %) as the top layer and a high porosity (80 %) as the lower layer, both high TCR (similar to 4.4 %/K) and low 1/f noise constant (4 x 10(-13)) could be simultaneously achieved. This transforms the ability to exploit porous silicon for future high sensitivity based thermal detectors.

This work presents Apis-Prime,2a hybrid deep learning model for soft sensing and time series forecast-ing, to estimate the daily weight variations of honeybee hives. Apis-Prime improves the state-of-the-art of earlier proposed WE-Bee (Anwar et al., 2022), and also helps optimize the beehive monitoring systems for the task of daily weight variation estimation. Weight variations of a honeybee hive are the most important indicator of hive productivity, and the health and strength of a bee colony. Currently, precise measurement of the weight of a hive requires an expensive weighing scale under each hive. On the other hand, sensors deployed inside the hive are cheaper than a weighing scale, and are shielded from the extreme weather variations outside the hive. In this work, honeybee activity is monitored using data from sensors inside the hive, along with monitoring the information related to the seasons, time of the day, weather, and the size of the hive. Apis-Prime's deep learning algorithm is based on two self-attention encoders, which collectively transform the sensor data into daily weight variations of the hive. Two parallel encoders simultaneously pay attention to time-based relationships and feature-based relationships within the daily sensor data and generate daily hive weight estimates with better accuracy. The comparison shows an average error of 19.7 grams/frame for Apis-Prime, compared to 21.05 grams/frame for the earlier proposed model WE-Bee. For system optimization, this work uses the attention weights of trained encoders of Apis-Prime to evaluate the sensor features collected by the monitoring system. This evaluation is used to identify and remove the unnecessary sensors/features from the dataset, reducing the number of features from 36 to 23, hence providing a significant optimization of cost, power, and data bandwidth. We provide a performance analysis of beehive weight estimations by Apis-Prime using the complete, as well as the optimized dataset on 2,170 days of beehive sensor recordings. Equally good results of daily weight estimations using the optimized feature set demonstrate the efficacy of the proposed model for the optimization of the beehive monitoring system for the task of hive weight estimation.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Aluminum gallium nitride/gallium nitride (AlGaN/GaN) high electron mobility transistor (HEMT)-based sensors hold promise as small solid-state physical and chemical sensors because they can operate without a reference electrode and can be integrated into miniaturized sensor arrays. However, overextended time periods, low-frequency noise causes anomalous variations (drift) in sensor signal, especially in liquid environments. These effects occur despite electromagnetic interference mitigation. To understand the low-frequency noise, 1/ ${f}$ noise measurements between 0.1 and 100 kHz were undertaken, in both air and water, under constant pH and normal laboratory pressure conditions. The 1/ ${f}^{\gamma }$ noise for the device in water was larger in magnitude than in air, and estimates for the $\gamma $ -parameter in air and water were approximately 1 and 1.5, respectively. The corner frequency was observed between 100 and 1000 Hz. Based on this analysis, alternating current (ac) excitation at 1 kHz was applied to the conduction channel to compare the sensor stability in deionized water with dc operation. In this controlled test, the introduction of ac excitation resulted in a strong correlation of sensor signal with the ambient temperature variations over nearly 90 h of testing (effectively acting as a temperature sensor with a high degree of stability) while operation in dc mode resulted in largely no correlation with temperature. This indicates that ac excitation above the corner frequency is a potentially effective method to mitigate long-term sensor instability, a critical limitation for any AlGaN/GaN transistor-based physical or chemical sensors in aqueous environments.

Investigations into porous silicon thermo-resistive type thermal sensors and their advantages in speed-sensitivity trade-off relative to other comparable thermal materials are presented in this work. Porous silicon films were suspended above a silicon substrate using successive patterning and micromachining steps. The 3w method was used in both supported and suspended configurations, allowing the analysis of both cross-plane and in-plane thermal properties of the micromachined films. By utilising a low noise, broad-frequency measurement of the in-phase and out-of-phase temperature components, thermal conductivity and thermal diffusivity were simul-taneously determined. The measurements showed isotropic thermal conductivity of 0.38 +/- 0.02 W/m K and 0.12 +/- 0.01 W/m K, and thermal diffusivity of 0.39 +/- 0.04 mm2/s and 0.23 +/- 0.02 mm2/s, for the surface micro -machined released porous silicon films at 50 % and 77 % porosity, respectively. The implemented suspended 3w method leveraged a thermal model that accounted for the finite length of the heater (180 mu m) and membranes (400 mu m x 400 mu m), eliminating the millimetre scale dimensional constraints in previous works. Use of a thermal passivation technique rendered the thermal properties of the films robust against successive photolithography and micromachining. The obtained thermal properties were utilised in finite element modelling of a thermo-resistive thermal sensor with 50 mu m x 50 mu m x 100 nm dimensions. The modelling results suggest that a thermal time constant of 5 ms could be achieved, comparable to that of amorphous silicon based thermal sensors but with 2-4 times larger temperature sensitivity due to smaller intrinsic thermal conductivity and heat capacity in the porous silicon films, thus achieving a significant improvement in overall speed-sensitivity trade-off.

Novel micromachining processes were developed to produce optical filters operating in the long-wave infrared region (8-12 mu m). The filters were composed of a multilayer porous silicon top mirror and silicon bottom mirror separated by air cavity. Release of the top mirror membranes (with sizes ranging between 300 x 300 mu m(2) and 600 x 600 mu m(2)) was achieved using electropolishing. Inclusion of stress-relief notches in the top mirror (the suspended structure) improved both the flatness and the yield. Due to the high porosity of the films, a key finding was the need to reduce the plasma power during the etching process, to reduce damage to the film. The optical response of the device was evaluated by comparing the measured transmittance to the model, with favourable results confirming the future potential application of this technology for long wave infrared spectral filtering.

In this work, an approximate analytic formula is developed which accurately models the one-dimensional collapse kinetics of viscous glass tubes, driven by surface tension and low-to-moderate pressure differences. This is in contrast to existing analytic approaches from the literature where either surface tension is the only driving force, or extremely high pressure differences are assumed. Extensive model validation is provided against numerical computation of the exact one-dimensional and two-dimensional models for cross-sectional collapse, as well as with experimental data from the literature. Practical utility of this formula is demonstrated for effortlessly solving the inverse problem for determining the viscosity and surface tension of glass tubes.

Decision making capability of a system is highly dependent upon the quality and quantity of training data. Majority of beehive monitoring systems developed for research purposes are designed to collect data through a small set of sensors, and from locations with little geographic diversity. This hinders the development of a dataset that can be used to effectively train machine learning models. In this work, we explain the design and development of a multi-sensory, remote data acquisition system for beehives (BeeDAS), with focus on low-power consumption and long-range communication. We address design challenges associated with such systems and highlight the critical issues that need consideration. The proposed system enables collection of data from beehives at remote locations and harsh environment. Results of field deployments elucidate the effectiveness of various sensors which measure temperature, humidity, atmospheric pressure, CO2, acoustics, vibrations and the weight of a hive in hostile environment. This work also uses random forest regression to evaluate the feature importance of different sensors, environmental variables such as temperature, humidity, rain, wind speed as well as the information related to seasons, towards estimating the daily hive weight change, on a dataset comprised of 1,250 days of sensor recordings. We also evaluate the protocol designed for communication using Narrow Band Internet of Things (NB-IoT). The issues related to power optimization, sleep intervals and data storage in remote monitoring are also discussed.

Here the thermal transport properties of low thermal conductivity porous silicon thin films attached to high thermal conductivity silicon substrates are studied using the 3 omega method implemented over the 100 Hz to 33 kHz frequency range. The thermal conductivity and thermal diffusivity of the films are extracted using temperature impedance monitoring of electrical contacts deposited on films, combined with an extended-frequency, multi-layer thermal model. From the extracted thermal conductivity and diffusivity of the films, the heat capacity could be determined. Validation of the approach is performed using the known properties of thick substrate glass and SU-8 layers spun on silicon substrates, the lat -ter ranging in thickness from 1.35 to 12.5 sim. The technique was then applied to porous silicon films with porosities ranging from 45% to 77%. The extracted thermal properties for as-fabricated films show a reduction of thermal conductivity and diffusivity from 1.7 to 0.15 W/mK and 1.9 to 0.2 mm(2)/s, re-spectively as the porosity increases. After passivation by annealing in nitrogen and at 600 degrees C, the same films exhibited higher values of thermal conductivity and diffusivity ranging from 2.7 to 0.7 W/mK and 2.5 to 0.65 mm(2)/s. The ability to extract both thermal conductivity and thermal diffusivity for these films removes the need to make assumptions around specific heat capacity, commonly made during analysis of porous media. These results show for the first time a monotonic increase in specific heat capacity of porous silicon films as a function of porosity. (c) 2021 Elsevier Ltd. All rights reserved.

Elastic modulus and hardness of thin-films are critically important in determining the behaviour of free-standing actuatable microstructures. In this study, nanoindentation has been used to investigate the mechanical properties of thermally evaporated Ge and BaF2 thin-films. Nanoindentation experiments indicate that Ge and BaF2 thin-films are characterised by a reduced modulus of 95 ± 3 GPa and 33 ± 9 GPa, respectively, and hardness of 4.6 ± 0.4 GPa and 0.75 ± 0.4 GPa, respectively. The elastoplastic response of both thin-films was predominantly elastic for low indentation loads, but exhibited plasticity ≥ 60% for indentation loads approaching 8 mN. Indentation-induced creep deformation was found to be limited to ≤ 5%.

3D printing is evolving into a standard tool for prototyping various optical components suitable for application in the terahertz range of the electromagnetic spectrum. This work takes the next step in this evolution by demonstrating the fabrication and subsequent evaluation of Fabry – Pérot interferometers (FPIs). Large optical area (centimetre scale) Fabry–Pérot transmission filters have been 3D printed with polylactic acid (PLA) using a commonly used low-cost 3D printer. The advantages of the proposed approach include low cost, rapid prototyping and repeatability. Terahertz transmission measurements for two demonstrated filter designs realised to target optimisation of either signal transmission or spectral filter performance have been performed using terahertz time-domain spectroscopy (THz-TDS) and demonstrate good agreement with the simulated response in the operating spectral band of 0.30–0.75 THz (wavelengths from 1000 down to 400 μm). The critical spectral characteristics assessed were the filter peak transmission magnitude, central wavelength and full width at half-maximum (FWHM) of the transmission peak, as well as the free spectral range (FSR). The signal transmission levels were observed to reach beyond 90% for the first series of filters that targeted optimisation of this aspect; however, this was accompanied by diminished out-of-band rejection and broader transmission peaks in comparison to the second series of filters which targeted the overall performance. For the latter filter series, the resolution in terms of FWHM values of the transmission peaks was reduced to 40–50 GHz, with the out-of-band rejection approaching a ratio of 10:1. This level of spectral performance, along with the achieved signal peak transmission characteristics of 65–75%, provides adequate performance for many applications harnessing the terahertz spectral range.

High performance distributed Bragg reflectors (DBRs) are key elements to achieving high finesse MEMS-based Fabry-Perot interferometers (FPIs). Suitable mechanical parameters combined with high contrast between the refractive indices of the constituent optical materials are the main requirements. In this paper, Germanium (Ge) and barium fluoride (BaF2) optical thin-films have been investigated for mid-wave infrared (MWIR) and long-wave infrared (LWIR) filter applications. Thin-film deposition and fabrication processes were optimised to achieve mechanical and optical properties that provide flat suspended structures with uniform thickness and maximum reflectivity. Ge-BaF2-Ge 3-layer solid-material DBRs have been fabricated that matched the predicted simulation performance, although a degradation in performance was observed for wavelengths beyond 10 mu m that is associated with optical absorption in the BaF2 material. Ge-Air-Ge 3-layer air-gap DBRs, in which air rather than BaF2 served as the low refractive index layer, were realized to exhibit layer flatness at the level of 10 to 20 nm across lateral DBR dimensions of several hundred micrometers. Measured DBR reflectance was found to be greater than or similar to 90% over the entire wavelength range of the MWIR band and for the LWIR band up to a wavelength of 11 mu m. Simulations based on the measured DBR reflectance indicates that MEMS-based FPIs are able to achieve a peak transmission of greater than or similar to 90% over the entire MWIR band and up to 10 mu m in the LWIR band, with a corresponding spectral passband of less than or similar to 50 nm in the MWIR and less than or similar to 80 nm in the LWIR. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License.