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1. Hyperspectral imaging for high-throughput, spatially resolved spectroscopic scatterometry of silicon nanopillar arrays

   https://doi.org/10.1364/OE.388158  

   Gawlik, Brian ; Barrera, Crystal ; Yu, Edward T. ; Sreenivasan, S. V. ( April 2020 , Optics Express)

   Modern high-throughput nanopatterning techniques, such as nanoimprint lithography, make it possible to fabricate arrays of nanostructures (features with dimensions of 10’s to 100’s of nm) over large area substrates (cm²to m²scale) such as Si wafers, glass sheets, and flexible roll-to-roll webs. The ability to make such large-area nanostructure arrays (LNAs) has created an extensive design space, enabling a wide array of applications including optical devices, such as wire-grid polarizers, transparent conductors, color filters, and anti-reflection surfaces, and building blocks for electronic components, such as ultracapacitors, sensors, and memory storage architectures. However, existing metrology methods will have trouble scaling alongside fabrication methods. Scanning electron microscopy (SEM) and atomic force microscopy (AFM), for instance, have micron scale fields of view (FOV) that preclude comprehensive characterization of LNAs, which may be manufactured at m²per minute rates. Scatterometry approaches have larger FOVs (typically 100’s of µm to a few mm), but traditional scatterometry systems measure samples one point at a time, which also makes them too slow for large-scale LNA manufacturing. In this work, we demonstrate parallelization of the traditional spectroscopic scatterometry approach using hyperspectral imaging, increasing the throughput of the technique by a factor of 10⁶-10⁷. We demonstrate this approach by using hyperspectral imaging and inverse modeling of reflectance spectra to derive 3-dimensional geometric data for Si nanopillar array structures over both mm and cm-scale with µm-scale spatial resolution. This work suggests that geometric measurements for a variety of LNAs can be performed with the potential for high speed over large areas which may be critical for future LNA manufacturing.

    

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2. Transparent InGaZnO-Based Resistive Random Access Memory

   Qin, Fei ; Lee, Sunghwan ( May 2022 , Materials Research Society)

   The major focus of artificial intelligence (AI) research is made on biomimetic synaptic processes that are mimicked by functional memory devices in the computer industry [1]. It is urgent to find a memory technology for suiting with Brain-Inspired Computing to break the von Neumann bottleneck which limits the efficiency of conventional computer architectures [2]. Silicon-based flash memory, which currently dominates the market for data storage devices, is facing challenging issues to meet the needs of future data storage device development due to the limitations, such as high-power consumption, high operation voltage, and low retention capacity [1]. The emerging resistive random-access memory (RRAM) has elicited intense research as its simple sandwiched structure, including top electrode (TE) layer, bottom electrode (BE) layer, and an intermediate resistive switching (RS) layer, can store data using RS phenomenon between the high resistance state (HRS) and the low resistance state (LRS). This class of emerging devices is expected to outperform conventional memory devices [3]. Specifically, the advantages of RRAM include low-voltage operation, short programming time, great cyclic stability, and good scalability [4]. Among the materials for RS layer, indium gallium zinc oxide (IGZO) has attracted attention because of its abundance and high atomic diffusion property of oxygen atoms, transparency, and its easily modulated electrical properties by controlling the stoichiometric ratio of indium and gallium as well as oxygen potential in the sputter gas [5, 6]. Moreover, since the IGZO can be applied to both the thin-film transistor (TFT) channel and RS layer, the IGZO-based fully integrated transparent electronics are very promising [5]. In this work, we proposed transparent IGZO-based RRAMs. First, we chose ITO to serve as both TE and BE to achieve high transmittance in the visible regime of light. All three layers (TE, RS, BE layers) were deposited using a multi-target magnetron sputtering system on glass substrates to demonstrate fully transparent oxide-based devices. I-V characteristics were evaluated by a semiconductor parameter analyzer, and our devices showed typical butterfly curves indicating the bipolar RS property. And the IGZO-based RRAM can survive more than 50 continuous sweeping cycles. The optical transmission analysis was carried out via an UV-Vis spectrometer and the average transmittance around 80% out of entire devices in the visible-light wavelength range, implying high transparency. To investigate the thickness dependence on the properties of RS layer, 50nm, 100nm and 150nm RS layer of IGZO RRAM were fabricated. Also, the oxygen partial pressure during the sputtering of IGZO was varied to optimize the property because the oxygen vacancy concentration governs the RS and RRAM performance. Electrode selection is crucial and can impact the performance of the whole device [7]. Thus, Cu TE was chosen for our second type of device because the diffusion of Cu ions can be beneficial for the formation the conductive filament (CF). Finally, a ~5 nm SiO2 barrier layer was employed between TE and RS layers to confine the diffusion of Cu into the RS layer. At the same time, this SiO2 inserting layer can provide an additional interfacial series resistance in the device to lower the off current, consequently, improve the on/off ratio and whole performance. In conclusion, the transparent IGZO-based RRAMs were established. To tune the property of RS layer, the thickness layer and sputtering conditions of RS were adjusted. In order to engineer the diffusion capability of the TE material to the RS layer and the BE, a set of TE materials and a barrier layer were integrated in IGZO-based RRAM and the performance was compared. Our encouraging results clearly demonstrate that IGZO is a promising material in RRAM applications and overcoming the bottleneck of current memory technologies. 

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3. LCPOM: Precise Reconstruction of Polarized Optical Microscopy Images of Liquid Crystals

   Chen, Chuqiao ; Palacio-Betancur, Viviana ; Norouzi, Sepideh ; Zubieta Rico, Pablo F. ; Sadati, Monirosadat ; Rowan, Stuart J. ( July 2023 , arXivorg)

   When viewed with a cross-polarized optical microscope (POM), liquid crystals display interference colors and complex patterns that depend on the material's microscopic orientation. That orientation can be manipulated by application of external fields, which provides the basis for applications in optical display and sensing technologies. The color patterns themselves have a high information content. Traditionally, however, calculations of the optical appearance of liquid crystals have been performed by assuming that a single-wavelength light source is employed, and reported in a monochromatic scale. In this work, the original Jones matrix method is extended to calculate the colored images that arise when a liquid crystal is exposed to a multi-wavelength source. By accounting for the material properties, the visible light spectrum and the CIE color matching functions, we demonstrate that the proposed approach produces colored POM images that are in quantitative agreement with experimental data. Results are presented for a variety of systems, including radial, bipolar, and cholesteric droplets, where results of simulations are compared to experimental microscopy images. The effects of droplet size, topological defect structure, and droplet orientation are examined systematically. The technique introduced here generates images that can be directly compared to experiments, thereby facilitating machine learning efforts aimed at interpreting LC microscopy images, and paving the way for the inverse design of materials capable of producing specific internal microstructures in response to external stimuli. 

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4. (Digital Presentation) Investigation of Top Electrodes Impact on Performance of Transparent Amorphous Indium Gallium Zinc Oxide (a-InGaZnO) Based Resistive Random Access Memory

   https://doi.org/10.1149/MA2022-01191075mtgabs  

   Qin, Fei ; Lee, Sunghwan ( July 2022 , ECS Meeting Abstracts)

   The traditional von Neumann architecture limits the increase in computing efficiency and results in massive power consumption in modern computers due to the separation of storage and processing units. The novel neuromorphic computation system, an in-memory computing architecture with low power consumption, is aimed to break the bottleneck and meet the needs of the next generation of artificial intelligence (AI) systems. Thus, it is urgent to find a memory technology to implement the neuromorphic computing nanosystem. Nowadays, the silicon-based flash memory dominates non-volatile memory market, however, it is facing challenging issues to achieve the requirements of future data storage device development due to the drawbacks, such as scaling issue, relatively slow operation speed, and high voltage for program/erase operations. The emerging resistive random-access memory (RRAM) has prompted extensive research as its simple two-terminal structure, including top electrode (TE) layer, bottom electrode (BE) layer, and an intermediate resistive switching (RS) layer. It can utilize a temporary and reversible dielectric breakdown to cause the RS phenomenon between the high resistance state (HRS) and the low resistance state (LRS). RRAM is expected to outperform conventional memory device with the advantages, notably its low-voltage operation, short programming time, great cyclic stability, and good scalability. Among the materials for RS layer, indium gallium zinc oxide (IGZO) has shown attractive prospects in abundance and high atomic diffusion property of oxygen atoms, transparency. Additionally, its electrical properties can be easily modulated by controlling the stoichiometric ratio of indium and gallium as well as oxygen potential in the sputter gas. Moreover, since the IGZO can be applied to both the thin-film transistor (TFT) channel and RS layer, it has a great potential for fully integrated transparent electronics application. In this work, we proposed amorphous transparent IGZO-based RRAMs and investigated switching behaviors of the memory cells prepared with different top electrodes. First, ITO was choosing to serve as both TE and BE to achieve high transmittance. A multi-target magnetron sputtering system was employed to deposit all three layers (TE, RS, BE layers) on glass substrate. I-V characteristics were evaluated by a semiconductor parameter analyzer, and the bipolar RS feature of our RRAM devices was demonstrated by typical butterfly curves. The optical transmission analysis was carried out via a UV-Vis spectrometer and the average transmittance was around 80% out of entire devices in the visible-light wavelength range, implying high transparency. We adjusted the oxygen partial pressure during the sputtering of IGZO to optimize the property because the oxygen vacancy concentration governs the RS performance. Electrode selection is crucial and can impact the performance of the whole device. Thus, Cu TE was chosen for our second type of device because the diffusion of Cu ions can be beneficial for the formation of the conductive filament (CF). A ~5 nm SiO 2 barrier layer was employed between TE and RS layers to confine the diffusion of Cu into the RS layer. At the same time, this SiO 2 inserting layer can provide an additional interfacial series resistance in the device to lower the off current, consequently, improve the on/off ratio and whole performance. Finally, an oxygen affinity metal Ti was selected as the TE for our third type of device because the concentration of the oxygen atoms can be shifted towards the Ti electrode, which provides an oxygengettering activity near the Ti metal. This process may in turn lead to the formation of a sub-stoichiometric region in the neighboring oxide that is believed to be the origin of better performance. In conclusion, the transparent amorphous IGZO-based RRAMs were established. To tune the property of RS layer, the sputtering conditions of RS were varied. To investigate the influence of TE selections on switching performance of RRAMs, we integrated a set of TE materials, and a barrier layer on IGZO-based RRAM and compared the switch characteristics. Our encouraging results clearly demonstrate that IGZO is a promising material in RRAM applications and breaking the bottleneck of current memory technologies. 

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5. Augmented reality head-up displays effect on drivers’ spatial knowledge acquisition

   https://doi.org/10.1177/1071181319631287  

   de Oliveira Faria, Nayara ; Kandil, Dina ; Gabbard, Joseph L. ( November 2019 , Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Background: Drivers gather most of the information they need to drive by looking at the world around them and at visual displays within the vehicle. Navigation systems automate the way drivers navigate. In using these systems, drivers offload both tactical (route following) and strategic aspects (route planning) of navigational tasks to the automated SatNav system, freeing up cognitive and attentional resources that can be used in other tasks (Burnett, 2009). Despite the potential benefits and opportunities that navigation systems provide, their use can also be problematic. For example, research suggests that drivers using SatNav do not develop as much environmental spatial knowledge as drivers using paper maps (Waters & Winter, 2011; Parush, Ahuvia, & Erev, 2007). With recent growth and advances of augmented reality (AR) head-up displays (HUDs), there are new opportunities to display navigation information directly within a driver’s forward field of view, allowing them to gather information needed to navigate without looking away from the road. While the technology is promising, the nuances of interface design and its impacts on drivers must be further understood before AR can be widely and safely incorporated into vehicles. Specifically, an impact that warrants investigation is the role of AR HUDS in spatial knowledge acquisition while driving. Acquiring high levels of spatial knowledge is crucial for navigation tasks because individuals who have greater levels of spatial knowledge acquisition are more capable of navigating based on their own internal knowledge (Bolton, Burnett, & Large, 2015). Moreover, the ability to develop an accurate and comprehensive cognitive map acts as a social function in which individuals are able to navigate for others, provide verbal directions and sketch direction maps (Hill, 1987). Given these points, the relationship between spatial knowledge acquisition and novel technologies such as AR HUDs in driving is a relevant topic for investigation. Objectives: This work explored whether providing conformal AR navigational cues improves spatial knowledge acquisition (as compared to traditional HUD visual cues) to assess the plausibility and justification for investment in generating larger FOV AR HUDs with potentially multiple focal planes. Methods: This study employed a 2x2 between-subjects design in which twenty-four participants were counterbalanced by gender. We used a fixed base, medium fidelity driving simulator for where participants drove while navigating with one of two possible HUD interface designs: a world-relative arrow post sign and a screen-relative traditional arrow. During the 10-15 minute drive, participants drove the route and were encouraged to verbally share feedback as they proceeded. After the drive, participants completed a NASA-TLX questionnaire to record their perceived workload. We measured spatial knowledge at two levels: landmark and route knowledge. Landmark knowledge was assessed using an iconic recognition task, while route knowledge was assessed using a scene ordering task. After completion of the study, individuals signed a post-trial consent form and were compensated $10 for their time. Results: NASA-TLX performance subscale ratings revealed that participants felt that they performed better during the world-relative condition but at a higher rate of perceived workload. However, in terms of perceived workload, results suggest there is no significant difference between interface design conditions. Landmark knowledge results suggest that the mean number of remembered scenes among both conditions is statistically similar, indicating participants using both interface designs remembered the same proportion of on-route scenes. Deviance analysis show that only maneuver direction had an influence on landmark knowledge testing performance. Route knowledge results suggest that the proportion of scenes on-route which were correctly sequenced by participants is similar under both conditions. Finally, participants exhibited poorer performance in the route knowledge task as compared to landmark knowledge task (independent of HUD interface design). Conclusions: This study described a driving simulator study which evaluated the head-up provision of two types of AR navigation interface designs. The world-relative condition placed an artificial post sign at the corner of an approaching intersection containing a real landmark. The screen-relative condition displayed turn directions using a screen-fixed traditional arrow located directly ahead of the participant on the right or left side on the HUD. Overall results of this initial study provide evidence that the use of both screen-relative and world-relative AR head-up display interfaces have similar impact on spatial knowledge acquisition and perceived workload while driving. These results contrast a common perspective in the AR community that conformal, world-relative graphics are inherently more effective. This study instead suggests that simple, screen-fixed designs may indeed be effective in certain contexts. 

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