Photoluminescence enhancement with all-dielectric coherent metasurfaces

Mie resonances have recently attracted much attention in research on dielectric metasurfaces, owning to their enriched multipole resonances, negligible optical loss, and efficient light emitter integration. Although there is a rapid advancement in this field, some fundamental developments are still required to provide a simpler and more versatile paradigm for photoluminescence (PL) control. In this work, we proposed that an all-dielectric coherent metasurface can engineer the PL response by tuning the array size. Such PL manipulation is attributed to the collective Mie resonances that mediate the inter-unit interactions between unit elements and alter the PL intensity. Metasurfaces with different chip sizes are utilized to explore the array size effect on the collective Mie resonances, field enhancement, and Q-factor in TiO2 metasurfaces. Incorporating the all-dielectric coherent metasurface with fluorescent photon emitters, we performed the dependence of PL enhancement on array size, which achieves an enhancement factor of ∼10 at the central area of a 90 × 90 μm2 TiO2 metasurface array. These findings provide an additional degree of freedom to engineer the near-field confinement and enhancement, allowing one to manipulate incoherent photon emission and tune light–matter interaction at the nanoscale.

Unsupervised Online Assessment of Visual Working Memory in 4- to 10-Year-Old Children: Array Size Influences Capacity Estimates and Task Performance

The events of the COVID-19 Pandemic forced many psychologists to abandon lab-based approaches and embrace online experimental techniques. Although lab-based testing will always be the gold standard of experimental precision, several protocols have evolved to enable supervised online testing for paradigms that require direct observation and/or interaction with participants. However, many tasks can be completed online in an unsupervised way, reducing reliance on lab-based resources (e.g., personnel and equipment), increasing flexibility for families, and reducing participant anxiety and/or demand characteristics. The current project demonstrates the feasibility and utility of unsupervised online testing by incorporating a classic change-detection task that has been well-validated in previous lab-based research. In addition to serving as proof-of-concept, our results demonstrate that large online samples are quick and easy to acquire, facilitating novel research questions and speeding the dissemination of results. To accomplish this, we assessed visual working memory (VWM) in 4- to 10-year-old children in an unsupervised online change-detection task using arrays of 1–4 colored circles. Maximum capacity (max K) was calculated across the four array sizes for each child, and estimates were found to be on-par with previously published lab-based findings. Importantly, capacity estimates varied markedly across array size, with estimates derived from larger arrays systematically underestimating VWM capacity for our youngest participants. A linear mixed effect analysis (LME) confirmed this observation, revealing significant quadratic trends for 4- through 7-year-old children, with capacity estimates that initially increased with increasing array size and subsequently decreased, often resulting in estimates that were lower than those obtained from smaller arrays. Follow-up analyses demonstrated that these regressions may have been based on explicit guessing strategies for array sizes perceived too difficult to attempt for our youngest children. This suggests important interactions between VWM performance, age, and array size, and further suggests estimates such as optimal array size might capture both quantitative aspects of VWM performance and qualitative effects of attentional engagement/disengagement. Overall, findings suggest that unsupervised online testing of VWM produces reasonably good estimates and may afford many benefits over traditional lab-based testing, though efforts must be made to ensure task comprehension and compliance.

A Simplified Ground Thermal Response Model for Analyzing Solar-Assisted Ground Source Heat Pump Systems

Ground source heat pump systems that are installed in areas with heating or cooling dominant seasons, or in buildings with utilization characteristics that lead to a disparity in demand, often encounter challenges related to ground thermal imbalance. This imbalance can lead to long-term ground temperature changes and may cause premature system failure. This paper focuses on combining a ground source heat pump system with a solar thermal array, with the goal of eliminating the effect of ground thermal imbalance, and minimizing system lifetime cost. A thermal mass ground heat transfer model is combined with a time-stepping model to analyze the system for a variety of solar array sizes. The details associated with this modelling technique are presented, and case studies are provided to illustrate the results of the calculations for three different buildings. It is shown that increasing the solar array size can offset ground thermal imbalances, but increasing the array size also results in a larger initial system cost. An economic analysis is then carried out to determine the system lifetime cost as a function of this solar array size, and an optimal array size from an economic perspective was found. The result of the study shows that hybridizing a ground source heat pump system with a solar array produces a viable system from a technical and economic standpoint, can be used to avoid premature system failure, and can reduce system lifetime cost.

A Simplified Ground Thermal Response Model for Analyzing Solar-Assisted Ground Source Heat Pump Systems

Ground source heat pump systems that are installed in areas with heating or cooling dominant seasons, or in buildings with utilization characteristics that lead to a disparity in demand, often encounter challenges related to ground thermal imbalance. This imbalance can lead to long-term ground temperature changes and may cause premature system failure. This paper focuses on combining a ground source heat pump system with a solar thermal array, with the goal of eliminating the effect of ground thermal imbalance, and minimizing system lifetime cost. A thermal mass ground heat transfer model is combined with a time-stepping model to analyze the system for a variety of solar array sizes. The details associated with this modelling technique are presented, and case studies are provided to illustrate the results of the calculations for three different buildings. It is shown that increasing the solar array size can offset ground thermal imbalances, but increasing the array size also results in a larger initial system cost. An economic analysis is then carried out to determine the system lifetime cost as a function of this solar array size, and an optimal array size from an economic perspective was found. The result of the study shows that hybridizing a ground source heat pump system with a solar array produces a viable system from a technical and economic standpoint, can be used to avoid premature system failure, and can reduce system lifetime cost.

Optimal Transponder Array and Survey Line Configurations for GNSS-A Observation Evaluated by Numerical Simulation

The Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) has enabled us to measure seafloor crustal deformation in the precision of centimeters, leading to numerous discoveries of subseafloor tectonic phenomena. The moving observation conducted by our research group allows us to measure both the horizontal and vertical absolute positions of a reference point on the seafloor. However, the observation frequency of our GNSS-A observation system is still insufficient to observe short-term phenomena. This paper focused on the possibility to reduce the observation time per a seafloor site by shrinking the seafloor transponder array size and the survey line radius, which were empirically defined to be equal to the seafloor site depth in the early research. We evaluated the effects of changing these sizes on the GNSS-A positioning accuracy by conducting a series of numerical experiments. The results of the numerical experiments indicated that for a seafloor site with a depth of 3,000 m, the positioning accuracy is rapidly degraded as the transponder array size and the survey line radius are reduced to less than 3,000 m. Additional experiments done for transponder array sizes and survey line radii around 2,000–4,000 m revealed that shrinking the survey line radius has a dominant effect on the decrease in positioning accuracy. Thus, shrinking the transponder array size and the survey line radius is not a suitable option for reducing observation time, and the empirically defined observation configurations are concluded to be quite optimal when regarding both the positioning accuracy and the observation time.

Ground-Based Augmentation System Antenna Array Size Reduction via Self-Cardioid Element

A Ground-Based Augmentation System (GBAS) monitors the signals of Global Navigation Satellite Systems and broadcasts differential correction signals. It relies on Multipath Limiting Antennas (MLAs) that can receive signals over almost the entire upper hemisphere while greatly attenuating signals reflected from the ground. The current Federal Aviation Administration (FAA)-approved system utilizes an MLA that is approximately 182.9 cm tall. In this paper, a substitute MLA is designed that is only 97.05 cm tall (approximately 44% reduction). The size reduction is accomplished by reducing the number of array elements from 19 to 11. We developed a novel self-cardioid antenna element that allows for this reduction.

Estimating the optimum size of a tidal array at a multi-inlet system considering environmental and performance constraints

This paper investigates the optimum tidal energy converter array density at a tidal inlet by applying surrogate-based optimisation. The SBO procedure comprises problem formulation, design of experiments, numerical simulations, surrogate model construction and constrained optimisation. This study presents an example for the Faro-Olhão Inlet in the Ria Formosa (Portugal), a potential site for tidal in-stream energy extraction. A 35 kW EvopodTM floating tidal energy converter from Oceanflow Energy Ltd. has been used for array size calculations considering two design variables: 1) number of array rows, and 2) number of tidal energy converter per row. Arrays up to 13 rows with 6 to 11 tidal energy converters each are studied to assess their impacts on array performance, inlets discharges and bathymetry changes. The analysis identified the positive/negative feedbacks between the two design variables in real case complex flow fields under variable bathymetry and channel morphology. The non-uniformity of tidal currents along the array region causes the variability of the resource in each row, as well as makes it difficult to predict the resultant array configuration interactions. Four different multi-objective optimisation models are formulated subject to a set of performance and environmental constraints. Results from the optimisation models imply that the largest array size that meets the environmental constraints is made of 5 rows with 6 tidal energy converter each and an overall capacity factor of 11.6% resulting in an energy production of 1.01 GWh/year. On the other hand, a higher energy production (1.20 GWh/year) is achieved by an optimum array configuration, made of 3 rows with 10 tidal energy converters per row, which maximises power output satisfying environmental and performance restrictions. This optimal configuration permits a good level of energy extraction while having a reduced effect on the hydrodynamic functioning of the multi-inlet system. These results prove the suitability and the potential wide use of the surrogate-based optimisation method to define array characteristics that enhance power production and at the same time respect the environmental surrounding conditions.

A general approach to optimizing tumor treating fields therapy.

e14668 Background: Tumor Treating Fields (TTFields) are alternating electric fields used to non-invasively treat cancer. TTFields are delivered via transducer arrays placed on the skin close to the tumor. Post-hoc analysis [1] has shown that delivering higher field power to the tumor and increasing usage (percent of time patient is actively treated) improve patient survival. Thus, optimizing the position of arrays to maximize TTFields power at the tumor could improve survival. At the same time, minimizing the array area to maximize patient comfort and consequently maximizing usage is also likely to improve survival. However, optimizing TTFields delivery is non-trivial since the field distribution is influenced by array positioning and geometry, the anatomy of the patient and the heterogeneous electric properties of different tissues. Here we present a general approach to optimizing Tumor Treating Fields using numerical simulations. Methods: Delivery of TTFields to the brains, lungs and abdomens of realistic computational models was investigated. The effect of the transducer array size and position on the field distribution within the phantoms was analyzed, and an approach for optimizing TTFields delivery developed. Results: Field power is generally highest in the region between the arrays, with larger arrays generally delivering higher field power. Anatomical features such as bones, the spine or a resection cavity significantly influence the field within this region. A general approach to optimizing TTFields delivery is: Maximize field power by using the largest arrays possible. To maximize patient comfort, array size are chose so that significant portions of the skin in the region of disease are not covered by the arrays. Place virtual arrays on a realistic computational model of the patient such that the tumor is located between them and simulate TTFields delivery to the patient. Apply an iterative algorithm to shift the arrays around their initial positions until field power in the tumor bed is maximized. Conclusions: We have developed a general approach to optimizing delivery of TTFields to the tumor. Effective TTFields treatment planning is expected to improve patient outcome. [1] Ballo et. al., submitted to RED Journal 2018.