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2. An efficient neural optimizer for resonant nanostructures: demonstration of highly-saturated red silicon structural color

Author

Lin, Ronghui, Valuckas, Vytautas, Do, Thi Thu Ha, Nemati, Arash, Kuznetsov, Arseniy I., Teng, Jinghua, and Ha, Son Tung

Subjects
Physics - Optics, Physics - Computational Physics
Abstract

Freeform nanostructures have the potential to support complex resonances and their interactions, which are crucial for achieving desired spectral responses. However, the design optimization of such structures is nontrivial and computationally intensive. Furthermore, the current "black box" design approaches for freeform nanostructures often neglect the underlying physics. Here, we present a hybrid data-efficient neural optimizer for resonant nanostructures by combining a reinforcement learning algorithm and Powell's local optimization technique. As a case study, we design and experimentally demonstrate silicon nanostructures with a highly-saturated red color. Specifically, we achieved CIE color coordinates of (0.677, 0.304)-close to the ideal Schrodinger's red, with polarization independence, high reflectance (>85%), and a large viewing angle (i.e., up to ~ 25deg). The remarkable performance is attributed to underlying generalized multipolar interferences within each nanostructure rather than the collective array effects. Based on that, we were able to demonstrate pixel size down to ~400 nm, corresponding to a printing resolution of 65,000 pixels per inch. Moreover, the proposed design model requires only ~300 iterations to effectively search a 13-dimensional design space - an order of magnitude more efficient than the previously reported approaches. Our work significantly extends the free-form optical design toolbox for high-performance flat-optical components and metadevices.

Published
2023

4. Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients

Author

Diray-Arce, Joann, Fourati, Slim, Jayavelu, Naresh Doni, Patel, Ravi, Maguire, Cole, Chang, Ana C, Dandekar, Ravi, Qi, Jingjing, Lee, Brian H, van Zalm, Patrick, Schroeder, Andrew, Chen, Ernie, Konstorum, Anna, Brito, Anderson, Gygi, Jeremy P, Kho, Alvin, Chen, Jing, Pawar, Shrikant, Gonzalez-Reiche, Ana Silvia, Hoch, Annmarie, Milliren, Carly E, Overton, James A, Westendorf, Kerstin, Network, IMPACC, Abraham, James, Adkisson, Michael, Albert, Marisa, Torres, Luz Altamirano, Alvarenga, Bonny, Anderson, Matthew L, Anderson, Evan J, Arnett, Azlann, Asashima, Hiromitsu, Atkinson, Mark A, Baden, Lindsey R, Barton, Brenda, Beach, Katherine, Beagle, Elizabeth, Becker, Patrice M, Bell, Matthew R, Bernui, Mariana, Bime, Chris, Kumar, Arun Boddapati, Booth, Leland J, Borresen, Brittney, Brakenridge, Scott C, Bristow, Laurel, Bryant, Robert, Calfee, Carolyn S, Manuel, Juan Carreño, Carrillo, Sidney, Chak, Suzanna, Chang, Iris, Connors, Jennifer, Conway, Michelle, Corry, David B, Cowan, David, Croen, Brett, Dela Cruz, Charles S, Cusimano, Gina, Eaker, Lily, Edwards, Carolyn, Ehrlich, Lauren IR, Elashoff, David, Erickson, Heidi, Erle, David J, Farhadian, Shelli, Farrugia, Keith, Fatou, Benoit, Fernandes, Andrea, Fernandez-Sesma, Ana, Fragiadakis, Gabriela K, Furukawa, Sara, Geltman, Janelle N, Ghale, Rajani, Bermúdez, Maria González Carolina, Goonewardene, Michael I, Sanchez, Estella Guerrero, Guirgis, Faheem W, Hafler, David A, Hamilton, Sydney, Harris, Paul, Nemati, Arash Hayati, Hendrickson, Carolyn M, Agudelo, Nelson I Higuita, Hodder, Thomas, Holland, Steven M, Hough, Catherine L, Huerta, Christopher, Hurley, Kerin C, Hutton, Scott R, Iwasaki, Akiko, Jauregui, Alejandra, Jha, Meenakshi, Johnson, Brandi, Joyner, David, Kangelaris, Kirsten N, Kelly, Geoffrey, Khalil, Zain, and Khan, Zenab

Subjects
Biomedical and Clinical Sciences, Immunology, Prevention, Rare Diseases, Clinical Research, 2.1 Biological and endogenous factors, Detection, screening and diagnosis, Aetiology, 4.1 Discovery and preclinical testing of markers and technologies, Good Health and Well Being, Humans, COVID-19, SARS-CoV-2, Longitudinal Studies, Multiomics, Disease Progression, IMPACC Network, immunophenotyping, longitudinal modeling, multi-omics, systems immunology, Biomedical and clinical sciences
Abstract

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.

Published
2023

22. A numerical investigation of nitridation in solid oxide fuel cell stacks operated with ammonia

Author

Babaie Rizvandi, Omid, Nemati, Arash, Chen, Ming, Frandsen, Henrik Lund, Babaie Rizvandi, Omid, Nemati, Arash, Chen, Ming, and Frandsen, Henrik Lund

Abstract

Operating solid oxide fuel cell (SOFC) stacks with ammonia induces the risk of nitriding in the fuel electrode and other metallic surfaces in the stack. This study aims to investigate the nitriding in the fuel electrode of an ammonia-fueled SOFC stack using a 3D Multiphysics model of a full stack. Based on the resulting species concentrations, a so-called nitriding potential is determined and compared to its critical level for various operating conditions and design modifications. The effects of the gas inflow temperatures, counter-flow configuration, and nickel coating over the inlet header of the stack are investigated. The results show that nitriding occurs in the first few centimeters of the fuel electrode for all investigated operating conditions considered in this study. Moreover, it is indicated that higher gas inflow temperatures and counter-flow configuration reduce the nitriding in the fuel electrode. Furthermore, the model illustrates the nitriding in the fuel active electrode for the gas inflow temperatures up to 700 °C. Finally, a significant reduction in nitriding in the fuel electrode is shown for a proposed nickel coating over the metallic inlet header due to a spreading of the ammonia decomposition.

Published
2024

23. Detailed 3D multiphysics modeling of an ammonia-fueled solid oxide fuel cell:Anode off-gas recirculation and Ni nitriding degradation

Author

Nemati, Arash, Rizvandi, Omid Babaie, Mondi, Francesco, Frandsen, Henrik Lund, Nemati, Arash, Rizvandi, Omid Babaie, Mondi, Francesco, and Frandsen, Henrik Lund

Abstract

A deep understanding of underlying processes and possible challenges is required for the development of ammonia-fueled solid oxide fuel cell (SOFC) systems. In this context, a detailed 3D multiphysics model of an ammonia-fueled SOFC is developed in the current study. Anode off-gas recirculation and nickel nitriding as two of the main aspects of ammonia-fueled SOFCs are investigated in the current study. The developed model is validated with experimental data under various conditions including direct and pre-cracked ammonia cases for various flow rates at different temperatures (700–850 °C) as well as different recirculation rates. A good agreement is achieved between the model results and the measurement indicating that the physics are well captured. Furthermore, nickel nitriding as one of the main challenges in the direct ammonia-fueled SOFCs is addressed and qualitatively validated with experimental data. The model can explain the reduction of performance difference between direct ammonia-fueled SOFC compared to its pre-cracked counterpart by reducing the fuel flow rate (increasing fuel utilization) and increasing the operating temperature. The highest performance difference (5.87%) is observed at 700 °C and fuel utilization of 14%, and the lowest difference (0.05%) belongs to 850 °C and fuel utilization of 70% at 0.5 A/cm2. Anode off-gas recirculation is found to yield significant savings in ammonia fuel around 21–27% while a slight power reduction (0.34–0.88%) is observed by increasing the recirculation rate from 70 to 90% compared to the case without recirculation. Excessive amount of nitrogen in the high recirculation rates does not show a significant effect on the performance. Nickel nitriding is reduced by increasing the temperature and fuel utilization.

Published
2024

30. Schrödinger's Red Beyond 65,000 Pixel‐Per‐Inch by Multipolar Interaction in Freeform Meta‐Atom through Efficient Neural Optimizer.

Author

Lin, Ronghui, Valuckas, Vytautas, Do, Thi Thu Ha, Nemati, Arash, Kuznetsov, Arseniy I., Teng, Jinghua, and Ha, Son Tung

Subjects
MACHINE learning, PIXEL density measurement, REINFORCEMENT learning, SPECTRAL sensitivity, CHROMATICITY, COLOR in design
Abstract

Freeform nanostructures have the potential to support complex resonances and their interactions, which are crucial for achieving desired spectral responses. However, the design optimization of such structures is nontrivial and computationally intensive. Furthermore, the current "black box" design approaches for freeform nanostructures often neglect the underlying physics. Here, a hybrid data‐efficient neural optimizer for resonant nanostructures by combining a reinforcement learning algorithm and Powell's local optimization technique is presented. As a case study, silicon nanostructures with a highly‐saturated red color are designed and experimentally demonstrated. Specifically, color coordinates of (0.677, 0.304) in the International Commission on Illumination (CIE) chromaticity diagram – close to the ideal Schrödinger's red, with polarization independence, high reflectance (>85%), and a large viewing angle (i.e., up to ± 25°) is achieved. The remarkable performance is attributed to underlying generalized multipolar interferences within each nanostructure rather than the collective array effects. Based on that, pixel size down to ≈400 nm, corresponding to a printing resolution of 65000 pixels per inch is demonstrated. Moreover, the proposed design model requires only ≈300 iterations to effectively search a thirteen‐dimensional (13D) design space – an order of magnitude more efficient than the previously reported approaches. The work significantly extends the free‐form optical design toolbox for high‐performance flat‐optical components and metadevices. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Greatly Enhanced Resonant Exciton‐trion Conversion in Electrically Modulated Atomically Thin WS 2 at Room Temperature

Author

Wang, Zeng, primary, Sebek, Matej, additional, Liang, Xinan, additional, Elbanna, Ahmed, additional, Nemati, Arash, additional, Zhang, Nan, additional, Goh, Choon Hwa Ken, additional, Jiang, Mengting, additional, Pan, Jisheng, additional, Shen, Zexiang, additional, Su, Xiaodi, additional, Thanh, Nguyen Thi Kim, additional, Sun, Handong, additional, and Teng, Jinghua, additional

Published
2023
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