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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Non-planar platinum group metal-free fuel cell cathodes for enhanced oxygen transport and water rejection

Proton exchange membrane fuel cells (PEMFC) with cathodes using platinum group metal-free (PGM-free) catalysts could significantly reduce costs, but the lower volumetric oxygen reduction reaction (ORR) activity requires thick electrodes that suffer from liquid water flooding and increased oxygen transport resistance. To address these challenges, we developed a 3D gas diffusion electrode (GDE) architecture to enhance liquid water removal through the diffusion media and reduce cathode saturation. The cathode features a uniform catalyst layer adjacent to the membrane for high ORR activity and then pillars of the hydrophilic catalyst layer that pass through the microporous layer (MPL), providing a low capillary pressure barrier pathway to the carbon fiber paper layer and channel. The non-planar cathode also increases the interfacial area between the catalyst layer and hydrophobic MPL for a greater fraction of the cathode with high O 2 concentration. Our studies included parametric experimental study of the pillar density to identify the optimum pitch between pillars. Our measurements show significant improvements in the mass transport region of the polarization curve with 3D structured electrodes leading to an 8% increase in maximum current density, 19% increase in maximum power density, and 16% increase in current density at 0.67 V with air.

25 ENERGY STORAGE↗
DOE OSTI2023

Atomically dispersed Pt single sites and nanoengineered structural defects enable a high electrocatalytic activity and durability for hydrogen evolution reaction and overall urea electrolysis

The scarcity and high cost of PGM electrocatalysts are the key bottleneck in the mass-scale commercialization of many electrolysis technologies. Bifunctional single-atom electrocatalysts (SACs) are promising alternatives for PGM electrocatalysts in next-generation electrolysis technologies because of their superior intrinsic activity and perfect atom utilization. Regulating the coordination environment of platinum atomic sites identifies their electrocatalytic performance. Therefore, exploring more appropriate supports could facilitate the construction of active and durable electrocatalysts with ultralow noble metal content. Herein, we report on a reliable approach for producing a novel type of SACs composed of atomically dispersed Pt active sites stabilized on defective NiCo layered double hydroxide (Pt/D-NiCo LDH) nanosheets as an ultralow-Pt hybrid electrocatalyst for hydrogen evolution reaction (HER), urea oxidation reaction (UOR), and full urea-water electrolysis. The optimized Pt 1 /D NiCo LDH-24 SAC displays a remarkable HER and UOR performance where it yields a current density of 10 mA cm -2 at 37 mV and 1.25 V vs. RHE for HER and UOR, respectively. Finally, symmetrical urea electrolyzer constructed of Pt 1 /D-NiCo LDH-24 electrodes attains 10 mA cm -2 at a cell voltage of 1.32 V vs. RHE, demonstrating superior activity and durability over 60 h operation when compared to commercial Pt/C( + )||RuO 2 ( - ) system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Electrochemical Capacitance Traces with Interlayer Spacing in Two‐dimensional Conductive Metal–Organic Frameworks

Abstract Electrically conductive metal–organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double‐layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure‐function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene‐based 2D layered conductive MOFs with variable alkyl functional groups, Ni 3 (HIR 3 ‐TAT) 2 (TAT=triazatruxene; R=H, Et, n ‐Bu, n ‐Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in‐plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double‐layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni 3 (HIH 3 ‐TAT) 2 to Ni 3 (HIBu 3 ‐TAT) 2 . Partial exfoliation of Ni 3 (HIBu 3 ‐TAT) 2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox‐active sites may motivate further design and engineering of electrode materials for EC.

Su, Alice Y.↗
DOE OSTI2024

Electrochemical Capacitance Traces with Interlayer Spacing in Two‐dimensional Conductive Metal–Organic Frameworks

Abstract Electrically conductive metal–organic frameworks (MOFs) are promising candidates for electrochemical capacitors (EC) for fast energy storage due to their high specific surface areas and potential for redox activity. To maximize energy density, traditional inorganic pseudocapacitors have utilized faradaic processes in addition to double‐layer capacitance. Although conductive MOFs are usually comprised of redox active ligands which allow faradaic reactions upon electrochemical polarization, systematic studies providing deeper understanding of the charge storage processes and structure‐function relationships have been scarce. Here, we investigate the charge storage mechanisms of a series of triazatruxene‐based 2D layered conductive MOFs with variable alkyl functional groups, Ni 3 (HIR 3 ‐TAT) 2 (TAT=triazatruxene; R=H, Et, n ‐Bu, n ‐Pent). Functionalization of the triazatruxene core allows for systematic variation of structural parameters while maintaining in‐plane conjugation between ligands and metals. Specifically, R groups modulate interlayer spacing, which in turn shifts the charge storage mechanism from double‐layer capacitance towards pseudocapacitance, leading to an increase in molar specific capacitance from Ni 3 (HIH 3 ‐TAT) 2 to Ni 3 (HIBu 3 ‐TAT) 2 . Partial exfoliation of Ni 3 (HIBu 3 ‐TAT) 2 renders redox active ligand moieties more accessible, and thus increases the dominance of faradaic processes. Our strategy of controlling charge storage mechanism through tuning the accessibility of redox‐active sites may motivate further design and engineering of electrode materials for EC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

SineKAN: Kolmogorov-Arnold Networks using sinusoidal activation functions

Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation functions on the edges of the computational graph followed by summation on nodes. The learnable edge activation functions in the original implementation are basis spline functions (B-Spline). Here, we present a model in which learnable grids of B-Spline activation functions are replaced by grids of re-weighted sine functions (SineKAN). We evaluate numerical performance of our model on a benchmark vision task. We show that our model can perform better than or comparable to B-Spline KAN models and an alternative KAN implementation based on periodic cosine and sine functions representing a Fourier Series. Further, we show that SineKAN has numerical accuracy that could scale comparably to dense neural networks (DNNs). Compared to the two baseline KAN models, SineKAN achieves a substantial speed increase at all hidden layer sizes, batch sizes, and depths. Current advantage of DNNs due to hardware and software optimizations are discussed along with theoretical scaling. Additionally, properties of SineKAN compared to other KAN implementations and current limitations are also discussed.

Reinhardt, Eric↗
DOE OSTI2026

Unraveling the Synergistic effects of La and Al co-doping on Ni/Co-free P2-type Na 0.67 Mn 0.67 Fe 0.33 O 2 layered oxide cathodes for sodium-ion batteries

Recent developments in high-performance cathodes for sodium-ion batteries (SIBs) tend to mitigate use of critical Ni and Co active species to satisfy sustainability. P2-type layered oxide cathodes based on Mn and Fe promise high capacity, sustainability, and low cost on account of the abundance and multiple redox characteristics of Mn and Fe. However, their commercialization is still challenged due to poor cycling stability caused by phase changes emanating from inherent Jahn-Teller distortions. Herein, we propose a novel strategy of trivalent La and Al co-doping to alleviate the drawbacks, innovating a new cathode of Na 0.67 Mn 0.62 Al 0.05 Fe 0.31 La 0.02 O 2 (AlLa). The co-doped cathode delivers an impressive capacity of 128.7 mAh/g at 1C and 106.5 mAh/g at high rate of 5C with a good capacity retention of 85% after 100 cycles. These are superior to the unmodified material, whose specific capacity was 118.6 mAh/g at 1C and 61.1 mAh/g at 5C with a retention of only 65% after 100 cycles. The synergistic contribution from La and Al associated with their improved oxygen bonding, pillaring, and local electronic structural modification stemming from rigid Lasingle bondO and Alsingle bondO bonding resulted in the observed structural and electrochemical improvement. Overall, this research offers novel strategies for designing high-performance cathode materials for sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Role of mixed conducting Pr 0.1 Gd 0.1 Ce 0.8 O 1.9-δ barrier layer on the promotion of SOFC performance

The cathode activity in a solid oxide fuel cell can be promoted by introducing various catalysts to reduce its polarization resistance towards oxygen reduction, and thus improve cell performance. Here, in this work, the La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 (LSCF) cathode surface is modified by the infiltration of Pr 6 O 11 and the power density at 0.8 V and 750 °C is improved by 21%. Moreover, by replacing the traditional barrier layer Gd 0.2 Ce 0.8 O 1.9 with mixed conducting Pr 0.1 Gd 0.1 Ce 0.8 O 1.9 (PGCO), the power density increases by 38%. The ohmic resistance is dramatically reduced by applying the PGCO interlayer. The distribution of relaxation time was used to analyze the mechanism for which the polarization resistance was decreased, attributing to the mixed conduction nature in PrO x . An increase of power density, ~0.358 W/cm 2 (71%) at 0.8 V, is achieved with the implementation of both surface modification and buffer layer engineering.

08 HYDROGEN↗
DOE OSTI2022

Sodium trithiocarbonate cathode for high-performance sodium–sulfur batteries

The high abundance and low cost of sodium and sulfur make room-temperature sodium-sulfur (RT Na-S) batteries an attractive technology compared to the current lithium-ion batteries for large-scale grid-storage applications. However, the commercialization of RT Na-S batteries is impeded by the slow kinetics of Na-S chemistry, severe sodium polysulfide shuttling, and uncontrollable growth of dendritic Na. Herein, sodium trithiocarbonate (Na 2 CS 3 ) is applied as a cathode material to facilitate concurrent improvement in both electrodes, leading to a high-rate performance with extended cycle life. The conductive characteristic of the carbon-sulfur resonance bond provides fast ion and electron transfer throughout the cathode, resulting in superior electrochemical reactivity. At the cathode, the presence of Na2CS3 forms an oligomer-structured layer to suppress the dissolution and shuttling of active materials. Meanwhile, when small portions of Na 2 CS 3 intermediates migrate to the anode, a stable solid electrolyte interphase (SEI) layer with uniform Na-ion flux is formed, enabling improved Na stripping and plating performance. A series of electrochemical and materials characterization, accompanied by density functional theory calculations demonstrate that Na 2 CS 3 is a promising candidate to realize high-rate performance long cycle life RT Na-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Enhancing the Reaction Kinetics and Stability of Co‐Free Li‐Rich Cathode Materials via a Multifunctional Strategy

Co-free Li-rich layered oxides (CFLLOs) with anionic redox activity are among the most promising cathode materials for high-energy-density and low-cost lithium-ion batteries (LIBs). However, irreversible oxygen release often causes severe structural deterioration, electrolyte decomposition, and the formation of unstable cathode-electrolyte interface (CEI) film with high impedance. Additionally, the elimination of cobalt elements further deteriorates the reaction kinetics, leading to reduced capacity and poor rate performance. Here, in this study, a multifunctional strategy is proposed, incorporating Li 2 MnO 3 phase content regulation, micro-nano structure design, and heteroatom substitution. The increased content of Li 2 MnO 3 phase enhances the capacity through oxygen redox. The smaller nanoscale primary particles induce greater tensile strain and introduce more grain boundaries, thereby improving the reaction kinetics and reactivity, while the larger micron-sized secondary particles help to reduce interfacial side reactions. Furthermore, Na⁺ doping modulates the local coordination environment of oxygen, stabilizing both the anion framework and the crystal structure. As a result, the designed cathode exhibits enhanced rate performance, delivering a capacity of 158 mAh g⁻¹ at 5.0 C and improved cyclic stability, with a high capacity retention of 99% after 400 cycles at 1.0 C. This multifunctional strategy holds great promise for advancing the practical application of CFLLOs in next-generation LIBs.

Co-free Li-rich layered oxide↗
DOE OSTI2021

From Langmuir isotherm to Brunauer–Emmett–Teller isotherm

Abstract Developed for multilayer adsorption, the Brunauer–Emmett–Teller ( BET) isotherm considers the adsorption of the first layer as an equilibrium chemical reaction between adsorbate molecules and adsorption sites and the adsorption of the second and subsequent layers as a condensation–evaporation process. Following the recent development of an activity‐based formulation for the Langmuir isotherm for monolayer adsorption, we present an activity‐based formulation for the BET isotherm in which species concentrations are replaced with species activities. Capturing the adsorbent surface heterogeneity for the adsorption of the first layer, the resulting thermodynamic BET isotherm is shown to accurately represent pure component adsorption isotherms over the relative pressure range of zero to unity or prior to the onset of capillary condensation. The thermodynamic BET isotherm should facilitate accurate estimation of monolayer adsorption capacity and the corresponding adsorbent surface area.

Vyawahare, Pradeep↗
DOE OSTI2022

Super-porous Pt/CuO/Pt hybrid platform for ultra-sensitive and selective H 2 O 2 detection

A super-porous Pt/CuO/Pt hybrid electrode is demonstrated with extremely high sensing performance parameters for the hydrogen peroxide (H 2 O 2 ) detection. A unique physiochemical approach is adapted for the fabrication of 3-D super-porous Pt/CuO/Pt sensing platform. Here, the super-porous Pt/CuO/Pt hybrid platform demonstrates a superior sensitivity of 16,694 µA mM -1 cm -2 with a limit of detection of 2.91 nM (S/N = 3). It also demonstrates an excellent selectivity against the interfering molecules such as NaCl, fructose, ascorbic acid, citric acid, dopamine and glucose with a wide linear range. The demonstrated performance ranks the Pt/CuO/Pt hybrid platform as one of the best H 2 O 2 sensors as summarized in the Table 2. The super-porous CuO layer is fabricated by a dynamic hydrogen bubbling technique of electrochemical deposition and metallic Pt NP decoration is achieved by the physical vapor deposition (PVD) and post-annealing. The super-porous CuO layer offers a drastically improved electrochemical active surface area, and the Pt NP decoration offers a significantly improved conductivity and improved charge accumulation for the H 2 O 2 reduction. The DFT simulations confirm the predominance of CuO over Cu 2 O and Pt over Pd for the H 2 O 2 detection based on the adsorption energy, density of states and charge accumulation calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Molecular Determination of Organic Adsorption Sites on Smectite during Fe Redox Processes Using ToF-SIMS Analysis

Turnover of soil organic carbon (SOC) is strongly affected by a balance between mineral protection and microbial degradation. However, the mechanisms controlling the heterogeneous and preferential adsorption of different types of SOC remain elusive, especially for humic substrates (HSs) and microbial carbon (MC), two hotly-debated forms of SOC prevalent in soils. In this work, the heterogeneous adsorption of HSs and MC on a clay mineral (nontronite NAu-2) during microbial-mediated Fe redox cycling was determined with the use of time-of-flight secondary ion mass spectrometry (ToF-SIMS). The results revealed that HSs pre-adsorbed on NAu-2 would partially inhibit the microbial Fe(III) reduction and structural modification of NAu-2, thus retarding the subsequent adsorption of MC. In contrast, NAu-2 without pre-coated HSs was adsorbed by a significant amount of MC from microbial polysaccharides as a result of Fe(III) reduction. This was attributed to the deposition of a thin Al-rich layer on clay surface, which provided active sites for MC adsorption. This study provides direct and detailed molecular evidence for the first time to explain the preferential adsorption of MC over HSs on the surface of clay minerals in the iron redox processes, which could be critical for the preservation of MC in soil. The results also indicate that ToF-SIMS is a unique tool for understanding complex organic-mineral-microbe interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Environmental Factors Associated With Fall Phytoplankton Blooms in the Northern Bering and Chukchi Seas

This study investigates environmental drivers of fall phytoplankton blooms in the Arctic, focusing on the northern Bering and Chukchi seas. Random Forests models were used to analyze covariates of fall phytoplankton blooms from 2013 to 2018, incorporating shipboard, remote sensing, and modeled environmental properties. Four regional models and one comprehensive all-station model considered fall as well as midsummer conditions. Midsummer properties included suspended particulate matter, chlorophyll-a, and the proportion of degraded pheophytin to chlorophyll-a used as a proxy for bloom stage. Open water duration was one of the highest ranked factors in predicting fall blooms. Open water duration also influences the stage of midsummer (July) blooms as indicated by pheophytin proportions, which in turn were the highest-ranked factor for predicting fall bloom events in the Chirikov Basin (northern Bering Sea between St. Lawrence Island and the Bering Strait) and the Chukchi Sea. Wind direction, specifically easterly winds, was an important predictor in the northern Bering Sea. Maximum wind speed ranked highly at stations located within the nutrient-poor Alaska Coastal Current in the Chukchi Sea. However, stormy days, average and maximum wind speeds generally ranked low in importance as a predictor of fall bloom events. Other parameters, including photosynthetic active radiation, modeled nutrient concentrations, mixed layer depth, and time since sea ice breakup date showed strong but regionally varying relationships with fall blooms. Altogether, results from these Random Forests models suggest that high wind events and storms in the absence of sea ice provide an incomplete narrative for initiating fall bloom events.

Gaffey, C. B. [Clark University, Worcester, MA (Un↗
DOE OSTI2021

Development of electronically passivating surfaces to enhance battery performance

For many decades, lithium metal batteries (LMBs) have been studied for their high energy density, though they suffer from high reactivity, which safety concerns such as explosions and fires. These events can occur as a result of degradation due to redox reactions and lithium morphology that evolve during cycling. Mostly, the failure is caused by the electrolyte degradation leading to the creation of a solid electrolyte interphase (SEI), which tends to induce electron leakage, lithium dendrite growth, and capacity decay. SEI formation is practically inevitable. This work investigated the minimization of degradation events by modifying different battery configurations. Modifications were made by exchanging electrolytes, electrode surfaces, and even annexing innovative components. Our goal is to achieve a configuration where Li-ion transfer is facilitated, and electron transfer is limited which would enable a longer lithium metal battery life cycle. When performing these modifications and testing their electrochemical performance, a current reduction was observed when the electrodes were spontaneously coated with preformed SEI. Herein several classes of artificial SEI layers are explored for their ability to form passivating layers through use of a redox active molecule.

25 ENERGY STORAGE↗
DOE OSTI2025

Editorial: Functionalization of porous materials for sustainable energy applications

Global energy demands are shifting toward a more sustainable future, with the goal of achieving carbon neutrality by 2050. Emerging technologies are driving this transition. The industry, academia, government, non-profit organizations, and the broader community are collaboratively working to reduce greenhouse gas (GHG) emissions and address climate change to ensure a sustainable future. According to the International Energy Agency, in 2022, the production, transportation, and processing of oil and gas resulted in 5.1 billion tons of CO 2 -equivalent emissions, representing nearly 15% of all energy-related GHG emissions. Moreover, the end-use of oil and gas accounted for an additional 40% of emissions. The IEA’s Net Zero Emissions by 2050 Scenario calls for immediate, collective action from the industry, transportation and other stakeholders to mitigate these emissions. In this effort, the development of energy materials will play a critical role in reducing emissions. Among these, porous materials offer an innovative solution, leveraging their high surface area, adjustable pore sizes, and chemical versatility to address these pressing challenges effectively. By carefully designing their nanostructures, the architecture and properties of these materials can be tailored for specific applications. Key factors such as chemical composition, particle size, pore distribution, and surface area optimization enhance the reactivity and energy conversion efficiency. Additionally, pre- and post-functionalization processes can introduce targeted chemical properties, further improving their performance. This Research Topic explores recent advancements in energy and materials science through four scholarly papers, showcasing innovative solutions for sustainable energy technologies while providing valuable insights into the unique properties and structure of porous materials (Figure 1). Li et al. present their work on highly defective NiFeV layered triple hydroxides, highlighting enhanced electrocatalytic activity and stability for oxygen evolution reactions (OER). Kovalskii et al. contribute a mini-review on hydrogen storage using hexagonal boron nitride (h-BN) and BN-based materials, offering an insightful overview of these promising materials. Chava et al. discuss their recent achievements in ceramic electrolytes used for improvement of performance of solid-state batteries. Lastly, Li et al. review the properties of porous materials with a focus on shrinkage behavior during the drying process, shedding light on key considerations for material design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An Accuracy-Maximization Approach for Claims Classifiers in Document Content Analytics for Cybersecurity

This paper presents our research approach and findings towards maximizing the accuracy of our classifier of feature claims for cybersecurity literature analytics, and introduces the resulting model ClaimsBERT. Its architecture, after extensive evaluations of different approaches, introduces a feature map concatenated with a Bidirectional Encoder Representation from Transformers (BERT) model. We discuss deployment of this new concept and the research insights that resulted in the selection of Convolution Neural Networks for its feature mapping aspects. We also present our results showing ClaimsBERT to outperform all other evaluated approaches. This new claims classifier represents an essential processing stage within our vetting framework aiming to improve the cybersecurity of industrial control systems (ICS). Furthermore, in order to maximize the accuracy of our new ClaimsBERT classifier, we propose an approach for optimal architecture selection and determination of optimized hyperparameters, in particular the best learning rate, number of convolutions, filter sizes, activation function, the number of dense layers, as well as the number of neurons and the drop-out rate for each layer. Fine-tuning these hyperparameters within our model led to an increase in classification accuracy from 76% obtained with BertForSequenceClassification’s original model to a 97% accuracy obtained with ClaimsBERT.

Ameri, Kimia (ORCID:0000000328791871)↗
DOE OSTI2024

Photolithography system including selective light array

A system, device, and method for imparting or transferring a geometric pattern on the surface of a substrate. The device comprises, a housing forming at least a partially enclosed space, a light source body comprising an array of light emitters, a base disposed below the light source body and configured for supporting the substrate having a photoresist layer thereon, and a controller for activating a predetermined number of individual light emitters corresponding to the predetermined geometric pattern. Each individual light emitter within the array of light emitters is selectively activatable to emit a light. The array of light emitters comprises a plurality of light-emitting diodes, a plurality of quantum dots, or both.

Young, Barbara Diane↗